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1. Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: A collaborative meta-analysis of individual participant data

Author: Shlipak, Michael, Matsushita, K, Coresh, J, Sang, Y, Chalmers, J, Fox, C, Guallar, E, Jafar, T, Jassal, SK, Landman, GWD, and Muntner, P
Abstract: © 2015 Elsevier Ltd.Background: The usefulness of estimated glomerular filtration rate (eGFR) and albuminuria for prediction of cardiovascular outcomes is controversial. We aimed to assess the addition of creatinine-based eGFR and albuminuria to traditiona
Published: 2015

2. Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses

Author: Gaziano, L, Sun, L, Arnold, M, Bell, S, Cho, K, Kaptoge, SK, Song, RJ, Burgess, S, Posner, DC, Mosconi, K, Cohen, CR, Mason, AM, Bolton, TR, Tao, R, Allara, E, Schubert, P, Chen, L, Staley, JR, Staplin, N, Altay, S, Amiano, P, Arndt, PV, Arnlov, J, Barr, ELM, Bjorkelund, C, Boer, JMA, Brenner, H, Casiglia, E, Chiodini, P, Cooper, JA, Coresh, J, Cushman, M, Dankner, R, Davidson, KW, de Jongh, RT, Donfrancesco, C, Engstrom, G, Freisling, H, de la Camara, AG, Gudnason, V, Hankey, GJ, Hansson, P, Heath, AK, Hoorn, EJ, Imano, H, Jassal, SK, Kaaks, R, Katzke, V, Kauhanen, J, Kiechl, S, Koenig, W, Kronmal, RA, Kyro, C, Lawlor, DA, Ljungberg, B, MacDonald, C, Masala, G, Meisinger, C, Melander, O, Iribas, CM, Ninomiya, T, Nitsch, D, Nordestgaard, BG, OnlandMoret, C, Palmieri, L, Petrova, D, Garcia, JRQ, Rosengren, A, Sacerdote, C, Sakurai, M, Santiuste, C, Schulze, MB, Sieri, S, Sundstrom, J, Tikhonoff, V, Tjonneland, A, Tong, T, Tumino, R, Tzoulaki, I, van der Schouw, YT, Verschuren, WMM, Volzke, H, Wallace, RB, Wannamethee, SG, Weiderpass, E, Willeit, P, Woodward, M, Yamagishi, K, ZamoraRos, R, Akwo, EA, Pyarajan, S, Gagnon, DR, Tsao, PS, Muralidhar, S, Edwards, TL, Damrauer, SM, Joseph, J, Pennells, L, Wilson, PWF, Harrison, S, Gaziano, TA, Inouye, M, Baigent, C, Casas, JP, Langenberg, C, Wareham, N, Riboli, E, Gaziano, JM, Danesh, J, Hung, AM, Butterworth, AS, Wood, AM, Di Angelantonio, E, Gaziano, L, Sun, L, Arnold, M, Bell, S, Cho, K, Kaptoge, SK, Song, RJ, Burgess, S, Posner, DC, Mosconi, K, Cohen, CR, Mason, AM, Bolton, TR, Tao, R, Allara, E, Schubert, P, Chen, L, Staley, JR, Staplin, N, Altay, S, Amiano, P, Arndt, PV, Arnlov, J, Barr, ELM, Bjorkelund, C, Boer, JMA, Brenner, H, Casiglia, E, Chiodini, P, Cooper, JA, Coresh, J, Cushman, M, Dankner, R, Davidson, KW, de Jongh, RT, Donfrancesco, C, Engstrom, G, Freisling, H, de la Camara, AG, Gudnason, V, Hankey, GJ, Hansson, P, Heath, AK, Hoorn, EJ, Imano, H, Jassal, SK, Kaaks, R, Katzke, V, Kauhanen, J, Kiechl, S, Koenig, W, Kronmal, RA, Kyro, C, Lawlor, DA, Ljungberg, B, MacDonald, C, Masala, G, Meisinger, C, Melander, O, Iribas, CM, Ninomiya, T, Nitsch, D, Nordestgaard, BG, OnlandMoret, C, Palmieri, L, Petrova, D, Garcia, JRQ, Rosengren, A, Sacerdote, C, Sakurai, M, Santiuste, C, Schulze, MB, Sieri, S, Sundstrom, J, Tikhonoff, V, Tjonneland, A, Tong, T, Tumino, R, Tzoulaki, I, van der Schouw, YT, Verschuren, WMM, Volzke, H, Wallace, RB, Wannamethee, SG, Weiderpass, E, Willeit, P, Woodward, M, Yamagishi, K, ZamoraRos, R, Akwo, EA, Pyarajan, S, Gagnon, DR, Tsao, PS, Muralidhar, S, Edwards, TL, Damrauer, SM, Joseph, J, Pennells, L, Wilson, PWF, Harrison, S, Gaziano, TA, Inouye, M, Baigent, C, Casas, JP, Langenberg, C, Wareham, N, Riboli, E, Gaziano, JM, Danesh, J, Hung, AM, Butterworth, AS, Wood, AM, and Di Angelantonio, E
Abstract: BACKGROUND: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. METHODS: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. RESULTS: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min-1·1.73 m-2, with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min-1·1.73 m-2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. CONCLUSIONS: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches th
Published: 2022

3. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: Bikbov, B, Purcell, CA, Levey, AS, Smith, M, Abdoli, A, Abebe, M, Adebayo, OM, Afarideh, M, Agarwal, SK, Agudelo-Botero, M, Ahmadian, E, Al-Aly, Z, Alipour, V, Almasi-Hashiani, A, Al-Raddadi, RM, Alvis-Guzman, N, Amini, S, Andrei, T, Andrei, CL, Andualem, Z, Anjomshoa, M, Arabloo, J, Ashagre, AF, Asmelash, D, Ataro, Z, Atout, MMW, Ayanore, MA, Badawi, A, Bakhtiari, A, Ballew, SH, Balouchi, A, Banach, M, Barquera, S, Basu, S, Bayih, MT, Bedi, N, Bello, AK, Bensenor, IM, Bijani, A, Boloor, A, Borzì, AM, Cámera, LA, Carrero, JJ, Carvalho, F, Castro, F, Catalá-López, F, Chang, AR, Chin, KL, Chung, SC, Cirillo, M, Cousin, E, Dandona, L, Dandona, R, Daryani, A, Das Gupta, R, Demeke, FM, Demoz, GT, Desta, DM, Do, HP, Duncan, BB, Eftekhari, A, Esteghamati, A, Fatima, SS, Fernandes, JC, Fernandes, E, Fischer, F, Freitas, M, Gad, MM, Gebremeskel, GG, Gebresillassie, BM, Geta, B, Ghafourifard, M, Ghajar, A, Ghith, N, Gill, PS, Ginawi, IA, Gupta, R, Hafezi-Nejad, N, Haj-Mirzaian, A, Hariyani, N, Hasan, M, Hasankhani, M, Hasanzadeh, A, Hassen, HY, Hay, SI, Heidari, B, Herteliu, C, Hoang, CL, Hosseini, M, Hostiuc, M, Irvani, SSN, Islam, SMS, Jafari Balalami, N, James, SL, Jassal, SK, Jha, V, Jonas, JB, Joukar, F, Jozwiak, JJ, Kabir, A, Kahsay, A, Kasaeian, A, Kassa, TD, Kassaye, HG, Khader, YS, Khalilov, R, Khan, EA, Khan, MS, Khang, YH, Kisa, A, Kovesdy, CP, Kuate Defo, B, Kumar, GA, Larsson, AO, Lim, LL, Lopez, AD, Lotufo, PA, Majeed, A, Malekzadeh, R, März, W, Masaka, A, Meheretu, HAA, Miazgowski, T, Mirica, A, Mirrakhimov, EM, Mithra, P, Moazen, B, Mohammad, DK, Mohammadpourhodki, R, Mohammed, S, Mokdad, AH, Morales, L, Moreno Velasquez, I, Mousavi, SM, Mukhopadhyay, S, Nachega, JB, Nadkarni, GN, Nansseu, JR, Natarajan, G, Nazari, J, Neal, B, Negoi, RI, Nguyen, CT, Nikbakhsh, R, Noubiap, JJ, Nowak, C, Olagunju, AT, Ortiz, A, Owolabi, MO, Palladino, R, Pathak, M, Poustchi, H, Prakash, S, Prasad, N, Rafiei, A, Raju, SB, Ramezanzadeh, K, Rawaf, S, Rawaf, DL, Rawal, L, Reiner RC, Rezapour, A, Ribeiro, DC, Roever, L, Rothenbacher, D, Rwegerera, GM, Saadatagah, S, Safari, S, Sahle, BW, Salem, H, Sanabria, J, Santos, IS, Sarveazad, A, Sawhney, M, Schaeffner, E, Schmidt, MI, Schutte, AE, Sepanlou, SG, Shaikh, MA, Sharafi, Z, Sharif, M, Sharifi, A, Silva, DAS, Singh, JA, Singh, NP, Sisay, MMM, Soheili, A, Sutradhar, I, Teklehaimanot, BF, Tesfay, BE, Teshome, GF, Thakur, JS, Tonelli, M, Tran, KB, Tran, BX, Tran Ngoc, C, Ullah, I, Valdez, PR, Varughese, S, Vos, T, Vu, LG, Waheed, Y, Werdecker, A, Wolde, HF, Wondmieneh, AB, Wulf Hanson, S, Yamada, T, Yeshaw, Y, Yonemoto, N, Yusefzadeh, H, Zaidi, Z, Zaki, L, Zaman, SB, Zamora, N, Zarghi, A, Zewdie, KA, Ärnlöv, J, Coresh, J, Perico, N, Remuzzi, G, Murray, CJL, Vos, T., Veritati - Repositório Institucional da Universidade Católica Portuguesa, Bikbov, B, Purcell, Ca, Levey, A, Smith, M, Abdoli, A, Abebe, M, Adebayo, Om, Afarideh, M, Agarwal, Sk, Agudelo-Botero, M, Ahmadian, E, Al-Aly, Z, Alipour, V, Almasi-Hashiani, A, Al-Raddadi, Rm, Alvis-Guzman, N, Amini, S, Andrei, T, Andrei, Cl, Andualem, Z, Anjomshoa, M, Arabloo, J, Ashagre, Af, Asmelash, D, Ataro, Z, Atout, Mmw, Ayanore, Ma, Badawi, A, Bakhtiari, A, Ballew, Sh, Balouchi, A, Banach, M, Barquera, S, Basu, S, Bayih, Mt, Bedi, N, Bello, Ak, Bensenor, Im, Bijani, A, Boloor, A, Borzì, Am, Cámera, La, Carrero, Jj, Carvalho, F, Castro, F, Catalá-López, F, Chang, Ar, Chin, Kl, Chung, Sc, Cirillo, M, Cousin, E, Dandona, L, Dandona, R, Daryani, A, Das, Gupta, R, Demeke, Fm, Demoz, Gt, Desta, Dm, Do, Hp, Duncan, Bb, Eftekhari, A, Esteghamati, A, Fatima, S, Fernandes, Jc, Fernandes, E, Fischer, F, Freitas, M, Gad, Mm, Gebremeskel, Gg, Gebresillassie, Bm, Geta, B, Ghafourifard, M, Ghajar, A, Ghith, N, Gill, P, Ginawi, Ia, Gupta, R, Hafezi-Nejad, N, Haj-Mirzaian, A, Hariyani, N, Hasan, M, Hasankhani, M, Hasanzadeh, A, Hassen, Hy, Hay, Si, Heidari, B, Herteliu, C, Hoang, Cl, Hosseini, M, Hostiuc, M, Irvani, Ssn, Islam, Sm, Jafari, Balalami, N, James, Sl, Jassal, Sk, Jha, V, Jonas, Jb, Joukar, F, Jozwiak, Jj, Kabir, A, Kahsay, A, Kasaeian, A, Kassa, Td, Kassaye, Hg, Khader, Y, Khalilov, R, Khan, Ea, Khan, M, Khang, Yh, Kisa, A, Kovesdy, Cp, Kuate, Defo, B, Kumar, Ga, Larsson, Ao, Lim, Ll, Lopez, Ad, Lotufo, Pa, Majeed, A, Malekzadeh, R, März, W, Masaka, A, Meheretu, Haa, Miazgowski, T, Mirica, A, Mirrakhimov, Em, Mithra, P, Moazen, B, Mohammad, Dk, Mohammadpourhodki, R, Mohammed, S, Mokdad, Ah, Morales, L, Moreno, Velasquez, I, Mousavi, Sm, Mukhopadhyay, S, Nachega, Jb, Nadkarni, Gn, Nansseu, Jr, Natarajan, G, Nazari, J, Neal, B, Negoi, Ri, Nguyen, Ct, Nikbakhsh, R, Noubiap, Jj, Nowak, C, Olagunju, At, Ortiz, A, Owolabi, Mo, Palladino, R, Pathak, M, Poustchi, H, Prakash, S, Prasad, N, Rafiei, A, Raju, Sb, Ramezanzadeh, K, Rawaf, S, Rawaf, Dl, Rawal, L, Reiner, Rc, Jr, Rezapour, A, Ribeiro, Dc, Roever, L, Rothenbacher, D, Rwegerera, Gm, Saadatagah, S, Safari, S, Sahle, Bw, Salem, H, Sanabria, J, Santos, I, Sarveazad, A, Sawhney, M, Schaeffner, E, Schmidt, Mi, Schutte, Ae, Sepanlou, Sg, Shaikh, Ma, Sharafi, Z, Sharif, M, Sharifi, A, Silva, Da, Singh, Ja, Singh, Np, Sisay, Mmm, Soheili, A, Sutradhar, I, Teklehaimanot, Bf, Tesfay, Be, Teshome, Gf, Thakur, J, Tonelli, M, Tran, Kb, Tran, Bx, Tran, Ngoc, Ullah, I, Valdez, Pr, Varughese, S, Vos, T, Vu, Lg, Waheed, Y, Werdecker, A, Wolde, Hf, Wondmieneh, Ab, Wulf, Hanson, S, Yamada, T, Yeshaw, Y, Yonemoto, N, Yusefzadeh, H, Zaidi, Z, Zaki, L, Zaman, Sb, Zamora, N, Zarghi, A, Zewdie, Ka, Ärnlöv, J, Coresh, J, Perico, N, Remuzzi, G, Murray, Cjl, Vos, T., and GBD Chronic Kidney Disease Collaboration
Subjects: Systems Analysis, Gout, Cost effectiveness, 030204 cardiovascular system & hematology, Global Health, GLOMERULAR-FILTRATION-RATE, Global Burden of Disease, COST-EFFECTIVENESS, 0302 clinical medicine, Cause of Death, Prevalence, Global health, Diabetic Nephropathies, Registries, 030212 general & internal medicine, SUB-SAHARAN AFRICA, 11 Medical and Health Sciences, Incidence, Mortality rate, 1. No poverty, General Medicine, Hälsovetenskaper, GBD Chronic Kidney Disease Collaboration, CKD-EPI EQUATION, 3. Good health, Europe, Cardiovascular Diseases, Quality-Adjusted Life Years, Life Sciences & Biomedicine, Asia, Oceania, 195 COUNTRIES, ATHEROSCLEROSIS RISK, CARDIOVASCULAR OUTCOMES, Risk Assessment, Article, 03 medical and health sciences, Medicine, General & Internal, SDG 3 - Good Health and Well-being, RISK-FACTOR, General & Internal Medicine, Environmental health, Health Sciences, medicine, Humans, GBD, chronic kidney disease, Mortality, Risk factor, Renal Insufficiency, Chronic, Disease burden, QM, Science & Technology, Australasia, business.industry, PERIPHERAL ARTERIAL-DISEASE, Bayes Theorem, medicine.disease, Health Surveys, Quality-adjusted life year, RENAL-DISEASE, Latin America, Years of potential life lost, Africa, North America, Human medicine, business, RC, Kidney disease
Abstract: Background Health system planning requires careful assessment of chronic kidney disease (CKD) epidemiology, but data for morbidity and mortality of this disease are scarce or non-existent in many countries. We estimated the global, regional, and national burden of CKD, as well as the burden of cardiovascular disease and gout attributable to impaired kidney function, for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. We use the term CKD to refer to the morbidity and mortality that can be directly attributed to all stages of CKD, and we use the term impaired kidney function to refer to the additional risk of CKD from cardiovascular disease and gout. Methods The main data sources we used were published literature, vital registration systems, end-stage kidney disease registries, and household surveys. Estimates of CKD burden were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool, and induded incidence, prevalence, years lived with disability, mortality, years of life lost, and disability-adjusted life-years (DALYs). A comparative risk assessment approach was used to estimate the proportion of cardiovascular diseases and gout burden attributable to impaired kidney function. Findings Globally, in 2017,1.2 million (95% uncertainty interval [UI] 1.2 to 1.3) people died from CKD. The global all-age mortality rate from CKD increased 41.5% (95% UI 35.2 to 46.5) between 1990 and 2017, although there was no significant change in the age-standardised mortality rate (2.8%, -1.5 to 6.3). In 2017,697.5 million (95% UI 649.2 to 752.0) cases of all-stage CKD were recorded, for a global prevalence of 9.1% (8.5 to 9.8). The global all-age prevalence of CKD increased 29.3% (95% UI 26.4 to 32.6) since 1990, whereas the age-standardised prevalence remained stable (1.2%, -1.1 to 3.5). CKD resulted in 35.8 million (95% UI 33.7 to 38.0) DALYs in 2017, with diabetic nephropathy accounting for almost a third of DALYs. Most of the burden of CKD was concentrated in the three lowest quintiles of Socio-demographic Index (SDI). In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD was much higher than expected for the level of development, whereas the disease burden in western, eastern, and central sub-Saharan Africa, east Asia, south Asia, central and eastern Europe, Australasia, and western Europe was lower than expected. 1.4 million (95% UI 1.2 to 1.6) cardiovascular disease-related deaths and 25.3 million (22.2 to 28.9) cardiovascular disease DALYs were attributable to impaired kidney function. Interpretation Kidney disease has a major effect on global health, both as a direct cause of global morbidity and mortality and as an important risk factor for cardiovascular disease. CKD is largely preventable and treatable and deserves greater attention in global health policy decision making, particularly in locations with low and middle SDI. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.
Published: 2020
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4. Measures of chronic kidney disease and risk of incident peripheral artery disease: a collaborative meta-analysis of individual participant data

Author: Matsushita, K, Ballew, Sh, Coresh, J, Arima, H, Ärnlöv, J, Cirillo, Massimo, Ebert, N, Hiramoto, Js, Kimm, H, Shlipak, Mg, Visseren, Flj, Gansevoort, Rt, Kovesdy, Cp, Shalev, V, Woodward, M, Kronenberg, F, Chronic Kidney Disease Prognosis Consortium: Chalmers, J, Perkovic, V, Grams, Me, Sang, Y, Schaeffner, E, Martus, P, Levin, A, Djurdjev, O, Tang, M, Heine, G, Seiler, S, Zawada, A, Emrich, I, Sarnak, M, Katz, R, Brenner, H, Schöttker, B, Rothenbacher, D, Saum, Ku, Köttgen, A, Schneider, M, Eckardt, Ku, Green, J, Kirchner, Hl, Chang, Ar, Black, C, Marks, A, Prescott, G, Clark, L, Fluck, N, Jee, Sh, Mok, Y, Chodick, G, Wetzels, Jfm, Blankestijn, Pj, Van, Zuilen, Bots, M, Peralta, C, Hiromoto, J, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Kenealy, T, Elley, Cr, Collins, Jf, Drury, Pl, Bakker, Sj, Heerspink, Hjl, Jassal, Sk, Bergstrom, J, Jh, Ix, Barrett Connor, E, Kalantar Zadeh, K, Carrero, Jj, Gasparini, A, Qureshi, Ar, Barany, P, Algra, A, Van, Der, Graaf, Y, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Lannfelt, L, Larsson, A, Hallan, S, Levey, As, Chen, J, Kwak, L, Sang, Y., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Matsushita, K, Ballew, Sh, Coresh, J, Arima, H, Ärnlöv, J, Cirillo, Massimo, Ebert, N, Hiramoto, J, Kimm, H, Shlipak, Mg, Visseren, Flj, Gansevoort, Rt, Kovesdy, Cp, Shalev, V, Woodward, M, Kronenberg, F, Chronic Kidney Disease Prognosis Consortium: Chalmers, J, Perkovic, V, Grams, Me, Sang, Y, Schaeffner, E, Martus, P, Levin, A, Djurdjev, O, Tang, M, Heine, G, Seiler, S, Zawada, A, Emrich, I, Sarnak, M, Katz, R, Brenner, H, Schöttker, B, Rothenbacher, D, Saum, Ku, Köttgen, A, Schneider, M, Eckardt, Ku, Green, J, Kirchner, Hl, Chang, Ar, Black, C, Marks, A, Prescott, G, Clark, L, Fluck, N, Jee, Sh, Mok, Y, Chodick, G, Wetzels, Jfm, Blankestijn, Pj, Van, Zuilen, Ad, Bots, M, Peralta, C, Hiromoto, J, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Kenealy, T, Elley, Cr, Collins, Jf, Drury, Pl, Bakker, Sj, Heerspink, Hjl, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett Connor, E, Kalantar Zadeh, K, Carrero, Jj, Gasparini, A, Qureshi, Ar, Barany, P, Algra, A, Van, Der, Graaf, Y, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Lannfelt, L, Larsson, A, Hallan, S, Levey, A, Chen, J, Kwak, L, and Sang, Y.
Subjects: Male, Databases, Factual, Endocrinology, Diabetes and Metabolism, nefropatia, arteriopatia periferica, epidemiologia, 030204 cardiovascular system & hematology, GLOMERULAR-FILTRATION-RATE, arteriopatia periferica, 0302 clinical medicine, Endocrinology, Risk Factors, CRITICAL LIMB ISCHEMIA, 030212 general & internal medicine, epidemiologia, POPULATION, biology, CYSTATIN C, Incidence, Middle Aged, PREVALENCE, Diabetes and Metabolism, nefropatia, Creatinine, Female, medicine.symptom, Glomerular Filtration Rate, Adult, medicine.medical_specialty, Renal function, ATHEROSCLEROSIS RISK, HEART-ASSOCIATION, CARDIOVASCULAR OUTCOMES, 03 medical and health sciences, Peripheral Arterial Disease, Internal medicine, Diabetes mellitus, medicine, Internal Medicine, Albuminuria, Humans, Risk factor, Renal Insufficiency, Chronic, Aged, business.industry, Critical limb ischemia, medicine.disease, Intermittent claudication, Surgery, Cystatin C, biology.protein, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, Kidney disease
Abstract: BACKGROUND: Some evidence suggests that chronic kidney disease is a risk factor for lower-extremity peripheral artery disease. We aimed to quantify the independent and joint associations of two measures of chronic kidney disease (estimated glomerular filtration rate [eGFR] and albuminuria) with the incidence of peripheral artery disease.METHODS: In this collaborative meta-analysis of international cohorts included in the Chronic Kidney Disease Prognosis Consortium (baseline measurements obtained between 1972 and 2014) with baseline measurements of eGFR and albuminuria, at least 1000 participants (this criterion not applied to cohorts exclusively enrolling patients with chronic kidney disease), and at least 50 peripheral artery disease events, we analysed adult participants without peripheral artery disease at baseline at the individual patient level with Cox proportional hazards models to quantify associations of creatinine-based eGFR, urine albumin-to-creatinine ratio (ACR), and dipstick proteinuria with the incidence of peripheral artery disease (including hospitalisation with a diagnosis of peripheral artery disease, intermittent claudication, leg revascularisation, and leg amputation). We assessed discrimination improvement through c-statistics.FINDINGS: We analysed 817 084 individuals without a history of peripheral artery disease at baseline from 21 cohorts. 18 261 cases of peripheral artery disease were recorded during follow-up across cohorts (median follow-up was 7·4 years [IQR 5·7-8·9], range 2·0-15·8 years across cohorts). Both chronic kidney disease measures were independently associated with the incidence of peripheral artery disease. Compared with an eGFR of 95 mL/min per 1·73 m(2), adjusted hazard ratios (HRs) for incident study-specific peripheral artery disease was 1·22 (95% CI 1·14-1·30) at an eGFR of 45 mL/min per 1·73 m(2) and 2·06 (1·70-2·48) at an eGFR of 15 mL/min per 1·73 m(2). Compared with an ACR of 5 mg/g, the adjusted HR for incident study-specific peripheral artery disease was 1·50 (1·41-1·59) at an ACR of 30 mg/g and 2·28 (2·12-2·44) at an ACR of 300 mg/g. The adjusted HR at an ACR of 300 mg/g versus 5 mg/g was 3·68 (95% CI 3·00-4·52) for leg amputation. eGFR and albuminuria contributed multiplicatively (eg, adjusted HR 5·76 [4·90-6·77] for incident peripheral artery disease and 10·61 [5·70-19·77] for amputation in eGFR INTERPRETATION: Even mild-to-moderate chronic kidney disease conferred increased risk of incident peripheral artery disease, with a strong association between albuminuria and amputation. Clinical attention should be paid to the development of peripheral artery disease symptoms and signs in people with any stage of chronic kidney disease.FUNDING: American Heart Association, US National Kidney Foundation, and US National Institute of Diabetes and Digestive and Kidney Diseases.
Published: 2017

5. Adiposity and risk of decline in glomerular filtration rate : Meta-analysis of individual participant data in a global consortium

Author: Chang AR, Grams ME, Ballew SH, Bilo H, Correa A, Evans M, Gutierrez OM, Hosseinpanah F, Iseki K, Kenealy T, Klein B, Kronenberg F, Lee BJ, Li Y, Miura K, Navaneethan SD, Roderick PJ, Valdivielso JM, Visseren FLJ, Zhang L, Gansevoort RT, Hallan SI, Levey AS, Matsushita K, Shalev V, Woodward M, Astor B, Appel L, Greene T, Chen T, Chalmers J, Arima H, Perkovic V, Yatsuya H, Tamakoshi K, Hirakawa Y, Coresh J, Sang Y, Polkinghorne K, Chadban S, Atkins R, Levin A, Djurdjev O, Klein R, Lee K, Liu L, Zhao M, Wang F, Wang J, Tang M, Heine G, Emrich I, Zawada A, Bauer L, Nally J, Schold J, Shlipak M, Sarnak M, Katz R, Hiramoto J, Iso H, Yamagishi K, Umesawa M, Muraki I, Fukagawa M, Maruyama S, Hamano T, Hasegawa T, Fujii N, Jafar T, Hatcher J, Poulter N, Chaturvedi N, Wheeler D, Emberson J, Townend J, Landray M, Brenner H, Schöttker B, Saum KU, Rothenbacher D, Fox C, Hwang SJ, Köttgen A, Schneider MP, Eckardt KU, Green J, Kirchner HL, Ito S, Miyazaki M, Nakayama M, Yamada G, Cirillo M, Romundstad S, Øvrehus M, Langlo KA, Irie F, Sairenchi T, Rebholz CM, Young B, Boulware LE, Ishikawa S, Yano Y, Kotani K, Nakamura T, Jee SH, Kimm H, Mok Y, Chodick G, Wetzels JFM, Blankestijn PJ, van Zuilen AD, Bots M, Inker L, Peralta C, Kollerits B, Ritz E, Nitsch D, Fletcher A, Bottinger E, Nadkarni GN, Ellis SB, Nadukuru R, Fernandez E, Betriu A, Bermudez-Lopez M, Stengel B, Metzger M, Flamant M, Houillier P, Haymann JP, Froissart M, Ueshima H, Okayama A, Tanaka S, Okamura T, Elley CR, Collins JF, Drury PL, Ohkubo T, Asayama K, Metoki H, Kikuya M, Iseki C, Nelson RG, Knowler WC, Bakker SJL, Heerspink HJL, Brunskill N, Major R, Shepherd D, Medcalf J, Jassal SK, Bergstrom J, Ix JH, Barrett-Connor E, Kovesdy C, Kalantar-Zadeh K, Sumida K, Muntner P, Warnock D, Judd S, Panwar B, de Zeeuw D, Brenner B, Sedaghat S, Ikram MA, Hoorn EJ, Dehghan A, Wong TY, Sabanayagam C, Cheng CY, Banu R, Segelmark M, Stendahl M, Schön S, Tangri N, Sud M, Naimark D, Wen CP, Tsao CK, Tsai MK, Chen CH, Konta T, Hirayama A, Ichikawa K, Hadaegh F, Mirbolouk M, Azizi F, Solbu MD, Jenssen TG, Eriksen BO, Eggen AE, Lannfelt L, Larsson A, Ärnlöv J, Landman GWD, van Hateren KJJ, Kleefstra N, Chen J, Kwak L, Surapaneni A., Chang, Ar, Grams, Me, Ballew, Sh, Bilo, H, Correa, A, Evans, M, Gutierrez, Om, Hosseinpanah F, Iseki K, Kenealy, T, Klein, B, Kronenberg, F, Lee, Bj, Li, Y, Miura, K, Navaneethan, Sd, Roderick, Pj, Valdivielso, Jm, Visseren, Flj, Zhang, L, Gansevoort, Rt, Hallan, Si, Levey, A, Matsushita, K, Shalev, V, Woodward, M, Astor, B, Appel, L, Greene, T, Chen, T, Chalmers, J, Arima, H, Perkovic, V, Yatsuya, H, Tamakoshi, K, Hirakawa, Y, Coresh, J, Sang, Y, Polkinghorne, K, Chadban, S, Atkins, R, Levin, A, Djurdjev, O, Klein, R, Lee, K, Liu, L, Zhao, M, Wang, F, Wang, J, Tang, M, Heine, G, Emrich, I, Zawada, A, Bauer, L, Nally, J, Schold, J, Shlipak, M, Sarnak, M, Katz, R, Hiramoto, J, Iso, H, Yamagishi, K, Umesawa, M, Muraki, I, Fukagawa, M, Maruyama, S, Hamano, T, Hasegawa, T, Fujii, N, Jafar, T, Hatcher, J, Poulter, N, Chaturvedi, N, Wheeler, D, Emberson, J, Townend, J, Landray, M, Brenner, H, Schöttker, B, Saum, Ku, Rothenbacher, D, Fox, C, Hwang, Sj, Köttgen, A, Schneider, Mp, Eckardt, Ku, Green, J, Kirchner, Hl, Ito, S, Miyazaki, M, Nakayama, M, Yamada, G, Cirillo, M, Romundstad, S, Øvrehus, M, Langlo, Ka, Irie, F, Sairenchi, T, Rebholz, Cm, Young, B, Boulware, Le, Ishikawa, S, Yano, Y, Kotani, K, Nakamura, T, Jee, Sh, Kimm, H, Mok, Y, Chodick, G, Wetzels, Jfm, Blankestijn, Pj, van Zuilen, Ad, Bots, M, Inker, L, Peralta, C, Kollerits, B, Ritz, E, Nitsch, D, Fletcher, A, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Fernandez, E, Betriu, A, Bermudez-Lopez, M, Stengel, B, Metzger, M, Flamant, M, Houillier, P, Haymann, Jp, Froissart, M, Ueshima, H, Okayama, A, Tanaka, S, Okamura, T, Elley, Cr, Collins, Jf, Drury, Pl, Ohkubo, T, Asayama, K, Metoki, H, Kikuya, M, Iseki, C, Nelson, Rg, Knowler, Wc, Bakker, Sjl, Heerspink, Hjl, Brunskill, N, Major, R, Shepherd, D, Medcalf, J, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Kovesdy, C, Kalantar-Zadeh, K, Sumida, K, Muntner, P, Warnock, D, Judd, S, Panwar, B, de Zeeuw, D, Brenner, B, Sedaghat, S, Ikram, Ma, Hoorn, Ej, Dehghan, A, Wong, Ty, Sabanayagam, C, Cheng, Cy, Banu, R, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Wen, Cp, Tsao, Ck, Tsai, Mk, Chen, Ch, Konta, T, Hirayama, A, Ichikawa, K, Hadaegh, F, Mirbolouk, M, Azizi, F, Solbu, Md, Jenssen, Tg, Eriksen, Bo, Eggen, Ae, Lannfelt, L, Larsson, A, Ärnlöv, J, Landman, Gwd, van Hateren, Kjj, Kleefstra, N, Chen, J, Kwak, L, Surapaneni, A., Lifestyle Medicine (LM), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Asayama, Kei, and Sedaghat, SeyyedMah
Subjects: CHRONIC KIDNEY-DISEASE, Male, 030232 urology & nephrology, 030204 cardiovascular system & hematology, OBESITY PARADOX, Body Mass Index, BMI, eGFR, CKD-PC, Cohort Studies, 0302 clinical medicine, Risk Factors, Urologi och njurmedicin, Medicine, ALL-CAUSE MORTALITY, Adiposity, 2. Zero hunger, Aged, 80 and over, Medicine(all), education.field_of_study, Hazard ratio, ASSOCIATION, General Medicine, Middle Aged, 3. Good health, Cohort, Female, Waist Circumference, Life Sciences & Biomedicine, WAIST CIRCUMFERENCE, Obesity paradox, Glomerular Filtration Rate, Adult, Waist, Population, Renal function, 03 medical and health sciences, Medicine, General & Internal, General & Internal Medicine, CKD, Urology and Nephrology, Humans, Mortality, education, Aged, Science & Technology, business.industry, Research, medicine.disease, Body Height, BODY-MASS INDEX, Kidney Failure, Chronic, WEIGHT, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, Body mass index, Demography, Kidney disease
Abstract: ObjectiveTo evaluate the associations between adiposity measures (body mass index, waist circumference, and waist-to-height ratio) with decline in glomerular filtration rate (GFR) and with all cause mortality.DesignIndividual participant data meta-analysis.SettingCohorts from 40 countries with data collected between 1970 and 2017.ParticipantsAdults in 39 general population cohorts (n=5 459 014), of which 21 (n=594 496) had data on waist circumference; six cohorts with high cardiovascular risk (n=84 417); and 18 cohorts with chronic kidney disease (n=91 607).Main outcome measuresGFR decline (estimated GFR decline ≥40%, initiation of kidney replacement therapy or estimated GFR 2) and all cause mortality.ResultsOver a mean follow-up of eight years, 246 607 (5.6%) individuals in the general population cohorts had GFR decline (18 118 (0.4%) end stage kidney disease events) and 782 329 (14.7%) died. Adjusting for age, sex, race, and current smoking, the hazard ratios for GFR decline comparing body mass indices 30, 35, and 40 with body mass index 25 were 1.18 (95% confidence interval 1.09 to 1.27), 1.69 (1.51 to 1.89), and 2.02 (1.80 to 2.27), respectively. Results were similar in all subgroups of estimated GFR. Associations weakened after adjustment for additional comorbidities, with respective hazard ratios of 1.03 (0.95 to 1.11), 1.28 (1.14 to 1.44), and 1.46 (1.28 to 1.67). The association between body mass index and death was J shaped, with the lowest risk at body mass index of 25. In the cohorts with high cardiovascular risk and chronic kidney disease (mean follow-up of six and four years, respectively), risk associations between higher body mass index and GFR decline were weaker than in the general population, and the association between body mass index and death was also J shaped, with the lowest risk between body mass index 25 and 30. In all cohort types, associations between higher waist circumference and higher waist-to-height ratio with GFR decline were similar to that of body mass index; however, increased risk of death was not associated with lower waist circumference or waist-to-height ratio, as was seen with body mass index.ConclusionsElevated body mass index, waist circumference, and waist-to-height ratio are independent risk factors for GFR decline and death in individuals who have normal or reduced levels of estimated GFR.
Published: 2019

6. Serum potassium and adverse outcomes across the range of kidney function: a CKD Prognosis Consortium meta-analysis

Author: Kovesdy, CP, Matsushita, K, Sang, Y, Brunskill, NJ, Carrero, JJ, Chodick, G, Hasegawa, T, Heerspink, HL, Hirayama, A, Landman, GWD, Levin, A, Nitsch, D, Wheeler, DC, Coresh, J, Hallan, SI, Shalev, V, Grams, ME, Astor, B, Appel, L, Greene, T, Chen, T, Chalmers, J, Woodward, M, Arima, H, Perkovic, V, Djurdjev, O, Zhang, L, Liu, L, Zhao, M, Wang, F, Wang, J, Tang, M, Iso, H, Yamagishi, K, Umesawa, M, Muraki, I, Fukagawa, M, Maruyama, S, Hamano, T, Fujii, N, Wheeler, D, Emberson, J, Townend, J, Landray, M, Green, J, Kirchner, HL, Chang, AR, Cirillo, Massimo, Jee, SH, Kimm, H, Mok, Y, Wetzels, JFM, Blankestijn, PJ, van Zuilen, Bots, M, Sarnak, M, Inker, L, Roderick, P, Fletcher, A, Bottinger, E, Nadkarni, GN, Ellis, SB, Nadukuru, R, Brunskill, N, Major, R, Shepherd, D, Medcalf, J, Gansevoort, RT, Bakker, SJL, Heerspink, HJL, Jassal, SK, Bergstrom, J, Ix, JH, Barrett-Connor, E, Kovesdy, C, Kalantar-Zadeh, K, de Zeeuw, D, Brenner, B, Gasparini, A, Elinder, CG, Barany, P, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Wen, CP, Tsao, CK, Tsai, MK, Chen, CH, Konta, T, Ichikawa, K, Bilo, HJG, van Hateren, KJJ, Kleefstra, N, Hallan, S, Levey, AS, Ballew, SH, Chen, J, Kwak, L, Woodward, M., Kovesdy, Cp, Matsushita, K, Sang, Y, Brunskill, Nj, Carrero, Jj, Chodick, G, Hasegawa, T, Heerspink, Hl, Hirayama, A, Landman, Gwd, Levin, A, Nitsch, D, Wheeler, Dc, Coresh, J, Hallan, Si, Shalev, V, Grams, Me, Astor, B, Appel, L, Greene, T, Chen, T, Chalmers, J, Woodward, M, Arima, H, Perkovic, V, Djurdjev, O, Zhang, L, Liu, L, Zhao, M, Wang, F, Wang, J, Tang, M, Iso, H, Yamagishi, K, Umesawa, M, Muraki, I, Fukagawa, M, Maruyama, S, Hamano, T, Fujii, N, Wheeler, D, Emberson, J, Townend, J, Landray, M, Green, J, Kirchner, Hl, Chang, Ar, Cirillo, Massimo, Jee, Sh, Kimm, H, Mok, Y, Wetzels, Jfm, Blankestijn, Pj, Van, Zuilen, Ad, Bots, M, Sarnak, M, Inker, L, Roderick, P, Fletcher, A, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Brunskill, N, Major, R, Shepherd, D, Medcalf, J, Gansevoort, Rt, Bakker, Sjl, Heerspink, Hjl, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Kovesdy, C, Kalantar-Zadeh, K, De, Zeeuw, D, Brenner, B, Gasparini, A, Elinder, Cg, Barany, P, Evans, M, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Wen, Cp, Tsao, Ck, Tsai, Mk, Chen, Ch, Konta, T, Ichikawa, K, Bilo, Hjg, Van, Hateren, Kjj, Kleefstra, N, Hallan, S, Levey, A, Ballew, Sh, Chen, J, Kwak, L, Woodward, M., Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Groningen Kidney Center (GKC), and Methods in Medicines evaluation & Outcomes research (M2O)
Subjects: Hyperkalemia, 030232 urology & nephrology, HEMODIALYSIS-PATIENTS, Comorbidity, 030204 cardiovascular system & hematology, GLOMERULAR-FILTRATION-RATE, HYPERKALEMIA, End-stage renal disease, CHRONIC RENAL-INSUFFICIENCY, 0302 clinical medicine, SODIUM ZIRCONIUM CYCLOSILICATE, Risk Factors, Cause of Death, Estimated glomerular filtration rate, ESTIMATED GFR, education.field_of_study, Hazard ratio, Middle Aged, Prognosis, CHRONIC HEART-FAILURE, EUROPEAN-SOCIETY, Cardiovascular Diseases, medicine.symptom, Cardiology and Cardiovascular Medicine, Glomerular Filtration Rate, Adult, medicine.medical_specialty, Population, Renal function, Hypokalemia, End stage renal disease, 03 medical and health sciences, Internal medicine, medicine, Humans, Albuminuria, Renal Insufficiency, Chronic, Mortality, education, CKD Prognosis Consortium, Aged, business.industry, Proportional hazards model, POLYMERIC POTASSIUM BINDER, medicine.disease, SERUM POTASSIUM, Potassium, Kidney Failure, Chronic, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, Kidney disease
Abstract: Item does not contain fulltext Aims: Both hypo- and hyperkalaemia can have immediate deleterious physiological effects, and less is known about long-term risks. The objective was to determine the risks of all-cause mortality, cardiovascular mortality, and end-stage renal disease associated with potassium levels across the range of kidney function and evaluate for consistency across cohorts in a global consortium. Methods and results: We performed an individual-level data meta-analysis of 27 international cohorts [10 general population, 7 high cardiovascular risk, and 10 chronic kidney disease (CKD)] in the CKD Prognosis Consortium. We used Cox regression followed by random-effects meta-analysis to assess the relationship between baseline potassium and adverse outcomes, adjusted for demographic and clinical characteristics, overall and across strata of estimated glomerular filtration rate (eGFR) and albuminuria. We included 1 217 986 participants followed up for a mean of 6.9 years. The average age was 55 +/- 16 years, average eGFR was 83 +/- 23 mL/min/1.73 m2, and 17% had moderate- to-severe increased albuminuria levels. The mean baseline potassium was 4.2 +/- 0.4 mmol/L. The risk of serum potassium of >5.5 mmol/L was related to lower eGFR and higher albuminuria. The risk relationship between potassium levels and adverse outcomes was U-shaped, with the lowest risk at serum potassium of 4-4.5 mmol/L. Compared with a reference of 4.2 mmol/L, the adjusted hazard ratio for all-cause mortality was 1.22 [95% confidence interval (CI) 1.15-1.29] at 5.5 mmol/L and 1.49 (95% CI 1.26-1.76) at 3.0 mmol/L. Risks were similar by eGFR, albuminuria, renin-angiotensin-aldosterone system inhibitor use, and across cohorts. Conclusions: Outpatient potassium levels both above and below the normal range are consistently associated with adverse outcomes, with similar risk relationships across eGFR and albuminuria.
Published: 2018

7. Global Cardiovascular and Renal Outcomes of Reduced GFR

Author: Thomas, B, Matsushita, K, Abate, KH, Al Aly, Z, Ärnlöv, J, Asayama, K, Atkins, R, Badawi, A, Ballew, SH, Banerjee, A, Barregård, L, Barrett Connor, E, Basu, S, Bello, AK, Bensenor, I, Bergstrom, J, Bikbov, B, Blosser, C, Brenner, H, Carrero, JJ, Chadban, S, CIRILLO, Massimo, Cortinovis, M, Courville, K, Dandona, L, Dandona, R, Estep, K, Fernandes, J, Fischer, F, Fox, C, Gansevoort, RT, Gona, PN, Gutierrez, OM, Hamidi, S, Hanson, SW, Himmelfarb, J, Jassal, SK, Jee, SH, Jha, V, Jimenez Corona, A, Jonas, JB, Kengne, AP, Khader, Y, Khang, YH, Kim, YJ, Klein, B, Klein, R, Kokubo, Y, Kolte, D, Lee, K, Levey, AS, Li, Y, Lotufo, P, El, Razek, HMA, Mendoza, W, Metoki, H, Mok, Y, Muraki, I, Muntner, PM, Noda, H, Ohkubo, T, Ortiz, A, Perico, N, Polkinghorne, K, Al Radaddi, R, Remuzzi, G, Roth, G, Rothenbacher, D, Satoh, M, Saum, KU, Sawhney, M, Schöttker, B, Shankar, A, Shlipak, M, Silva, DAS, Toyoshima, H, Ukwaja, K, Umesawa, M, Vollset, SE, Warnock, DG, Werdecker, A, Yamagishi, K, Yano, Y, Yonemoto, N, Zaki, MES, Naghavi, M, Forouzanfar, MH, Murray, CJL, Coresh, J, Vos, T, Global Burden of Disease, GFR Collaborators, CKD Prognosis Consortium, Global Burden of Disease Genitourinary Expert Group, Bello, A, Hanson, S, Vos, T., Thomas, B, Matsushita, K, Abate, Kh, Al Aly, Z, Ärnlöv, J, Asayama, K, Atkins, R, Badawi, A, Ballew, Sh, Banerjee, A, Barregård, L, Barrett Connor, E, Basu, S, Bello, Ak, Bensenor, I, Bergstrom, J, Bikbov, B, Blosser, C, Brenner, H, Carrero, Jj, Chadban, S, Cirillo, Massimo, Cortinovis, M, Courville, K, Dandona, L, Dandona, R, Estep, K, Fernandes, J, Fischer, F, Fox, C, Gansevoort, Rt, Gona, Pn, Gutierrez, Om, Hamidi, S, Hanson, Sw, Himmelfarb, J, Jassal, Sk, Jee, Sh, Jha, V, Jimenez Corona, A, Jonas, Jb, Kengne, Ap, Khader, Y, Khang, Yh, Kim, Yj, Klein, B, Klein, R, Kokubo, Y, Kolte, D, Lee, K, Levey, A, Li, Y, Lotufo, P, El, Razek, Hma, Mendoza, W, Metoki, H, Mok, Y, Muraki, I, Muntner, Pm, Noda, H, Ohkubo, T, Ortiz, A, Perico, N, Polkinghorne, K, Al Radaddi, R, Remuzzi, G, Roth, G, Rothenbacher, D, Satoh, M, Saum, Ku, Sawhney, M, Schöttker, B, Shankar, A, Shlipak, M, Silva, Da, Toyoshima, H, Ukwaja, K, Umesawa, M, Vollset, Se, Warnock, Dg, Werdecker, A, Yamagishi, K, Yano, Y, Yonemoto, N, Zaki, Me, Naghavi, M, Forouzanfar, Mh, Murray, Cjl, Coresh, J, Vos, T, Global Burden of, Disease, Gfr, Collaborator, CKD Prognosis, Consortium, Global Burden of Disease Genitourinary Expert, Group, Bello, A, Hanson, S, and Vos, T.
Subjects: Epidemiology and outcomes, cardiovascular disease, chronic dialysis, chronic kidney disease, end stage kidney disease, urologic and male genital diseases, Global Health, Kidney, Risk Assessment, female genital diseases and pregnancy complications, Cardiovascular Diseases, Risk Factors, Epidemiology and outcome, chronic dialysi, Humans, Kidney Diseases, Clinical Epidemiology, Glomerular Filtration Rate
Abstract: The burden of premature death and health loss from ESRD is well described. Less is known regarding the burden of cardiovascular disease attributable to reduced GFR. We estimated the prevalence of reduced GFR categories 3, 4, and 5 (not on RRT) for 188 countries at six time points from 1990 to 2013. Relative risks of cardiovascular outcomes by three categories of reduced GFR were calculated by pooled random effects meta-analysis. Results are presented as deaths for outcomes of cardiovascular disease and ESRD and as disability-adjusted life years for outcomes of cardiovascular disease, GFR categories 3, 4, and 5, and ESRD. In 2013, reduced GFR was associated with 4% of deaths worldwide, or 2.2 million deaths (95% uncertainty interval [95% UI], 2.0 to 2.4 million). More than half of these attributable deaths were cardiovascular deaths (1.2 million; 95% UI, 1.1 to 1.4 million), whereas 0.96 million (95% UI, 0.81 to 1.0 million) were ESRD-related deaths. Compared with metabolic risk factors, reduced GFR ranked below high systolic BP, high body mass index, and high fasting plasma glucose, and similarly with high total cholesterol as a risk factor for disability-adjusted life years in both developed and developing world regions. In conclusion, by 2013, cardiovascular deaths attributed to reduced GFR outnumbered ESRD deaths throughout the world. Studies are needed to evaluate the benefit of early detection of CKD and treatment to decrease these deaths.
Published: 2016

8. Past Decline Versus Current eGFR and Subsequent Mortality Risk

Author: Naimark DMJ, Grams ME, Matsushita K, Black C, Drion I, Fox CS, Inker LA, Ishani A, Jee SA, Kitamura A, Lea JP, Nally J, Peralta CA, Rothenbacher D, Ryu S, Tonelli M, Yatsuya H, Coresh J, Gansevoort RT, Warnock DG, Woodward M, de Jong PE, the CKD Prognosis Consortium, Wright JTJr, Appel LJ, Greene T, MacMahon S, Chalmers J, Arima H, Yamashita K, Toyoshima H, Tamakoshi K, Hemmelgarn B, James M, Sang Y, Atkins RC, Polkinghorne KR, Chadban S, Shankar A, Klein R, Klein BEK, Lee KE, Levin A, Djurdjev O, Sacks FM, Curhan GC, Zawada AM, Rogacev KS, Seiler S, Heine GH, Navaneethan SD, Schold JD, Shlipak M, Sarnak MJ, Katz R, Imano H, Yamagishi K, Wheeler DC, Emberson J, Townend JN, Landray MJ, Brenner H, Müller H, Schöttker B, Hwang S-J, Meigs JB, Uphadhay A, Green J, Kirchner HL, Perkins R, Chang AR, Fluck N, Prescott GJ, Cirillo M, Hallan S, Aasarød K, Øien CM, Radtke M, Irie F, Iso H, Sairenchi T, Smith DH, Thorp ML, Johnson ES, Lee BJ, Guallar E, Chang SY, Cho J, Shin H, Chodick G, Shalev V, Birnbaum YC, Shainberg B, Wetzels JFM, Blankestijn PJ, van Zuilen AD, Levey AS, Neaton JD, Froissart M, Stengel B, Metzger M, Haymann J-P, Houillier P, Flamant M, Elley CR, Kenealy T, Moyes SA, Collins JF, Drury PL, Ohkubo T, Metoki H, Nakayama M, Imai Y, Iseki K, Nelson RG, Knowler WC, Bakker SJL, LHillege H, Jassal SK, Bergstrom J, Ix JH, Barrett-Connor E, Heerspink HJL, Brenner BE, de Zeeuw D, Kimm H, Mok Y, Tangri N, Wen C-P, Wen S-F, Tsao C-K, Tsai M-K, Ärnlöv J, Lannfelt L, Larsson A, Kovesdy CP, Kalantar-Zadeh K, Bilo HJ, Kleefstra N, Groenier KH, Joosten H, Ballew SH, Naimark, Dmj, Grams, Me, Matsushita, K, Black, C, Drion, I, Fox, C, Inker, La, Ishani, A, Jee, Sa, Kitamura, A, Lea, Jp, Nally, J, Peralta, Ca, Rothenbacher, D, Ryu, S, Tonelli, M, Yatsuya, H, Coresh, J, Gansevoort, Rt, Warnock, Dg, Woodward, M, de Jong, Pe, the CKD Prognosis, Consortium, Wright, Jtjr, Appel, Lj, Greene, T, Macmahon, S, Chalmers, J, Arima, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Hemmelgarn, B, James, M, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Zawada, Am, Rogacev, K, Seiler, S, Heine, Gh, Navaneethan, Sd, Schold, Jd, Shlipak, M, Sarnak, Mj, Katz, R, Imano, H, Yamagishi, K, Wheeler, Dc, Emberson, J, Townend, Jn, Landray, Mj, Brenner, H, Müller, H, Schöttker, B, Hwang, S-J, Meigs, Jb, Uphadhay, A, Green, J, Kirchner, Hl, Perkins, R, Chang, Ar, Fluck, N, Prescott, Gj, Cirillo, M, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Iso, H, Sairenchi, T, Smith, Dh, Thorp, Ml, Johnson, E, Lee, Bj, Guallar, E, Chang, Sy, Cho, J, Shin, H, Chodick, G, Shalev, V, Birnbaum, Yc, Shainberg, B, Wetzels, Jfm, Blankestijn, Pj, van Zuilen, Ad, Levey, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Elley, Cr, Kenealy, T, Moyes, Sa, Collins, Jf, Drury, Pl, Ohkubo, T, Metoki, H, Nakayama, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Bakker, Sjl, Lhillege, H, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Heerspink, Hjl, Brenner, Be, de Zeeuw, D, Kimm, H, Mok, Y, Tangri, N, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Ärnlöv, J, Lannfelt, L, Larsson, A, Kovesdy, Cp, Kalantar-Zadeh, K, Bilo, Hj, Kleefstra, N, Groenier, Kh, Joosten, H, Ballew, Sh, Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)
Subjects: Gerontology, Male, CHRONIC KIDNEY-DISEASE, medicine.medical_specialty, Time Factors, 030232 urology & nephrology, Renal function, 030204 cardiovascular system & hematology, ALL-CAUSE, GLOMERULAR-FILTRATION-RATE, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Cause of Death, Epidemiology, Risk of mortality, medicine, EQUATION, Humans, Clinical Epidemiology, Renal Insufficiency, Chronic, Aged, Proportional Hazards Models, business.industry, Hazard ratio, STAGE RENAL-DISEASE, DEATH, General Medicine, Middle Aged, POPULATION COHORTS, Confidence interval, Increased risk, Nephrology, CARDIOVASCULAR-DISEASE, COLLABORATIVE METAANALYSIS, Female, business, HIGHER ALBUMINURIA, All cause mortality, Glomerular Filtration Rate
Abstract: A single determination of eGFR associates with subsequent mortality risk. Prior decline in eGFR indicates loss of kidney function, but the relationship to mortality risk is uncertain. We conducted an individual-level meta-analysis of the risk of mortality associated with antecedent eGFR slope, adjusting for established risk factors, including last eGFR, among 1.2 million subjects from 12 CKD and 22 other cohorts within the CKD Prognosis Consortium. Over a 3-year antecedent period, 12% of participants in the CKD cohorts and 11% in the other cohorts had an eGFR slope-5 ml/min per 1.73 m(2) per year, whereas 7% and 4% had a slope5 ml/min per 1.73 m(2) per year, respectively. Compared with a slope of 0 ml/min per 1.73 m(2) per year, a slope of -6 ml/min per 1.73 m(2) per year associated with adjusted hazard ratios for all-cause mortality of 1.25 (95% confidence interval [95% CI], 1.09 to 1.44) among CKD cohorts and 1.15 (95% CI, 1.01 to 1.31) among other cohorts during a follow-up of 3.2 years. A slope of +6 ml/min per 1.73 m(2) per year also associated with higher all-cause mortality risk, with adjusted hazard ratios of 1.58 (95% CI, 1.29 to 1.95) among CKD cohorts and 1.43 (95% CI, 1.11 to 1.84) among other cohorts. Results were similar for cardiovascular and noncardiovascular causes of death and stronger for longer antecedent periods (3 versus3 years). We conclude that prior decline or rise in eGFR associates with an increased risk of mortality, independent of current eGFR.
Published: 2016

9. Age and Association of Kidney Measures With Mortality and End-stage Renal Disease

Author: Wright, Jt, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Jong, De, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Brenner, Be, Zeeuw, De, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Wright JT Jr, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, van Zuilen AD, Sarnak, M, Levey, A, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, de Jong PE, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.
Subjects: Male, BLOOD-PRESSURE, urologic and male genital diseases, Kidney, età, GLOMERULAR-FILTRATION-RATE, Cohort Studies, eGFR, Young adult, Renal disorder [IGMD 9], ALL-CAUSE MORTALITY, GENERAL-POPULATION, insufficienza renale, biology, CYSTATIN C, CARDIOVASCULAR RISK, Age Factors, General Medicine, Middle Aged, female genital diseases and pregnancy complications, RISK POPULATION COHORTS, medicine.anatomical_structure, Female, medicine.symptom, Glomerular Filtration Rate, albuminuria, rischio, mortalità, Adult, Risk, medicine.medical_specialty, Adolescent, Renal function, Context (language use), End stage renal disease, Young Adult, Internal medicine, medicine, Albuminuria, Humans, OLDER-ADULTS, Aged, urogenital system, business.industry, URINARY ALBUMIN EXCRETION, medicine.disease, Endocrinology, Cystatin C, COLLABORATIVE METAANALYSIS, biology.protein, Kidney Failure, Chronic, business, Kidney disease
Abstract: Context Chronic kidney disease (CKD) is prevalent in older individuals, but the risk implications of low estimated glomerular filtration rate (eGFR) and high albuminuria across the full age range are controversial.Objective To evaluate possible effect modification (interaction) by age of the association of eGFR and albuminuria with clinical risk, examining both relative and absolute risks.Design, Setting, and Participants Individual-level meta-analysis including 2 051 244 participants from 33 general population or high-risk (of vascular disease) cohorts and 13 CKD cohorts from Asia, Australasia, Europe, and North/South America, conducted in 1972-2011 with a mean follow-up time of 5.8 years (range, 0-31 years).Main Outcome Measures Hazard ratios (HRs) of mortality and end-stage renal disease (ESRD) according to eGFR and albuminuria were meta-analyzed across age categories after adjusting for sex, race, cardiovascular disease, diabetes, systolic blood pressure, cholesterol, body mass index, and smoking. Absolute risks were estimated using HRs and average incidence rates.Results Mortality (112 325 deaths) and ESRD (8411 events) risks were higher at lower eGFR and higher albuminuria in every age category. In general and high-risk cohorts, relative mortality risk for reduced eGFR decreased with increasing age; eg, adjusted HRs at an eGFR of 45 mL/min/1.73 m(2) vs 80 mL/min/1.73 m(2) were 3.50 (95% CI, 2.55-4.81), 2.21 (95% CI, 2.02-2.41), 1.59 (95% CI, 1.42-1.77), and 1.35 (95% CI, 1.23-1.48) in age categories 18-54, 55-64, 65-74, and >= 75 years, respectively (P Conclusions Both low eGFR and high albuminuria were independently associated with mortality and ESRD regardless of age across a wide range of populations. Mortality showed lower relative risk but higher absolute risk differences at older age.
Published: 2012
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10. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis

Author: Fox, Cs, Matsushita, K, Woodward, M, Bilo, Hj, Chalmers, J, Heerspink, Hj, Lee, Bj, Perkins, Rm, Rossing, P, Sairenchi, T, Tonelli, M, Vassalotti, Ja, Yamagishi, K, Coresh, J, Jong, De, Wen, Cp, Nelson, Rg, Chronic, Kidney, Disease, Prognosis, Consortium, Investigators/collaborators:, Wright, J, Appel, L, Greene, T, Astor, Bc, Macmahon, S, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Hwang, Sj, Meigs, Jb, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Li, S, Chen, Sc, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Menon, V, Kramer, Hj, Boer, De, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Knowler, Wc, Gansevoort, Rt, Mahmoodi, Bk, Bakker, Sj, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Lambers, Heerspink, Brenner, Be, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, B, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Groningen Kidney Center (GKC), Methods in Medicines evaluation & Outcomes research (M2O), Lifestyle Medicine (LM), Fox, C, Matsushita, K, Woodward, M, Bilo, Hj, Chalmers, J, Heerspink, Hj, Lee, Bj, Perkins, Rm, Rossing, P, Sairenchi, T, Tonelli, M, Vassalotti, Ja, Yamagishi, K, Coresh, J, de Jong PE, Wen, Cp, Nelson, Rg, Investigators/Collaborators: Wright J, Chronic Kidney Disease Prognosis Consortium, Appel, L, Greene, T, Astor, Bc, Macmahon, S, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Hwang, Sj, Meigs, Jb, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Li, S, Chen, Sc, Wetzels, Jf, Blankestijn, Pj, van Zuilen AD, Sarnak, M, Levey, A, Menon, V, Kramer, Hj, de Boer IH, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Knowler, Wc, Gansevoort, Rt, Mahmoodi, Bk, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Lambers Heerspink HJ, Brenner, Be, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, B, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.
Subjects: medicine.medical_specialty, Population, UNITED-STATES, Renal function, ALL-CAUSE, GLOMERULAR-FILTRATION-RATE, albuminuria, End stage renal disease, Diabetic nephropathy, CKD-PC Consortium, Diabetes mellitus, Internal medicine, eGFR, Medicine, ESTIMATED GFR, education, Intensive care medicine, Renal disorder [IGMD 9], OUTCOMES, education.field_of_study, end-stage renal disease, diabetes, business.industry, Hazard ratio, PROTEINURIA, General Medicine, mortality, medicine.disease, RISK POPULATION COHORTS, PREVALENCE, diabete, COLLABORATIVE METAANALYSIS, Albuminuria, medicine.symptom, HIGHER ALBUMINURIA, business, Kidney disease
Abstract: Item does not contain fulltext BACKGROUND: Chronic kidney disease is characterised by low estimated glomerular filtration rate (eGFR) and high albuminuria, and is associated with adverse outcomes. Whether these risks are modified by diabetes is unknown. METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and end-stage renal disease (ESRD) associated with eGFR and albuminuria in individuals with and without diabetes. FINDINGS: We analysed data for 1,024,977 participants (128,505 with diabetes) from 30 general population and high-risk cardiovascular cohorts and 13 chronic kidney disease cohorts. In the combined general population and high-risk cohorts with data for all-cause mortality, 75,306 deaths occurred during a mean follow-up of 8.5 years (SD 5.0). In the 23 studies with data for cardiovascular mortality, 21,237 deaths occurred from cardiovascular disease during a mean follow-up of 9.2 years (SD 4.9). In the general and high-risk cohorts, mortality risks were 1.2-1.9 times higher for participants with diabetes than for those without diabetes across the ranges of eGFR and albumin-to-creatinine ratio (ACR). With fixed eGFR and ACR reference points in the diabetes and no diabetes groups, HR of mortality outcomes according to lower eGFR and higher ACR were much the same in participants with and without diabetes (eg, for all-cause mortality at eGFR 45 mL/min per 1.73 m(2) [vs 95 mL/min per 1.73 m(2)], HR 1.35; 95% CI 1.18-1.55; vs 1.33; 1.19-1.48 and at ACR 30 mg/g [vs 5 mg/g], 1.50; 1.35-1.65 vs 1.52; 1.38-1.67). The overall interactions were not significant. We identified much the same findings for ESRD in the chronic kidney disease cohorts. INTERPRETATION: Despite higher risks for mortality and ESRD in diabetes, the relative risks of these outcomes by eGFR and ACR are much the same irrespective of the presence or absence of diabetes, emphasising the importance of kidney disease as a predictor of clinical outcomes. FUNDING: US National Kidney Foundation.
Published: 2012
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11. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate

Author: Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, As, Chronic, Kidney, Disease, Prognosis, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, Es, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Menon, V, Boer, De, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Jong, De, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, Zeeuw, De, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, A, Chronic, Kidney, Disease, Prognosi, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, E, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Sarnak, M, Menon, V, De, Boer, Ih, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, De, Jong, Pe, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, De, Zeeuw, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)
Subjects: CHRONIC KIDNEY-DISEASE, Gerontology, Male, EVALUATION PROGRAM KEEP, Population, Renal function, Black People, Ckd epi equation, urologic and male genital diseases, Risk Assessment, White People, Article, Decision Support Techniques, Cohort Studies, Sex Factors, Asian People, EPIDEMIOLOGY COLLABORATION EQUATION, Diabetes mellitus, CYSTATIN-C, Medicine, Humans, education, ALL-CAUSE MORTALITY, Cardiovascular mortality, Aged, Renal disorder [IGMD 9], GENERAL-POPULATION, education.field_of_study, business.industry, CARDIOVASCULAR RISK, Hazard ratio, STAGE RENAL-DISEASE, General Medicine, POPULATION COHORTS, Middle Aged, Models, Theoretical, medicine.disease, female genital diseases and pregnancy complications, Net reclassification improvement, SERUM CREATININE VALUES, Cardiovascular Diseases, Kidney Failure, Chronic, Female, business, Algorithms, Demography, Glomerular Filtration Rate
Abstract: Contains fulltext : 110640.pdf (Publisher’s version ) (Closed access) CONTEXT: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. OBJECTIVE: To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics. DESIGN, SETTING, AND PARTICIPANTS: A meta-analysis of data from 1.1 million adults (aged >/= 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. MAIN OUTCOME MEASURES: All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years). RESULTS: Estimated GFR was classified into 6 categories (>/=90, 60-89, 45-59, 30-44, 15-29, and /=65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts. CONCLUSION: The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.
Published: 2012

12. Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data

Author: Matsushita, K, Coresh, J, Sang, Y, Chalmers, J, Fox, C, Guallar, E, Jafar, T, Jassal, Sk, Landman, Gw, Muntner, P, Roderick, P, Sairenchi, T, Schöttker, B, Shankar, A, Shlipak, M, Tonelli, M, Townend, J, van Zuilen, A, Yamagishi, K, Yamashita, K, Gansevoort, R, Sarnak, M, Warnock, Dg, Woodward, M, Ärnlöv J, CKD Prognosis Consortium, Macmahon, S, Arima, H, Yatsuya, H, Toyoshima, H, Tamakoshi, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Sacks, Fm, Curhan, Gc, Sarnak, Mj, Katz, R, Iso, H, Kitamura, A, Imano, H, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Wheeler, Dc, Emberson, J, Townend, Jn, Landray, Mj, Brenner, H, Rothenbacher, D, Müller, H, Fox, Cs, Hwang, Sj, Meigs, Jb, Upadhyay, A, Perkins, R, Chang, Ar, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Romundstad, S, Ryu, S, Chang, Y, Cho, J, Shin, H, Chodick, G, Shalev, V, Ash, N, Shainberg, B, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Levey, As, Inker, La, Menon, V, Peralta, C, Nitsch, D, Fletcher, A, Bulpitt, C, Elley, Cr, Kenealy, T, Moyes, Sa, Collins, Jf, Drury, P, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Gansevoort, Rt, Bakker, Sj, Hillege, Hl, Heerspink, Hj, Bergstrom, J, Jh, Ix, Barrett Connor, E, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Mok, Y, Tangri, N, Sud, M, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Kleefstra, N, Groenier, Kh, Joosten, H, Drion, I, Jong, De, Iseki, K, Stengel, B, Warnock, D, Ballew, Sh, Woodward, M., Matsushita, K, Coresh, J, Sang, Y, Chalmers, J, Fox, C, Guallar, E, Jafar, T, Jassal, Sk, Landman, Gw, Muntner, P, Roderick, P, Sairenchi, T, Schöttker, B, Shankar, A, Shlipak, M, Tonelli, M, Townend, J, van Zuilen, A, Yamagishi, K, Yamashita, K, Gansevoort, R, Sarnak, M, Warnock, Dg, Woodward, M, Ärnlöv, J, CKD Prognosis, Consortium, Macmahon, S, Arima, H, Yatsuya, H, Toyoshima, H, Tamakoshi, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Sacks, Fm, Curhan, Gc, Sarnak, Mj, Katz, R, Iso, H, Kitamura, A, Imano, H, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Wheeler, Dc, Emberson, J, Townend, Jn, Landray, Mj, Brenner, H, Rothenbacher, D, Müller, H, Hwang, Sj, Meigs, Jb, Upadhyay, A, Perkins, R, Chang, Ar, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Romundstad, S, Ryu, S, Chang, Y, Cho, J, Shin, H, Chodick, G, Shalev, V, Ash, N, Shainberg, B, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Levey, A, Inker, La, Menon, V, Peralta, C, Nitsch, D, Fletcher, A, Bulpitt, C, Elley, Cr, Kenealy, T, Moyes, Sa, Collins, Jf, Drury, P, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Gansevoort, Rt, Bakker, Sj, Hillege, Hl, Heerspink, Hj, Bergstrom, J, Ix, Jh, Barrett Connor, E, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Mok, Y, Tangri, N, Sud, M, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Lannfelt, L, Larsson, A, Bilo, Hj, Kleefstra, N, Groenier, Kh, Joosten, H, Drion, I, De, Jong, Pe, Iseki, K, Stengel, B, Warnock, D, Ballew, Sh, Woodward, M., Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)
Subjects: CHRONIC KIDNEY-DISEASE, Male, Endocrinology, Diabetes and Metabolism, Coronary Disease, 030204 cardiovascular system & hematology, chemistry.chemical_compound, 0302 clinical medicine, Endocrinology, cardiovascular disease, Risk Factors, eGFR, EQUATION, ARTERY-DISEASE, EPIDEMIOLOGY, 030212 general & internal medicine, RISK, education.field_of_study, CYSTATIN C, biology, ASSOCIATION, Middle Aged, 3. Good health, Stroke, 1101 Medical Biochemistry and Metabolomics, Cardiovascular Diseases, Creatinine, eGFR, albuminuria, cardiovascular disease, HEART, Female, medicine.symptom, Life Sciences & Biomedicine, Glomerular Filtration Rate, Adult, medicine.medical_specialty, Population, Renal function, 1117 Public Health and Health Services, Endocrinology & Metabolism, 03 medical and health sciences, Diabetes mellitus, Internal medicine, CKD, Internal Medicine, medicine, Albuminuria, Humans, education, CKD Prognosis Consortium, Heart Failure, Science & Technology, business.industry, MORTALITY, 1103 Clinical Sciences, medicine.disease, chemistry, Cystatin C, Heart failure, biology.protein, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, Follow-Up Studies, Kidney disease
Abstract: Item does not contain fulltext BACKGROUND: The usefulness of estimated glomerular filtration rate (eGFR) and albuminuria for prediction of cardiovascular outcomes is controversial. We aimed to assess the addition of creatinine-based eGFR and albuminuria to traditional risk factors for prediction of cardiovascular risk with a meta-analytic approach. METHODS: We meta-analysed individual-level data for 637 315 individuals without a history of cardiovascular disease from 24 cohorts (median follow-up 4.2-19.0 years) included in the Chronic Kidney Disease Prognosis Consortium. We assessed C statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in a 5 year timeframe, contrasting prediction models for traditional risk factors with and without creatinine-based eGFR, albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria), or both. FINDINGS: The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR, and more evident for cardiovascular mortality (C statistic difference 0.0139 [95% CI 0.0105-0.0174] for ACR and 0.0065 [0.0042-0.0088] for eGFR) and heart failure (0.0196 [0.0108-0.0284] and 0.0109 [0.0059-0.0159]) than for coronary disease (0.0048 [0.0029-0.0067] and 0.0036 [0.0019-0.0054]) and stroke (0.0105 [0.0058-0.0151] and 0.0036 [0.0004-0.0069]). Dipstick proteinuria showed smaller improvement than ACR. The discrimination improvement with eGFR or ACR was especially evident in individuals with diabetes or hypertension, but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these disorders. In individuals with chronic kidney disease, the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the C statistic for cardiovascular mortality fell by 0.0227 (0.0158-0.0296) after omission of eGFR and ACR compared with less than 0.007 for any single modifiable traditional predictor. INTERPRETATION: Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when these measures are already assessed for clinical purpose or if cardiovascular mortality and heart failure are outcomes of interest. ACR could have particularly broad implications for cardiovascular prediction. In populations with chronic kidney disease, the simultaneous assessment of eGFR and ACR could facilitate improved classification of cardiovascular risk, supporting current guidelines for chronic kidney disease. Our results lend some support to also incorporating eGFR and ACR into assessments of cardiovascular risk in the general population. FUNDING: US National Kidney Foundation, National Institute of Diabetes and Digestive and Kidney Diseases.
Published: 2015

13. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013

Author: Vos, T, Barber, Rm, Bell, B, Bertozzi Villa, A, Biryukov, S, Bolliger, I, Charlson, F, Davis, A, Degenhardt, L, Dicker, D, Duan, L, Erskine, H, Feigin, Vl, Ferrari, Aj, Fitzmaurice, C, Fleming, T, Graetz, N, Guinovart, C, Haagsma, J, Hansen, Gm, Hanson, Sw, Heuton, Kr, Higashi, H, Kassebaum, N, Kyu, H, Laurie, E, Liang, X, Lofgren, K, Lozano, R, Macintyre, Mf, Moradi Lakeh, M, Naghavi, M, Nguyen, G, Odell, S, Ortblad, K, Roberts, Da, Roth, Ga, Sandar, L, Serina, Pt, Stanaway, Jd, Steiner, C, Thomas, B, Vollset, Se, Whiteford, H, Wolock, Tm, Ye, P, Zhou, M, Ãvila, Ma, Aasvang, Gm, Abbafati, C, Abbasoglu, Ozgoren, A, Abd Allah, F, Abdel, Aziz, Abera, Sf, Aboyans, V, Abraham, Jp, Abraham, B, Abubakar, I, Abu Raddad, Lj, Abu Rmeileh, Nm, Aburto, Tc, Achoki, T, Ackerman, In, Adelekan, A, Ademi, Z, Adou, Ak, Adsuar, Jc, Arnlov, J, Agardh, Ee, Khabouri, Al, Alam, Ss, Alasfoor, D, Albittar, Mi, Alegretti, Ma, Aleman, Av, Alemu, Za, Alfonso Cristancho, R, Alhabib, S, Ali, R, Alla, F, Allebeck, P, Allen, Pj, Almazroa, Ma, Alsharif, U, Alvarez, E, Alvis, Guzman, Ameli, N, O, Amini, H, Ammar, W, Anderson, Bo, Anderson, Hr, Antonio, Ca, Anwari, P, Apfel, H, Arsenijevic, Vs, Artaman, A, Asghar, Rj, Assadi, R, Atkins, Ls, Atkinson, C, Badawi, A, Bahit, Mc, Bakfalouni, T, Balakrishnan, K, Balalla, S, Banerjee, A, Barker Collo, Sl, Barquera, S, Barregard, L, Barrero, Lh, Basu, S, Basu, A, Baxter, A, Beardsley, J, Bedi, N, Beghi, E, Bekele, T, Bell, Ml, Benjet, C, Bennett, Da, Bensenor, Im, Benzian, H, Bernabe, E, Beyene, Tj, Bhala, N, Bhalla, A, Bhutta, Z, Bienhoff, K, Bikbov, B, Bin, Abdulhak, Blore, Jd, Blyth, Fm, Bohensky, Ma, Bora, Basara, B, Borges, G, Bornstein, Nm, Bose, D, Boufous, S, Bourne, Rr, Boyers, Ln, Brainin, M, Brauer, M, Brayne, Ce, Brazinova, A, Breitborde, Nj, Brenner, H, Briggs, Ad, Brooks, Pm, Brown, J, Brugha, Ts, Buchbinder, R, Buckle, Gc, Bukhman, G, Bulloch, Ag, Burch, M, Burnett, R, Cardenas, R, Cabral, Nl, Campos, Nonato, Campuzano, Ir, Carapetis, Jc, Carpenter, Do, Caso, V, Castaneda Orjuela, Ca, Catala Lopez, F, Chadha, Vk, Chang, Jc, Chen, H, Chen, W, Chiang, Pp, Chimed Ochir, O, Chowdhury, R, Christensen, H, Christophi, Ca, Chugh, Ss, Cirillo, Massimo, Coggeshall, M, Cohen, A, Colistro, V, Colquhoun, Sm, Contreras, Ag, Cooper, Lt, Cooper, C, Cooperrider, K, Coresh, J, Cortinovis, M, Criqui, Mh, Crump, Ja, Cuevas Nasu, L, Dandona, R, Dandona, L, Dansereau, E, Dantes, Hg, Dargan, Pi, Davey, G, Davitoiu, Dv, Dayama, A, La, De, Cruz, Gongora, De, V, Vega, La, De, Sf, Leo, D, Del, Pozo, Cruz, Dellavalle, Rp, Deribe, K, Derrett, S, Des, Jarlais, Dessalegn, M, Deveber, Ga, Dharmaratne, Sd, Diaz Torne, C, Ding, El, Dokova, K, Dorsey, Er, Driscoll, Tr, Duber, H, Durrani, Am, Edmond, Km, Ellenbogen, Rg, Endres, M, Ermakov, Sp, Eshrati, B, Esteghamati, A, Estep, K, Fahimi, S, Farzadfar, F, Fay, Df, Felson, Dt, Fereshtehnejad, Sm, Fernandes, Jg, Ferri, Cp, Flaxman, A, Foigt, N, Foreman, Kj, Fowkes, Fg, Franklin, Rc, Furst, T, Futran, Nd, Gabbe, Bj, Gankpe, Fg, Garcia, Guerra, Geleijnse, Fa, Gessner, Bd, Gibney, Kb, Gillum, Rf, Ginawi, Ia, Giroud, M, Giussani, G, Goenka, S, Goginashvili, K, Gona, P, Gonzalez, De, Cosio, T, Gosselin, Ra, Gotay, Cc, Goto, A, Gouda, Hn, Guerrant, Rl, Gugnani, Hc, Gunnell, D, Gupta, R, Gutierrez, Ra, Hafezi Nejad, N, Hagan, H, Halasa, Y, Hamadeh, Rr, Hamavid, H, Hammami, M, Hankey, Gj, Hao, Y, Harb, Hl, Haro, Jm, Havmoeller, R, Hay, Rj, Hay, S, Hedayati, Mt, Heredia, Pi, Heydarpour, P, Hijar, M, Hoek, Hw, Hoffman, Hj, Hornberger, Jc, Hosgood, Hd, Hossain, M, Hotez, Pj, Hoy, Dg, Hsairi, M, Hu, H, Hu, G, Huang, Jj, Huang, C, Huiart, L, Husseini, A, Iannarone, M, Iburg, Km, Innos, K, Inoue, M, Jacobsen, Kh, Jassal, Sk, Jeemon, P, Jensen, Pn, Jha, V, Jiang, G, Jiang, Y, Jonas, Jb, Joseph, J, Juel, K, Kan, H, Karch, A, Karimkhani, C, Karthikeyan, G, Katz, R, Kaul, A, Kawakami, N, Kazi, Ds, Kemp, Ah, Kengne, Ap, Khader, Ys, Khalifa, Se, Khan, Ea, Khan, G, Khang, Yh, Khonelidze, I, Kieling, C, Kim, D, Kim, S, Kimokoti, Rw, Kinfu, Y, Kinge, Jm, Kissela, Bm, Kivipelto, M, Knibbs, L, Knudsen, Ak, Kokubo, Y, Kosen, S, Kramer, A, Kravchenko, M, Krishnamurthi, Rv, Krishnaswami, S, Kuate, Defo, Kucuk, B, Bicer, B, Kuipers, Ej, Kulkarni, Vs, Kumar, K, Kumar, Ga, Kwan, Gf, Lai, T, Lalloo, R, Lam, H, Lan, Q, Lansingh, Vc, Larson, H, Larsson, A, Lawrynowicz, Ae, Leasher, Jl, Lee, Jt, Leigh, J, Leung, R, Levi, M, Li, B, Li, Y, Liang, J, Lim, S, Lin, Hh, Lind, M, Lindsay, Mp, Lipshultz, Se, Liu, S, Lloyd, Bk, Lockett, Ohno, S, Logroscino, G, Looker, Kj, Lopez, Ad, Lopez Olmedo, N, Lortet Tieulent, J, Lotufo, Pa, Low, N, Lucas, Rm, Lunevicius, R, Lyons, Ra, Ma, J, Ma, S, Mackay, Mt, Majdan, M, Malekzadeh, R, Mapoma, Cc, Marcenes, W, March, Lm, Margono, C, Marks, Gb, Marzan, Mb, Masci, Jr, Mason Jones, Aj, Matzopoulos, Rg, Mayosi, Bm, Mazorodze, Tt, Mcgill, Nw, Mcgrath, Jj, Mckee, M, Mclain, A, Mcmahon, Bj, Meaney, Pa, Mehndiratta, Mm, Mejia Rodriguez, F, Mekonnen, W, Melaku, Ya, Meltzer, M, Memish, Za, Mensah, G, Meretoja, A, Mhimbira, Fa, Micha, R, Miller, Tr, Mills, Ej, Mitchell, Pb, Mock, Cn, Moffitt, Te, Mohamed, Ibrahim, N, Mohammad, Ka, Mokdad, Ah, Mola, Gl, Monasta, L, Montico, M, Montine, Tj, Moore, Ar, Moran, Ae, Morawska, L, Mori, R, Moschandreas, J, Moturi, Wn, Moyer, M, Mozaffarian, D, Mueller, Uo, Mukaigawara, M, Murdoch, Me, Murray, J, Murthy, Ks, Naghavi, P, Nahas, Z, Naheed, A, Naidoo, Ks, Naldi, L, Nand, D, Nangia, V, Narayan, Km, Nash, D, Nejjari, C, Neupane, Sp, Newman, Lm, Newton, Cr, Ng, M, Ngalesoni, Fn, Nhung, Nt, Nisar, Mi, Nolte, S, Norheim, Of, Norman, Re, Norrving, B, Nyakarahuka, L, Ih, Oh, Ohkubo, T, Omer, Sb, Opio, Jn, Ortiz, A, Pandian, Jd, Panelo, Ci, Papachristou, C, Park, Ek, Parry, Cd, Caicedo, Aj, Patten, Sb, Paul, Vk, Pavlin, Bi, Pearce, N, Pedraza, Ls, Pellegrini, Ca, Pereira, Dm, Perez Ruiz, Fp, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, Cb, Petzold, M, Phillips, Mr, Phillips, D, Phillips, B, Piel, Fb, Plass, D, Poenaru, D, Polanczyk, Gv, Polinder, S, Pope, Ca, Popova, S, Poulton, Rg, Pourmalek, F, Prabhakaran, D, Prasad, Nm, Qato, D, Quistberg, Da, Rafay, A, Rahimi, K, Rahimi Movaghar, V, Rahman, Su, Raju, M, Rakovac, I, Rana, Sm, Razavi, H, Refaat, A, Rehm, J, Remuzzi, G, Resnikoff, S, Ribeiro, Al, Riccio, Pm, Richardson, L, Richardus, Jh, Riederer, Am, Robinson, M, Roca, A, Rodriguez, A, Rojas Rueda, D, Ronfani, L, Rothenbacher, D, Roy, N, Ruhago, Gm, Sabin, N, Sacco, Rl, Ksoreide, K, Saha, S, Sahathevan, R, Sahraian, Ma, Sampson, U, Sanabria, Jr, Sanchez Riera, L, Santos, Is, Satpathy, M, Saunders, Je, Sawhney, M, Saylan, Mi, Scarborough, P, Schoettker, B, Schneider, Ij, Schwebel, Dc, Scott, Jg, Seedat, S, Sepanlou, Sg, Serdar, B, Servan Mori, Ee, Shackelford, K, Shaheen, A, Shahraz, S, Shamah, Levy, T, Shangguan, S, She, J, Sheikhbahaei, S, Shepard, Ds, Shi, P, Shibuya, K, Shinohara, Y, Shiri, R, Shishani, K, Shiue, I, Shrime, Mg, Sigfusdottir, Id, Silberberg, Dh, Simard, Ep, Sindi, S, Singh, Ja, Singh, L, Skirbekk, V, Sliwa, K, Soljak, M, Soneji, S, Soshnikov, Ss, Speyer, P, Sposato, La, Sreeramareddy, Ct, Stoeckl, H, Stathopoulou, Vk, Steckling, N, Stein, Mb, Stein, Dj, Steiner, Tj, Stewart, A, Stork, E, Stovner, Lj, Stroumpoulis, K, Sturua, L, Sunguya, Bf, Swaroop, M, Sykes, Bl, Tabb, Km, Takahashi, K, Tan, F, Tandon, N, Tanne, D, Tanner, M, Tavakkoli, M, Taylor, Hr, Ao, Te, Temesgen, Am, Ten, Have, M, Tenkorang, Ey, Terkawi, As, Theadom, Am, Thomas, E, Thorne Lyman, Al, Thrift, Ag, Tleyjeh, Im, Tonelli, M, Topouzis, F, Towbin, Ja, Toyoshima, H, Traebert, J, Tran, Bx, Trasande, L, Trillini, M, Truelsen, T, Trujillo, U, Tsilimbaris, M, Tuzcu, Em, Ukwaja, Kn, Undurraga, Ea, Uzun, Sb, Van, Brakel, Van, Wh, Vijver, De, Van, S, Dingenen, R, Van, Gool, Varakin, Yy, Vasankari, Tj, Vavilala, Ms, Veerman, Lj, Velasquez, Melendez, G, Venketasubramanian, N, Vijayakumar, L, Villalpando, S, Violante, Fs, Vlassov, Vv, Waller, S, Wallin, Mt, Wan, X, Wang, L, Wang, J, Wang, Y, Warouw, Ts, Weichenthal, S, Weiderpass, E, Weintraub, Rg, Werdecker, A, Wessells, Kr, Westerman, R, Wilkinson, Jd, Williams, Hc, Williams, Tn, Woldeyohannes, Sm, Wolfe, Cd, Wong, Jq, Wong, H, Woolf, Ad, Wright, Jl, Wurtz, B, Xu, G, Yang, G, Yano, Y, Yenesew, Ma, Yentur, Gk, Yip, P, Yonemoto, N, Yoon, Sj, Younis, M, Yu, C, Kim, Ky, Zaki, Mel, Zhang, Y, Zhao, Z, Zhao, Y, Zhu, J, Zonies, D, Zunt, Jr, Salomon, Ja, Murray, C. J., Vos, T, Barber, Rm, Bell, B, Bertozzi-Villa, A, Biryukov, S, Bolliger, I, Charlson, F, Davis, A, Degenhardt, L, Dicker, D, Duan, L, Erskine, H, Feigin, Vl, Ferrari, Aj, Fitzmaurice, C, Fleming, T, Graetz, N, Guinovart, C, Haagsma, J, Hansen, Gm, Hanson, Sw, Heuton, Kr, Higashi, H, Kassebaum, N, Kyu, H, Laurie ELiang, X, Lofgren, K, Lozano, R, Macintyre, Mf, Moradi-Lakeh, M, Naghavi, M, Nguyen, G, Odell, S, Ortblad, K, Roberts, Da, Roth, Ga, Sandar, L, Serina, Pt, Stanaway, Jd, Steiner, C, Thomas, B, Vollset, Se, Whiteford, H, Wolock, Tm, Ye, P, Zhou, M, Ãvila, Ma, Aasvang, Gm, Abbafati, C, Abbasoglu Ozgoren, A, Abd-Allah, F, Abdel Aziz MI, Abera, Sf, Aboyans, V, Abraham, Jp, Abraham, B, Abubakar, I, Abu-Raddad, Lj, Abu-Rmeileh, Nm, Aburto, Tc, Achoki TAckerman IN, Adelekan, A, Ademi, Z, Adou, Ak, Adsuar, Jc, Arnlov, J, Agardh, Ee, Al Khabouri MJ, Alam, S, Alasfoor, D, Albittar, Mi, Alegretti MAAleman AV, Alemu, Za, Alfonso-Cristancho, R, Alhabib, S, Ali, R, Alla, F, Allebeck, P, Allen, Pj, Almazroa, Ma, Alsharif, U, Alvarez, E, Alvis-Guzman NAmeli, O, Amini, H, Ammar, W, Anderson, Bo, Anderson, Hr, Antonio, Ca, Anwari, P, Apfel, H, Arsenijevic, V, Artaman, A, Asghar, Rj, Assadi, R, Atkins, L, Atkinson, C, Badawi, A, Bahit, Mc, Bakfalouni, T, Balakrishnan, K, Balalla, S, Banerjee, A, Barker-Collo, Sl, Barquera, S, Barregard, L, Barrero LHBasu, S, Basu, A, Baxter, A, Beardsley, J, Bedi, N, Beghi, E, Bekele, T, Bell, Ml, Benjet, C, Bennett, Da, Bensenor, Im, Benzian, H, Bernabe, E, Beyene TJBhala, N, Bhalla, A, Bhutta, Z, Bienhoff, K, Bikbov, B, Bin Abdulhak, A, Blore, Jd, Blyth, Fm, Bohensky, Ma, Bora Basara, B, Borges, G, Bornstein, Nm, Bose, D, Boufous, S, Bourne, Rr, Boyers, Ln, Brainin, M, Brauer, M, Brayne, Ce, Brazinova, A, Breitborde, Nj, Brenner, H, Briggs, Ad, Brooks, Pm, Brown JBrugha TS, Buchbinder, R, Buckle, Gc, Bukhman, G, Bulloch, Ag, Burch, M, Burnett, R, Cardenas, R, Cabral, Nl, Campos Nonato IR, Campuzano JCCarapetis JR, Carpenter, Do, Caso, V, Castaneda-Orjuela, Ca, Catala-Lopez, F, Chadha, Vk, Chang, Jc, Chen, H, Chen, W, Chiang, Pp, Chimed-Ochir, O, Chowdhury, R, Christensen, H, Christophi, Ca, Chugh, S, Cirillo, M, Coggeshall, M, Cohen, A, Colistro, V, Colquhoun, Sm, Contreras, Ag, Cooper LTCooper, C, Cooperrider, K, Coresh, J, Cortinovis, M, Criqui, Mh, Crump, Ja, Cuevas-Nasu, L, Dandona, R, Dandona, L, Dansereau, E, Dantes, Hg, Dargan, Pi, Davey, G, Davitoiu, Dv, Dayama, A, De la Cruz-Gongora, V, de la Vega SF, De Leo, D, del Pozo-Cruz, B, Dellavalle, Rp, Deribe, K, Derrett, S, Des Jarlais DC, Dessalegn, M, Deveber, Ga, Dharmaratne, Sd, Diaz-Torne, C, Ding, El, Dokova, K, Dorsey, Er, Driscoll, Tr, Duber, H, Durrani, Am, Edmond, Km, Ellenbogen, Rg, Endres, M, Ermakov, Sp, Eshrati, B, Esteghamati, A, Estep, K, Fahimi, S, Farzadfar, F, Fay, Df, Felson, Dt, Fereshtehnejad SMFernandes JG, Ferri, Cp, Flaxman, A, Foigt, N, Foreman, Kj, Fowkes, Fg, Franklin, Rc, Furst, T, Futran, Nd, Gabbe, Bj, Gankpe, Fg, Garcia-Guerra FAGeleijnse JM, Gessner, Bd, Gibney, Kb, Gillum, Rf, Ginawi, Ia, Giroud, M, Giussani, G, Goenka, S, Goginashvili, K, Gona, P, Gonzalez de Cosio TGosselin RA, Gotay, Cc, Goto, A, Gouda, Hn, Guerrant, Rl, Gugnani, Hc, Gunnell, D, Gupta, R, Gutierrez, Ra, Hafezi-Nejad, N, Hagan HHalasa, Y, Hamadeh, Rr, Hamavid, H, Hammami, M, Hankey, Gj, Hao, Y, Harb, Hl, Haro, Jm, Havmoeller, R, Hay, Rj, Hay, S, Hedayati, Mt, Heredia Pi IB, Heydarpour, P, Hijar, M, Hoek, Hw, Hoffman, Hj, Hornberger, Jc, Hosgood, Hd, Hossain, M, Hotez, Pj, Hoy, Dg, Hsairi, M, Hu, H, Hu, G, Huang JJHuang, C, Huiart, L, Husseini, A, Iannarone, M, Iburg, Km, Innos, K, Inoue, M, Jacobsen, Kh, Jassal, Sk, Jeemon, P, Jensen, Pn, Jha, V, Jiang, G, Jiang YJonas JB, Joseph, J, Juel, K, Kan, H, Karch, A, Karimkhani, C, Karthikeyan, G, Katz, R, Kaul, A, Kawakami, N, Kazi, D, Kemp, Ah, Kengne, Ap, Khader, Y, Khalifa, Se, Khan, Ea, Khan, G, Khang, Yh, Khonelidze, I, Kieling, C, Kim, D, Kim, S, Kimokoti, Rw, Kinfu, Y, Kinge, Jm, Kissela, Bm, Kivipelto MKnibbs, L, Knudsen, Ak, Kokubo, Y, Kosen, S, Kramer, A, Kravchenko, M, Krishnamurthi, Rv, Krishnaswami, S, Kuate Defo, B, Kucuk Bicer, B, Kuipers EJKulkarni VS, Kumar, K, Kumar, Ga, Kwan, Gf, Lai, T, Lalloo, R, Lam, H, Lan, Q, Lansingh, Vc, Larson, H, Larsson, A, Lawrynowicz, Ae, Leasher, Jl, Lee, Jt, Leigh, J, Leung, R, Levi, M, Li, B, Li, Y, Liang, J, Lim, S, Lin, Hh, Lind, M, Lindsay, Mp, Lipshultz, Se, Liu, S, Lloyd, Bk, Lockett Ohno, S, Logroscino, G, Looker, Kj, Lopez, Ad, Lopez-Olmedo, N, Lortet-Tieulent, J, Lotufo, Pa, Low, N, Lucas, Rm, Lunevicius, R, Lyons, Ra, Ma, J, Ma, S, Mackay MTMajdan, M, Malekzadeh, R, Mapoma, Cc, Marcenes, W, March, Lm, Margono, C, Marks, Gb, Marzan, Mb, Masci, Jr, Mason-Jones, Aj, Matzopoulos RGMayosi BM, Mazorodze, Tt, Mcgill, Nw, Mcgrath, Jj, Mckee, M, Mclain, A, Mcmahon, Bj, Meaney, Pa, Mehndiratta, Mm, Mejia-Rodriguez, F, Mekonnen, W, Melaku, Ya, Meltzer, M, Memish, Za, Mensah, G, Meretoja, A, Mhimbira, Fa, Micha, R, Miller, Tr, Mills, Ej, Mitchell, Pb, Mock, Cn, Moffitt TEMohamed Ibrahim, N, Mohammad, Ka, Mokdad, Ah, Mola, Gl, Monasta, L, Montico, M, Montine, Tj, Moore, Ar, Moran, Ae, Morawska, L, Mori RMoschandreas, J, Moturi, Wn, Moyer, M, Mozaffarian, D, Mueller, Uo, Mukaigawara, M, Murdoch, Me, Murray, J, Murthy, K, Naghavi, P, Nahas ZNaheed, A, Naidoo, K, Naldi, L, Nand, D, Nangia, V, Narayan, Km, Nash, D, Nejjari, C, Neupane, Sp, Newman, Lm, Newton, Cr, Ng, M, Ngalesoni FNNhung NT, Nisar, Mi, Nolte, S, Norheim, Of, Norman, Re, Norrving, B, Nyakarahuka, L, Oh, Ih, Ohkubo, T, Omer, Sb, Opio, Jn, Ortiz, A, Pandian JDPanelo CI, Papachristou, C, Park, Ek, Parry, Cd, Caicedo, Aj, Patten, Sb, Paul, Vk, Pavlin, Bi, Pearce, N, Pedraza, L, Pellegrini, Ca, Pereira, Dm, Perez-Ruiz, Fp, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, Cb, Petzold, M, Phillips, Mr, Phillips, D, Phillips, B, Piel, Fb, Plass, D, Poenaru, D, Polanczyk GVPolinder, S, Pope, Ca, Popova, S, Poulton, Rg, Pourmalek, F, Prabhakaran, D, Prasad, Nm, Qato, D, Quistberg, Da, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, Su, Raju, M, Rakovac, I, Rana, Sm, Razavi, H, Refaat, A, Rehm, J, Remuzzi, G, Resnikoff, S, Ribeiro, Al, Riccio, Pm, Richardson, L, Richardus, Jh, Riederer, Am, Robinson, M, Roca, A, Rodriguez, A, Rojas-Rueda, D, Ronfani, L, Rothenbacher, D, Roy, N, Ruhago, Gm, Sabin, N, Sacco, Rl, Ksoreide, K, Saha, S, Sahathevan, R, Sahraian, Ma, Sampson, U, Sanabria, Jr, Sanchez-Riera, L, Santos, I, Satpathy, M, Saunders, Je, Sawhney, M, Saylan MIScarborough, P, Schoettker, B, Schneider, Ij, Schwebel, Dc, Scott, Jg, Seedat, S, Sepanlou, Sg, Serdar, B, Servan-Mori, Ee, Shackelford, K, Shaheen AShahraz, S, Shamah Levy, T, Shangguan, S, She, J, Sheikhbahaei, S, Shepard, D, Shi, P, Shibuya, K, Shinohara, Y, Shiri, R, Shishani, K, Shiue, I, Shrime, Mg, Sigfusdottir, Id, Silberberg, Dh, Simard, Ep, Sindi, S, Singh, Ja, Singh, L, Skirbekk, V, Sliwa, K, Soljak, M, Soneji, S, Soshnikov, S, Speyer PSposato LA, Sreeramareddy, Ct, Stoeckl, H, Stathopoulou, Vk, Steckling, N, Stein, Mb, Stein, Dj, Steiner, Tj, Stewart, A, Stork, E, Stovner LJStroumpoulis, K, Sturua, L, Sunguya, Bf, Swaroop, M, Sykes, Bl, Tabb, Km, Takahashi, K, Tan, F, Tandon, N, Tanne, D, Tanner, M, Tavakkoli, M, Taylor, Hr, Te Ao BJ, Temesgen, Am, Ten Have, M, Tenkorang, Ey, Terkawi, A, Theadom, Am, Thomas, E, Thorne-Lyman, Al, Thrift, Ag, Tleyjeh, Im, Tonelli, M, Topouzis, F, Towbin, Ja, Toyoshima, H, Traebert, J, Tran, Bx, Trasande, L, Trillini, M, Truelsen, T, Trujillo, U, Tsilimbaris, M, Tuzcu, Em, Ukwaja KNUndurraga EA, Uzun, Sb, van Brakel WH, van de Vijver, S, Van Dingenen, R, van Gool CH, Varakin, Yy, Vasankari, Tj, Vavilala, M, Veerman LJVelasquez-Melendez, G, Venketasubramanian, N, Vijayakumar, L, Villalpando, S, Violante, F, Vlassov, Vv, Waller, S, Wallin, Mt, Wan, X, Wang, L, Wang, J, Wang, Y, Warouw, T, Weichenthal, S, Weiderpass, E, Weintraub, Rg, Werdecker, A, Wessells, Kr, Westerman, R, Wilkinson, Jd, Williams HCWilliams TN, Woldeyohannes, Sm, Wolfe, Cd, Wong, Jq, Wong, H, Woolf, Ad, Wright, Jl, Wurtz, B, Xu, G, Yang, G, Yano, Y, Yenesew, Ma, Yentur GKYip, P, Yonemoto, N, Yoon, Sj, Younis, M, Yu, C, Kim, Ky, Zaki Mel, S, Zhang, Y, Zhao, Z, Zhao, Y, Zhu, J, Zonies, D, Zunt, Jr, Salomon, Ja, Murray, Cj., Vos, Theo, Barber, Ryan M., Bell, Brad, Bertozzi-Villa, Amelia, Biryukov, Stan, Bolliger, Ian, Charlson, Fiona, Davis, Adrian, Degenhardt, Louisa, Dicker, Daniel, Duan, Leilei, Erskine, Holly, Feigin, Valery L., Ferrari, Alize J., Fitzmaurice, Christina, Fleming, Thoma, Graetz, Nichola, Guinovart, Caterina, Haagsma, Juanita, Hansen, Gillian M., Hanson, Sarah Wulf, Heuton, Kyle R., Higashi, Hideki, Kassebaum, Nichola, Kyu, Hmwe, Laurie, Evan, Liang, Xiofeng, Lofgren, Katherine, Lozano, Rafael, Macintyre, Michael F., Moradi-Lakeh, Maziar, Naghavi, Mohsen, Nguyen, Grant, Odell, Shaun, Ortblad, Katrina, Roberts, David Allen, Roth, Gregory A., Sandar, Logan, Serina, Peter T., Stanaway, Jeffrey D., Steiner, Caitlyn, Thomas, Bernadette, Vollset, Stein Emil, Whiteford, Harvey, Wolock, Timothy M., Ye, Pengpeng, Zhou, Maigeng, Ãvila, Marco A., Aasvang, Gunn Marit, Abbafati, Cristiana, Ozgoren, Ayse Abbasoglu, Abd-Allah, Foad, Aziz, Muna I. Abdel, Abera, Semaw F., Aboyans, Victor, Abraham, Jerry P., Abraham, Biju, Abubakar, Ibrahim, Abu-Raddad, Laith J., Abu-Rmeileh, Niveen M.E., Aburto, Tania C., Achoki, Tom, Ackerman, Ilana N., Adelekan, Ademola, Ademi, Zanfina, Adou, Arsène K., Adsuar, Josef C., Arnlov, Johan, Agardh, Emilie E., Al Khabouri, Mazin J., Alam, Sayed Saidul, Alasfoor, Deena, Albittar, Mohammed I., Alegretti, Miguel A., Aleman, Alicia V., Alemu, Zewdie A., Alfonso-Cristancho, Rafael, Alhabib, Samia, Ali, Raghib, Alla, Francoi, Allebeck, Peter, Allen, Peter J., Almazroa, Mohammad Abdulaziz, Alsharif, Ubai, Alvarez, Elena, Alvis-Guzman, Nelson, Ameli, Omid, Amini, Heresh, Ammar, Walid, Anderson, Benjamin O., Anderson, H. Ro, Antonio, Carl Abelardo T., Anwari, Palwasha, Apfel, Henry, Arsenijevic, Valentain S. Arsic, Artaman, Al, Asghar, Rana J., Assadi, Reza, Atkins, Lydia S., Atkinson, Charle, Badawi, Alaa, Bahit, Maria C., Bakfalouni, Talal, Balakrishnan, Kalpana, Balalla, Shivanthi, Banerjee, Amitava, Barker-Collo, Suzanne L., Barquera, Simon, Barregard, Lar, Barrero, Lope H., Basu, Sanjay, Basu, Arindam, Baxter, Amanda, Beardsley, Justin, Bedi, Neeraj, Beghi, Ettore, Bekele, Tolesa, Bell, Michelle L., Benjet, Corina, Bennett, Derrick A., Bensenor, Isabela M., Benzian, Habib, Bernabe, Eduardo, Beyene, Tariku J., Bhala, Neeraj, Bhalla, Ashish, Bhutta, Zulfiqar, Bienhoff, Kelly, Bikbov, Bori, Abdulhak, Aref Bin, Blore, Jed D., Blyth, Fiona M., Bohensky, Megan A., Basara, Berrak Bora, Borges, Guilherme, Bornstein, Natan M., Bose, Dipan, Boufous, Soufiane, Bourne, Rupert R., Boyers, Lindsay N., Brainin, Michael, Brauer, Michael, Brayne, Carol E.G., Brazinova, Alexandra, Breitborde, Nicholas J.K., Brenner, Hermann, Briggs, Adam D.M., Brooks, Peter M., Brown, Jonathan, Brugha, Traolach S., Buchbinder, Rachelle, Buckle, Geoffrey C., Bukhman, Gene, Bulloch, Andrew G., Burch, Michael, Burnett, Richard, Cardenas, Rosario, Cabral, Norberto L., Campos-Nonato, Ismael R., Campuzano, Julio C., Carapetis, Jonathan R., Carpenter, David O., Caso, Valeria, Castaneda-Orjuela, Carlos A., Catala-Lopez, Ferran, Chadha, Vineet K., Chang, Jung-Chen, Chen, Honglei, Chen, Wanqing, Chiang, Peggy P., Chimed-Ochir, Odgerel, Chowdhury, Rajiv, Christensen, Hanne, Christophi, Costas A., Chugh, Sumeet S., Cirillo, Massimo, Coggeshall, Megan, Cohen, Aaron, Colistro, Valentina, Colquhoun, Samantha M., Contreras, Alejandra G., Cooper, Leslie T., Cooper, Cyru, Cooperrider, Kimberly, Coresh, Josef, Cortinovis, Monica, Criqui, Michael H., Crump, John A., Cuevas-Nasu, Lucia, Dandona, Rakhi, Dandona, Lalit, Dansereau, Emily, Dantes, Hector G., Dargan, Paul I., Davey, Gail, Davitoiu, Dragos V., Dayama, Anand, De La Cruz-Gongora, Vanessa, De La Vega, Shelley F., De Leo, Diego, Del Pozo-Cruz, Borja, Dellavalle, Robert P., Deribe, Kebede, Derrett, Sarah, Des Jarlais, Don C., Dessalegn, Muluken, Deveber, Gabrielle A., Dharmaratne, Samath D., Diaz-Torne, Cesar, Ding, Eric L., Dokova, Klara, Dorsey, E.R., Driscoll, Tim R., Duber, Herbert, Durrani, Adnan M., Edmond, Karen M., Ellenbogen, Richard G., Endres, Matthia, Ermakov, Sergey P., Eshrati, Babak, Esteghamati, Alireza, Estep, Kara, Fahimi, Saman, Farzadfar, Farshad, Fay, Derek F.J., Felson, David T., Fereshtehnejad, Seyed-Mohammad, Fernandes, Jefferson G., Ferri, Cluesa P., Flaxman, Abraham, Foigt, Nataliya, Foreman, Kyle J., Fowkes, F Gerry R., Franklin, Richard C., Furst, Thoma, Futran, Neal D., Gabbe, Belinda J., Gankpe, Fortune G., Garcia-Guerra, Francisco A., Geleijnse, Johanna M., Gessner, Bradford D., Gibney, Katherine B., Gillum, Richard F., Ginawi, Ibrahim A., Giroud, Maurice, Giussani, Giorgia, Goenka, Shifalika, Goginashvili, Ketevan, Gona, Philimon, De Cosio, Teresita Gonzalez, Gosselin, Richard A., Gotay, Carolyn C., Goto, Atsushi, Gouda, Hebe N., Guerrant, Richard L., Gugnani, Harish C., Gunnell, David, Gupta, Rajeev, Gupta, Rahul, Gutierrez, Reyna A., Hafezi-Nejad, Nima, Hagan, Holly, Halasa, Yara, Hamadeh, Randah R., Hamavid, Hannah, Hammami, Mouhanad, Hankey, Graeme J., Hao, Yuantao, Harb, Hilda L., Haro, Josep Maria, Havmoeller, Rasmu, Hay, Roderick J., Hay, Simon, Hedayati, Mohammad T., Pi, Ileana B. Heredia, Heydarpour, Pouria, Hijar, Martha, Hoek, Hans W., Hoffman, Howard J., Hornberger, John C., Hosgood, H. Dean, Hossain, Mazeda, Hotez, Peter J., Hoy, Damian G., Hsairi, Mohamed, Hu, Howard, Hu, Guoqing, Huang, John J., Huang, Cheng, Huiart, Laetitia, Husseini, Abdullatif, Iannarone, Marissa, Iburg, Kim M., Innos, Kaire, Inoue, Manami, Jacobsen, Kathryn H., Jassal, Simerjot K., Jeemon, Panniyammakal, Jensen, Paul N., Jha, Vivekanand, Jiang, Guohong, Jiang, Ying, Jonas, Jost B., Joseph, Jonathan, Juel, Knud, Kan, Haidong, Karch, Andre, Karimkhani, Chante, Karthikeyan, Ganesan, Katz, Ronit, Kaul, Anil, Kawakami, Norito, Kazi, Dhruv S., Kemp, Andrew H., Kengne, Andre P., Khader, Yousef S., Khalifa, Shams Eldin A.H., Khan, Ejaz A., Khan, Gulfaraz, Khang, Young-Ho, Khonelidze, Irma, Kieling, Christian, Kim, Daniel, Kim, Sungroul, Kimokoti, Ruth W., Kinfu, Yohanne, Kinge, Jonas M., Kissela, Brett M., Kivipelto, Miia, Knibbs, Luke, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kosen, Soewarta, Kramer, Alexander, Kravchenko, Michael, Krishnamurthi, Rita V., Krishnaswami, Sanjay, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kuipers, Ernst J., Kulkarni, Veena S., Kumar, Kaushalendra, Kumar, G Anil, Kwan, Gene F., Lai, Taavi, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lansingh, Van C., Larson, Heidi, Larsson, Ander, Lawrynowicz, Alicia E.B., Leasher, Janet L., Lee, Jong-Tae, Leigh, Jame, Leung, Ricky, Levi, Miriam, Li, Bin, Li, Yichong, Li, Yongmei, Liang, Juan, Lim, Stephen, Lin, Hsien-Ho, Lind, Margaret, Lindsay, M Patrice, Lipshultz, Steven E., Liu, Shiwei, Lloyd, Belinda K., Ohno, Summer Lockett, Logroscino, Giancarlo, Looker, Katharine J., Lopez, Alan D., Lopez-Olmedo, Nancy, Lortet-Tieulent, Joannie, Lotufo, Paulo A., Low, Nicola, Lucas, Robyn M., Lunevicius, Raimunda, Lyons, Ronan A., Ma, Jixiang, Ma, Stefan, Mackay, Mark T., Majdan, Marek, Malekzadeh, Reza, Mapoma, Christopher C., Marcenes, Wagner, March, Lyn M., Margono, Chri, Marks, Guy B., Marzan, Melvin B., Masci, Joseph R., Mason-Jones, Amanda J., Matzopoulos, Richard G., Mayosi, Bongani M., Mazorodze, Tasara T., Mcgill, Neil W., Mcgrath, John J., Mckee, Martin, Mclain, Abby, Mcmahon, Brian J., Meaney, Peter A., Mehndiratta, Man Mohan, Mejia-Rodriguez, Fabiola, Mekonnen, Wubegzier, Melaku, Yohannes A., Meltzer, Michele, Memish, Ziad A., Mensah, George, Meretoja, Atte, Mhimbira, Francis A., Micha, Renata, Miller, Ted R., Mills, Edward J., Mitchell, Philip B., Mock, Charles N., Moffitt, Terrie E., Ibrahim, Norlinah Mohamed, Mohammad, Karzan A., Mokdad, Ali H., Mola, Glen L., Monasta, Lorenzo, Montico, Marcella, Montine, Thomas J., Moore, Ami R., Moran, Andrew E., Morawska, Lidia, Mori, Rintaro, Moschandreas, Joanna, Moturi, Wilkister N., Moyer, Madeline, Mozaffarian, Dariush, Mueller, Ulrich O., Mukaigawara, Mitsuru, Murdoch, Michele E., Murray, Joseph, Murthy, Kinnari S., Naghavi, Paria, Nahas, Ziad, Naheed, Aliya, Naidoo, Kovin S., Naldi, Luigi, Nand, Devina, Nangia, Vinay, Narayan, K.M. Venkat, Nash, Deni, Nejjari, Chakib, Neupane, Sudan P., Newman, Lori M., Newton, Charles R., Ng, Marie, Ngalesoni, Frida N., Nhung, Nguyen T., Nisar, Muhammad I., Nolte, Sandra, Norheim, Ole F., Norman, Rosana E., Norrving, Bo, Nyakarahuka, Luke, Oh, In Hwan, Ohkubo, Takayoshi, Omer, Saad B., Opio, John Nelson, Ortiz, Alberto, Pandian, Jeyaraj D., Panelo, Carlo Irwin A., Papachristou, Christina, Park, Eun-Kee, Parry, Charles D., Caicedo, Angel J. Paternina, Patten, Scott B., Paul, Vinod K., Pavlin, Boris I., Pearce, Neil, Pedraza, Lilia S., Pellegrini, Carlos A., Pereira, David M., Perez-Ruiz, Fernando P., Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Peterson, Carrie B., Petzold, Max, Phillips, Michael R., Phillips, David, Phillips, Bryan, Piel, Frederic B., Plass, Dietrich, Poenaru, Dan, Polanczyk, Guilherme V., Polinder, Suzanne, Pope, C.A., Popova, Svetlana, Poulton, Richie G., Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Noela M., Qato, Dima, Quistberg, D.A., Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Vafa, Rahman, Sajjad Ur, Raju, Murugesan, Rakovac, Ivo, Rana, Saleem M., Razavi, Homie, Refaat, Amany, Rehm, Jurgen, Remuzzi, Giuseppe, Resnikoff, Serge, Ribeiro, Antonio L., Riccio, Patricia M., Richardson, Lee, Richardus, Jan Hendrik, Riederer, Anne M., Robinson, Margot, Roca, Anna, Rodriguez, Alina, Rojas-Rueda, David, Ronfani, Luca, Rothenbacher, Dietrich, Roy, Nobhojit, Ruhago, George M., Sabin, Nsanzimana, Sacco, Ralph L., Ksoreide, Kjetil, Saha, Sukanta, Sahathevan, Ramesh, Sahraian, Mohammad Ali, Sampson, Uchechukwu, Sanabria, Juan R., Sanchez-Riera, Lidia, Santos, Itamar S., Satpathy, Maheswar, Saunders, James E., Sawhney, Monika, Saylan, Mete I., Scarborough, Peter, Schoettker, Ben, Schneider, Ione J.C., Schwebel, David C., Scott, James G., Seedat, Soraya, Sepanlou, Sadaf G., Serdar, Berrin, Servan-Mori, Edson E., Shackelford, Katya, Shaheen, Amira, Shahraz, Saeid, Levy, Teresa Shamah, Shangguan, Siyi, She, Jun, Sheikhbahaei, Sara, Shepard, Donald S., Shi, Peilin, Shibuya, Kenji, Shinohara, Yukito, Shiri, Rahman, Shishani, Kawkab, Shiue, Ivy, Shrime, Mark G., Sigfusdottir, Inga D., Silberberg, Donald H., Simard, Edgar P., Sindi, Shireen, Singh, Jasvinder A., Singh, Lavanya, Skirbekk, Vegard, Sliwa, Karen, Soljak, Michael, Soneji, Samir, Soshnikov, Sergey S., Speyer, Peter, Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Stoeckl, Heidi, Stathopoulou, Vasiliki Kalliopi, Steckling, Nadine, Stein, Murray B., Stein, Dan J., Steiner, Timothy J., Stewart, Andrea, Stork, Eden, Stovner, Lars J., Stroumpoulis, Konstantino, Sturua, Lela, Sunguya, Bruno F., Swaroop, Mamta, Sykes, Bryan L., Tabb, Karen M., Takahashi, Ken, Tan, Feng, Tandon, Nikhil, Tanne, David, Tanner, Marcel, Tavakkoli, Mohammad, Taylor, Hugh R., Te Ao, Braden J., Temesgen, Awoke Misganaw, Have, Margreet Ten, Tenkorang, Eric Yeboah, Terkawi, Abdullah Sulieman, Theadom, Alice M., Thomas, Elissa, Thorne-Lyman, Andrew L., Thrift, Amanda G., Tleyjeh, Imad M., Tonelli, Marcello, Topouzis, Foti, Towbin, Jeffrey A., Toyoshima, Hideaki, Traebert, Jefferson, Tran, Bach X., Trasande, Leonardo, Trillini, Matia, Truelsen, Thoma, Trujillo, Ulise, Tsilimbaris, Miltiadi, Tuzcu, Emin M., Ukwaja, Kingsley N., Undurraga, Eduardo A., Uzun, Selen B., Van Brakel, Wim H., Van De Vijver, Steven, Dingenen, Rita Van, Van Gool, Coen H., Varakin, Yuri Y., Vasankari, Tommi J., Vavilala, Monica S., Veerman, Lennert J., Velasquez-Melendez, Gustavo, Venketasubramanian, Narayanaswamy, Vijayakumar, Lakshmi, Villalpando, Salvador, Violante, Francesco S., Vlassov, Vasiliy V., Waller, Stephen, Wallin, Mitchell T., Wan, Xia, Wang, Linhong, Wang, Jianli, Wang, Yanping, Warouw, Tati S., Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G., Werdecker, Andrea, Wessells, K. Ryan, Westerman, Ronny, Wilkinson, James D., Williams, Hywel C., Williams, Thomas N., Woldeyohannes, Solomon M., Wolfe, Charles D.A., Wong, John Q., Wong, Haidong, Woolf, Anthony D., Wright, Jonathan L., Wurtz, Brittany, Xu, Gelin, Yang, Gonghuan, Yano, Yuichiro, Yenesew, Muluken A., Yentur, Gokalp K., Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Younis, Mustafa, Yu, Chuanhua, Kim, Kim Yun, Zaki, Maysaa El Sayed, Zhang, Yong, Zhao, Zheng, Zhao, Yong, Zhu, Jun, Zonies, David, Zunt, Joseph R., Salomon, Joshua A., Murray, Christopher J.L., Cell biology, Gastroenterology & Hepatology, Epidemiology, Health Technology Assessment (HTA), and Public Health
Subjects: Male, Gerontology, Nutrition and Disease, Epidemiology, years lived with disability, Global burden of disease, acute and chronic diseases, countries, Prevalence, Disease, Global Health, Medical and Health Sciences, Conduct disorder, Otitis-media, Cost of Illness, Residence Characteristics, Voeding en Ziekte, 80 and over, Global health, 2.2 Factors relating to the physical environment, 2.1 Biological and endogenous factors, countries, Aetiology, Child, Aged, 80 and over, Medicine(all), education.field_of_study, ATTENTION-DEFICIT/HYPERACTIVITY DISORDER, Incidence, Mortality rate, Incidence (epidemiology), Pain Research, Neglected Diseases, Alcohol dependence, General Medicine, Middle Aged, Global burden of disease, Global Burden of Disease Study 2013 Collaborators, Mental Health, Infectious Diseases, Attention deficit/Hyperactivity disorder, Burden of Illness, Child, Preschool, Acute Disease, Female, Life Sciences & Biomedicine, Adult, medicine.medical_specialty, Adolescent, GBD 2013, Population, acute and chronic diseases, Young Adult, Mental-disorders, Age Distribution, Medicine, General & Internal, Weights, General & Internal Medicine, medicine, Humans, Life Science, Disabled Persons, Sex Distribution, Preschool, education, Developing Countries, VLAG, Aged, Science & Technology, business.industry, Developed Countries, Cutaneous Leishmaniasis, Infant, Newborn, Infant, Health outcomes, Newborn, medicine.disease, Comorbidity, Brain Disorders, years lived with disability, Good Health and Well Being, Disease, injury, incidence, prevalence, YLDs, GBD 2010, Chronic Disease, Wounds and Injuries, business, 2.4 Surveillance and distribution, Iron-deficiency, Demography
Abstract: Summary Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries. Funding Bill & Melinda Gates Foundation. Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries. Funding Bill & Melinda Gates Foundation.
Published: 2015
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14. Urine creatinine-based estimates of fat-free mass in community-dwelling older persons: The Rancho Bernardo study

Author: Jassal, SK, Wassel, CL, Laughlin, GA, Barrett-Connor, E, Rifkin, DE, and Ix, JH
Subjects: human activities
Abstract: © 2015 .Objectives: To determine whether a previously developed and externally validated equation using common variables (demographics and weight) that are important determinants of muscle mass to estimate 24-hour urine creatinine excretion rate (eCER) is associated with muscle mass and whether spot urine creatinine (UCr) provides similar estimates of muscle mass. Design: Observational cross-sectional cohort study. Setting: The Rancho Bernardo Study, San Diego, California. Subjects: A total of 1,371 Caucasian, middle class, community-dwelling older adults. Intervention: Morning spot UCr and fat-free mass (FFM) by dual-energy x-ray absorptiometry were measured. eCER was calculated: eCER (mg/day)=879.89+12.51 × weight (kilogram) - 6.19 × age+34.51 if black - 379.42 if female. Pearson correlation coefficients and linear regression were used to determine strengths of association of eCER and spot UCr with FFM. Results: Mean age was 70years, and 58% were women. eCER was strongly correlated with FFM (. r=0.95, P
Published: 2015
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15. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without hypertension: a meta-analysis

Author: Mahmoodi, Bk, Matsushita, K., Woodward, M., Blankestijn, Pj, Cirillo, Massimo, Ohkubo, T., Rossing, P., Sarnak, Mj, Stengel, B., Yamagishi, K., Yamashita, K., Zhang, L., Coresh, J., PE de Jong, Wright, BC Astor for the Chronic Kidney Disease Prognosis C. o. n. s. o. r. t. i. u. m. Investigators/Collaborators: J., Appel, L., Greene, T., Astor, Bc, Chalmers, J., Macmahon, S., Arima, H., Yatsuya, H., Toyoshima, H., Tamakoshi, K., Sang, Y., Atkins, R. C., Polkinghorne, Kr, Chadban, S., Shankar, A., Klein, R., Bek, Klein, Lee, Ke, Wang, H., Wang, F., Zuo, L., Levin, A., Djurdjev, O., Tonelli, M., Sacks, Fm, Curhan, Gc, Shlipak, M., Peralta, C., Katz, R., Fried, L., Iso, H., Kitamura, A., Ohira, T., Jafar, Th, Islam, M., Hatcher, J., Poulter, N., Chaturvedi, N., Landray, M. J., Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D., Brenner, H., Muller, H., Schottker, B., Fox, Cs, Hwang, S. J., Meigs, Jb, Perkins, Rm, Fluck, N., Clark, Le, Prescott, Gj, Marks, A., Black, C., Hallan, S., Aasarod, K., Oien, Cm, Radtke, M., Irie, F., Sairenchi, T., Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S., Chen, S. C., Lee, Bj, Wetzels, Jf, AD van Zuilen, Sarnak, M., Levey, As, Menon, V., Kramer, Hj, IH de Boer, Kronenberg, F., Kollerits, B., Roderick, E. R. i. t. z. P., Nitsch, D., Fletcher, A., Bulpitt, C., Ishani, A., Neaton, Jd, Froissart, M., Metzger, M., Haymann, J. P., Houillier, P., Flamant, M., Metoki, H., Nakayama, M., Kikuya, M., Imai, Y., Iseki, K., Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H., Jassal, Sk, Barrett Connor, E., Bergstrom, J., HJ Lambers Heerspink, Brenner, Be, de Zeeuw, D., Warnock, Dg, Muntner, P., Judd, S., Mcclellan, W., Jee, Sh, Kimm, H., Jo, J., Mok, Y., Parving, H. H., Tangri, N., Naimark, D., Wen, C. P., Wen, S. F., Tsao, C. K., Tsai, M. K., Arnlov, J., Lannfelt, L., Larsson, A., Bilo, Hj, Joosten, H., Kleefstra, N., Groenier, Kh, Steering Committee: BC Astor, I. D. r. i. o. n., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M. W. o. o. d. w. a. r. d., Grams, M., Camarata, L., Hui, X., Seltzer, J., Winegrad, H., Mahmoodi, Bk, Matsushita, K, Woodward, M, Blankestijn, Pj, Cirillo, M, Ohkubo, T, Rossing, P, Sarnak, Mj, Stengel, B, Yamagishi, K, Yamashita, K, Zhang, L, Coresh, J, de Jong, Pe, Investigators/Collaborators: J Wright, BC Astor for the Chronic Kidney Disease Prognosis Consortium., Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Arima, H, Yatsuya, H, Toyoshima, H, Tamakoshi, K, Sang, Y, C Atkins, R, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Wang, H, Wang, F, Zuo, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, J Landray, M, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Muller, H, Schottker, B, Fox, C, Hwang, S-J, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Hallan, S, Aasarod, K, Oien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, S-C, Lee, Bj, Wetzels, Jf, van Zuilen, Ad, Sarnak, M, Levey, A, Menon, V, Kramer, Hj, de Boer, Ih, Kronenberg, F, Kollerits, B, P Roderick, E Ritz., Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Lambers Heerspink, Hj, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Parving, H-H, Tangri, N, Naimark, D, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Arnlov, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Steering Committee: BC Astor, I Drion., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M Woodward., Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad., H
Subjects: Male, medicine.medical_specialty, hypertension, Blood Pressure, BLOOD-PRESSURE, GLOMERULAR-FILTRATION-RATE, Article, albuminuria, DIABETIC-NEPHROPATHY, End stage renal disease, CKD-PC Consortium, Risk Factors, Cause of Death, Internal medicine, REVERSE EPIDEMIOLOGY, eGFR, EQUATION, medicine, Humans, Intensive care medicine, Aged, Proportional Hazards Models, ALL-CAUSE MORTALITY, Renal disorder [IGMD 9], Aged, 80 and over, end-stage renal disease, business.industry, General Medicine, Middle Aged, medicine.disease, mortality, RISK POPULATION COHORTS, PREVALENCE, Chronic Disease, COLLABORATIVE METAANALYSIS, Kidney Failure, Chronic, Female, HIGHER ALBUMINURIA, business, Glomerular Filtration Rate, Kidney disease
Abstract: Item does not contain fulltext BACKGROUND: Hypertension is the most prevalent comorbidity in individuals with chronic kidney disease. However, whether the association of the kidney disease measures, estimated glomerular filtration rate (eGFR) and albuminuria, with mortality or end-stage renal disease (ESRD) differs by hypertensive status is unknown. METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and ESRD associated with eGFR and albuminuria in individuals with and without hypertension. FINDINGS: We analysed data for 45 cohorts (25 general population, seven high-risk, and 13 chronic kidney disease) with 1,127,656 participants, 364,344 of whom had hypertension. Low eGFR and high albuminuria were associated with mortality irrespective of hypertensive status in the general population and high-risk cohorts. All-cause mortality risk was 1.1-1.2 times higher in individuals with hypertension than in those without hypertension at preserved eGFR. A steeper relative risk gradient in individuals without hypertension than in those with hypertension at eGFR range 45-75 mL/min per 1.73 m(2) led to much the same mortality risk at lower eGFR. With a reference eGFR of 95 mL/min per 1.73 m(2) in each group to explicitly assess interaction, adjusted HR for all-cause mortality at eGFR 45 mL/min per 1.73 m(2) was 1.77 (95% CI 1.57-1.99) in individuals without hypertension versus 1.24 (1.11-1.39) in those with hypertension (p for overall interaction=0.0003). Similarly, for albumin-creatinine ratio of 300 mg/g (vs 5 mg/g), HR was 2.30 (1.98-2.68) in individuals without hypertension versus 2.08 (1.84-2.35) in those with hypertension (p for overall interaction=0.019). We recorded much the same results for cardiovascular mortality. The associations of eGFR and albuminuria with ESRD, however, did not differ by hypertensive status. Results for chronic kidney disease cohorts were similar to those for general and high-risk population cohorts. INTERPRETATION: Chronic kidney disease should be regarded as at least an equally relevant risk factor for mortality and ESRD in individuals without hypertension as it is in those with hypertension. FUNDING: US National Kidney Foundation.
Published: 2012

16. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis

Author: Chronic Kidney Disease Prognosis Consortium, Matsushita, K, van der Velde, M, Astor, Bc, Woodward, M, Levey, As, de Jong PE, Coresh, J, Investigators/Collaborators: Levey AS, Gansevoort R. T., El Nahas, M, Eckardt, Ku, Kasiske, Bl, Tonelli, M, Hemmelgarn, B, Wang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, Sj, Shankar, A, Klein, R, Klein, Be, Wang, H, Wang, F, Zhang, L, Liu, L, Shlipak, M, Sarnak, Mj, Katz, R, Fried, Lp, Jafar, T, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Rothenbacher, D, Brenner, H, Raum, E, Koenig, W, Fox, Cs, Hwang, Sj, Meigs, Jb, Cirillo, Massimo, Hallan, S, Lydersen, S, Holmen, J, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Gansevoort, Rt, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, Wm, Cushman, M, Howard, G, Mcclure, La, Jee, Sh, Kimm, H, Yun, Je, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Arnlöv, J, Auguste, P, Veldhuis, K, Camarata, L, Thomas, B, Manley, T., Chronic Kidney Disease Prognosis, Consortium, Matsushita, K, van der Velde, M, Astor, Bc, Woodward, M, Levey, A, de Jong, Pe, Coresh, J, Investigators/Collaborators: Levey AS, Gansevoort R. T., El Nahas, M, Eckardt, Ku, Kasiske, Bl, Tonelli, M, Hemmelgarn, B, Wang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, Sj, Shankar, A, Klein, R, Klein, Be, Wang, H, Wang, F, Zhang, L, Liu, L, Shlipak, M, Sarnak, Mj, Katz, R, Fried, Lp, Jafar, T, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Rothenbacher, D, Brenner, H, Raum, E, Koenig, W, Fox, C, Hwang, Sj, Meigs, Jb, Cirillo, Massimo, Hallan, S, Lydersen, S, Holmen, J, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Gansevoort, Rt, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, Wm, Cushman, M, Howard, G, Mcclure, La, Jee, Sh, Kimm, H, Yun, Je, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Arnlöv, J, Auguste, P, Veldhuis, K, Camarata, L, Thomas, B, Manley, T., Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)
Subjects: Male, CHRONIC KIDNEY-DISEASE, medicine.medical_specialty, Pathology, Population, Urology, Renal function, POOLED ANALYSIS, chemistry.chemical_compound, RISK-FACTOR, CYSTATIN-C, medicine, Risk of mortality, EQUATION, Albuminuria, Humans, Risk factor, Mortality, education, OLDER-ADULTS, Aged, Proportional Hazards Models, Creatinine, education.field_of_study, OUTCOMES, SERUM CREATININE, business.industry, Hazard ratio, General Medicine, Middle Aged, medicine.disease, PREVALENCE, RENAL-DISEASE, chemistry, Cardiovascular Diseases, Chronic Disease, Female, Kidney Diseases, medicine.symptom, business, Kidney disease, Glomerular Filtration Rate
Abstract: BACKGROUND: Substantial controversy surrounds the use of estimated glomerular filtration rate (eGFR) and albuminuria to define chronic kidney disease and assign its stages. We undertook a meta-analysis to assess the independent and combined associations of eGFR and albuminuria with mortality. METHODS: In this collaborative meta-analysis of general population cohorts, we pooled standardised data for all-cause and cardiovascular mortality from studies containing at least 1000 participants and baseline information about eGFR and urine albumin concentrations. Cox proportional hazards models were used to estimate hazard ratios (HRs) for all-cause and cardiovascular mortality associated with eGFR and albuminuria, adjusted for potential confounders. FINDINGS: The analysis included 105,872 participants (730,577 person-years) from 14 studies with urine albumin-to-creatinine ratio (ACR) measurements and 1,128,310 participants (4,732,110 person-years) from seven studies with urine protein dipstick measurements. In studies with ACR measurements, risk of mortality was unrelated to eGFR between 75 mL/min/1.73 m(2) and 105 mL/min/1.73 m(2) and increased at lower eGFRs. Compared with eGFR 95 mL/min/1.73 m(2), adjusted HRs for all-cause mortality were 1.18 (95% CI 1.05-1.32) for eGFR 60 mL/min/1.73 m(2), 1.57 (1.39-1.78) for 45 mL/min/1.73 m(2), and 3.14 (2.39-4.13) for 15 mL/min/1.73 m(2). ACR was associated with risk of mortality linearly on the log-log scale without threshold effects. Compared with ACR 0.6 mg/mmol, adjusted HRs for all-cause mortality were 1.20 (1.15-1.26) for ACR 1.1 mg/mmol, 1.63 (1.50-1.77) for 3.4 mg/mmol, and 2.22 (1.97-2.51) for 33.9 mg/mmol. eGFR and ACR were multiplicatively associated with risk of mortality without evidence of interaction. Similar findings were recorded for cardiovascular mortality and in studies with dipstick measurements. INTERPRETATION: eGFR less than 60 mL/min/1.73 m(2) and ACR 1.1 mg/mmol (10 mg/g) or more are independent predictors of mortality risk in the general population. This study provides quantitative data for use of both kidney measures for risk assessment and definition and staging of chronic kidney disease. FUNDING: Kidney Disease: Improving Global Outcomes (KDIGO), US National Kidney Foundation, and Dutch Kidney Foundation.
Published: 2010

17. Circulating 25-hydroxy-vitamin D and risk of cardiovascular disease: a meta-analysis of prospective studies.

Author: Wang L, Song Y, Manson JE, Pilz S, März W, Michaëlsson K, Lundqvist A, Jassal SK, Barrett-Connor E, Zhang C, Eaton CB, May HT, Anderson JL, Sesso HD, Wang, Lu, Song, Yiqing, Manson, Joann E, Pilz, Stefan, März, Winfried, and Michaëlsson, Karl
Abstract: Background: Vitamin D status has been linked to the risk of cardiovascular disease (CVD). However, the optimal 25-hydroxy-vitamin D (25[OH]-vitamin D) levels for potential cardiovascular health benefits remain unclear.Methods and Results: We searched MEDLINE and EMBASE from 1966 through February 2012 for prospective studies that assessed the association of 25(OH)-vitamin D concentrations with CVD risk. A total of 24 articles met our inclusion criteria, from which 19 independent studies with 6123 CVD cases in 65 994 participants were included for a meta-analysis. In a comparison of the lowest with the highest 25(OH)-vitamin D categories, the pooled relative risk was 1.52 (95% confidence interval, 1.30-1.77) for total CVD, 1.42 (95% confidence interval, 1.19-1.71) for CVD mortality, 1.38 (95% confidence interval, 1.21-1.57) for coronary heart disease, and 1.64 (95% confidence interval, 1.27-2.10) for stroke. These associations remained strong and significant when analyses were limited to studies that excluded participants with baseline CVD and were better controlled for season and confounding. We used a fractional polynomial spline regression analysis to assess the linearity of dose-response association between continuous 25(OH)-vitamin D and CVD risk. The CVD risk increased monotonically across decreasing 25(OH)-vitamin D below ≈60 nmol/L, with a relative risk of 1.03 (95% confidence interval, 1.00-1.06) per 25-nmol/L decrement in 25(OH)-vitamin D.Conclusions: This meta-analysis demonstrated a generally linear, inverse association between circulating 25(OH)-vitamin D ranging from 20 to 60 nmol/L and risk of CVD. Further research is needed to clarify the association of 25(OH)-vitamin D higher than 60 nmol/L with CVD risk and assess causality of the observed associations. [ABSTRACT FROM AUTHOR]
Published: 2012
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18. Sex differences in the association of Framingham Cardiac Risk Score with cognitive decline in community-dwelling elders without clinical heart disease.

Author: Laughlin GA, McEvoy LK, von Mühlen D, Daniels LB, Kritz-Silverstein D, Bergstrom J, Cummins K, Der-Martirosian C, Jassal SK, Barrett-Connor E, Laughlin, Gail A, McEvoy, Linda K, von Mühlen, Denise, Daniels, Lori B, Kritz-Silverstein, Donna, Bergstrom, Jaclyn, Cummins, Kevin, Der-Martirosian, Claudia, Jassal, Simerjot K, and Barrett-Connor, Elizabeth
Published: 2011
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19. A cross-sectional and 10-year prospective study of postmenopausal estrogen therapy and blood pressure, renal function, and albuminuria: the Rancho Bernardo Study.

Author: Fung MM, Poddar S, Bettencourt R, Jassal SK, Barrett-Connor E, Fung, Maple M, Poddar, Sameer, Bettencourt, Ricki, Jassal, Simerjot Kaur, and Barrett-Connor, Elizabeth
Published: 2011
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20. A prospective study of albuminuria and cognitive function in older adults: the Rancho Bernardo study.

Author: Jassal SK, Kritz-Silverstein D, and Barrett-Connor E
Abstract: Chronic kidney disease is a risk factor for cognitive impairment. Albuminuria is an early manifestation of chronic kidney disease and a marker of endothelial dysfunction and vascular risk. Results of prior studies of albuminuria and cognitive function are contradictory. The authors studied 1,345 community-dwelling women and men in southern California (mean age, 75 years) at a 1992-1996 research clinic visit, when urine albumin/creatinine ratio (ACR) was measured in spot morning urine and cognitive function was evaluated by using the Mini-Mental State Examination Trail-Making Test B, and category fluency test. An ACR of > or =30 mg/g was found in 17% of women and 15% of men in 1992-1996. Analysis of covariance was used to compare cognitive function score by categorical ACR. Between 1999 and 2002, 759 participants returned for repeat cognitive function testing. For men, but not women, baseline albuminuria, but not estimated glomerular filtration rate, was associated with reduced cognitive function at follow-up on all tests (P's < 0.05). An ACR of > or =30 mg/g was associated with greater annual decline in Mini-Mental State Examination and category fluency scores. Albuminuria may be an easily measured marker predicting future cognitive function decline. Results imply a common underlying mechanism affecting the renal and cerebral microvasculature. [ABSTRACT FROM AUTHOR]
Published: 2010
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21. Usefulness of microalbuminuria versus the metabolic syndrome as a predictor of cardiovascular disease in women and men>40 years of age (from the Rancho Bernardo Study).

Author: Jassal SK, Langenberg C, von Mühlen D, Bergstrom J, Barrett-Connor E, Jassal, Simerjot Kaur, Langenberg, Claudia, von Mühlen, Denise, Bergstrom, Jaclyn, and Barrett-Connor, Elizabeth
Abstract: To examine the sex-specific contributions of the metabolic syndrome and microalbuminuria to cardiovascular disease (CVD) and coronary heart disease (CHD) mortality in community-dwelling older adults, 869 women and 575 men aged 40 to 96 years (mean age 71) completed questionnaires, physical examinations, and fasting laboratory tests between 1992 and 1995. Participants were followed over an average of 8 years. CVD and CHD mortality were analyzed using Cox proportional hazards models. At baseline, 267 participants had the Adult Treatment Panel III metabolic syndrome, 151 had microalbuminuria, and 34 had both. During follow-up, there were 180 CVD deaths, including 83 CHD deaths. In women, microalbuminuria was associated with a twofold increased risk of CVD and CHD mortality (p
Published: 2008
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22. Serum uric acid levels improve prediction of incident type 2 diabetes in individuals with impaired fasting glucose: the Rancho Bernardo Study.

Author: Kramer CK, von Mühlen D, Jassal SK, Barrett-Connor E, Kramer, Caroline Kaercher, von Mühlen, Denise, Jassal, Simerjot Kaur, and Barrett-Connor, Elizabeth
Abstract: Objective: To determine whether serum uric acid predicts incident type 2 diabetes by glucose tolerance status in older community-dwelling adults.Research Design and Methods: Participants without diabetes at baseline were evaluated for incident type 2 diabetes 13 years later. Baseline glucose tolerance status was defined as normoglycemia, impaired fasting glucose, and impaired postchallenge glucose tolerance.Results: A total of 566 participants were included (mean age 63.3 +/- 8.6 years; 41% men). Regression models adjusted for age, sex, BMI, diuretic use, and estimated glomerular filtration rate showed that for each 1 mg/dl increment in uric acid levels, incident type 2 diabetes risk increased by approximately 60%. When analyses were stratified by glucose status, uric acid levels independently predicted incident type 2 diabetes among participants who had impaired fasting glucose (odds ratio 1.75, 95% CI 1.1-2.9, P = 0.02).Conclusions: Uric acid may be a useful predictor of type 2 diabetes in older adults with impaired fasting glucose. [ABSTRACT FROM AUTHOR]
Published: 2009
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23. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Author: Lozano, Rafael, Fullman, Nancy, Abate, Degu, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Monika, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banerjee, Amitava, Banoub, Joseph Adel Mattar, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Barthelemy, Celine M, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Battista, Robert J, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Berhe, Abadi Kidanemariam, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhansali, Anil, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Biehl, Molly H, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bitew, Helen, Bizuneh, Hailemichael, Bjertness, Espen, Bobasa, Eshetu Mulisa, Boufous, Soufiane, Bourne, Rupert, Bozorgmehr, Kayvan, Bragazzi, Nicola Luigi, Brainin, Michael, Brant, Luisa C, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Bukhman, Gene, Busse, Reinhard, Butt, Zahid 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Subjects: GENDER-DIFFERENCES, SUICIDE, Medicine (all), Burden of Disease Study 2017, SDG, CONSUMPTION, 11 Medical And Health Sciences, GBD, Sustainable Development Goals, PREVENTION, ALCOHOL-USE, CARDIOVASCULAR-DISEASE, SMOKING PREVALENCE, General & Internal Medicine, factors risk, Medicine and Health Sciences, Human medicine, CESSATION, PERSPECTIVE, TRANSITION
Abstract: Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Published: 2018

24. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: Stanaway, Jeffrey D., Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S., Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A., Adane, Akilew Awoke, Adebayo, Oladimeji M., Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O., Adib, Mina G., Admasie, Amha, Adsuar, Jose C., Afanvi, Kossivi Agbelenko, Afarideh, Mohsen, Agarwal, Gina, Aggarwal, Anju, Aghayan, Sargis Aghasi, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akbari, Mohammad Esmaeil, Akinyemiju, Tomi, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Mekhlafi, Hesham M., Alahdab, Fares, Alam, Khurshid, Alam, Samiah, Alam, Tahiya, Alashi, Alaa, Alavian, Seyed Moayed, Alene, Kefyalew Addis, Ali, Komal, Ali, Syed Mustafa, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A., Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansha, Mustafa Geleto, Antó, Josep M., Antonio, Carl Abelardo T., Anwari, Palwasha, Appiah, Lambert Tetteh, Appiah, Seth Christopher Yaw, Arabloo, Jalal, Aremu, Olatunde, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avokpaho, Euripide F.G.A., Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Ayuk, Tambe B., Azzopardi, Peter S., Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Ball, Kylie, Ballew, Shoshana H., Banach, Maciej, Banoub, Joseph Adel Mattar, Barac, Aleksandra, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H., Basu, Sanjay, Baune, Bernhard T., Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Bekru, Eyasu Tamru, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bensenor, Isabela M., Bergeron, Gilles, Berhane, Adugnaw, Bernabe, Eduardo, Bernstein, Robert S., Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhattarai, Suraj, Bhutta, Zulfiqar A., Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Bisanzio, Donal, Biswas, Tuhin, Bjørge, Tone, Blacker, Brigette F., Bleyer, Archie, Borschmann, Rohan, Bou-Orm, Ibrahim R., Boufous, Soufiane, Bourne, Rupert, Brady, Oliver J., Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J.K., Brenner, Hermann, Briko, Andrey Nikolaevich, Britton, Gabrielle, Brugha, Traolach, Buchbinder, Rachelle, Burnett, Richard T., Busse, Reinhard, Butt, Zahid A., Cahill, Leah E., Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R., Cárdenas, Rosario, Carreras, Giulia, Carrero, Juan J., Carvalho, Félix, Castañeda-Orjuela, Carlos A., Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Causey, Kate, Cercy, Kelly M., Cerin, Ester, Chaiah, Yazan, Chang, Hsing Yi, Chang, Jung Chen, Chang, Kai Lan, Charlson, Fiona J., Chattopadhyay, Aparajita, Chattu, Vijay Kumar, Chee, Miao Li, Cheng, Ching Yu, Chew, Adrienne, Chiang, Peggy Pei Chia, Chimed-Ochir, Odgerel, Chin, Ken Lee, Chitheer, Abdulaal, Choi, Jee Young J., Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J., Chung, Sheng Chia, Cicuttini, Flavia M., Cirillo, Massimo, Cohen, Aaron J., Collado-Mateo, Daniel, Cooper, Cyrus, Cooper, Owen R., Coresh, Josef, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa, Megan, Cousin, Ewerton, Criqui, Michael H., Cromwell, Elizabeth A., Cundiff, David K., Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dadi, Abel Fekadu, Damasceno, Albertino Antonio Moura, Dandona, Lalit, Dandona, Rakhi, Darby, Sarah C., Dargan, Paul I., Daryani, Ahmad, Das Gupta, Rajat, Das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davitoiu, Dragos Virgil, Davletov, Kairat, De la Cruz-Góngora, Vanessa, De La Hoz, Fernando Pio, De Leo, Diego, De Neve, Jan Walter, Degenhardt, Louisa, Deiparine, Selina, Dellavalle, Robert P., Demoz, Gebre Teklemariam, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Deshpande, Aniruddha, Des Jarlais, Don C., Dessie, Getenet Ayalew, Deveber, Gabrielle Aline, Dey, Subhojit, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Dinberu, Mesfin Tadese, Ding, Eric L., Diro, Helen Derara, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B., Duraes, Andre R., Ebert, Natalie, Ebrahimi, Hedyeh, Ebrahimpour, Soheil, Edvardsson, David, Effiong, Andem, Eggen, Anne Elise, El Bcheraoui, Charbel, El-Khatib, Ziad, Elyazar, Iqbal Rf, Enayati, Ahmadali, Endries, Aman Yesuf, Er, Benjamin, Erskine, Holly E., Eskandarieh, Sharareh, Esteghamati, Alireza, Estep, Kara, Fakhim, Hamed, Faramarzi, Mahbobeh, Fareed, Mohammad, Farid, Talha A., Farinha, Carla Sofia E.sá, Farioli, Andrea, Faro, Andre, Farvid, Maryam S., Farzaei, Mohammad Hosein, Fatima, Batool, Fay, Kairsten A., Fazaeli, Ali Akbar, Feigin, Valery L., Feigl, Andrea B., Fereshtehnejad, Seyed Mohammad, Fernandes, Eduarda, Fernandes, Joao C., Ferrara, Giannina, Ferrari, Alize J., Ferreira, Manuela L., Filip, Irina, Finger, Jonas David, Fischer, Florian, Foigt, Nataliya A., Foreman, Kyle J., Fukumoto, Takeshi, Fullman, Nancy, Fürst, Thomas, Furtado, João M., Futran, Neal D., Gall, Seana, Gallus, Silvano, Gamkrelidze, Amiran, Ganji, Morsaleh, Garcia-Basteiro, Alberto L., Gardner, William M., Gebre, Abadi Kahsu, Gebremedhin, Amanuel Tesfay, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijnse, Johanna M., Geramo, Yilma Chisha Dea, Gething, Peter W., Gezae, Kebede Embaye, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Ghimire, Mamata, Ghosh, Rakesh, Ghoshal, Aloke Gopal, Giampaoli, Simona, Gill, Paramjit Singh, Gill, Tiffany K., Gillum, Richard F., Ginawi, Ibrahim Abdelmageed, Giussani, Giorgia, Gnedovskaya, Elena V., Godwin, William W., Goli, Srinivas, Gómez-Dantés, Hector, Gona, Philimon N., Gopalani, Sameer Vali, Goulart, Alessandra C., Grada, Ayman, Grams, Morgan E., Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gutiérrez, Reyna Alma, Gutiérrez-Torres, Daniela S., Haagsma, Juanita A., Habtewold, Tesfa Dejenie, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hagos, 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Roth, Ga, Sahraian, Ma, Salomon, Ja, Salvi, Dd, Samy, Am, Sanchez-Niño, Md, Sánchez-Pimienta, Tg, Santomauro, Df, Santos, Jv, Santric Milicevic, Mm, Sao Jose, Bp, Sarker, Ar, Sawant, Ar, Schmidt, Mi, Schneider, Ijc, Schutte, Ae, Schwebel, Dc, Scott, Jg, Sepanlou, Sg, Serre, Ml, Shaheen, Aa, Shaikh, Ma, Shin, Mj, Shrime, Mg, Sibai, Am, Siddiqi, Tj, Sigfusdottir, Id, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Smith, Dl, Sobaih, Bh, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Starodubov, Vi, Stein, Dj, Stein, Mb, Stokes, Ma, Subart, Ml, Sufiyan, Mb, Sunguya, Bf, Sur, Pj, Sykes, Bl, Szoeke, Cei, Tadakamadla, Sk, Tassew, Sg, Tekalign, Tg, Tekelemedhin, Sw, Tekle, Mg, Temsah, Mh, Thankappan, Kr, Thomas, Hj, Thomas, Ml, Thurston, Gd, To, Qg, Torre, Ae, Tovani-Palone, Mr, Towbin, Ja, Tran, Bx, Tran, Kb, Truelsen, Tc, Truong, Nt, Tsadik, Ag, Tuzcu, Em, Tymeson, Hd, Ukwaja, Kn, Updike, Rl, Uthman, Oa, Valdez, Pr, Vasankari, Tj, Vladimirov, Sk, Vollset, Se, Vu, Gt, Waller, Sg, Walson, Jl, Wang, Yp, Weintraub, Rg, Werkneh, Aa, West, Jj, Whiteford, Ha, Wiyeh, Ab, Wolfe, Cda, Wong, Ty, Yahyazadeh Jabbari, Sh, Yan, Ll, Yasin, Yj, Yimer, Em, Yoon, Sj, Younis, Mz, Zaman, Sb, Zhang, Al, Zimsen, Srm, Murray, Cjl., Stanaway, Jeffrey D, Afshin, Ashkan, Gakidou, Emmanuela, Lim, Stephen S, Abate, Degu, Abate, Kalkidan Hassen, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Molla, Abebe, Zegeye, Abera, Semaw F, Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, Adane, Akilew Awoke, Adebayo, Oladimeji M, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Ademi, Zanfina, Adetokunboh, Olatunji O, Adib, Mina G, Admasie, Amha, Adsuar, Jose C, Afanvi, Kossivi Agbelenko, Afarideh, 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Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Ataro, Zerihun, Ausloos, Marcel, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Ball, Kylie, Ballew, Shoshana H, Banach, Maciej, Banoub, Joseph Adel Mattar, Barac, Aleksandra, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Bekru, Eyasu Tamru, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Bergeron, Gille, Berhane, Adugnaw, Bernabe, Eduardo, Bernstein, Robert S, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhattarai, Suraj, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Bori, Bilano, Ver, 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Shokraneh, Farhad, Shoman, Haitham, Shrime, Mark G, Shupler, Matthew S, Si, Si, Siabani, Soraya, Sibai, Abla Mehio, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singh, Jasvinder A, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Skirbekk, Vegard, Smith, David L, Smith, Mari, Sobaih, Badr Hasan, Sobhani, Soheila, Somayaji, Ranjani, Soofi, Moslem, Sorensen, Reed J D, Soriano, Joan B, Soyiri, Ireneous N, Spinelli, Angela, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Starodubov, Vladimir I, Steckling, Nadine, Stein, Dan J, Stein, Murray B, Stevanovic, Goran, Stockfelt, Leo, Stokes, Mark A, Sturua, Lela, Subart, Michelle L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sykes, Bryan L, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh 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Muthiah, Vaezi, Afsane, Valdez, Pascual R, Van Donkelaar, Aaron, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Venkateswaran, Vidhya, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vu, Giang Thu, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Waller, Stephen G, Walson, Judd L, Wang, Yafeng, Wang, Yanping, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weldegebreal, Fitsum, Werdecker, Andrea, Werkneh, Adhena Ayaliew, West, J Jason, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Wong, Tien Yin, Wu, Shouling, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yadollahpour, Ali, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zavala-Arciniega, Lui, Zhang, Anthony Lin, Zhang, Hao, Zhang, Kai, Zhou, Maigeng, Zimsen, Stephanie R M, Zodpey, Sanjay, and Murray, Christopher J L
Subjects: Science & Technology, GBD, risks, risk factors, comparative risk assesment, Dalys, Medicine (all), CHOLESTEROL, BLOOD-PRESSURE, 11 Medical And Health Sciences, ILLNESS, TRENDS, humanities, Medicine, General & Internal, TOBACCO CONTROL, General & Internal Medicine, parasitic diseases, Medicine and Health Sciences, CARDIOVASCULAR-DISEASES, TRIAL, Human medicine, Life Sciences & Biomedicine, METAANALYSIS
Abstract: Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk– outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Lancet 2018; 392: 1923–94 *Collaborators listed at the end of the paper Correspondence to: Prof Christopher J L Murray, Institute for Health Metrics and Evalution, Seattle, WA 98121, USA cjlm@uw.edu Global Health Metrics 1924 www.thelancet.com Vol 392 November 10, 2018 Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.
Published: 2018

25. Population and fertility by age and sex for 195 countries and territories, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: Murray, Christopher J L, Callender, Charlton S K H, Kulikoff, Xie Rachel, Srinivasan, Vinay, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbasi, Nooshin, Abbastabar, Hedayat, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdoli, Nasrin, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Abejie, Ayenew Negesse, Aboyans, Victor, Abraha, Haftom Niguse, Abreu, Daisy Maria Xavier, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen M E, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adamu, Abdu A, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Agesa, Kareha M, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmed, Muktar Beshir, Ahmed, Sayem, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, Atique, Suleman, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Banach, Maciej, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Bergeron, Gilles, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Biswas, Tuhin, Bizuneh, Hailemichael, Bleyer, Archie, Basara, Berrak Bora, Bosetti, Cristina, Boufous, Soufiane, Brady, Oliver J, Bragazzi, Nicola Luigi, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Brewer, Jerry D, Briant, Paul Svitil, Britton, Gabrielle, Burstein, Roy, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carrero, Juan J, Carvalho, Félix, Castañeda-Orjuela, Carlos A, Castillo Rivas, Jacqueline, Castro, Franz, Catalá-López, Ferrán, Çavlin, Alanur, Cerin, Ester, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chin, Ken Lee, Chisumpa, Vesper Hichilombwe, Chitheer, Abdulaal, Choi, Jee-Young J, Chowdhury, Rajiv, Christopher, Devasahayam J, Cicuttini, Flavia M, Ciobanu, Liliana G, Cirillo, Massimo, Claro, Rafael M, Collado-Mateo, Daniel, Constantin, Maria-Magdalena, Conti, Sara, Cooper, Cyrus, Cooper, Leslie Trumbull, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa, Megan, Cromwell, Elizabeth, Crowe, Christopher Stephen, Cukelj, Petra, Cunningham, Matthew, Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I, Daryani, Ahmad, Das Gupta, Rajat, Das Neves, José, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De Leo, Diego, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta Tilahun, Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Balem, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Des Jarlais, Don C, Dessie, Getenet Ayalew, Dharmaratne, Samath D, Dhimal, Meghnath, Dicker, Daniel, Ding, Eric L, Dinsa, Girmaye Deye, Djalalinia, Shirin, Do, Huyen Phuc, Dokova, Klara, Doku, David Teye, Dolan, Kate A, Doyle, Kerrie E, Driscoll, Tim R, Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duraes, Andre R, Ebrahimpour, Soheil, Edvardsson, David, El Bcheraoui, Charbel, El-Khatib, Ziad, Elyazar, Iqbal Rf, Enayati, Ahmadali, Endries, Aman Yesuf, Ermakov, Sergey Petrovich, Eshrati, Babak, Eskandarieh, Sharareh, Esmaeili, Reza, Esteghamati, Alireza, Esteghamati, Sadaf, Estep, Kara, Fakhim, Hamed, Farag, Tamer, Faramarzi, Mahbobeh, Fareed, Mohammad, Farinha, Carla Sofia E Sá, Faro, Andre, Farvid, Maryam S, Farzadfar, Farshad, Farzaei, Mohammad Hosein, Fay, Kairsten A, Fazeli, Mir Sohail, Feigin, Valery L, Feigl, Andrea B, Feizy, Fariba, Fenny, Ama P, Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Feyissa, Garumma Tolu, Filip, Irina, Finegold, Samuel, Fischer, Florian, Flor, Luisa Sorio, Foigt, Nataliya A, Foreman, Kyle J, Fornari, Carla, Fürst, Thomas, Fukumoto, Takeshi, Fuller, John E, Fullman, Nancy, Gakidou, Emmanuela, Gallus, Silvano, Gamkrelidze, Amiran, Ganji, Morsaleh, Gankpe, Fortune Gbetoho, Garcia, Gregory M, Garcia-Gordillo, Miguel Á, Gebre, Abadi Kahsu, Gebre, Teshome, Gebregergs, Gebremedhin Berhe, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelano, Tilayie Feto, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M, Genova-Maleras, Ricard, Gething, Peter, Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Ghadiri, Keyghobad, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Ghiasvand, Hesam, Ghimire, Mamata, Ghoshal, Aloke Gopal, Gill, Paramjit Singh, Gill, Tiffany K, Giussani, Giorgia, Gnedovskaya, Elena V, Goli, Srinivas, Gomez, Ricardo Santiago, Gómez-Dantés, Hector, Gona, Philimon N, Goodridge, Amador, Gopalani, Sameer Vali, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Grosso, Giuseppe, Gugnani, Harish Chander C, Guo, Jingwen, Guo, Yuming, Gupta, Prakash C, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Haagsma, Juanita A, Hachinski, Vladimir, Hafezi-Nejad, Nima, Hagos, Tekleberhan B, Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randah R, Hamidi, Samer, Handal, Alexis J, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Haririan, Hamidreza, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid Yimam, Havmoeller, Rasmus, Hay, Simon I, He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I, Heibati, Behzad, Heidari, Behnam, Hendrie, Delia, Henok, Andualem, Henry, Nathaniel J, Herteliu, Claudiu, Heydarpour, Fatemeh, Hibstu, Desalegn T, Hole, Michael K, Homaie Rad, Enayatollah, Hoogar, Praveen, Hosgood, H Dean, Hosseini, Seyed Mostafa, Hosseini Chavoshi, Meimanat M, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hsairi, Mohamed, Hsiao, Thomas, Hu, Guoqing, Huang, John J, Iburg, Kim Moesgaard, Igumbor, Ehimario U, Ikeda, Chad Thomas, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irenso, Asnake Ararsa, Irvani, Seyed Sina Naghibi, Isehunwa, Oluwaseyi Oluwakemi, Islam, Sheikh Mohammed Shariful, Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovljevic, Mihajlo, Jalu, Moti Tolera, James, Spencer L, Jassal, Simerjot K, Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Ji, John S, Jonas, Jost B, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Kapil, Umesh, Karami, Manoochehr, Matin, Behzad Karami, Karch, André, Karema, Corine, Karimi, Seyed M, Kasaeian, Amir, Kassa, Dessalegn H, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassa, Zemenu Yohannes, Kassebaum, Nicholas J, Kastor, Anshul, Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Karyani, Ali Kazemi, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kereselidze, Maia, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A, Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khang, Young-Ho, Khanna, Tripti, Khater, Mona M, 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Subjects: Adult, Male, Population Density, GBD, population, fertility, Adolescent, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, Global Health, Global Burden of Disease, Young Adult, Child, Preschool, General & Internal Medicine, Female, Human medicine, Mortality, Child, Population Growth, Birth Rate, Aged, Human, Maternal Age
Abstract: Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-cotnponent method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings From 1950 to 2017, TFRs decreased by 49.4% (95% uncertainty interval [UI] 46.4-52.0). The TFR decreased from 4.7 livebirths (4.5-4.9) to 2.4 livebirths (2.2-2.5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83.8 million people per year since 1985. The global population increased by 197-2% (193.3-200.8) since 1950, from 2.6 billion (2.5-2.6) to 7.6 billion (7.4-7.9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2.0%; this rate then remained nearly constant until 1970 and then decreased to 1.1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2.5% in 1963 to O7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2.7%. The global average age increased from 26.6 years in 1950 to 32.1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59.9% to 65.3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1.0 livebirths (95% UI 0. 9-1.2) in Cyprus to a high of 7.1 livebirths (6.8-7.4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0.08 livebirths (0.07-0.09) in South Korea to 2.4 livebirths (2.2-2.6) in Niger, and the TFR over age 30 years (I F030; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0.3 livebirths (0.3-0-4) in Puerto Rico to a high of 3.1 livebirths (3.0-3.2) in Niger. TF030 was higher than TFU25 in 145 countries and territories in 2017.33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2.0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
Published: 2018

26. Cystatin C Use for CKD Detection in the Veterans Health Administration System: A Qualitative Study of Barriers and Facilitators.

Author: Lamprea-Montealegre JA, Shapiro A, Bontrager NAB, Rifkin DE, Jassal SK, Gregg LP, Navaneethan SD, Navarra K, Shlipak MG, Estrella MM, and Wang V
Abstract: Rationale & Objective: The measurement of cystatin C has been recommended to enhance chronic kidney disease (CKD) detection and risk stratification in clinical practice. This study gathered insights into the perceptions and experiences of clinical staff regarding the use of cystatin C in CKD detection within the Veterans Health Administration (VHA) system., Study Design: A qualitative approach was employed to explore barriers and facilitators of clinical staff regarding the use of cystatin C in CKD detection within the VHA system. The Organizational Theory of Implementation Effectiveness informed the development of a semistructured interview guide., Setting & Participants: Health care providers, nurses, and clinical pharmacists from the VHA systems in San Francisco, San Diego, and Houston were interviewed between October 2021 and May 2022., Exposures: Participants' experiences with cystatin C testing., Outcomes: Perceived barriers and facilitators to cystatin C testing., Analytical Approach: Participant responses from individual interviews were analyzed by a multidisciplinary team using rapid qualitative analysis methods., Results: Fourteen in-depth interviews were conducted across the 3 VHA systems. Ten of 11 providers worked in primary care. Five key barriers to using cystatin C for CKD detection were identified. These included lack of patient awareness of CKD testing, lack of provider awareness about cystatin C, knowledge barriers about cystatin C testing, unclear roles and ownership of CKD detection, and lack of clinic support to enhance CKD detection. Suggested interventions to overcome these barriers included educational and training programs, improved clinic workflows, and electronic health record aids to support CKD detection and use of cystatin C., Limitations: The results may not be generalizable to other health care systems outside the VHA., Conclusions: The findings indicate a need for targeted interventions such as educational and training programs, improved clinical workflows, and electronic health record aids to address barriers limiting the use of cystatin C in clinical practice for enhanced CKD detection., (© 2024 The Authors.)
Published: 2024
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27. Hypercalcaemia of malignancy: a case of vitamin-D-mediated hypercalcaemia in lymphoma.

Author: Mehta K, Awan M, Devlin S, and Jassal SK
Subjects: Humans, Male, Calcitriol biosynthesis, Ergocalciferols, Lymphoma complications, Lymphoma diagnosis, Positron Emission Tomography Computed Tomography, Aged, 80 and over, Hypercalcemia etiology, Hypercalcemia diagnosis, Paraneoplastic Syndromes complications, Vitamin D adverse effects
Abstract: Hypercalcaemia of malignancy (HCM) is a paraneoplastic syndrome that often portends a poor prognosis. We present an extremely rare (<1%) case of HCM due to extrarenal calcitriol (1,25-(OH) 2 D) production in a patient with splenic marginal zone lymphoma. A man in his 80s presented with a 3-week history of fatigue, unsteadiness and abdominal pain, and new findings of anaemia, kidney injury and hypercalcaemia. Laboratory evaluation, bone marrow biopsy and positron emission tomography/computed tomography (PET/CT) confirmed the diagnosis of splenic marginal zone lymphoma which produced calcitriol (1,25-(OH) 2 D 3 ), causing the patient's hypercalcaemia., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2024. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2024
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28. Development and Validation of the American Heart Association's PREVENT Equations.

Author: Khan SS, Matsushita K, Sang Y, Ballew SH, Grams ME, Surapaneni A, Blaha MJ, Carson AP, Chang AR, Ciemins E, Go AS, Gutierrez OM, Hwang SJ, Jassal SK, Kovesdy CP, Lloyd-Jones DM, Shlipak MG, Palaniappan LP, Sperling L, Virani SS, Tuttle K, Neeland IJ, Chow SL, Rangaswami J, Pencina MJ, Ndumele CE, and Coresh J
Subjects: Adult, Humans, Male, Female, Middle Aged, Aged, Creatinine, Glycated Hemoglobin, American Heart Association, Risk Factors, Albumins, Risk Assessment, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Heart Failure diagnosis, Heart Failure epidemiology, Atherosclerosis
Abstract: Background: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD., Methods: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets., Results: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P =0.01)., Conclusions: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables., Competing Interests: Disclosures Dr Coresh reports grants from the National Institutes of Health (NIH) and from the National Kidney Foundation during the conduct of the study and personal fees and other support from Healthy.io outside the submitted work. Dr Khan reports grants from NIH during the conduct of the study (R21 HL165376). Dr Chang reports consulting fees from Novartis, Reata, and Amgen, and grants from Novartis, Novo Nordisk, NIH, and the National Kidney Foundation. Dr Palaniappan reports grants from NIH during the conduct of the study (K24 HL150476). Dr Tuttle reports unpaid support from the American Heart Association and grant support from NIH (01MD014712, OT2OD032581, U2CDK114886, UL1TR002319, U54DK083912, U01DK100846, OT2HL161847, and UM1AI109568); the Centers for Disease Control and Prevention (75D301-21-P-12254), as well as Bayer and Travere, paid to the institution; consulting fees from Eli Lilly, Boehringer Ingelheim, AstraZeneca, Goldfinch Bio, Novo Nordisk, Bayer, and Travere Therapeutics Inc; honoraria from Eli Lilly, AstraZeneca, Novo Nordisk, and Bayer; unpaid participation as a Data Safety and Monitoring Board chair for National Institute of Diabetes and Digestive and Kidney diseases (NIDDK)/NIH and George Clinical Institute; and unpaid participation as a Diabetic Kidney Disease collaborative chair for the American Society of Nephrology. Dr Neeland reports speaker and consulting fees from Boehringer Ingelheim, Eli Lilly and Co, Nestle Health Science, and Bayer Pharmaceuticals. Dr Virani reports grants from NIH, US Department of Veterans Affairs, Tahir and Jooma Family. The views expressed in this article are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the US Department of Health and Human Services. All other coauthors have nothing to disclose.
Published: 2024
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29. Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis.

Author: Grams ME, Coresh J, Matsushita K, Ballew SH, Sang Y, Surapaneni A, Alencar de Pinho N, Anderson A, Appel LJ, Ärnlöv J, Azizi F, Bansal N, Bell S, Bilo HJG, Brunskill NJ, Carrero JJ, Chadban S, Chalmers J, Chen J, Ciemins E, Cirillo M, Ebert N, Evans M, Ferreiro A, Fu EL, Fukagawa M, Green JA, Gutierrez OM, Herrington WG, Hwang SJ, Inker LA, Iseki K, Jafar T, Jassal SK, Jha V, Kadota A, Katz R, Köttgen A, Konta T, Kronenberg F, Lee BJ, Lees J, Levin A, Looker HC, Major R, Melzer Cohen C, Mieno M, Miyazaki M, Moranne O, Muraki I, Naimark D, Nitsch D, Oh W, Pena M, Purnell TS, Sabanayagam C, Satoh M, Sawhney S, Schaeffner E, Schöttker B, Shen JI, Shlipak MG, Sinha S, Stengel B, Sumida K, Tonelli M, Valdivielso JM, van Zuilen AD, Visseren FLJ, Wang AY, Wen CP, Wheeler DC, Yatsuya H, Yamagata K, Yang JW, Young A, Zhang H, Zhang L, Levey AS, and Gansevoort RT
Subjects: Adult, Female, Humans, Male, Middle Aged, Atrial Fibrillation, Retrospective Studies, Aged, Disease Progression, Internationality, Comorbidity, Albuminuria diagnosis, Albuminuria epidemiology, Creatinine analysis, Cystatin C analysis, Glomerular Filtration Rate, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic epidemiology, Albumins analysis
Abstract: Importance: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US., Objective: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes., Design, Setting, and Participants: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021., Exposures: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR)., Main Outcomes and Measures: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses., Results: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years])., Conclusions and Relevance: In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations.
Published: 2023
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30. Global competency impact of sustained remote international engagement for students.

Author: Kelly T, Bekele A, Kapadia SG, Jassal SK, Ineza D, Uwizeyimana T, Clarke O, Flickinger TE, Dillingham R, and Durieux ME
Subjects: Humans, Cultural Competency, Rwanda, Students, Cognition, Communication
Abstract: Background: To provide just equity in academic exchange, as well as to reduce prohibitive travel cost and address environmental concerns, the past paradigm of international student exchange has fundamentally shifted from one directional travel to mutually beneficial bidirectional remote communication between students all over the globe. Current analysis aims to quantify cultural competency and evaluate academic outcomes., Methods: Sixty students half from the US and half from Rwanda grouped in teams of 4 engaged in a nine-month project-focused relationship. Cultural competency was evaluated prior to project initiation and six months after completion of the project. Student perspective of project development was analyzed weekly and final academic outcome was evaluated., Results: Change in cultural competency was not significant; however, students did identify satisfaction in team interaction and academic outcomes were achieved., Conclusion: A single remote exchange between students in two countries may not be transformative but it can provide cultural enrichment and successful academic project outcome and may serve to enhance cultural curiosity., (© 2023. The Author(s).)
Published: 2023
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31. Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP.

Author: Matsushita K, Kaptoge S, Hageman SHJ, Sang Y, Ballew SH, Grams ME, Surapaneni A, Sun L, Arnlov J, Bozic M, Brenner H, Brunskill NJ, Chang AR, Chinnadurai R, Cirillo M, Correa A, Ebert N, Eckardt KU, Gansevoort RT, Gutierrez O, Hadaegh F, He J, Hwang SJ, Jafar TH, Jassal SK, Kayama T, Kovesdy CP, Landman GW, Levey AS, Lloyd-Jones DM, Major RW, Miura K, Muntner P, Nadkarni GN, Nowak C, Ohkubo T, Pena MJ, Polkinghorne KR, Sairenchi T, Schaeffner E, Schneider MP, Shalev V, Shlipak MG, Solbu MD, Stempniewicz N, Tollitt J, Valdivielso JM, van der Leeuw J, Wang AY, Wen CP, Woodward M, Yamagishi K, Yatsuya H, Zhang L, Dorresteijn JAN, Di Angelantonio E, Visseren FLJ, Pennells L, and Coresh J
Subjects: Humans, Aged, Aged, 80 and over, Risk Factors, Creatinine, Albuminuria diagnosis, Albuminuria epidemiology, Glomerular Filtration Rate, Heart Disease Risk Factors, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases prevention & control, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic epidemiology
Abstract: Aims: The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach., Methods: In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP. We validated C-statistics and net reclassification improvement (NRI), accounting for competing risk of non-CVD death, in 5,997 719 participants from 34 different datasets., Results: In the target population of SCORE2 and SCORE2-OP without diabetes, the CKD Add-on (eGFR only) and CKD Add-on (eGFR + ACR) improved C-statistic by 0.006 (95%CI 0.004-0.008) and 0.016 (0.010-0.023), respectively, for SCORE2 and 0.012 (0.009-0.015) and 0.024 (0.014-0.035), respectively, for SCORE2-OP. Similar results were seen when we included individuals with diabetes and tested the CKD Add-on (eGFR + dipstick). In 57 485 European participants with CKD, SCORE2 or SCORE2-OP with a CKD Add-on showed a significant NRI [e.g. 0.100 (0.062-0.138) for SCORE2] compared to the qualitative approach in the ESC guideline., Conclusion: Our Add-ons with CKD measures improved CVD risk prediction beyond SCORE2 and SCORE2-OP. This approach will help clinicians and patients with CKD refine risk prediction and further personalize preventive therapies for CVD., Competing Interests: Conflict of interest: Ku.M. reports grants from NIDDK; grants and personal fees from Kyowa Kirin, personal fees from Akebia outside the submitted work. M.G. reports grants from NIH and National Kidney Foundation outside the submitted work. J.A. reports personal fees from AstraZeneca, Novartis, and Boerhinger Ingelheim outside the submitted work. A.R.C. reports personal fees from Novartis, Reata, and Amgen; grants from Novo Nordisk outside the submitted work. N.E. reports personal fees from Bayer and AG Leverkusen outside the submitted work. K.E. reports grants from Amgen, Astra Zenceca, Bayer, Evotec, and Vifor; personal fees from Akebia, Astra Zeneca, Bayer, Otsuka, and Retrophin outside the submitted work. S.K.J reports salary support from US Government and Department of Veterans Affairs during the conduct of the study. C.K. reports personal fees from Bayer, Abbott, Astra-Zeneca, Takeda, Tricida, Akebia, Cara Therapeutics, Vifor, Rockwell, CSL Behring, Reata, Boehringer Ingelheim, and GSK outside the submitted work. A.S.L. reports grants and contracts from NIH and NKF for studies in CKD and a contract from AstraZeneca for DSMB for clinical trials of dapagliflozin. Ka.M. reports grants from Ministry of Health, Labor, and Welfare, Japan. G.N.N reports personal fees from Renalytix, Daiichi Sankyo, Menarini Medical, Qiming Capital, and Variant Bio; other fees from Pensieve Health, Nexus I Connect outside the submitted work; patent KidneyIntelX pending to Renalytix. M.G.S. reports grants from NIH- NIA/NIDDK/NHLBI during the conduct of the study; personal fees from Cricket Health, Intercept Pharmaceuticals, Bayer Pharmaceuticals, AztraZeneca, Boeringer Ingelheim; grants from Bayer Pharmaceuticals outside the submitted work. M.D.S reports a honoraria from AstraZeneca outside the submitted work. N.S. is a current employee of GSK and employed at AMGA. M.W. reports personal fees from Amgen and Freeline outside the submitted work. J.C. reports grants from National Institute of Health and National Kidney Foundation, during the conduct of the study; personal fees from Healthy.io and SomaLogic outside the submitted work. No other potential conflicts of interest relevant to this article were reported. All other authors report no potential conflicts., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Published: 2023
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32. Virtual interviewing for graduate medical education recruitment and selection: A BEME systematic review: BEME Guide No. 80.

Author: Daniel M, Gottlieb M, Wooten D, Stojan J, Haas MRC, Bailey J, Evans S, Lee D, Goldberg C, Fernandez J, Jassal SK, Rudolf F, Guluma K, Lander L, Pott E, Goldhaber NH, Thammasitboon S, Uraiby H, Grafton-Clarke C, Gordon M, Pawlikowska T, Corral J, Partha I, Kolman KB, Westrick J, and Dolmans D
Subjects: Humans, Pandemics, Education, Medical, Graduate, Fellowships and Scholarships, COVID-19 epidemiology, Education, Medical, Internship and Residency
Abstract: Background: The COVID-19 pandemic caused graduate medical education (GME) programs to pivot to virtual interviews (VIs) for recruitment and selection. This systematic review synthesizes the rapidly expanding evidence base on VIs, providing insights into preferred formats, strengths, and weaknesses., Methods: PubMed/MEDLINE, Scopus, ERIC, PsycINFO, MedEdPublish, and Google Scholar were searched from 1 January 2012 to 21 February 2022. Two authors independently screened titles, abstracts, full texts, performed data extraction, and assessed risk of bias using the Medical Education Research Quality Instrument. Findings were reported according to Best Evidence in Medical Education guidance., Results: One hundred ten studies were included. The majority (97%) were from North America. Fourteen were conducted before COVID-19 and 96 during the pandemic. Studies involved both medical students applying to residencies (61%) and residents applying to fellowships (39%). Surgical specialties were more represented than other specialties. Applicants preferred VI days that lasted 4-6 h, with three to five individual interviews (15-20 min each), with virtual tours and opportunities to connect with current faculty and trainees. Satisfaction with VIs was high, though both applicants and programs found VIs inferior to in-person interviews for assessing 'fit.' Confidence in ranking applicants and programs was decreased. Stakeholders universally noted significant cost and time savings with VIs, as well as equity gains and reduced carbon footprint due to eliminating travel., Conclusions: The use of VIs for GME recruitment and selection has accelerated rapidly. The findings of this review offer early insights that can guide future practice, policy, and research.
Published: 2022
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33. Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses.

Author: Gaziano L, Sun L, Arnold M, Bell S, Cho K, Kaptoge SK, Song RJ, Burgess S, Posner DC, Mosconi K, Robinson-Cohen C, Mason AM, Bolton TR, Tao R, Allara E, Schubert P, Chen L, Staley JR, Staplin N, Altay S, Amiano P, Arndt V, Ärnlöv J, Barr ELM, Björkelund C, Boer JMA, Brenner H, Casiglia E, Chiodini P, Cooper JA, Coresh J, Cushman M, Dankner R, Davidson KW, de Jongh RT, Donfrancesco C, Engström G, Freisling H, de la Cámara AG, Gudnason V, Hankey GJ, Hansson PO, Heath AK, Hoorn EJ, Imano H, Jassal SK, Kaaks R, Katzke V, Kauhanen J, Kiechl S, Koenig W, Kronmal RA, Kyrø C, Lawlor DA, Ljungberg B, MacDonald C, Masala G, Meisinger C, Melander O, Moreno Iribas C, Ninomiya T, Nitsch D, Nordestgaard BG, Onland-Moret C, Palmieri L, Petrova D, Garcia JRQ, Rosengren A, Sacerdote C, Sakurai M, Santiuste C, Schulze MB, Sieri S, Sundström J, Tikhonoff V, Tjønneland A, Tong T, Tumino R, Tzoulaki I, van der Schouw YT, Monique Verschuren WM, Völzke H, Wallace RB, Wannamethee SG, Weiderpass E, Willeit P, Woodward M, Yamagishi K, Zamora-Ros R, Akwo EA, Pyarajan S, Gagnon DR, Tsao PS, Muralidhar S, Edwards TL, Damrauer SM, Joseph J, Pennells L, Wilson PWF, Harrison S, Gaziano TA, Inouye M, Baigent C, Casas JP, Langenberg C, Wareham N, Riboli E, Gaziano JM, Danesh J, Hung AM, Butterworth AS, Wood AM, and Di Angelantonio E
Subjects: Humans, Mendelian Randomization Analysis methods, Prospective Studies, Risk Factors, Kidney, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases genetics, Coronary Disease diagnosis, Coronary Disease epidemiology, Coronary Disease genetics, Diabetes Mellitus epidemiology, Stroke diagnosis, Stroke epidemiology, Stroke genetics
Abstract: Background: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke., Methods: Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank., Results: There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min -1 ·1.73 m -2 , compared with those with eGFR between 60 and 105 mL·min -1 ·1.73 m -2 . Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min -1 ·1.73 m -2 , with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min -1 ·1.73 m -2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min -1 ·1.73 m -2 . Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD., Conclusions: In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function.
Published: 2022
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34. Improving chronic kidney disease detection and treatment in the United States: the chronic kidney disease cascade of care (C 3 ) study protocol.

Author: Lamprea-Montealegre JA, Joshi P, Shapiro AS, Madden E, Navarra K, Potok OA, Gregg LP, Podchiyska T, Robinson A, Goldstein MK, Peralta CA, Jassal SK, Navaneethan SD, Rifkin DE, Wang V, Shlipak MG, and Estrella MM
Subjects: Creatinine, Humans, Primary Health Care methods, United States epidemiology, United States Department of Veterans Affairs, Cystatin C, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic epidemiology, Renal Insufficiency, Chronic therapy
Abstract: Background: There are major gaps in the implementation of guideline-concordant care for persons with chronic kidney disease (CKD). The CKD Cascade of Care (C 3 ) initiative seeks to improve CKD care by improving detection and treatment of CKD in primary care., Methods: C 3 is a multi-modal initiative deployed in three major academic medical centers within the Department of Veterans Affairs (VA) Health Care System: San Francisco VA, San Diego VA, and Houston VA. The main objective of the first phase of C 3 described in this protocol is to establish the infrastructure for universal CKD detection among primary care patients at high-risk for CKD with a triple-marker screen comprising cystatin C, creatinine, and albuminuria. Across the three sites, a comprehensive educational intervention and the integration of primary care-based clinical champions will be employed with the goal of improving CKD detection and treatment. The San Francisco VA will also implement a practice-facilitation intervention leveraging telehealth and health informatics tools and capabilities for enhanced CKD detection. Parallel formative evaluation across the three sites will assess the feasibility and acceptability of integrating cystatin C as part of routine CKD detection in primary care practice. The effectiveness of the interventions will be assessed using a pre-post observational design for change in the proportion of patients tested annually for CKD. Secondary outcomes will assess change in the initiation of cardio-kidney protective therapies and in nephrology referrals of high-risk patients., Discussion: The first phase of C 3 is a multi-facility multi-modal initiative that aims to improve CKD care by implementing a triple-marker screen for enhanced CKD detection in primary care., (© 2022. The Author(s).)
Published: 2022
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35. Association of Gender and Race/Ethnicity with Internal Medicine In-Training Examination Performance in Graduate Medical Education.

Author: Klein R, Koch J, Snyder ED, Volerman A, Simon W, Jassal SK, Cosco D, Cioletti A, Ufere NN, Burnett-Bowie SM, Palamara K, Schaeffer S, Julian KA, and Thompson V
Subjects: Clinical Competence, Education, Medical, Graduate, Educational Measurement, Ethnicity, Female, Humans, Internal Medicine education, Male, United States epidemiology, Internship and Residency
Abstract: Background: Disparities in objective assessments in graduate medical education such as the In-Training Examination (ITE) that disadvantage women and those self-identifying with race/ethnicities underrepresented in medicine (URiM) are of concern., Objective: Examine ITE trends longitudinally across post-graduate year (PGY) with gender and race/ethnicity., Design: Longitudinal analysis of resident ITE metrics at 7 internal medicine residency programs, 2014-2019. ITE trends across PGY of women and URiM residents compared to non-URiM men assessed via ANOVA. Those with ITE scores associated with less than 90% probability of passing the American Board of Internal Medicine certification exam (ABIM-CE) were identified and odds of being identified as at-risk between groups were assessed with chi square., Participants: A total of 689 IM residents, including 330 women and URiM residents (48%)., Main Measures: ITE score KEY RESULTS: There was a significant difference in ITE score across PGY for women and URiM residents compared to non-URiM men (F (2, 1321) 4.46, p=0.011). Adjusting for program, calendar year, and baseline ITE, women and URiM residents had smaller ITE score gains (adjusted mean change in score between PGY1 and PGY3 (se), non-URiM men 13.1 (0.25) vs women and URiM residents 11.4 (0.28), p<0.001). Women and URiM residents had greater odds of being at potential risk for not passing the ABIM-CE (OR 1.75, 95% CI 1.10 to 2.78) with greatest odds in PGY3 (OR 3.13, 95% CI 1.54 to 6.37)., Conclusion: Differences in ITE over training were associated with resident gender and race/ethnicity. Women and URiM residents had smaller ITE score gains across PGY translating into greater odds of potentially being seen as at-risk for not passing the ABIM-CE. Differences in ITE over training may reflect differences in experiences of women and URiM residents during training and may lead to further disparities., (© 2022. The Author(s), under exclusive licence to Society of General Internal Medicine.)
Published: 2022
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36. Albuminuria Testing in Hypertension and Diabetes: An Individual-Participant Data Meta-Analysis in a Global Consortium.

Author: Shin JI, Chang AR, Grams ME, Coresh J, Ballew SH, Surapaneni A, Matsushita K, Bilo HJG, Carrero JJ, Chodick G, Daratha KB, Jassal SK, Nadkarni GN, Nelson RG, Nowak C, Stempniewicz N, Sumida K, Traynor JP, Woodward M, Sang Y, and Gansevoort RT
Subjects: Adult, Aged, Albuminuria epidemiology, Glomerular Filtration Rate, Humans, Middle Aged, Renal Insufficiency, Chronic diagnosis, Albuminuria diagnosis, Creatinine urine, Diabetes Mellitus urine, Hypertension urine
Abstract: [Figure: see text].
Published: 2021
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37. Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets.

Author: Matsushita K, Jassal SK, Sang Y, Ballew SH, Grams ME, Surapaneni A, Arnlov J, Bansal N, Bozic M, Brenner H, Brunskill NJ, Chang AR, Chinnadurai R, Cirillo M, Correa A, Ebert N, Eckardt KU, Gansevoort RT, Gutierrez O, Hadaegh F, He J, Hwang SJ, Jafar TH, Kayama T, Kovesdy CP, Landman GW, Levey AS, Lloyd-Jones DM, Major RW, Miura K, Muntner P, Nadkarni GN, Naimark DM, Nowak C, Ohkubo T, Pena MJ, Polkinghorne KR, Sabanayagam C, Sairenchi T, Schneider MP, Shalev V, Shlipak M, Solbu MD, Stempniewicz N, Tollitt J, Valdivielso JM, van der Leeuw J, Wang AY, Wen CP, Woodward M, Yamagishi K, Yatsuya H, Zhang L, Schaeffner E, and Coresh J
Abstract: Background: Chronic kidney disease (CKD) measures (estimated glomerular filtration rate [eGFR] and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. "CKD Patch" is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures., Methods: Utilizing data from 4,143,535 adults from 35 datasets, we developed several "CKD Patches" incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch., Findings: We confirmed the prediction improvement with the CKD Patch for CVD mortality beyond SCORE and ASCVD beyond PCE in validation datasets (Δc-statistic 0.027 [95% CI 0.018-0.036] and 0.010 [0.007-0.013] and categorical net reclassification improvement 0.080 [0.032-0.127] and 0.056 [0.044-0.067], respectively). The median (IQI) of the ratio of predicted risk for CVD mortality with CKD Patch vs. the original prediction with SCORE was 2.64 (1.89-3.40) in very high-risk CKD (e.g., eGFR 30-44 ml/min/1.73m 2 with albuminuria ≥30 mg/g), 1.86 (1.48-2.44) in high-risk CKD (e.g., eGFR 45-59 ml/min/1.73m 2 with albuminuria 30-299 mg/g), and 1.37 (1.14-1.69) in moderate risk CKD (e.g., eGFR 60-89 ml/min/1.73m 2 with albuminuria 30-299 mg/g), indicating considerable risk underestimation in CKD with SCORE. The corresponding estimates for ASCVD with PCE were 1.55 (1.37-1.81), 1.24 (1.10-1.54), and 1.21 (0.98-1.46)., Interpretation: The "CKD Patch" can be used to quantitatively enhance ASCVD and CVD mortality risk prediction equations recommended in major US and European guidelines according to CKD measures, when available., Funding: US National Kidney Foundation and the NIDDK., Competing Interests: Dr. Matsushita reports grants from NIH during the conduct of the study; grants and personal fees from Kyowa Kirin and personal fees from Akebia outside the submitted work. Dr. Grams reports grants from NKF and grants from NIH during the conduct of the study and received travel funds to speak at DCI Director's meeting. Dr. Ärnlöv reports personal fees from AstraZeneca outside the submitted work. Dr. Ebert reports personal fees from Bayer AG, personal fees from Siemens Healthineers, and personal fees from Roche Diagnostics outside the submitted work. Dr. Eckardt reports grants from Astra Zeneca, grants from Bayer, grants from FMC, and grants from Vifor during the conduct of the study; personal fees from Akebia, personal fees from Astellas, personal fees from Bayer, and personal fees from Vifor outside the submitted work. Dr. Gutierrez reports grants and personal fees from Akebia, grants and personal fees from Amgen, grants from GSK, personal fees from QED, grants from National Institutes of Health, and grants from American Heart Association outside the submitted work. Dr. Kovesdy reports personal fees from Amgen, personal fees from Sanofi-Aventis, personal fees from Fresenius Medical Care, personal fees from Keryx, grants from Shire, personal fees from Bayer, personal fees from Abbott, personal fees from Abbvie, personal fees from Dr. Schar, personal fees from Astra-Zeneca, personal fees from Takeda, personal fees from Tricida, and personal fees from Reata outside the submitted work. Dr. Levey reports grants from NIDDK during the conduct of the study. Dr. Lloyd-Jones reports grants from NIH during the conduct of the study. Dr. Muntner reports grant support and consulting fees unrelated to this project. Dr. Nadkarni reports grants, personal fees, non-financial support and other from Renalytix AI, non-financial support and other from Pensieve Health, personal fees from Reata, personal fees from AstraZeneca, and personal fees from GLG Consulting outside the submitted work. Dr. Ohkubo reports grants from Omron Healthcare Co. Ltd. outside the submitted work. Dr. Shlipak reports consultancy fees from Cricket Health and Intercept Pharmaceuticals and stocks/stock options from TAI Diagnostics where he is a Scientific Advisor outside the submitted work. Dr. Woodward reports personal fees from Amgen and personal fees from Kirin outside the submitted work. Dr. Zhang reports grants from National Natural Science Foundation of China, grants from Beijing Nova Program Interdisciplinary Cooperation Project, grants from University of Michigan Health System-Peking University Health Science Center Joint Institute for Translational and Clinical Research, grants from PKU-Baidu Fund, grants from Peking University, and grants from AstraZeneca during the conduct of the study. Dr. Schaeffner reports other from Siemens Healthineers, other support from Fresenius Kabi and other support from Fresenius Medical Care outside the submitted work. Dr. Coresh reports grants from NIH and grants from National Kidney Foundation during the conduct of the study; personal fees and other support from Healthy.io outside the submitted work. All other coauthors have nothing to disclose., (© 2020 The Authors.)
Published: 2020
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38. Global Cardiovascular and Renal Outcomes of Reduced GFR.

Author: Thomas B, Matsushita K, Abate KH, Al-Aly Z, Ärnlöv J, Asayama K, Atkins R, Badawi A, Ballew SH, Banerjee A, Barregård L, Barrett-Connor E, Basu S, Bello AK, Bensenor I, Bergstrom J, Bikbov B, Blosser C, Brenner H, Carrero JJ, Chadban S, Cirillo M, Cortinovis M, Courville K, Dandona L, Dandona R, Estep K, Fernandes J, Fischer F, Fox C, Gansevoort RT, Gona PN, Gutierrez OM, Hamidi S, Hanson SW, Himmelfarb J, Jassal SK, Jee SH, Jha V, Jimenez-Corona A, Jonas JB, Kengne AP, Khader Y, Khang YH, Kim YJ, Klein B, Klein R, Kokubo Y, Kolte D, Lee K, Levey AS, Li Y, Lotufo P, El Razek HMA, Mendoza W, Metoki H, Mok Y, Muraki I, Muntner PM, Noda H, Ohkubo T, Ortiz A, Perico N, Polkinghorne K, Al-Radaddi R, Remuzzi G, Roth G, Rothenbacher D, Satoh M, Saum KU, Sawhney M, Schöttker B, Shankar A, Shlipak M, Silva DAS, Toyoshima H, Ukwaja K, Umesawa M, Vollset SE, Warnock DG, Werdecker A, Yamagishi K, Yano Y, Yonemoto N, Zaki MES, Naghavi M, Forouzanfar MH, Murray CJL, Coresh J, and Vos T
Subjects: Global Health, Humans, Risk Assessment, Risk Factors, Cardiovascular Diseases epidemiology, Cardiovascular Diseases etiology, Glomerular Filtration Rate, Kidney physiopathology, Kidney Diseases epidemiology, Kidney Diseases etiology
Abstract: The burden of premature death and health loss from ESRD is well described. Less is known regarding the burden of cardiovascular disease attributable to reduced GFR. We estimated the prevalence of reduced GFR categories 3, 4, and 5 (not on RRT) for 188 countries at six time points from 1990 to 2013. Relative risks of cardiovascular outcomes by three categories of reduced GFR were calculated by pooled random effects meta-analysis. Results are presented as deaths for outcomes of cardiovascular disease and ESRD and as disability-adjusted life years for outcomes of cardiovascular disease, GFR categories 3, 4, and 5, and ESRD. In 2013, reduced GFR was associated with 4% of deaths worldwide, or 2.2 million deaths (95% uncertainty interval [95% UI], 2.0 to 2.4 million). More than half of these attributable deaths were cardiovascular deaths (1.2 million; 95% UI, 1.1 to 1.4 million), whereas 0.96 million (95% UI, 0.81 to 1.0 million) were ESRD-related deaths. Compared with metabolic risk factors, reduced GFR ranked below high systolic BP, high body mass index, and high fasting plasma glucose, and similarly with high total cholesterol as a risk factor for disability-adjusted life years in both developed and developing world regions. In conclusion, by 2013, cardiovascular deaths attributed to reduced GFR outnumbered ESRD deaths throughout the world. Studies are needed to evaluate the benefit of early detection of CKD and treatment to decrease these deaths., (Copyright © 2017 by the American Society of Nephrology.)
Published: 2017
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39. Vitamin D Insufficiency and Cognitive Function Trajectories in Older Adults: The Rancho Bernardo Study.

Author: Laughlin GA, Kritz-Silverstein D, Bergstrom J, Reas ET, Jassal SK, Barrett-Connor E, and McEvoy LK
Subjects: Aged, California, Comorbidity, Cross-Sectional Studies, Female, Follow-Up Studies, Humans, Independent Living, Logistic Models, Longitudinal Studies, Male, Mental Status and Dementia Tests, Prevalence, Vitamin D blood, Vitamin D Deficiency blood, Cognition, Vitamin D Deficiency epidemiology, Vitamin D Deficiency psychology
Abstract: Background: Evidence of a role for vitamin D (VitD) in cognitive aging is mixed and based primarily on extreme VitD deficiency. We evaluated the association of VitD insufficiency with cognitive function in older, community-dwelling adults living in a temperate climate with year-round sunshine., Methods: A population-based longitudinal study of 1,058 adults (median age 75; 62% women) who had cognitive function assessed and serum levels of 25-hydroxyvitaminD (25OHD) measured in 1997-99 and were followed for up to three additional cognitive function assessments over a 12-year period., Results: Overall, 14% (n = 145) of participants had VitD insufficiency defined as 25OHD <30 ng/ml. Adjusting for age, sex, education, and season, VitD insufficiency was associated with poorer baseline performance on the Mini-Mental Status Exam (MMSE) (p = 0.013), Trails Making Test B (Trails B) (p = 0.015), Category Fluency (p = 0.006), and Long Term Retrieval (p = 0.019); differences were equivalent to 5 years of age. For those with VitD insufficiency, the odds of mildly impaired performance at baseline were 38% higher for MMSE (p = 0.08), 78% higher for Trails B (p = 0.017), and 2-fold higher for Category Fluency and Long Term Retrieval (both p = 0.001). VitD insufficiency was not related to the rate of cognitive decline on any test or the risk of developing impaired performance during follow-up., Conclusion: In this population with little VitD deficiency, even moderately low VitD was associated with poorer performance on multiple domains of cognitive function. Low VitD did not predict 12-year cognitive decline. Clinical trials are essential to establish a causal link between VitD and cognitive well-being.
Published: 2017
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40. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Author: Forouzanfar MH, Alexander L, Anderson HR, Bachman VF, Biryukov S, Brauer M, Burnett R, Casey D, Coates MM, Cohen A, Delwiche K, Estep K, Frostad JJ, Astha KC, Kyu HH, Moradi-Lakeh M, Ng M, Slepak EL, Thomas BA, Wagner J, Aasvang GM, Abbafati C, Abbasoglu Ozgoren A, Abd-Allah F, Abera SF, Aboyans V, Abraham B, Abraham JP, Abubakar I, Abu-Rmeileh NM, Aburto TC, Achoki T, Adelekan A, Adofo K, Adou AK, Adsuar JC, Afshin A, Agardh EE, Al Khabouri MJ, Al Lami FH, Alam SS, Alasfoor D, Albittar MI, Alegretti MA, Aleman AV, Alemu ZA, Alfonso-Cristancho R, Alhabib S, Ali R, Ali MK, Alla F, Allebeck P, Allen PJ, Alsharif U, Alvarez E, Alvis-Guzman N, Amankwaa AA, Amare AT, Ameh EA, Ameli O, Amini H, Ammar W, Anderson BO, Antonio CA, Anwari P, Argeseanu Cunningham S, Arnlöv J, Arsenijevic VS, Artaman A, Asghar RJ, Assadi R, Atkins LS, Atkinson C, Avila MA, Awuah B, Badawi A, Bahit MC, Bakfalouni T, Balakrishnan K, Balalla S, Balu RK, Banerjee A, Barber RM, Barker-Collo SL, Barquera S, Barregard L, Barrero LH, Barrientos-Gutierrez T, Basto-Abreu AC, Basu A, Basu S, Basulaiman MO, Batis Ruvalcaba C, Beardsley J, Bedi N, Bekele T, Bell ML, Benjet C, Bennett DA, Benzian H, Bernabé E, Beyene TJ, Bhala N, Bhalla A, Bhutta ZA, Bikbov B, Bin Abdulhak AA, Blore JD, Blyth FM, Bohensky MA, Bora Başara B, Borges G, Bornstein NM, Bose D, Boufous S, Bourne RR, Brainin M, Brazinova A, Breitborde NJ, Brenner H, Briggs AD, Broday DM, Brooks PM, Bruce NG, Brugha TS, Brunekreef B, Buchbinder R, Bui LN, Bukhman G, Bulloch AG, Burch M, Burney PG, Campos-Nonato IR, Campuzano JC, Cantoral AJ, Caravanos J, Cárdenas R, Cardis E, Carpenter DO, Caso V, Castañeda-Orjuela CA, Castro RE, Catalá-López F, Cavalleri F, Çavlin A, Chadha VK, Chang JC, Charlson FJ, Chen H, Chen W, Chen Z, Chiang PP, Chimed-Ochir O, Chowdhury R, Christophi CA, Chuang TW, Chugh SS, Cirillo M, Claßen TK, Colistro V, Colomar M, Colquhoun SM, Contreras AG, Cooper C, Cooperrider K, Cooper LT, Coresh J, Courville KJ, Criqui MH, Cuevas-Nasu L, Damsere-Derry J, Danawi H, Dandona L, Dandona R, Dargan PI, Davis A, Davitoiu DV, Dayama A, de Castro EF, De la Cruz-Góngora V, De Leo D, de Lima G, Degenhardt L, del Pozo-Cruz B, Dellavalle RP, Deribe K, Derrett S, Des Jarlais DC, Dessalegn M, deVeber GA, Devries KM, Dharmaratne SD, Dherani MK, Dicker D, Ding EL, Dokova K, Dorsey ER, Driscoll TR, Duan L, Durrani AM, Ebel BE, Ellenbogen RG, Elshrek YM, Endres M, Ermakov SP, Erskine HE, Eshrati B, Esteghamati A, Fahimi S, Faraon EJ, Farzadfar F, Fay DF, Feigin VL, Feigl AB, Fereshtehnejad SM, Ferrari AJ, Ferri CP, Flaxman AD, Fleming TD, Foigt N, Foreman KJ, Paleo UF, Franklin RC, Gabbe B, Gaffikin L, Gakidou E, Gamkrelidze A, Gankpé FG, Gansevoort RT, García-Guerra FA, Gasana E, Geleijnse JM, Gessner BD, Gething P, Gibney KB, Gillum RF, Ginawi IA, Giroud M, Giussani G, Goenka S, Goginashvili K, Gomez Dantes H, Gona P, Gonzalez de Cosio T, González-Castell D, Gotay CC, Goto A, Gouda HN, Guerrant RL, Gugnani HC, Guillemin F, Gunnell D, Gupta R, Gupta R, Gutiérrez RA, Hafezi-Nejad N, Hagan H, Hagstromer M, Halasa YA, Hamadeh RR, Hammami M, Hankey GJ, Hao Y, Harb HL, Haregu TN, Haro JM, Havmoeller R, Hay SI, Hedayati MT, Heredia-Pi IB, Hernandez L, Heuton KR, Heydarpour P, Hijar M, Hoek HW, Hoffman HJ, Hornberger JC, Hosgood HD, Hoy DG, Hsairi M, Hu G, Hu H, Huang C, Huang JJ, Hubbell BJ, Huiart L, Husseini A, Iannarone ML, Iburg KM, Idrisov BT, Ikeda N, Innos K, Inoue M, Islami F, Ismayilova S, Jacobsen KH, Jansen HA, Jarvis DL, Jassal SK, Jauregui A, Jayaraman S, Jeemon P, Jensen PN, Jha V, Jiang F, Jiang G, Jiang Y, Jonas JB, Juel K, Kan H, Kany Roseline SS, Karam NE, Karch A, Karema CK, Karthikeyan G, Kaul A, Kawakami N, Kazi DS, Kemp AH, Kengne AP, Keren A, Khader YS, Khalifa SE, Khan EA, Khang YH, Khatibzadeh S, Khonelidze I, Kieling C, Kim D, Kim S, Kim Y, Kimokoti RW, Kinfu Y, Kinge JM, Kissela BM, Kivipelto M, Knibbs LD, Knudsen AK, Kokubo Y, Kose MR, Kosen S, Kraemer A, Kravchenko M, Krishnaswami S, Kromhout H, Ku T, Kuate Defo B, Kucuk Bicer B, Kuipers EJ, Kulkarni C, Kulkarni VS, Kumar GA, Kwan GF, Lai T, Lakshmana Balaji A, Lalloo R, Lallukka T, Lam H, Lan Q, Lansingh VC, Larson HJ, Larsson A, Laryea DO, Lavados PM, Lawrynowicz AE, Leasher JL, Lee JT, Leigh J, Leung R, Levi M, Li Y, Li Y, Liang J, Liang X, Lim SS, Lindsay MP, Lipshultz SE, Liu S, Liu Y, Lloyd BK, Logroscino G, London SJ, Lopez N, Lortet-Tieulent J, Lotufo PA, Lozano R, Lunevicius R, Ma J, Ma S, Machado VM, MacIntyre MF, Magis-Rodriguez C, Mahdi AA, Majdan M, Malekzadeh R, Mangalam S, Mapoma CC, Marape M, Marcenes W, Margolis DJ, Margono C, Marks GB, Martin RV, Marzan MB, Mashal MT, Masiye F, Mason-Jones AJ, Matsushita K, Matzopoulos R, Mayosi BM, Mazorodze TT, McKay AC, McKee M, McLain A, Meaney PA, Medina C, Mehndiratta MM, Mejia-Rodriguez F, Mekonnen W, Melaku YA, Meltzer M, Memish ZA, Mendoza W, Mensah GA, Meretoja A, Mhimbira FA, Micha R, Miller TR, Mills EJ, Misganaw A, Mishra S, Mohamed Ibrahim N, Mohammad KA, Mokdad AH, Mola GL, Monasta L, Montañez Hernandez JC, Montico M, Moore AR, Morawska L, Mori R, Moschandreas J, Moturi WN, Mozaffarian D, Mueller UO, Mukaigawara M, Mullany EC, Murthy KS, Naghavi M, Nahas Z, Naheed A, Naidoo KS, Naldi L, Nand D, Nangia V, Narayan KM, Nash D, Neal B, Nejjari C, Neupane SP, Newton CR, Ngalesoni FN, Ngirabega Jde D, Nguyen G, Nguyen NT, Nieuwenhuijsen MJ, Nisar MI, Nogueira JR, Nolla JM, Nolte S, Norheim OF, Norman RE, Norrving B, Nyakarahuka L, Oh IH, Ohkubo T, Olusanya BO, Omer SB, Opio JN, Orozco R, Pagcatipunan RS Jr, Pain AW, Pandian JD, Panelo CI, Papachristou C, Park EK, Parry CD, Paternina Caicedo AJ, Patten SB, Paul VK, Pavlin BI, Pearce N, Pedraza LS, Pedroza A, Pejin Stokic L, Pekericli A, Pereira DM, Perez-Padilla R, Perez-Ruiz F, Perico N, Perry SA, Pervaiz A, Pesudovs K, Peterson CB, Petzold M, Phillips MR, Phua HP, Plass D, Poenaru D, Polanczyk GV, Polinder S, Pond CD, Pope CA, Pope D, Popova S, Pourmalek F, Powles J, Prabhakaran D, Prasad NM, Qato DM, Quezada AD, Quistberg DA, Racapé L, Rafay A, Rahimi K, Rahimi-Movaghar V, Rahman SU, Raju M, Rakovac I, Rana SM, Rao M, Razavi H, Reddy KS, Refaat AH, Rehm J, Remuzzi G, Ribeiro AL, Riccio PM, Richardson L, Riederer A, Robinson M, Roca A, Rodriguez A, Rojas-Rueda D, Romieu I, Ronfani L, Room R, Roy N, Ruhago GM, Rushton L, Sabin N, Sacco RL, Saha S, Sahathevan R, Sahraian MA, Salomon JA, Salvo D, Sampson UK, Sanabria JR, Sanchez LM, Sánchez-Pimienta TG, Sanchez-Riera L, Sandar L, Santos IS, Sapkota A, Satpathy M, Saunders JE, Sawhney M, Saylan MI, Scarborough P, Schmidt JC, Schneider IJ, Schöttker B, Schwebel DC, Scott JG, Seedat S, Sepanlou SG, Serdar B, Servan-Mori EE, Shaddick G, Shahraz S, Levy TS, Shangguan S, She J, Sheikhbahaei S, Shibuya K, Shin HH, Shinohara Y, Shiri R, Shishani K, Shiue I, Sigfusdottir ID, Silberberg DH, Simard EP, Sindi S, Singh A, Singh GM, Singh JA, Skirbekk V, Sliwa K, Soljak M, Soneji S, Søreide K, Soshnikov S, Sposato LA, Sreeramareddy CT, Stapelberg NJ, Stathopoulou V, Steckling N, Stein DJ, Stein MB, Stephens N, Stöckl H, Straif K, Stroumpoulis K, Sturua L, Sunguya BF, Swaminathan S, Swaroop M, Sykes BL, Tabb KM, Takahashi K, Talongwa RT, Tandon N, Tanne D, Tanner M, Tavakkoli M, Te Ao BJ, Teixeira CM, Téllez Rojo MM, Terkawi AS, Texcalac-Sangrador JL, Thackway SV, Thomson B, Thorne-Lyman AL, Thrift AG, Thurston GD, Tillmann T, Tobollik M, Tonelli M, Topouzis F, Towbin JA, Toyoshima H, Traebert J, Tran BX, Trasande L, Trillini M, Trujillo U, Dimbuene ZT, Tsilimbaris M, Tuzcu EM, Uchendu US, Ukwaja KN, Uzun SB, van de Vijver S, Van Dingenen R, van Gool CH, van Os J, Varakin YY, Vasankari TJ, Vasconcelos AM, Vavilala MS, Veerman LJ, Velasquez-Melendez G, Venketasubramanian N, Vijayakumar L, Villalpando S, Violante FS, Vlassov VV, Vollset SE, Wagner GR, Waller SG, Wallin MT, Wan X, Wang H, Wang J, Wang L, Wang W, Wang Y, Warouw TS, Watts CH, Weichenthal S, Weiderpass E, Weintraub RG, Werdecker A, Wessells KR, Westerman R, Whiteford HA, Wilkinson JD, Williams HC, Williams TN, Woldeyohannes SM, Wolfe CD, Wong JQ, Woolf AD, Wright JL, Wurtz B, Xu G, Yan LL, Yang G, Yano Y, Ye P, Yenesew M, Yentür GK, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Younoussi Z, Yu C, Zaki ME, Zhao Y, Zheng Y, Zhou M, Zhu J, Zhu S, Zou X, Zunt JR, Lopez AD, Vos T, and Murray CJ
Subjects: Female, Global Health statistics & numerical data, Health Behavior, Humans, Male, Nutritional Status, Occupational Exposure adverse effects, Risk Assessment methods, Risk Factors, Sanitation trends, Environmental Exposure adverse effects, Global Health trends, Metabolic Diseases epidemiology, Occupational Diseases epidemiology
Abstract: Background: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution., Methods: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol., Findings: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa., Interpretation: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks., Funding: Bill & Melinda Gates Foundation., (Copyright © 2015 Elsevier Ltd. All rights reserved.)
Published: 2015
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41. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

Author: Murray CJ, Barber RM, Foreman KJ, Abbasoglu Ozgoren A, Abd-Allah F, Abera SF, Aboyans V, Abraham JP, Abubakar I, Abu-Raddad LJ, Abu-Rmeileh NM, Achoki T, Ackerman IN, Ademi Z, Adou AK, Adsuar JC, Afshin A, Agardh EE, Alam SS, Alasfoor D, Albittar MI, Alegretti MA, Alemu ZA, Alfonso-Cristancho R, Alhabib S, Ali R, Alla F, Allebeck P, Almazroa MA, Alsharif U, Alvarez E, Alvis-Guzman N, Amare AT, Ameh EA, Amini H, Ammar W, Anderson HR, Anderson BO, Antonio CA, Anwari P, Arnlöv J, Arsic Arsenijevic VS, Artaman A, Asghar RJ, Assadi R, Atkins LS, Avila MA, Awuah B, Bachman VF, Badawi A, Bahit MC, Balakrishnan K, Banerjee A, Barker-Collo SL, Barquera S, Barregard L, Barrero LH, Basu A, Basu S, Basulaiman MO, Beardsley J, Bedi N, Beghi E, Bekele T, Bell ML, Benjet C, Bennett DA, Bensenor IM, Benzian H, Bernabé E, Bertozzi-Villa A, Beyene TJ, Bhala N, Bhalla A, Bhutta ZA, Bienhoff K, Bikbov B, Biryukov S, Blore JD, Blosser CD, Blyth FM, Bohensky MA, Bolliger IW, Bora Başara B, Bornstein NM, Bose D, Boufous S, Bourne RR, Boyers LN, Brainin M, Brayne CE, Brazinova A, Breitborde NJ, Brenner H, Briggs AD, Brooks PM, Brown JC, Brugha TS, Buchbinder R, Buckle GC, Budke CM, Bulchis A, Bulloch AG, Campos-Nonato IR, Carabin H, Carapetis JR, Cárdenas R, Carpenter DO, Caso V, Castañeda-Orjuela CA, Castro RE, Catalá-López F, Cavalleri F, Çavlin A, Chadha VK, Chang JC, Charlson FJ, Chen H, Chen W, Chiang PP, Chimed-Ochir O, Chowdhury R, Christensen H, Christophi CA, Cirillo M, Coates MM, Coffeng LE, Coggeshall MS, Colistro V, Colquhoun SM, Cooke GS, Cooper C, Cooper LT, Coppola LM, Cortinovis M, Criqui MH, Crump JA, Cuevas-Nasu L, Danawi H, Dandona L, Dandona R, Dansereau E, Dargan PI, Davey G, Davis A, Davitoiu DV, Dayama A, De Leo D, Degenhardt L, Del Pozo-Cruz B, Dellavalle RP, Deribe K, Derrett S, Des Jarlais DC, Dessalegn M, Dharmaratne SD, Dherani MK, Diaz-Torné C, Dicker D, Ding EL, Dokova K, Dorsey ER, Driscoll TR, Duan L, Duber HC, Ebel BE, Edmond KM, Elshrek YM, Endres M, Ermakov SP, Erskine HE, Eshrati B, Esteghamati A, Estep K, Faraon EJ, Farzadfar F, Fay DF, Feigin VL, Felson DT, Fereshtehnejad SM, Fernandes JG, Ferrari AJ, Fitzmaurice C, Flaxman AD, Fleming TD, Foigt N, Forouzanfar MH, Fowkes FG, Paleo UF, Franklin RC, Fürst T, Gabbe B, Gaffikin L, Gankpé FG, Geleijnse JM, Gessner BD, Gething P, Gibney KB, Giroud M, Giussani G, Gomez Dantes H, Gona P, González-Medina D, Gosselin RA, Gotay CC, Goto A, Gouda HN, Graetz N, Gugnani HC, Gupta R, Gupta R, Gutiérrez RA, Haagsma J, Hafezi-Nejad N, Hagan H, Halasa YA, Hamadeh RR, Hamavid H, Hammami M, Hancock J, Hankey GJ, Hansen GM, Hao Y, Harb HL, Haro JM, Havmoeller R, Hay SI, Hay RJ, Heredia-Pi IB, Heuton KR, Heydarpour P, Higashi H, Hijar M, Hoek HW, Hoffman HJ, Hosgood HD, Hossain M, Hotez PJ, Hoy DG, Hsairi M, Hu G, Huang C, Huang JJ, Husseini A, Huynh C, Iannarone ML, Iburg KM, Innos K, Inoue M, Islami F, Jacobsen KH, Jarvis DL, Jassal SK, Jee SH, Jeemon P, Jensen PN, Jha V, Jiang G, Jiang Y, Jonas JB, Juel K, Kan H, Karch A, Karema CK, Karimkhani C, Karthikeyan G, Kassebaum NJ, Kaul A, Kawakami N, Kazanjan K, Kemp AH, Kengne AP, Keren A, Khader YS, Khalifa SE, Khan EA, Khan G, Khang YH, Kieling C, Kim D, Kim S, Kim Y, Kinfu Y, Kinge JM, Kivipelto M, Knibbs LD, Knudsen AK, Kokubo Y, Kosen S, Krishnaswami S, Kuate Defo B, Kucuk Bicer B, Kuipers EJ, Kulkarni C, Kulkarni VS, Kumar GA, Kyu HH, Lai T, Lalloo R, Lallukka T, Lam H, Lan Q, Lansingh VC, Larsson A, Lawrynowicz AE, Leasher JL, Leigh J, Leung R, Levitz CE, Li B, Li Y, Li Y, Lim SS, Lind M, Lipshultz SE, Liu S, Liu Y, Lloyd BK, Lofgren KT, Logroscino G, Looker KJ, Lortet-Tieulent J, Lotufo PA, Lozano R, Lucas RM, Lunevicius R, Lyons RA, Ma S, Macintyre MF, Mackay MT, Majdan M, Malekzadeh R, Marcenes W, Margolis DJ, Margono C, Marzan MB, Masci JR, Mashal MT, Matzopoulos R, Mayosi BM, Mazorodze TT, Mcgill NW, Mcgrath JJ, Mckee M, Mclain A, Meaney PA, Medina C, Mehndiratta MM, Mekonnen W, Melaku YA, Meltzer M, Memish ZA, Mensah GA, Meretoja A, Mhimbira FA, Micha R, Miller TR, Mills EJ, Mitchell PB, Mock CN, Mohamed Ibrahim N, Mohammad KA, Mokdad AH, Mola GL, Monasta L, Montañez Hernandez JC, Montico M, Montine TJ, Mooney MD, Moore AR, Moradi-Lakeh M, Moran AE, Mori R, Moschandreas J, Moturi WN, Moyer ML, Mozaffarian D, Msemburi WT, Mueller UO, Mukaigawara M, Mullany EC, Murdoch ME, Murray J, Murthy KS, Naghavi M, Naheed A, Naidoo KS, Naldi L, Nand D, Nangia V, Narayan KM, Nejjari C, Neupane SP, Newton CR, Ng M, Ngalesoni FN, Nguyen G, Nisar MI, Nolte S, Norheim OF, Norman RE, Norrving B, Nyakarahuka L, Oh IH, Ohkubo T, Ohno SL, Olusanya BO, Opio JN, Ortblad K, Ortiz A, Pain AW, Pandian JD, Panelo CI, Papachristou C, Park EK, Park JH, Patten SB, Patton GC, Paul VK, Pavlin BI, Pearce N, Pereira DM, Perez-Padilla R, Perez-Ruiz F, Perico N, Pervaiz A, Pesudovs K, Peterson CB, Petzold M, Phillips MR, Phillips BK, Phillips DE, Piel FB, Plass D, Poenaru D, Polinder S, Pope D, Popova S, Poulton RG, Pourmalek F, Prabhakaran D, Prasad NM, Pullan RL, Qato DM, Quistberg DA, Rafay A, Rahimi K, Rahman SU, Raju M, Rana SM, Razavi H, Reddy KS, Refaat A, Remuzzi G, Resnikoff S, Ribeiro AL, Richardson L, Richardus JH, Roberts DA, Rojas-Rueda D, Ronfani L, Roth GA, Rothenbacher D, Rothstein DH, Rowley JT, Roy N, Ruhago GM, Saeedi MY, Saha S, Sahraian MA, Sampson UK, Sanabria JR, Sandar L, Santos IS, Satpathy M, Sawhney M, Scarborough P, Schneider IJ, Schöttker B, Schumacher AE, Schwebel DC, Scott JG, Seedat S, Sepanlou SG, Serina PT, Servan-Mori EE, Shackelford KA, Shaheen A, Shahraz S, Shamah Levy T, Shangguan S, She J, Sheikhbahaei S, Shi P, Shibuya K, Shinohara Y, Shiri R, Shishani K, Shiue I, Shrime MG, Sigfusdottir ID, Silberberg DH, Simard EP, Sindi S, Singh A, Singh JA, Singh L, Skirbekk V, Slepak EL, Sliwa K, Soneji S, Søreide K, Soshnikov S, Sposato LA, Sreeramareddy CT, Stanaway JD, Stathopoulou V, Stein DJ, Stein MB, Steiner C, Steiner TJ, Stevens A, Stewart A, Stovner LJ, Stroumpoulis K, Sunguya BF, Swaminathan S, Swaroop M, Sykes BL, Tabb KM, Takahashi K, Tandon N, Tanne D, Tanner M, Tavakkoli M, Taylor HR, Te Ao BJ, Tediosi F, Temesgen AM, Templin T, Ten Have M, Tenkorang EY, Terkawi AS, Thomson B, Thorne-Lyman AL, Thrift AG, Thurston GD, Tillmann T, Tonelli M, Topouzis F, Toyoshima H, Traebert J, Tran BX, Trillini M, Truelsen T, Tsilimbaris M, Tuzcu EM, Uchendu US, Ukwaja KN, Undurraga EA, Uzun SB, Van Brakel WH, Van De Vijver S, van Gool CH, Van Os J, Vasankari TJ, Venketasubramanian N, Violante FS, Vlassov VV, Vollset SE, Wagner GR, Wagner J, Waller SG, Wan X, Wang H, Wang J, Wang L, Warouw TS, Weichenthal S, Weiderpass E, Weintraub RG, Wenzhi W, Werdecker A, Westerman R, Whiteford HA, Wilkinson JD, Williams TN, Wolfe CD, Wolock TM, Woolf AD, Wulf S, Wurtz B, Xu G, Yan LL, Yano Y, Ye P, Yentür GK, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Yu C, Zaki ME, Zhao Y, Zheng Y, Zonies D, Zou X, Salomon JA, Lopez AD, and Vos T
Subjects: Aged, Female, Humans, Male, Middle Aged, Mortality, Premature, Quality-Adjusted Life Years, Socioeconomic Factors, Chronic Disease epidemiology, Communicable Diseases epidemiology, Global Health statistics & numerical data, Health Transition, Life Expectancy, Wounds and Injuries epidemiology
Abstract: Background: The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development., Methods: We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time., Findings: Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries., Interpretation: Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition--in which increasing sociodemographic status brings structured change in disease burden--is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions., Funding: Bill & Melinda Gates Foundation., (Copyright © 2015 Elsevier Ltd. All rights reserved.)
Published: 2015
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42. Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data.

Author: Matsushita K, Coresh J, Sang Y, Chalmers J, Fox C, Guallar E, Jafar T, Jassal SK, Landman GW, Muntner P, Roderick P, Sairenchi T, Schöttker B, Shankar A, Shlipak M, Tonelli M, Townend J, van Zuilen A, Yamagishi K, Yamashita K, Gansevoort R, Sarnak M, Warnock DG, Woodward M, and Ärnlöv J
Subjects: Adult, Cardiovascular Diseases epidemiology, Cardiovascular Diseases urine, Coronary Disease diagnosis, Coronary Disease epidemiology, Coronary Disease urine, Creatinine urine, Female, Follow-Up Studies, Heart Failure diagnosis, Heart Failure epidemiology, Heart Failure urine, Humans, Male, Middle Aged, Risk Factors, Stroke diagnosis, Stroke epidemiology, Stroke urine, Albuminuria urine, Cardiovascular Diseases diagnosis, Glomerular Filtration Rate
Abstract: Background: The usefulness of estimated glomerular filtration rate (eGFR) and albuminuria for prediction of cardiovascular outcomes is controversial. We aimed to assess the addition of creatinine-based eGFR and albuminuria to traditional risk factors for prediction of cardiovascular risk with a meta-analytic approach., Methods: We meta-analysed individual-level data for 637 315 individuals without a history of cardiovascular disease from 24 cohorts (median follow-up 4·2-19·0 years) included in the Chronic Kidney Disease Prognosis Consortium. We assessed C statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in a 5 year timeframe, contrasting prediction models for traditional risk factors with and without creatinine-based eGFR, albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria), or both., Findings: The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR, and more evident for cardiovascular mortality (C statistic difference 0·0139 [95% CI 0·0105-0·0174] for ACR and 0·0065 [0·0042-0·0088] for eGFR) and heart failure (0·0196 [0·0108-0·0284] and 0·0109 [0·0059-0·0159]) than for coronary disease (0·0048 [0·0029-0·0067] and 0·0036 [0·0019-0·0054]) and stroke (0·0105 [0·0058-0·0151] and 0·0036 [0·0004-0·0069]). Dipstick proteinuria showed smaller improvement than ACR. The discrimination improvement with eGFR or ACR was especially evident in individuals with diabetes or hypertension, but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these disorders. In individuals with chronic kidney disease, the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the C statistic for cardiovascular mortality fell by 0·0227 (0·0158-0·0296) after omission of eGFR and ACR compared with less than 0·007 for any single modifiable traditional predictor., Interpretation: Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when these measures are already assessed for clinical purpose or if cardiovascular mortality and heart failure are outcomes of interest. ACR could have particularly broad implications for cardiovascular prediction. In populations with chronic kidney disease, the simultaneous assessment of eGFR and ACR could facilitate improved classification of cardiovascular risk, supporting current guidelines for chronic kidney disease. Our results lend some support to also incorporating eGFR and ACR into assessments of cardiovascular risk in the general population., Funding: US National Kidney Foundation, National Institute of Diabetes and Digestive and Kidney Diseases., (Copyright © 2015 Elsevier Ltd. All rights reserved.)
Published: 2015
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43. Urine creatinine-based estimates of fat-free mass in community-dwelling older persons: the Rancho Bernardo study.

Author: Jassal SK, Wassel CL, Laughlin GA, Barrett-Connor E, Rifkin DE, and Ix JH
Subjects: Age Factors, Aged, Body Weight, California, Cohort Studies, Cross-Sectional Studies, Female, Humans, Male, Reproducibility of Results, Sex Factors, Creatinine urine, Geriatric Assessment methods, Muscle, Skeletal
Abstract: Objectives: To determine whether a previously developed and externally validated equation using common variables (demographics and weight) that are important determinants of muscle mass to estimate 24-hour urine creatinine excretion rate (eCER) is associated with muscle mass and whether spot urine creatinine (UCr) provides similar estimates of muscle mass., Design: Observational cross-sectional cohort study., Setting: The Rancho Bernardo Study, San Diego, California., Subjects: A total of 1,371 Caucasian, middle class, community-dwelling older adults., Intervention: Morning spot UCr and fat-free mass (FFM) by dual-energy x-ray absorptiometry were measured. eCER was calculated: eCER (mg/day) = 879.89 + 12.51 × weight (kilogram) - 6.19 × age + 34.51 if black - 379.42 if female. Pearson correlation coefficients and linear regression were used to determine strengths of association of eCER and spot UCr with FFM., Results: Mean age was 70 years, and 58% were women. eCER was strongly correlated with FFM (r = 0.95, P < .001), a correlation that was superior to that of spot UCr (r = 0.40, P < .001)., Conclusions: An equation incorporating age, weight, sex, and race to estimate eCER is highly correlated with FFM in community-dwelling older persons and provides a more precise estimate than spot UCr. A simple screening tool for sarcopenia in older persons may allow interventions to maintain or improve muscle mass. Future studies should evaluate whether eCER predicts sarcopenia-related frailty and mortality in older persons., (Published by Elsevier Inc.)
Published: 2015
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44. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Author: Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, Mullany EC, Biryukov S, Abbafati C, Abera SF, Abraham JP, Abu-Rmeileh NM, Achoki T, AlBuhairan FS, Alemu ZA, Alfonso R, Ali MK, Ali R, Guzman NA, Ammar W, Anwari P, Banerjee A, Barquera S, Basu S, Bennett DA, Bhutta Z, Blore J, Cabral N, Nonato IC, Chang JC, Chowdhury R, Courville KJ, Criqui MH, Cundiff DK, Dabhadkar KC, Dandona L, Davis A, Dayama A, Dharmaratne SD, Ding EL, Durrani AM, Esteghamati A, Farzadfar F, Fay DF, Feigin VL, Flaxman A, Forouzanfar MH, Goto A, Green MA, Gupta R, Hafezi-Nejad N, Hankey GJ, Harewood HC, Havmoeller R, Hay S, Hernandez L, Husseini A, Idrisov BT, Ikeda N, Islami F, Jahangir E, Jassal SK, Jee SH, Jeffreys M, Jonas JB, Kabagambe EK, Khalifa SE, Kengne AP, Khader YS, Khang YH, Kim D, Kimokoti RW, Kinge JM, Kokubo Y, Kosen S, Kwan G, Lai T, Leinsalu M, Li Y, Liang X, Liu S, Logroscino G, Lotufo PA, Lu Y, Ma J, Mainoo NK, Mensah GA, Merriman TR, Mokdad AH, Moschandreas J, Naghavi M, Naheed A, Nand D, Narayan KM, Nelson EL, Neuhouser ML, Nisar MI, Ohkubo T, Oti SO, Pedroza A, Prabhakaran D, Roy N, Sampson U, Seo H, Sepanlou SG, Shibuya K, Shiri R, Shiue I, Singh GM, Singh JA, Skirbekk V, Stapelberg NJ, Sturua L, Sykes BL, Tobias M, Tran BX, Trasande L, Toyoshima H, van de Vijver S, Vasankari TJ, Veerman JL, Velasquez-Melendez G, Vlassov VV, Vollset SE, Vos T, Wang C, Wang X, Weiderpass E, Werdecker A, Wright JL, Yang YC, Yatsuya H, Yoon J, Yoon SJ, Zhao Y, Zhou M, Zhu S, Lopez AD, Murray CJ, and Gakidou E
Subjects: Adolescent, Adult, Child, Female, Humans, Male, Models, Theoretical, Prevalence, Regression Analysis, Cost of Illness, Obesity epidemiology, Overweight epidemiology
Abstract: Background: In 2010, overweight and obesity were estimated to cause 3·4 million deaths, 3·9% of years of life lost, and 3·8% of disability-adjusted life-years (DALYs) worldwide. The rise in obesity has led to widespread calls for regular monitoring of changes in overweight and obesity prevalence in all populations. Comparable, up-to-date information about levels and trends is essential to quantify population health effects and to prompt decision makers to prioritise action. We estimate the global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013., Methods: We systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports. We used mixed effects linear regression to correct for bias in self-reports. We obtained data for prevalence of obesity and overweight by age, sex, country, and year (n=19,244) with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs)., Findings: Worldwide, the proportion of adults with a body-mass index (BMI) of 25 kg/m(2) or greater increased between 1980 and 2013 from 28·8% (95% UI 28·4-29·3) to 36·9% (36·3-37·4) in men, and from 29·8% (29·3-30·2) to 38·0% (37·5-38·5) in women. Prevalence has increased substantially in children and adolescents in developed countries; 23·8% (22·9-24·7) of boys and 22·6% (21·7-23·6) of girls were overweight or obese in 2013. The prevalence of overweight and obesity has also increased in children and adolescents in developing countries, from 8·1% (7·7-8·6) to 12·9% (12·3-13·5) in 2013 for boys and from 8·4% (8·1-8·8) to 13·4% (13·0-13·9) in girls. In adults, estimated prevalence of obesity exceeded 50% in men in Tonga and in women in Kuwait, Kiribati, Federated States of Micronesia, Libya, Qatar, Tonga, and Samoa. Since 2006, the increase in adult obesity in developed countries has slowed down., Interpretation: Because of the established health risks and substantial increases in prevalence, obesity has become a major global health challenge. Not only is obesity increasing, but no national success stories have been reported in the past 33 years. Urgent global action and leadership is needed to help countries to more effectively intervene., Funding: Bill & Melinda Gates Foundation., (Copyright © 2014 Elsevier Ltd. All rights reserved.)
Published: 2014
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45. Associations of estimated glomerular filtration rate and albuminuria with mortality and renal failure by sex: a meta-analysis.

Author: Nitsch D, Grams M, Sang Y, Black C, Cirillo M, Djurdjev O, Iseki K, Jassal SK, Kimm H, Kronenberg F, Oien CM, Levey AS, Levin A, Woodward M, and Hemmelgarn BR
Subjects: Albuminuria etiology, Albuminuria physiopathology, Cause of Death trends, Disease Progression, Female, Global Health, Humans, Male, Prognosis, Renal Insufficiency complications, Renal Insufficiency physiopathology, Risk Factors, Sex Factors, Albuminuria mortality, Glomerular Filtration Rate, Renal Insufficiency mortality
Abstract: Objective: To assess for the presence of a sex interaction in the associations of estimated glomerular filtration rate and albuminuria with all-cause mortality, cardiovascular mortality, and end stage renal disease., Design: Random effects meta-analysis using pooled individual participant data., Setting: 46 cohorts from Europe, North and South America, Asia, and Australasia., Participants: 2,051,158 participants (54% women) from general population cohorts (n=1,861,052), high risk cohorts (n=151,494), and chronic kidney disease cohorts (n=38,612). Eligible cohorts (except chronic kidney disease cohorts) had at least 1000 participants, outcomes of either mortality or end stage renal disease of ≥ 50 events, and baseline measurements of estimated glomerular filtration rate according to the Chronic Kidney Disease Epidemiology Collaboration equation (mL/min/1.73 m(2)) and urinary albumin-creatinine ratio (mg/g)., Results: Risks of all-cause mortality and cardiovascular mortality were higher in men at all levels of estimated glomerular filtration rate and albumin-creatinine ratio. While higher risk was associated with lower estimated glomerular filtration rate and higher albumin-creatinine ratio in both sexes, the slope of the risk relationship for all-cause mortality and for cardiovascular mortality were steeper in women than in men. Compared with an estimated glomerular filtration rate of 95, the adjusted hazard ratio for all-cause mortality at estimated glomerular filtration rate 45 was 1.32 (95% CI 1.08 to 1.61) in women and 1.22 (1.00 to 1.48) in men (P(interaction)<0.01). Compared with a urinary albumin-creatinine ratio of 5, the adjusted hazard ratio for all-cause mortality at urinary albumin-creatinine ratio 30 was 1.69 (1.54 to 1.84) in women and 1.43 (1.31 to 1.57) in men (P(interaction)<0.01). Conversely, there was no evidence of a sex difference in associations of estimated glomerular filtration rate and urinary albumin-creatinine ratio with end stage renal disease risk., Conclusions: Both sexes face increased risk of all-cause mortality, cardiovascular mortality, and end stage renal disease with lower estimated glomerular filtration rates and higher albuminuria. These findings were robust across a large global consortium.
Published: 2013
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46. Kidney function and progression of coronary artery calcium in community-dwelling older adults (from the Rancho Bernardo Study).

Author: Jassal SK, Chonchol M, Laughlin GA, Cummins KM, Smits G, Kramer CK, Ix JH, and Barrett-Connor E
Subjects: Aged, Calcinosis epidemiology, Calcinosis physiopathology, California epidemiology, Coronary Angiography, Coronary Artery Disease diagnostic imaging, Coronary Artery Disease epidemiology, Disease Progression, Female, Follow-Up Studies, Humans, Incidence, Male, Middle Aged, Prognosis, Retrospective Studies, Calcinosis metabolism, Calcium metabolism, Coronary Artery Disease metabolism, Coronary Vessels metabolism, Glomerular Filtration Rate physiology
Abstract: Longitudinal studies of the association of estimated glomerular filtration rate (eGFR) and albuminuria with coronary artery calcium (CAC), a measure of cardiovascular disease burden, are few and contradictory. In this study, 421 community-dwelling men and women (mean age 67 years) without known heart disease had eGFRs assessed using the Modification of Diet in Renal Disease (MDRD) equation and albuminuria assessed by urine albumin/creatinine ratio (ACR) from 1997 to 1999. The mean eGFR was 78 ml/min/1.73 m(2), and the median ACR was 10 mg/g. CAC was measured using electron-beam computed tomography from 2000 to 2001, when the median total Agatston CAC score was 77; 4.5 years later, 338 participants still without heart disease underwent repeat scans (median CAC score 112); 46% of participants showed CAC progression, defined as an increase ≥2.5 mm(3) in square root-transformed CAC volume score. Cross-sectional and longitudinal logistic regression analyses showed no separate or joint association between eGFR or ACR and CAC severity or progression. In conclusion, this study does not support the use of eGFR or ACR to identify asymptomatic older adults who should be screened for subclinical cardiovascular disease with initial or sequential scanning for CAC. In the elderly, kidney function and CAC may not progress together., (Published by Elsevier Inc.)
Published: 2012
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47. Vitamin d, parathyroid hormone, and cardiovascular mortality in older adults: the Rancho Bernardo study.

Author: Jassal SK, Chonchol M, von Mühlen D, Smits G, and Barrett-Connor E
Subjects: Age Factors, Aged, Aged, 80 and over, Biomarkers blood, California epidemiology, Cardiovascular Diseases complications, Confounding Factors, Epidemiologic, Female, Glomerular Filtration Rate, Humans, Male, Multivariate Analysis, Odds Ratio, Proportional Hazards Models, Prospective Studies, Renal Insufficiency, Chronic blood, Renal Insufficiency, Chronic complications, Sunlight, Vitamin D blood, White People statistics & numerical data, Cardiovascular Diseases blood, Cardiovascular Diseases mortality, Parathyroid Hormone blood, Vitamin D analogs & derivatives
Abstract: Background: recent systematic reviews have cast doubt on the association between vitamin D and cardiovascular disease. No prior studies have investigated the association between 25-hydroxyvitamin D (25[OH]D), 1,25-dihydroxyvitamin D (1,25[OH](2)D), or intact parathyroid hormone and cardiovascular mortality in a temperate climate., Methods: a total of 1073 community-dwelling older adults were evaluated in 1997-1999; serum levels of 25(OH)D (mean 42 ng/mL), 1,25(OH)(2)D (median 29 pg/mL), and intact parathyroid hormone (median 46 pg/mL) were measured; mean estimated glomerular filtration rate was 74 mL/min/1.73 m(2). Participants were followed up to 10.4 (mean 6.4) years with 111 cardiovascular deaths., Results: in unadjusted Cox proportional hazards models, higher levels of 1,25(OH)(2)D were protective against cardiovascular mortality, whereas higher levels of intact parathyroid hormone predicted increased risk of cardiovascular death. After adjusting for age alone or multiple covariates, there was no significant association between 25(OH)D, 1,25(OH)(2)D, or intact parathyroid hormone and cardiovascular mortality; results did not differ by an estimated glomerular filtration rate ≥ 60 mL/min/1.73 m(2) or<60 mL/min/1.73 m(2)., Conclusion: in this prospective study of Caucasian, middle-income, community-dwelling older adults living in sunny southern California, serum levels of 25(OH)D, 1,25(OH)(2)D, and intact parathyroid hormone were not independently associated with cardiovascular mortality., (Published by Elsevier Inc.)
Published: 2010
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48. A prospective study of uric acid by glucose tolerance status and survival: the Rancho Bernardo Study.

Author: Kramer CK, von Mühlen D, Jassal SK, and Barrett-Connor E
Subjects: Aged, Biomarkers blood, Blood Glucose metabolism, Cardiovascular Diseases blood, Diabetes Mellitus, Type 2 diagnosis, Female, Glucose Intolerance diagnosis, Glucose Tolerance Test, Humans, Male, Middle Aged, Prediabetic State blood, Predictive Value of Tests, Prospective Studies, Risk Factors, Survival Analysis, Cardiovascular Diseases mortality, Diabetes Mellitus, Type 2 blood, Glucose Intolerance blood, Uric Acid blood
Abstract: Objectives: Little is known about uric acid (UA) levels and mortality in the context of glycaemia. We examined whether serum UA levels predict all-cause and cardiovascular disease (CVD) mortality differentially in older adults by glucose tolerance status., Design and Methods: Between 1984 and 1987, 2342 community-dwelling men and women had an oral glucose tolerance test, UA measurement, and assessment of traditional CVD risk factors. We defined glucose tolerance status as normoglycaemia (NG), pre-diabetes (pre-DM), and type 2 diabetes mellitus (T2DM). Ninety per cent were followed for vital status up to 23 years. Death certificates were coded using the Ninth International Classification of Diseases., Results: Baseline age was 69.5 years; 44.4% were men. At baseline 939 had NG, 957 pre-DM, and 446 T2DM. The mean UA by glucose tolerance status was 327.1, 362.8, and 374.7 micromol L(-1). During follow-up, there were 1318 deaths 46.8% attributed to CVD. In Cox-regression analysis, each 119 micromol L(-1) (2 mg dL(-1)) increment in UA levels predicted an increased hazard ratio (HR) for all-cause deaths independent of age, smoking, body mass index, alcohol, physical activity, diuretic use and estimated glomerular filtration rate in all groups (NG: HR 1.25 95% CI 1.06-1.47, P =0.005; pre-DM: HR 1.20 95% CI 1.06-1.37, P = 0.04; T2DM: HR 1.20 95% CI 1.01-1.47, P = 0.04). After adjusting for CVD risk factors, the UA association with CVD mortality was significant only in the pre-DM and T2DM groups., Conclusion: All-cause mortality was independently associated with UA in all groups, but UA predicted CVD mortality only in those with abnormal glucose tolerance.
Published: 2010
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49. Peripheral arterial disease and osteoporosis in older adults: the Rancho Bernardo Study.

Author: von Mühlen D, Allison M, Jassal SK, and Barrett-Connor E
Subjects: Adult, Aged, Aged, 80 and over, Bone Density physiology, California epidemiology, Epidemiologic Methods, Female, Femur Neck physiopathology, Hip Joint physiopathology, Humans, Male, Middle Aged, Osteoporosis epidemiology, Osteoporosis physiopathology, Osteoporotic Fractures epidemiology, Osteoporotic Fractures etiology, Osteoporotic Fractures physiopathology, Peripheral Arterial Disease epidemiology, Sex Factors, Osteoporosis etiology, Peripheral Arterial Disease complications
Abstract: Summary: We examined the association between peripheral arterial disease (PAD) and bone health in 1,332 adults. We found a weak association between PAD and osteoporosis and bone loss only in women, but the association was not independent of age. PAD was not associated with fractures in this community-based population., Introduction: Increased rates of osteoporosis have been reported in patients with cardiovascular disease, suggesting a link between osteoporosis and atherosclerosis., Methods: We examined the association between PAD and bone health in 1,332 adults who attended a research visit in 1992-1996, when the ankle-brachial index (ABI), bone mineral density (BMD), and spine X-rays were obtained. A total of 837 participants attended a follow-up visit in 1997-2000., Results: PAD defined by an ABI < or = 0.90 was present in 15.4% of the women and 13.3% of the men. Prevalence of osteoporosis was significantly higher in women with PAD compared to women without PAD (p < 0.05). During an average 4-year follow-up, women with PAD had a significantly higher rate of bone loss than women without PAD (p = 0.05). The associations were no longer significant after age adjustment. In men, PAD was not associated with osteoporosis, but men with PAD had lower BMD at the femoral neck than men without PAD (p = 0.03). PAD was not associated with osteoporotic fractures in either sex., Conclusion: We found a weak and age-dependent association between PAD and osteoporosis in women but not men. PAD was not associated with fractures in this community-based population.
Published: 2009
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50. Associations between the metabolic syndrome and bone health in older men and women: the Rancho Bernardo Study.

Author: von Muhlen D, Safii S, Jassal SK, Svartberg J, and Barrett-Connor E
Subjects: Aged, Cohort Studies, Cross-Sectional Studies, Female, Fractures, Bone physiopathology, Fractures, Bone therapy, Humans, Male, Metabolic Syndrome diagnosis, Metabolic Syndrome physiopathology, Osteoporosis metabolism, Osteoporosis physiopathology, Prevalence, Risk Factors, Sex Factors, Bone Density physiology, Fractures, Bone etiology, Metabolic Syndrome complications, Osteoporosis etiology
Abstract: Unlabelled: We examined the associations of metabolic syndrome (MS) with BMD, osteoporosis, and osteoporotic fractures in 417 men and 671 women from the Rancho Bernardo Study. After adjusting for BMI, MS was associated with lower, not higher BMD. Incidence of osteoporotic non-vertebral fractures was higher in participants with MS. MS may be another risk factor for osteoporotic fractures., Introduction: The metabolic syndrome (MS) is a cluster of risk factors, including abdominal obesity, high glucose, triglycerides, hypertension and low HDL levels, associated with cardiovascular disease morbidity. The association between components of the MS and bone mineral density (BMD) has been researched, but results are contradictory., Methods: We used multivariate regression models to examine the cross-sectional associations of MS defined by NCEP-ATP III criteria with BMD and osteoporosis, and the longitudinal association of MS with fractures in 420 men and 676 women from the Rancho Bernardo Study., Results: Prevalence of MS at baseline was 23.5% in men and 18.2% in women. In age-adjusted analyses, men and women with MS had higher BMD at total hip when compared to those without MS (p < 0.001 and p = 0.01, respectively). Men but not women with MS also had higher BMD at femoral neck (p = 0.05). After adjusting for BMI, these associations were reversed, such that MS was associated with lower and not higher BMD., Conclusion: Incidence of osteoporotic non-vertebral fractures was higher in participants with MS. MS may be another risk factor for osteoporotic fractures. The association of MS with higher BMD was explained by the higher BMI in those with MS.
Published: 2007
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