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5. Blood pressure classification using the Japanese Society of Hypertension Guidelines for the Management of Hypertension and cardiovascular events among young to middle-aged working adults

Author

Kuwahara, Keisuke, Ohkubo, Takayoshi, Inoue, Yosuke, Honda, Toru, Yamamoto, Shuichiro, Nakagawa, Tohru, Okazaki, Hiroko, Yamamoto, Makoto, Miyamoto, Toshiaki, Gommori, Naoki, Kochi, Takeshi, Ogasawara, Takayuki, Yamamoto, Kenya, Konishi, Maki, Kabe, Isamu, Dohi, Seitaro, and Mizoue, Tetsuya

Published
2024
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9. Prologue: Special Spotlight Issue on Japan

Author

Yano, Yuichiro, Nishiyama, Akira, Ishimitsu, Toshihiko, Kashihara, Naoki, Rakugi, Hiromi, Tamura, Kouichi, Itoh, Hiroshi, Tsuchihashi, Takuya, Sakima, Atsushi, Arima, Hisatomi, Matayoshi, Tetsutaro, Imai, Yutaka, Miura, Katsuyuki, Hisamatsu, Takashi, Asayama, Kei, Ohkubo, Takayoshi, Node, Kouihci, and Kario, Kazuomi

Published
2024
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10. Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP.

Author

Matsushita, Kunihiro, Kaptoge, Stephen, Hageman, Steven, Sang, Yingying, Ballew, Shoshana, Grams, Morgan, Surapaneni, Aditya, Sun, Luanluan, Arnlov, Johan, Bozic, Milica, Brenner, Hermann, Brunskill, Nigel, Chang, Alex, Chinnadurai, Rajkumar, Cirillo, Massimo, Correa, Adolfo, Ebert, Natalie, Eckardt, Kai-Uwe, Gansevoort, Ron, Gutierrez, Orlando, Hadaegh, Farzad, He, Jiang, Hwang, Shih-Jen, Jafar, Tazeen, Jassal, Simerjot, Kayama, Takamasa, Kovesdy, Csaba, Landman, Gijs, Levey, Andrew, Lloyd-Jones, Donald, Major, Rupert, Miura, Katsuyuki, Muntner, Paul, Nadkarni, Girish, Nowak, Christoph, Ohkubo, Takayoshi, Pena, Michelle, Polkinghorne, Kevan, Sairenchi, Toshimi, Schaeffner, Elke, Schneider, Markus, Shalev, Varda, Shlipak, Michael, Solbu, Marit, Stempniewicz, Nikita, Tollitt, James, Valdivielso, José, van der Leeuw, Joep, Wang, Angela, Wen, Chi-Pang, Woodward, Mark, Yamagishi, Kazumasa, Yatsuya, Hiroshi, Zhang, Luxia, Dorresteijn, Jannick, Di Angelantonio, Emanuele, Visseren, Frank, Pennells, Lisa, and Coresh, Josef

Subjects
Cardiovascular disease, Chronic kidney disease, Meta-analysis, Risk prediction, Humans, Aged, Aged, 80 and over, Cardiovascular Diseases, Risk Factors, Creatinine, Renal Insufficiency, Chronic, Albuminuria, Glomerular Filtration Rate, Heart Disease Risk Factors
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.

Published
2023

15. Development of Risk Prediction Equations for Incident Chronic Kidney Disease

Author

Nelson, Robert G, Grams, Morgan E, Ballew, Shoshana H, Sang, Yingying, Azizi, Fereidoun, Chadban, Steven J, Chaker, Layal, Dunning, Stephan C, Fox, Caroline, Hirakawa, Yoshihisa, Iseki, Kunitoshi, Ix, Joachim, Jafar, Tazeen H, Köttgen, Anna, Naimark, David MJ, Ohkubo, Takayoshi, Prescott, Gordon J, Rebholz, Casey M, Sabanayagam, Charumathi, Sairenchi, Toshimi, Schöttker, Ben, Shibagaki, Yugo, Tonelli, Marcello, Zhang, Luxia, Gansevoort, Ron T, Matsushita, Kunihiro, Woodward, Mark, Coresh, Josef, and Shalev, Varda

Subjects
Clinical Research, Kidney Disease, Patient Safety, Prevention, Renal and urogenital, Good Health and Well Being, Aged, Female, Glomerular Filtration Rate, Humans, Male, Middle Aged, Models, Theoretical, Renal Insufficiency, Chronic, Risk Assessment, Risk Factors, CKD Prognosis Consortium, Medical and Health Sciences, General & Internal Medicine
Abstract

ImportanceEarly identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions.ObjectiveTo develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR).Design, setting, and participantsIndividual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540).ExposuresDemographic and clinical factors.Main outcomes and measuresIncident eGFR of less than 60 mL/min/1.73 m2.ResultsAmong 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25.Conclusions and relevanceEquations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.

Published
2019

20. Diagnostic Value of Home Blood Pressure

Author

Kario, Kazuomi, Imai, Yutaka, Kollias, Anastasios, Niiranen, Teemu J., Ohkubo, Takayoshi, McManus, Richard J., Stergiou, George S., Mancia, Giuseppe, Series Editor, Agabiti Rosei, Enrico, Series Editor, Stergiou, George S., editor, and Parati, Gianfranco, editor

Published
2020
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21. Home Blood Pressure Monitoring Schedule

Author

Niiranen, Teemu J., McManus, Richard J., Ohkubo, Takayoshi, Stergiou, George S., Mancia, Giuseppe, Series Editor, Agabiti Rosei, Enrico, Series Editor, Stergiou, George S., editor, and Parati, Gianfranco, editor

Published
2020
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24. Home Blood Pressure Variability

Author

Parati, Gianfranco, Ochoa, Juan Eugenio, Imai, Yutaka, Kollias, Anastasios, Manios, Efstathios, Ohkubo, Takayoshi, Kario, Kazuomi, Stergiou, George S., Bilo, Grzegorz, Mancia, Giuseppe, Series Editor, Agabiti Rosei, Enrico, Series Editor, Stergiou, George S., editor, and Parati, Gianfranco, editor

Published
2020
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25. Nocturnal Home Blood Pressure Monitoring

Author

Stergiou, George S., Andreadis, Emmanuel, Asayama, Kei, Kario, Kazuomi, Kollias, Anastasios, Ohkubo, Takayoshi, Parati, Gianfranco, Weber, Michael A., Imai, Yutaka, Mancia, Giuseppe, Series Editor, Agabiti Rosei, Enrico, Series Editor, Stergiou, George S., editor, and Parati, Gianfranco, editor

Published
2020
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27. Age-stratified and blood-pressure-stratified effects of blood-pressure-lowering pharmacotherapy for the prevention of cardiovascular disease and death: an individual participant-level data meta-analysis

Author

Rahimi, Kazem, Bidel, Zeinab, Nazarzadeh, Milad, Copland, Emma, Canoy, Dexter, Wamil, Malgorzata, Majert, Jeannette, McManus, Richard, Adler, Amanda, Agodoa, Larry, Algra, Ale, Asselbergs, Folkert W, Beckett, Nigel S, Berge, Eivind, Black, Henry, Boersma, Eric, Brouwers, Frank P J, Brown, Morris, Brugts, Jasper J, Bulpitt, Christopher J, Byington, Robert P, Cushman, William C, Cutler, Jeffrey, Devereaux, Richard B, Dwyer, Jamie P, Estacio, Ray, Fagard, Robert, Fox, Kim, Fukui, Tsuguya, Gupta, Ajay K, Holman, Rury R, Imai, Yutaka, Ishii, Masao, Julius, Stevo, Kanno, Yoshihiko, Kjeldsen, Sverre E, Kostis, John, Kuramoto, Kizuku, Lanke, Jan, Lewis, Edmund, Lewis, Julia B, Lievre, Michel, Lindholm, Lars H, Lueders, Stephan, MacMahon, Stephen, Mancia, Giuseppe, Matsuzaki, Masunori, Mehlum, Maria H, Nissen, Steven, Ogawa, Hiroshi, Ogihara, Toshio, Ohkubo, Takayoshi, Palmer, Christopher R, Patel, Anushka, Pfeffer, Marc Allan, Pitt, Bertram, Poulter, Neil R, Rakugi, Hiromi, Reboldi, Gianpaolo, Reid, Christopher, Remuzzi, Giuseppe, Ruggenenti, Piero, Saruta, Takao, Schrader, Joachim, Schrier, Robert, Sever, Peter, Sleight, Peter, Staessen, Jan A, Suzuki, Hiromichi, Thijs, Lutgarde, Ueshima, Kenji, Umemoto, Seiji, van Gilst, Wiek H, Verdecchia, Paolo, Wachtell, Kristian, Whelton, Paul, Wing, Lindon, Woodward, Mark, Yui, Yoshiki, Yusuf, Salim, Zanchetti, Alberto, Zhang, Zhen-Yu, Anderson, Craig, Baigent, Colin, Brenner, Barry Morton, Collins, Rory, de Zeeuw, Dick, Lubsen, Jacobus, Malacco, Ettore, Neal, Bruce, Perkovic, Vlado, Rodgers, Anthony, Rothwell, Peter, Salimi-Khorshidi, Gholamreza, Sundström, Johan, Turnbull, Fiona, Viberti, Giancarlo, Wang, Jiguang, Chalmers, John, Davis, Barry R, Pepine, Carl J, and Teo, Koon K

Published
2021
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31. Alcohol drinking and brain morphometry in apparently healthy community-dwelling Japanese men

Author

Horie, Minoru, Nakagawa, Yoshihisa, Yamamoto, Takashi, Nakano, Yasutaka, Ogawa, Emiko, Maegawa, Hiroshi, Morino, Katsutaro, Miyazawa, Itsuko, Watanabe, Yoshiyuki, Nozaki, Kazuhiko, Tooyama, Ikuo, Shiino, Akihiko, Andoh, Akira, Tsuru, Teruhiko, Ogita, Hisakazu, Miyamatsu, Naomi, Nakamura, Yasuyuki, Kadota, Aya, Kondo, Keiko, Torii, Sayuki, Kadowaki, Takashi, Kadowaki, Sayaka, Suzuki, Sentaro, Ito, Takahiro, Kunimura, Ayako, Segawa, Hiroyoshi, Fujiyoshi, Akira, Higashiyama, Aya, Okamura, Tomonori, Azuma, Koichiro, Sawamura, Tatsuya, Igase, Michiya, Tabara, Yasuharu, Sekikawa, Akira, Barinas-Mitchell, Emma J.M., Edmundowicz, Daniel, Ohkubo, Takayoshi, Hozawa, Atsushi, Murakami, Yoshitaka, Okuda, Nagako, Arima, Hisatomi, Satoh, Atsushi, Kita, Yoshikuni, Hisamatsu, Takashi, Yanagita, Masahiko, Abbott, Robert D., Ohno, Seiko, Takashima, Naoyuki, Miyagawa, Naoko, Zaid, Maryam, Saito, Yoshino, Syaifullah, Ali Haidar, Moniruzzaman, Mohammad, Waki, Takashi, Ueshima, Hirotsugu, and Miura, Katsuyuki

Published
2021
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35. Incorporating kidney disease measures into cardiovascular risk prediction: Development and validation in 9 million adults from 72 datasets

Author

Matsushita, Kunihiro, Jassal, Simerjot K, Sang, Yingying, Ballew, Shoshana H, Grams, Morgan E, Surapaneni, Aditya, Arnlov, Johan, Bansal, Nisha, Bozic, Milica, Brenner, Hermann, Brunskill, Nigel J, Chang, Alex R, Chinnadurai, Rajkumar, Cirillo, Massimo, Correa, Adolfo, Ebert, Natalie, Eckardt, Kai-Uwe, Gansevoort, Ron T, Gutierrez, Orlando, Hadaegh, Farzad, He, Jiang, Hwang, Shih-Jen, Jafar, Tazeen H, Kayama, Takamasa, Kovesdy, Csaba P, Landman, Gijs W, Levey, Andrew S, Lloyd-Jones, Donald M, Major, Rupert W., Miura, Katsuyuki, Muntner, Paul, Nadkarni, Girish N, Naimark, David MJ, Nowak, Christoph, Ohkubo, Takayoshi, Pena, Michelle J, Polkinghorne, Kevan R, Sabanayagam, Charumathi, Sairenchi, Toshimi, Schneider, Markus P, Shalev, Varda, Shlipak, Michael, Solbu, Marit D, Stempniewicz, Nikita, Tollitt, James, Valdivielso, José M, van der Leeuw, Joep, Wang, Angela Yee-Moon, Wen, Chi-Pang, Woodward, Mark, Yamagishi, Kazumasa, Yatsuya, Hiroshi, Zhang, Luxia, Schaeffner, Elke, and Coresh, Josef

Published
2020
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36. Factors influencing the continuation of home blood pressure measurement in community-dwelling older adults: the NOSE study

Author

Wada, Arisa, primary, Kabayama, Mai, additional, Godai, Kayo, additional, Kido, Michiko, additional, Ohata, Yuka, additional, Murakami, Naoko, additional, Nakamura, Yuko, additional, Yoshida, Hiroko, additional, Hashimoto, Sumiyo, additional, Higashi, Makiko, additional, Hatanaka, Hiromi, additional, Kikuchi, Takeshi, additional, Terauchi, Keiji, additional, Nagayoshi, Sho, additional, Matsuno, Fumie, additional, Shinomiya, Noboru, additional, Asayama, Kei, additional, Ohkubo, Takayoshi, additional, Rakugi, Hiromi, additional, Tabara, Yasuharu, additional, and Kamide, Kei, additional

Published
2023
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46. Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index

Author

Wen, Wanqing, Zheng, Wei, Okada, Yukinori, Takeuchi, Fumihiko, Tabara, Yasuharu, Hwang, Joo-Yeon, Dorajoo, Rajkumar, Li, Huaixing, Tsai, Fuu-Jen, Yang, Xiaobo, He, Jiang, Wu, Ying, He, Meian, Zhang, Yi, Liang, Jun, Guo, Xiuqing, Sheu, Wayne Huey-Herng, Delahanty, Ryan, Guo, Xingyi, Kubo, Michiaki, Yamamoto, Ken, Ohkubo, Takayoshi, Go, Min Jin, Liu, Jian Jun, Gan, Wei, Chen, Ching-Chu, Gao, Yong, Li, Shengxu, Lee, Nanette R, Wu, Chen, Zhou, Xueya, Song, Huaidong, Yao, Jie, Lee, I-Te, Long, Jirong, Tsunoda, Tatsuhiko, Akiyama, Koichi, Takashima, Naoyuki, Cho, Yoon Shin, Ong, Rick TH, Lu, Ling, Chen, Chien-Hsiun, Tan, Aihua, Rice, Treva K, Adair, Linda S, Gui, Lixuan, Allison, Matthew, Lee, Wen-Jane, Cai, Qiuyin, Isomura, Minoru, Umemura, Satoshi, Kim, Young Jin, Seielstad, Mark, Hixson, James, Xiang, Yong-Bing, Isono, Masato, Kim, Bong-Jo, Sim, Xueling, Lu, Wei, Nabika, Toru, Lee, Juyoung, Lim, Wei-Yen, Gao, Yu-Tang, Takayanagi, Ryoichi, Kang, Dae-Hee, Wong, Tien Yin, Hsiung, Chao Agnes, Wu, I-Chien, Juang, Jyh-Ming Jimmy, Shi, Jiajun, Choi, Bo Youl, Aung, Tin, Hu, Frank, Kim, Mi Kyung, Lim, Wei Yen, Wang, Tzung-Dao, Shin, Min-Ho, Lee, Jeannette, Ji, Bu-Tian, Lee, Young-Hoon, Young, Terri L, Shin, Dong Hoon, Chun, Byung-Yeol, Cho, Myeong-Chan, Han, Bok-Ghee, Hwu, Chii-Min, Assimes, Themistocles L, Absher, Devin, Yan, Xiaofei, Kim, Eric, Kuo, Jane Z, Kwon, Soonil, Taylor, Kent D, Chen, Yii-Der I, Rotter, Jerome I, Qi, Lu, Zhu, Dingliang, Wu, Tangchun, Mohlke, Karen L, and Gu, Dongfeng

Subjects
Biological Sciences, Genetics, Obesity, Nutrition, Human Genome, Women's Health, 5'-Nucleotidase, Aldehyde Dehydrogenase, Aldehyde Dehydrogenase, Mitochondrial, Asian People, Blood Proteins, Body Mass Index, Cardiac Myosins, Asia, Eastern, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Glycoproteins, Humans, KCNQ1 Potassium Channel, Male, Myosin Light Chains, Polymorphism, Single Nucleotide, Proteinase Inhibitory Proteins, Secretory, Medical and Health Sciences, Genetics & Heredity
Abstract

Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488-47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10(-13)), ALDH2/MYL2 (rs671, P = 3.40 × 10(-11); rs12229654, P = 4.56 × 10(-9)), ITIH4 (rs2535633, P = 1.77 × 10(-10)) and NT5C2 (rs11191580, P = 3.83 × 10(-8)) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10(-8)) and an additional 14 at P < 1.0 × 10(-3) with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity.

Published
2014

47. 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, Marie, Fleming, Tom, Robinson, Margaret, Thomson, Blake, Graetz, Nicholas, Margono, Christopher, Mullany, Erin C, Biryukov, Stan, Abbafati, Cristiana, Abera, Semaw Ferede, Abraham, Jerry P, Abu-Rmeileh, Niveen ME, Achoki, Tom, AlBuhairan, Fadia S, Alemu, Zewdie A, Alfonso, Rafael, Ali, Mohammed K, Ali, Raghib, Guzman, Nelson Alvis, Ammar, Walid, Anwari, Palwasha, Banerjee, Amitava, Barquera, Simon, Basu, Sanjay, Bennett, Derrick A, Bhutta, Zulfiqar, Blore, Jed, Cabral, Norberto, Nonato, Ismael Campos, Chang, Jung-Chen, Chowdhury, Rajiv, Courville, Karen J, Criqui, Michael H, Cundiff, David K, Dabhadkar, Kaustubh C, Dandona, Lalit, Davis, Adrian, Dayama, Anand, Dharmaratne, Samath D, Ding, Eric L, Durrani, Adnan M, Esteghamati, Alireza, Farzadfar, Farshad, Fay, Derek FJ, Feigin, Valery L, Flaxman, Abraham, Forouzanfar, Mohammad H, Goto, Atsushi, Green, Mark A, Gupta, Rajeev, Hafezi-Nejad, Nima, Hankey, Graeme J, Harewood, Heather C, Havmoeller, Rasmus, Hay, Simon, Hernandez, Lucia, Husseini, Abdullatif, Idrisov, Bulat T, Ikeda, Nayu, Islami, Farhad, Jahangir, Eiman, Jassal, Simerjot K, Jee, Sun Ha, Jeffreys, Mona, Jonas, Jost B, Kabagambe, Edmond K, Khalifa, Shams Eldin Ali Hassan, Kengne, Andre Pascal, Khader, Yousef Saleh, Khang, Young-Ho, Kim, Daniel, Kimokoti, Ruth W, Kinge, Jonas M, Kokubo, Yoshihiro, Kosen, Soewarta, Kwan, Gene, Lai, Taavi, Leinsalu, Mall, Li, Yichong, Liang, Xiaofeng, Liu, Shiwei, Logroscino, Giancarlo, Lotufo, Paulo A, Lu, Yuan, Ma, Jixiang, Mainoo, Nana Kwaku, Mensah, George A, Merriman, Tony R, Mokdad, Ali H, Moschandreas, Joanna, Naghavi, Mohsen, Naheed, Aliya, Nand, Devina, Narayan, KM Venkat, Nelson, Erica Leigh, Neuhouser, Marian L, Nisar, Muhammad Imran, Ohkubo, Takayoshi, Oti, Samuel O, and Pedroza, Andrea

Subjects
Pediatric, Prevention, Obesity, Nutrition, 3.1 Primary prevention interventions to modify behaviours or promote wellbeing, Aetiology, Prevention of disease and conditions, and promotion of well-being, 2.4 Surveillance and distribution, Metabolic and endocrine, Stroke, Good Health and Well Being, Adolescent, Adult, Child, Cost of Illness, Female, Humans, Male, Models, Theoretical, Overweight, Prevalence, Regression Analysis, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundIn 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.MethodsWe 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).FindingsWorldwide, 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.InterpretationBecause 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.FundingBill & Melinda Gates Foundation.

Published
2014

48. Decline in Estimated Glomerular Filtration Rate and Subsequent Risk of End-Stage Renal Disease and Mortality

Author

Coresh, Josef, Turin, Tanvir Chowdhury, Matsushita, Kunihiro, Sang, Yingying, Ballew, Shoshana H, Appel, Lawrence J, Arima, Hisatomi, Chadban, Steven J, Cirillo, Massimo, Djurdjev, Ognjenka, Green, Jamie A, Heine, Gunnar H, Inker, Lesley A, Irie, Fujiko, Ishani, Areef, Ix, Joachim H, Kovesdy, Csaba P, Marks, Angharad, Ohkubo, Takayoshi, Shalev, Varda, Shankar, Anoop, Wen, Chi Pang, de Jong, Paul E, Iseki, Kunitoshi, Stengel, Benedicte, Gansevoort, Ron T, and Levey, Andrew S

Subjects
Kidney Disease, Clinical Research, Renal and urogenital, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Cohort Studies, Creatinine, Disease Progression, Endpoint Determination, Female, Glomerular Filtration Rate, Humans, Kidney Failure, Chronic, Male, Middle Aged, Reference Values, Risk, Medical and Health Sciences, General & Internal Medicine
Abstract

ImportanceThe established chronic kidney disease (CKD) progression end point of end-stage renal disease (ESRD) or a doubling of serum creatinine concentration (corresponding to a change in estimated glomerular filtration rate [GFR] of −57% or greater) is a late event.ObjectiveTo characterize the association of decline in estimated GFR with subsequent progression to ESRD with implications for using lesser declines in estimated GFR as potential alternative end points for CKD progression. Because most people with CKD die before reaching ESRD, mortality risk also was investigated.Data sources and study selectionIndividual meta-analysis of 1.7 million participants with 12,344 ESRD events and 223,944 deaths from 35 cohorts in the CKD Prognosis Consortium with a repeated measure of serum creatinine concentration over 1 to 3 years and outcome data.Data extraction and synthesisTransfer of individual participant data or standardized analysis of outputs for random-effects meta-analysis conducted between July 2012 and September 2013, with baseline estimated GFR values collected from 1975 through 2012.Main outcomes and measuresEnd-stage renal disease (initiation of dialysis or transplantation) or all-cause mortality risk related to percentage change in estimated GFR over 2 years, adjusted for potential confounders and first estimated GFR.ResultsThe adjusted hazard ratios (HRs) of ESRD and mortality were higher with larger estimated GFR decline. Among participants with baseline estimated GFR of less than 60 mL/min/1.73 m2, the adjusted HRs for ESRD were 32.1 (95% CI, 22.3-46.3) for changes of −57% in estimated GFR and 5.4 (95% CI, 4.5-6.4) for changes of −30%. However, changes of −30% or greater (6.9% [95% CI, 6.4%-7.4%] of the entire consortium) were more common than changes of −57% (0.79% [95% CI, 0.52%-1.06%]). This association was strong and consistent across the length of the baseline period (1 to 3 years), baseline estimated GFR, age, diabetes status, or albuminuria. Average adjusted 10-year risk of ESRD (in patients with a baseline estimated GFR of 35 mL/min/1.73 m2) was 99% (95% CI, 95%-100%) for estimated GFR change of −57%, was 83% (95% CI, 71%-93%) for estimated GFR change of −40%, and was 64% (95% CI, 52%-77%) for estimated GFR change of −30% vs 18% (95% CI, 15%-22%) for estimated GFR change of 0%. Corresponding mortality risks were 77% (95% CI, 71%-82%), 60% (95% CI, 56%-63%), and 50% (95% CI, 47%-52%) vs 32% (95% CI, 31%-33%), showing a similar but weaker pattern.Conclusions and relevanceDeclines in estimated GFR smaller than a doubling of serum creatinine concentration occurred more commonly and were strongly and consistently associated with the risk of ESRD and mortality, supporting consideration of lesser declines in estimated GFR (such as a 30% reduction over 2 years) as an alternative end point for CKD progression.

Published
2014

49. Isolated Diastolic Hypertension in the IDACO Study: An Age-Stratified Analysis Using 24-Hour Ambulatory Blood Pressure Measurements

Author

McEvoy, John W., Yang, Wen-Yi, Thijs, Lutgarde, Zhang, Zhen-Yu, Melgarejo, Jesus D., Boggia, José, Hansen, Tine W., Asayama, Kei, Ohkubo, Takayoshi, Dolan, Eamon, Stolarz-Skrzypek, Katarzyna, Malyutina, Sofia, Casiglia, Edoardo, Lind, Lars, Filipovský, Jan, Maestre, Gladys E., Li, Yan, Wang, Ji-Guang, Imai, Yutaka, Kawecka-Jaszcz, Kalina, Sandoya, Edgardo, Narkiewicz, Krzysztof, O’Brien, Eoin, Vanassche, Thomas, and Staessen, Jan A.

Published
2021
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