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1. Additional file 2 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

Author: Harbers, Marjolein C., Beulens, Joline W.J., Boer, Jolanda MA, Karssenberg, Derek, Mackenbach, Joreintje D., Rutters, Femke, Vaartjes, Ilonca, Verschuren, WM Monique, and van der Schouw, Yvonne T.
Abstract: Additional file 2. Components of the DHD15-index and corresponding dietary recommendations and their threshold (minimum score) and cut-off (maximum score) values.
Published: 2021
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2. Additional file 1 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

Author: Harbers, Marjolein C., Beulens, Joline W.J., Boer, Jolanda MA, Karssenberg, Derek, Mackenbach, Joreintje D., Rutters, Femke, Vaartjes, Ilonca, Verschuren, WM Monique, and van der Schouw, Yvonne T.
Abstract: Additional file 1. Distribution of home locations in 2015 in the study population.
Published: 2021
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3. Additional file 4 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

Author: Harbers, Marjolein C., Beulens, Joline W.J., Boer, Jolanda MA, Karssenberg, Derek, Mackenbach, Joreintje D., Rutters, Femke, Vaartjes, Ilonca, Verschuren, WM Monique, and van der Schouw, Yvonne T.
Abstract: Additional file 4. Participant characteristics across quartiles of FFR proportion in the 1500m buffer.
Published: 2021
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4. Additional file 3 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

Author: Harbers, Marjolein C., Beulens, Joline W.J., Boer, Jolanda MA, Karssenberg, Derek, Mackenbach, Joreintje D., Rutters, Femke, Vaartjes, Ilonca, Verschuren, WM Monique, and van der Schouw, Yvonne T.
Abstract: Additional file 3. Participant characteristics across quartiles of FFR proportion in the 1000m buffer.
Published: 2021
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5. Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors

Author: Bakker, Mark K, van der Spek, Rick AA, van Rheenen, Wouter, Morel, Sandrine, Bourcier, Romain, Hostettler, Isabel C, Alg, Varinder S, van Eijk, Kristel R, Koido, Masaru, Akiyama, Masato, Terao, Chikashi, Matsuda, Koichi, Walters, Robin G, Lin, Kuang, Li, Liming, Millwood, Iona Y, Chen, Zhengming, Rouleau, Guy A, Zhou, Sirui, Rannikmäe, Kristiina, Sudlow, Cathie LM, Houlden, Henry, van den Berg, Leonard H, Dina, Christian, Naggara, Olivier, Gentric, Jean-Christophe, Shotar, Eimad, Eugène, François, Desal, Hubert, Winsvold, Bendik S, Børte, Sigrid, Johnsen, Marianne Bakke, Brumpton, Ben M, Sandvei, Marie Søfteland, Willer, Cristen J, Hveem, Kristian, Zwart, John-Anker, Verschuren, WM Monique, Friedrich, Christoph M, Hirsch, Sven, Schilling, Sabine, Dauvillier, Jérôme, Martin, Olivier, HUNT All-In Stroke, China Kadoorie Biobank Collaborative Group, BioBank Japan Project Consortium, ICAN Study Group, CADISP Group, Genetics and Observational Subarachnoid Haemorrhage (GOSH) Study investigators, International Stroke Genetics Consortium (ISGC), Jones, Gregory T, Bown, Matthew J, Ko, Nerissa U, Kim, Helen, Coleman, Jonathan RI, Breen, Gerome, Zaroff, Jonathan G, Klijn, Catharina JM, Malik, Rainer, Dichgans, Martin, Sargurupremraj, Muralidharan, Tatlisumak, Turgut, Amouyel, Philippe, Debette, Stéphanie, Rinkel, Gabriel JE, Worrall, Bradford B, Pera, Joanna, Slowik, Agnieszka, Gaál-Paavola, Emília I, Niemelä, Mika, Jääskeläinen, Juha E, von Und Zu Fraunberg, Mikael, Lindgren, Antti, Broderick, Joseph P, Werring, David J, Woo, Daniel, Redon, Richard, Bijlenga, Philippe, Kamatani, Yoichiro, Veldink, Jan H, and Ruigrok, Ynte M
Subjects: BioBank Japan Project Consortium, Blood Pressure, Cardiovascular, Medical and Health Sciences, International Stroke Genetics Consortium, White People, Asian People, Risk Factors, Clinical Research, Genetics, ICAN Study Group, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Polymorphism, Aetiology, China Kadoorie Biobank Collaborative Group, CADISP Group, Prevention, Smoking, Human Genome, Neurosciences, Endothelial Cells, Intracranial Aneurysm, Single Nucleotide, Subarachnoid Hemorrhage, Biological Sciences, Brain Disorders, Stroke, Case-Control Studies, Hypertension, HUNT All-In Stroke, Genetics and Observational Subarachnoid Haemorrhage (GOSH) Study investigators, Genome-Wide Association Study, Developmental Biology
Abstract: Rupture of an intracranial aneurysm leads to subarachnoid hemorrhage, a severe type of stroke. To discover new risk loci and the genetic architecture of intracranial aneurysms, we performed a cross-ancestry, genome-wide association study in 10,754 cases and 306,882 controls of European and East Asian ancestry. We discovered 17 risk loci, 11 of which are new. We reveal a polygenic architecture and explain over half of the disease heritability. We show a high genetic correlation between ruptured and unruptured intracranial aneurysms. We also find a suggestive role for endothelial cells by using gene mapping and heritability enrichment. Drug-target enrichment shows pleiotropy between intracranial aneurysms and antiepileptic and sex hormone drugs, providing insights into intracranial aneurysm pathophysiology. Finally, genetic risks for smoking and high blood pressure, the two main clinical risk factors, play important roles in intracranial aneurysm risk, and drive most of the genetic correlation between intracranial aneurysms and other cerebrovascular traits.
Published: 2020

6. Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women

Author: Frank J.M. Broekmans, Peter Kraft, Soares Al, Nanette Santoro, Siobán D. Harlow, van der Schouw Yt, Minouk J. Schoemaker, A. H. Eliassen, Anthony J. Swerdlow, Jennifer A. Smith, Renée M.G. Verdiesen, Katherine S. Ruth, Verschuren Wm, Dale P. Sandler, Maria Carolina Borges, van Gils Ch, Anna Murray, Onland-Moret Nc, and Debbie A Lawlor
Subjects: endocrine system, endocrine system diseases, biology, urogenital system, Anti-Müllerian hormone, Single-nucleotide polymorphism, Genome-wide association study, Locus (genetics), medicine.disease, Bioinformatics, Polycystic ovary, female genital diseases and pregnancy complications, Menopause, Breast cancer, Mendelian randomization, biology.protein, medicine
Abstract: Anti-Müllerian hormone (AMH) is expressed by antral stage ovarian follicles in women. Consequently, circulating AMH levels are detectable until menopause. Variation in age-specific AMH levels has been associated with breast cancer and polycystic ovary syndrome (PCOS), amongst other diseases. Identification of genetic variants underlying variation in AMH levels could provide clues about the physiological mechanisms that explain these AMH-disease associations. To date, only one variant in MCM8 has been identified to be associated with circulating AMH levels in women. We aimed to identify additional variants for AMH through a GWAS meta-analysis including data from 7049 premenopausal women of European ancestry, which more than doubles the sample size of the largest previous GWAS. We identified four loci associated with AMH levels at p < 5×10−8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41, and CDCA7. The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among SNPs for AMH levels and for age at menopause (rg= 0.82, FDR=0.003). Exploratory Mendelian randomization analyses did not support a causal effect of AMH on breast cancer or PCOS risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored. In conclusion, we identified a variant in the AMH gene and three other loci that may affect circulating AMH levels in women.
Published: 2020

7. Glycated hemoglobin measurement and prediction of cardiovascular disease

Author: Emerging Risk Factors Collaboration, Di Angelantonio E, Gao P, Khan H, Butterworth AS, Wormser D, Kaptoge S, Kondapally Seshasai SR, Thompson A, Sarwar N, Willeit P, Ridker PM, Barr EL, Khaw KT, Psaty BM, Brenner H, Balkau B, Dekker JM, Lawlor DA, Daimon M, Willeit J, Njølstad I, Nissinen A, Brunner EJ, Kuller LH, Price JF, Sundström J, Knuiman MW, Feskens EJ, Verschuren WM, Wald N, Bakker SJ, Whincup PH, Ford I, Goldbourt U, Gómez de la Cámara A, Gallacher J, Simons LA, Rosengren A, Sutherland SE, Björkelund C, Blazer DG, Wassertheil Smoller S, Onat A, Marín Ibañez A, Casiglia E, Jukema JW, Simpson LM, Giampaoli S, Nordestgaard BG, Selmer R, Wennberg P, Kauhanen J, Salonen JT, Dankner R, Barrett Connor E, Kavousi M, Gudnason V, Evans D, Wallace RB, Cushman M, D'Agostino RB Sr, Umans JG, Kiyohara Y, Nakagawa H, Sato S, Gillum RF, Folsom AR, van der Schouw YT, Moons KG, Griffin SJ, Sattar N, Wareham NJ, Selvin E, Thompson SG, Danesh J. Collaborators Simpson LM, Coresh J, Wagenknecht L, Shaw JE, Zimmet PZ, Magliano D, Wannamethee SG, Morris RW, Kiechl S, Santer P, Bonora E, Casas JP, Ebrahim S, Ben Shlomo Y, Yarnell JW, Elwood P, Bachman DL, Nietert PJ, Håheim LL, Søgaard AJ, Tybjaerg Hansen A, Frikke Schmidt R, Benn M, Palmieri L, Vanuzzo D, Bonnet F, Copin N, Roussel R, Gómez Gerique JA, Rubio Herrera MA, Gutiérrez Fuentes JA, Friedlander Y, McCallum J, Simons J, Lee AJ, McLachlan S, Taylor JO, Guralnik JM, Phillips CL, Evans DA, Kohout F, Cohen H, George L, Fillenbaum G, McGloin JM, Khaw K., Schöttker B, Müller H, Rothenbacher D, Jansson J., Hallmans G, Tuomilehto J, Donfrancesco C, Woodward M, Oizumi T, Kayama T, Kato T, Danker R, Chetrit A, Wilhelmsen L, Eriksson H, Lappas G, Bengtsson C, Lissner L, Skoog I, Cremer P, Arima H, Ninomiya T, Hata J, Nijpels G, Stehouwer CD, Tuomainen T., Voutilainen S, Kurl S, de Boer IH, Bertoni AG, Veschuren WM, Dullaart RP, Lambers Heerspink HJ, Hilege HL, Trompet S, Stott DJ, Dagenais GR, Cantin B, Dehghan D, Hofman A, Franco OH, Tunstall Pedoe H, Lee E, Best L, Howard BV, Can G, Ademoğlu E, Sakurai M, Nakamura K, Morikawa Y, Løchen M., Mathiesen EB, Wilsgaard T, Byberg L, Cederholm T, Olsson E, Pradhan AD, Cook NR, Kromhout D, Walker M, Watson S, Burgess S, Gregson J, Harshfield E, Pennells L, Spackman S, Warnakula S, Wood AM, Danesh J., PANICO, SALVATORE, Emerging Risk Factors, Collaboration, Di Angelantonio, E, Gao, P, Khan, H, Butterworth, A, Wormser, D, Kaptoge, S, Kondapally Seshasai, Sr, Thompson, A, Sarwar, N, Willeit, P, Ridker, Pm, Barr, El, Khaw, Kt, Psaty, Bm, Brenner, H, Balkau, B, Dekker, Jm, Lawlor, Da, Daimon, M, Willeit, J, Njølstad, I, Nissinen, A, Brunner, Ej, Kuller, Lh, Price, Jf, Sundström, J, Knuiman, Mw, Feskens, Ej, Verschuren, Wm, Wald, N, Bakker, Sj, Whincup, Ph, Ford, I, Goldbourt, U, Gómez de la Cámara, A, Gallacher, J, Simons, La, Rosengren, A, Sutherland, Se, Björkelund, C, Blazer, Dg, Wassertheil Smoller, S, Onat, A, Marín Ibañez, A, Casiglia, E, Jukema, Jw, Simpson, Lm, Giampaoli, S, Nordestgaard, Bg, Selmer, R, Wennberg, P, Kauhanen, J, Salonen, Jt, Dankner, R, Barrett Connor, E, Kavousi, M, Gudnason, V, Evans, D, Wallace, Rb, Cushman, M, D'Agostino RB, Sr, Umans, Jg, Kiyohara, Y, Nakagawa, H, Sato, S, Gillum, Rf, Folsom, Ar, van der Schouw, Yt, Moons, Kg, Griffin, Sj, Sattar, N, Wareham, Nj, Selvin, E, Thompson, Sg, Danesh J., Collaborators Simpson LM, Coresh, J, Wagenknecht, L, Shaw, Je, Zimmet, Pz, Magliano, D, Wannamethee, Sg, Morris, Rw, Kiechl, S, Santer, P, Bonora, E, Casas, Jp, Ebrahim, S, Ben Shlomo, Y, Yarnell, Jw, Elwood, P, Bachman, Dl, Nietert, Pj, Håheim, Ll, Søgaard, Aj, Tybjaerg Hansen, A, Frikke Schmidt, R, Benn, M, Palmieri, L, Vanuzzo, D, Panico, Salvatore, Bonnet, F, Copin, N, Roussel, R, Gómez Gerique, Ja, Rubio Herrera, Ma, Gutiérrez Fuentes, Ja, Friedlander, Y, Mccallum, J, Simons, J, Lee, Aj, Mclachlan, S, Taylor, Jo, Guralnik, Jm, Phillips, Cl, Evans, Da, Kohout, F, Cohen, H, George, L, Fillenbaum, G, Mcgloin, Jm, Khaw, K., Schöttker, B, Müller, H, Rothenbacher, D, Jansson, J., Hallmans, G, Tuomilehto, J, Donfrancesco, C, Woodward, M, Oizumi, T, Kayama, T, Kato, T, Danker, R, Chetrit, A, Wilhelmsen, L, Eriksson, H, Lappas, G, Bengtsson, C, Lissner, L, Skoog, I, Cremer, P, Arima, H, Ninomiya, T, Hata, J, Nijpels, G, Stehouwer, Cd, Tuomainen, T., Voutilainen, S, Kurl, S, de Boer, Ih, Bertoni, Ag, Veschuren, Wm, Dullaart, Rp, Lambers Heerspink, Hj, Hilege, Hl, Trompet, S, Stott, Dj, Dagenais, Gr, Cantin, B, Dehghan, D, Hofman, A, Franco, Oh, Tunstall Pedoe, H, Lee, E, Best, L, Howard, Bv, Can, G, Ademoğlu, E, Sakurai, M, Nakamura, K, Morikawa, Y, Løchen, M., Mathiesen, Eb, Wilsgaard, T, Byberg, L, Cederholm, T, Olsson, E, Pradhan, Ad, Cook, Nr, Kromhout, D, Walker, M, Watson, S, Burgess, S, Gregson, J, Harshfield, E, Pennells, L, Spackman, S, Warnakula, S, Wood, Am, and Danesh, J.
Published: 2014

8. 2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts): Developed with the special contribution of the European Association for Cardiovascular Prevention Rehabilitation (EACPR)

Author: Authors/Task Force Members, Piepoli MF, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL, Cooney MT, Corrà U, Cosyns B, Deaton C, Graham I, Hall MS, Hobbs FD, Løchen ML, Löllgen H, Marques-Vidal P, Perk J, Prescott E, Redon J, Richter DJ, Sattar N, Smulders Y, Tiberi M, van der Worp HB, van Dis I, Verschuren WM, Additional Contributor: Simone Binno (Italy), Document Reviewers, De Backer G, Roffi M, Aboyans V, Bachl N, Bueno H, Carerj S, Cho L, Cox J, De Sutter J, Egidi G, Fisher M, Fitzsimons D, Franco OH, Guenoun M, Jennings C, Jug B, Kirchhof P, Kotseva K, Lip GY, Mach F, Mancia G, Bermudo FM, Mezzani A, Niessner A, Ponikowski P, Rauch B, Rydén L, Stauder A, Turc G, Wiklund O, Windecker S, and Zamorano JL
Published: 2016

9. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

Author: Swerdlow, Daniel I, Preiss, David, Kuchenbaecker, Karoline B, Holmes, Michael V, Engmann, Jorgen EL, Shah, Tina, Sofat, Reecha, Stender, Stefan, Johnson, Paul CD, Scott, Robert A, Leusink, Maarten, Verweij, Niek, Sharp, Stephen J, Guo, Yiran, Giambartolomei, Claudia, Chung, Christina, Peasey, Anne, Amuzu, Antoinette, Li, KaWah, Palmen, Jutta, Howard, Philip, Cooper, Jackie A, Drenos, Fotios, Li, Yun R, Lowe, Gordon, Gallacher, John, Stewart, Marlene CW, Tzoulaki, Ioanna, Buxbaum, Sarah G, van der A, Daphne L, Forouhi, Nita G, Onland-Moret, N Charlotte, van der Schouw, Yvonne T, Schnabel, Renate B, Hubacek, Jaroslav A, Kubinova, Ruzena, Baceviciene, Migle, Tamosiunas, Abdonas, Pajak, Andrzej, Topor-Madry, Roman, Stepaniak, Urszula, Malyutina, Sofia, Baldassarre, Damiano, Sennblad, Bengt, Tremoli, Elena, de Faire, Ulf, Veglia, Fabrizio, Ford, Ian, Jukema, J Wouter, Westendorp, Rudi GJ, de Borst, Gert Jan, de Jong, Pim A, Algra, Ale, Spiering, Wilko, Maitland-van der Zee, Anke H, Klungel, Olaf H, de Boer, Anthonius, Doevendans, Pieter A, Eaton, Charles B, Robinson, Jennifer G, Duggan, David, DIAGRAM Consortium, MAGIC Consortium, InterAct Consortium, Kjekshus, John, Downs, John R, Gotto, Antonio M, Keech, Anthony C, Marchioli, Roberto, Tognoni, Gianni, Sever, Peter S, Poulter, Neil R, Waters, David D, Pedersen, Terje R, Amarenco, Pierre, Nakamura, Haruo, McMurray, John JV, Lewsey, James D, Chasman, Daniel I, Ridker, Paul M, Maggioni, Aldo P, Tavazzi, Luigi, Ray, Kausik K, Seshasai, Sreenivasa Rao Kondapally, Manson, JoAnn E, Price, Jackie F, Whincup, Peter H, Morris, Richard W, Lawlor, Debbie A, Smith, George Davey, Ben-Shlomo, Yoav, Schreiner, Pamela J, Fornage, Myriam, Siscovick, David S, Cushman, Mary, Kumari, Meena, Wareham, Nick J, Verschuren, WM Monique, Redline, Susan, and Patel, Sanjay R
Subjects: Male, HDL, Clinical Trials and Supportive Activities, DIAGRAM Consortium, Medical and Health Sciences, Body Mass Index, LDL, Clinical Research, Risk Factors, General & Internal Medicine, Genetics, Diabetes Mellitus, Humans, Genetic Testing, Polymorphism, Metabolic and endocrine, Nutrition, Aged, Randomized Controlled Trials as Topic, MAGIC Consortium, Diabetes, Body Weight, Evaluation of treatments and therapeutic interventions, Single Nucleotide, InterAct Consortium, Middle Aged, Cholesterol, 6.1 Pharmaceuticals, Hydroxymethylglutaryl CoA Reductases, Female, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Type 2
Abstract: BackgroundStatins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target.MethodsWe used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis.FindingsData were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials).InterpretationThe increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition.FundingThe funding sources are cited at the end of the paper.
Published: 2015

10. Design and cohortdescription of the InterAct Project: an examination of the interaction of geneticand lifestyle factors on the incidence of type 2 diabetes in the EPIC Study

Author: InterAct Consortium, Langenberg C, Sharp S, Forouhi NG, Franks PW, Schulze MB, Kerrison N, Ekelund U, Barroso I, Tormo MJ, Spranger J, Griffin S, van der Schouw YT, Amiano P, Ardanaz E, Arriola L, Balkau B, Barricarte A, Beulens JW, Boeing H, Bueno de Mesquita HB, Buijsse B, Chirlaque Lopez MD, Clavel Chapelon F, Crowe FL, de Lauzon Guillan B, Deloukas P, Dorronsoro M, Drogan D, Froguel P, Gonzalez C, Grioni S, Groop L, Groves C, Hainaut P, Halkjaer J, Hallmans G, Hansen T, Huerta Castaño JM, Kaaks R, Key TJ, Khaw KT, Koulman A, Mattiello A, Navarro C, Nilsson P, Norat T, Overvad K, Palla L, Palli D, Pedersen O, Peeters PH, Quirós JR, Ramachandran A, Rodriguez Suarez L, Rolandsson O, Romaguera D, Romieu I, Sacerdote C, Sánchez MJ, Sandbaek A, Slimani N, Sluijs I, Spijkerman AM, Teucher B, Tjonneland A, Tumino R, van der A. DL, Verschuren WM, Tuomilehto J, Feskens E, McCarthy M, Riboli E, Wareham N.J., PANICO, SALVATORE, Interact, Consortium, Langenberg, C, Sharp, S, Forouhi, Ng, Franks, Pw, Schulze, Mb, Kerrison, N, Ekelund, U, Barroso, I, Panico, Salvatore, Tormo, Mj, Spranger, J, Griffin, S, van der Schouw, Yt, Amiano, P, Ardanaz, E, Arriola, L, Balkau, B, Barricarte, A, Beulens, Jw, Boeing, H, Bueno de Mesquita, Hb, Buijsse, B, Chirlaque Lopez, Md, Clavel Chapelon, F, Crowe, Fl, de Lauzon Guillan, B, Deloukas, P, Dorronsoro, M, Drogan, D, Froguel, P, Gonzalez, C, Grioni, S, Groop, L, Groves, C, Hainaut, P, Halkjaer, J, Hallmans, G, Hansen, T, Huerta Castaño, Jm, Kaaks, R, Key, Tj, Khaw, Kt, Koulman, A, Mattiello, A, Navarro, C, Nilsson, P, Norat, T, Overvad, K, Palla, L, Palli, D, Pedersen, O, Peeters, Ph, Quirós, Jr, Ramachandran, A, Rodriguez Suarez, L, Rolandsson, O, Romaguera, D, Romieu, I, Sacerdote, C, Sánchez, Mj, Sandbaek, A, Slimani, N, Sluijs, I, Spijkerman, Am, Teucher, B, Tjonneland, A, Tumino, R, van der A., Dl, Verschuren, Wm, Tuomilehto, J, Feskens, E, Mccarthy, M, Riboli, E, and Wareham, N. J.
Published: 2011

11. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data

Author: Holmes, Michael V, Dale, Caroline E, Zuccolo, Luisa, Silverwood, Richard J, Guo, Yiran, Ye, Zheng, Prieto-Merino, David, Dehghan, Abbas, Trompet, Stella, Wong, Andrew, Cavadino, Alana, Drogan, Dagmar, Padmanabhan, Sandosh, Li, Shanshan, Yesupriya, Ajay, Leusink, Maarten, Sundstrom, Johan, Hubacek, Jaroslav A, Pikhart, Hynek, Swerdlow, Daniel I, Panayiotou, Andrie G, Borinskaya, Svetlana A, Finan, Chris, Shah, Sonia, Kuchenbaecker, Karoline B, Shah, Tina, Engmann, Jorgen, Folkersen, Lasse, Eriksson, Per, Ricceri, Fulvio, Melander, Olle, Sacerdote, Carlotta, Gamble, Dale M, Rayaprolu, Sruti, Ross, Owen A, McLachlan, Stela, Vikhireva, Olga, Sluijs, Ivonne, Scott, Robert A, Adamkova, Vera, Flicker, Leon, Bockxmeer, Frank M van, Power, Christine, Marques-Vidal, Pedro, Meade, Tom, Marmot, Michael G, Ferro, Jose M, Paulos-Pinheiro, Sofia, Humphries, Steve E, Talmud, Philippa J, Mateo Leach, Irene, Verweij, Niek, Linneberg, Allan, Skaaby, Tea, Doevendans, Pieter A, Cramer, Maarten J, van der Harst, Pim, Klungel, Olaf H, Dowling, Nicole F, Dominiczak, Anna F, Kumari, Meena, Nicolaides, Andrew N, Weikert, Cornelia, Boeing, Heiner, Ebrahim, Shah, Gaunt, Tom R, Price, Jackie F, Lannfelt, Lars, Peasey, Anne, Kubinova, Ruzena, Pajak, Andrzej, Malyutina, Sofia, Voevoda, Mikhail I, Tamosiunas, Abdonas, Maitland-van der Zee, Anke H, Norman, Paul E, Hankey, Graeme J, Bergmann, Manuela M, Hofman, Albert, Franco, Oscar H, Cooper, Jackie, Palmen, Jutta, Spiering, Wilko, de Jong, Pim A, Kuh, Diana, Hardy, Rebecca, Uitterlinden, Andre G, Ikram, M Arfan, Ford, Ian, Hyppönen, Elina, Almeida, Osvaldo P, Wareham, Nicholas J, Khaw, Kay-Tee, Hamsten, Anders, Husemoen, Lise Lotte N, Tjønneland, Anne, Tolstrup, Janne S, Rimm, Eric, Beulens, Joline WJ, and Verschuren, WM Monique
Subjects: Genetic Markers, Adult, Male, Alcohol Drinking, Genotype, Clinical Sciences, Coronary Disease, Cardiovascular, Oral and gastrointestinal, Substance Misuse, Alcohol Use and Health, Clinical Research, Models, General & Internal Medicine, Genetics, 2.1 Biological and endogenous factors, Humans, Aetiology, Polymorphism, Aged, Alcohol Dehydrogenase, Single Nucleotide, InterAct Consortium, Statistical, Middle Aged, Mendelian Randomization Analysis, Brain Disorders, Stroke, Alcoholism, Heart Disease, Good Health and Well Being, Public Health and Health Services, Female, Biomarkers
Abstract: ObjectiveTo use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease.DesignMendelian randomisation meta-analysis of 56 epidemiological studies.Participants261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers.Main outcome measuresOdds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption.ResultsCarriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)).ConclusionsIndividuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health.
Published: 2014

12. Susceptibility to Chronic Mucus Hypersecretion, a Genome Wide Association Study

Author: Dijkstra, Akkelies E., Smolonska, J, Van Den Berge, M, Wijmenga, C, Zanen, P, Luinge, MA, Platteel, M, Lammers, JW, Dahlback, M, Tosh, K, Hiemstra, PS, Sterk, PJ, Spira, A, Vestbo, J, Nordestgaard, BG, Benn, M, Nielsen, SF, Dahl, M, Verschuren, WM, Picavet, HSJ, Smit, HA, Owsijewitsch, M, Kauczor, HU, De Koning, HJ, Nizankowska-Mogilnicka, E, Mejza, F, Nastalek, P, Van Diemen, CC, Cho, MH, Silverman, EK, Crapo, JD, Beaty, TH, Lomas, DA, Bakke, Per, Gulsvik, Amund, Bosse, Y, Obeidat, MA, Loth, DW, Lahousse, L, Rivadeneira, F, Uitterlinden, AG, Hofman, A, Stricker, BH, Brusselle, GG, Van Duijn, CM, Brouwer, U, Koppelman, GH, Vonk, JM, Nawijn, MC, Groen, HJM, Timens, W, Boezen, HM, Postma, DS, Alizadeh, BZ, De Boer, RA, Bruinenberg, M, Franke, L, Van Der Harst, P, Hillege, HL, Van Der Klauw, MM, Navis, G, Ormel, J, Rosmalen, J, Slaets, JP, Snieder, H, Stolk, RP, Wolffenbuttel, B, Amsterdam institute for Infection and Immunity, Pulmonology, Clinical Chemistry, Public Health, Otorhinolaryngology and Head and Neck Surgery, Epidemiology, Internal Medicine, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Life Course Epidemiology (LCE), Damage and Repair in Cancer Development and Cancer Treatment (DARE), and Guided Treatment in Optimal Selected Cancer Patients (GUTS)
Subjects: CHROMATIN, Male, Chronic bronchitis, Pulmonology, Epidemiology, OBSTRUCTIVE PULMONARY-DISEASE CHRONIC-BRONCHITIS GENETIC EPIDEMIOLOGY GENERAL-POPULATION BINDING-PROTEIN RISK-FACTORS COPD CHROMATIN SATB1 EXPRESSION, lcsh:Medicine, Genome-wide association study, Lung/metabolism, Mucus/metabolism, Drug Addiction, Matrix Attachment Region Binding Proteins/genetics, Recreational Drug Addiction, Cohort Studies, Pulmonary Disease, Chronic Obstructive, Medicine and Health Sciences, Psychology, Clinical Epidemiology, lcsh:Science, Lung, Cells, Cultured, GENETIC EPIDEMIOLOGY, GENERAL-POPULATION, Aged, 80 and over, education.field_of_study, Multidisciplinary, Medical sciences: 700::Basic medical, dental and veterinary sciences: 710::Medical genetics: 714 [VDP], Genomics, respiratory system, Middle Aged, 3. Good health, Functional Genomics, BINDING-PROTEIN, medicine.anatomical_structure, CHRONIC-BRONCHITIS, Genetic Epidemiology, Medical sciences: 700::Clinical medical sciences: 750::Lung diseases: 777 [VDP], Epidemiological Methods and Statistics, Female, medicine.symptom, Transcriptome Analysis, Medisinske fag: 700::Klinisk medisinske fag: 750::Lungesykdommer: 777 [VDP], Research Article, EXPRESSION, Adult, Chronic Obstructive Pulmonary Disease, Population, Addiction, Single-nucleotide polymorphism, Biology, Environmental and Occupational Lung Diseases, OBSTRUCTIVE PULMONARY-DISEASE, Polymorphism, Single Nucleotide, Environmental Epidemiology, SATB1, SDG 3 - Good Health and Well-being, medicine, Genome-Wide Association Studies, Genetics, SNP, COPD, Humans, education, Lifecourse Epidemiology, Aged, lcsh:R, Biology and Life Sciences, Computational Biology, Correction, Matrix Attachment Region Binding Proteins, Genome Analysis, Pulmonary Disease, Chronic Obstructive/genetics, Medisinske fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710::Medisinsk genetikk: 714 [VDP], Mucus, Genetic epidemiology, Immunology, Respiratory Infections, Chronic Disease, RISK-FACTORS, Sputum, lcsh:Q, Genome Expression Analysis, Genome-Wide Association Study
Abstract: Background: Chronic mucus hypersecretion (CMH) is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA) study of CMH in Caucasian populations. Methods: GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and metaanalysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (>= 20 pack-years). Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP). Results: A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25610(-6), OR = 1.17), located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1) on chromosome 3. The risk allele (G) was associated with higher mRNA expression of SATB1 (4.3610 29) in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture. Conclusions: Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH. Background: Chronic mucus hypersecretion (CMH) is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA) study of CMH in Caucasian populations. Methods: GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years). Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP). Results: A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25x10 -6, OR = 1.17), located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1) on chromosome 3. The risk allele (G) was associated with higher mRNA expression of SATB1 (4.3x10 -9) in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture. Conclusions: Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH.
Published: 2013
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13. Loci influencing blood pressure identified using a cardiovascular gene-centric array (vol 22, pg 1663, 2013)

Author: Ganesh, SK, Tragante, V, Guo, W, Guo, YR, Lanktree, MB, Smith, EN, Johnson, T, Castillo, BA, Barnard, J, Baumert, J, Chang, YPC, Elbers, CC, Farrall, M, Fischer, ME, Franceschini, N, Gaunt, TR, Gho, JMIH, Gieger, C, Gong, Y, Isaacs, Aaron, Kleber, ME, Leach, IM, McDonough, CW, Meijs, MFL, Mellander, O, Molony, CM, Nolte, IM (Ilja), Padmanabhan, S, Price, TS, Rajagopalan, R, Shaffer, J, Shah, S, Shen, HQ, Soranzo, N, van der Most, PJ, Van Iperen, EPA, van Setten, J, Vonk, JM, Zhang, Lei, Beitelshees, AL, Berenson, GS, Bhatt, DL, Boer, JMA, Boerwinkle, E, Burkley, B, Burt, A, Chakravarti, A, Chen, W, Cooper-DeHoff, RM, Curtis, SP, Dreisbach, A, Duggan, D, Ehret, GB, Fabsitz, RR, Fornage, M, Fox, E, Furlong, CE, Gansevoort, RT, Hofker, MH, Hovingh, GK, Kirkland, SA, Kottke-Marchant, K, Kutlar, A, Lacroix, AZ, Langaee, TY, Li, YR, Lin, HH, Liu, K, Maiwald, S, Malik, R, Murugesan, G, Newton-Cheh, C, OConnell, JR, Onland-Moret, NC, Ouwehand, WH, Palmas, W, Penninx, BW, Pepine, CJ, Pettinger, M, Polak, JF, Ramachandran, VS, Ranchalis, J, Redline, S, Ridker, PM, Rose, LM, Scharnag, H, Schork, NJ, Shimbo, D, Shuldiner, AR, Srinivasan, SR (Sathanur), Stolk, RP (Ronald), Taylor, HA, Thorand, B, Trip, MD, Duijn, Cornelia, Verschuren, WM, Wijmenga, C, Winkelmann, BR, Wyatt, S, Young, JH, Boehm, BO, Caulfield, MJ, Chasman, DI, Davidson, KW, Doevendans, PA, FitzGerald, GA, Gums, JG, Hakonarson, H, Hillege, HL, Illig, T, Jarvik, GP, Johnson, JA, Kastelein, JJP, Koenig, W, Marz, W, Mitchell, BD, Murray, SS, Oldehinkel, AJ (A.), Rader, DJ, Reilly, MP, Reiner, AP, Schadt, EE, Silverstein, RL, Snieder, H, Stanton, AV, Uitterlinden, André, van der Harst, P, van der Schouw, YT, Samani, NJ, Johnson, AD, Munroe, PB, de Bakker, PIW, Zhu, XF, Levy, D, Keating, BJ, Asselbergs, FW, Epidemiology, Public Health, Clinical Genetics, Immunology, Child and Adolescent Psychiatry / Psychology, and Internal Medicine
Published: 2013

14. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

Author: Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J. Tipping RW, Ford CE, Pressel SL, Folsom AR, Chambless LE, Wagenknecht LE, Panagiotakos DB, Pitsavos C, Chrysohoou C, Stefanadis C, Knuiman M, Whincup PH, Wannamethee SG, Morris RW, Kiechl S, Willeit J, Oberhollenzer F, Mayr A, Wald N, Ebrahim S, Yarnell JW, Gallacher J, Casiglia E, Tikhonoff V, Nietert PJ, Sutherland SE, Bachman DL, Keil JE, de Boer IH, Kizer JR, Mukamal KJ, Tybjaerg Hansen A, Nordestgaard BG, Benn M, Frikke Schmidt R, Palmieri L, Vanuzzo D, Pilotto L, de la Cámara AG, Rubio MA, Simons L, McCallum J, Friedlander Y, Fowkes FG, Lee AJ, Taylor J, Guralnik JM, Phillips CL, Wallace R, Blazer DG, Khaw KT, Brenner H, Raum E, Müller H, Rothenbacher D, Jansson JH, Wennberg P, Nissinen A, Donfrancesco C, Giampaoli S, Salomaa V, Harald K, Jousilahti P, Vartiainen E, Woodward M, D'Agostino RB, Vasan RS, Fox CS, Pencina MJ, Bladbjerg E, Jørgensen T, Møller L, Jespersen J, Dankner R, Chetrit A, Lubin F, Wilhelmsen L, Eriksson H, Svärdsudd K, Welin L, Rosengren A, Lappas G, Björkelund C, Lissner L, Bengtsson C, Cremer P, Nagel D, Strandberg TE, Tilvis RS, Miettinen TA, Kiyohara Y, Arima H, Doi Y, Ninomiya T, Rodriguez B, Dekker JM, Nijpels G, Rimm E, Pai JK, Sato S, Iso H, Kitamura A, Noda H, Goldbourt U, Nyyssönen K, Tuomainen TP, Salonen JT, Deeg D, Poppelaars JL, Meade TW, Cooper JA, Hedblad B, Berglund G, Engström G, Verschuren WM, Blokstra A, Cushman M, Psaty BM, Shea S, Döring A, Koenig W, Meisinger C, Mraz W, Bueno de Mesquita HB, Fletcher A, Kuller LH, Grandits G, Selmer R, Tverdal A, Nystad W, Gillum R, Mussolino M, Hankinson S, Manson JE, Bauer KA, Davidson KW, Kirkland S, Shaffer J, Korin MR, Holme I, Ducimetiere P, Jouven X, Bakker SJ, Gansevoort RT, Hillege HL, Crespo CJ, Garcia Palmieri MR, Amouyel P, Arveiler D, Evans A, Ferrières J, Schulte H, Assmann G, Westendorp RG, Buckley BM, Packard CJ, Cantin B, Lamarche B, Després JP, Dagenais GR, Barrett Connor E, Wingard DL, Bettencourt R, Gudnason V, Aspelund T, Sigurdsson G, Thorsson B, Trevisan M, Witteman J, Kardys I, Breteler M, Hofman A, Tunstall Pedoe H, Tavendale R, Lowe GD, Howard BV, Zhang Y, Best L, Umans J, Ben Shlomo Y, Davey Smith G, Onat A, Hergenç G, Can G, Njølstad I, Mathiesen EB, Løchen ML, Wilsgaard T, Zethelius B, Risérus U, Berne C, Gaziano JM, Ridker P, Ulmer H, Diem G, Concin H, Tosetto A, Rodeghiero F, Tinker L, Liu S, Marmot IM, Clarke R, Collins R, Brunner E, Shipley M, Buring J, Shepherd J, Cobbe SM, Ford I, Robertson M, Ibañez AM, Feskens EJ, Kromhout D, Walker M, Watson S, Alexander M, Erqou S, Haycock P, Perry PL, Thompson SG, Wood AM, Wormser D, Danesh J., PANICO, SALVATORE, Interne Geneeskunde, RS: NUTRIM - R1 - Metabolic Syndrome, RS: CARIM School for Cardiovascular Diseases, Emerging Risk Factors, Collaboration, Sarwar, N, Gao, P, Seshasai, Sr, Gobin, R, Kaptoge, S, Di Angelantonio, E, Ingelsson, E, Lawlor, Da, Selvin, E, Stampfer, M, Stehouwer, Cd, Lewington, S, Pennells, L, Thompson, A, Sattar, N, White, Ir, Ray, Kk, Danesh J., Tipping RW, Ford, Ce, Pressel, Sl, Folsom, Ar, Chambless, Le, Wagenknecht, Le, Panagiotakos, Db, Pitsavos, C, Chrysohoou, C, Stefanadis, C, Knuiman, M, Whincup, Ph, Wannamethee, Sg, Morris, Rw, Kiechl, S, Willeit, J, Oberhollenzer, F, Mayr, A, Wald, N, Ebrahim, S, Yarnell, Jw, Gallacher, J, Casiglia, E, Tikhonoff, V, Nietert, Pj, Sutherland, Se, Bachman, Dl, Keil, Je, de Boer, Ih, Kizer, Jr, Mukamal, Kj, Tybjaerg Hansen, A, Nordestgaard, Bg, Benn, M, Frikke Schmidt, R, Palmieri, L, Panico, Salvatore, Vanuzzo, D, Pilotto, L, de la Cámara, Ag, Rubio, Ma, Simons, L, Mccallum, J, Friedlander, Y, Fowkes, Fg, Lee, Aj, Taylor, J, Guralnik, Jm, Phillips, Cl, Wallace, R, Blazer, Dg, Khaw, Kt, Brenner, H, Raum, E, Müller, H, Rothenbacher, D, Jansson, Jh, Wennberg, P, Nissinen, A, Donfrancesco, C, Giampaoli, S, Salomaa, V, Harald, K, Jousilahti, P, Vartiainen, E, Woodward, M, D'Agostino, Rb, Vasan, R, Fox, C, Pencina, Mj, Bladbjerg, E, Jørgensen, T, Møller, L, Jespersen, J, Dankner, R, Chetrit, A, Lubin, F, Wilhelmsen, L, Eriksson, H, Svärdsudd, K, Welin, L, Rosengren, A, Lappas, G, Björkelund, C, Lissner, L, Bengtsson, C, Cremer, P, Nagel, D, Strandberg, Te, Tilvis, R, Miettinen, Ta, Kiyohara, Y, Arima, H, Doi, Y, Ninomiya, T, Rodriguez, B, Dekker, Jm, Nijpels, G, Rimm, E, Pai, Jk, Sato, S, Iso, H, Kitamura, A, Noda, H, Goldbourt, U, Nyyssönen, K, Tuomainen, Tp, Salonen, Jt, Deeg, D, Poppelaars, Jl, Meade, Tw, Cooper, Ja, Hedblad, B, Berglund, G, Engström, G, Verschuren, Wm, Blokstra, A, Cushman, M, Psaty, Bm, Shea, S, Döring, A, Koenig, W, Meisinger, C, Mraz, W, Bueno de Mesquita, Hb, Fletcher, A, Kuller, Lh, Grandits, G, Selmer, R, Tverdal, A, Nystad, W, Gillum, R, Mussolino, M, Hankinson, S, Manson, Je, Bauer, Ka, Davidson, Kw, Kirkland, S, Shaffer, J, Korin, Mr, Holme, I, Ducimetiere, P, Jouven, X, Bakker, Sj, Gansevoort, Rt, Hillege, Hl, Crespo, Cj, Garcia Palmieri, Mr, Amouyel, P, Arveiler, D, Evans, A, Ferrières, J, Schulte, H, Assmann, G, Westendorp, Rg, Buckley, Bm, Packard, Cj, Cantin, B, Lamarche, B, Després, Jp, Dagenais, Gr, Barrett Connor, E, Wingard, Dl, Bettencourt, R, Gudnason, V, Aspelund, T, Sigurdsson, G, Thorsson, B, Trevisan, M, Witteman, J, Kardys, I, Breteler, M, Hofman, A, Tunstall Pedoe, H, Tavendale, R, Lowe, Gd, Howard, Bv, Zhang, Y, Best, L, Umans, J, Ben Shlomo, Y, Davey Smith, G, Onat, A, Hergenç, G, Can, G, Njølstad, I, Mathiesen, Eb, Løchen, Ml, Wilsgaard, T, Zethelius, B, Risérus, U, Berne, C, Gaziano, Jm, Ridker, P, Ulmer, H, Diem, G, Concin, H, Tosetto, A, Rodeghiero, F, Tinker, L, Liu, S, Marmot, Im, Clarke, R, Collins, R, Brunner, E, Shipley, M, Buring, J, Shepherd, J, Cobbe, Sm, Ford, I, Robertson, M, Ibañez, Am, Feskens, Ej, Kromhout, D, Walker, M, Watson, S, Alexander, M, Erqou, S, Haycock, P, Perry, Pl, Thompson, Sg, Wood, Am, Wormser, D, Danesh, J., and University of Groningen
Subjects: Adult, Blood Glucose, Male, medicine.medical_specialty, PATHOPHYSIOLOGY, 030209 endocrinology & metabolism, Coronary Disease, Disease, 030204 cardiovascular system & hematology, THERAPY, Diabetes Complications, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Diabetes mellitus, Internal medicine, General & Internal Medicine, medicine, Diabetes Mellitus, Humans, CORONARY-HEART-DISEASE, Prospective cohort study, Stroke, Aged, Glucose Metabolism Disorders, business.industry, Vascular disease, MORTALITY, Absolute risk reduction, ASIA-PACIFIC REGION, WOMEN, General Medicine, Fasting, 11 Medical And Health Sciences, Articles, Middle Aged, medicine.disease, Impaired fasting glucose, 3. Good health, Endocrinology, Blood pressure, ATHEROSCLEROSIS, Cardiovascular Diseases, CARDIOVASCULAR-DISEASES, Female, coronary-heart-disease asia-pacific region cardiovascular-diseases task-force pathophysiology atherosclerosis mortality therapy women, business, TASK-FORCE
Abstract: Summary Background Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances. Methods We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease. Findings Analyses included data for 698 782 people (52 765 non-fatal or fatal vascular outcomes; 8·49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2·00 (95% CI 1·83–2·19) for coronary heart disease; 2·27 (1·95–2·65) for ischaemic stroke; 1·56 (1·19–2·05) for haemorrhagic stroke; 1·84 (1·59–2·13) for unclassified stroke; and 1·73 (1·51–1·98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40–59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10–12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3·90 mmol/L and 5·59 mmol/L. Compared with fasting blood glucose concentrations of 3·90–5·59 mmol/L, HRs for coronary heart disease were: 1·07 (0·97–1·18) for lower than 3·90 mmol/L; 1·11 (1·04–1·18) for 5·60–6·09 mmol/L; and 1·17 (1·08–1·26) for 6·10–6·99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors. Interpretation Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and non-linearly associated with risk of vascular disease. Funding British Heart Foundation, UK Medical Research Council, and Pfizer.
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15. Dietary Fatty Acids, Macronutrient Substitutions, Food Sources and Incidence of Coronary Heart Disease: Findings From the EPIC-CVD Case-Cohort Study Across Nine European Countries

Author: Steur, Marinka, Johnson, Laura, Sharp, Stephen J, Imamura, Fumiaki, Sluijs, Ivonne, Key, Timothy J, Wood, Angela, Chowdhury, Rajiv, Guevara, Marcela, Jakobsen, Marianne U, Johansson, Ingegerd, Koulman, Albert, Overvad, Kim, Sánchez, Maria-José, Van Der Schouw, Yvonne T, Trichopoulou, Antonia, Weiderpass, Elisabete, Wennberg, Maria, Zheng, Ju-Sheng, Boeing, Heiner, Boer, Jolanda MA, Boutron-Ruault, Marie-Christine, Ericson, Ulrika, Heath, Alicia K, Huybrechts, Inge, Imaz, Liher, Kaaks, Rudolf, Krogh, Vittorio, Kühn, Tilman, Kyrø, Cecilie, Masala, Giovanna, Melander, Olle, Moreno-Iribas, Conchi, Panico, Salvatore, Quirós, José R, Rodríguez-Barranco, Miguel, Sacerdote, Carlotta, Santiuste, Carmen, Skeie, Guri, Tjønneland, Anne, Tumino, Rosario, Verschuren, WM Monique, Zamora-Ros, Raul, Dahm, Christina C, Perez-Cornago, Aurora, Schulze, Matthias B, Tong, Tammy YN, Riboli, Elio, Wareham, Nicholas J, Danesh, John, Butterworth, Adam S, and Forouhi, Nita G
Subjects: 2. Zero hunger, saturated fat, Incidence, primary prevention, Fatty Acids, Coronary Disease, Nutrients, Dietary Fats, 3. Good health, Cohort Studies, Europe, nutritional epidemiology, Food, Humans, coronary heart disease, dietary guidelines
Abstract: Background There is controversy about associations between total dietary fatty acids, their classes (saturated fatty acids [SFAs], monounsaturated fatty acids, and polyunsaturated fatty acids), and risk of coronary heart disease (CHD). Specifically, the relevance of food sources of SFAs to CHD associations is uncertain. Methods and Results We conducted a case-cohort study involving 10 529 incident CHD cases and a random subcohort of 16 730 adults selected from a cohort of 385 747 participants in 9 countries of the EPIC (European Prospective Investigation into Cancer and Nutrition) study. We estimated multivariable adjusted country-specific hazard ratios (HRs) and 95% CIs per 5% of energy intake from dietary fatty acids, with and without isocaloric macronutrient substitutions, using Prentice-weighted Cox regression models and pooled results using random-effects meta-analysis. We found no evidence for associations of the consumption of total or fatty acid classes with CHD, regardless of macronutrient substitutions. In analyses considering food sources, CHD incidence was lower per 1% higher energy intake of SFAs from yogurt (HR, 0.93 [95% CI, 0.88-0.99]), cheese (HR, 0.98 [95% CI, 0.96-1.00]), and fish (HR, 0.87 [95% CI, 0.75-1.00]), but higher for SFAs from red meat (HR, 1.07 [95% CI, 1.02-1.12]) and butter (HR, 1.02 [95% CI, 1.00-1.04]). Conclusions This observational study found no strong associations of total fatty acids, SFAs, monounsaturated fatty acids, and polyunsaturated fatty acids, with incident CHD. By contrast, we found associations of SFAs with CHD in opposite directions dependent on the food source. These findings should be further confirmed, but support public health recommendations to consider food sources alongside the macronutrients they contain, and suggest the importance of the overall food matrix.

16. Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries

Author: Deschasaux, Mélanie, Huybrechts, Inge, Julia, Chantal, Hercberg, Serge, Egnell, Manon, Srour, Bernard, Kesse-Guyot, Emmanuelle, Latino-Martel, Paule, Biessy, Carine, Casagrande, Corinne, Murphy, Neil, Jenab, Mazda, Ward, Heather A, Weiderpass, Elisabete, Overvad, Kim, Tjønneland, Anne, Rostgaard-Hansen, Agnetha Linn, Boutron-Ruault, Marie-Christine, Mancini, Francesca Romana, Mahamat-Saleh, Yahya, Kühn, Tilman, Katzke, Verena, Bergmann, Manuela M, Schulze, Matthias B, Trichopoulou, Antonia, Karakatsani, Anna, Peppa, Eleni, Masala, Giovanna, Agnoli, Claudia, De Magistris, Maria Santucci, Tumino, Rosario, Sacerdote, Carlotta, Boer, Jolanda MA, Verschuren, WM Monique, Van Der Schouw, Yvonne T, Skeie, Guri, Braaten, Tonje, Redondo, M Luisa, Agudo, Antonio, Petrova, Dafina, Colorado-Yohar, Sandra M, Barricarte, Aurelio, Amiano, Pilar, Sonestedt, Emily, Ericson, Ulrika, Otten, Julia, Sundström, Björn, Wareham, Nicholas J, Forouhi, Nita G, Vineis, Paolo, Tsilidis, Konstantinos K, Knuppel, Anika, Papier, Keren, Ferrari, Pietro, Riboli, Elio, Gunter, Marc J, and Touvier, Mathilde
Subjects: 2. Zero hunger, Research, 3. Good health
Abstract: Objective: To determine if the Food Standards Agency nutrient profiling system (FSAm-NPS), which grades the nutritional quality of food products and is used to derive the Nutri-Score front-of-packet label to guide consumers towards healthier food choices, is associated with mortality. Design: Population based cohort study. Setting: European Prospective Investigation into Cancer and Nutrition (EPIC) cohort from 23 centres in 10 European countries. Participants: 521 324 adults; at recruitment, country specific and validated dietary questionnaires were used to assess their usual dietary intakes. A FSAm-NPS score was calculated for each food item per 100 g content of energy, sugars, saturated fatty acids, sodium, fibre, and protein, and of fruit, vegetables, legumes, and nuts. The FSAm-NPS dietary index was calculated for each participant as an energy weighted mean of the FSAm-NPS score of all foods consumed. The higher the score the lower the overall nutritional quality of the diet. Main outcome measure: Associations between the FSAm-NPS dietary index score and mortality, assessed using multivariable adjusted Cox proportional hazards regression models. Results: After exclusions, 501 594 adults (median follow-up 17.2 years, 8 162 730 person years) were included in the analyses. Those with a higher FSAm-NPS dietary index score (highest versus lowest fifth) showed an increased risk of all cause mortality (n=53 112 events from non-external causes; hazard ratio 1.07, 95% confidence interval 1.03 to 1.10, P

17. Biomarkers of Dietary Omega-6 Fatty Acids and Incident Cardiovascular Disease and Mortality

Author: Marklund, Matti, Wu, Jason HY, Imamura, Fumiaki, Del Gobbo, Liana C, Fretts, Amanda, De Goede, Janette, Shi, Peilin, Tintle, Nathan, Wennberg, Maria, Aslibekyan, Stella, Chen, Tzu-An, De Oliveira Otto, Marcia C, Hirakawa, Yoichiro, Eriksen, Helle Højmark, Kröger, Janine, Laguzzi, Federica, Lankinen, Maria, Murphy, Rachel A, Prem, Kiesha, Samieri, Cécilia, Virtanen, Jyrki, Wood, Alexis C, Wong, Kerry, Yang, Wei-Sin, Zhou, Xia, Baylin, Ana, Boer, Jolanda MA, Brouwer, Ingeborg A, Campos, Hannia, Chaves, Paulo HM, Chien, Kuo-Liong, De Faire, Ulf, Djoussé, Luc, Eiriksdottir, Gudny, El-Abbadi, Naglaa, Forouhi, Nita G, Michael Gaziano, J, Geleijnse, Johanna M, Gigante, Bruna, Giles, Graham, Guallar, Eliseo, Gudnason, Vilmundur, Harris, Tamara, Harris, William S, Helmer, Catherine, Hellenius, Mai-Lis, Hodge, Allison, Hu, Frank B, Jacques, Paul F, Jansson, Jan-Håkan, Kalsbeek, Anya, Khaw, Kay-Tee, Koh, Woon-Puay, Laakso, Markku, Leander, Karin, Lin, Hung-Ju, Lind, Lars, Luben, Robert, Luo, Juhua, McKnight, Barbara, Mursu, Jaakko, Ninomiya, Toshiharu, Overvad, Kim, Psaty, Bruce M, Rimm, Eric, Schulze, Matthias B, Siscovick, David, Skjelbo Nielsen, Michael, Smith, Albert V, Steffen, Brian T, Steffen, Lyn, Sun, Qi, Sundström, Johan, Tsai, Michael Y, Tunstall-Pedoe, Hugh, Uusitupa, Matti IJ, Van Dam, Rob M, Veenstra, Jenna, Monique Verschuren, WM, Wareham, Nick, Willett, Walter, Woodward, Mark, Yuan, Jian-Min, Micha, Renata, Lemaitre, Rozenn N, Mozaffarian, Dariush, Risérus, Ulf, and Cohorts For Heart And Aging Research In Genomic Epidemiology (CHARGE) Fatty Acids And Outcomes Research Consortium (FORCE)
Subjects: linoleic acid, Male, primary prevention, biomarkers, Middle Aged, Protective Factors, Recommended Dietary Allowances, Dietary Fats, Risk Assessment, 3. Good health, cardiovascular diseases, Observational Studies as Topic, Risk Factors, arachidonic acid, Humans, epidemiology, Female, Diet, Healthy, diet, Nutritive Value, Risk Reduction Behavior, Aged
Abstract: BACKGROUND: Global dietary recommendations for and cardiovascular effects of linoleic acid, the major dietary omega-6 fatty acid, and its major metabolite, arachidonic acid, remain controversial. To address this uncertainty and inform international recommendations, we evaluated how in vivo circulating and tissue levels of linoleic acid (LA) and arachidonic acid (AA) relate to incident cardiovascular disease (CVD) across multiple international studies. METHODS: We performed harmonized, de novo, individual-level analyses in a global consortium of 30 prospective observational studies from 13 countries. Multivariable-adjusted associations of circulating and adipose tissue LA and AA biomarkers with incident total CVD and subtypes (coronary heart disease, ischemic stroke, cardiovascular mortality) were investigated according to a prespecified analytic plan. Levels of LA and AA, measured as the percentage of total fatty acids, were evaluated linearly according to their interquintile range (ie, the range between the midpoint of the first and fifth quintiles), and categorically by quintiles. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Heterogeneity was explored by age, sex, race, diabetes mellitus, statin use, aspirin use, omega-3 levels, and fatty acid desaturase 1 genotype (when available). RESULTS: In 30 prospective studies with medians of follow-up ranging 2.5 to 31.9 years, 15 198 incident cardiovascular events occurred among 68 659 participants. Higher levels of LA were significantly associated with lower risks of total CVD, cardiovascular mortality, and ischemic stroke, with hazard ratios per interquintile range of 0.93 (95% CI, 0.88-0.99), 0.78 (0.70-0.85), and 0.88 (0.79-0.98), respectively, and nonsignificantly with lower coronary heart disease risk (0.94; 0.88-1.00). Relationships were similar for LA evaluated across quintiles. AA levels were not associated with higher risk of cardiovascular outcomes; in a comparison of extreme quintiles, higher levels were associated with lower risk of total CVD (0.92; 0.86-0.99). No consistent heterogeneity by population subgroups was identified in the observed relationships. CONCLUSIONS: In pooled global analyses, higher in vivo circulating and tissue levels of LA and possibly AA were associated with lower risk of major cardiovascular events. These results support a favorable role for LA in CVD prevention.

18. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

Author: Swerdlow, Daniel I, Preiss, David, Kuchenbaecker, Karoline B, Holmes, Michael V, Engmann, Jorgen EL, Shah, Tina, Sofat, Reecha, Stender, Stefan, Johnson, Paul CD, Scott, Robert A, Leusink, Maarten, Verweij, Niek, Sharp, Stephen J, Guo, Yiran, Giambartolomei, Claudia, Chung, Christina, Peasey, Anne, Amuzu, Antoinette, Li, KaWah, Palmen, Jutta, Howard, Philip, Cooper, Jackie A, Drenos, Fotios, Li, Yun R, Lowe, Gordon, Gallacher, John, Stewart, Marlene CW, Tzoulaki, Ioanna, Buxbaum, Sarah G, Van Der A, Daphne L, Forouhi, Nita G, Onland-Moret, N Charlotte, Van Der Schouw, Yvonne T, Schnabel, Renate B, Hubacek, Jaroslav A, Kubinova, Ruzena, Baceviciene, Migle, Tamosiunas, Abdonas, Pajak, Andrzej, Topor-Madry, Roman, Stepaniak, Urszula, Malyutina, Sofia, Baldassarre, Damiano, Sennblad, Bengt, Tremoli, Elena, De Faire, Ulf, Veglia, Fabrizio, Ford, Ian, Jukema, J Wouter, Westendorp, Rudi GJ, De Borst, Gert Jan, De Jong, Pim A, Algra, Ale, Spiering, Wilko, Maitland-Van Der Zee, Anke H, Klungel, Olaf H, De Boer, Anthonius, Doevendans, Pieter A, Eaton, Charles B, Robinson, Jennifer G, Duggan, David, DIAGRAM Consortium, MAGIC Consortium, InterAct Consortium, Kjekshus, John, Downs, John R, Gotto, Antonio M, Keech, Anthony C, Marchioli, Roberto, Tognoni, Gianni, Sever, Peter S, Poulter, Neil R, Waters, David D, Pedersen, Terje R, Amarenco, Pierre, Nakamura, Haruo, McMurray, John JV, Lewsey, James D, Chasman, Daniel I, Ridker, Paul M, Maggioni, Aldo P, Tavazzi, Luigi, Ray, Kausik K, Seshasai, Sreenivasa Rao Kondapally, Manson, JoAnn E, Price, Jackie F, Whincup, Peter H, Morris, Richard W, Lawlor, Debbie A, Smith, George Davey, Ben-Shlomo, Yoav, Schreiner, Pamela J, Fornage, Myriam, Siscovick, David S, Cushman, Mary, Kumari, Meena, Wareham, Nick J, Verschuren, WM Monique, Redline, Susan, Patel, Sanjay R, Whittaker, John C, Hamsten, Anders, Delaney, Joseph A, Dale, Caroline, Gaunt, Tom R, Wong, Andrew, Kuh, Diana, Hardy, Rebecca, Kathiresan, Sekar, Castillo, Berta A, Van Der Harst, Pim, Brunner, Eric J, Tybjaerg-Hansen, Anne, Marmot, Michael G, Krauss, Ronald M, Tsai, Michael, Coresh, Josef, Hoogeveen, Ronald C, Psaty, Bruce M, Lange, Leslie A, Hakonarson, Hakon, Dudbridge, Frank, Humphries, Steve E, Talmud, Philippa J, Kivimäki, Mika, Timpson, Nicholas J, Langenberg, Claudia, Asselbergs, Folkert W, Voevoda, Mikhail, Bobak, Martin, Pikhart, Hynek, Wilson, James G, Reiner, Alex P, Keating, Brendan J, Hingorani, Aroon D, and Sattar, Naveed
Subjects: Male, Body Weight, Cholesterol, HDL, Cholesterol, LDL, Middle Aged, Polymorphism, Single Nucleotide, 3. Good health, Body Mass Index, Diabetes Mellitus, Type 2, Risk Factors, Humans, Female, Hydroxymethylglutaryl CoA Reductases, Genetic Testing, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Aged, Randomized Controlled Trials as Topic
Abstract: BACKGROUND: Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target. METHODS: We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis. FINDINGS: Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials). INTERPRETATION: The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition. FUNDING: The funding sources are cited at the end of the paper.

19. Consumption of Meat, Fish, Dairy Products, and Eggs and Risk of Ischemic Heart Disease

Author: Key, Timothy J, Appleby, Paul N, Bradbury, Kathryn E, Sweeting, Michael, Wood, Angela, Johansson, Ingegerd, Kühn, Tilman, Steur, Marinka, Weiderpass, Elisabete, Wennberg, Maria, Lund Würtz, Anne Mette, Agudo, Antonio, Andersson, Jonas, Arriola, Larraitz, Boeing, Heiner, Boer, Jolanda MA, Bonnet, Fabrice, Boutron-Ruault, Marie-Christine, Cross, Amanda J, Ericson, Ulrika, Fagherazzi, Guy, Ferrari, Pietro, Gunter, Marc, Huerta, José María, Katzke, Verena, Khaw, Kay-Tee, Krogh, Vittorio, La Vecchia, Carlo, Matullo, Giuseppe, Moreno-Iribas, Conchi, Naska, Androniki, Nilsson, Lena Maria, Olsen, Anja, Overvad, Kim, Palli, Domenico, Panico, Salvatore, Molina-Portillo, Elena, Quirós, J Ramón, Skeie, Guri, Sluijs, Ivonne, Sonestedt, Emily, Stepien, Magdalena, Tjønneland, Anne, Trichopoulou, Antonia, Tumino, Rosario, Tzoulaki, Ioanna, Van Der Schouw, Yvonne T, Verschuren, WM Monique, Di Angelantonio, Emanuele, Langenberg, Claudia, Forouhi, Nita, Wareham, Nick, Butterworth, Adam, Riboli, Elio, and Danesh, John
Subjects: Adult, Male, Meat, Time Factors, Eggs, Myocardial Ischemia, Blood Pressure, Recommended Dietary Allowances, Diet Surveys, Risk Assessment, Risk Factors, Humans, Prospective Studies, Aged, 2. Zero hunger, fish, heart diseases, dairy products, Cholesterol, HDL, food and beverages, Middle Aged, Protective Factors, 3. Good health, Europe, Cross-Sectional Studies, Seafood, Female, Diet, Healthy, Nutritive Value, Risk Reduction Behavior, Biomarkers
Abstract: BACKGROUND: There is uncertainty about the relevance of animal foods to the pathogenesis of ischemic heart disease (IHD). We examined meat, fish, dairy products, and eggs and risk for IHD in the pan-European EPIC cohort (European Prospective Investigation Into Cancer and Nutrition). METHODS: In this prospective study of 409 885 men and women in 9 European countries, diet was assessed with validated questionnaires and calibrated with 24-hour recalls. Lipids and blood pressure were measured in a subsample. During a mean of 12.6 years of follow-up, 7198 participants had a myocardial infarction or died of IHD. The relationships of animal foods with risk were examined with Cox regression with adjustment for other animal foods and relevant covariates. RESULTS: The hazard ratio (HR) for IHD was 1.19 (95% CI, 1.06-1.33) for a 100-g/d increment in intake of red and processed meat, and this remained significant after exclusion of the first 4 years of follow-up (HR, 1.25 [95% CI, 1.09-1.42]). Risk was inversely associated with intakes of yogurt (HR, 0.93 [95% CI, 0.89-0.98] per 100-g/d increment), cheese (HR, 0.92 [95% CI, 0.86-0.98] per 30-g/d increment), and eggs (HR, 0.93 [95% CI, 0.88-0.99] per 20-g/d increment); the associations with yogurt and eggs were attenuated and nonsignificant after exclusion of the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish, or milk. In analyses modeling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese, or eggs was associated with ≈20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non-high-density lipoprotein cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non-high-density lipoprotein cholesterol. CONCLUSIONS: Risk for IHD was positively associated with consumption of red and processed meat and inversely associated with consumption of yogurt, cheese, and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non-high-density lipoprotein cholesterol and for red and processed meat with systolic blood pressure, which could mediate such effects.

20. Cardiovascular Risk Factors Associated With Venous Thromboembolism

Author: Gregson, John, Kaptoge, Stephen, Bolton, Thomas, Pennells, Lisa, Willeit, Peter, Burgess, Stephen, Bell, Steven, Sweeting, Michael, Rimm, Eric B, Kabrhel, Christopher, Zöller, Bengt, Assmann, Gerd, Gudnason, Vilmundur, Folsom, Aaron R, Arndt, Volker, Fletcher, Astrid, Norman, Paul E, Nordestgaard, Børge G, Kitamura, Akihiko, Mahmoodi, Bakhtawar K, Whincup, Peter H, Knuiman, Matthew, Salomaa, Veikko, Meisinger, Christa, Koenig, Wolfgang, Kavousi, Maryam, Völzke, Henry, Cooper, Jackie A, Ninomiya, Toshiharu, Casiglia, Edoardo, Rodriguez, Beatriz, Ben-Shlomo, Yoav, Després, Jean-Pierre, Simons, Leon, Barrett-Connor, Elizabeth, Björkelund, Cecilia, Notdurfter, Marlene, Kromhout, Daan, Price, Jackie, Sutherland, Susan E, Sundström, Johan, Kauhanen, Jussi, Gallacher, John, Beulens, Joline WJ, Dankner, Rachel, Cooper, Cyrus, Giampaoli, Simona, Deen, Jason F, Gómez De La Cámara, Agustín, Kuller, Lewis H, Rosengren, Annika, Svensson, Peter J, Nagel, Dorothea, Crespo, Carlos J, Brenner, Hermann, Albertorio-Diaz, Juan R, Atkins, Robert, Brunner, Eric J, Shipley, Martin, Njølstad, Inger, Lawlor, Deborah A, Van Der Schouw, Yvonne T, Selmer, Randi Marie, Trevisan, Maurizio, Verschuren, WM Monique, Greenland, Philip, Wassertheil-Smoller, Sylvia, Lowe, Gordon DO, Wood, Angela M, Butterworth, Adam S, Thompson, Simon G, Danesh, John, Di Angelantonio, Emanuele, Meade, Tom, and Emerging Risk Factors Collaboration
Subjects: 2. Zero hunger, Adult, Male, Venous Thrombosis, Smoking, Coronary Disease, Venous Thromboembolism, Middle Aged, 16. Peace & justice, United Kingdom, 3. Good health, Body Mass Index, Cardiovascular Diseases, Risk Factors, Outcome Assessment, Health Care, Diabetes Mellitus, Humans, Female, Obesity, Prospective Studies, Pulmonary Embolism
Abstract: IMPORTANCE: It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). OBJECTIVE: To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. DESIGN, SETTING, AND PARTICIPANTS: This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731 728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421 537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. EXPOSURES: A panel of several established cardiovascular risk factors. MAIN OUTCOMES AND MEASURES: Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25 131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). RESULTS: Of the 731 728 participants from the ERFC, 403 396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421 537 participants from the UK Biobank, 233 699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. CONCLUSIONS AND RELEVANCE: Older age, smoking, and adiposity were consistently associated with higher VTE risk.

21. Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries

Author: Deschasaux, Mélanie, Huybrechts, Inge, Julia, Chantal, Hercberg, Serge, Egnell, Manon, Srour, Bernard, Kesse-Guyot, Emmanuelle, Latino-Martel, Paule, Biessy, Carine, Casagrande, Corinne, Murphy, Neil, Jenab, Mazda, Ward, Heather A, Weiderpass, Elisabete, Overvad, Kim, Tjønneland, Anne, Rostgaard-Hansen, Agnetha Linn, Boutron-Ruault, Marie-Christine, Mancini, Francesca Romana, Mahamat-Saleh, Yahya, Kühn, Tilman, Katzke, Verena, Bergmann, Manuela M, Schulze, Matthias B, Trichopoulou, Antonia, Karakatsani, Anna, Peppa, Eleni, Masala, Giovanna, Agnoli, Claudia, De Magistris, Maria Santucci, Tumino, Rosario, Sacerdote, Carlotta, Boer, Jolanda Ma, Verschuren, Wm Monique, Van Der Schouw, Yvonne T, Skeie, Guri, Braaten, Tonje, Redondo, M Luisa, Agudo, Antonio, Petrova, Dafina, Colorado-Yohar, Sandra M, Barricarte, Aurelio, Amiano, Pilar, Sonestedt, Emily, Ericson, Ulrika, Otten, Julia, Sundström, Björn, Wareham, Nicholas J, Forouhi, Nita G, Vineis, Paolo, Tsilidis, Konstantinos K, Knuppel, Anika, Papier, Keren, Ferrari, Pietro, Riboli, Elio, Gunter, Marc J, and Touvier, Mathilde
Subjects: 2. Zero hunger, Adult, Male, Middle Aged, 3. Good health, Cohort Studies, Europe, Food Preferences, Nutrition Assessment, Food Labeling, Surveys and Questionnaires, Humans, Female, Mortality, Nutritive Value, Proportional Hazards Models
Abstract: OBJECTIVE: To determine if the Food Standards Agency nutrient profiling system (FSAm-NPS), which grades the nutritional quality of food products and is used to derive the Nutri-Score front-of-packet label to guide consumers towards healthier food choices, is associated with mortality. DESIGN: Population based cohort study. SETTING: European Prospective Investigation into Cancer and Nutrition (EPIC) cohort from 23 centres in 10 European countries. PARTICIPANTS: 521 324 adults; at recruitment, country specific and validated dietary questionnaires were used to assess their usual dietary intakes. A FSAm-NPS score was calculated for each food item per 100 g content of energy, sugars, saturated fatty acids, sodium, fibre, and protein, and of fruit, vegetables, legumes, and nuts. The FSAm-NPS dietary index was calculated for each participant as an energy weighted mean of the FSAm-NPS score of all foods consumed. The higher the score the lower the overall nutritional quality of the diet. MAIN OUTCOME MEASURE: Associations between the FSAm-NPS dietary index score and mortality, assessed using multivariable adjusted Cox proportional hazards regression models. RESULTS: After exclusions, 501 594 adults (median follow-up 17.2 years, 8 162 730 person years) were included in the analyses. Those with a higher FSAm-NPS dietary index score (highest versus lowest fifth) showed an increased risk of all cause mortality (n=53 112 events from non-external causes; hazard ratio 1.07, 95% confidence interval 1.03 to 1.10, P

22. Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight

Author: NCD Risk Factor Collaboration (NCD-RisC), Iurilli, Maria LC, Zhou, Bin, Bennett, James E, Carrillo-Larco, Rodrigo M, Sophiea, Marisa K, Rodriguez-Martinez, Andrea, Bixby, Honor, Solomon, Bethlehem D, Taddei, Cristina, Danaei, Goodarz, Di Cesare, Mariachiara, Stevens, Gretchen A, Riley, Leanne M, Savin, Stefan, Cowan, Melanie J, Bovet, Pascal, Damasceno, Albertino, Chirita-Emandi, Adela, Hayes, Alison J, Ikeda, Nayu, Jackson, Rod T, Khang, Young-Ho, Laxmaiah, Avula, Liu, Jing, Miranda, J Jaime, Saidi, Olfa, Sebert, Sylvain, Sorić, Maroje, Starc, Gregor, Gregg, Edward W, Abarca-Gómez, Leandra, Abdeen, Ziad A, Abdrakhmanova, Shynar, Ghaffar, Suhaila Abdul, Rahim, Hanan F Abdul, Abu-Rmeileh, Niveen M, Garba, Jamila Abubakar, Acosta-Cazares, Benjamin, Adams, Robert J, Aekplakorn, Wichai, Afsana, Kaosar, Afzal, Shoaib, Agdeppa, Imelda A, Aghazadeh-Attari, Javad, Aguilar-Salinas, Carlos A, Agyemang, Charles, Ahmad, Mohamad Hasnan, Ahmad, Noor Ani, Ahmadi, Ali, Ahmadi, Naser, Ahmed, 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Jardena J, Pudule, Iveta, Puhakka, Soile E, Puiu, Maria, Punab, Margus, Qasrawi, Radwan F, Qorbani, Mostafa, Bao, Tran Quoc, Radic, Ivana, Radisauskas, Ricardas, Rahimikazerooni, Salar, Rahman, Mahfuzar, Rahman, Mahmudur, Raitakari, Olli, Raj, Manu, Rakhimova, Ellina, Rakhmatulloev, Sherali, Rakovac, Ivo, Rao, Sudha Ramachandra, Ramachandran, Ambady, Ramke, Jacqueline, Ramos, Elisabete, Ramos, Rafel, Rampal, Lekhraj, Rampal, Sanjay, Rarra, Vayia, Rascon-Pacheco, Ramon A, Rasmussen, Mette, Rech, Cassiano Ricardo, Redon, Josep, Reganit, Paul Ferdinand M, Regecová, Valéria, Revilla, Luis, Rezaianzadeh, Abbas, Ribas-Barba, Lourdes, Ribeiro, Robespierre, Riboli, Elio, Richter, Adrian, Rigo, Fernando, Rinaldo, Natascia, De Wit, Tobias F Rinke, Rito, Ana, Ritti-Dias, Raphael M, Rivera, Juan A, Robitaille, Cynthia, Roccaldo, Romana, Rodrigues, Daniela, Rodríguez-Artalejo, Fernando, Del Cristo Rodriguez-Perez, María, Rodríguez-Villamizar, Laura A, Roggenbuck, Ulla, Rojas-Martinez, Rosalba, Rojroongwasinkul, Nipa, Romaguera, Dora, Romeo, Elisabetta L, Rosario, Rafaela V, Rosengren, Annika, Rouse, Ian, Roy, Joel GR, Rubinstein, Adolfo, Rühli, Frank J, Ruidavets, Jean-Bernard, Ruiz-Betancourt, Blanca Sandra, Ruiz-Castell, Maria, Moreno, Emma Ruiz, Rusakova, Iuliia A, Jonsson, Kenisha Russell, Russo, Paola, Rust, Petra, Rutkowski, Marcin, Sabanayagam, Charumathi, Sacchini, Elena, Sachdev, Harshpal S, Sadjadi, Alireza, Safarpour, Ali Reza, Safiri, Saeid, Saki, Nader, Salanave, Benoit, Martinez, Eduardo Salazar, Salmerón, Diego, Salomaa, Veikko, Salonen, Jukka T, Salvetti, Massimo, Samoutian, Margarita, Sánchez-Abanto, Jose, Sandjaja, Sans, Susana, Marina, Loreto Santa, Santos, Diana A, Santos, Ina S, Santos, Lèlita C, Santos, Maria Paula, Santos, Osvaldo, Santos, Rute, Sanz, Sara Santos, Saramies, Jouko L, Sardinha, Luis B, Sarrafzadegan, Nizal, Sathish, Thirunavukkarasu, Saum, Kai-Uwe, Savva, Savvas, Savy, Mathilde, Sawada, Norie, Sbaraini, Mariana, Scazufca, Marcia, Schaan, Beatriz D, Rosario, Angelika Schaffrath, Schargrodsky, Herman, Schienkiewitz, Anja, Schipf, Sabine, Schmidt, Carsten O, Schmidt, Ida Maria, Schnohr, Peter, Schöttker, Ben, Schramm, Sara, Schramm, Stine, Schröder, Helmut, Schultsz, Constance, Schutte, Aletta E, Sein, Aye Aye, Selamat, Rusidah, Sember, Vedrana, Sen, Abhijit, Senbanjo, Idowu O, Sepanlou, Sadaf G, Sequera, Victor, Serra-Majem, Luis, Servais, Jennifer, Ševcíková, Ludmila, Shalnova, Svetlana A, Shamah-Levy, Teresa, Shamshirgaran, Morteza, Shanthirani, Coimbatore Subramaniam, Sharafkhah, Maryam, Sharma, Sanjib K, Shaw, Jonathan E, Shayanrad, Amaneh, Shayesteh, Ali Akbar, Shengelia, Lela, Shi, Zumin, Shibuya, Kenji, Shimizu-Furusawa, Hana, Shin, Dong Wook, Shirani, Majid, Shiri, Rahman, Shrestha, Namuna, Si-Ramlee, Khairil, Siani, Alfonso, Siantar, Rosalynn, Sibai, Abla M, Silva, Antonio M, Silva, Diego Augusto Santos, Simon, Mary, Simons, Judith, Simons, Leon A, Sjöberg, Agneta, Sjöström, Michael, Skodje, Gry, Slowikowska-Hilczer, Jolanta, Slusarczyk, Przemyslaw, Smeeth, Liam, So, Hung-Kwan, Soares, Fernanda Cunha, Sobek, Grzegorz, Sobngwi, Eugène, Sodemann, Morten, Söderberg, Stefan, Soekatri, Moesijanti YE, Soemantri, Agustinus, Sofat, Reecha, Solfrizzi, Vincenzo, Somi, Mohammad Hossein, Sonestedt, Emily, Song, Yi, Sørensen, Thorkild IA, Sørgjerd, Elin P, Jérome, Charles Sossa, Soto-Rojas, Victoria E, Soumaré, Aïcha, Sovic, Slavica, Sparboe-Nilsen, Bente, Sparrenberger, Karen, Spinelli, Angela, Spiroski, Igor, Staessen, Jan A, Stamm, Hanspeter, Stathopoulou, Maria G, Staub, Kaspar, Stavreski, Bill, Steene-Johannessen, Jostein, Stehle, Peter, Stein, Aryeh D, Stergiou, George S, Stessman, Jochanan, Stevanovic, Ranko, Stieber, Jutta, Stöckl, Doris, Stocks, Tanja, Stokwiszewski, Jakub, Stoyanova, Ekaterina, Stratton, Gareth, Stronks, Karien, Strufaldi, Maria Wany, Sturua, Lela, Suárez-Medina, Ramón, Suka, Machi, Sun, Chien-An, Sundström, Johan, Sung, Yn-Tz, Sunyer, Jordi, Suriyawongpaisal, Paibul, Swinburn, Boyd A, Sy, Rody G, Syddall, Holly E, Sylva, René Charles, Szklo, Moyses, Szponar, Lucjan, Tai, E Shyong, Tammesoo, Mari-Liis, Tamosiunas, Abdonas, Tan, Eng Joo, Tang, Xun, Tanrygulyyeva, Maya, Tanser, Frank, Tao, Yong, Tarawneh, Mohammed Rasoul, Tarp, Jakob, Tarqui-Mamani, Carolina B, Braunerová, Radka Taxová, Taylor, Anne, Taylor, Julie, Tchibindat, Félicité, Tebar, William R, Tell, Grethe S, Tello, Tania, Tham, Yih Chung, Thankappan, KR, Theobald, Holger, Theodoridis, Xenophon, Thijs, Lutgarde, Thomas, Nihal, Thuesen, Betina H, Tichá, Lubica, Timmermans, Erik J, Tjonneland, Anne, Tolonen, Hanna K, Tolstrup, Janne S, Topbas, Murat, Topór-Madry, Roman, Torheim, Liv Elin, Tormo, María José, Tornaritis, Michael J, Torrent, Maties, Torres-Collado, Laura, Toselli, Stefania, Touloumi, Giota, Traissac, Pierre, Tran, Thi Tuyet-Hanh, Trichopoulos, Dimitrios, Trichopoulou, Antonia, Trinh, Oanh TH, Trivedi, Atul, Tshepo, Lechaba, Tsigga, Maria, Tsugane, Shoichiro, Tuliakova, Azaliia M, Tulloch-Reid, Marshall K, Tullu, Fikru, Tuomainen, Tomi-Pekka, Tuomilehto, Jaakko, Turley, Maria L, Twig, Gilad, Tynelius, Per, Tzotzas, Themistoklis, Tzourio, Christophe, Ueda, Peter, Ugel, Eunice, Ukoli, Flora AM, Ulmer, Hanno, Unal, Belgin, Usupova, Zhamyila, Uusitalo, Hannu MT, Uysal, Nalan, Vaitkeviciute, Justina, Valdivia, Gonzalo, Vale, Susana, Valvi, Damaskini, Van Dam, Rob M, Van Der Heyden, Johan, Van Der Schouw, Yvonne T, Van Herck, Koen, Van Minh, Hoang, Van Schoor, Natasja M, Van Valkengoed, Irene GM, Vanderschueren, Dirk, Vanuzzo, Diego, Varbo, Anette, Varela-Moreiras, Gregorio, Varona-Pérez, Patricia, Vasan, Senthil K, Vega, Tomas, Veidebaum, Toomas, Velasquez-Melendez, Gustavo, Velika, Biruta, Veronesi, Giovanni, Verschuren, WM Monique, Victora, Cesar G, Viegi, Giovanni, Viet, Lucie, Villalpando, Salvador, Vineis, Paolo, Vioque, Jesus, Virtanen, Jyrki K, Visser, Marjolein, Visvikis-Siest, Sophie, Viswanathan, Bharathi, Vladulescu, Mihaela, Vlasoff, Tiina, Vocanec, Dorja, Vollenweider, Peter, Völzke, Henry, Voutilainen, Ari, Voutilainen, Sari, Vrijheid, Martine, Vrijkotte, Tanja GM, Wade, Alisha N, Wagner, Aline, Waldhör, Thomas, Walton, Janette, Wambiya, Elvis OA, Bebakar, Wan Mohamad Wan, Mohamud, Wan Nazaimoon Wan, De Souza Wanderley Júnior, Rildo, Wang, Ming-Dong, Wang, Ningli, Wang, Qian, Wang, Xiangjun, Wang, Ya Xing, Wang, Ying-Wei, Wannamethee, S Goya, Wareham, Nicholas, Weber, Adelheid, Wedderkopp, Niels, Weerasekera, Deepa, Weghuber, Daniel, Wei, Wenbin, Weres, Aneta, Werner, Bo, Whincup, Peter H, Widhalm, Kurt, Widyahening, Indah S, Wiecek, Andrzej, Wilks, Rainford J, Willeit, Johann, Willeit, Peter, Williams, Julianne, Wilsgaard, Tom, Wojtyniak, Bogdan, Wong-McClure, Roy A, Wong, Andrew, Wong, Jyh Eiin, Wong, Tien Yin, Woo, Jean, Woodward, Mark, Wu, Frederick C, Wu, Jianfeng, Wu, Li Juan, Wu, Shouling, Xu, Haiquan, Xu, Liang, Yaacob, Nor Azwany, Yamborisut, Uruwan, Yan, Weili, Yang, Ling, Yang, Xiaoguang, Yang, Yang, Yardim, Nazan, Yaseri, Mehdi, Yasuharu, Tabara, Ye, Xingwang, Yiallouros, Panayiotis K, Yoosefi, Moein, Yoshihara, Akihiro, You, Qi Sheng, You, San-Lin, Younger-Coleman, Novie O, Md Yusof, Safiah, Yusoff, Ahmad Faudzi, Zaccagni, Luciana, Zafiropulos, Vassilis, Zainuddin, Ahmad A, Zakavi, Seyed Rasoul, Zamani, Farhad, Zambon, Sabina, Zampelas, Antonis, Zamrazilová, Hana, Zapata, Maria Elisa, Zargar, Abdul Hamid, Ko Zaw, Ko, Zdrojewski, Tomasz, Zejglicova, Kristyna, Vrkic, Tajana Zeljkovic, Zeng, Yi, Zhang, Luxia, Zhang, Zhen-Yu, Zhao, Dong, Zhao, Ming-Hui, Zhao, Wenhua, Zhen, Shiqi, Zheng, Wei, Zheng, Yingfeng, Zholdin, Bekbolat, Zhou, Maigeng, Zhu, Dan, Zins, Marie, Zitt, Emanuel, Zocalo, Yanina, Cisneros, Julio Zuñiga, Zuziak, Monika, Ezzati, Majid, and Filippi, Sarah
Subjects: 2. Zero hunger, obesity, BMI, Epidemiology and Global Health, underweight, None, 1. No poverty, 3. Good health, Research Article
Abstract: Funder: Wellcome Trust; FundRef: http://dx.doi.org/10.13039/100004440, Funder: Medical Research Council; FundRef: http://dx.doi.org/10.13039/501100000265, From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions.

23. Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement

Author: Jia, Peng, Yu, Chao, Remais, Justin V, Stein, Alfred, Liu, Yu, Brownson, Ross C, Lakerveld, Jeroen, Wu, Tong, Yang, Lijian, Smith, Melody, Amer, Sherif, Pearce, Jamie, Kestens, Yan, Kwan, Mei-Po, Lai, Shengjie, Xu, Fei, Chen, Xi, Rundle, Andrew, Xiao, Qian, Xue, Hong, Luo, Miyang, Zhao, Li, Cheng, Guo, Yang, Shujuan, Zhou, Xiaolu, Li, Yan, Panter, Jenna, Kingham, Simon, Jones, Andy, Johnson, Blair T, Shi, Xun, Zhang, Lin, Wang, Limin, Wu, Jianguo, Mavoa, Suzanne, Toivonen, Tuuli, Mwenda, Kevin M, Wang, Youfa, Verschuren, WM Monique, Vermeulen, Roel, and James, Peter
Subjects: Artificial intelligence, Spatial Analysis, Internationality, Lifecourse epidemiology, Health Status, Advisory Committees, Reporting guideline, Spatial epidemiology, 3. Good health, Checklist, Cohort Studies, Big data, Exposome, Reporting standard, Epidemiologic Studies, Research Design, ISLE, Spatial lifecourse epidemiology, Humans, Public Health, Exposomics, Location-based
Abstract: Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies to investigate the long-term effects of environmental, behavioural, psychosocial, and biological factors on health-related states and events and the underlying mechanisms. With the growing number of studies reporting findings from this field and the critical need for public health and policy decisions to be based on the strongest science possible, transparency and clarity in reporting in spatial lifecourse epidemiologic studies is essential. A task force supported by the International Initiative on Spatial Lifecourse Epidemiology (ISLE) identified a need for guidance in this area and developed a Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) Statement. The aim is to provide a checklist of recommendations to improve and make more consistent reporting of spatial lifecourse epidemiologic studies. The STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement for cohort studies was identified as an appropriate starting point to provide initial items to consider for inclusion. Reporting standards for spatial data and methods were then integrated to form a single comprehensive checklist of reporting recommendations. The strength of our approach has been our international and multidisciplinary team of content experts and contributors who represent a wide range of relevant scientific conventions, and our adherence to international norms for the development of reporting guidelines. As spatial, location-based, and artificial intelligence technologies used in spatial lifecourse epidemiology continue to evolve at a rapid pace, it will be necessary to revisit and adapt the ISLE-ReSt at least every 2-3 years from its release.

24. Cardiovascular surveys: manual of operations

Author: Salvatore Panico, Angela Döring, Paola Primatesta, Jiri Holub, Steven Allender, Sidsel Graff-Iversen, Antonia Trichopoulou, W. M. Monique Verschuren, Paola Ciccarelli, Primatesta, P, Allender, S, Ciccarelli, P, Doring, A, Graff Iversen, S, Holub, J, Panico, Salvatore, Trichopoulou, A, and Verschuren, Wm
Subjects: medicine.medical_specialty, Epidemiology, Population, Disease, Angina, Manuals as Topic, Medicine, Humans, education, Stroke, Cause of death, Response rate (survey), education.field_of_study, business.industry, Public health, Incidence (epidemiology), medicine.disease, Europe, Survival Rate, Cardiovascular Diseases, Population Surveillance, Emergency medicine, Medical emergency, Morbidity, Cardiology and Cardiovascular Medicine, business
Abstract: Cardiovascular disease (CVD) is the leading cause of death and hospitalization in both men and women in nearly all countries of Europe. The most frequent forms of CVD are those of an atherosclerotic origin, mainly ischaemic heart disease, stroke and heart failure. The magnitude of the problem contrasts with the usual paucity and poor quality of data available on incidence and prevalence of CVD, except for few rigorous but limited studies. The objectives of the health interview and health examination surveys (HIS/HES) are to evaluate the frequency and the distribution of the disease, to evaluate trends and treatment effectiveness, to estimate risk factors distribution and prevalence of high risk conditions and to monitor prevention programmes. According to the EUROCISS project (EUROpean Cardiovascular Surveillance Set) recommendations, surveys are aimed at describing the prevalence of the following CVD conditions: myocardial infarction, heart failure, angina pectoris, peripheral arterial disease, stroke, and ischaemic heart disease.HIS and HES were developed to supplement information collected from routine databases and population-based registers to implement consistent public health policies. HIS can be repeated periodically in a new sample of the population, or can follow up over time the population recruited at baseline. Procedures and methods to collect information from participants include self-administered questionnaires, direct interviewer-administered questions and telephone interviews. A minimum set of questions to be administered every year, along with a longer, more detailed module to be administered periodically are recommended to evaluate CVD prevalence. The addition of HES provides more detailed and objective information that can be used to improve estimates regarding prevalence of both risk factors and disease status. The selection of more specialized CVD-specific tests will depend on the objective the survey is designed to achieve, the assumed response rate and the cost and time considerations. For HES on CVD the minimum required is to perform the following measurements: height, weight, blood pressure, waist circumference, total and high density lipoprotein-cholesterol and glucose assay in a nonfasting blood sample. The next appropriate step would be to perform an electrocardiogram. High costs usually make HES difficult to carry out. Standardization of measurements, training of personnel and quality control are essential to assure reliable data. A high response rate is extremely important, as nonrespondents tend to have different health characteristics from the rest of the sample and their omission therefore results in bias. This manual of operations is intended for health professionals and policy makers and provides a standardized and simple model for the implementation of a CVD survey.
Published: 2008

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1. Additional file 2 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

2. Additional file 1 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

3. Additional file 4 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

4. Additional file 3 of Residential exposure to fast-food restaurants and its association with diet quality, overweight and obesity in the Netherlands: a cross-sectional analysis in the EPIC-NL cohort

5. Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors

6. Genome-wide association study meta-analysis identifies three novel loci for circulating anti-Müllerian hormone levels in women

7. Glycated hemoglobin measurement and prediction of cardiovascular disease

9. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

10. Design and cohortdescription of the InterAct Project: an examination of the interaction of geneticand lifestyle factors on the incidence of type 2 diabetes in the EPIC Study

11. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data

12. Susceptibility to Chronic Mucus Hypersecretion, a Genome Wide Association Study

13. Loci influencing blood pressure identified using a cardiovascular gene-centric array (vol 22, pg 1663, 2013)

14. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

15. Dietary Fatty Acids, Macronutrient Substitutions, Food Sources and Incidence of Coronary Heart Disease: Findings From the EPIC-CVD Case-Cohort Study Across Nine European Countries

16. Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries

17. Biomarkers of Dietary Omega-6 Fatty Acids and Incident Cardiovascular Disease and Mortality

18. HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials

19. Consumption of Meat, Fish, Dairy Products, and Eggs and Risk of Ischemic Heart Disease

20. Cardiovascular Risk Factors Associated With Venous Thromboembolism

21. Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries

22. Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight

23. Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement

24. Cardiovascular surveys: manual of operations

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