Dale Caroline E, Fatemifar Ghazaleh, Palmer Tom M, White Jon, Prieto-Merino David, Zabaneh Delilah, Engmann Jorgen E L, Shah Tina, Wong Andrew, Warren Helen R, McLachlan Stela, Trompet Stella, Moldovan Max, Morris Richard W, Sofat Reecha, Kumari Meena, Hyppönen Elina, Jefferis Barbara J, Gaunt Tom R, Ben-Shlomo Yoav, Zhou Ang, Gentry-Maharaj Aleksandra, Ryan Andy, Mutsert Renée de, Noordam Raymond, Caulfield Mark J, Jukema J Wouter, Worrall Bradford B, Munroe Patricia B, Menon Usha, Power Chris, Kuh Diana, Lawlor Debbie A, Humphries Steve E, Mook-Kanamori Dennis O, Sattar Naveed, Kivimaki Mika, Price Jacqueline F, Davey Smith George, Dudbridge Frank, Hingorani Aroon D, Holmes Michael V, Casas Juan P
From Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, United Kingdom (C.E.D., G.F., D.P.-M., A.D.H., J.P.C.); Department of Mathematics and Statistics, Lancaster University, United Kingdom (T.M.P.); UCLGenetics Institute, University College London, United Kingdom (J.W.); Applied Statistical Methods in Medical Research Group, Universidad Catolica de San Antonio de Murcia, Spain (D.P.-M.); Social Genetic & Developmental Psychiatry, King's College London, United Kingdom (D.Z.); Institute of Cardiovascular Science, University College London, United Kingdom (J.E.L.E., T.S., A.D.H., S.E.H.); MRC Unit for Lifelong Health & Ageing at UCL, London, United Kingdom (A.W., D.K.); Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (H.R.W., M.J.C., P.B.M.); NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (H.R.W., M.J.C., P.B.M.); Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, United Kingdom (S.M., J.F.P.); Department of Cardiology, Leiden University Medical Center, The Netherlands (S.T., W.J.); South Australian Health and Medical Research Institute, Adelaide (M.M., E.H.); EMBL Australia, Adelaide (M.M.); School of Social and Community Medicine, University of Bristol, United Kingdom (R.W.M., T.R.G., Y.B.-S., D.A.L., G.D.S.); Centre for Clinical Pharmacology, University College London, United Kingdom (R.S.); Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom (M.K.); Centre for Population Health Research, School of Health Sciences and Sansom Institute, University of South Australia, Adelaide (E.H., A.Z.); Population, Policy & Practice, UCL Great Ormond Street Institute of Child Health, London, United Kingdom (E.H., C.P.); Department of Primary Care & Population Health, University College London, Royal Free Campus, United Kingdom (B.J.J.); MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom (T.R.G., D.A.L., G.D.S.); Department of Women's Cancer, Institute for Women's Health, UCL, London, United Kingdom (A.G.-M., A.R., U.M.); Department of Clinical Epidemiology, Leiden University Medical Center, The Netherlands (R.d.M., D.O.M.-K.); Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, The Netherlands (R.N., S.T.); Interuniversity Cardiology Institute Netherlands, Utrecht (W.J.); Departments of Neurology and Public Health Sciences, University of Virginia, Charlottesville (B.B.W.); Department of Public Health and Primary Care, Leiden University Medical Center, The Netherlands (D.O.M.-K.); BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, United Kingdom (N.S.); Department of Epidemiology and Public Health, University College London, United Kingdom (M.K.); Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom (F.D.); Department of Health Sciences, University of Leicester, United Kingdom (F.D.); Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, United Kingdom (M.V.H.); Medical Research Council Population Health Research Unit at the University of Oxford, United Kingdom (M.V.H.); and National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals, United Kingdom (M.V.H.).
Circulation. 2017 Jun 13;135(24):2373-2388. doi: 10.1161/CIRCULATIONAHA.116.026560. Epub 2017 May 12.
The implications of different adiposity measures on cardiovascular disease etiology remain unclear. In this article, we quantify and contrast causal associations of central adiposity (waist-to-hip ratio adjusted for body mass index [WHRadjBMI]) and general adiposity (body mass index [BMI]) with cardiometabolic disease.
Ninety-seven independent single-nucleotide polymorphisms for BMI and 49 single-nucleotide polymorphisms for WHRadjBMI were used to conduct Mendelian randomization analyses in 14 prospective studies supplemented with coronary heart disease (CHD) data from CARDIoGRAMplusC4D (Coronary Artery Disease Genome-wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics; combined total 66 842 cases), stroke from METASTROKE (12 389 ischemic stroke cases), type 2 diabetes mellitus from DIAGRAM (Diabetes Genetics Replication and Meta-analysis; 34 840 cases), and lipids from GLGC (Global Lipids Genetic Consortium; 213 500 participants) consortia. Primary outcomes were CHD, type 2 diabetes mellitus, and major stroke subtypes; secondary analyses included 18 cardiometabolic traits.
Each one standard deviation (SD) higher WHRadjBMI (1 SD≈0.08 U) associated with a 48% excess risk of CHD (odds ratio [OR] for CHD, 1.48; 95% confidence interval [CI], 1.28-1.71), similar to findings for BMI (1 SD≈4.6 kg/m; OR for CHD, 1.36; 95% CI, 1.22-1.52). Only WHRadjBMI increased risk of ischemic stroke (OR, 1.32; 95% CI, 1.03-1.70). For type 2 diabetes mellitus, both measures had large effects: OR, 1.82 (95% CI, 1.38-2.42) and OR, 1.98 (95% CI, 1.41-2.78) per 1 SD higher WHRadjBMI and BMI, respectively. Both WHRadjBMI and BMI were associated with higher left ventricular hypertrophy, glycemic traits, interleukin 6, and circulating lipids. WHRadjBMI was also associated with higher carotid intima-media thickness (39%; 95% CI, 9%-77% per 1 SD).
Both general and central adiposity have causal effects on CHD and type 2 diabetes mellitus. Central adiposity may have a stronger effect on stroke risk. Future estimates of the burden of adiposity on health should include measures of central and general adiposity.
不同肥胖测量指标对心血管疾病病因的影响尚不清楚。在本文中，我们对中心性肥胖（校正体重指数后的腰臀比[WHRadjBMI]）和全身性肥胖（体重指数[BMI]）与心脏代谢疾病的因果关联进行量化和对比。
利用97个独立的BMI单核苷酸多态性和49个WHRadjBMI单核苷酸多态性，在14项前瞻性研究中进行孟德尔随机化分析，并补充来自CARDIoGRAMplusC4D（冠状动脉疾病全基因组复制和荟萃分析[CARDIoGRAM]加冠状动脉疾病[C4D]遗传学；总计66842例）的冠心病数据、来自METASTROKE的中风数据（12389例缺血性中风病例）、来自DIAGRAM的2型糖尿病数据（糖尿病遗传学复制和荟萃分析；34840例）以及来自GLGC（全球脂质遗传联盟；213500名参与者）联盟的血脂数据。主要结局为冠心病、2型糖尿病和主要中风亚型；次要分析包括18种心脏代谢特征。
WHRadjBMI每升高1个标准差（SD）（1 SD≈0.08 U）与冠心病风险增加48%相关（冠心病比值比[OR]为1.48；95%置信区间[CI]为1.28 - 1.71），与BMI的结果相似（1 SD≈4.6 kg/m²；冠心病OR为1.36；95% CI为1.22 - 1.52）。只有WHRadjBMI增加缺血性中风风险（OR为1.32；95% CI为1.03 - 1.70）。对于2型糖尿病，两种测量指标均有较大影响：WHRadjBMI和BMI每升高1个SD，OR分别为1.82（95% CI为1.38 - 2.
