Associations of body mass and fat indexes with cardiometabolic traits
journal contributionposted on 28.09.2018, 10:56 by Joshua A. Bell, David Carslake, Linda M. O’Keeffe, Monika Frysz, Laura D. Howe, Mark Hamer, Kaitlin H. Wade, Nicholas J. Timpson, George Davey Smith
Background Body mass index (BMI) is criticized for not distinguishing fat from lean mass and ignoring fat distribution, leaving its ability to detect health effects unclear. Objectives The aim of this study was to compare BMI with total and regional fat indexes from dual-energy x-ray absorptiometry in their associations with cardiometabolic traits. Duration of exposure to and change in each index across adolescence were examined in relation to detailed traits in young adulthood. Methods BMI was examined alongside total, trunk, arm, and leg fat indexes (each in kilograms per square meter) from dual-energy x-ray absorptiometry at ages 10 and 18 years in relation to 230 traits from targeted metabolomics at age 18 years in 2,840 offspring from the Avon Longitudinal Study of Parents and Children. Results Higher total fat mass index and BMI at age 10 years were similarly associated with cardiometabolic traits at age 18 years, including higher systolic and diastolic blood pressure, higher very low-density lipoprotein and low-density lipoprotein cholesterol, lower high-density lipoprotein cholesterol, higher triglycerides, and higher insulin and glycoprotein acetyls. Associations were stronger for both indexes measured at age 18 years and for gains in each index from age 10 to 18 years (e.g., 0.45 SDs [95% confidence interval: 0.38 to 0.53] in glycoprotein acetyls per SD unit gain in fat mass index vs. 0.38 SDs [95% confidence interval: 0.27 to 0.48] per SD unit gain in BMI). Associations resembled those for trunk fat index. Higher lean mass index was weakly associated with traits and was not protective against higher fat mass index. Conclusions The results of this study support abdominal fatness as a primary driver of cardiometabolic dysfunction and BMI as a useful tool for detecting its effects.
JAB is supported by a Cancer Research UK programme grant (C18281/A19169); LMOK by a UK Medical Research Council (MRC) Population Health Scientist fellowship (MR/M014509/1); LDH by an MRC Career Development Award fellowship (MR/M020894/1); MH by the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre; KHW and NJT by a Wellcome Trust Investigator grant (202802/Z/16/Z); NJT additionally by the University of Bristol NIHR Biomedical Research Centre (BRC-S- BRC-1215-20011). DC, KHW, NJT and GDS work in/have worked in the MRC Integrative Epidemiology Unit at the University of Bristol which is supported by the MRC (MC_UU_12013/1,3,4,9 (2013-2018); MC_UU_00011/1 (2018-2023)) and the University of Bristol. The MRC and Wellcome Trust (102215/2/13/2), and the University of Bristol provide core support for ALSPAC.
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