BMI and Mortality in UK Biobank: Revised Estimates Using Mendelian Randomization

Abstract

Objective: The aim of this study was to obtain estimates of the causal relationship between BMI and mortality.

Methods: Mendelian randomization (MR) with BMI-associated genotypic variation was used to test the causal effect of BMI on all-cause and cause-specific mortality in UK Biobank participants of White British ancestry.

Results: MR analyses supported a causal association between higher BMI and greater risk of all-cause mortality (hazard ratio [HR] per 1 kg/m² : 1.03; 95% CI: 0.99-1.07) and mortality from cardiovascular diseases (HR: 1.10; 95% CI: 1.01-1.19), specifically coronary heart disease (HR: 1.12; 95% CI: 1.00-1.25) and those excluding coronary heart disease/stroke/aortic aneurysm (HR: 1.24; 95% CI: 1.03-1.48), stomach cancer (HR: 1.18; 95% CI: 0.87-1.62), and esophageal cancer (HR: 1.22; 95% CI: 0.98-1.53), and a decreased risk of lung cancer mortality (HR: 0.96; 95% CI: 0.85-1.08). Sex stratification supported the causal role of higher BMI increasing bladder cancer mortality risk (males) but decreasing respiratory disease mortality risk (males). The J-shaped observational association between BMI and mortality was visible with MR analyses, but the BMI at which mortality was minimized was lower and the association was flatter over a larger BMI range.

Conclusions: Results support a causal role of higher BMI in increasing the risk of all-cause mortality and mortality from several specific causes.

Figure 1

Flowchart of those included in main analyses. Of those with valid BMI, genetic, and survival data, 335,308 were of White British ancestry. Of those who had died by February 16, 2016, 9,570 were of White British ancestry.

Figure 2

Assessment of linearity in associations of the GRS (comprising 77 SNPs) and all‐cause mortality in the UK Biobank sample of White British ancestry. Association between the GRS (comprising 77 SNPs) and all‐cause mortality, adjusted for secular trends (date of birth) and the first 10 genetic principal components. Linearity tests were conducted after removing data below or above the 1st or 99th percentile of BMI because of the scarcity of data toward the tails of the BMI distribution. Hazard ratios (HRs) were calculated relative to the mean GRS value with 1,000 bootstrap resamples to obtain 95% confidence intervals (CIs). The black lines represent the fitted HRs from cubic spline models (with the mean value of the GRS as the reference). GRS, genetic risk score; SNPs, single‐nucleotide polymorphisms.

Figure 3

(A) Assessment of linearity in associations of BMI and all‐cause mortality in the UK Biobank sample of White British ancestry using BMI. Observational associations between BMI and all‐cause mortality obtained using conventional Cox regression adjusted for secular trends (date of birth), current occupation, qualifications, smoking status, alcohol intake, and physical activity. (B) Assessment of linearity in associations of BMI and all‐cause mortality in the UK Biobank sample of White British ancestry using instrument‐free BMI. Approximate analogue using MR stratified by categories of the instrument‐free exposure (divided at the 5th, 10th, 25th, 50th, 75th, and 85th percentile) adjusted for secular trends (date of birth) and first 10 genetic principal components. Localized average causal effects were then joined together and plotted against the corresponding percentiles of the original exposure. Linearity tests were conducted after removing data below or above the 1st or 99th percentile, respectively, because of the scarcity of data toward the tails of the BMI distribution. Hazard ratios (HRs) were calculated relative to the mean BMI (27 kg/m²), with 1,000 bootstrap resamples to obtain 95% confidence intervals (CIs). The black lines represent the fitted HRs from cubic spline models (with mean BMI as the reference).