Obesity and cardiovascular outcomes: another look at a meta-analysis of Mendelian randomization studies

J Investig Med. 2020 Feb;68(2):357-363. doi: 10.1136/jim-2019-001069. Epub 2019 Jul 21.

Abstract

This study used the inverse variance heterogeneity (IVhet) model to conduct a reanalysis of a recent meta-analysis that reported a positive association, based on the random-effects (RE) model, between obesity and the incidence of type 2 diabetes and coronary heart disease, but not all-cause stroke, in adults. Data emanated from a recent meta-analysis of five Mendelian randomization studies representing 881,692 adults. Results were pooled using the IVhet model and reported as OR's and 95% CI. Small-study effects were examined using the Doi plot and Luis Furuya-Kanamori (LFK) index. Influence analysis was also conducted. The association between obesity and type 2 diabetes, coronary heart disease, and all-cause stroke was, respectively, 1.38 (95% CI 1.00 to 1.90, p=0.05, I2 =93%), 1.10 (95% CI 0.90 to 1.35, p=0.35, I2 =87%), and 1.02 (95% CI 0.95 to 1.09, p=0.64, I2 =0%). Compared with the original RE model, results were similar for all-cause stroke, but point estimates for type 2 diabetes and coronary heart disease were smaller (29.3% and 9.8%) with wider (7.0% and 14.7%), overlapping CI. Major asymmetry suggestive of small-study effects was observed (LFK=3.59). With the exception of one study for type 2 diabetes, results remained uncertain (overlapping 95% CI) when each study was deleted from the model once. A lack of certainty exists regarding the association between obesity and the incidence of type 2 diabetes, coronary heart disease, and all-cause stroke in adults.

Keywords: coronary heart disease; meta-analysis; obesity; stroke; type 2 diabetes.

MeSH terms

  • Coronary Disease / epidemiology
  • Coronary Disease / genetics*
  • Diabetes Mellitus, Type 2 / epidemiology
  • Diabetes Mellitus, Type 2 / genetics*
  • Humans
  • Mendelian Randomization Analysis / methods*
  • Meta-Analysis as Topic*
  • Obesity / epidemiology
  • Obesity / genetics*
  • Stroke / epidemiology
  • Stroke / genetics*