4.7 Article

Comparison of intergenerational instrumental variable analyses of body mass index and mortality in UK Biobank

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INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
卷 52, 期 2, 页码 545-561

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OXFORD UNIV PRESS
DOI: 10.1093/ije/dyac159

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Mendelian randomization; instrumental variable; proxy genotype; offspring as instrument; intergenerational; body mass index; mortality; UK Biobank

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This study applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality. The results suggested that higher BMI increased mortality, but caution is required in interpreting the exact values as causal.
Background An increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants. Methods In Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation. Results Complete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m(2) of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent-offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother-son) and 1.23 (95% CI: 1.16, 1.29; father-daughter). Conclusion Both methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them.

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