Estimating the influence of body mass index (BMI) on mortality using offspring BMI as an instrumental variable.
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ABSTRACT: Objective
High body mass index (BMI) is an important predictor of mortality but estimating underlying causality is hampered by confounding and pre-existing disease. Here, we use information from the offspring to approximate parental BMIs, with an aim to avoid biased estimation of mortality risk caused by reverse causality.Methods
The analyses were based on information on 9674 offspring-mother and 9096 offspring-father pairs obtained from the 1958 British birth cohort. Parental BMI-mortality associations were analysed using conventional methods and using offspring BMI as a proxy, or instrument, for their parents' BMI.Results
In the conventional analysis, associations between parental BMI and all-cause mortality were U-shaped (Pcurvature < 0.001), while offspring BMI had linear associations with parental mortality (Ptrend < 0.001, Pcurvature > 0.46). Curvature was particularly pronounced for mortality from respiratory diseases and from lung cancer. Instrumental variable analyses suggested a positive association between BMI and mortality from all causes [mothers: HR per SD of BMI 1.43 (95% CI 1.21-1.69), fathers: HR 1.17 (1.00-1.36)] and from coronary heart disease [mothers: HR 1.65 (1.15-2.36), fathers: HR 1.51 (1.17-1.97)]. These were larger than HR from the equivalent conventional analyses, despite some attenuation by adjustment for social indicators and smoking.Conclusions
Analyses using offspring BMI as a proxy for parental BMI suggest that the apparent adverse consequences of low BMI are considerably overestimated and adverse consequences of overweight are underestimated in conventional epidemiological studies.
SUBMITTER: Hypponen E
PROVIDER: S-EPMC7612209 | biostudies-literature |
REPOSITORIES: biostudies-literature
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| S-EPMC6688790 | biostudies-literature
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Project description:BackgroundObesity, typically quantified in terms of Body Mass Index (BMI) exceeding threshold values, is considered a leading cause of premature death worldwide. For given body size (BMI), it is recognized that risk is also affected by body shape, particularly as a marker of abdominal fat deposits. Waist circumference (WC) is used as a risk indicator supplementary to BMI, but the high correlation of WC with BMI makes it hard to isolate the added value of WC.Methods and findingsWe considered a USA population sample of 14,105 non-pregnant adults (age ≥ 18) from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 with follow-up for mortality averaging 5 yr (828 deaths). We developed A Body Shape Index (ABSI) based on WC adjusted for height and weight: ABSI ≡ WC/(BMI(2/3)height(1/2)). ABSI had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of +33% per standard deviation of ABSI [95% confidence interval: +20%-+48%), whereas elevated death rates were found for both high and low values of BMI and WC. 22% (8%-41%) of the population mortality hazard was attributable to high ABSI, compared to 15% (3%-30%) for BMI and 15% (4%-29%) for WC. The association of death rate with ABSI held even when adjusted for other known risk factors including smoking, diabetes, blood pressure, and serum cholesterol. ABSI correlation with mortality hazard held across the range of age, sex, and BMI, and for both white and black ethnicities (but not for Mexican ethnicity), and was not weakened by excluding deaths from the first 3 yr of follow-up.ConclusionsBody shape, as measured by ABSI, appears to be a substantial risk factor for premature mortality in the general population derivable from basic clinical measurements. ABSI expresses the excess risk from high WC in a convenient form that is complementary to BMI and to other known risk factors.
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Project description:BACKGROUND:Body Mass Index (BMI), like most human phenotypes, is substantially heritable. However, BMI is not normally distributed; the skew appears to be structural, and increases as a function of age. Moreover, twin correlations for BMI commonly violate the assumptions of the most common variety of the classical twin model, with the MZ twin correlation greater than twice the DZ correlation. This study aimed to decompose twin correlations for BMI using more general skew-t distributions. METHODS:Same sex MZ and DZ twin pairs (N = 7,086) from the community-based Washington State Twin Registry were included. We used latent profile analysis (LPA) to decompose twin correlations for BMI into multiple mixture distributions. LPA was performed using the default normal mixture distribution and the skew-t mixture distribution. Similar analyses were performed for height as a comparison. Our analyses are then replicated in an independent dataset. RESULTS:A two-class solution under the skew-t mixture distribution fits the BMI distribution for both genders. The first class consists of a relatively normally distributed, highly heritable BMI with a mean in the normal range. The second class is a positively skewed BMI in the overweight and obese range, with lower twin correlations. In contrast, height is normally distributed, highly heritable, and is well-fit by a single latent class. Results in the replication dataset were highly similar. CONCLUSIONS:Our findings suggest that two distinct processes underlie the skew of the BMI distribution. The contrast between height and weight is in accord with subjective psychological experience: both are under obvious genetic influence, but BMI is also subject to behavioral control, whereas height is not.
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