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. 2024 Jun 28;45(24):2145-2154.
doi: 10.1093/eurheartj/ehae206.

Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study

Yuebin Lv  1 , Yue Zhang  2 , Xinwei Li  1   3 , Xiang Gao  4 , Yongyong Ren  2 , Luojia Deng  2 , Lanjing Xu  1   5 , Jinhui Zhou  1 , Bing Wu  1   6 , Yuan Wei  1   3 , Xingyao Cui  1   3 , Zinan Xu  1   7 , Yanbo Guo  1   3 , Yidan Qiu  1   5 , Lihong Ye  1   8 , Chen Chen  1 , Jun Wang  1 , Chenfeng Li  1   9 , Yufei Luo  1   9 , Zhaoxue Yin  10 , Chen Mao  7 , Qiong Yu  3 , Hui Lu  2 , Virginia Byers Kraus  11 , Yi Zeng  12 , Shilu Tong  1   13 , Xiaoming Shi  1
Affiliations

Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study

Yuebin Lv et al. Eur Heart J. .

Abstract

Background and aims: Emerging evidence has raised an obesity paradox in observational studies of body mass index (BMI) and health among the oldest-old (aged ≥80 years), as an inverse relationship of BMI with mortality was reported. This study was to investigate the causal associations of BMI, waist circumference (WC), or both with mortality in the oldest-old people in China.

Methods: A total of 5306 community-based oldest-old (mean age 90.6 years) were enrolled in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) between 1998 and 2018. Genetic risk scores were constructed from 58 single-nucleotide polymorphisms (SNPs) associated with BMI and 49 SNPs associated with WC to subsequently derive causal estimates for Mendelian randomization (MR) models. One-sample linear MR along with non-linear MR analyses were performed to explore the associations of genetically predicted BMI, WC, and their joint effect with all-cause mortality, cardiovascular disease (CVD) mortality, and non-CVD mortality.

Results: During 24 337 person-years of follow-up, 3766 deaths were documented. In observational analyses, higher BMI and WC were both associated with decreased mortality risk [hazard ratio (HR) 0.963, 95% confidence interval (CI) 0.955-0.971 for a 1-kg/m2 increment of BMI and HR 0.971 (95% CI 0.950-0.993) for each 5 cm increase of WC]. Linear MR models indicated that each 1 kg/m2 increase in genetically predicted BMI was monotonically associated with a 4.5% decrease in all-cause mortality risk [HR 0.955 (95% CI 0.928-0.983)]. Non-linear curves showed the lowest mortality risk at the BMI of around 28.0 kg/m2, suggesting that optimal BMI for the oldest-old may be around overweight or mild obesity. Positive monotonic causal associations were observed between WC and all-cause mortality [HR 1.108 (95% CI 1.036-1.185) per 5 cm increase], CVD mortality [HR 1.193 (95% CI 1.064-1.337)], and non-CVD mortality [HR 1.110 (95% CI 1.016-1.212)]. The joint effect analyses indicated that the lowest risk was observed among those with higher BMI and lower WC.

Conclusions: Among the oldest-old, opposite causal associations of BMI and WC with mortality were observed, and a body figure with higher BMI and lower WC could substantially decrease the mortality risk. Guidelines for the weight management should be cautiously designed and implemented among the oldest-old people, considering distinct roles of BMI and WC.

Keywords: Body mass index; Causal inference; Mendelian randomization; Mortality; Waist circumference.

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Figures

Structured Graphical Abstract
Structured Graphical Abstract
Opposite causal associations of body mass index (BMI) and waist circumference (WC) with mortality among Chinese oldest-old based on 1998–2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). Upper: a scheme for the study design. Left lower: non-linear Mendelian randomization results for the causal association of BMI and WC with mortality. Right lower: joint effect analyses of BMI and WC on mortality. CVD, cardiovascular disease.
Figure 1
Figure 1
A diagram of assumptions for Mendelian randomization. The three assumptions are as follows: (1) the genetic variant is robustly associated with the exposure body mass index or waist circumference, (2) the genetic variant should not be associated with confounders of the body mass index–mortality or waist circumference–mortality association, and (3) the genetic variant must influence the mortality only through the exposure body mass index or waist circumference
Figure 2
Figure 2
Associations of body mass index and waist circumference with all-cause, cardiovascular disease, and non-cardiovascular disease mortality in Cox models, and their linear Mendelian randomization causal effect estimates using two-stage least squares regression model. WC, waist circumference; HR, hazard ratio. #Data were adjusted for sex and age
Figure 3
Figure 3
Non-linear Mendelian randomization of body mass index and waist circumference regarding all-cause, cardiovascular disease, and non-cardiovascular disease mortality. Dose-response curves between body mass index and all-cause (left), cardiovascular disease (middle), and non-cardiovascular disease (right) mortality are shown in the upper row. Curves for waist circumference regarding all-cause, cardiovascular disease, and non-cardiovascular disease mortality are shown in the lower row. Gradient at each point of the curve is the localized average causal effect. The shaded areas represent 95% confidence intervals
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