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Body mass index, waist circumference, and mortality in subjects older than 80 years: a Mendelian randomization study.
Lv, Yuebin; Zhang, Yue; Li, Xinwei; Gao, Xiang; Ren, Yongyong; Deng, Luojia; Xu, Lanjing; Zhou, Jinhui; Wu, Bing; Wei, Yuan; Cui, Xingyao; Xu, Zinan; Guo, Yanbo; Qiu, Yidan; Ye, Lihong; Chen, Chen; Wang, Jun; Li, Chenfeng; Luo, Yufei; Yin, Zhaoxue; Mao, Chen; Yu, Qiong; Lu, Hui; Kraus, Virginia Byers; Zeng, Yi; Tong, Shilu; Shi, Xiaoming.
Afiliación
  • Lv Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Zhang Y; Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
  • Li X; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Gao X; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
  • Ren Y; Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
  • Deng L; Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
  • Xu L; Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
  • Zhou J; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Wu B; Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China.
  • Wei Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Cui X; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Xu Z; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
  • Guo Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Qiu Y; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
  • Ye L; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Chen C; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
  • Wang J; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Li C; Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
  • Luo Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Yin Z; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
  • Mao C; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Yu Q; Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, China.
  • Lu H; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Kraus VB; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
  • Zeng Y; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Tong S; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
  • Shi X; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, #7 Panjiayuan Nanli, Chaoyang, Beijing 100021, China.
Eur Heart J ; 45(24): 2145-2154, 2024 Jun 28.
Article en En | MEDLINE | ID: mdl-38626306
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Índice de Masa Corporal / Circunferencia de la Cintura / Análisis de la Aleatorización Mendeliana Límite: Aged80 / Female / Humans / Male País/Región como asunto: Asia Idioma: En Revista: Eur Heart J Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Índice de Masa Corporal / Circunferencia de la Cintura / Análisis de la Aleatorización Mendeliana Límite: Aged80 / Female / Humans / Male País/Región como asunto: Asia Idioma: En Revista: Eur Heart J Año: 2024 Tipo del documento: Article País de afiliación: China
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