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All-cause mortality risk with different metabolic abdominal obesity phenotypes: the Rural Chinese Cohort Study

Published online by Cambridge University Press:  16 March 2023

Xiaoyan Wu
Affiliation:
Department of Cardio-Cerebrovascular Disease and Diabetes Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen, Guangdong, People’s Republic of China Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Yang Zhao
Affiliation:
Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Qionggui Zhou
Affiliation:
Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Minghui Han
Affiliation:
Department of Epidemiology and Health Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
Ranran Qie
Affiliation:
Department of Epidemiology and Health Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
Pei Qin
Affiliation:
Department of Medical Record Management, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, Guangdong, People’s Republic of China
Yanyan Zhang
Affiliation:
Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Zelin Huang
Affiliation:
Department of Biostatistics and Epidemiology, Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Jiong Liu
Affiliation:
Department of Biostatistics and Epidemiology, Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Fulan Hu
Affiliation:
Department of Biostatistics and Epidemiology, Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Xinping Luo
Affiliation:
Department of Biostatistics and Epidemiology, Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Ming Zhang
Affiliation:
Department of Biostatistics and Epidemiology, Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Yu Liu
Affiliation:
Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Xizhuo Sun*
Affiliation:
Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
Dongsheng Hu*
Affiliation:
Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People’s Republic of China
*
*Corresponding authors: Xizhuo Sun, email sunxz632@126.com; Dongsheng Hu, email dongshenghu563@126.com
*Corresponding authors: Xizhuo Sun, email sunxz632@126.com; Dongsheng Hu, email dongshenghu563@126.com
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Abstract

We aimed to investigate the association of metabolic obesity phenotypes with all-cause mortality risk in a rural Chinese population. This prospective cohort study enrolled 15 704 Chinese adults (38·86 % men) with a median age of 51·00 (interquartile range: 41·00–60·00) at baseline (2007–2008) and followed up during 2013–2014. Obesity was defined by waist circumference (WC: ≥ 90 cm for men and ≥ 80 cm for women) or waist-to-height ratio (WHtR: ≥ 0·5). The hazard ratio (HR) and 95 % CI for the risk of all-cause mortality related to metabolic obesity phenotypes were calculated using the Cox hazards regression model. During a median follow-up of 6·01 years, 864 deaths were identified. When obesity was defined by WC, the prevalence of participants with metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO) at baseline was 12·12 %, 2·80 %, 41·93 % and 43·15 %, respectively. After adjusting for age, sex, alcohol drinking, smoking, physical activity and education, the risk of all-cause mortality was higher with both MUNO (HR = 1·20, 95 % CI 1·14, 1·26) and MUO (HR = 1·20, 95 % CI 1·13, 1·27) v. MHNO, but the risk was not statistically significant with MHO (HR = 0·99, 95 % CI 0·89, 1·10). This result remained consistent when stratified by sex. Defining obesity by WHtR gave similar results. MHO does not suggest a greater risk of all-cause mortality compared to MHNO, but participants with metabolic abnormality, with or without obesity, have a higher risk of all-cause mortality. These results should be cautiously interpreted as the representation of MHO is small.

Information

Type
Research Article
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Nutrition Society
Figure 0

Fig. 1. Flow chart of the selection of participants.

Figure 1

Table 1. Baseline characteristics of study participants by metabolic obesity phenotypes

Figure 2

Table 2. Association of metabolic obesity phenotypes at baseline with risk of all-cause mortality

Figure 3

Fig. 2. Association of metabolic obesity phenotypes (by WC) at baseline with risk of all-cause mortality by sex and age. Abbreviations: HR, hazard ratio; MHNO, metabolically healthy non-obesity; MHO, metabolically healthy obesity; MUNO, metabolically unhealthy non-obesity; MUO, metabolically unhealthy obesity; WC, waist circumference. aPer 1000 person-years. bUnadjusted model. cAdjusted for sex, age, alcohol drinking, smoking, physical activity level and education. Each group adjusted for the other covariates except for itself.

Figure 4

Fig. 3. Association of metabolic obesity phenotypes (by WHtR) at baseline with risk of all-cause mortality by sex and age. Abbreviations: HR, hazard ratio; MHNO, metabolically healthy non-obesity; MHO, metabolically healthy obesity; MUNO, metabolically unhealthy non-obesity; MUO, metabolically unhealthy obesity; WHtR, waist-to-height ratio. aPer 1000 person-years. bUnadjusted model. cAdjusted for sex, age, alcohol drinking, smoking, physical activity level and education. Each group adjusted for the other covariates except for itself.

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Wu et al. supplementary material

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