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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.
In China, most cities have gradually controlled the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and brought coronavirus disease 2019 (COVID-19) under control locally. This means that crucial work has shifted from internal management of the pandemic to external prevention and control, especially management of international travelers and imported goods. There is much uncertainty about variants of concern for SARS-CoV-2, which pose challenges to the steady resumption of social and economic life once the mutant strains begin to spread. The sporadic outbreaks of COVID-19 in different provinces of China caused by these mutant strains emphasizes the need for both prevention and control measures. Therefore, we introduce China’s experience with preventing and controlling COVID-19 in the postpandemic period, which may serve as a reference in various settings.
Metabolically healthy obesity refers to a subset of obese people with a normal metabolic profile. We aimed to explore the association between metabolically healthy and obesity status and risk of hypertension among Chinese adults from The Rural Chinese Cohort Study. This prospective cohort study enrolled 9137 Chinese adults without hypertension, type 2 diabetes or treatment for lipid abnormality at baseline (2007–2008) and followed up during 2013–2014. Modified Poisson regression models were used to examine the risk of hypertension by different metabolically healthy and obesity status, estimating relative risks (RR) and 95 % CI. During 6 years of follow-up, we identified 1734 new hypertension cases (721 men). After adjusting for age, sex, smoking and other confounding factors, risk of hypertension was increased with metabolically healthy general obesity (MHGO) defined by BMI (RR 1·75, 95 % CI 1·02, 3·00) and metabolically healthy abdominal obesity (MHAO) defined by waist circumference (RR 1·51, 95 % CI 1·12, 2·04) as compared with metabolically healthy non-obesity. The associations between metabolically healthy and obesity status and hypertension outcome were consistent after stratifying by sex, age, smoking, alcohol drinking and physical activity. Both MHGO and MHAO were associated with increased risk of hypertension. Obesity control programmes should be implemented to prevent or delay the development of hypertension in rural China.
To compare the ability of a body shape index (ABSI) and body adiposity estimator (BAE) to BMI, waist circumference (WC) and waist:height ratio (WHtR) for predicting development of type 2 diabetes mellitus (T2DM) in rural adult Chinese. The prospective cohort study included 11 687 eligible participants who were free of T2DM at baseline. The risk of new-onset T2DM for ABSI, BAE, BMI, WC and WHtR quintiles was estimated by Cox proportional-hazards regression at follow-up. We also compared the power of ABSI and BAE to BMI, WC and WHtR for predicting the development of T2DM. With increasing ABSI, BAE, BMI, WC and WHtR, T2DM incidence was substantially increased (Ptrend<0·0001). After adjustment for multi-covariates, risk of T2DM was increased from the second to fifth quintile as compared with first quintile for ABSI (1·27; 95 % CI 0·95, 1·69; 1·35; 95 % CI 1·00, 1·82; 1·75; 95 % CI 1·33, 2·32 and 1·87; 95 % CI 1·40, 2·49; Ptrend<0·0001); BAE (1·82; 95 % CI 1·38, 2·41; 1·93; 95 % CI 1·38, 2·68; 2·73; 95 % CI 1·94, 3·84 and 4·18; 95 % CI 2·98, 5·87; Ptrend<0·0001); BMI (1·42; 95 % CI 1·03, 1·97; 1·62; 95 % CI 1·18, 2·23; 2·59; 95 % CI 1·92, 3·50 and 3·90; 95 % CI 2·90, 5·26; Ptrend<0·0001); WC (1·53; 95 % CI 1·08, 2·17; 1·66; 95 % CI 1·18, 2·33; 2·72; 1·97, 3·76 and 4·09; 95 % CI 2·97, 5·62; Ptrend<0·0001); and WHtR (1·40; 95 % CI 0·98, 1·99; 2·06; 95 % CI 1·47, 2·88; 2·90; 95 % CI 2·10, 4·01 and 4·22; 95 % CI 3·05, 5·85; Ptrend<0·0001). ABSI, BAE, BMI, WC and WHR were effective and comparable in discriminating cases from non-cases of T2DM. Risk of T2DM was increased with elevated ABSI and BAE, but the predictive ability for T2DM did not differ than that of BMI, WC and WHtR in a rural Chinese population.
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