Objective: The relationship between physical activity (PA) and the risk of frailty has not reached a conclusive result. This systematic review with meta-analysis aimed to evaluate the effect of PA on the onset of frailty in the community-dwelling middle and older age adults by pooling data from cohort studies. Methods: A systematic literature search was performed via PubMed, Embase, and Web of Science up to June 01, 2021. Pooled adjusted effect estimates (ES) with 95% confidence interval (CI) were calculated by using the random-effect model and by comparing the highest with lowest levels of PA. Heterogeneity was tested using the I² statistic and Q-test. The quality of evidence was evaluated by using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results: A total of ten cohort studies with 14 records were selected, and the GRADE approach classified the quality of evidence as low. In comparison with the lowest level of PA, the highest level of PA was associated with 41% decreased odds of frailty (ES: 0.59, 95% CI: 0.51–0.67; I² = 70.0%, P_{-heterogeneity} < 0.001) after pooling results from included studies. In stratified analysis by frailty assessment approach, the highest level of PA was significantly associated with 37% (ES 0.63, 95% CI: 0.52–0.77, 49% (ES: 0.51, 95% CI: 0.41–0.63), and 30% (ES: 0.70, 95% CI: 0.65–0.75) reduced odds of frailty when pooling studies using criteria of physical frailty, multidimensional model, and accumulation of disability, respectively. Stratified analyses further by PA indicators and PA assessment tools yielded similar protective effects in any subgroups. Conclusions: This study with moderate-certainty evidence shows that a higher level of PA was associated with lower odds of frailty, and the benefits of PA for frailty prevention were independent of frailty assessment tools, PA indicators, and PA assessment methods. Findings from this study may help implement active exercise strategies to prevent frailty.

Background: Obesity is a crucial risk factor for obstructive sleep apnea (OSA), but the association between adiposity deposition and OSA risk has not reached a consistent conclusion. This study sought to reveal the association of multiple adiposity indicators with OSA risk. Methods: This cross-sectional study included 9,733 participants aged 35–74 years, recruited from an ongoing population-based cohort. OSA was assessed by the Berlin Questionnaire. Six adiposity indicators, including neck circumference (NC), body fat percentage (BF%), waist-to-hip ratio (WHR), visceral adiposity index (VAI), lipid accumulation product (LAP), and resting metabolic rate (RMR), were selected. Multivariate logistic regression models were used to examine the association of adiposity indicators with OSA risk. Results: One thousand six hundred twenty-six participants (16.71%) were classified into the OSA group. NC, BF%, WHR, VAI, LAP, and RMR were all positively associated with the risk of OSA after adjusting for confounders, regardless of age, sex, and history of dyslipidemia. Every 1-unit increment of NC, BF%, and VAI was associated with a 13%, 9%, and 14% increased risk of OSA, respectively; every 0.01-unit increment of WHR was associated with a 3% increased risk of OSA; every 10-unit increment of LAP and RMR was associated with 2% and 4% increased risk of OSA, respectively. Conclusions: NC, BF%, WHR, VAI, LAP, and RMR were all independently and positively associated with OSA risk, regardless of age, sex, history of dyslipidemia, and menopausal status. Application of these new indicators could help to more comprehensively reflect and predict the risk of OSA in the general population.

Background: Data are limited on whether several easily measured indices are independent predictors of type 2 diabetes mellitus (T2DM) in hypertensive patients. This study aimed to assess the association of hypertriglyceridemic-waist phenotype, triglyceride glucose (TyG) index, lipid accumulation product (LAP), and visceral adiposity index (VAI) with T2DM risk in hypertensive patients. Methods: This cross-sectional study included 5321 hypertensive patients from the baseline survey of the Guangzhou Heart Study. Face-to-face questionnaire survey, physical examination, and fasting blood sample collection were completed for all subjects. Odds ratio (OR) with 95% confidence interval (95% CI) were calculated by using the logistic regression model. The potential nonlinear relationship was examined using restricted cubic spline regression. Results: The prevalence of T2DM was 19.98% among hypertensive patients. After adjusting for confounders, participants with elevated triglyceride levels and enlarged waist circumference (HTGW) were associated with a 2.57-fold risk of T2DM (OR 2.57, 95% CI 2.05, 3.23). When comparing with subjects within the lowest quartile of the indices, those in the highest quartile of TyG, LAP, and VAI were associated with 5.35-fold (95% CI 4.33, 6.64), 2.65-fold (95% CI 2.11, 3.34), and 2.17-fold (95% CI 1.77, 2.67) risk of T2DM after adjusting for confounders. Every 1-unit increment of TyG, LAP, and VAI was associated with 81%, 38%, and 31% increased risk of T2DM, respectively. The nonlinear association was observed for TyG, LAP, and VAI (all P_Non-linear < 0.001). Conclusions: The results found that among hypertensive patients, HTGW and a higher level of TyG, LAP, and VAI were associated with an elevated risk of T2DM. The findings suggested that HTGW, TyG, LAP, and VAI may serve as simple and effective tools for T2DM risk assessment in the prevention and management of main chronic diseases.

Background: No studies investigated the whole effect of modifiable lifestyle factors on OSA risk. This study aimed to examine the individual and combined effects of lifestyle factors on OSA risk among Chinese adults. Methods: This cross-sectional study included 9733 participants aged 35 to 74 years from the baseline survey of Guangzhou Heart Study. OSA was evaluated by Berlin Questionnaire. The healthy lifestyle score (HLS), representing the overall effect of lifestyles, was derived from seven lifestyle factors: active smoking, passive smoking, alcohol, diet, waist-hip ratio, leisure-time physical activity, and mental status. Odds ratio (OR) with 95% confidence interval (CI) was calculated using the multivariate logistic regression model. Results: 8107 participants were divided into the non-OSA group and 1626 participants into the OSA group. No passive smoking (OR 0.83, 95% CI 0.74–0.94), healthy waist-hip ratio (OR 0.67, 95% CI 0.58–0.77) and healthy mental status (OR 0.45, 95% CI 0. 29–0.73) were associated with a reduced risk of OSA after adjusting for confounders, while others not. Participants with higher HLS were negatively associated with OSA risk (P_-trend < 0.001). In comparison to the participants with 0–3 HLS, the OR for participants with 4, 5, 6, and 7 HLS was 0.68 (95% CI 0.56–0.84), 0.71 (95% CI 0.59–0.86), 0.62 (95% CI 0.51–0.76) and 0.49 (95% CI 0.37–0.65) after adjusting for confounders. Every 1-score increment of HLS was associated with a 13% lower risk of OSA. Conclusions: The results suggest that HLS reflecting the combined effect of multiple-dimensional lifestyle factors was inversely associated with OSA risk. Preventive strategies integrating multiple lifestyle factors may provide a more feasible approach for OSA prevention.

Background: Limited evidence was available on the association of the integrated effect of multidimensional lifestyle factors with mortality among Chinese populations. This cohort study was to examine the effect of combined lifestyle factors on the risk of mortality by highlighting the number of healthy lifestyles and their overall effects.Methods: A total of 11,395 participants from the Guangzhou Heart Study (GZHS) were followed up until 1 January 2020. Individual causes of death were obtained from the platform of the National Death Registry of China. The healthy lifestyle index (HLI) was established from seven dimensions of lifestyle, and lifestyle patterns were extracted from eight dimensions of lifestyle using principal component analysis (PCA). Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using the Cox proportional hazard regression model.Results: During 35,837 person-years of follow-up, 184 deaths (1.61%) were observed, including 64 from cardiovascular disease. After adjustment for confounders, HLI was associated with a 50% (HR: 0.50, 95% CI: 0.25–0.99) reduced risk of all-cause mortality when comparing the high (6–7 lifestyle factors) with low (0–2 lifestyle factors) categories. Three lifestyle patterns were defined and labeled as pattern I, II, and III. Lifestyle pattern II with higher factor loadings of non-smoking and low-level alcohol drinking was associated with a decreased risk of all-cause mortality (HR: 0.63, 95% CI: 0.43–0.92, P_–trend = 0.023) when comparing the high with low tertiles of pattern score, after adjustment for confounders. Every 1-unit increment of pattern II score was associated with a decreased risk (HR: 0.97, 95% CI: 0.95–0.99) of all-cause mortality. The other two patterns were not associated with all-cause mortality, and the association of cardiovascular mortality risk was observed with neither HLI nor any lifestyle pattern.Conclusion: The results suggest that the more dimensions of the healthy lifestyle the lower the risk of death, and adherence to the lifestyle pattern characterized with heavier loading of non-smoking and low-level alcohol drinking reduces the risk of all-cause mortality. The findings highlight the need to consider multi-dimensional lifestyles rather than one when developing health promotion strategies.