Network analysis of smoking-related sleep characteristics in Chinese adults.

The associations between multiple sleep characteristics and smoking behavior are inconsistent, and it is unclear which sleep characteristics are most crucial for tobacco prevention. This study aimed to explore the associations between smoking status/intensity and multiple sleep characteristics and to identify the potential core domain of smoking-related sleep using network analysis. Data were obtained from a survey of cancer-related risk factors among Chinese adults. Logistic regression models were used to quantify the associations between sleep characteristics and smoking status/intensity. Network analyses were employed to identify the core sleep characteristics. A total of 5,228 participants with a median age of 44 years old were included in the study. Current smoking was significantly positively associated with long nap time, difficulty falling asleep, late bedtime, getting up after 7 am, and waking up earlier than expected. There was significant positive association between current smoking and short sleep duration in young adults under 45 years old. Late bedtime and getting up after 7 am were only associated with current heavy smoking, but not current light smoking. Network analyses showed that multiple smoking-related sleep characteristics were interconnected, with difficulty falling asleep and late bedtime as central characteristics in the network. The study found that the associations between sleep characteristics and smoking varied by age and smoking intensity and highlights the potential benefits of sleep health promotion in smoking cessation, with a particular focus on difficulty falling asleep and late bedtime.

Associations of body mass index trajectory, waist circumference trajectory, or both with type 2 diabetes mellitus risk in Chinese adults: The China-PAR project.

AIMS: To identify the trajectories of body mass index (BMI) and waist circumference (WC), and assess the associations of BMI trajectory, WC trajectory, or the two combined, with type 2 diabetes mellitus (T2DM) risk in Chinese adults. MATERIALS AND METHODS: This study was based on a prospective project-the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR). A total of 54 434 participants (39.21% men) who were measured on at least two occasions were included. Three slowly increasing trajectory patterns were identified for BMI, and four for WC, by latent mixed modelling. A nine-category variable was derived by combining the WC trajectory (low, moderate, moderate-high/high) and the BMI trajectory (low, moderate, high). Logistic regression models were applied to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: The risk of developing T2DM increased with elevated BMI or WC trajectory levels (all ptrend <0.001). The risks were 2.85 (2.59-3.14) for high BMI trajectory and 4.34 (3.78-4.99) for high WC trajectory versus low trajectory groups, respectively. The association was more pronounced among younger individuals (pinteraction <0.001). In the joint analysis, compared to participants with low WC and BMI trajectory, those with moderate-high/high WC combined with high BMI trajectory had the highest risk of T2DM (OR 3.96, 95% CI 3.48-4.50); even those who maintained moderate-high/high WC but low BMI trajectory showed a higher T2DM risk (OR 3.00, 95% CI 2.31-3.91). CONCLUSIONS: This study suggests that simultaneous dynamic and continuous monitoring of BMI and WC may contribute more than single measurements to predicting T2DM risk and determining preventive strategies.

Physical activity domains and patterns with risk of depressive symptoms: A cross-sectional study in China.

BACKGROUND: The health benefits of domain-specific physical activity (PA) on depressive symptoms were inconclusive. Few studies explored PA patterns and depressive symptoms. This study aimed to investigate the associations of PA domains and patterns with depressive symptoms. METHODS: We conducted a cross-sectional study in China with 5047 adults. Latent class analysis was applied to identify the PA patterns and logistic regression analysis was used to calculate odds ratios (ORs) and 95 % confidence intervals (CIs). RESULTS: The ORs (95 % CIs) for the active versus inactive groups were 0.79 (0.69-0.91) for leisure-time PA, 0.57 (0.49-0.65) for transport PA, 0.95 (0.82-1.09) for household PA, and 1.38 (1.18-1.62) for occupational PA. We found non-linear associations between leisure-time PA, transport PA and depressive symptoms, with the lowest risk at 11 METs-h/week of leisure-time PA (equal to 147 min/week moderate PA or 88 min/week vigorous PA) and 23 METs-h/week of transport PA. There was a marginal inverse association with household PA for men while not for women. We identified four PA patterns and found a lower risk of depressive symptoms associated with "low occupational PA pattern" versus "moderate PA level pattern" (0.45 (0.38-0.52)). LIMITATIONS: Given the cross-sectional design, causality cannot be inferred. CONCLUSIONS: Our study supported an inverse association of leisure-time PA and transport PA with depressive symptoms and a positive association of occupational PA. The observed inconsistent association of household PA among men and women, and the finding that "low occupational PA pattern" was associated with a lower risk of depressive symptoms warrant further investigation.

Dose-response association of Chinese visceral adiposity index with comorbidity of hypertension and diabetes mellitus among elderly people.

Background: Chinese visceral adiposity index (CVAI) is a reliable indicator of visceral obesity, but little is known about the association of CVAI with comorbidity of hypertension (HTN) and diabetes mellitus (DM). This study aimed to explore the associations of CVAI with HTN-DM comorbidity, HTN or DM, HTN, and DM in elderly people and evaluate the mediating role of insulin resistance in the associations. Methods: A total of 3,316 Chinese participants aged ≥60 years were included in this cross-sectional study. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic splines were applied to explore the dose-response associations. Mediation analyses were used to assess the mediating effect of triglyceride-glucose (TyG) index in the associations. Results: The prevalence rate of HTN-DM comorbidity, HTN or DM, HTN, and DM was 13.78%, 72.26%, 67.16%, and 18.88%, respectively. Linear associations between CVAI and HTN-DM comorbidity, HTN or DM, HTN, and DM were found, and ORs (95%CIs) were 1.45 (1.30-1.61), 1.39 (1.28-1.52), 1.36 (1.25-1.48), and 1.28 (1.16-1.41) for per SD increase in CVAI. Compared with quartile 1 of CVAI, the risk of HTN-DM comorbidity, HTN or DM, HTN, and DM increased 190%, 125%, 112%, and 96% for quartile 4. In addition, we found TyG index playing a key role in the associations of CVAI with HTN-DM comorbidity, HTN or DM, and DM. Conclusion: CVAI is linearly and positively correlated with HTN-DM comorbidity, HTN or DM, HTN, and DM. The potential mechanism is insulin resistance largely mediating the associations.

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

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.

Dose-Response Association of Low and Normal Ankle Brachial Index With the Risk of Cardiovascular Disease Morbidity and Mortality.

We quantitatively evaluated the dose-response association of low and normal ankle brachial index (ABI) with the risk of morbidity and mortality from cardiovascular diseases (CVDs). PubMed, Embase, and Web of Science were systematically searched for cohort studies. Random effects or fixed effects models were used to estimate the pooled relative risks (RRs) and 95% confidence intervals (95% CIs). Generalized least squares regression was used to assess study-specific dose-response associations per 0.1 ABI decrease. Restricted cubic splines were used to evaluate linear or nonlinear trends. Twelve cohort studies (57 031 participants) were included in this meta-analysis. For low vs normal ABI levels, the pooled RRs were 2.03 (95% CI, 1.72-2.41; I2 = 52.9%; pheterogeneity=0.030) and 2.29 (95% CI, 1.98-2.64; I2 = 39.5%; pheterogeneity =0.158) for CVD morbidity and CVD mortality, respectively. For per 0.1 ABI decrease from 1.40 the risk for CVD morbidity and CVD mortality increased by 8% (1.08, 95% CI 1.04-1.11) and 11% (1.11, 95% CI 1.07-1.15), respectively. Restricted cubic splines showed inverse linear associations for CVD morbidity and CVD mortality. As a non-invasive index, lower ABI was significantly associated with the increased risk of morbidity and mortality from CVDs in an inverse linear manner.

Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of SLC30A8 gene: a nested case-control study.

To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of SLC30A8 gene and T2DM risk, and the interactions among SNPs, methylation, and environmental factors on T2DM risk. We genotyped 9 SNPs and tested methylation at 46 CpG loci of SLC30A8 in the baseline DNA of 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study. A conditional logistic regression model was used to estimate the associations between SNPs and SLC30A8 methylation and T2DM risk. Multifactor Dimensionality Reduction analysis was used to estimate the effect of interactions among SNPs, methylation, and environment on T2DM risk. Probability of T2DM was decreased with rs11558471 (GG vs. AA, OR = 0.55, 95% CI 0.32, 0.96), with rs13266634 (TT vs. CC, OR = 0.55, 95% CI 0.32, 0.94), with rs3802177 (AA vs. GG, OR = 0.54, 95%CI 0.31, 0.94), and its probability was increased with rs2466293 of SLC30A8 (GA vs. AA, OR = 1.63, 95% CI 1.08-2.47). Its probability was also significantly associated with methylation of CG9 and CG45 (OR = 0.56 [95% CI 0.33-0.97] and 1.61 [95%CI 1.03--2.51]). T2DM probability was significantly associated with the interaction effect between rs2466293 and hypertension (p = 0.045). T2DM probability was also significantly associated with the combination effects of rs2466293 with BMI, hypertension, and hypertriglyceridemia, with the combination effects of hypertriglyceridemia with rs11558471, rs13266634, and methylation of CG45.

Joint effect of physical activity and blood lipid levels on all-cause and cardiovascular disease mortality: The Rural Chinese Cohort Study.

BACKGROUND AND AIMS: We aimed to evaluate the joint effect of physical activity (PA) and blood lipid levels on all-cause and cardiovascular disease (CVD) mortality. METHODS AND RESULTS: We analyzed 17,236 participants from the Rural Chinese Cohort Study. Cox's proportional-hazards regression models were used to assess the hazard ratios (HRs) and 95% confidence intervals (CIs) between the joint effect of PA and blood lipid levels and risk of all-cause and CVD mortality. Restricted cubic splines were used to estimate the dose-response relationship of PA with risk of all-cause and CVD mortality. During a median follow-up of 6.01 years there were 1106 deaths (484 from CVD) among participants. For all-cause mortality, compared with the group with dyslipidemia and extremely light PA (ELPA), the HRs with dyslipidemia and light PA (LPA), moderate PA (MPA), and heavy PA (HPA) were 0.56 (95% CI 0.45-0.70), 0.59 (0.46-0.75), and 0.59 (0.45-0.78), respectively, while the HRs of groups with normal lipid levels and ELPA, LPA, MPA, and HPA were 0.88 (0.72-1.04), 0.59 (0.48-0.73), 0.53 (0.41-0.67), and 0.38 (0.29-0.50), respectively. We observed similar effects on CVD mortality. Restricted cubic splines showed a curvilinear relationship between PA and risk of all-cause and CVD mortality with normal lipid levels and with dyslipidemia. CONCLUSION: Higher PA reduces the risk of all-cause and CVD mortality. Higher levels of PA are needed in the population.

Association between cardiorespiratory fitness and risk of all-cause and cause-specific mortality.

OBJECTIVE: The association of cardiorespiratory fitness (CRF) with all-cause and cause-specific mortality remains unclear in Chinese population. This study aimed to evaluate the risk of all-cause, cardiovascular disease (CVD), cancer and other-cause mortality in Chinese adults using estimated CRF (eCRF). PATIENTS AND METHODS: We analysed data for 15,566 participants aged ≥20 years recruited in The Rural Chinese Cohort Study during 2007 to 2008 and followed for mortality during 2013 to 2014. eCRF was calculated with sex-specific longitudinal non-exercise algorithms. Cox proportional-hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cause-specific mortality risk according to baseline eCRF. RESULTS: During a median of 6.01 years of follow-up, 859 deaths occurred, including 359 from CVD, 221 from cancer, and 279 from other causes. Each 1 metabolic equivalent increment in eCRF was associated with decreased risk of all-cause mortality (men: HR 0.70, 95% CI [0.66-0.74]; women: 0.59, [0.54-0.64]); CVD mortality (men: 0.70 [0.64-0.77]; women: 0.55, [0.48-0.62]); and other-cause mortality (men: 0.68 [0.62-0.75]; women: 0.57, [0.49-0.66]). The area under receiver operating characteristic curve was significantly higher for eCRF than its modifiable components (waist circumference, body mass index and resting heart rate) in predicting all-cause and cause-specific mortality incidence (all p < .001). CONCLUSION: eCRF was inversely associated with all-cause, CVD and other-cause mortality.

Cardiorespiratory fitness and mortality from all causes, cardiovascular disease and cancer: dose-response meta-analysis of cohort studies.

OBJECTIVE: Current evidence of the associations between cardiorespiratory fitness (CRF) and mortality is limited. We performed a meta-analysis to assess the dose-response association of CRF with mortality from all causes, cardiovascular disease (CVD) and cancer in healthy population. METHODS: PubMed, EMBASE and Web of Science were searched up to 26 December 2019 for reports of cohort studies giving risk estimates for all-cause, CVD and cancer mortality by level of CRF. Cohort studies were included if CRF was assessed by an exercise stress test and reported as at least three levels or per incremental increase, and the association of CRF with all-cause, CVD and cancer mortality was evaluated. Generalised least-squares regression models were used to assess the quantitative relation of CRF with all-cause, CVD and cancer mortality. RESULTS: 34 cohort studies were eligible for the meta-analysis. The pooled relative risks (RRs) for all-cause, CVD and cancer mortality per one-metabolic equivalent increase in CRF were 0.88 (95% CI 0.83 to 0.93), 0.87 (95% CI0.83 to 0.91) and 0.93 (95% CI 0.91 to 0.96), respectively. As compared with lowest CRF, with intermediate CRF, the summary RRs for all-cause, CVD and cancer mortality were 0.67 (95% CI 0.61 to 0.74), 0.60 (95% CI 0.51 to 0.69) and 0.76 (95% CI 0.69 to 0.84), respectively, and with highest CRF were 0.47 (95% CI 0.39 to 0.56), 0.49 (95% CI 0.42 to 0.56) and 0.57 (95% CI 0.46 to 0.70), respectively. CONCLUSION: Our analysis showed inverse dose-response associations of CRF with all-cause, CVD and cancer mortality, which provides evidence for public health recommendations for preventing all-cause, CVD and cancer mortality. PROSPERO REGISTRATION NUMBER: CRD42020208883.

Independent and joint associations of non-exercise cardiorespiratory fitness and obesity with risk of type 2 diabetes mellitus in the Rural Chinese Cohort Study.

BACKGROUND AND AIMS: An association between cardiorespiratory fitness (CRF) and type 2 diabetes mellitus (T2DM) has not been established in the Chinese population. This study aimed to estimate the independent and joint associations of CRF and obesity with T2DM incidence in the rural Chinese population. METHODS AND RESULTS: We conducted a prospective study of 11,825 non-T2DM subjects among rural Chinese adults. Cox regression models were used to estimate the independent and joint associations between CRF and obesity exposure on T2DM. Restricted cubic splines were used to model the dose-response association. During a median follow-up of 6.01 years, 835 participants developed T2DM. In comparison to quartile 1 of CRF, the multivariate hazard ratios (HRs) and 95% confidence intervals (CIs) of quartiles 2, 3, 4 were 0.75 (0.61-0.91), 0.54 (0.43-0.68), and 0.42 (0.32-0.55), respectively. When stratified by sex, the results were similar. Joint analyses showed that overweight/obesity-unfit individuals had a 2.28 times higher risk of developing T2DM than the normal weight-fit referent (HR 2.28, 95% CI 1.84-2.83; Pinteraction <0.001). The risk for the overweight/obesity-fit category (HR 1.61, 95% CI 1.21-2.15) was larger than for the normal weight-unfit category (HR 1.38, 95% CI 0.97-1.95) versus the normal weight-fit referent. Similar joint associations for waist circumference and CRF with T2DM were also observed. CONCLUSION: A negative association was observed between CRF and risk of T2DM. Overweight/obese or abdominal obesity and unfit participants showed the highest risks of T2DM. It is therefore strongly recommended that fitness-enhancing be encouraged for the prevention of T2DM, especially among obesity participants.

Metabolic Score for Visceral Fat: a novel predictor for the risk of type 2 diabetes mellitus.

To investigate the association between the Metabolic Score for Visceral Fat (METS-VF) and risk of type 2 diabetes mellitus (T2DM) and compare the predictive value of the METS-VF for T2DM incidence with other obesity indices in Chinese people. A total of 12 237 non-T2DM participants aged over 18 years from the Rural Chinese Cohort Study of 2007-2008 were included at baseline and followed up during 2013-2014. The cox proportional hazards regression was used to calculate hazard ratios (HR) and 95 % CI for the association between baseline METS-VF and T2DM risk. Restricted cubic splines were used to model the association between METS-VF and T2DM risk. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the ability of METS-VF to predict T2DM incidence. During a median follow-up of 6·01 (95 % CI 5·09, 6·06) years, 837 cases developed T2DM. After adjusting for potential confounding factors, the adjusted HR for the highest v. lowest METS-VF quartile was 5·97 (95 % CI 4·28, 8·32), with a per 1-sd increase in METS-VF positively associated with T2DM risk. Positive associations were also found in the sensitivity and subgroup analyses, respectively. A significant nonlinear dose-response association was observed between METS-VF and T2DM risk for all participants (Pnonlinearity = 0·0347). Finally, the AUC value of METS-VF for predicting T2DM was largest among six indices. The METS-VF may be a reliable and applicable predictor of T2DM incidence in Chinese people regardless of sex, age or BMI.

Metabolic Score for Visceral Fat: A reliable indicator of visceral obesity for predicting risk for hypertension.

OBJECTIVES: The aim of this study was to investigate the association of the Metabolic Score for Visceral Fat (METS-VF) with the risk for hypertension and to compare the ability of the METS-VF, the metabolic score for insulin resistance, visceral adiposity index, waist-to-height ratio, waist circumference, and body mass index to predict hypertension incidence based on a large prospective study of rural Chinese individuals. METHODS: In all, 10 297 non-hypertensive adults (≥18 y of age) from a rural Chinese cohort study in 2007 and 2008 were included at baseline and followed up in 2013 and 2014. Multivariable logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between baseline METS-VF and hypertension risk. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the ability of METS-VF to predict hypertension incidence. RESULTS: We identified 2071 hypertension cases during follow-up. After adjusting for multivariable confounding factors, the adjusted ORs (95% CIs) for the highest versus lowest METS-VF quartile overall and for men and women were 3.84 (3.23-4.56), 3.25 (2.48-4.24), and 4.14 (3.30-5.20), respectively. Also, per-SD increase in METS-VF was positively associated with hypertension risk overall and for men and women. Similar results were found in the sensitivity and subgroup analyses. Finally, the AUC value for hypertension was higher for METS-VF than the other five indices overall and for men and women. CONCLUSIONS: The present study indicated that METS-VF was positively associated with hypertension incidence and performed better in predicting hypertension risk than five other indices, which suggests that METS-VF is a reliable predictor of hypertension in the Chinese population.

Fried-food consumption and risk of overweight/obesity, type 2 diabetes mellitus, and hypertension in adults: a meta-analysis of observational studies.

Recent studies have reported conflicting associations of fried-food consumption and risk of overweight/obesity, type 2 diabetes mellitus (T2DM) and hypertension, and a meta-analysis is not available. We aimed to explore the association between fried-food consumption and risk of overweight/obesity, T2DM and hypertension in adults through a meta-analysis. We searched PubMed, EMBASE, and Web of Science for studies published up to 17 June 2020. Pooled relative risks (RRs) and 95% confidence intervals (CIs) were calculated by random-effects models. In comparing the highest to lowest fried-food intake, the pooled RRs (95% CIs) were 1.16 (1.07-1.25; I2 = 71.0%, Pheterogeneity < 0.001) for overweight/obesity (cohort: 1.19 [0.97-1.47], n = 2; cross-sectional: 1.14 [1.03-1.27], n = 9), 1.07 (0.90-1.27; 84.7%) for T2DM (cohort: 1.01 [0.89-1.15], n = 9; case-control: 2.33 [1.80-3.01], n = 1), and 1.20 (1.05-1.38; I2=91.8%) for hypertension (cohort: 1.06 [0.98-1.15], n = 8; cross-sectional: 2.16 [0.59-7.87], n = 3). Our meta-analysis indicates fried-food consumption is associated with increased risk of overweight/obesity and hypertension but not T2DM in adults, but the findings should be interpreted with caution due to high heterogeneity and unstable subgroup analyses of this meta-analysis. More studies are warranted to investigate the total fried-food consumption and these health outcomes.

Serum uric acid and risk of prehypertension: a dose-response meta-analysis of 17 observational studies of approximately 79 thousand participants.

BACKGROUND: Studies examining the association between levels of serum uric acid (SUA) and risk of prehypertension still remained controversial conclusions. Also, a quantitative assessment of the dose-response association between them has not been reported. We aimed to quantitatively evaluate risk of prehypertension with levels of SUA based on observational study. METHODS: We searched the PubMed, Embase, and Web of Science databases up to December 3, 2019 for relevant studies. Pooled relative risks (RRs) and 95% confidence intervals (CIs) were calculated using random-effects models. The possible linear or non-linear SUA-prehypertension association was modelled by restricted cubic splines. RESULTS: We included 17 articles (17 studies) with a total of 79,358 participants and 34,591 cases of prehypertension. Compared with lowest levels of SUA, risk of prehypertension increased 46% (RR 1.46, 95% CI 1.28-1.66) for highest levels of SUA. For per 1 mg/dL increment in levels of SUA, risk of prehypertension increased by 12% (RR 1.12, 95% CI 1.08-1.17). Also, we found evidence of a linear SUA-prehypertension association (Pnon-linearity=.368). CONCLUSION: Elevated levels of SUA may be associated with increased risk of prehypertension. Present findings provide the evidence that lowering levels of SUA should be suggested in order to reduce the risk of prehypertension. More longitudinal and intervention studies are needed to clarify the optimal protective levels and whether reducing levels of SUA could prevent or control prehypertension and the progression of prehypertension to hypertension.

Association between shift work and risk of metabolic syndrome: A systematic review and meta-analysis.

AIMS: A comprehensive assessment of the association of shift work with risk of metabolic syndrome (MetS) through a systematic review and meta-analysis has not been reported. We aimed to evaluate the relationship from observational studies. DATA SYNTHESIS: We searched PubMed, Embase, and Web of Science databases from inception to December 16, 2020. Articles were chosen according to established inclusion criteria. Studies with data on men and women and different types of shift work were treated as independent studies. Relative risks (RRs) and 95% confidence intervals (CIs) were pooled by using random-effects models with heterogeneity (I2) > 50%; otherwise, a fixed-effects model was used. A total of 7192 articles was searched from PubMed, Embase and Web of science. Finally, we included 23 articles (38 studies) in this meta-analysis. The pooled RRs and 95% CI of MetS risk with shift work, 1-shift work, 2-shift work, and 3-shift work versus non-shift work were 1.30 (95% CI 1.19-1.41), 0.95 (95% CI 0.82-1.11), 1.19 (95% CI 0.91-1.56) and 1.17 (95% CI 1.00-1.37), respectively. The results from subgroup analyses stratified by sex, age, and region supported our overall findings that shift work is a risk factor for MetS. CONCLUSIONS: This meta-analysis suggests that shift work increases risk of MetS. Higher risk of MetS was found in the shift workers who were 2-shift or 3-shift or women or Asian workers.

Association of hypertriglyceridemic waist-to-height ratio and its dynamic status with risk of type 2 diabetes mellitus: The Rural Chinese Cohort Study.

AIMS: To evaluate the risk of type 2 diabetes mellitus (T2DM) in a prospective study with hypertriglyceridemic waist-to-height ratio (HWHtR) and its dynamic status. METHODS: We collected data for 12,248 participants ≥18 years in this study. Cox's proportional-hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for T2DM risk by baseline HWHtR. Multiple logistic regression analysis was used to estimate odds ratios (ORs) and 95% CIs for T2DM risk by transformation in HWHtR. RESULTS: We identified 839 T2DM cases during a median follow-up of 5.92 years. Compared with normal TG level and normal WHtR, T2DM risk was increased with high TG level and high WHtR (aHR 2.04, 95% CI 1.49-2.79). Similar results were observed in subgroup analyses by sex and age. During follow-up, T2DM risk was increased with stable high TG level and high WHtR (aOR 4.45, 95% CI 2.76-7.17) compared with stable normal TG level and normal WHtR. The results above were robust in sensitivity analyses. CONCLUSIONS: HWHtR phenotype and its dynamic status were associated with risk of T2DM. Our study suggests that primary prevention and avoiding the appearance of the HWHtR phenotype in the rural Chinese population may reduce the T2DM risk.

Long-term association of ambient air pollution and hypertension in adults and in children: A systematic review and meta-analysis.

AIMS: The association of long-term ambient air pollution and hypertension has been inconsistently reported. We performed an updated systematic review and meta-analysis to assess the association between long-term exposure to ambient air pollution and risk of hypertension in adults and in children. METHODS: PubMed, EMBASE, and Web of Science were searched up to August 7, 2020 for published articles examining the association of long-term exposure to ambient air pollution, including particulate matter (PM; ultrafine particles, PM1, PM1-2.5, PM2.5, PM2.5-10 and PM10), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulfur dioxide (SO2), ozone (O3), carbon monoxide (CO) and hypertension. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for hypertension with each 10-µg/m3 increase in air pollutants were calculated by random-effects models. RESULTS: We included 57 studies (53 of adults and 4 of children) in the meta-analysis. Risk of hypertension was significantly increased in adults with each 10-µg/m3 increase in exposure to PM2.5 (OR 1.10, 95% CI 1.07-1.14; I2 = 93.1%; n = 37), PM10 (1.04, 1.02-1.07; I2 = 44.8%; n = 22), and SO2 (1.21, 1.08-1.36; I2 = 96.6%; n = 3). Hypertension was not significantly associated with PM1 (n = 2), PM2.5-10 (n = 16), NO2 (n = 27), or NOx (n = 17). In children, the summary ORs (95% CIs) for each 10-µg/m3 increase in PM2.5, PM10, SO2 and O3 were 2.82 (0.51-15.68; I2 = 83.8%; n = 2), 1.15 (1.01-1.32; I2 = 0; n = 2), 8.57 (0.13-575.58; I2 = 94.2%; n = 2), and 1.26 (0.81-1.09, I2 = 91.6%; n = 2), respectively. CONCLUSIONS: Long-term ambient air pollution is a potential risk factor for hypertension in adults. More studies are needed to explore the effects of long-term air pollution on hypertension in children.

Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of KCNQ1 gene: A nested case-control study.

BACKGROUND: To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of KCNQ1 gene and type 2 diabetes mellitus (T2DM) risk and the interactions among SNPs, methylation, and environmental factors on T2DM risk. METHODS: We genotyped five SNPs and tested methylation at 39 CpG loci of KCNQ1 in 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study. Conditional logistic regression model was used to estimate the associations between SNPs and KCNQ1 methylation and T2DM risk. Multifactor dimensionality reduction (MDR) analysis was used to estimate the effect of the interactions SNPs-SNPs, SNPs-methylation, methylation-methylation and SNPs, and methylation-environment on T2DM risk. RESULTS: Probability of T2DM was decreased with rs2283228 of KCNQ1 (CA vs AA, odds ratio [OR] = 0.65, 95% confidence interval [CI] 0.42-0.99). T2DM probability was significantly increased with rs2237895 combined with hypertriglyceridemia (OReg  = 2.76, 95% CI 1.35-5.62), with hypertension (OReg  = 2.23, 95% CI 1.25-3.98), and with body mass index (BMI; OReg  = 1.93, 95% CI 1.12-3.34). T2DM probability was associated with methylation of CG11 and CG41 (OR = 1.89, 95% CI 1.23-2.89, P = .003). It was significantly associated with the interaction between BMI, hypertriglyceridemia, and CG5 methylation (P = .028 and .028), and the combined effects of CG11 with hypertriglyceridemia and hypertension. On MDR analysis, no significant interaction was observed. CONCLUSION: T2DM probability was reduced 35% with rs2283228 polymorphism. It was associated with rs2237895 combined with hypertension, with BMI and with hypertriglyceridemia. The methylation at two CpG loci of KCNQ1 significantly increased T2DM risk by 89%.

Solid fuel use and cardiovascular events: A systematic review and meta-analysis of observational studies.

Although solid fuel use has been increasingly linked to cardiovascular events (CVEs), conclusions have been inconsistent. We systematically searched 3 databases (PubMed, Embase, and Web of Science) up to July 3, 2020, to identify English language reports that assessed the association of solid fuel use with CVEs. Summary relative risks (RRs) and 95% confidence intervals (CIs) were estimated with a random-effects model. Subgroup analyses and sensitivity analyses were conducted to explore the potential sources of heterogeneity and to test the stability of the results. We finally included 13 observational studies (8 cohort, 3 cross-sectional, and 2 case-control studies comprising 791,220 participants) in the meta-analysis. The risk of CVEs was increased 21% with the highest versus the lowest solid fuel use (highest/lowest, RRpooled  = 1.21, 95% CI: 1.10-1.34). As for the subgroup analyses on study design, the pooled RR for cohort studies, case-control studies, and cross-sectional studies were 1.11 (95%CI: 1.03-1.19), 4.80 (95%CI: 2.22-10.39), and 1.46 (95%CI: 0.82-2.62), respectively. The results of this study suggested that high solid fuel use was associated with increased CVE risk, and that reducing the use of solid fuel will be important for improving the health of the populations in developing countries.