This study examined the association of obesity and dyslipidemia according to body measurements among Chinese adults in Shanghai, a place in the process of rapid urbanization. Using the baseline data of the Shanghai Suburban Adult Cohort and Biobank study (SSACB), the subjects completed questionnaires and physical examinations, and fasting blood was collected for biochemical assays. We estimated the odds ratios (OR) and 95% confidence interval (CI) by multivariable logistic regression. The prevalence was 12.9% and 28.8% in both general and central obesity, respectively. Compared with the non-obese, the general or central obesity participants had a higher level of TC, TG, LDL-C and lower level of HDL-C. The OR (95%CI) for dyslipidemia was 1.79 (1.69–1.91) and 1.91 (1.83–2.00) in general or central obesity, respectively. Positive associations were also observed between obesity and high TC, high LDL-C, low HDL-C and high TG, with the adjusted OR ranging from 1.11 to 2.00. Significant modifying effect of gender, age, hypertension, and diabetes were found in the association of obesity and different forms of dyslipidemia. The findings of our study indicated that participants with obesity, including general or central obesity, have a higher prevalence of dyslipidemia and gender, age, hypertension, and diabetes might be potential modifiers of the association. More effective attention and interventions should be directed to managing body weight to reduce the prevalence of dyslipidemia.

Background: The correlation between nontraditional lipids and ischemic stroke (IS) is inconsistent and controversial. This study aimed to examine the association of four nontraditional lipids with IS risk in Chinese adults. Methods: This prospective community-based cohort study was performed in Songjiang District, Shanghai, China. The study began in 2016 and included 34,294 participants without stroke before the investigation. The association between nontraditional lipids (nonhigh-density lipoprotein cholesterol [non-HDL-C], total cholesterol/high-density lipoprotein cholesterol [TC/HDL-C], triglyceride [TG]/HDL-C, and low-density lipoprotein cholesterol [LDL-C]/HDL-C) and IS was studied with multivariate Cox regression models. The dose–response associations between these four serum lipids and IS were explored using restricted cubic spline (RCS) analysis. Results: There were a total of 458 IS cases with 166,380 person-years of follow-up. Compared with the lowest tertiles, the highest tertiles of the nontraditional blood lipids showed greater IS risk after controlling for potential confounders. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) were as follows: TC/HDL-C, 1.63 (1.28–2.07); TG/HDL-C, 1.65 (1.28–2.13); LDL-C/HDL-C, 1.51 (1.18–1.92); and non-HDL-C, 1.43 (1.13–1.81). The fully adjusted RCS curves presented a nonlinear relationship, and the risk increased when the TC/HDL-C, TG/HDL-C, and LDL-C/HDL-C levels were > 3.47, > 0.92, and > 1.98, respectively. Conclusions: This community-based cohort study presents a positive association between the four nontraditional lipids and IS incidence. Maintaining relatively low lipid ratios can be beneficial for preventing stroke. Nontraditional lipids can be considered targets for managing blood lipids.

Background: Depression in children and adolescents is a rising concern in China. Dietary behavior is a critical determinant of mental health. Meal timing, or the schedule of meal consumption, has been related to several metabolic disorders. However, the effect of meal timing on mental health is scarce, particularly in children and adolescents who are in a critical period of physical and psychological development. Objective: This research examined the relationship between meal timing and depression in children and adolescents in China. Methods: Children and adolescents from grades 1 to 9 were recruited from 16 districts in Shanghai, China, from January 3 to January 21, 2020. Ten schools attended the study. A survey was distributed to the students and their parents to collect demographic and health-related information. Depression was measured by the Children’s Depression Inventory-Short Form. Breakfast consumption was analyzed as a binary outcome. Participants were defined as breakfast consumers if they never skipped breakfast during the week. They were otherwise defined as breakfast skippers if they skipped breakfast at least once per week. A similar categorization was applied to analyze food intake proximal to bed. Daily eating windows were calculated using the last food intake time frame—the first food intake time frame. Participants were classified into eating window groups of less than 10 hours, 10-12 hours, and more than 12 hours. A logistic regression model was used to compute the odds ratio (OR) and 95% CI. Results: A total of 6874 participants were included in the analysis. Participants who skipped breakfast were associated with a 2.70 times higher occurrence of depression (OR 2.70, 95% CI 2.24‐3.26; P<.001). The prevalence of depression was 1.28 times higher in participants who ate before bed than in those who never ate before bed (OR 1.28, 95% CI 1.08‐1.50; P<.001). The occurrence of depression was 1.37 times higher if the eating time window was shorter than 10 hours (OR 1.37, 95% CI 1.08‐1.73; P=.009) and 1.23 times higher if the eating time window was longer than 12 hours (OR 1.23, 95% CI 1.01‐1.50; P=.004). The lowest occurrence of depression was observed at 11.5 hours. Subgroup analysis showed that such relationships remained significant in adolescents aged 10 years or older. In children, only skipping breakfast was associated with a higher odds of depression (OR 2.77, 95% CI 1.94‐3.96; P<.001). Conclusions: Breakfast skipping and eating before bed significantly increase the occurrence of depression. The optimal daily eating window to lower the occurrence of depression is 11.5 hours in children and adolescents. Daily eating windows longer than 12 hours or shorter than 10 hours are associated with an elevated occurrence of depression. Current findings advocate evidence-based dietary strategies to prevent and treat depression in children and adolescents.

This study was designed to examine the association of soy isoflavones (SI) intake with different body measurements indicative of obesity in Chinese adults of Shanghai, a population consuming foods rich in SI. This study used baseline data from the Shanghai Gaofeng cohort study. SI intake was measured by using a self-reported food frequency questionnaire (FFQ). A restricted cubic spline (RCS) was performed to examine the possible nonlinear relationship of SI intake with obesity. A logistic regression model was applied to estimate the odds ratios (OR) and 95% confidence interval (CI). Compared with the lowest tertile group of SI intake, the highest tertile group had a lower prevalence of obesity and central obesity. The OR for overall obesity was 0.91 (95% CI: 0.85, 0.98) in the highest versus the lowest SI tertile group; the associations differed by sex and menopausal status. A negative association was also observed between SI intake and central obesity, and a significant modifying effect of sex was found on the association. No significant interactions were observed between SI intake and physical activity (PA) levels. Our results suggest that Chinese adults with higher dietary intake of SI may be less likely to be obese, particularly for postmenopausal women.

A prospective community-based cohort study was conducted to investigate the effects of obesity on hyperhomocysteinemia (HHcy) in community residents from Shanghai, China, with a median follow-up period of 2.98 years. The exposures were high body mass index (BMI) (BMI ≥ 28.0 kg/m²) and high waist circumference (WC) (WC ≥ 85.0 cm for female and WC ≥ 90.0 for male) at baseline investigation, and the outcome was the incident of HHcy after the follow-up. A restricted cubic spline (RCS) was performed to assess the possible nonlinear relationship of BMI and WC with HHcy. A Cox proportional hazard regression model was used to evaluate the association between BMI and WC measured obesity and the risk of HHcy (Hcy level > 15 µmol/L). No significant non-linearity was found between BMI and WC with HHcy. Cox regression model showed that underweight measured by BMI was negatively associated with the risk of HHcy after controlling for confounder variables (adjusted HR = 0.64, 95% CI = 0.42 to 0.99). While abdominal obesity was positively associated with the risk of HHcy for those without CVD-related comorbidities (adjusted HR = 1.26, 95% CI = 1.05 to 1.51). Our results suggested that individuals could maintain a relatively low BMI and normal WC to lower the risk of HHcy.

(1) Introduction: The available studies on the association between type 2 diabetes mellitus (T2DM) and menopause report conflicting results. (2) Objective: This study aimed to investigate the association of menopausal status, age at menopause, and length of the reproductive period with T2DM. (3) Methods: This cross-sectional study is part of the ‘China Eastern Cohort Study’, which is a community-based cohort study. Multistage, stratified, clustered sampling was used to recruit the study participants in Shanghai, China. Age at menarche and menopause was recorded, and reproductive period was calculated. Weighted logistic regression was used to calculate the prevalence ratios (PRs) with 95% confidence intervals (CIs) of T2DM. Restricted cubic splines were used to assess the relationship between age at menopause, reproductive period, and T2DM. (4) Results: A total of 20,128 women were included. The prevalence of T2DM was 13.7%. Postmenopausal women exhibited a higher prevalence of T2DM than premenopausal women (p < 0.001) and an unfavorable metabolic profile, including higher body mass index, hypertension, and hyperlipidemia. A higher risk of T2DM was observed in postmenopausal women (PR2.12, 95%CI: 1.79–2.51, p < 0.001) compared with premenopausal women, independently of confounding factors. After adjustment for confounding factors, age at menopause and reproductive period were not significantly associated with T2DM. (5) Conclusions: Postmenopausal status is associated with T2DM, while menopausal age and reproductive period are not associated with T2DM. Menopausal status should be considered during T2DM screening.