The relationship between childhood adversity and sleep quality among rural older adults in China: the mediating role of anxiety and negative coping.

BACKGROUND: Studies have revealed the effects of childhood adversity, anxiety, and negative coping on sleep quality in older adults, but few studies have focused on the association between childhood adversity and sleep quality in rural older adults and the potential mechanisms of this influence. In this study, we aim to evaluate sleep quality in rural older adults, analyze the impact of adverse early experiences on their sleep quality, and explore whether anxiety and negative coping mediate this relationship. METHODS: Data were derived from a large cross-sectional study conducted in Deyang City, China, which recruited 6,318 people aged 65 years and older. After excluding non-agricultural household registration and lack of key information, a total of 3,873 rural older adults were included in the analysis. Structural equation modelling (SEM) was used to analyze the relationship between childhood adversity and sleep quality, and the mediating role of anxiety and negative coping. RESULTS: Approximately 48.15% of rural older adults had poor sleep quality, and older adults who were women, less educated, widowed, or living alone or had chronic illnesses had poorer sleep quality. Through structural equation model fitting, the total effect value of childhood adversity on sleep quality was 0.208 (95% CI: 0.146, 0.270), with a direct effect value of 0.066 (95% CI: 0.006, 0.130), accounting for 31.73% of the total effect; the total indirect effect value was 0.142 (95% CI: 0.119, 0.170), accounting for 68.27% of the total effect. The mediating effects of childhood adversity on sleep quality through anxiety and negative coping were significant, with effect values of 0.096 (95% CI: 0.078, 0.119) and 0.024 (95% CI: 0.014, 0.037), respectively. The chain mediating effect of anxiety and negative coping between childhood adversity and sleep quality was also significant, with an effect value of 0.022 (95% CI: 0.017, 0.028). CONCLUSIONS: Anxiety and negative coping were important mediating factors for rural older adult's childhood adversity and sleep quality. This suggests that managing anxiety and negative coping in older adults may mitigate the negative effects of childhood adversity on sleep quality.

The Short-Term Effects and Burden of Ambient Air Pollution on Hospitalization for Type 2 Diabetes: Time-Stratified Case-Crossover Evidence From Sichuan, China.

Type 2 diabetes mellitus (T2DM), a complicated metabolic disease, might be developed or exacerbated by air pollution, resulting in economic and health burden to patients. So far, limited studies have estimated associations between short-term exposure to air pollution and disease burden of T2DM in China. Hence, we aimed to estimate the associations and burden of ambient air pollutants (NO2, PM10, PM2.5, SO2, and CO) on hospital admissions (HAs) for T2DM using a time-stratified case-crossover design. Data on HAs for T2DM during 2017-2019 were collected from hospital electronic health records in nine cities in Sichuan Province using conditional poisson regression. Totally, 92,381 T2DM hospitalizations were recorded. There were significant short-term effects of NO2, PM10, PM2.5, SO2 and CO on HAs for T2DM. A 10 µg/m3 increment of NO2, PM10, PM2.5, SO2 and CO as linked with a 3.39% (95% CI: 2.26%, 4.54%), 0.33% (95% CI: 0.04%, 0.62%), 0.76% (95% CI: 0.35%, 1.16%), 12.68% (95% CI: 8.14%, 17.42%) and 79.00% (95% CI: 39.81%, 129.18%) increase in HAs for T2DM at lag 6. Stratified analyses modified by age, sex, and season showed old (≥65 years) and female patients linked with higher impacts. Using WHO's air quality guidelines of NO2, PM10, PM2.5, and CO as the reference, the attributable number of T2DM HAs exceeding these pollutants exposures were 786, 323, 793, and 2,127 during 2017-2019. Besides, the total medical costs of 25.83, 10.54, 30.74, and 67.78 million China Yuan were attributed to NO2, PM10, PM2.5, and CO. In conclusion, short-term exposures to air pollutants were associated with higher risks of HAs for T2DM.

The inequality of health-income effect in employed workers in China: a longitudinal study from China Family Panel Studies.

BACKGROUND: The relationship between health and income is an essential part of human capital research. The majority of current analyses using classical regression models show that health has a significant impact on income after controlling for the endogeneity of health due to the measurement error and reverse causality. Currently, the Chinese government implements various policies including health related policies to fiercely fight for the domestic poverty issues, and thus only estimating the average effect of health on income could underestimate the impact for low income population and will make policy makers neglect or not pay enough attention to the significant role of health in poverty alleviation. To study the effect of health on income for workers at different income quantiles, we apply the quantile regression method to a panel data from a Chinese household survey. Furthermore, we test the heterogeneity of this health-income effect for different subgroups of workers characterized by sex, registered residence, and residential area. Lastly, we provide an explanation on the possible mechanism of the health-income effect. METHODS: This study uses data from four waves of the China Family Panel Studies (CPFS)- a biennial longitudinal study spanning from 2012 to 2018. The final data used in the regression analysis includes a balanced sample of 19,540 person-year observations aged between 18 to 70 years, with complete information of demographic and social economic status characteristics, job information, and health status of individuals. We use lagged self-reported health to control the potential endogeneity problem caused by reverse causality between health and income. Our identification on heterogenous treatment effects relies on panel quantile regressions, which generate more information than the commonly used mean regression method, and hopefully could reveal the effects of health on income for workers with income distributed at a wide range of quantiles. In addition, we compare the results derived from panel quantile regressions and mean regressions. Finally, we added interaction terms between health and other independent variables to recover the influence channel of health on income. RESULTS: The regression estimates show that the effects of health on income are more pronounced for workers distributed on the lower ends of income spectrum, and the health-income effect decreases monotonically with the increase of income. The treatment effect is robust to alternative measures of health and seems to be more pronounced for females than males, for rural workers than their urban counterparts. Finally, we find that health not only directly affects worker's income but also has different effects on income for different occupation cohorts. CONCLUSIONS: This study provides a different perspective on the impact of individual health status on income, uncovering the heterogeneous effects of health deterioration on income reduction for workers with different incomes by using panel data and rather advanced statistical techniques- panel quantile regressions. At present, the Chinese government is making every effort to solve the problem of poverty and our findings suggest public policies on health and income protections should emphasize different needs of workers with different incomes and special attention should be paid to low-income workers who are much more financially fragile to health deterioration than other income groups.