Associations of long-term exposure to ambient air pollution and physical activity with insomnia in Chinese adults

BACKGROUND

Air pollution is a potential environmental risk for sleep disturbance. However, the evidence is very limited in China. On the other hand, physical activity (PA) is a preventive behavior that can improve insomnia, but whether PA mitigates the negative impact of air pollution on insomnia is unknown.

METHODS

We obtained data from the baseline of China Multi-Ethnic Cohort (CMEC) survey, and examined the association between air pollution and insomnia, as well as PA's modification effect of on this association. We included 70,668 respondents and assessed insomnia by self-reported symptoms collected using electronic questionnaires. Using satellite data, we estimated the residence-specified, three-year average PM₁, PM_2.5, PM₁₀ (particulate matter with aerodynamic diameters of ≤1 μm, ≤2.5 μm and 10 μm, respectively), O₃ (ozone), and NO₂ (nitrogen dioxide) concentrations. We established the associations between air pollutants and insomnia through logistic regression. We evaluated the modification impact of total and domain-specific PA (leisure, occupation, housework, transportation) by introducing an interaction term.

RESULTS

Positive associations were observed between long-term exposure to PM₁, PM_2.5, PM₁₀, and O₃ and insomnia symptoms, with ORs (95% CI) of 1.09 (1.03-1.16), 1.11 (1.07-1.15), 1.07 (1.05-1.10) and 1.15 (1.11-1.20), respectively. As total PA increased, the ORs of air pollution for insomnia tended to decrease and then rise. We observed varying modification effects of domain-specific PA. With an increase in leisure PA, the ORs for PM_2.5 and PM₁₀ significantly declined. However, increased ORs of air pollutants were related to insomnia among participants with higher levels of occupational and housework PA.

CONCLUSION

Long-term exposure to higher concentrations of PM₁, PM_2.5, PM₁₀, and O₃ increases the risk of insomnia symptoms. Moderate to high levels of leisure PA alleviate the harmful effects of air pollution on insomnia, while high levels of occupation and housework PA intensify such effects.

Community Health Behaviors and Geographic Variation in Early-Onset Colorectal Cancer Survival Among Women

INTRODUCTION:

Despite overall reductions in colorectal cancer (CRC) morbidity and mortality, survival disparities by sex persist among young patients (age <50 years). Our study sought to quantify variance in early-onset CRC survival accounted for by individual/community-level characteristics among a population-based cohort of US women.

METHODS:

Geographic hot spots—counties with high early-onset CRC mortality rates among women—were derived using 3 geospatial autocorrelation approaches with Centers for Disease Control and Prevention national mortality data. We identified women (age: 15–49 years) diagnosed with CRC from 1999 to 2016 in the National Institutes of Health/National Cancer Institute's Surveillance, Epidemiology, and End Results program. Patterns of community health behaviors by hot spot classification were assessed by Spearman correlation (ρ). Generalized R² values were used to evaluate variance in survival attributed to individual/community-level features.

RESULTS:

Approximately 1 in every 16 contiguous US counties identified as hot spots (191 of 3,108), and 52.9% of hot spot counties (n = 101) were located in the South. Among 28,790 women with early-onset CRC, 13.7% of cases (n = 3,954) resided in hot spot counties. Physical inactivity and fertility were community health behaviors that modestly correlated with hot spot residence among women with early-onset CRC (ρ = 0.21 and ρ = −0.23, respectively; P < 0.01). Together, individual/community-level features accounted for distinct variance patterns in early-onset CRC survival among women (hot spot counties: 33.8%; non–hot spot counties: 34.1%).

DISCUSSION:

Individual/community-level features accounted for approximately one-third of variation in early-onset CRC survival among women and differed between hot spot vs non–hot spot counties. Understanding the impact of community health behaviors—particularly in regions with high early-onset CRC mortality rates—is critical for tailoring strategies to reduce early-onset CRC disparities.

Physical activity, sedentary behaviour and smoking status among psychiatric patients in Singapore - a cross-sectional study

BACKGROUND

Unhealthy behaviours such as physical inactivity, sedentary behaviour and smoking have been found to be more prevalent in people with psychiatric disorders than in the general population, leading to increased mortality risk. The present study seeks to identify correlates of physical activity and sedentary behaviour among psychiatric patients in Singapore, as well as investigate differences in their physical activity patterns by smoking status.

METHODS

Participants (n = 380) were recruited from a tertiary psychiatric hospital in Singapore as part of a study on the prevalence and correlates of smoking among psychiatric patients. Physical activity levels and sedentary behaviour were measured using the Global Physical Activity Questionnaire (GPAQ) and analysed based on GPAQ guidelines. Chi-square analyses were conducted to examine differences in physical activity by smoking status, and logistic regression analyses to yield sociodemographic correlates of meeting physical activity guidelines (as recommended by the World Health Organization) and sedentary behaviour.

RESULTS

Education was found to be significantly associated with meeting recommended physical activity levels, while age and marital status were significantly associated with excessive sedentary behaviour. Additionally, while no significant differences were found among current, former and non-smokers across all types of physical activity engagement levels, there was a high prevalence of inadequate physical activity (43.2%) and excessive sedentary behaviour (38.8%) among participants.

CONCLUSION

Given the high prevalence of inadequate physical activity and excessive sedentary behaviour among current, former and non-smokers with psychiatric disorders, programmes aimed at increasing physical activity and lowering sedentary behaviour levels should be integrated into targeted treatment plans to improve clinical outcomes.

Explaining the Inverse Association between Altitude and Obesity

PURPOSE

To better understand the inverse association between altitude and adult obesity.

METHODS

An ecological study design was used, involving 3,108 counties in the contiguous United States. Data were from several national sources, and assessment involved various statistical techniques, including multiple regression analysis.

RESULTS

Living in counties at higher altitude is associated with lower adult obesity. Compared with counties <500 meters, the percent of adult obesity decreases by 5.18% at 500-999 meters, 9.69% at 1,000-1,499 meters, 16.77% at 1,500-1,999 meters, 24.14% at 2,000-2,499 meters, and 35.28% at ≥2,500 meters. After adjusting for physical inactivity, smoking, and other variables, corresponding decreases in adult obesity with higher altitude groupings are 3.87%, 5.64%, 8.03%, 11.41%, and 17.54%, respectively. Various mechanisms are presented as possible explanations for the association between higher altitude and lower obesity. In addition, altitude may indirectly influence adult obesity, primarily through its relationship with physical inactivity and smoking. In an adjusted regression model, adult obesity was most strongly associated with physical inactivity followed by adult smoking and then altitude. Together they explain 39.04% of the variation in adult obesity. After accounting for these variables, sunlight, precipitation, ambient air temperature, education, income, food insecurity, limited access to healthy foods, race, sex, and rural living explain an additional 4.68% of the variation in adult obesity.

CONCLUSIONS

The inverse association between altitude and adult obesity remains significant after adjustment for several variables.