Gender differences in association of urbanization with psychological stress in Chinese adults: A population-based study - Li, Dianjiang; Ruan, Yuhui; Kang, Qi; Rong, Chao (Frontiers in Public Health, 2022)
Objective: To investigate the gender-specific associations between exposure to urbanization and psychological stress in China experiencing rapid urbanization. Methods: Data were obtained from the 2015 China Health and Nutrition Survey. A total of 4,388 men and 5,098 women aged at least 18 years were obtained from 288 communities across 12 provinces and municipalities. Tertiles of the urbanization index, summarizing 12 urbanization dimensions at the community level, were used to define low, medium, and high levels of urbanization. The psychological stress was measured based on the 10-item Perceived Stress Scale. The gender-stratified multilevel analysis (Level-1: Individuals, Level-2: Communities, and Level-3: provinces/municipalities) was used to estimate the association between exposure to urbanization and psychological stress. Results: After controlling for age, education status, marital status, work status, household income per capita, current smoking, alcohol drinking, sleep duration, BMI, and chronic conditions, the urbanization index was negatively associated with psychological stress in women (P trend = 0.017) but not men (P trend = 0.476). More specifically, a one-standard deviation increase in the score of community population density (β=-0.329, P=0.329), modern markets (β=-0.247, P=0.044), education (β=-0.448, P=0.002) and housing (β=-0.380, P=0.005) was negatively associated with psychological stress only in women, separately. Conclusions: Our data revealed that living in the most urbanized communities is associated with lower levels of psychological stress for women but not men. Thus, this study can help empower decision-makers to accurately target vulnerable communities and plan effective strategies to address psychological outcomes. Keywords: China, Urbanization, Community, Psychological stress, Multilevel analysis