Deliang Kong, Jiyuan Zhong, Cuihong Li, Wenjun Wang, Hao Yang, Zixun Liu, Tianyi Yang, Xiaoping Cheng, Guoqing Jiang, Jianjun Luo
The MHL attainment rate among residents in Chongqing was at a moderately high level; however, significant urban-rural disparities remained. Occupation, education level, and household economic conditions were the main sources of these differences. Greater attention should be paid to rural residents and populations with low education levels, low income, and poor health status. It is recommended to integrate primary healthcare, community education, and digital communication resources to promote equitable improvement in MHL.
BACKGROUND: Mental health literacy (MHL), as a core issue in public health, is closely associated with population mental health status and the ability to cope with psychological problems. This study aimed to evaluate the level of MHL among residents in Chongqing, identify its influencing factors, and explore the sources of urban-rural differences in MHL.
METHODS: A stratified multistage random sampling method was used to conduct a questionnaire survey among 36,874 permanent residents in Chongqing in 2025. The National Mental Health Literacy Questionnaire (NMHLQ) was used to assess MHL attainment. χ 2 tests, logistic regression, and urban-rural weighted logistic regression were used to identify the influencing factors of MHL among urban and rural residents. The generalized variance inflation factor (GVIF) was used to assess multicollinearity among variables. A weighted Fairlie nonlinear decomposition model was applied to quantify the contributions to urban-rural differences, and repeated Fairlie decomposition with adjusted sample coefficients was used as a sensitivity analysis. Stratified analyses were conducted to verify the robustness of the results. Statistical analyses were performed using SPSS 22.0, R 4.2.2, and Stata MP16.0.
RESULTS: The overall MHL attainment rate among residents was 32.21%, with urban residents showing a higher rate than rural residents (37.08% vs. 30.26%, p < 0.001). After weighting according to the urban-rural population structure, the overall attainment rate was 35.18%. Multivariable analysis showed that age, education level, income level, occupation, health behaviors, self-rated health (SRH), and chronic disease status were influencing factors of MHL among urban and rural residents. Urban-rural weighted logistic regression showed that urban residents had higher odds of MHL attainment than rural residents (OR = 1.36, 95%CI: 1.29-1.43, p < 0.001). After adjustment for covariates in the stratified analyses, urban residents still had higher odds of MHL attainment. Weighted Fairlie decomposition showed that 0.0442 (64.83%) of the difference could not be explained by the observed covariates, which may reflect unmeasured structural urban-rural differences or other unobserved factors. A total of 0.0240 (35.17%) of the difference was attributable to observed factors, and the contribution rates of occupation, education level, monthly household income, and regional distribution were 27.01, 26.55, 12.90, and -35.13%, respectively. Repeated Fairlie decomposition with adjusted sample coefficients showed relatively stable results.
CONCLUSION: The MHL attainment rate among residents in Chongqing was at a moderately high level; however, significant urban-rural disparities remained. Occupation, education level, and household economic conditions were the main sources of these differences. Greater attention should be paid to rural residents and populations with low education levels, low income, and poor health status. It is recommended to integrate primary healthcare, community education, and digital communication resources to promote equitable improvement in MHL.