Depression is a prevalent mental disorder among adolescents, with significant consequences including substance abuse, poor academic performance, delinquency, and suicide. A meta-analysis in mainland China revealed a 24.3% prevalence. Early intervention is crucial. China's Targeted Poverty Alleviation (TPA) policy, implemented in 2016, aimed to improve the lives of rural residents. While research exists on TPA's impact on rural health, there's a gap in understanding its effect on the mental health, particularly depression, of children and adolescents in these areas. Poverty is linked to increased illness and disability and contributes to mental health disparities, with lower-income groups often exhibiting higher depression rates. The high number of left-behind children in rural China (approximately 6.436 million in 2020), due to parental migration for work, further exacerbates this issue. Parental absence negatively impacts children's well-being and psychological health. This study addresses the lack of epidemiological data on depressive morbidity among rural Chinese children and adolescents by conducting a large-scale survey in Weining County, Guizhou Province, to understand the prevalence and correlates of depressive symptoms and inform effective interventions.

Existing literature highlights the significant prevalence of depression among adolescents globally, and particularly in China. Studies have shown a strong correlation between socioeconomic status (SES) and depression, with lower SES often associated with higher rates. The impact of poverty on adolescent mental health is well-documented, and parental absence is a significant risk factor, contributing to increased emotional distress and behavioral problems. Previous research also demonstrates a link between internet addiction and depression. However, there is a paucity of data specifically examining the prevalence of depression and its correlates among children and adolescents in impoverished rural areas of China, particularly in the context of the TPA policy.

A cross-sectional online survey was conducted from April 20 to May 10, 2022, in Weining County, China. The survey utilized snowball sampling through WeChat, targeting school students aged 9-18. Participants who completed the questionnaire in less than 120 seconds or fell outside the age range were excluded. The survey collected socio-demographic and clinical data, including age, gender, school type, grade, school record, parental education and occupation, parental absence, family relationships, peer relationships, teacher-student relationships, and internet addiction. Depression was assessed using the Chinese version of the Center for Epidemiologic Studies Depression Scale (CES-D), with a cut-off score of 16. Internet addiction was measured using Young's Internet Addiction Test (IAT). Data analysis involved Pearson's and Chi-squared tests for categorical variables, the Mann-Whitney U test for continuous variables, and univariate and multivariate logistic regression to examine correlates of depression. SPSS version 22.0 was used for statistical analysis, with p<0.05 considered statistically significant.

A total of 23,180 children and adolescents participated. The prevalence of depression (CES-D > 15) was 35.6%. Univariate analysis revealed significant associations between depression and age (12-18 years), gender (female), grade (junior middle school), parental absence, attending key schools or classes, moderate or severe internet addiction (IA), and poor school record or social relationships. Multivariate logistic regression identified female gender (OR = 1.175), junior middle school attendance (OR = 1.487), parental absence (OR = 1.272), attending key schools (OR = 1.221), attending key classes (OR = 1.099), and moderate or severe IA (OR = 13.593) as independent risk factors for depression. Conversely, adolescents with well-educated parents or parents in stable occupations showed a lower risk of depression.

The substantially higher prevalence of depression (35.6%) compared to previous meta-analyses (24.3%) highlights the significant impact of poverty as a risk factor for depression in this population. The findings align with existing research demonstrating the negative correlation between SES and mental health, emphasizing the detrimental effects of poverty on children's mental well-being. The higher risk among females, adolescents in higher grades, and those in key schools aligns with the increased academic pressure experienced by these groups. Parental absence consistently emerges as a significant risk factor, underscoring the importance of family support. The strong association with internet addiction further reinforces the need for integrated mental health interventions that address both online and offline behaviors. The protective effects of parental education and stable employment suggest the importance of socio-economic support in mitigating depression risk.

This study reveals a high prevalence of depression among children and adolescents in impoverished areas of rural China, even with the TPA policy in place. Several factors, including gender, school grade, parental absence, academic pressure, and internet addiction, contribute significantly to this risk. These findings underscore the urgent need for comprehensive mental health interventions targeting vulnerable groups. Future longitudinal studies are needed to better understand the causal relationships and long-term impact of these factors, and to evaluate the effectiveness of interventions designed to address these issues, particularly within the context of ongoing poverty alleviation efforts.

The study's limitations include the reliance on online surveys, potentially excluding individuals lacking internet access, the cross-sectional design, which prevents establishing causality, and the use of snowball sampling, which might introduce sampling bias. The use of a CES-D cutoff score of 16 for all age groups might lead to misclassification, particularly among younger children. Further research is needed to validate the appropriateness of this cut-off value in diverse age groups and explore the potential influence of factors not included in this study, such as social support and physical health.