This study used a unique rural sample from the poorest province in China to study the prevalence of mental health outcomes in underserved early adolescents, and to examine the associations between mental health, gender and rural residence by comparing this sample to a public urban sample. Major findings include: (1) 9/19 investigated mental health outcomes were found to be more prevalent in the rural sample compared to the urban sample; (2) rural residence was associated with significantly higher odds for 7/19 outcomes after adjusting for age, grade, weight and height; (3) girls were overall less likely to report drug use, poor peer support and externalizing behaviors but this gender difference was mostly driven by the urban sample.
In terms of drug use, the prevalence of alcohol use in the past month was similar in the rural (13.3%) and the urban samples (10.3%). However, the prevalence of having ever gotten into trouble due to alcohol was significantly higher in rural Zhijin (14.9% vs. 3.7%, p < 0.001). In the combined analysis, rural residence was also significantly associated with this outcome (OR 5.09, p = 0.001). These findings highlighted excessive drinking reaching harm as more likely in rural adolescents. Consequences of youth excessive drinking on a single occasion have been documented to range from poisoning to motor vehicle crash deaths, drownings and falls, suicides and burns to later dependency and injuries globally (Jernigan, 2001). Our findings were consistent with previous literature in many Chinese adolescents start drinking alcohol before 6th grade (Li et al., 1996). Therefore, alcohol use should be a priority target for mental health interventions, ideally starting before 6th grade and especially in rural China.
In terms of depressive symptoms, an alarming 32% of Zhijin students have felt “sad and hopeless almost every day for 2 weeks straight in the past year” (vs. 18.2% in Beijing, p = 0.003). In the combined analysis, rural residence was also significantly associated with this outcome (OR 2.56, p = 0.04). Though suicidal thought and planning were not significantly different between samples, hopelessness may be an early red flag for later depression (Mac Giollabhui et al., 2018). The combined analysis also showed that rural residence was associated with frequent insomnia (OR 2.07, p = 0.01). Previous studies have shown insomnia as a predictor of depression in Chinese teenagers (Luo et al., 2014). Future interventions against adolescent depression could use insomnia as a measurable target in early adolescents especially in rural China, before clinical depression was evident.
Under “social support”, 38.2% of Zhijin students (vs. 17.9% in Beijing, p < 0.001) rarely or never found their schoolmates helpful. 46.1% of them has little or no supervision on their free time (vs. 30.1% in Beijing, p = 0.003) and more than 63.2% felt not understood by their guardians (vs. 34.0% in Beijing, p < 0.001). In the combined analysis, rural residence was associated both with poor peer support (OR 2.90, p = 0.001) and poor parental understanding (OR 4.12, p < 0.001). Poor parental involvement and inadequate parenting practices have been shown to be modifiable mediators between socioeconomic status and child mental health, with a few published family-level programs that improved children’s cognitive and socioemotional skills by optimizing parenting skills and involvement (Verhulst et al., 2020). On the other hand, peer relationships have been found as an effective buffer between traumatic life events and depression in Chinese teens (Greenberger et al., 2000), making it an important target for school-level interventions.
Under “externalizing behaviors”, the prevalence of being bullied in the past month was 47.4% in rural Zhijin (vs. 20.3% in Beijing, p < 0.001). The high rural prevalence was concerning for being much higher than the 13.3% previous estimate in China (Eslea et al., 2003), the 35.5% in neighboring LMICs such as the Philippines (Rudatsikira, 2008), and almost four times the 12% average in developed Western Europe (WHO, 2016). Bullying victimization in early teenage years have been shown to be associated with anxiety and depression (Bond et al., 2001), and with teenage suicidal ideation in a Chinse study (Liu et al., 2017). Given our findings in early adolescents, interventions targeting bullying should start at or before 12 years-old. The prevalence of serious injuries was also much higher in the rural sample (46.7% in Zhijin vs. 16.2% in Beijing, p < 0.001), confirmed by an OR of 5.0 (p < 0.001) associated with rural residence in combined analysis. One explanation is the risk of farm-work-related injuries in rural youth, with known associations to sleep disturbances and school-related stress (Postel et al., 2009). Other researchers suggested maltreatment by guardians and involvement in violent episodes as major risk factors (Shi et al., 2014). Injuries, in turn, can lead to unexplained school absenteeism, confirmed by our finding of OR 5.21 for missing school (p < 0.001) associated with rural residence. High absenteeism is likely to also involve anxiety, transport, bullying and difficulties with schoolwork (Melvin et al., 2019).
In terms of gender differences, combined analysis showed that girls were overall less likely to have drunk recently, to ever get drunk, to have drinking-related troubles, to smoke and to experience passive smoking. However, separate gender analysis by sample showed that most gender differences were noted in the urban sample alone, likely due to the relatively small size of our rural sample. The combined analysis findings were consistent with the global male predominance in smoking (WHO, 2010) and drinking (Wilsnack et al., 2009), as well as parallel findings in Chinese adolescents (Yue et al., 2016). Being a girl was overall associated with better perceived social support from their peers but not from their guardians. This was interesting because Chinese families are known to favor male children in resource-allocation (Tian et al., 2018). Perceived peer support is thus especially important for girls as it is a protective factor associated with increased prosocial behavior, better motivation and academic performance in school (Wentzel et al., 2004). Finally, girls had lower odds of suffering from physical fights, serious injuries and bullying. These findings were consistent with the literature on male predominance of externalizing behaviors in children (Chaplin & Aldao, 2013). Overall, gender differences found in the combined analysis raise questions regarding the necessity to adopt different strategies and outcome measures by gender when designing future interventions.
This study has several strengths. First, its unique, underserved rural population from Guizhou has rarely been studied despite its needs and limited resources. Second, the combined analysis highlights the rural-urban inequality in adolescent mental health in China. Third, the GSHS survey covers a variety of mental health topics and has a wide international data base. Our findings help to add to the knowledge in adolescent mental health especially in LMICs. This study has a few important limitations. First, a cross-sectional study is unable to confirm causality or temporality. Second, the specific rural Guizhou sample and urban Beijing sample may not be generalizable to other contexts. They are examples of health inequity in China due to social determinants of health. Third, the rural and urban samples were collected in different studies, although this was done using the same GSHS tool in anonymous data collection. There is no reason to believe that the survey procedure may induce any difference. The comparison of the prevalence between samples may be affected by age distribution difference between your rural and urban sample. However, we were able to adjust the difference when estimating the ORs. Finally, the lack of information on internalized mental health measures and broader social-economic factors limited our ability to draw conclusions on important mental health outcomes such as anxiety, self-esteem and self-efficacy and the associations between outcomes and specific social determinants of health. More standardized, comprehensive mental health data in children and adolescents in LMICs are needed to understand the evolution of mental health in adolescents and their determinants.