Peking University Health Science Center, Beijing, P.R. China.
Inquiry. 2020 Jan-Dec;57:46958020965470. doi: 10.1177/0046958020965470.
Urbanization has been and will continue to be the mainstream trend of global population movement, including China. Depression is the most common mental disorders and the leading factor of disabilities. However, the impacts of urbanization on the depression occurrence are still unclear. This paper analyzed the data from 3 waves of the China Health and Retirement Longitudinal Study (CHARLS) with sample size as 8510 adults representing the middle aged and elderly group in China. Depression was identified and measured by the 10-item Center for Epidemiological Studies Depression Scale (CESD-10). Urbanization level was measured by population density, GDP per capita and secondary/tertiary industry as percentage to GDP in the China City Statistical Yearbook. The fixed effect regression model was used to explore the association between the changes of urbanization and depression. As result, depression is closely related to the urbanization, protective effects are found for 3 indicators above: The depression prevalence decreases while urbanization level increases (from lowest urbanization level to the highest: < 0.01). Among the 10 depression symptoms, "Bothered", "Reduced energy leading to diminished activity" and "Hopelessness" are the most significantly improved with urbanization. The impact of urbanization on residents' mental health is a long-term, multi-factor interaction. Therefore we need to fully consider all possible influencing factors, and longer follow-up study to verify.
城市化一直是并且将继续成为全球人口流动的主流趋势，包括中国。抑郁症是最常见的精神障碍，也是导致残疾的主要因素。然而，城市化对抑郁症发生的影响尚不清楚。本文分析了中国健康与退休纵向研究（CHARLS）的 3 波数据，样本量为 8510 名代表中国中老年人群的成年人。抑郁症通过 10 项流行病学研究中心抑郁量表（CESD-10）来识别和测量。城市化水平通过人口密度、人均 GDP 以及中国城市统计年鉴中第二/三产业占 GDP 的百分比来衡量。使用固定效应回归模型探讨城市化变化与抑郁症之间的关系。结果表明，抑郁症与城市化密切相关，上述 3 个指标均存在保护作用：随着城市化水平的提高，抑郁症的患病率降低（从最低城市化水平到最高城市化水平：<0.01）。在 10 个抑郁症状中，“困扰”、“减少能量导致活动减少”和“绝望”随着城市化的发展改善最明显。城市化对居民心理健康的影响是一个长期的、多因素相互作用的过程。因此，我们需要充分考虑所有可能的影响因素，并进行更长时间的随访研究来验证。
