《大气污染防治行动计划》实施后我国城市大气PM2.5浓度下降程度与中老年人精神健康状态改善的关系

Relationship between reduction of urban PM2.5 and mental health of middle-aged and elderly people after China's Air Pollution Prevention and Control Action Plan

  • 摘要:
    背景 流行病学证据表明颗粒物暴露与人群抑郁状况和认知能力有关联。2013—2017年我国实施了《大气污染防治行动计划》(后简称:“大气十条”)政策,以降低大气颗粒物浓度。但目前对我国大气颗粒物浓度下降程度与中老年人精神健康状态改善的关系研究较少。
    目的 分析“大气十条”政策实施后,我国城市大气颗粒物浓度下降状况与中老年人群的抑郁程度和认知功能变化的关系。
    方法 本研究利用中国健康与养老追踪调查(CHARLS)队列2011年及2018年调查数据,基于各城市对“大气十条”实际响应程度(研究期间各城市PM2.5动态变化轨迹),使用纵向聚类方法进行分组;响应程度越高,代表该市PM2.5浓度下降幅度越大。将受访者分配到对政策不同响应程度的组别,包括低响应程度A组(对照组),中响应程度B组和高响应程度C组。采用双重差分模型并考虑潜在的个体及城市级别的时变混杂以估计“大气十条”政策实施后PM2.5浓度改善程度与我国中老年人的抑郁程度和认知功能变化的关系。抑郁程度采用流调中心抑郁水平评定10条目量表进行衡量,共计10题,总分0~30分,得分越高表示抑郁程度越严重。认知功能参照国际中老年人认知功能测试问卷,包含记忆与认知状态两个维度进行评价,共计31题,总分0~31分,得分越高认知功能越好。选择结局相对完整的样本进行分析,其中抑郁分析纳入10729人,认知分析纳入4510人。
    结果 纵向聚类结果显示,PM2.5浓度下降幅度最大的城市群(即高响应程度C组)基线PM2.5浓度最高,主要分布于京津冀、成渝都市圈、武汉都市圈。在2011年,3组中老年人群的抑郁程度、认知水平均未见差异(Kruskal Wallis 检验,P抑郁=0.864,P认知=0.239)。相比于2011年,2018年低(A)、中(B)响应组人群的抑郁程度和认知水平均存在差异(配对Wilcox检验,均P<0.001);高响应(C)组人群2018年的抑郁程度相较于2011年未见差异(P=0.195),但认知水平差异有统计学意义(P=0.006)。双重差分模型显示:随着PM2.5浓度下降,相对于低响应(A)组,高响应(C)组的中老年人抑郁程度下降7.55%(95%CI:2.83%~12.03%),认知水平提高2.70%(95%CI:0.25%~5.22%);但未观察到中响应(B)组的干预效果。
    结论 实施“大气十条”政策后,PM2.5浓度下降对我国中老年人的抑郁程度和认知功能有一定的改善效果。随着我国人口老年化与精神相关疾病负担加重,推进环境空气污染治理具有重要的公共卫生学意义。

     

    Abstract:
    Background Epidemiological evidence indicates an association of particulate matter with depression and cognitive performance. From 2013 to 2017, China implemented the Air Pollution Prevention and Control Action Plan to reduce particulate matter concentration. There are few studies on the relationship between the decrease of particulate matter concentration and the improvement of mental health in middle-aged and elderly people.
    Objective To analyze the relationship between the decrease of city-level particulate matter concentration and the improvement of depression and cognitive function in the middle-aged and elderly population after the implementation of the Air Pollution Prevention and Control Action Plan.
    Methods Using the China Health and Retirement Longitudinal Study (CHARLS) data in 2011 and 2018, this study applied longitudinal data clustering technology to group cities based on the actual response of each city to the policy (the dynamic change trajectory of PM2.5 in each city during the study period); the higher the degree of response, the greater the reduction of PM2.5 concentration in the city. We assigned participants to three groups with different degrees of response to the policy, including low-response group A as the control group, medium-response intervention group B, and high-response intervention group C. A difference-in-differences (DID) model was used to estimate the influence of PM2.5 decline on the depression and cognitive function among middle-aged and elderly people in China by considering potential individual and city-level time-varying confounders. Depression was measured using the 10-item Center for the Epidemiological Studies of Depression Scale (CES-D10) (10 questions, total score range 0-30) with higher score representing higher severity of depression. Cognitive function was evaluated with reference to the international cognitive function test questionnaire for the middle-aged and the elderly which was further categorized into two dimensions of memory and cognitive status and included 31 questions with a score range of 0-31; the higher the score, the better the cognitive function. Samples with relatively complete outcomes were selected for analysis, including 10729 people in depression analysis and 4510 people in cognitive analysis.
    Results The longitudinal clustering results indicated that the urban groups with the highest decline of PM2.5 concentrations (high-response group C) had the highest baseline PM2.5 concentrations, mainly in Beijing-Tianjin-Hebei region, Chengdu-Chongqing metropolitan area, and Wuhan metropolitan area. In 2011, no significant differences were observed in depression and cognitive function among the three groups of middle-aged and elderly populations (Kruskal Wallis test: Pdepression=0.864, Pcognition=0.239). Significant differences were found in depression and cognitive function in both low-response group A and medium-response group B in 2018 compared to 2011 (paired Wilcox test, all P<0.001). However, in the high-response group C, there was no significant difference in depression in 2018 compared to 2011 (P=0.195), while a significant difference was detected in cognitive function (P=0.006). As PM2.5 concentrations decreased, the DID model showed that the depression of the middle-aged and elderly people in the high-response group C decreased by 7.55% (95%CI: 2.83%-12.03%), and the cognitive function improved by 2.70% (95%CI: 0.25%-5.22%) compared with the low-response group A. However, no intervention effect was observed in group B with moderate response level compared with group A with low response level.
    Conclusion After the implementation of the Air Pollution Prevention and Control Action Plan policy, the decrease of PM2.5 concentration has an ameliorative effect on the depression and cognitive function of middle-aged and elderly people in China. Given the aging population and the increasing burden of mental-related diseases in China, the promotion of environmental air pollution control has important public health implications.

     

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