Advanced analysis of depression tendency in China: an investigation of environmental and social factors based on geographical and temporal weighted regression.

IF 0.9 4区 医学 Q4 HEALTH CARE SCIENCES & SERVICES
Geospatial Health Pub Date : 2025-07-07 Epub Date: 2025-07-21 DOI:10.4081/gh.2025.1385
Yanhong Xu, Zhilin Hong, Huimei Lin, Xiaofeng Huang
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引用次数: 0

Abstract

The spatiotemporal distribution of depressive tendencies across China from 2011 to 2022 was investigated using the Baidu Depression Search Index (BDSI). We examined key influencing natural factors, such as water pollution, air pollution, and deforestation, along with economic indicators, such as gross domestic product per capita, disposable income per capita, and health professionals per 10,000 population. Geographical and Temporal Weighted Regression (GTWR) was applied to capture the spatiotemporal heterogeneity of the BDSI determinants. The results revealed significant regional disparities, with the China's eastern region consistently exhibiting the highest values reflecting heightened mental health concerns, while the western region were found to have the lowest. The BDSI trends followed different trajectories, all of which peaked in 2019 before a sharp decline in 2020. Water pollution transitioned from negative to positive influence in the East, while deforestation exhibited regionally variable effects. Air pollution, peaking in 2019 and 2022, demonstrated the highest impact variability. The economic indicators showed complex regional and temporal patterns underscoring the need for tailored interventions. Together, these findings provided critical insights into the intricate interplay between environmental, economic, and healthcare factors in shaping mental health that highlighted the necessity of region-specific policies to mitigate depressive tendencies and enhance public mental well-being. These research results offer targeted recommendations for regionally adaptive mental health strategies across China.

中国抑郁趋势的高级分析:基于地理和时间加权回归的环境和社会因素调查。
采用百度抑郁搜索指数(BDSI)分析了2011 - 2022年中国抑郁倾向的时空分布特征。我们研究了主要的影响自然因素,如水污染、空气污染和森林砍伐,以及经济指标,如人均国内生产总值、人均可支配收入和每万人口中的卫生专业人员。采用地理和时间加权回归(GTWR)来捕捉BDSI决定因素的时空异质性。结果显示了显著的地区差异,中国东部地区一直表现出最高的值,反映了人们对心理健康的高度关注,而西部地区则表现出最低的值。BDSI趋势遵循不同的轨迹,所有这些趋势都在2019年达到顶峰,然后在2020年急剧下降。东部地区水污染的影响由负向正转变,而森林砍伐的影响则表现出区域差异。空气污染在2019年和2022年达到峰值,表现出最高的影响变异性。经济指标显示出复杂的区域和时间格局,强调需要采取有针对性的干预措施。总之,这些发现为形成心理健康的环境、经济和医疗保健因素之间错综复杂的相互作用提供了重要的见解,强调了区域特定政策减轻抑郁倾向和提高公众心理健康的必要性。这些研究结果为中国的区域适应性心理健康策略提供了有针对性的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Geospatial Health
Geospatial Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.40
自引率
11.80%
发文量
48
审稿时长
12 months
期刊介绍: The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.
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