Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study

泊松回归 置信区间 萧条(经济学) 医学 广义加性模型 空气污染 相对风险 二元分析 重性抑郁障碍 情感(语言学) 环境卫生 人口学 统计 精神科 内科学 心理学 数学 人口 化学 认知 有机化学 沟通 社会学 经济 宏观经济学
作者
Ting Hu,Zhao-Yuan Xu,Jian Wang,Su Yao,Bingbing Guo
出处
期刊:World journal of psychiatry [Baishideng Publishing Group]
卷期号:13 (12): 1061-1078 被引量:1
标识
DOI:10.5498/wjp.v13.i12.1061
摘要

BACKGROUND The literature has discussed the relationship between environmental factors and depressive disorders; however, the results are inconsistent in different studies and regions, as are the interaction effects between environmental factors. We hypothesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity. AIM To investigate the effects of meteorological factors and air pollution on depressive disorders, including their lagged effects and interactions. METHODS The samples were obtained from a class 3 hospital in Harbin, China. Daily hospital admission data for depressive disorders from January 1, 2015 to December 31, 2022 were obtained. Meteorological and air pollution data were also collected during the same period. Generalized additive models with quasi-Poisson regression were used for time-series modeling to measure the non-linear and delayed effects of environmental factors. We further incorporated each pair of environmental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders. RESULTS Data for 2922 d were included in the study, with no missing values. The total number of depressive admissions was 83905. Medium to high correlations existed between environmental factors. Air temperature (AT) and wind speed (WS) significantly affected the number of admissions for depression. An extremely low temperature (-29.0 ℃) at lag 0 caused a 53% [relative risk (RR)= 1.53, 95% confidence interval (CI): 1.23-1.89] increase in daily hospital admissions relative to the median temperature. Extremely low WSs (0.4 m/s) at lag 7 increased the number of admissions by 58% (RR = 1.58, 95%CI: 1.07-2.31). In contrast, atmospheric pressure and relative humidity had smaller effects. Among the six air pollutants considered in the time-series model, nitrogen dioxide (NO2) was the only pollutant that showed significant effects over non-cumulative, cumulative, immediate, and lagged conditions. The cumulative effect of NO2 at lag 7 was 0.47% (RR = 1.0047, 95%CI: 1.0024-1.0071). Interaction effects were found between AT and the five air pollutants, atmospheric temperature and the four air pollutants, WS and sulfur dioxide. CONCLUSION Meteorological factors and the air pollutant NO2 affect daily hospital admissions for depressive disorders, and interactions exist between meteorological factors and ambient air pollution.

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