内科

目的探究空气颗粒污染物与抑郁症发作入院的关联性。方法收集2019年1月至2023年12月广西钦州市第三人民医院4 654例抑郁症发作入院患者的数据，收集同期钦州市空气颗粒污染物［PM2.5（细颗粒物）、PM10（可吸入颗粒物）］及气象因素（平均温度、相对湿度）等数据，应用R软件建立分布滞后非线性模型（DLNM），分析PM2.5、PM10对抑郁症发作入院的影响与滞后效应。结果广西钦州市第三人民医院抑郁症发作入院患者共4 654例，日均发作入院例数3例。性别分布：男性1 696（36.44%）例，女性2 958（63.56%）例；男女性别比为1∶1.74；年龄分布：˂18岁1 501（32.25%）例，18～60岁2 836（60.94%）例，>60岁317（6.81%）例。PM2.5日均浓度为25.68 μg/m3，PM10日均浓度为45.07 μg/m3，平均温度为22.69 ℃，日相对湿度为81.84%。滞后18 d至26 d（lag18～lag26）时，PM2.5对抑郁症发作入院的影响的相对危险度（RR）均大于1.00（均P<0.05），lag26时RR最高［1.031 22（1.001 48～1.061 85）］。lag3～lag9时，PM10对抑郁症发作入院的影响的RR均大于1.00（均P<0.05），lag3时RR值最高［1.034 82（1.001 75，1.068 99）］。累积滞后第28天（lag0～28）时，PM10对抑郁症发作入院的影响的RR最大［RR：1.947 84（1.049 16～3.616 31）］。在PM2.5暴露下，随着累积滞后天数增加，男性及女性人群、＞60岁人群的抑郁症发病风险逐渐升高。在PM10暴露下，随着累积滞后天数增加，男性人群、寒冷季节、＞60岁人群的抑郁症发病风险逐渐升高。结论 PM2.5、PM10暴露均会提高抑郁症发作入院风险，PM2.5、PM10暴露均对抑郁症发作入院风险有长期影响。

Objective To explore the association between air particulate pollutants and hospital admissions for depressive episodes. Methods The data of 4,654 patients admitted to the Third People's Hospital of Qinzhou, Guangxi, for depressive episodes from January 2019 to December 2023 were collected, the data of air particulate pollutants [PM2.5 (fine particulate matter), PM10 (inhalable particulate matter)] and meteorological factors (mean temperature, relative humidity) in Qinzhou during the same period were collected, and the distributed lag nonlinear model (DLNM) was established by R software to analyze the impacts and lag effects of PM2.5 and PM10 on the hospital admissions for depressive episodes. Results A total of 4,654 patients were admitted to the Third People's Hospital of Qinzhou, Guangxi, for depressive episodes, with an average daily hospital admission of 3 cases. In terms of sex distribution, 1,696 (36.44%) cases were males and 2,958 (63.56%) were females, with the gender ratio of males to females as 1∶1.74. In terms of age distribution, 1,501 (32.25%) cases aged younger than 18, 2,836 (60.94%) cases aged from 18 to 60, and 317 (6.81%) cases aged older than 60. The daily average concentration of PM2.5 was 25.68 μg/m3, the daily average concentration of PM10 was 45.07 μg/m3, the mean temperature was 22.69°C, and the daily relative humidity was 81.84%. For the impact of PM2.5 on the hospital admissions for depressive episodes, the RR was over 1.00 when laging 18 to 26 days (lag18~lag26) (all P<0.05), and the RR reached the highest at lag26 [1.031 22 (1.001 48~1.061 85)]. For the impact of PM10 on the hospital admissions for depressive episodes, the RR was over 1.00 at lag3~lag9 (all P<0.05), and the RR reached the highest at lag3 [1.034 82 (1.001 75, 1.068 99)]. The cumulative lag effect of PM10 on the hospital admissions for depressive episodes was the highest at lag0~28 [RR: 1.947 84 (1.049 16~3.616 31)]. Under PM2.5 exposure, the risks of hospital admissions for depressive episodes of males, females, and people older than 60 gradually increased with the cumulative lag days increasing. Under PM10 exposure, being males, cold weather, and being older than 60 gradually increased the risks for hospital admissions for depressive episodes with the cumulative lag days increasing. Conclusion PM2.5 and PM10 exposure can increase the risks for hospital admissions for depressive episodes, which is a long-term effect.