大气粗颗粒物与中国多城市抑郁症每日住院人数、费用和天数的关联

马亚婷; 徐洲阳; 倪晓莉; 郭新彪; 吴少伟

doi:10.16462/j.cnki.zhjbkz.2021.10.006

大气粗颗粒物与中国多城市抑郁症每日住院人数、费用和天数的关联

doi: 10.16462/j.cnki.zhjbkz.2021.10.006

1.
710061 西安，西安交通大学人文社会科学学院社会心理学研究所
2.
100191 北京，北京大学公共卫生学院劳动卫生与环境卫生学系
3.
710061 西安，西安交通大学公共卫生学院劳动卫生与环境卫生学系

基金项目:

国家自然科学基金 82073509

详细信息

通讯作者:
吴少伟，E-mail: shaowei_wu@xjtu.edu.cn

中图分类号: R181;R122.2;R749
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- 被引次数: 0
出版历程
- 收稿日期: 2021-06-07
- 修回日期: 2021-07-26
- 网络出版日期: 2021-11-17
- 刊出日期: 2021-10-10

Association of ambient coarse particulate matter with hospital admissions, related expenditures and stays for depression in China: a multicity study

1.
Institute of Social Psychology, School of Humanities and Social Sciences, Xi'an Jiaotong University, Xi'an 710061, China
2.
Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
3.
Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China

Funds:

National Natural Science Foundation of China 82073509

More Information

Corresponding author: WU Shao-wei, E-mail: shaowei_wu@xjtu.edu.cn

摘要

摘要: 目的基于中国城镇职工基本医疗保险和城镇居民基本医疗保险数据库，分析大气粗颗粒物(coarse particulate matter, PM_2.5-10)短期暴露与中国部分城市人群抑郁症住院人数、费用与天数的关联。方法基于2013―2017年中国56个地级及以上城市大气PM_2.5-10数据及抑郁症住院信息，进行两阶段时间序列分析。使用广义相加模型控制星期几效应、节假日效应、长期趋势、气象因素等混杂因素后，分别分析各城市大气PM_2.5-10短期暴露对抑郁症住院人数影响，并采用随机效应模型综合不同城市结果，进而计算住院人数、住院费用和住院天数的归因数及归因百分比。结果研究共纳入56个城市82 708例抑郁症住院患者信息。大气PM_2.5-10短期暴露与抑郁症住院人数、费用与天数之间存在正向关联。在lag0、lag02和lag03时间窗上，大气PM_2.5-10短期暴露浓度每升高10 μg/m³，抑郁症住院人数分别增加0.58%(95% CI: 0.04%~1.12%)、1.20%(95% CI: 0.10%~2.29%)和1.20%(95% CI: 0.01%~2.39%)。其中在lag03时间窗，住院人数、费用和天数归因于PM_2.5-10短期暴露的百分比达到最大，分别为4.14%(95% CI: 0.04%~8.03%)、3.67%(95% CI: 0.03%~7.14%)和3.89%(95% CI: 0.04%~7.54%)；平均每个患者因PM_2.5-10短期暴露导致的归因住院费用和天数分别为483.77(95% CI: 4.49~940.63)元和1.03(95% CI: 0.01~1.99) d。结论短期暴露于大气粗颗粒物与中国城市人群抑郁症住院人数、费用和天数的增加有关。
- 大气污染 /
- 粗颗粒物 /
- 抑郁症 /
- 住院 /
- 费用 /
- 关联
Abstract: Objective Based on China's urban employee basic medical insurance and urban residents' basic medical insurance database, this study aims to investigate the associations between short-term exposure to ambient coarse particulate matter (PM_2.5-10) and risk of hospital admissions, related expenditures and stays (counted as days in hospital) for depression. Methods A two-stage time-series study was conducted using the daily data in ambient PM_2.5-10 and hospital admissions for depression in 56 prefecture-level or above cities in China from 2013 to 2017. The generalized additive model (GAM) with adjustment for day-of-week effect, holiday effect, secular trend, and meteorological variables was used to investigate the city-specific associations between short-term exposure to PM_2.5-10 and risk of hospital admissions for depression, and a random-effects model was used to pool the city-specific associations to generate an overall association over different cities. Attributable numbers and fractions of hospital admissions, related expenditures and stays associated with short-term exposure to ambient PM_2.5-10 were also calculated based on the results of the two-stage time-series analyses. Results A total of 82 708 hospital admissions for depression were identified in the urban medical insurance schemes in 56 Chinese cities during the study period. Short-term exposure to ambient PM_2.5-10 was associated with increased hospital admissions, related expenditures and stays. For each 10 μg/m³ increase in lag0, lag02, and lag03, there were significant increases of 0.58% (95% CI: 0.04%-1.12%), 1.20% (95% CI: 0.10%-2.29%) and 1.20% (95% CI: 0.01%-2.39%) in hospital admissions for depression, respectively. The attributable fractions of hospital admissions, related expenditures and stays associated with ambient PM_2.5-10 reached maximum values at lag03, and were 4.14% (95% CI: 0.04%-8.03%), 3.67% (95% CI: 0.03%-7.14%) and 3.89% (95% CI: 0.04%-7.54%), respectively; and the average hospitalization expenditure and stay per patient due to short-term exposure to PM_2.5-10 were 483.77 (95% CI: 4.49-940.63) yuan and 1.03 (95% CI: 0.01-1.99) d, respectively. Conclusion Short-term exposure to ambient PM_2.5-10 is associated with increased risk of hospital admissions, expenditures and stays for depression in the general urban population in China.
- Air pollution /
- Coarse particulate matter /
- Depression /
- Hospital admissions /
- Expenditures /
- Association

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图 1 不同滞后时间窗大气PM_2.5-10浓度每升高10 μg/m³对应的抑郁症住院人数的百分比变化及其95% CI

Figure 1. The percentage change and 95% CI of the number of hospitalized depression patients corresponding to a 10 μg/m³ increase in atmospheric PM_2.5-10 concentration in different lag time windows

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表 1 2013―2017年中国56个城市抑郁症住院人数、费用和天数的分布[n(%)]

Table 1. The distribution of the number of hospitalizations, expenditures and days of depression in 56 cities in China from 2013 to 2017 [n(%)]

分类	住院人数(人)	住院费用(万元)	住院天数(万天)
地理区域
北方城市	41 378(50.03)	54 899.23(50.35)	94.67(43.48)
南方城市	41 330(49.97)	54 134.90(49.65)	123.04(56.52)
性别^a
男	25 084(30.33)	32 267.81(29.59)	73.32(33.68)
女	41 890(50.65)	55 930.85(51.30)	113.73(52.24)
年龄(岁) ^a
0~＜19	1 094(1.32)	1 699.79(1.56)	5.86(2.69)
19~＜40	10 609(12.83)	17 680.66(16.22)	38.33(17.61)
40~＜65	39 692(47.99)	47 542.80(43.60)	97.36(44.72)
≥65	15 579(18.84)	21 275.42(19.51)	45.49(20.89)
季节
温暖季节	41 578(50.27)	58 670.82(53.81)	105.96(48.67)
寒冷季节	41 130(49.73)	50 363.31(46.19)	111.75(51.33)
合计	82 708(100.00)	109 034.13(100.00)	217.71(100.00)
注：^a性别、年龄分组住院数据统计去除了缺失分组信息的个体

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表 2 2013―2017年中国56个城市日均大气PM_2.5-10及气象因素水平分布

Table 2. Distribution of average daily atmospheric PM_2.5-10 and meteorological factors in 56 cities in China from 2013 to 2017

气象因素	平均值	标准差	最小值	中位数	最大值	Q ^a
PM_2.5-10日均浓度(μg/m³)
北方城市	49.65	32.34	0.00	43.22	726.20	39.22
南方城市	27.44	19.68	0.00	23.15	1259.50	19.53
总体	38.35	28.88	0.00	30.63	1259.50	31.96
日均气温(℃)
北方城市	11.46	11.69	-28.90	12.90	35.30	19.30
南方城市	18.14	8.32	-6.60	19.20	36.10	13.60
总体	14.92	10.62	-28.90	16.50	36.10	15.90
日均相对湿度(%)
北方城市	62.72	18.08	7.00	64.00	100.00	28.00
南方城市	75.38	13.86	17.00	77.00	100.00	20.00
总体	69.28	17.24	7.00	71.00	100.00	24.00
注：^a即四分位数间距(inter-quartile range)。

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表 3 双污染物模型中不同滞后时间窗大气PM_2.5-10浓度每升高10 μg/m³对应的抑郁症住院人数的百分比变化及其95% CI

Table 3. The percentage change and 95% CI of the number of hospitalized depression patients corresponding to each increase of 10 μg/m³ of atmospheric PM_2.5-10 concentration in the dual-pollutant model with different lag time windows

滞后时间窗	单污染物模型(%)	调整PM_2.5(%)	调整CO(%)	调整SO₂(%)	调整O₃(%)	调整NO₂(%)
lag0	0.58(0.04~1.12)	0.41(-0.03~0.86)	0.35(-0.13~0.83)	0.48(-0.06~1.02)	0.39(-0.06~0.84)	0.29(-0.21~0.78)
lag02	1.20(0.10~2.29)	0.77(0.05~1.49)	0.78(-0.02~1.59)	0.76(-0.09~1.61)	0.75(0.05~1.46)	0.54(-0.23~1.31)
lag03	1.20(0.01~2.39)	0.82(0.07~1.58)	0.86(0.03~1.69)	0.78(-0.09~1.65)	0.82(0.08~1.56)	0.62(-0.16~1.40)

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表 4 不同滞后时间窗与大气PM_2.5-10相关抑郁症住院人数、费用和天数的归因数、归因百分比及其95% CI

Table 4. The attributable number, attribution percentage and 95% CI of the number of hospitalizations, expenditures and days of depression related to atmospheric PM_2.5-10 with different lag time windows

结果类型	住院人数(人)	住院费用(万元)	住院天数(万天)	平均住院费用(元)	平均住院天数(d)
lag0
归因数	1 680(117~3 206)	1 962.83(136.88~3 749.18)	4.17(0.29~7.96)	237.32(16.55~453.30)	0.50(0.04~0.96)
归因百分比(%)	2.03(0.14~3.88)	1.80(0.13~3.44)	1.91(0.13~3.65)
lag02
归因数	3 412(302~6 378)	3 991.22(353.01~7 472.64)	8.47(0.75~15.82)	482.57(42.68~903.74)	1.02(0.09~1.91)
归因百分比(%)	4.13(0.37~7.71)	3.66(0.32~6.85)	3.88(0.34~7.25)
lag03
归因数	3 421(32~6 640)	4 001.16(37.13~7 779.78)	8.49(0.08~16.47)	483.77(4.49~940.63)	1.03(0.01~1.99)
归因百分比(%)	4.14(0.04~8.03)	3.67(0.03~7.14)	3.89(0.04~7.54)

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表 5 不同亚组大气PM_2.5-10浓度每升高10 μg/m³对应的抑郁症住院人数的百分比变化及其95% CI(%)

Table 5. Percentage change and 95% CI of the number of hospitalized depression patients corresponding to each increase of atmospheric PM_2.5-10 concentration by 10 μg/m³ in different subgroups (%)

变量	Lag02	Lag03
地理区域
北方城市	0.78(-0.72~2.28)	1.00(-0.51~2.51)
南方城市	1.86(0.26~3.46)	1.49(-0.50~3.48)
Z值	0.927	0.207
P值	0.335	0.649
性别
男	1.22(0.07~2.37)	1.30(0.05~2.55)
女	0.72(-0.46~1.89)	0.69(-0.61~1.98)
Z值	0.361	0.450
P值	0.548	0.501
年龄(岁)
19~＜40	2.74(1.31~4.17)	2.32(-0.29~4.94)
40~＜65	0.90(-0.42~2.21)	1.14(-0.39~2.67)
≥65	1.44(0.09~2.79)	1.96(0.34~3.59)
Z值	0.623	0.834
P值	0.172	0.661
季节
温暖季节	-0.73(-2.10~0.65)	-0.26(-2.14~1.63)
寒冷季节	2.11(0.58~3.63)	1.52(-0.04~3.08)
Z值	7.503	2.571
P值	0.006	0.148

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表 6 大气PM_2.5-10短期暴露与抑郁症住院人数关联的荟萃回归结果及其95% CI(%)

Table 6. The regression results of the the association between short-term exposure to atmospheric PM_2.5-10 and the number of hospitalized depression patients and its 95% CI (%)

变量	lag02	lag03
地理区域
北方城市	-1.07(-3.33~1.19)	-0.62(-3.09~1.86)
南方城市	0.00	0.00
性别
男	0.63(-1.04~2.31)	0.41(-1.49~2.31)
女	0.00	0.00
年龄(岁)
19~＜40	1.30(-0.69~3.30)	0.35(-2.99~3.68)
40~＜65	-0.66(-2.36~1.05)	-1.00(-3.21~1.21)
≥65	0.00	0.00
季节
温暖季节	0.00	0.00
寒冷季节	2.77(0.66~4.88)	1.95(-0.48~4.38)

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