Chronic ozone exposure and depression among middle-aged and elderly people in China
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摘要:
目的 探究大气臭氧(ozone, O3)长期暴露与我国中老年人群抑郁的关联，为预防和干预抑郁提供科学指导。 方法 在我国大气污染防治重点区域中选择16个省、自治区、直辖市的45个县、区作为研究现场，按照严格的调查社区选择原则和调查对象纳入标准进行随机抽样，选择8 584名40~＜90岁中老年人作为研究对象。采用统一编制的调查问卷收集调查对象的人口学特征、社会经济状况、疾病和症状信息，使用9条目患者健康问卷(Patient Health Questionnaire 9, PHQ-9)评估调查对象的抑郁患病情况。通过距离社区最近的空气质量监测国控站点数据估算调查前1年大气污染物平均浓度和调查前2年大气污染物滑动平均浓度，采用多因素Logistic回归分析模型探讨O3暴露与罹患抑郁的关联。 结果 纳入研究的8 584名调查对象中，抑郁患病率为6.79%(583/8 584)。Logistic回归分析模型显示，未发现O3长期暴露与抑郁患病风险有关，总体上看，调查前2年的O3滑动平均年均浓度对应的效应值最大(OR=1.04, 95% CI: 0.96~1.13, P=0.326)，但无统计学意义；分层分析显示，与女性和不吸烟的调查对象相比，男性和现在吸烟的调查对象抑郁患病与O3暴露的关联更强，且组间差异具有统计学意义(均有P＜0.05)；空气动力学直径＜2.5 μm的颗粒物(particulate matter smaller than 2.5 μm in aerodynamic diameter, PM2.5)浓度和气温对抑郁患病与O3暴露的关联存在修饰作用，低PM2.5浓度、较高气温地区抑郁患病与O3暴露关联更强。 结论 本研究发现男性人群、吸烟人群以及生活在PM2.5浓度较低和年均气温较高地区的人群中，O3暴露与抑郁患病风险存在关联。 Abstract:Objective To investigate the association between chronic ozone (O3) exposure and depression among middle-aged and elderly people in China, in order to provide guidance for prevention and intervention of depression. Methods Among key areas for air pollution control in China, according to strict inclusion criteria for study sites and population, 8 584 participates aged 40~ < 90 from 45 districts/counties in 16 provinces were randomly selected and recruited using a stratified random sampling method. The demographic characteristics, socioeconomic factors, disease and symptom information were obtained through face-to-face questionnaire survey, and the depression was measured by Patient Health Questionnaire 9 (PHQ-9). One- and two-year moving average concentrations of air pollutant prior to the survey were calculated, referring to the data from the closest environmental monitoring station. The multivariate Logistic regression model was constructed to analyze the association between chronic O3 exposure and depression. Results The prevalence of depression was 6.79% (n=583) among the selected 8 584 participates. Statistically significant association between chronic O3 exposure and depression was not found from Logistic regression analysis model. The maximum OR value was 1.04 (95% CI: 0.96-1.13, P=0.326) for each 10 μg/m3 increase of two-year moving average concentrations of O3. In subgroup analysis, the stronger associations were observed in male and current smoking participants compared with female and never smoking individuals, and these differences were statistically significant (all P < 0.05). Moreover, modification effects of particulate matter smaller than 2.5 μm in aerodynamic diameter (PM2.5) and annual temperature were found on the O3-depression associations. Low PM2.5 concentrations (≤25th percentile in all districts/counties) and high temperature (≥75th percentile in all districts/counties) conditions enhanced the effects of O3 on depression. Conclusion Our findings indicated statistically positive association of O3 exposure and depression among male, current smoking individuals, population in low PM2.5 concentration and high temperature conditions. -
Key words:
- Ozone /
- Chronic exposure /
- Middle-aged and elderly /
- Depression /
- Association
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图 1 不同O3指标每升高10 μg/m3与抑郁患病的关联
Figure 1. Association between different O3 exposure indicators with 10 μg/m3 increase and depression
图 2 调查前2年O3滑动平均年均浓度每升高10 μg/m3与抑郁患病关联的分层分析
注：调查前2年PM2.5滑动平均年均浓度≤P25浓度为低PM2.5浓度，P25~＜P75浓度为中PM2.5浓度，≥P75浓度为高PM2.5浓度；调查前2年滑动平均温度≤P25温度为较低温，P25~＜P75温度为中等温，≥P75温度为较高温。
Figure 2. Risk of depression with 10 μg/m3 increase in two-year moving average concentration of O3 by subgroup
图 3 调查前2年O3滑动平均的年均浓度每升高10 μg/m3与抑郁患病关联的曲线分析
Figure 3. Curve association between depression and 10 μg/m3 increase in 2-year moving average concentration of O3
表 1 不同调查对象抑郁状态比较[n (%)]
Table 1. Characteristics of enrolled participants [n (%)]
变量 抑郁 χ2值 P值 是 否 年龄(岁) 13.81 ＜0.001 40~＜65 236(40.48) 3 876(48.44) 65~＜90 347(59.52) 4 125(51.56) 性别 51.08 ＜0.001 男 204(34.99) 4 026(50.32) 女 379(65.01) 3 975(49.68) BMI(kg/m2) 17.07 ＜0.001 ＜18.5 37(6.35) 286(3.57) 18.5~＜24.0 260(44.60) 3 528(44.09) 24.0~＜28.0 192(32.93) 3 063(38.28) ≥28.0 93(15.95) 1 102(13.77) 受教育程度 57.57 ＜0.001 小学及以下 264(45.28) 2 518(31.47) 中学 272(46.66) 4 207(52.58) 大学/大专及以上 47(8.06) 1 276(15.95) 就业情况 32.68 ＜0.001 就业 163(27.96) 2 854(35.67) 无业 163(27.96) 1 507(18.84) 退休 257(44.08) 3 640(45.49) 家庭年收入(万元) 13.87 ＜0.001 ＜10 467(80.10) 5 997(74.95) ≥10 99(16.98) 1 936(24.19) 社会支持程度 65.04 ＜0.001 低 27(4.63) 111(1.39) 中 242(41.51) 2 545(31.81) 高 314(53.86) 5 342(66.77) 吸烟 14.53 ＜0.001 不吸烟 444(76.16) 5 604(70.04) 过去吸烟 58(9.95) 764(9.55) 现在吸烟 81(13.89) 1 633(20.41) 饮酒 20.52 ＜0.001 是 60(10.29) 1 409(17.61) 否 523(89.71) 6 592(82.39) 自报慢性病患病 92.29 ＜0.001 是 415(71.18) 4 046(50.57) 否 168(28.82) 3 951(49.38) 
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表 2 污染物和气象数据描述性分析
Table 2. Summary statistics of air pollutants, meteorological indicators
变量 x±s Min a P50 Max b Q c 调查前1年 O3(μg/m3) 年均浓度 55.84±14.34 16.14 56.40 91.88 14.17 8 h最大值年均浓度 71.37±15.29 35.51 72.76 115.22 13.79 1 h最大值年均浓度 110.00±20.48 51.30 112.45 144.04 15.01 PM2.5(μg/m3) 53.06±15.37 24.76 52.33 89.22 19.25 NO2(μg/m3) 41.16±11.98 14.17 42.87 66.32 16.85 平均气温(℃) 15.49±4.15 4.36 14.75 23.20 4.36 调查前2年滑动平均 O3(μg/m3) 年均浓度 54.30±12.92 26.27 54.72 87.63 14.68 8 h最大值年均浓度 76.88±14.64 44.86 77.04 109.65 17.54 1 h最大值年均浓度 107.20±17.66 57.09 111.91 135.35 14.25 PM2.5(μg/m3) 55.98±15.88 27.03 54.51 93.09 21.34 NO2(μg/m3) 41.07±12.39 11.46 42.67 64.24 19.00 平均气温(℃) 15.41±4.14 4.67 14.71 23.28 4.14 注：a表示最小值；b表示最大值；c Q=P75-P25。
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表 3 调查前2年O3滑动平均年均浓度每升高10 μg/m3与抑郁患病关联的敏感性分析
Table 3. Sensitivity analysis of association between depression and 10 μg/m3 increase in two-year moving average concentration of O3
模型 OR (95% CI)值 P值 模型1 1.04(0.96~1.13) 0.326 模型2 1.04(0.96~1.13) 0.354 模型3 0.99(0.93~1.07) 0.865 模型4 1.03(0.95~1.12) 0.413 模型5 1.04(0.96~1.13) 0.323 模型6 1.02(0.94~1.11) 0.666 模型7 1.03(0.95~1.11) 0.475 注：主模型(模型1)中调整PM2.5、年龄、性别、婚姻状况、BMI、吸烟状态、饮酒状态、受教育程度、就业情况、家庭年收入、慢性病史、社会支持程度、实际睡眠时长、地理区域划分(华北、东北、华东、华中、华南、西南和西北)、居住方式和平均气温; 模型2：在模型1基础上将年龄作为连续变量纳入模型；模型3：在模型1基础上将地理区域重新划分为南方和北方纳入模型；模型4：在模型1基础上调整体力活动；模型5：在模型1基础上删除调整PM2.5；模型6：在模型1基础上删除调整PM2.5，调整NO2；模型7：在模型1基础上删除调整实际睡眠时长。
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