Department of Statistics, Faculty of Science, Ramkhamhaeng University, Bangkapi, Bangkok, Thailand.
Department of Psychology and Department of Physics, University of Connecticut, Storrs, Connecticut, United States of America.
PLoS One. 2022 Aug 18;17(8):e0272995. doi: 10.1371/journal.pone.0272995. eCollection 2022.
Chiang Mai is one of the most known cities of Northern Thailand, representative for various cities in the East and South-East Asian region exhibiting seasonal smog crises. While a few studies have attempted to address smog crises effects on human health in that geographic region, research in this regard is still in its infancy. We exploited a unique situation based on two factors: large pollutant concentration variations due to the Chiang Mai smog crises and a relatively large sample of out-patient visits. About 216,000 out-patient visits in the area of Chiang Mai during the period of 2011 to 2014 for upper (J30-J39) and lower (J44) respiratory tract diseases were evaluated with respect to associations with particulate matter (PM10), ozone (O3), and nitrogen dioxide (NO2) concentrations using single-pollutant and multiple-pollutants Poisson regression models. All three pollutants were found to be associated with visits due to upper respiratory tract diseases (with relative risks RR = 1.023 at cumulative lag 05, 95% CI: 1.021-1.025, per 10 μg/m3 PM10 increase, RR = 1.123 at lag 05, 95% CI: 1.118-1.129, per 10 ppb O3 increase, and RR = 1.110 at lag 05, 95% CI: 1.102-1.119, per 10 ppb NO2 increase). Likewise, all three pollutants were found to be associated with visits due to lower respiratory tract diseases (with RR = 1.016 at lag 06, 95% CI: 1.015-1.017, per 10 μg/m3 PM10 increase, RR = 1.073 at lag 06, 95% CI: 1.070-1.076, per 10 ppb O3 increase, and RR = 1.046 at lag 06, 95% CI: 1.040-1.051, per 10 ppb NO2 increase). Multi-pollutants modeling analysis identified O3 as a relatively independent risk factor and PM10-NO2 pollutants models as promising two-pollutants models. Overall, these results demonstrate the adverse effects of all three air pollutants on respiratory morbidity and call for air pollution reduction and control.
清迈是泰国北部最著名的城市之一,是东南亚和东亚多个城市季节性烟雾危机的代表。尽管有一些研究试图探讨该地区烟雾危机对人类健康的影响,但这方面的研究仍处于起步阶段。我们利用了一种独特的情况,这种情况基于两个因素:由于清迈烟雾危机,污染物浓度的大幅变化,以及门诊就诊的相对较大的样本。在 2011 年至 2014 年期间,对清迈地区约 216000 次上呼吸道(J30-J39)和下呼吸道(J44)疾病的门诊就诊情况进行了评估,这些就诊与颗粒物(PM10)、臭氧(O3)和二氧化氮(NO2)浓度之间的关系,使用单污染物和多污染物泊松回归模型进行了评估。结果表明,所有三种污染物都与上呼吸道疾病就诊有关(PM10 每增加 10μg/m3,累积滞后 05 时的相对风险 RR = 1.023,95%置信区间:1.021-1.025;O3 每增加 10ppb,滞后 05 时的 RR = 1.123,95%置信区间:1.118-1.129;NO2 每增加 10ppb,滞后 05 时的 RR = 1.110,95%置信区间:1.102-1.119)。同样,所有三种污染物都与下呼吸道疾病就诊有关(PM10 每增加 10μg/m3,滞后 06 时的 RR = 1.016,95%置信区间:1.015-1.017;O3 每增加 10ppb,滞后 06 时的 RR = 1.073,95%置信区间:1.070-1.076;NO2 每增加 10ppb,滞后 06 时的 RR = 1.046,95%置信区间:1.040-1.051)。多污染物模型分析确定 O3 是一个相对独立的风险因素,PM10-NO2 污染物模型是有前途的双污染物模型。总的来说,这些结果表明所有三种空气污染物对呼吸发病率都有不良影响,并呼吁减少和控制空气污染。