Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Department of Biological Sciences, National University of Singapore, Singapore, Singapore.
BMC Infect Dis. 2023 Jun 6;23(1):379. doi: 10.1186/s12879-023-08185-0.
A pertinent risk factor of upper respiratory tract infections (URTIs) and pneumonia is the exposure to major ambient air pollutants, with short term exposures to different air pollutants being shown to exacerbate several respiratory conditions.
Here, using disease surveillance data comprising of reported disease case counts at the province level, high frequency ambient air pollutant and climate data in Thailand, we delineated the association between ambient air pollution and URTI/Pneumonia burden in Thailand from 2000 - 2022. We developed mixed-data sampling methods and estimation strategies to account for the high frequency nature of ambient air pollutant concentration data. This was used to evaluate the effects past concentrations of fine particulate matter (PM), sulphur dioxide (SO), and carbon monoxide (CO) and the number of disease case count, after controlling for the confounding meteorological and disease factors.
Across provinces, we found that past increases in CO, SO and PM concentration were associated to changes in URTI and pneumonia case counts, but the direction of their association mixed. The contributive burden of past ambient air pollutants on contemporaneous disease burden was also found to be larger than meteorological factors, and comparable to that of disease related factors.
By developing a novel statistical methodology, we prevented subjective variable selection and discretization bias to detect associations, and provided a robust estimate on the effect of ambient air pollutants on URTI and pneumonia burden over a large spatial scale.
上呼吸道感染(URTIs)和肺炎的一个相关风险因素是暴露于主要的环境空气污染物,短期暴露于不同的空气污染物已被证明会加重几种呼吸道疾病。
在这里,我们使用包括省级报告病例数在内的疾病监测数据、泰国高频环境空气污染物和气候数据,描绘了 2000 年至 2022 年期间泰国环境空气污染与 URTI/肺炎负担之间的关系。我们开发了混合数据采样方法和估计策略,以考虑到环境空气污染物浓度数据的高频特性。这用于评估过去细颗粒物 (PM)、二氧化硫 (SO) 和一氧化碳 (CO) 浓度的变化以及疾病病例数的变化对疾病的影响,同时控制混杂的气象和疾病因素。
在各省份中,我们发现 CO、SO 和 PM 浓度的过去增加与 URTI 和肺炎病例数的变化有关,但它们的关联方向混杂。过去环境空气污染物对同期疾病负担的贡献负担也被发现大于气象因素,与疾病相关因素相当。
通过开发一种新的统计方法,我们防止了主观变量选择和离散化偏差来检测关联,并为环境空气污染物对上呼吸道感染和肺炎负担的影响提供了在大空间尺度上的稳健估计。