Dataset Information

Temporal Cross-Correlations between Ambient Air Pollutants and Seasonality of Tuberculosis: A Time-Series Analysis.

ABSTRACT: The associations between ambient air pollutants and tuberculosis seasonality are unclear. We assessed the temporal cross-correlations between ambient air pollutants and tuberculosis seasonality. Monthly tuberculosis incidence data and ambient air pollutants (PM_2.5, PM₁₀, carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂)) and air quality index (AQI) from 2013 to 2017 in Shanghai were included. A cross-correlogram and generalized additive model were used. A 4-month delayed effect of PM_2.5 (0.55), PM₁₀ (0.52), SO₂ (0.47), NO₂ (0.40), CO (0.39), and AQI (0.45), and a 6-month delayed effect of O₃ (-0.38) on the incidence of tuberculosis were found. The number of tuberculosis cases increased by 8%, 4%, 18%, and 14% for a 10 ?g/m³ increment in PM_2.5, PM₁₀, SO₂, and NO₂; 4% for a 10 unit increment in AQI; 8% for a 0.1 mg/m³ increment in CO; and decreased by 4% for a 10 ?g/m³ increment in O₃. PM_2.5 concentrations above 50 ?g/m³, 70 ?g/m³ for PM₁₀, 16 ?g/m³ for SO₂, 47 ?g/m³ for NO₂, 0.85 mg/m³ for CO, and 85 for AQI, and O₃ concentrations lower than 95 ?g/m³ were positively associated with the incidence of tuberculosis. Ambient air pollutants were correlated with tuberculosis seasonality. However, this sort of study cannot prove causality.

SUBMITTER: Wang H

PROVIDER: S-EPMC6540206 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Temporal Cross-Correlations between Ambient Air Pollutants and Seasonality of Tuberculosis: A Time-Series Analysis.

Wang Hua H Tian Changwei C Wang Wenming W Luo Xiaoming X

International journal of environmental research and public health 20190506 9

The associations between ambient air pollutants and tuberculosis seasonality are unclear. We assessed the temporal cross-correlations between ambient air pollutants and tuberculosis seasonality. Monthly tuberculosis incidence data and ambient air pollutants (PM2.5, PM10, carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2)) and air quality index (AQI) from 2013 to 2017 in Shanghai were included. A cross-correlogram ...[more]

PMID: 31064146

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Project description:BackgroundPrevious studies have suggested that there is an association between air pollutants and circulatory and respiratory diseases; however, relatively few have analyzed the association between air pollutants and outpatient visits based on the mortality, hospitalization rates, etc., especially in areas with relatively good air quality. Therefore, we conducted this study to research the association between air pollutants and outpatient visits in Fuzhou, China.MethodsWe used a generalized linear Poisson model to study the association between air pollution and outpatient visits for respiratory and circulatory diseases from 2016 to 2018 in Fuzhou, China.ResultsIn the single pollutant model, nitrogen dioxide (NO2) had a significant effect. For lag day 0 to lag day 5, the effect decreased with every 10??g/L increase in NO2. The daily maximum 8-h mean ozone (O3-8h) and upper respiratory outpatient visits were positively associated during the cold period [lag2, excess risk (ER) (95% confidence interval (CI)): 1.68% (0.44-2.94%)], while O3-8h and respiratory disease were positively associated during the warm period [lag5, ER (95% CI): 1.10% (0.11-2.10%) and lag4, ER (95% CI): 1.02% (0.032-2.02%)]. Similarly, particulate matter (PM) with an average aerodynamic diameter of less than 10??m (PM10) and lower respiratory diseases were positively associated during the warm period [lag0, ER (95% CI): 1.68% (0.44-2.94%)]. When the concentration of O3-8h was higher than 100??g/L, there was a positive effect on circulatory [lag5, ER (95% CI): 2.83% (0.65-5.06%)], respiratory [lag5, ER (95% CI): 2.47% (0.85-4.11%)] and upper respiratory [lag5, ER (95% CI): 3.06% (1.38-4.77%)] outpatient visits. The variation in O3-8h changed slightly when we adjusted for other air pollutants, and after adjusting for O3-8h, the ERs of the other air pollutants changed slightly. After adjusting for PM with an average aerodynamic diameter of less than 2.5??m (PM2.5), the ERs of the other air pollutants increased, and after adjusting for NO2, the ER of PM decreased.ConclusionExposure to ambient NO2, O3, PM2.5 and PM10 was associated with an increase in respiratory and circulatory system-related outpatient visits in Fuzhou, China.

Project description:Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration-response analyses were performed. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3, and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29), and 1.26 (1.24-1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM2.5, PM10, NO2, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM2.5, PM10, NO2, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.

Dataset Information

Temporal Cross-Correlations between Ambient Air Pollutants and Seasonality of Tuberculosis: A Time-Series Analysis.

Publications

Temporal Cross-Correlations between Ambient Air Pollutants and Seasonality of Tuberculosis: A Time-Series Analysis.

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