Effects of particulate air pollution on tuberculosis development in seven major cities of Korea from 2010 to 2016: methodological considerations involving long-term exposure and time lag

Kim, Honghyok; Yu, Sarah; Choi, Hong-Jo

doi:10.4178/epih.e2020012

Cited by 21 publications

(12 citation statements)

References 23 publications

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“…Therefore, in combination with the results of this study and previous studies, it can be seen that PM2.5 can damage the immune response of the lungs and accelerate the progress of tuberculosis. We can see that from some epidemiological studies, PM10, it has a similar effect and reaction mechanism to PM2.5 (Rivas-Santiago and Sarkar et al, 2015;Kim and Yu et al, 2020;Pompilio and Di Bonaventura, 2020;Xiang and Xu et al, 2021). PM2.5 and PM10 are so small in diameter that they can pass through the physical barrier of the respiratory tract.…”

Section: Discussionmentioning

confidence: 85%

Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China

Wang

et al. 2022

Environ Sci Pollut Res

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There is growing evidence that air pollution plays a role in TB, but few studies have comprehensively included the six common air pollutants. Our objectives were to investigate the association between short-term exposure to six common air pollutants and the risk of tuberculosis outpatient visits in Fuyang, China, during the period 2015-2020. We combined the two models to explore the effects of exposure to six air pollutants on the risk of tuberculosis outpatient visits, including Poisson generalized linear regression model and distributed lag non-linear model (DLNM). We performed stratified analyses for season, gender and age. We used the lag-specific relative risks and cumulative relative risk obtained by increasing pollutant concentration by per 10 units to evaluate the connection between six air pollutants and TB, PM2.5 (RR=1.0018, 95%CI: 1.0004-1.0032, delay of 12 days) and (RR=1.0169,95%CI: 1.0007-1.0333, lag 3 / 31 0-16 days), SO2 were 0.9549 (95%CI: 0.9389-0.9712, lag 0 days) and 0.8212 (95%CI: 0.7351-0.9173, 0-20 days lag). Stratified analyses showed that seasonal differences had a greater impact on TB, and male more likely to develop TB than female, older people more likely to develop TB than younger people. Exposure to O3, CO, PM10, PM2.5, and NO2 increases the risk of TB outpatient visits, except SO2 reduces the risk. Male and elderly people should be protected. We need to pay more attention to the impact of seasonal effects on TB.

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Section: Discussionmentioning

confidence: 85%

Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China

Wang

et al. 2022

Environ Sci Pollut Res

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“…There was an association between exposure to SO 2 and incidence of PTB, pooled adjusted RR = 1.08 (95% CI: 1.04–1.12), p < 0.001, N = 9, I 2 = 94.4% (Begg’s test, p = 0.517 and Egger’s test, p = 0.356) (Fig. 4 ) 7 , 35 , 39 , 40 , 43 , 44 , 47 – 49 . Hwang et al 27 (male RR = 1.07, 95% CI: 1.03–1.12 and female RR = 1.02, 95% CI: 0.98–1.07) reported similar findings in males.…”

Section: Resultsmentioning

confidence: 95%

“…There was a significant association between exposure to PM 10 and incidence of PTB, pooled adjusted RR = 1.06 (95% CI: 1.01–1.12), p = 0.022, N = 8, I 2 = 97.6% (Begg’s test, p = 0.536 and Egger’s test, p = 0.204) 7 , 29 , 35 , 39 , 40 , 43 , 44 , 49 . The studies by Lai et al 32 (HR = 0.95, 95% CI: 0.78–1.17) and Hwang et al 27 (male RR = 1.00, 95% CI: 0.96–1.05 and female RR = 1.01, 95% CI: 0.98–1.05) did not find a significant association.…”

Section: Resultsmentioning

confidence: 96%

A systematic review and meta-analysis on the association between ambient air pollution and pulmonary tuberculosis

Dimala

Kadia

2022

Sci Rep

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There is inconclusive evidence on the association between ambient air pollution and pulmonary tuberculosis (PTB) incidence, tuberculosis-related hospital admission and mortality. This review aimed to assess the extent to which selected air pollutants are associated to PTB incidence, hospital admissions and mortality. This was a systematic review of studies published in English from January 1st, 1946, through May 31st, 2022, that quantitatively assessed the association between PM2.5, PM10, NO2, SO2, CO, O3 and the incidence of, hospital admission or death from PTB. Medline, Embase, Scopus and The Cochrane Library were searched. Extracted data from eligible studies were analysed using STATA software. Random-effect meta-analysis was used to derive pooled adjusted risk and odds ratios. A total of 24 studies (10 time-series, 5 ecologic, 5 cohort, 2 case–control, 1 case cross-over, 1 cross-sectional) mainly from Asian countries were eligible and involved a total of 437,255 tuberculosis cases. For every 10 μg/m3 increment in air pollutant concentration, there was a significant association between exposure to PM2.5 (pooled aRR = 1.12, 95% CI: 1.06–1.19, p < 0.001, N = 6); PM10 (pooled aRR = 1.06, 95% CI: 1.01–1.12, p = 0.022, N = 8); SO2 (pooled aRR = 1.08, 95% CI: 1.04–1.12, p < 0.001, N = 9); and the incidence of PTB. There was no association between exposure to CO (pooled aRR = 1.04, 95% CI: 0.98–1.11, p = 0.211, N = 4); NO2 (pooled aRR = 1.08, 95% CI: 0.99–1.17, p = 0.057, N = 7); O3 (pooled aRR = 1.00, 95% CI: 0.99–1.02, p = 0.910, N = 6) and the incidence of PTB. There was no association between the investigated air pollutants and mortality or hospital admissions due to PTB. Overall quality of evidence was graded as low (GRADE approach). Exposure to PM2.5, PM10 and SO2 air pollutants was found to be associated with an increased incidence of PTB, while exposure to CO, NO2 and O3 was not. There was no observed association between exposure to these air pollutants and hospital admission or mortality due to PTB. The quality of the evidence generated, however, remains low. Addressing the tuberculosis epidemic by 2030 as per the 4th Sustainable Development Goal may require a more rigorous exploration of this association.

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“…Time-series decomposition was applied to preliminary analyse the numbers of admissions to explore changes in the number of hospitalized patients and the trend of admissions. Analysis of time series data are usually performed to identify long-term trends, seasonal variations and irregular fluctuations [30][31][32][33]. Long-term trend refers to the tendency for a phenomenon to continue to develop and change over a prolonged period of time.…”

Section: Discussionmentioning

confidence: 99%

Ambient air pollution, temperature and hospital admissions due to respiratory diseases in a cold, industrial city

Jia

Ning

et al. 2022

J Glob Health

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Background The influences of air pollution exposure and temperature on respiratory diseases have become major global health concerns. This study investigated the relationship between ambient air pollutant concentrations and temperature in cold industrial cities that have the risk of hospitalization for respiratory diseases. Methods A time-series study was conducted in Changchun, China, from 2015 to 2019 to analyse the number of daily admissions for respiratory diseases, air pollutant concentrations, and meteorological factors. Time-series decomposition was applied to analyse the trend and characteristics of the number of admissions. Generalized additive models and distributed lag nonlinear models were constructed to explore the effects of air pollutant concentrations and temperature on the number of admissions. Results The number of daily admissions showed an increasing trend, and the seasonal fluctuation was obvious, with more daily admissions in winter and spring than in summer and autumn. There were positive and gradually decreasing lag effects of PM10, PM2.5, NO 2 , and CO concentrations on the number of admissions, whereas O 3 showed a J-shaped trend. The results showed that within the 7-day lag period, 0.5°C was the temperature associated with the lowest relative risk of admission due to respiratory disease, and extremely low and high temperatures (<-18°C, >27°C, respectively) increased the risk of hospitalization for respiratory diseases by 8.3% and 12.1%, respectively. Conclusions From 2015 to 2019, respiratory diseases in Changchun showed an increasing trend with obvious seasonality. The increased concentrations of SO 2 , NO 2 , CO, PM2.5, O 3 and PM10 lead to an increased risk of hospitalization for respiratory diseases, with a significant lag effect. Both extreme heat and cold could lead to increases in the risk of admission due to respiratory disease.

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Effects of particulate air pollution on tuberculosis development in seven major cities of Korea from 2010 to 2016: methodological considerations involving long-term exposure and time lag

Cited by 21 publications

References 23 publications

Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China

Short-term effect of ambient air pollutant change on the risk of tuberculosis outpatient visits: a time-series study in Fuyang, China

A systematic review and meta-analysis on the association between ambient air pollution and pulmonary tuberculosis

Ambient air pollution, temperature and hospital admissions due to respiratory diseases in a cold, industrial city

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