Ambient Air Pollution Exposures and Newly Diagnosed Pulmonary Tuberculosis in Jinan, China: A Time Series Study

Ambient air pollution contributed to pulmonary tuberculosis in China

Published studies on outdoor air pollution and tuberculosis risk have shown heterogeneous results. Discrepancies in prior studies may be partially explained by the limited geographic scope, diverse exposure times, and heterogeneous statistical methods. Thus, we conducted a multi-province, multi-city time-series study to comprehensively investigate this issue. We selected 67 districts or counties from all geographic regions of China as study sites. We extracted data on newly diagnosed pulmonary tuberculosis (PTB) cases, outdoor air pollutant concentrations, and meteorological factors in 67 sites from January 1, 2014 to December 31, 2019. We utilized a generalized additive model to evaluate the relationship between ambient air pollutants and PTB risk. Between 2014 and 2019, there were 172,160 newly diagnosed PTB cases reported in 67 sites. With every 10-μg/m3 increase in SO2, NO2, PM10, PM2.5, and 1-mg/m3 in CO, the PTB risk increased by 1.97% [lag 0 week, 95% confidence interval (CI): 1.26, 2.68], 1.30% (lag 0 week, 95% CI: 0.43, 2.19), 0.55% (lag 8 weeks, 95% CI: 0.24, 0.85), 0.59% (lag 10 weeks, 95% CI: 0.16, 1.03), and 5.80% (lag 15 weeks, 95% CI: 2.96, 8.72), respectively. Our results indicated that ambient air pollutants were positively correlated with PTB risk, suggesting that decreasing outdoor air pollutant concentrations may help to reduce the burden of tuberculosis in countries with a high burden of tuberculosis and air pollution.

Association between ambient temperature, PM2.5 and tuberculosis in Northwest China

   Existing evidence suggested that the risk of tuberculosis (TB) infection was associated to the variations in temperature and PM2.5. A total of 9,111 cases of TB were reported in Ningxia Hui Autonomous Region, China from 2013 to 2015 on a daily basis, and 57.2% of them were male. The TB risk was more prominent for a lower temperature in males (RR of 1.724, 95% CI: 1.241, 2.394), the aged over 64 years (RR of 2.241, 95% CI: 1.554, 3.231), and the high mobility occupation subpopulation (RR of 2.758, 95% CI: 1.745, 4.359). High concentration of PM2.5 showed a short-term effect and was only associated with an increased risk in the early stages of exposure for the female, and aged 36-64 years group. There were 15.06% (1370 cases) of cases of TB may be attributable to the temperature, and 2.94% (268 cases) may be attributable to the increase of PM2.5 exposures. Low temperatures may be associated with significantly increase in the risk of TB, and high PM2.5 concentrations have a short-term association on increasing the risk of TB. Strengthening the monitoring and regular prevention and control of high risk groups will provide scientific guidance to reduce the incidence of TB.

Interaction between air pollutants and meteorological factors on pulmonary tuberculosis in northwest China: A case study of eight districts in Urumqi

Meteorological factors and air pollutants are associated with the spread of pulmonary tuberculosis (PTB), but few studies have examined the effects of their interactions on PTB. Therefore, this study investigated the impact of meteorological factors and air pollutants and their interactions on the risk of PTB in Urumqi, a city with a high prevalence of PTB and a high level of air pollution. The number of new PTB cases in eight districts of Urumqi from 2014 to 2019 was collected, along with data on meteorological factors and air pollutants for the same period. A generalized additive model was applied to explore the effects of meteorological factors and air pollutants and their interactions on the risk of PTB incidence. Segmented linear regression was used to estimate the nonlinear characteristics of the impact of meteorological factors on PTB. During 2014-2019, a total of 14,402 new cases of PTB were reported in eight districts, with March to May being the months of high PTB incidence. The exposure-response curves for temperature (Temp), relative humidity (RH), wind speed (WS), air pressure (AP), and diurnal temperature difference (DTR) were generally inverted "U" shaped, with the corresponding threshold values of - 5.411 °C, 52.118%, 3.513 m/s, 1021.625 hPa, and 8.161 °C, respectively. The effects of air pollutants on PTB were linear and lagged. All air pollutants were positively associated with PTB, except for O3, which was not associated with PTB, and the ER values for the effects on PTB were as follows: 0.931 (0.255, 1.612) for PM2.5, 1.028 (0.301, 1.760) for PM10, 5.061 (0.387, 9.952) for SO2, 2.830 (0.512, 5.200) for NO2, and 5.789 (1.508, 10.251) for CO. Meteorological factors and air pollutants have an interactive effect on PTB. The risk of PTB incidence was higher when in high Temp-high air pollutant, high RH-high air pollutant, high WS-high air pollutant, lowAP-high air pollutant, and high DTR-high air pollutant. In conclusion, both meteorological and pollutant factors had an influence on PTB, and the influence on PTB may have an interaction.

Air pollutants in bronchoalveolar lavage fluid and pulmonary tuberculosis: A mediation analysis of gene-specific methylation

Particulate matter (PM) exposure could alter the risk of tuberculosis, but the underlying mechanism is still unclear. We enrolled 132 pulmonary tuberculosis (PTB) patients and 30 controls. Bronchoalveolar lavage fluid samples were collected from all participants to detect organochlorine pesticides, polycyclic aromatic hydrocarbons, metal elements, and DNA methylation of immunity-related genes. We observed that γ-HCH, Bap, Sr, Ag, and Sn were related to an increased risk of PTB, while Cu and Ba had a negative effect. IFN-γ, IL-17A, IL-2, and IL-23 had a higher level in the PTB group, while IL-4 was lower. The methylation of 18 CpG sites was statistically associated with PTB risk. The methylation at the IL-4_06_121 site showed a significant mediating role on γ-HCH, Sr, and Sn. Our study suggests that PM exposure can increase the risk of tuberculosis by affecting DNA methylation and cytokine expression.

Population impact of fine particulate matter on tuberculosis risk in China: a causal inference

BACKGROUND

Previous studies have suggested the potential association between air pollution and tuberculosis incidence, but this association remains inconclusive and evidence to assess causality is particularly lacking. We aimed to draw causal inference between fine particulate matter less than 2.5 μm in diameter (PM2.5) and tuberculosis in China.

METHODS

Granger causality (GC) inference was performed within vector autoregressive models at levels and/or first-differences using annual national aggregated data during 1982-2019, annual provincial aggregated data during 1982-2019 and monthly provincial aggregated data during 2004-2018. Convergent cross-mapping (CCM) approach was used to determine the backbone nonlinear causal association based on the monthly provincial aggregated data during 2004-2018. Moreover, distributed lag nonlinear model (DLNM) was applied to quantify the causal effects.

RESULTS

GC tests identified PM2.5 driving tuberculosis dynamics at national and provincial levels in Granger sense. Empirical dynamic modeling provided the CCM causal intensity of PM2.5 effect on tuberculosis at provincial level and demonstrated that PM2.5 had a positive effect on tuberculosis incidence. Then, DLNM estimation demonstrated that the PM2.5 exposure driven tuberculosis risk was concentration- and time-dependent in a nonlinear manner. This result still held in the multi-pollutant model.

CONCLUSIONS

Causal inference showed that PM2.5 exposure driving tuberculosis, which showing a concentration gradient change. Air pollutant control may have potential public health benefit of decreasing tuberculosis burden.

Association Between Exposure to Ozone (O3) and the Short-Term Effect on Tuberculosis Outpatient Visits: A Time-Series Study in 16 Cities of Anhui Province, China

Introduction

Evidence has shown that air pollutant exposure plays a vital role in the progression of tuberculosis (TB). The aim of this research was to assess the short-term effects of ozone (O₃) exposure and TB outpatient visits in 16 prefecture-level cities of Anhui, China, 2015-2020.

Methods

Distributed lag nonlinear model (DLNM), Poisson generalized linear regression model and random effects model were applied in this study. The effects of different age and gender on TB were investigated by stratified analysis, and then we performed sensitivity analyses to verify the stability of the results.

Results

A total of 186,623 active TB cases were registered from January 1, 2015 to December 31,2020 in Anhui. The average concentration of ozone is 92.77 ± 42.95 μg/m³. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits was 1.0240 (95% CI: 1.0170-1.0310, lag 28 days) for each 10 µg/m³ increase in O₃ in the single-pollutant model. Estimation for 16 prefecture-level cities indicated that the strong association between O₃ and the risk of TB outpatient visits was in tongling (RR = 1.0555, 95% CI: 1.0089-1.1042), Suzhou (RR = 1.0475, 95% CI: 1.0268-1.0687), wuhu (RR = 1.0358, 95% CI: 1.0023-1.0704). Stratified analysis showed that the health effects of ozone exposure remained significant in male and older adults, and there was no significant association between exposure to ozone in children and adolescents and the risk of tuberculosis.

Discussion

We found that ozone exposure increases the risk of TB infection in outpatient patients, with males and the elderly being more susceptible, and it is necessary for government departments to develop targeted publicity and prevention measures in response to the local air quality conditions.

Environment pollutants exposure affects the endogenous activation of within-host Mycobacterium tuberculosis

OBJECTIVE

Epidemiological studies have linked ambient pollutants with tuberculosis (TB) risk, but the association has not been fully understood. Here, for the first time, we applied whole-genome sequencing (WGS) to assess the reproductive state of Mycobacterium tuberculosis (MTB) by profiling the mutation rate of MTB (MTBMR) during within-host endogenous reactivated progression, intending to dissect the actual effects of ambient pollutants on the endogenous reactivation.

METHODS

We conducted a retrospective cohort study on bacteriologically confirmed TB patients and followed them for relapse in Jiangsu and Sichuan Province, China. Endogenous and exogenous activation were distinguished by WGS of the pathogen. The average concentration of air pollution was estimated by considering a lag of 0-1 to 0-12 months. We applied a generalized additive model with a Poisson function to evaluate the relationships between ambient pollutants exposure and MTBMR.

RESULTS

In the single-pollutant adjusted models, the maximum effect for PM₁₀ (MTBMR increase: 81.87%, 95% CI: 38.38, 139.03) and PM_2.5 (MTBMR increase: 73.91%, 95% CI: 22.17, 147.55) was observed at a lag of 0-12 months for every 10 μg/m³ increase. For SO₂, the maximum effect was observed at lag 0-8 months, with MTBMR increasing by 128.06% (95% CI: 45.92, 256.44); and for NO₂, the maximum effect was observed at lag 0-9 months, with MTBMR increasing by 124.02% (95% CI: 34.5, 273.14). In contrast, the O₃ concentration was inversely associated with MTBMR, and the maximum reduction of MTBMR was 6.18% (95% CI: -9.24, -3.02) at a lag of 0-9 months. Similar results were observed for multi-pollutant models.

CONCLUSIONS

Increased exposure to ambient pollutants (PM₁₀, PM_2.5, SO₂, and NO₂) contributed to a faster MTBMR, indicating that MTB exhibits increased reproductive activity, thus accelerating within-host endogenous reactivation. O₃ exposure could decrease the MTBMR, suggesting that MTB exerts low reproductive activity by inhibiting within-host endogenous activation.

Tuberculosis Diagnoses Following Wildfire Smoke Exposure in California

Rationale: Wildfires are a significant cause of exposure to ambient air pollution in the United States and other settings. Although indoor air pollution is a known contributor to tuberculosis reactivation and progression, it is unclear whether ambient pollution exposures, including wildfire smoke, similarly increase risk. Objectives: To determine whether tuberculosis diagnosis was associated with recent exposure to acute outdoor air pollution events, including those caused by wildfire smoke. Methods: We conducted a case-crossover analysis of 6,238 patients aged ⩾15 years diagnosed with active tuberculosis disease between 2014 and 2019 in 8 California counties. Using geocoded address data, we characterized individuals' daily exposure to <2.5 μm-diameter particulate matter (PM_2.5) during counterfactual risk periods 3-6 months before tuberculosis diagnosis (hazard period) and the same time 1 year previously (control period). We compared the frequency of residential PM_2.5 exposures exceeding 35 μg/m³ (PM_2.5 events) overall and for wildfire-associated and nonwildfire events during individuals' hazard and control periods. Measurements and Main Results: In total, 3,139 patients experienced 1 or more PM_2.5 events during the hazard period, including 671 experiencing 1 or more wildfire-associated events. Adjusted odds of tuberculosis diagnosis increased by 5% (95% confidence interval, 3-6%) with each PM_2.5 event experienced over the 6-month observation period. Each wildfire-associated PM_2.5 event was associated with 23% (19-28%) higher odds of tuberculosis diagnosis in this time window, whereas no association was apparent for nonwildfire-associated events. Conclusions: Residential exposure to wildfire-associated ambient air pollution is associated with an increased risk of active tuberculosis diagnosis.

Ambient PM2.5 exposures could increase risk of tuberculosis recurrence

BACKGROUND

The effect of ambient PM2.5 on the incidence of tuberculosis (TB) has been investigated in epidemiological studies. However, they did not separately study new and relapsed TB infection and focused on relatively short-term effects of PM2.5. In this regard, we examined the associations of long-term PM2.5 exposures with both new and relapsed TB incidences in South Korea, where the disease burden of TB is greatest among high-income countries.

METHODS

An area-level ecological study of 250 districts was conducted from 2015 to 2019. Age- and sex-standardized TB incidence ratios for each district and year were used as outcome variables, and their associations with PM2.5 concentrations for one to five-year average were examined. Negative binomial regression models incorporating spatiotemporal autocorrelation were employed using integrated nested Laplace approximations. Stratified analyses were conducted by type of TB (total, new, and relapsed cases).

RESULTS

Districts with higher PM2.5 concentrations tended to have significantly higher TB recurrence rate. The relative risks per 10 µg/m3 PM2.5 increase were 1.218 (95% credible interval 1.051-1.411), 1.260 (1.039-1.527) and 1.473 (1.015-2.137) using the two, three and five-year average PM2.5 exposures, respectively.

CONCLUSIONS

The results imply that interventions for reducing air pollution might help prevent TB recurrence.

Long-term exposure to ambient air pollution and greenness in relation to pulmonary tuberculosis in China: A nationwide modelling study

Previous studies have attempted to clarify the relationship between the occurrence of pulmonary tuberculosis (PTB) and exposure to air pollutants. However, evidence from multi-centres, particularly at the national level, is scarce, and no study has examined the modifying effect of greenness on air pollution-TB associations. In this study, we examined the association between long-term exposure to ambient air pollutants (PM₁₀ p.m._2.5, and O₃) and monthly PTB or smear-positive pulmonary tuberculosis (SPPTB) incidence to further evaluate whether these associations were affected by greenness in mainland China using a two-stage analytic procedure. PM_2.5 was positively associated with both PTB and SPPTB incidence, with relative risk (RR) of 1.12 (95% confidence interval [CI]: 1.03, 1.22) and 1.08 (95% CI: 1.02, 1.10) per 10 μg/m³ increase, respectively. Furthermore, PM₁₀ was positively associated with PTB incidence, with RR of 1.07 (95% CI: 1.01, 1.13). However, O₃ was not associated with the monthly incidence of PTB or SPPTB. The normalized difference vegetation index (NDVI) exhibited a modifying effect on the association between PM_2.5 exposure and SPPTB incidence in northern areas, with RR of 1.16 (95% CI: 1.03, 1.31) in lower mean annual NDVI areas than in the higher areas (RR = 0.98, 95% CI: 0.87, 1.09). This nationwide analysis indicated that NDVI could reduce the effect of air pollutants on TB incidence particularly in the northern areas. Long-term exposure to particulate matter (PM) may increase the occurrence of PTB or SPPTB in China, and further studies involving larger numbers of SPPTB cases are required to confirm the effects of PM exposure on SPPTB incidence in the future.

Impact of the synergistic effect of pneumonia and air pollutants on newly diagnosed pulmonary tuberculosis in southern Taiwan

BACKGROUND

An increased incidence of pulmonary tuberculosis (PTB) among patients with pulmonary diseases exposed to air pollution has been reported.

OBJECTIVE

To comprehensively investigate the association between pneumonia (PN) and air pollution with PTB through a large-scale follow-up study.

METHODS

We conducted a retrospective study using data from the Kaohsiung Medical University Hospital Research Database and the Taiwan Air Quality Monitoring Database. We included adult patients with PN, PTB and other comorbidities according to ICD-9 codes. Control subjects without PN were matched by age, sex and ten comorbidities to each PN patient at a ratio of 4:1.

RESULTS

A total of 82,590 subjects were included. The PTB incidence rate was significantly higher in the PN group (2,391/100,000) than in the control group (1,388/100,000). The crude hazard ratio (HR) of PN-associated PTB incidence decreased with time, and the overall 7 years the HR (95% confidence interval; CI) was 1.74 (1.55-1.96). The overall adjusted HR and 95% CI of PN-related PTB in the multivariate Cox regression analysis was 3.38 (2.98-3.84). In addition, there was a cumulative lag effect of all air pollutants within 30 days of exposure. The peak adjusted HRs for PTB were noted on the 3rd, 8th, 12th and 12th days of PM_2.5, O₃, SO₂ and NO exposure, respectively. The overall peak HRs (95% CI) of PM_2.5, O₃, SO₂ and NO were 1.145 (1.139-1.152), 1.153 (1.145-1.161), 1.909 (1.839-1.982) and 1.312 (1.259-1.367), respectively, and there was a synergistic effect with pneumonia on the risk of PTB.

CONCLUSIONS

A strong association was found between past episodes of PN and the future risk of PTB. In addition, air pollutants including PM_2.5, SO₂, O₃ and NO, together with previous episodes of PN, had both long-term and short-term impact on the incidence of PTB.

Lagged Effects of Exposure to Air Pollutants on the Risk of Pulmonary Tuberculosis in a Highly Polluted Region

BACKGROUND

Although significant correlations have been observed between air pollutants and the development of pulmonary tuberculosis (PTB) in many developed countries, data are scarce for developing and highly polluted regions.

METHOD

A combined Poisson generalized linear regression-distributed lag nonlinear model was used to determine the associations between long-term exposure (2005-2017) to air pollutants and the risk of PTB in the Beijing-Tianjin-Hebei region.

RESULTS

The monthly PTB cases exhibited a fluctuating downward trend. For each 10 μg/m3 increase in concentration, the maximum lag-specific risk and cumulative relative risk (RR) were 1.011 (95% confidence interval (CI): 1.0091.012, lag: 3 months) and 1.042 (1.036-1.048, 5 months) for PM2.5, and 1.023 (1.015-1.031, 0 months) and 1.041 (1.026-1.055, 2 months) for NO2. The risk of PTB was negatively correlated with O3 exposure, and the minimum lag-specific risk and cumulative RR were 0.991 (95% CI: 0.987-0.994, lag: 0 months) and 0.974 (0.968-0.981, 4 months), respectively. No age-dependent effects were observed.

CONCLUSIONS

Our results revealed potential associations between outdoor exposure to PM2.5, NO2, and O3 and the risk of PTB. Further research should explore the corresponding interactions and potential mechanisms.

Modeling and Predicting Pulmonary Tuberculosis Incidence and Its Association with Air Pollution and Meteorological Factors Using an ARIMAX Model: An Ecological Study in Ningbo of China

The autoregressive integrated moving average with exogenous regressors (ARIMAX) modeling studies of pulmonary tuberculosis (PTB) are still rare. This study aims to explore whether incorporating air pollution and meteorological factors can improve the performance of a time series model in predicting PTB. We collected the monthly incidence of PTB, records of six air pollutants and six meteorological factors in Ningbo of China from January 2015 to December 2019. Then, we constructed the ARIMA, univariate ARIMAX, and multivariate ARIMAX models. The ARIMAX model incorporated ambient factors, while the ARIMA model did not. After prewhitening, the cross-correlation analysis showed that PTB incidence was related to air pollution and meteorological factors with a lag effect. Air pollution and meteorological factors also had a correlation. We found that the multivariate ARIMAX model incorporating both the ozone with 0-month lag and the atmospheric pressure with 11-month lag had the best performance for predicting the incidence of PTB in 2019, with the lowest fitted mean absolute percentage error (MAPE) of 2.9097% and test MAPE of 9.2643%. However, ARIMAX has limited improvement in prediction accuracy compared with the ARIMA model. Our study also suggests the role of protecting the environment and reducing pollutants in controlling PTB and other infectious diseases.

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

There is growing evidence that air pollution plays a role in TB, and most studies have been conducted in the core countries with inconsistent results. Few studies have comprehensively included the six common air pollutants, so they cannot consider whether various pollutants interact with each other. 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, 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 the Poisson generalized linear regression model and distributed lag non-linear model (DLNM). We performed stratified analyses for the season, type of cases, 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; PM_2.5 (RR = 1.0018, 95% CI: 1.0004-1.0032, delay of 12 days) and SO₂ (RR = 1.0169, 95% CI: 1.0007-1.0333, lag 0-16 days) were 0.9549 (95% CI: 0.9389-0.9712, lag 0 day) and 0.8212 (95% CI: 0.7351-0.9173, 0-20-day lag). Stratified analyses showed that seasonal differences had a greater impact on TB, males were more likely to develop TB than females, older people were more likely to develop TB than younger people, and air pollution had a great impact on new cases. Exposure to O₃, CO, PM₁₀, PM_2.5, and NO₂ increases the risk of TB outpatient visits, except SO₂ which reduces the risk. The incidence of TB has seasonal fluctuations. It is necessary for the government to establish a sound environmental monitoring and early warning system to strengthen the monitoring and emission management of pollutants in the atmosphere. Management, prevention, and treatment measures should be developed for high-risk groups (males and older people), reducing the risk of TB by reducing their specific behaviors and changing their lifestyle. We need to pay more attention to the impact of seasonal effects on TB to protect TB patients and avoid a shortage of medical resources, and it is necessary for the government to develop some seasonal preventive measures in the future.

Association of long-term exposure to ambient air pollution with the number of tuberculosis cases notified: a time-series study in Hong Kong

To analyze the association of long-term exposure to air pollution and its attributable risks with the number of tuberculosis (TB) cases notified, a quasi-Poisson regression model combined with a distributed lag nonlinear model (DLNM) was constructed using monthly data on air pollution and TB cases notified in Hong Kong from 1999 to 2018. Nonlinear relationships between PM₁₀, PM_2.5, and CO and TB cases notified were identified. The concentrations of PM₁₀, PM_2.5, and CO corresponding to the minimum numbers of TB cases notified (the minimum TB notification concentrations, MTNCs) were 58.3 μg/m³, 41.7 μg/m³, and 0.1 mg/m³, respectively. Compared with the MTNCs, the overall cumulative numbers of TB cases notified increased by 76.93% (95% CI: 13.08%, 176.83%), 88.81% (95% CI: 26.09%, 182.71%), and 233.43% (95% CI: 13.56%, 879.03%) for the 95th percentiles of PM₁₀ and PM_2.5 and for the 97.5th percentiles of CO, respectively. The TB notification rate attributed to concentration ranges above the 97.5th percentile of PM₁₀, PM_2.5, and CO was 3.38% (95% empirical confidence intervals [eCI]: 0.93%, 5.61%), 4.73% (95% eCI: 1.87%, 7.15%), and 3.34% (95% eCI: 0.29%, 5.83%), respectively. Long-term exposure to high concentrations of air pollution in Hong Kong may be associated with increases in the number of TB cases notified for this area.

Associations between lung-deposited dose of particulate matter and culture-positive pulmonary tuberculosis pleurisy

Epidemiological studies identified the relationship between air pollution and pulmonary tuberculosis. Effects of lung-deposited dose of particulate matter (PM) on culture-positive pulmonary tuberculosis remain unclear. This study investigates the association between lung-deposited dose of PM and pulmonary tuberculosis pleurisy. A case-control study of subjects undergoing pleural effusion drainage of pulmonary tuberculosis (case) and chronic heart failure (control) was conducted. Metals and biomarkers were quantified in the pleural effusion. The air pollution exposure was measured and PM deposition in the head, tracheobronchial, alveolar region, and total lung region was estimated by Multiple-path Particle Dosimetry (MPPD) Model. We performed multiple logistic regression to examine the associations of these factors with the risk of tuberculosis. We observed that 1-μg/m³ increase in PM₁₀ was associated with 1.226-fold increased crude odds ratio (OR) of tuberculosis (95% confidence interval (CI): 1.023-1.469, p<0.05), 1-μg/m³ increase in PM_2.5-10 was associated with 1.482-fold increased crude OR of tuberculosis (95% CI: 1.048-2.097, p < 0.05), 1-ppb increase in NO₂ was associated with 1.218-fold increased crude OR of tuberculosis (95% CI: 1.025-1.447, p < 0.05), and 1-ppb increase in O₃ was associated with 0.735-fold decreased crude OR of tuberculosis (95% CI: 0.542 0.995). We observed 1-μg/m³ increase in PM deposition in head and nasal region was associated with 1.699-fold increased crude OR of tuberculosis (95% CI: 1.065-2.711, p < 0.05), 1-μg/m³ increase in PM deposition in tracheobronchial region was associated with 1.592-fold increased crude OR of tuberculosis (95% CI: 1.095-2.313, p < 0.05), 1-μg/m³ increase in PM deposition in alveolar region was associated with 3.981-fold increased crude OR of tuberculosis (95% CI: 1.280-12.386, p < 0.05), and 1-μg/m³ increase in PM deposition in total lung was associated with 1.511-fold increased crude OR of tuberculosis (95% CI: 1.050-2.173, p < 0.05). The results indicate that particle deposition in alveolar region could cause higher risk of pulmonary tuberculosis pleurisy than deposition in other lung regions.

Ambient air pollutants, diabetes and risk of newly diagnosed drug-resistant tuberculosis

BACKGROUND

Drug-resistant tuberculosis (DR-TB), diabetes and exposure to air pollution are thought to be important threat to human health, but no studies have explored the effects of ambient air pollutants on DR-TB when adjusting diabetes status so far.

METHODS

We performed a study among 3759 newly diagnosed TB cases with drug-susceptibility testing results, diabetes status, and individual air pollution data in Shandong from 2015 to 2019. Generalized linear mixed models (GLMM) including three models (Model 1: without covariates, Model 2: adjusted by diabetes status only, Model 3: with all covariates) were applied.

RESULTS

Of 3759 TB patients enrolled, 716 (19.05%) were DR-TB, and 333 (8.86%) had diabetes. High exposure to O₃ was associated with an increased risk of RFP-resistance (Model 2 or 3: odds ratio (OR) = 1.008, 95% confidence intervals (CI): 1.002-1.014), ethambutol-resistance (Model 3: OR = 1.015, 95%CI: 1.004-1.027) and any rifampicin+streptomycin resistance (Model 1,2,3: OR = 1.01, 95%CI: 1.002-1.018) at 90 days. In contrast, NO₂ was associated with a reduced risk of DR-TB (Model 3: OR = 0.99, 95%CI: 0.981-0.999) and multidrug-resistant TB (MDR-TB) (Model 3: OR = 0.977, 95%CI: 0.96-0.994) at 360 days. Additionally, SO₂ (Model 1, 2, 3: OR = 0.987, 95%CI: 0.977-0.998) showed a protective effect on MDR-TB at 90 days. PM_2.5 (90 days, Model 2: OR = 0.991, 95%CI: 0.983-0.999), PM₁₀ (360 days, Model 2: OR = 0.992, 95%CI: 0.985-0.999) had protective effects on any RFP+SM resistance.

CONCLUSIONS

O₃ contributed to an elevated risk of TB resistance but PM_2.5, PM₁₀, SO₂, NO₂ showed an inverse effect. Air pollutants may affect the development of drug resistance among TB cases by adjusting the status of diabetes.

Association between ambient air pollution and tuberculosis risk: A systematic review and meta-analysis

There is a growing body of evidence suggesting an association between air pollution exposure and tuberculosis (TB) incidence, but no meta-analysis has assembled all evidence so far. This review and meta-analysis aimed to derive a more reliable estimation on the association between air pollution and TB incidence. PubMed, Embase and Web of Science electronic databases were systemically searched for eligible literature. The PECO framework was used to form the eligibility criteria. Effect estimates and 95% confidence intervals (CIs) published in the included studies were pooled quantitatively. Seventeen articles met the inclusion criteria. The pooled estimates showed that long-term exposure to particulate matter with an aerodynamic diameter ≤10 μm (PM₁₀) was associated with increased incidence of TB (per 10 μg/m³ increase in concentrations of PM₁₀: risk ratios (RR) = 1.058, 95% CI: 1.021-1.095). Besides, long-term exposure to sulfur dioxide (SO₂) and nitrogen dioxide (NO₂) were significantly associated with TB incidence (per 1 ppb increase, SO₂: RR = 1.016, 95% CI: 1.001-1.031; NO₂: 1.010, 95% CI: 1.002-1.017). We did not find a significant association of PM_2.5, ozone (O₃) or carbon monoxide (CO) with TB risk, regardless of long-term or short-term exposure. However, in view of the 2016 ASA Statement and the biological plausibility of PM_2.5 damaging host immunity, the association between PM_2.5 and TB risk remains to be further established. This meta-analysis shows that long-term exposure to PM₁₀, SO₂ or NO₂ is associated with increased odds of TB, and the specific biological mechanisms warrant further research.

Epidemiological characteristics of tuberculosis and effects of meteorological factors and air pollutants on tuberculosis in Shijiazhuang, China: A distribution lag non-linear analysis

BACKGROUND

Tuberculosis (TB) is a serious public health problem in China. There is evidence to prove that meteorological factors and exposure to air pollutants have a certain impact on TB. But the evidence of this relationship is insufficient, and the conclusions are inconsistent.

METHODS

Descriptive epidemiological methods were used to describe the distribution characteristics of TB in Shijiazhuang in the past five years. Through the generalized linear regression model (GLM) and the generalized additive model (GAM), the risk factors that affect the incidence of TB are screened. A combination of GLM and distribution lag nonlinear model (DLNM) was used to evaluate the lag effect of environmental factors on the TB. Results were tested for robustness by sensitivity analysis.

RESULTS

The incidence of TB in Shijiazhuang showed a downward trend year by year, with seasonality and periodicity. Every 10 μg/m³ of PM₁₀ changes, the RR distribution is bimodal. The first peak of RR occurs on the second day of lag (RR = 1.00166, 95% CI: 1.00023, 1.00390); the second risk period starts from 13th day of lag and peaks on15th day (RR = 1.00209, 95% CI: 1.00076, 1.00341), both of which are statistically significant. The cumulative effect of increasing 10 μg/m³ showed a similar bimodal distribution. Time zones where the RR makes sense are days 4-6 and 13-20. RR peaked on the 18th day (RR = 1.02239, 95% CI: 1.00623, 1.03882). The RR has a linear relationship with the concentration. Under the same concentration, the RR peaks within 15-20 days.

CONCLUSION

TB in Shijiazhuang City showed a downward trend year by year, with obvious seasonal fluctuations. The air pollutant PM₁₀ increases the risk of TB. The development of TB has a short-term lag and cumulative lag effects. We should focus on protecting susceptible people from TB in spring and autumn, and strengthen the monitoring and emission management of PM₁₀ in the atmosphere.

The relationship between seasonality, latitude and tuberculosis notifications in Pakistan

Background

Pakistan ranks amongst the top 20 highest burden tuberculosis (TB) countries in the world. Approximately 369,548 cases of TB (all forms) were notified in 2018, with an estimated incidence of 265 per 100,000 people per year. In other settings, TB has been shown to demonstrate seasonal variation, with higher incidence in the spring/summer months and lower incidence in the autumn/winter; the amplitude of seasonal variation has also been reported to be higher with increasing distance from the equator.

Methods

Notifications of newly-diagnosed pulmonary and extrapulmonary TB cases were obtained for 139 districts in Pakistan from 2011 to 2017. Data were provided by the Pakistan National TB Control Programme, Islamabad, Pakistan. Statistical analyses were performed to determine whether there was seasonal variation in TB notifications in Pakistan; whether the amplitude of seasonal variation in TB notifications varied according to latitude; whether the amplitude of seasonal variation of TB in Pakistan differed between extrapulmonary TB vs. pulmonary TB. To assess the quarterly seasonality of TB, we used the X-13-ARIMA-SEATS seasonal adjustment programme from the United States Census Bureau. The mean difference and corresponding 95% confidence intervals of seasonal amplitudes between different latitudes and clinical phenotype of TB were estimated using linear regression.

Results

TB notifications were highest in quarter 2, and lowest in quarter 4. The mean amplitude of seasonal variation was 25.5% (95% CI 25.0 to 25.9%). The mean seasonal amplitude of TB notifications from latitude 24.5°N- < 26.5°N was 29.5% (95% CI 29.3 to 29.7%) whilst the mean seasonal amplitude of TB notifications from latitude 34.5°N - < 36.5°N was 21.7% (95% CI 19.6 to 23.9%). The mean seasonal amplitude of TB notifications across Pakistan between latitudes 24.5°N to 36.5°N reached statistically significant difference (p < 0.001). The amplitude of seasonal variation was greater for extrapulmonary TB (mean seasonal amplitude: 32.6, 95% CI 21.4 to 21.8%) vs. smear positive pulmonary TB mean seasonal amplitude: 21.6, 95% CI 32.1 to 33.1%), p < 0.001.

Conclusion

TB notifications in Pakistan exhibit seasonal variation with a peak in quarter 2 (April–June) and trough in quarter 4 (October–December). The amplitude of seasonality decreases with increasing latitude, and is more pronounced for extrapulmonary than for pulmonary TB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-05899-x.

Mechanistic Implications of Biomass-Derived Particulate Matter for Immunity and Immune Disorders

Particulate matter (PM) is a major and the most harmful component of urban air pollution, which may adversely affect human health. PM exposure has been associated with several human diseases, notably respiratory and cardiovascular diseases. In particular, recent evidence suggests that exposure to biomass-derived PM associates with airway inflammation and can aggravate asthma and other allergic diseases. Defective or excess responsiveness in the immune system regulates distinct pathologies, such as infections, hypersensitivity, and malignancies. Therefore, PM-induced modulation of the immune system is crucial for understanding how it causes these diseases and highlighting key molecular mechanisms that can mitigate the underlying pathologies. Emerging evidence has revealed that immune responses to biomass-derived PM exposure are closely associated with the risk of diverse hypersensitivity disorders, including asthma, allergic rhinitis, atopic dermatitis, and allergen sensitization. Moreover, immunological alteration by PM accounts for increased susceptibility to infectious diseases, such as tuberculosis and coronavirus disease-2019 (COVID-19). Evidence-based understanding of the immunological effects of PM and the molecular machinery would provide novel insights into clinical interventions or prevention against acute and chronic environmental disorders induced by biomass-derived PM.

Tuberculosis incidence in area with sulfur dioxide pollution: an observation

Tuberculosis is an important public health problem that needs good control. The interrelationship between air pollution and incidence of tuberculosis is interesting. In the present report, the authors report the observation on tuberculosis incidence in area with sulfur dioxide pollution. The retrospective analysis on public available on incidence of tuberculosis and ambient air sulfur dioxide level in Thailand is done. There is no significant relationship between air sulfur dioxide level and corresponding incidence of tuberculosis (r = –0.224, P = 0.535). In conclusion, there is a lack of association between air sulfur dioxide level and corresponding incidence of tuberculosis in our setting.

Ambient air pollution and respiratory bacterial infections, a troubling association: epidemiology, underlying mechanisms, and future challenges

The World Health Organization attributed more than four million premature deaths to ambient air pollution in 2016. Numerous epidemiologic studies demonstrate that acute respiratory tract infections and exacerbations of pre-existing chronic airway diseases can result from exposure to ambient (outdoor) air pollution. In this context, the atmosphere contains both chemical and microbial pollutants (bioaerosols), whose impact on human health remains unclear. Therefore, this review: summarises the findings from recent studies on the association between exposure to air pollutants-especially particulate matter and ozone-and onset or exacerbation of respiratory infections (e.g. pneumonia, cystic fibrosis lung infection, and tuberculosis); discusses the mechanisms underlying the relationship between air pollution and respiratory bacterial infections, which is necessary to define prevention and treatment strategies; demonstrates the relevance of air pollution modelling in investigating and preventing the impact of exposure to air pollutants on human health; and outlines future actions required to improve air quality and reduce morbidity and mortality related to air pollution.

Association Between Ambient Air Pollution and Elevated Risk of Tuberculosis Development

Background

Broad-scale evidence has shown the significant association between ambient air pollutants and the development of tuberculosis (TB). However, the impact of air quality on the risk of TB in Taiwan is still poorly understood.

Objective

To develop a probabilistic integrated population-level risk assessment approach for evaluating the contribution of ambient air pollution exposure to the risk of TB development among different regions of Taiwan.

Materials and methods

A Bayesian-based probabilistic risk assessment model was implemented to link exposure concentrations of various air pollutants quantified in a probabilistic manner with the population-based exposure-response models developed by using an epidemiological investigation.

Results

The increment of the risk of TB occurred in a region with a higher level of air pollution, indicating a strong relationship between ambient air pollution exposures and TB incidences. Carbon monoxide (CO) exposure showed the highest population attributable fraction (PAF), followed by nitrogen oxides (NO_X) and nitrogen dioxide (NO₂) exposures. In a region with higher ambient air pollution, it is most likely (80% risk probability) that the contributions of CO exposure to development of TB were 1.6–12.2% (range of median PAFs), whereas NO_X and NO₂ exposures contributed 1.2–9.8% to developing TB.

Conclusion

Our findings provide strong empirical support for the hypothesis and observations from the literature that poor air quality is highly likely to link aetiologically to the risk of TB. Therefore, substantial reductions in CO, NO_X, and NO₂ exposures are predicted to have health benefits to susceptible and latently infected individuals that provide complementary mitigation efforts in reducing the burden of TB. Considering that people continue to be exposed to both TB bacilli and ambient air pollutants, our approach can be applied for different countries/regions to identify which air pollutants contribute to a higher risk of TB in order to develop potential mitigation programs.