Particulate air pollution and susceptibility to the development of pulmonary tuberculosis disease in North Carolina: an ecological study

Long-term exposure to ambient fine particulate matter (PM2.5) and attributable pulmonary tuberculosis notifications in Ningxia Hui Autonomous Region, China: a health impact assessment

INTRODUCTION

Long-term exposure to fine particulate matter (≤2.5 µm (PM2.5)) has been associated with pulmonary tuberculosis (TB) notifications or incidence in recent publications. Studies quantifying the relative contribution of long-term PM2.5 on TB notifications have not been documented. We sought to perform a health impact assessment to estimate the PM2.5- attributable TB notifications during 2007-2017 in Ningxia Hui Autonomous Region (NHAR), China.

METHODS

PM2.5 attributable TB notifications were estimated at township level (n=358), stratified by age group and summed across NHAR. PM2.5-associated TB-notifications were estimated for total and anthropogenic PM2.5 mass and expressed as population attributable fractions (PAFs). The main analysis used effect and uncertainty estimates from our previous study in NHAR, defining a counterfactual of the lowest annual PM2.5 (30 µg/m3) level, above which we assumed excess TB notifications. Sensitivity analyses included counterfactuals based on the 5th (31 µg/m3) and 25th percentiles (38 µg/m3), and substituting effect estimates from a recent meta-analysis. We estimated the influence of PM2.5 concentrations, population growth and baseline TB-notification rates on PM2.5 attributable TB notifications.

RESULTS

Over 2007-2017, annual PM2.5 had an estimated average PAF of 31.2% (95% CI 22.4% to 38.7%) of TB notifications while the anthropogenic PAF was 12.2% (95% CI 9.2% to 14.5%). With 31 and 38 µg/m3 as counterfactuals, the PAFs were 29.2% (95% CI 20.9% to 36.3%) and 15.4% (95% CI 10.9% to 19.6%), respectively. PAF estimates under other assumptions ranged between 6.5% (95% CI 2.9% to 9.6%) and 13.7% (95% CI 6.2% to 19.9%) for total PM2.5, and 2.6% (95% CI 1.2% to 3.8%) to 5.8% (95% CI 2.7% to 8.2%) for anthropogenic PM2.5. Relative to 2007, overall changes in PM2.5 attributable TB notifications were due to reduced TB-notification rates (-23.8%), followed by decreasing PM2.5 (-6.2%), and population growth (+4.9%).

CONCLUSION

We have demonstrated how the potential impact of historical or hypothetical air pollution reduction scenarios on TB notifications can be estimated, using public domain, PM2.5 and population data. The method may be transferrable to other settings where comparable TB-notification data are available.

A systematic review and meta-analysis of the association between air pollutants and the incidence of tuberculosis

Objective

To investigate the association between air pollutants and the incidence of tuberculosis (TB) through a systematic review and meta-analysis, and to provide directions for future research and prevention of TB.

Methods

A search was conducted for all literature related to the incidence of TB and air pollution in the database. We screened the retrieved articles and proceeded statistical analyses using random effects models to investigate the relationships between five air pollutants (PM2.5, PM10, SO2, NO2 and O3) and the incidence of TB.

Results

The initial search identified 100 pieces of literature and 9 studies met the screening criteria after the screening. The single-day lagged risk ratio (RR) and 95% Confidence Intervals (CIs) for the combined effects estimates are as follows: PM2.5: 1.059 (0.966, 1.160); PM10: 1.000 (0.996, 1.004); SO2: 0.980 (0.954, 1.007); NO2: 1.011 (0.994, 1.027); O3: 0.994 (0.980,1.008). The cumulative lagged results for these five pollutants are listed like this: PM2.5: 1.095 (0.983, 1.219); PM10: 1.035 (1.006, 1.066); SO2: 0.964 (0.830, 1.121); NO2: 1.037 (1.010, 1.065); O3: 0.982 (0.954, 1.010).

Conclusion

The single-day lag effects of PM2.5, PM10, SO2, NO2, and O3 are not statistically significantly relevant for the occurrence of TB. However, the cumulative lag results show that both PM10 and NO2 contribute to the prevalence of TB, while the statistical relationship between the cumulative lag effects of PM2.5, SO2, and O3 and the onset of TB remains unknown.

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.

Spatio-Temporal Pattern of Tuberculosis Distribution in Romania and Particulate Matter Pollution Associated With Risk of Infection

The study proposes a dynamic spatio-temporal profile of the distribution of tuberculosis incidence and air pollution in Romania, where this infectious disease induces more than 8,000 new cases annually. The descriptive analysis for the years 2012-2021 assumes an identification of the structuring patterns of mycobacterium tuberculosis risk in the Romanian population, according to gender and age, exploiting spatial modeling techniques of time series data. Through spatial autocorrelation, the degree of similarity between the analyzed territorial systems was highlighted and the relationships that are built between the analysis units in spatial proximity were investigated. By modeling the geographical distribution of tuberculosis, the spatial correlation with particulate matter (PM2.5) pollution was revealed. The identification of clusters of infected persons is an indispensable step in the construction of efficient tuberculosis management systems. The results highlight the link between the distribution of tuberculosis, air pollution and socio-economic development, which requires a detailed analysis of the epidemiological data obtained in the national tuberculosis surveillance and control program from the perspective of geographical distribution.

Impact of diesel exhaust particles on infections with Mycobacterium bovis BCG in in vitro human macrophages and an in vivo Galleria mellonella model

There are strong suggestions for a link between pulmonary tuberculosis (TB) and air quality. Diesel exhaust is one of the main contributors to pollution and it is reported to be able to modify susceptibility to lung infections. In this study we exposed THP-1 human macrophages and Mycobacterium bovis BCG to diesel exhaust particles (DEPs). High cytotoxicity and activation of apoptosis was found in THP-1 cells at 3 and 6 days, but no effect was found on the growth of M. bovis BCG. Infection of THP-1 cells exposed to a non-cytotoxic DEP concentration showed a limited capacity to engulf latex beads. However, M. bovis BCG infection of macrophages did not result in an increase in the bacterial burden, but it did result in an increase in the bacteria recovered from the extracellular media, suggesting a poor contention of M. bovis BCG. We also observed that DEP exposure limited the production of cytokines. Using the Galleria mellonella model of infection, we observed that larvae exposed to low levels of DEPs were less able to survive after infection with M. bovis BCG and had a higher internal bacterial load after 4 days of infection. Unraveling the links between air pollution and impairment of human antimycobacterial immunity is vital, because pollution is rapidly increasing in areas where TB incidence is extremely high.

Short-term effects of high-resolution (1-km) ambient PM2.5 and PM10 on hospital admission for pulmonary tuberculosis: a case-crossover study in Hainan, China

Introduction

There is limited evidence regarding particulate matter (PM)'s short-term effects on pulmonary tuberculosis (PTB) hospital admission. Our study aimed to determine the short-term associations of the exposure to ambient PM with aerodynamic diameters <2.5 μm (PM2.5) and < 10 μm (PM10) with hospital admission for PTB in Hainan, a tropical province in China.

Methods

We collected individual data on patients hospitalized with PTB, PM2.5, PM10, and meteorological data from 2016 to 2019 in Hainan Province, China. Conditional logistic regression models with a time-stratified case-crossover design were used to assess the short-term effects of PM2.5 and PM10 on hospital admission for PTB at a spatial resolution of 1 km  ×  1 km. Stratified analyses were performed according to age at admission, sex, marital status, administrative division, and season of admission.

Results

Each interquartile range (IQR) increases in the concentrations of PM2.5 and PM10 were associated with 1.155 (95% confidence interval [CI]: 1.041-1.282) and 1.142 (95% CI: 1.033-1.263) hospital admission risks for PTB at lag 0-8 days, respectively. The stratified analyses showed that the effects of PM2.5 and PM10 were statistically significant for patients aged ≥65 years, males, married, and those residing in prefecture-level cities. Regarding seasonal differences, the associations between PM and hospital admission for PTB were statistically significant in the warm season but not in the cold season. The effect of PM2.5 was consistently stronger than that of PM10 in most subgroups.

Conclusion

Short-term exposure to PM increases the risk of hospital admission for PTB. The potential impact of PM with smaller aerodynamic diameter is more detrimental. Our findings highlight the importance of reducing ambient PM level to alleviate the burden of PTB.

Effect of gaseous pollutant and greenness exposure on mortality during treatment of newly treated tuberculosis patients: a provincial population-based cohort study

BACKGROUND

Previous studies addressing the impact of environmental factors on TB prognosis are scarce, with only some studies examining the effect of particulate pollutants on TB mortality. Moreover, few studies have evaluated the effects of multiple gaseous pollutants and greenness exposures on newly treated TB patients on a large population scale.

METHODS

Through the Centers for Disease Control and Prevention, data were collected from January 1, 2015 to December 31, 2020 for newly treated TB patients in Anhui Province, China. Data on gaseous pollutants sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone were collected through the National Earth System Science Data Center of China. Normalized vegetation index data were obtained through NASA. The Cox proportional risk model was also applied to calculate the hazard ratios of SO2, NO2, CO, O3, and NDVI with 95% confidence intervals for mortality among newly treated TB patients.

RESULTS

Multifactorial Cox regression analysis showed that for every 0.10 μg/m3 increase in SO2, the risk of death among newly treated TB patients increased by 13.2% (HR = 1.132, 95% CI: 1.045-1.1.225), for every 10 μg/m3 increase in NO2, the risk of death among newly treated TB patients increased by 11.4%, and for each 0.1 mg/m3 increase in CO, the risk of death among newly treated TB patients increased by 5.8%. For each 0.1 increase in NDVI 250m-buffer and 500m-buffer, the risk of death among newly treated TB patients decreased by 8.5% and 6.4%, respectively. The effect of gaseous pollutants on mortality decreased progressively with elevated greenness exposure when greenness exposure was grouped from low to high.

CONCLUSION

Gaseous pollutants are a risk factor during the treatment of newly treated TB patients and greenness exposure is a protective factor. Higher greenness exposure reduces the risk of death due to exposure to gaseous pollutants.

Influential factors of tuberculosis in mainland China based on MGWR model

Tuberculosis (TB), as a respiratory infectious disease, has damaged public health globally for decades, and mainland China has always been an area with high incidence of TB. Since the outbreak of COVID-19, it has seriously occupied medical resources and affected medical treatment of TB patients. Therefore, the authenticity and reliability of TB data during this period have also been questioned by many researchers. In response to this situation, this paper excludes the data from 2019 to the present, and collects the data of TB incidence in mainland China and the data of 11 influencing factors from 2014 to 2018. Using spatial autocorrelation methods and multiscale geographically weighted regression (MGWR) model to study the temporal and spatial distribution of TB incidence in mainland China and the influence of selected influencing factors on TB incidence. The experimental results show that the distribution of TB patients in mainland China shows spatial aggregation and spatial heterogeneity during this period. And the R2 and the adjusted R2 of MGWR model are 0.932 and 0.910, which are significantly better than OLS model (0.466, 0.429) and GWR model (0.836, 0.797). The fitting accuracy indicators MAE, MSE and MAPE of MGWR model reached 5.802075, 110.865107 and 0.088215 respectively, which also show that the overall fitting effect is significantly better than OLS model (19.987574, 869.181549, 0.314281) and GWR model (10.508819, 267.176741, 0.169292). Therefore, this model is based on real and reliable TB data, which provides decision-making references for the prevention and control of TB in mainland China and other countries.

Moderating the role of social progress with greenhouse gases to determine the health vulnerability in developing countries

Human activities have compelled massive environmental degradation, which causes climate vulnerability and that has emerged as a significant health issue. The present study assesses the role of social progress with greenhouse gases to determine the health vulnerability in 77 developing countries from 2011 to 2020. The empirical results are estimated by using the panel ARDL econometric approach. The study found that greenhouse gas emission proposes a U-shaped relationship to determine health vulnerability. In this study, social progress is used as the moderator variable, which shifts the turning point of the U-shaped curve. For this purpose, the interaction term of social progress with greenhouse gases shifts the turning point to the left side of the U-shaped curve and further flattens it. Furthermore, this study explores that urbanization, export openness, and government education expenditure negatively impact health vulnerability while industrialization increases health vulnerability. The study recommends that government should pay special attention to declining greenhouse gases and rising social progress to improve health vulnerability.Graphical abstact.

Human exposure risk assessment for infectious diseases due to temperature and air pollution: an overview of reviews

Air pollution and global temperature change are expected to affect infectious diseases. Air pollution usually causes inflammatory response and disrupts immune defense system, while temperature mainly exacerbates the effect of vectors on humans. Yet to date overview of systematic reviews assessing the exposure risk of air pollutants and temperature on infectious diseases is unavailable. This article aims to fill this research gap. PubMed, Embase, the Cochrane Library, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature were searched. Systematic reviews and meta-analyses investigated the exposure risk of pollutants or temperature on infectious diseases were included. Two investigators screened literature, extracted data and performed the risk of bias assessments independently. A total of 23 articles met the inclusion criteria, which 3 (13%) were "low" quality and 20 (87%) were "critically low" quality. COVID-19 morbidity was associated with long-term exposure PM2.5 (RR = 1.056 per 1 [Formula: see text], 95% CI: 1.039-1.072) and NO2 (RR = 1.042 per 1 [Formula: see text], 95% CI: 1.017-1.068). In addition, for each 1 °C increase in temperature, the morbidity risk of dengue increased 13% (RR = 1.130 per 1 °C, 95% CI: 1.120-1.150), infectious diarrhea increased 8% (RR = 1.080 per 1 °C, 95% CI: 1.050-1.200), and hand, foot and mouth disease (HFMD) increased 5% (RR = 1.050 per 1 °C, 95% CI: 1.020-1.080). In conclusion, PM2.5 and NO2 increased the risk of COVID-19 and temperatures were associated with dengue, infectious diarrhoea and HFMD morbidity. Moreover, the exposure risk of temperature on COVID-19 was recommended to be further explored.

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.

Spatial-temporal analysis of pulmonary tuberculosis among students in the Zhejiang Province of China from 2007-2020

Background

Pulmonary tuberculosis (PTB) is a serious chronic communicable disease that causes a significant disease burden in China; however, few studies have described its spatial epidemiological features in students.

Methods

Data of all notified PTB cases from 2007 to 2020 in the student population were collected in the Zhejiang Province, China using the available TB Management Information System. Analyses including time trend, spatial autocorrelation, and spatial-temporal analysis were performed to identify temporal trends, hotspots, and clustering, respectively.

Results

A total of 17,500 PTB cases were identified among students in the Zhejiang Province during the study period, accounting for 3.75% of all notified PTB cases. The health-seeking delay rate was 45.32%. There was a decreasing trend in PTB notifications throughout the period; clustering of cases was seen in the western area of Zhejiang Province. Additionally, one most likely cluster along with three secondary clusters were identified by spatial-temporal analysis.

Conclusion

Although was a downward trend in PTB notifications among students during the time period, an upward trend was seen in bacteriologically confirmed cases since 2017. The risk of PTB was higher among senior high school and above than of junior high school. The western area of Zhejiang Province was the highest PTB risk settings for students, and more comprehensive interventions should be strengthened such as admission screening and routine health monitoring to improve early identification of PTB.

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.

Effects of long-term ambient air pollution exposure on township-level pulmonary tuberculosis notification rates during 2005-2017 in Ningxia, China

Studies examining long-term effects of ambient air pollution exposure, measured as annual averages, on pulmonary tuberculosis (TB) incidence are scarce, particularly in endemic, rural settings. We performed a small-area study in Ningxia Hui Autonomous Region (NHAR), a high TB-burden area in rural China, using township-level (n = 358 non-overlapping townships) annual TB notification data (2005-2017). We aimed to determine if annual average concentrations of ambient air pollution (particulate matter <2·5 μm [PM_2·5], nitrogen dioxide [NO₂] ozone [O₃]) were associated with TB notification rates (as a proxy for incidence). Air pollution effects on TB notification rates at township-level were estimated as incidence rate ratios (IRR), fitted using a generalised estimating equation (GEE) adjusted for covariates (age, sex, occupation, education, ethnicity, remoteness [urban or rural], household crowding and solid fuel use). A total of 38,942 TB notifications were reported in NHAR between 2005 and 2017. The mean annual TB notification rate was 67 (standard deviation [SD]; 7) per 100,000 people. Median concentrations of PM_2·5, NO₂, and O₃ were 42 μg/m³ (interquartile range [IQR]; 38-48 μg/m³), 15 ppb (IQR; 12-16 ppb), and 56 ppb (IQR; 56-57 ppb), respectively. In single pollutant models, adjusted for covariates, an interquartile range (IQR) increase (10 μg/m³) in PM_2·5 was significantly associated with higher TB notification rates (IRR: 1∙35; 95% CI: 1·25-1·48). Comparable effects on notifications of TB were observed for increases in NO₂ exposure (IRR: 1·20 per IQR (4 ppb) increase; 95% CI: 1·08-1·31). Ground-level ozone was not associated with TB notification rate in any models. The observed effects were consistent over time, in multi-pollutant models, and appeared robust to additional adjustment for indicators of household crowding, solid fuel use and remoteness. More rigorous study designs are needed to understand if improving air quality has population-level benefits on TB disease incidence in endemic settings.

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.

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.

Pivotal role of environmental toxicants on developing infectious diseases in LMICs: a protocol for a systematic review and meta-analysis

INTRODUCTION

Environmental toxicants such as chemical pollution have an enormous impact on the health of people and the planet. Emerging findings suggest that non-communicable diseases are linked to early and chronic environmental exposures. However, the rapid globalisation in developing countries, environmental change and the emergence, spread, persistence and severity of infectious diseases are not yet well understood. The aim of this study is to understand which environmental toxicants are commonly associated with infectious diseases in low-income and middle-income countries (LMICs).

METHODS AND ANALYSIS

A total of four electronic databases, MEDLINE through PubMed, Scopus, Web of Science and CENTRAL (the Cochrane Library) be searched to identify relevant studies and will be screened by two independent reviewers. The Cochrane risk of bias (ROB) tool for randomised control trials (RCTs) and ROB assessment tool for non-randomised studies for non-RCTs will be used to assess the ROB. A meta-analysis will be used to determine the pooled effect if we find out the included articles have similar environmental exposure, participant groups, study design and outcome measures. A narrative synthesis of the findings will be provided, along with summaries of the intervention effect. Heterogeneity between the studies will be assessed, and sensitivity analysis will be conducted based on study quality.

ETHICS AND DISSEMINATION

Findings will be summarised in a single manuscript. This review attempts to explore the pivotal role of environmental toxicants in predisposing, developing, persistent and severity of infectious diseases in LMICs. Findings from this study will highlight the effects of individual environmental toxicants' role on infectious disease outcomes for the early prevention and limit toxic exposure to guide individual, community, and occupational health policy for future strategies.

PROSPERO REGISTRATION NUMBER

CRD42021274359.

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

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 PM_2.5, 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 PM_2.5 (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 PM_2.5, 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.

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.

Study on the Associations between Meteorological Factors and the Incidence of Pulmonary Tuberculosis in Xinjiang, China

Pulmonary tuberculosis (PTB) has been a major threat to global public health. The association between meteorological factors and the incidence of PTB has been widely investigated by the generalized additive model, auto-regressive integrated moving average model and the distributed lag model, etc. However, these models could not address a non-linear or lag correlation between them. In this paper, a penalized distributed lag non-linear model, as a generalized and improved one, was applied to explore the influence of meteorological factors (such as air temperature, relative humidity and wind speed) on the PTB incidence in Xinjiang from 2004 to 2019. Moreover, we firstly use a comprehensive index (apparent temperature, AT) to access the impact of multiple meteorological factors on the incidence of PTB. It was found that the relationships between air temperature, relative humidity, wind speed, AT and PTB incidence were nonlinear (showed “wave-type “, “invested U-type”, “U-type” and “wave-type”, respectively). When air temperature at the lowest value (−16.1 °C) could increase the risk of PTB incidence with the highest relative risk (RR = 1.63, 95% CI: 1.21–2.20). An assessment of relative humidity demonstrated an increased risk of PTB incidence between 44.5% and 71.8% with the largest relative risk (RR = 1.49, 95% CI: 1.32–1.67) occurring at 59.2%. Both high and low wind speeds increased the risk of PTB incidence, especially at the lowest wind speed 1.4 m/s (RR = 2.20, 95% CI: 1.95–2.51). In particular, the lag effects of low and high AT on PTB incidence were nonlinear. The lag effects of extreme cold AT (−18.5 °C, 1st percentile) on PTB incidence reached a relative risk peak (RR = 2.18, 95% CI: 2.06–2.31) at lag 1 month. Overall, it was indicated that the environment with low air temperature, suitable relative humidity and wind speed is more conducive to the transmission of PTB, and low AT is associated significantly with increased risk of PTB in Xinjiang.

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.

PM2.5 mediated alterations in the in vitro human granuloma and its effect on reactivation of mycobacteria

Exposure to particulate matter pollutant PM_2.5 diminishes the immune response to mycobacterial antigens relevant to contain the infection in the granuloma, thus leading to reactivation of latent bacilli. The present study was therefore designed based on the hypothesis that exposure to PM_2.5 affects the granuloma formation and reactivation of latent mycobacterial bacilli contained in the granuloma. For the sampling of PM_2.5, based on initial standardisations, Teflon filter was selected over the quartz filter. Two different approaches were used to study the effect of PM_2.5 on the human PBMC granuloma formed by Mycobacterium bovis BCG at multiplicity of infection (MOI) 0.1. In the first approach, granuloma formed in the presence of PM_2.5 was loosely packed and ill-defined with significant downregulation of dormancy-associated mycobacterial genes, upregulation of reactivation-associated rpfB gene along with a significant increase in TNFα level without any change in the bacterial load in terms of CFUs. In the second approach, preformed human PBMC granuloma using M. bovis BCG was treated with PM_2.5 that resulted in the disruption of granuloma architecture along with downregulation of not only dormancy-associated genes but also reactivation-associated rpfB gene of mycobacterial bacilli recovered from granuloma. However, there was no significant change in the host cytokine levels. Therefore, it can be inferred that PM_2.5 can modulate the granuloma formation in vitro as well as mycobacterial gene expression in the granuloma with a possible role in the reactivation of latent bacilli.

Short-term effects of ambient air pollution and meteorological factors on tuberculosis in semi-arid area, northwest China: a case study in Lanzhou

To investigate the short-term effects of ambient air pollution and meteorological factors on daily tuberculosis (TB), semi-parametric generalized additive model was used to assess the impacts of ambient air pollutants and meteorological factors on daily TB case from 2005 to 2010 in Chengguan District, Lanzhou, China. Then a non-stratification parametric model and a stratification parametric model were applied to study the interactive effect of air pollutants and meteorological factors on daily TB. The results show that sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter with aerodynamic diameter less than 10μm (PM₁₀) were positively correlated with daily TB case; the excess risk (ER) and 95% confidence interval (CI) were 1.79% (0.40%, 3.20%), 3.86% (1.81%, 5.96%), and 0.32% (0.02%, 0.62%), respectively. Daily TB case was positively correlated with maximum temperature, minimum temperature, average temperature, vapor pressure, and relative humidity, but negatively correlated with atmospheric pressure, wind speed, and sunshine duration. The association with average temperature was the strongest, whose ER and 95% CI were 4.43% (3.15%, 5.72%). In addition, there were significant interaction effects between air pollutants and meteorological factors on daily TB case.

Effect of ambient air pollution on tuberculosis risks and mortality in Shandong, China: a multi-city modeling study of the short- and long-term effects of pollutants

Few studies conducted in China have assessed the effects of ambient air pollution exposure on tuberculosis (TB) risk and mortality, especially with a multicity setting. We evaluated the effect of short- and long-term ambient sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and particulate matter≤2.5 μm in aerodynamic diameter (PM_2.5) exposures on development and mortality of active TB in 7 Chinese cities in Shandong province from January 1, 2013, to December 31, 2017. We estimated the pollution-associated risk to new infection TB, recurrent TB, and mortality in relation to 1-μg/m³ increases in air pollutants using the penalized multivariate Poisson regression models. A total of 83,555 new infective TB and 3060 recurrent TB including 997 deaths were recorded. Short- and long-term exposures to outdoor air pollutants (SO₂, NO₂, CO, O₃, and PM_2.5) were significantly associated with new infection TB, recurrent TB risk, and mortality. The dominant positive effects of SO₂, NO₂, CO, and PM_2.5 for new infection and recurrent TB risk were observed at long-term (>30 days) exposure, whereas the dominant effects of SO₂, CO, and PM_2.5 for mortality were observed at short-term (≤30 days) exposures. Of the 5 air pollutants we assessed, SO₂ and PM_2.5 exhibited more consistent and strong associations with TB-related outcomes. We estimated an increase of 1.33% (95% CI 1.29%, 1.37%) and 3.04% (95% CI 2.98%, 3.11%) in new infection TB count for each 1-μg/m³ increase of SO₂ at lag 0-180 days and PM_2.5 at lag 0-365 days, respectively. This epidemiologic study in China shows that air pollution exposure is associated with increased risk of active TB development and mortality. The control of ambient air pollution may benefit the control and decrease the mortality of TB disease.

Long-term exposure to indoor air pollution and risk of tuberculosis

Indoor air pollution (IAP) is a recognized risk factor for various diseases. This paper examines the role of indoor solid fuel exposure in the risk of mycobacterium tuberculosis (TB) in Delhi Metropolitan, India. Using a cross-sectional design, subjects were screened for a history of active TB and lifelong exposure to IAP sources, such as solid fuel burning and kerosene. The TB prevalence rate in the study area was 1117 per 100 000 population. Every year, increase in solid fuel exposure was associated with a three percent higher likelihood of a history of active TB. Subjects exposed to solid fuel and kerosene use for both heating home and cooking showed significant associations with TB. Age, household expenditure (a proxy of income), lung function, and smoking also showed significant associations with TB. Smokers and solid fuel-exposed subjects were four times more likely to have a history of active TB than non-smoker and unexposed subjects. These finding calls strategies to mitigate solid fuel exposure, such as use of clean cookstove and ventilation, to mitigate the risk of TB which aligns with the United Nations' goal of "End TB by 2030."

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.

Spatial modeling of individual-level infectious disease transmission: Tuberculosis data in Manitoba, Canada

Geographically dependent individual level models (GD-ILMs) are a class of statistical models that can be used to study the spread of infectious disease through a population in discrete-time in which covariates can be measured both at individual and area levels. The typical ILMs to illustrate spatial data are based on the distance between susceptible and infectious individuals. A key feature of GD-ILMs is that they take into account the spatial location of the individuals in addition to the distance between susceptible and infectious individuals. As a motivation of this article, we consider tuberculosis (TB) data which is an infectious disease which can be transmitted through individuals. It is also known that certain areas/demographics/communities have higher prevalent of TB (see Section 4 for more details). It is also of interest of policy makers to identify those areas with higher infectivity rate of TB for possible preventions. Therefore, we need to analyze this data properly to address those concerns. In this article, the expectation conditional maximization algorithm is proposed for estimating the parameters of GD-ILMs to be able to predict the areas with the highest average infectivity rates of TB. We also evaluate the performance of our proposed approach through some simulations. Our simulation results indicate that the proposed method provides reliable estimates of parameters which confirms accuracy of the infectivity rates.

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.

A Scoping Review on Air Quality Monitoring, Policy and Health in West African Cities

Ambient air pollution is a global health threat that causes severe mortality and morbidity from respiratory, cardiovascular, and other diseases. Its impact is especially concerning in cities; as the urban population increases, especially in low- and middle-income countries, large populations risk suffering from these health effects. The Economic Community of West African States (ECOWAS) comprises 15 West African countries, in which many cities are currently experiencing fast growth and industrialization. However, government-led initiatives in air quality monitoring are scarce in ECOWAS countries, which makes it difficult to effectively control and regulate air quality and subsequent health issues. A scoping study was performed following the Arksey and O’Malley methodological framework in order to assess the precise status of air quality monitoring, related policy, and legislation in this region. Scientific databases and gray literature searches were conducted, and the results were contrasted through expert consultations. It was found that only two ECOWAS countries monitor air quality, and most countries have insufficient legislation in place. Public health surveillance data in relation to air quality data is largely unavailable. In order to address this, improved air quality surveillance, stricter and better-enforced regulations, regional cooperation, and further research are strongly suggested for ECOWAS.

Associations of ambient air pollutants with regional pulmonary tuberculosis incidence in the central Chinese province of Hubei: a Bayesian spatial-temporal analysis

BACKGROUND

Air pollution and pulmonary tuberculosis (PTB) are still serious worldwide problems, especially in areas of developing countries. Whether there is an association between high ambient air pollutant concentrations and PTB has not been fully explored.

METHODS

Bayesian spatial-temporal models were constructed to analyse the association between ambient air pollutants (particulate matter with aerodynamic diameters of ≤10 μm (PM₁₀), sulfur dioxide (SO₂) and nitrogen dioxide (NO₂)) and PTB incidence, adjusting for socioeconomic covariates. We collected data on pulmonary TB, ambient air pollution (PM₁₀, SO₂ and NO₂) concentrations and socioeconomic covariates from 17 prefectures in the central Chinese province of Hubei between Jan 1, 2006, and Dec 31, 2015.

RESULTS

For every annual 10 μg/m³ increase in SO₂, the relative risk (RR) of PTB incidence was 1.046 (95% credible interval [CI], 1.038-1.054) in the study area. Moreover, we found positive associations with each annual 10 μg/m³ increase in ambient air pollutants (PM₁₀, SO₂ and NO₂) in females but only with SO₂ in males. A significant association for each 10 μg/m³ increase in SO₂ was observed in all the age groups, with a significant association for PM₁₀ only in children under 14 years of age. A significant response relationship was also observed at a 0-1 month moving average lag for each 10 μg/m³ increase in SO₂.

CONCLUSIONS

High ambient air pollution concentrations in areas of developing countries might increase the risk of regional PTB incidence, especially for women and young people. Precautions and protective measures and efforts to reduce ambient air pollutant concentrations should be strengthened in developing countries.

Spatio-temporal co-occurrence of hotspots of tuberculosis, poverty and air pollution in Lima, Peru

Growing evidence suggests pollution and other environmental factors have a role in the development of tuberculosis (TB), however, such studies have never been conducted in Peru. Considering the association between air pollution and specific geographic areas, our objective was to determine the spatial distribution and clustering of TB incident cases in Lima and their co-occurrence with clusters of fine particulate matter (PM2.5) and poverty. We found co-occurrences of clusters of elevated concentrations of air pollutants such as PM2.5, high poverty indexes, and high TB incidence in Lima. These findings suggest an interplay of socio-economic and environmental in driving TB incidence.

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

OBJECTIVES

Epidemiological evidence of associations between ambient particulate matter (PM) and tuberculosis (TB) risk is accumulating. Two previous studies in Korea found associations between air pollution—especially sulfur dioxide (SO₂)—and TB. In this study, we conducted an annual time-series cross-sectional study to assess the effect of PM with an aerodynamic diameter less than 10 μm (PM₁₀) on TB risk in seven major cities of Korea from 2010 to 2016, taking into account time lag and long-term cumulative exposure.

METHODS

Age-standardized TB notification rates were derived using the Korea National TB Surveillance System. Annual average PM₁₀ concentrations were obtained from annual Korean air quality reports. We applied a generalized linear mixed model with unconstrained distributed lags of exposure to PM₁₀. We adjusted for potential confounders such as age, health behaviors, and area-level characteristics.

RESULTS

Both average annual PM₁₀ concentrations and age-standardized TB notification rates decreased over time. The association between cumulative exposure to PM₁₀ and TB incidence became stronger as a longer exposure duration was considered. An increase of one standard deviation (5.63 μg/m³) in PM₁₀ exposure for six years was associated with a 1.20 (95% confidence interval, 1.17 to 1.22) times higher TB notification rate. The marginal association of exposure duration with the TB notification rate was highest at four and five years prior to TB notification. This association remained consistent even after adjusting it for exposure to SO₂.

CONCLUSIONS

The findings of this study suggest that cumulative exposure to PM₁₀ may affect TB risk, with a potential lag effect.

Short-term Effect of Air Pollution on Tuberculosis Based on Kriged Data: A Time-series Analysis

Tuberculosis (TB) has a very high mortality rate worldwide. However, only a few studies have examined the associations between short-term exposure to air pollution and TB incidence. Our objectives were to estimate associations between short-term exposure to air pollutants and TB incidence in Wuhan city, China, during the 2015–2016 period. We applied a generalized additive model to access the short-term association of air pollution with TB. Daily exposure to each air pollutant in Wuhan was determined using ordinary kriging. The air pollutants included in the analysis were particulate matter (PM) with an aerodynamic diameter less than or equal to 2.5 micrometers (PM_2.5), PM with an aerodynamic diameter less than or equal to 10 micrometers (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ground-level ozone (O₃). Daily incident cases of TB were obtained from the Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Both single- and multiple-pollutant models were used to examine the associations between air pollution and TB. Seasonal variation was assessed by splitting the all-year data into warm (May–October) and cold (November–April) seasons. In the single-pollutant model, for a 10 μg/m³ increase in PM_2.5, PM₁₀, and O₃ at lag 7, the associated TB risk increased by 17.03% (95% CI: 6.39, 28.74), 11.08% (95% CI: 6.39, 28.74), and 16.15% (95% CI: 1.88, 32.42), respectively. In the multi-pollutant model, the effect of PM_2.5 on TB remained statistically significant, while the effects of other pollutants were attenuated. The seasonal analysis showed that there was not much difference regarding the impact of air pollution on TB between the warm season and the cold season. Our study reveals that the mechanism linking air pollution and TB is still complex. Further research is warranted to explore the interaction of air pollution and TB.

Nonrenewable energy-environmental and health effects on human capital: empirical evidence from Pakistan

This research work reconnoiters the impact of nonrenewable energy (NRE) consumptions, environmental pollution, and mortality rate on human capital in the presence of economic growth and two common diseases, measles and tuberculosis (TB) in Pakistan. The study uses data from 1995 to 2017 and employs the Autoregressive Distributive Lag (ARDL) model to investigate cointegration and long-run dynamics. Results indicate that nonrenewable energy (oil, coal, and gas) increase air pollution, measles, TB cases, and mortality rate, which affect the human capital in Pakistan. The results of the ARDL confirm the long-run and short-run effects of fossils fuels, air pollution, and diseases on human capital. The results of the Granger Causality confirm the feedback hypothesis between nonrenewable consumption and human capital, between air pollution and human capital. Measles and TB diseases Granger cause human capital. The study recommends some essential points for energy management, environmental management, and diseases control programs to uplift the human capital in Pakistan.

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.

Association of social deprivation and outdoor air pollution with pulmonary tuberculosis in spatiotemporal analysis

The objective of this study was to identify the association between social deprivation, outdoor air pollution, and tuberculosis (TB) incidence rate or mortality rate. The study sample comprised 25 districts in Seoul, Korea. We used two public data derived from the Community Health Survey and Seoul Statistics. The geographic information system analysis and random effects Poisson regression were applied to explore the association of social deprivation and air pollution with TB incidence and mortality. An 1 ppb increase in sulfur dioxide (SO₂) concentration was significantly associated with the risk of TB incidence (risk ratio [RR] = 1.046, 95% confidence interval [CI]: 1.028, 1.065). An 1 unit increase in the deprivation index was significantly related to a6% increase in the mortality of TB (RR = 1.063, 95% CI: 1.031, 1.097). : Our results imply that social deprivation and air pollution may affect the different TB outcomes. Effective policy-making for TB control should reflect the differing outcomes between TB incidence and mortality.

The Effect of Treatment during A Haze/Post-Haze Year on Subsequent Respiratory Morbidity Status among Successful Treatment Tuberculosis Cases

The purpose of this study was to evaluate the respiratory morbidity status within the two to three years among successful (completed/cured) treatment of tuberculosis cases during a haze year (2015) and a post-haze year (2016). The study was conducted among 133 cases of a 2015 group and 103 cases of a 2016 group between January to March 2018 in Pekanbaru city, Indonesia. The St George Respiratory Questionnaire (SGRQ) was used to assess respiratory morbidity status. A higher score corresponds to worse respiratory morbidity. Based on a directed acyclic graph, quantile regression models were constructed to assess the associations between haze/post-haze year and the SGRQ (symptom, activity, impact, and total) domains score. The subsequent respiratory morbidity status of tuberculosis (TB) cases was poorer among respondents treated during a haze year (2015). Among SGRQ domains, only the activity domain score showed significant difference, in which the median for the 2015 group was 23.7 (inter-quartile range (IQR); 17.2, 30.9) compared to 18.4 (IQR; 11.9, 24.8) for the 2016 group. The effect was limited to the 2015 group who were exposed by an average PM₁₀ index ≥ 55 during TB treatment. This raises concern for monitoring and improving the quality of life of TB patients treated during a haze year.

Urban Air Pollution Particulates Suppress Human T-Cell Responses to Mycobacterium Tuberculosis

Tuberculosis (TB) and air pollution both contribute significantly to the global burden of disease. Epidemiological studies show that exposure to household and urban air pollution increase the risk of new infections with Mycobacterium tuberculosis (M.tb) and the development of TB in persons infected with M.tb and alter treatment outcomes. There is increasing evidence that particulate matter (PM) exposure weakens protective antimycobacterial host immunity. Mechanisms by which exposure to urban PM may adversely affect M.tb-specific human T cell functions have not been studied. We, therefore, explored the effects of urban air pollution PM_2.5 (aerodynamic diameters ≤2.5µm) on M.tb-specific T cell functions in human peripheral blood mononuclear cells (PBMC). PM_2.5 exposure decreased the capacity of PBMC to control the growth of M.tb and the M.tb-induced expression of CD69, an early surface activation marker expressed on CD3⁺ T cells. PM_2.5 exposure also decreased the production of IFN-γ in CD3⁺, TNF-α in CD3⁺ and CD14⁺ M.tb-infected PBMC, and the M.tb-induced expression of T-box transcription factor TBX21 (T-bet). In contrast, PM_2.5 exposure increased the expression of anti-inflammatory cytokine IL-10 in CD3⁺ and CD14⁺ PBMC. Taken together, PM_2.5 exposure of PBMC prior to infection with M.tb impairs critical antimycobacterial T cell immune functions.

Long-term effect of exposure to ambient air pollution on the risk of active tuberculosis

OBJECTIVES

To explore the long-term effect of exposure to ambient air pollution on the risk of active tuberculosis (TB).

METHODS

We constructed a distributed-lag nonlinear model (DLNM) to evaluate the relatively long-term influence of outdoor PM_2.5, PM₁₀, SO₂ and NO₂ exposure on active TB risk in the city of Lianyungang in Jiangsu Province, China.

RESULTS

There were 7,282 TB cases reported in the study area during 2014-2017, with annual median (interquartile range) concentrations of PM_2.5, PM₁₀, SO₂ and NO₂ at 45.86 (34.57-64.14) μg/m³, 85.43 (62.86-116.14) μg/m³, 22.00 (15.71-30.86) μg/m³ and 30.00 (23.29-38.57) μg/m³, respectively. The single-pollutant model showed that for each 10 μg/m³ increase in concentration, the cumulative relative risk of TB was 1.12 (lag 0-24 weeks, 95% CI: 1.03-1.22) for PM_2.5 with reference to 35 μg/m³; 1.11 (lag 0-21 weeks, 95% CI: 1.06-1.17) for PM₁₀ with reference to 70 μg/m³; 1.37 (lag 0-20 weeks, 95% CI: 1.16-1.62) for SO₂ with reference to 60 μg/m³; and 1.29 (lag 0-22 weeks, 95% CI: 1.11-1.49) for NO₂ with reference to 40 μg/m³. In the multipollutant model considering both PM₁₀ and NO₂, the association remained significant.

CONCLUSIONS

Our results revealed a potential association between outdoor exposure to PM_2.5, PM₁₀, SO₂, and NO₂ and active TB. Considering that people from developing countries continue to be exposed to both severe outdoor air pollution and high rates of latent TB infection, the association between worsening air pollution and active TB deserves further attention.

Association of air pollution with the risk of initial outpatient visits for tuberculosis in Wuhan, China

Objectives

Previous studies suggested the association of air pollution with initial Mycobacterium tuberculosis infection and the disease development. However, few studies have been conducted on air pollution and initial tuberculosis (TB) consults using short-interval data. We investigated the weekly association between air pollution and initial TB outpatient visits.

Methods

We used a Poisson regression model combined with a distributed lag non-linear model to conduct a time-series study with weekly air pollution data and TB cases during 2014–2017 in Wuhan, China.

Results

A 10 µg/m3 increase in NO2 (nitrogen dioxide) was associated with 11.74% (95% CI: 0.70 to 23.98, lag 0–1 weeks), 21.45% (95% CI: 1.44 to 45.41, lag 0–2 weeks) and 12.8% (95% CI: 0.97 to 26.02, lag 0–1 weeks) increase in initial TB consults among all patients with TB, old patients (≥60 years old) and male ones, respectively. A 10 µg/m3 increase in SO2 (sulfur dioxide) was associated with −22.23% (95% CI: −39.23 to −0.49, lag 0–16 weeks), −28.65% (95% CI: −44.3 to −8.58, lag 0–16 weeks), −23.85 (95% CI: −41.79 to −0.37, lag 0–8 weeks) and −23.82% (95% CI: −41.31 to −1.11, lag 0–16 weeks) increase in initial TB consults among the total, young (aged 15–59 years old), old and male patients, respectively. In old patients, a 0.1 mg/m3 increase in CO (carbon monoxide) and a 10 µg/m3 increase in PM2.5 (particulate matter) were separately associated with 42.32% (95% CI: 1.16 to 100.22, lag 0–16 weeks) and 17.38% (95% CI: 0.28 to 37.38, lag 0–16 weeks) increases in TB consults.

Conclusion

Our study first highlighted the importance of weekly association between air pollution and the risk of initial TB consults, which is helpful for the arrangements of TB screening and medical assistance.

Season and size of urban particulate matter differentially affect cytotoxicity and human immune responses to Mycobacterium tuberculosis

Exposure to air pollution particulate matter (PM) and tuberculosis (TB) are two of the leading global public health challenges affecting low and middle income countries. An estimated 4.26 million premature deaths are attributable to household air pollution and an additional 4.1 million to outdoor air pollution annually. Mycobacterium tuberculosis (M.tb) infects a large proportion of the world's population with the risk for TB development increasing during immunosuppressing conditions. There is strong evidence that such immunosuppressive conditions develop during household air pollution exposure, which increases rates of TB development. Exposure to urban air pollution has been shown to alter the outcome of TB therapy. Here we examined whether in vitro exposure to urban air pollution PM alters human immune responses to M.tb. PM2.5 and PM10 (aerodynamic diameters <2.5μm, <10μm) were collected monthly from rainy, cold-dry and warm-dry seasons in Iztapalapa, a highly populated TB-endemic municipality of Mexico City with elevated outdoor air pollution levels. We evaluated the effects of seasonality and size of PM on cytotoxicity and antimycobacterial host immunity in human peripheral blood mononuclear cells (PBMC) from interferon gamma (IFN-γ) release assay (IGRA)+ and IGRA- healthy study subjects. PM10 from cold-dry and warm-dry seasons induced the highest cytotoxicity in PBMC. With the exception of PM2.5 from the cold-dry season, pre-exposure to all seasonal PM reduced M.tb phagocytosis by PBMC. Furthermore, M.tb-induced IFN-γ production was suppressed in PM2.5 and PM10-pre-exposed PBMC from IGRA+ subjects. This observation coincides with the reduced expression of M.tb-induced T-bet, a transcription factor regulating IFN-γ expression in T cells. Pre-exposure to PM10 compared to PM2.5 led to greater loss of M.tb growth control. Exposure to PM2.5 and PM10 collected in different seasons differentially impairs M.tb-induced human host immunity, suggesting biological mechanisms underlying altered M.tb infection and TB treatment outcomes during air pollution exposures.

Ambient air pollution and health in Sub-Saharan Africa: Current evidence, perspectives and a call to action

BACKGROUND

People from low- and middle-income countries are disproportionately affected by the global burden of adverse health effects caused by ambient air pollution (AAP). However, data from Sub-Saharan Africa (SSA) are still scarce. We systematically reviewed the literature to describe the existing knowledge on AAP and health outcomes in SSA.

METHODS

We searched PubMed, Medline-OVID, EMBASE and Scopus databases to identify studies of AAP and health outcomes published up to November 15, 2017. We used a systematic review approach to critically analyze and summarize levels of outdoor air pollutants, and data on health effects associated with AAP. We excluded occupational and indoor exposure studies.

RESULTS

We identified 60 articles, with 37 only describing levels of AAP and 23 assessing the association between air pollution and health outcomes. Most studies (75%) addressing the relation between AAP and disease were cross-sectional. In general, exposure data were only obtained for selected cities in the framework of temporary international collaborative research initiatives without structural long-term continuation. Measurements of AAP revealed 10-20 fold higher levels than WHO standards. Of the 23 studies reporting health effects, 14 originated from South Africa, and most countries within SSA contributed no data at all. No studies, except from South Africa, were based on reliable morbidity or mortality statistics at regional or country level. The majority of studies investigated self-reported respiratory symptoms. Children and the elderly were found to be more susceptible to AAP.

CONCLUSION

AAP and its negative health effects have been understudied in SSA compared with other continents. The limited direct measurements of air pollutants indicate that AAP in SAA cities is high compared with international standards. Efforts are needed to monitor AAP in African cities, to identify its main sources, and to reduce adverse health effects by enforcing legislation.

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

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 μg/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 μg/m³ increment in O₃. PM_2.5 concentrations above 50 μg/m³, 70 μg/m³ for PM₁₀, 16 μg/m³ for SO₂, 47 μg/m³ for NO₂, 0.85 mg/m³ for CO, and 85 for AQI, and O₃ concentrations lower than 95 μg/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.

Air pollution inequality and health inequality in China: An empirical study

China's residents experience unequal exposure to air pollution in different regions, and the corresponding health consequences have increased remarkably. To ensure sustainable development, China should monitor health inequality and its potential determinants. This study empirically examines the health inequalities (represented by perinatal and tuberculosis mortalities) caused by air pollution inequalities (represented by SO₂ and NO_x emissions) from 31 Chinese provinces in the period 2006 to 2015, using the generalized method of moments (GMM) and quantile regression (QR). The GMM results reveal a strong positive relationship between SO₂/NO_x emission inequality and tuberculosis mortality inequality. In contrast, the QR results show that perinatal mortality inequality is closely related to emission inequality across all percentiles for SO₂ emission and at the 75th percentile for NO_x emission. Our findings help policymakers to identify health disparities and be mindful of air pollution inequality as a factor in the elimination of health inequality.

Risks of hospital admissions from a spectrum of causes associated with particulate matter pollution

Ambient particulate matter (PM) pollution has been linked to elevated hospital admissions (HAs), especially from respiratory and cardiovascular diseases. However, few studies have estimated the associations between PM pollution and HAs for a wider range of broad disease categories. This study aimed to evaluate the effects of PM with aerodynamic diameter ≤ 2.5 μm (PM_2.5) and ≤10 μm (PM₁₀) on a range of broad and specific causes of HAs in Chengdu, China during 2015-2016, using a generalized additive model (GAM). Age-, gender- and season-specific analyses were also performed on the broad categories. We further calculated the corresponding morbidity burden due to PM exposure. During the study period, the daily mean level for PM_2.5 and PM₁₀ was 57.3 μg/m³ and 94.7 μg/m³, respectively. For broad disease categories, each 10 μg/m³ increase in PM₁₀ at lag06 was associated with increments of 0.65% (95% CI: 0.32%-0.99%) in HAs from respiratory, 0.49% (95% CI: 0.04%-0.95%) from circulatory and 0.91% (95% CI: 0.15%-1.69%) from skin and subcutaneous tissue diseases. By contrast, only respiratory HAs showed a significant positive association with elevated PM_2.5 at lag06 (1.03% increase per 10 μg/m³, 95% CI: 0.50%-1.56%, p < 0.001). Increased HAs risks for several more refined specific causes within respiratory, circulatory, skin and subcutaneous tissue, nervous and genitourinary diseases were also observed. Subgroup analyses indicated that effect estimates were modified by age, gender and season. Overall, the largest morbidity burden was observed in myocardial infarction, about 11.27% (95% CI: 3.45%-18.07%) and 11.11% (95% CI: 4.07%-17.27%) of HAs for myocardial infarction could be attributable to PM_2.5 and PM₁₀ levels exceeding the WHO's air quality guidelines (24-h mean: 25 μg/m³ for PM_2.5 and 50 μg/m³ for PM₁₀). Our study suggests that both PM_2.5 and PM₁₀ increase risks of morbidity from broad range of causes of HAs in Chengdu, and result in substantial morbidity burden.

Association of childhood pulmonary tuberculosis with exposure to indoor air pollution: a case control study

Background

Crude measures of exposure to indicate indoor air pollution have been associated with the increased risk for acquiring tuberculosis. Our study aimed to determine an association between childhood pulmonary tuberculosis (PTB) and exposure to indoor air pollution (IAP), based on crude exposure predictors and directly sampled and modelled pollutant concentrations.

Methods

In this case control study, children diagnosed with PTB were compared to children without PTB. Questionnaires about children’s health; and house characteristics and activities (including household air pollution) and secondhand smoke (SHS) exposure were administered to caregivers of participants. A subset of the participants’ homes was sampled for measurements of PM₁₀ over a 24-h period (n = 105), and NO₂ over a period of 2 to 3 weeks (n = 82). IAP concentrations of PM₁₀ and NO₂ were estimated in the remaining homes using predictive models. Logistic regression was used to look for association between IAP concentrations, crude measures of IAP, and PTB.

Results

Of the 234 participants, 107 were cases and 127 were controls. Pollutants concentrations (μg/m³) for were PM₁₀ median: 48 (range: 6.6–241) and NO₂ median: 16.7 (range: 4.5–55). Day-to-day variability within- household was large. In multivariate models adjusted for age, sex, socioeconomic status, TB contact and HIV status, the crude exposure measures of pollution viz. cooking fuel type (clean or dirty fuel) and SHS showed positive non-significant associations with PTB. Presence of dampness in the household was a significant risk factor for childhood TB acquisition with aOR of 2.4 (95% CI: 1.1–5.0). The crude exposure predictors of indoor air pollution are less influenced by day-to-day variability. No risk was observed between pollutant concentrations and PTB in children for PM₁₀ and NO₂.

Conclusion

Our study suggests increased risk of childhood tuberculosis disease when children are exposed to SHS, dirty cooking fuel, and dampness in their homes. Yet, HIV status, age and TB contact are the most important risk factors of childhood PTB in this population.

A systematic literature review and critical appraisal of epidemiological studies on outdoor air pollution and tuberculosis outcomes

Ambient air pollution is the leading environmental risk factor for disease globally. Air pollutants can increase the risk of some respiratory infections, but their effects on tuberculosis (TB) are unclear. In this systematic literature review, we aimed to assess epidemiological studies on the association between outdoor air pollutants and TB incidence, hospital admissions and death (collectively referred to here as 'TB outcomes'). We sought to consolidate available evidence on this topic and propose recommendations for future studies. Following PRISMA guidelines, we searched PubMed, Web of Science, Google Scholar, and Scopus with no restrictions imposed on year of publication. A total of 11 epidemiological studies, performed in Asia, Europe and North America, met our inclusion criteria (combined sample size: 215,337 people). We extracted key study characteristics from each eligible publication, including design, exposure assessment, analytical approaches and effect estimates. The studies were assessed for overall quality and risk of bias using standard criteria. The pollutant most frequently associated with statistically significant effects on TB outcomes was fine particulate matter ( < 2.5 µm; PM_2.5); 6/11 studies assessed PM_2.5, of which 4/6 demonstrated a significant association). There was some evidence of significant associations between PM₁₀ ( < 10 µm), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) and TB outcomes, but these associations were inconsistent. The existing epidemiological evidence is limited and shows mixed results. However, it is plausible that exposure to air pollutants, particularly PM_2.5, may suppress important immune defence mechanisms, increasing an individual's susceptibility to development of active TB and TB-related mortality. Considering the small number of studies relative to the demonstrably large global health burdens of air pollution and TB, further research is required to corroborate the findings in the current literature. Based on a critical assessment of existing evidence, we conclude with methodological suggestions for future studies.

Ambient air pollution exposures and risk of drug-resistant tuberculosis

BACKGROUND

Few epidemiological studies have explored the effects of air pollution on the risk of drug-resistant tuberculosis (DR-TB).

OBJECTIVE

To investigate the short and long term residential concentrations of ambient air pollutants (particulate matter <10 μm in diameter (PM₁₀) and particulate matter≤2.5 μm in diameter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO)) in relation to the risk of DR-TB in a typical air pollution city, Jinan city, China.

METHODS

A total of 752 new culture-confirmed TB cases reported in TB prevention and control institutions of Jinan from January 1, 2014 to December 31, 2015 were included. Average individual-level concentrations of air pollution for 5 different exposure windows, vary from 90 days to 720 days to diagnosis were estimated using measurements from monitor closest to the patient home addresses. Logistic regression model adjusted for potential confounders was employed to evaluate correlation between air pollution and DR-TB risk at different five exposure windows individually.

RESULTS

There were substantially increased mono-drug resistance and poly-drug resistance risks for ambient PM_2.5, PM₁₀, O₃, and CO exposures. High exposure to PM_2.5, PM₁₀, and CO was also significantly associated with increased incidence of multi-drug resistance (MDR) both in the single- and multi-pollutants regression models. The dominant positive associations for PM_2.5was observed at 540 days exposure, for O₃ was observed at 180 days exposure, and for PM₁₀ and CO was observed from 90 days to 540 days exposures.

CONCLUSIONS

Our finding suggest that exposure to ambient air pollution (PM_2.5, PM₁₀, O₃, and CO) are associated with increased risk of DR-TB. We provided epidemiological evidence of association between pollution exposure and mono-, poly- and multi-drug resistance.

The association of household fine particulate matter and kerosene with tuberculosis in women and children in Pune, India

OBJECTIVES

Household air pollution (HAP) is a risk factor for respiratory disease, however has yet to be definitively associated with tuberculosis (TB). We aimed to assess the association between HAP and TB.

METHODS

A matched case-control study was conducted among adult women and children patients with TB and healthy controls matched on geography, age and sex. HAP was assessed using questionnaires for pollution sources and 24-hour household concentrations of particulate matter <2.5 μm in diameter (PM_2.5).

RESULTS

In total, 192 individuals in 96 matched pairs were included. The median 24-hour time-weighted average PM_2.5 was nearly seven times higher than the WHO's recommendation of 25 µg/m³, and did not vary between controls (179 µg/m³; IQR: 113-292) and cases (median 157 µg/m³; 95% CI 93 to 279; p=0.57). Reported use of wood fuel was not associated with TB (OR 2.32; 95% CI 0.65 to 24.20) and kerosene was significantly associated with TB (OR 5.49, 95% CI 1.24 to 24.20) in adjusted analysis. Household PM_2.5 was not associated with TB in univariate or adjusted analysis. Controlling for PM_2.5 concentration, kerosene was not significantly associated with TB, but effect sizes ranged from OR 4.30 (95% CI 0.78 to 30.86; p=0.09) to OR 5.49 (0.82 to 36.75; p=0.08).

CONCLUSIONS

Use of kerosene cooking fuel is positively associated with TB in analysis using reported sources of exposure. Ubiquitously high levels of particulates limited detection of a difference in household PM_2.5 between cases and controls.