Ambient air pollution and risk of tuberculosis: a cohort study

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.

Analyzing risk factors of tuberculosis using type-2 interval-valued trapezoidal fuzzy numbers with Einstein aggregation operators extended to MCDM

The principal motive of this work is to evolve and initiate an extension from interval-valued fuzzy sets to type-2 interval-valued fuzzy sets (T2IVFS) related to weighted aggregation functions containing the Einstein operator. The chief reason for this extension is that the constancy of the terms can also be taken into data during the aggregation operation. The main goal of this article is to compose the aggregation operators and their characteristics such as the Type-2 interval-valued fuzzy Einstein weighted arithmetic aggregating operator (T2IVFEWA), Type-2 interval-valued fuzzy Einstein weighted geometric aggregating operator (T2IVFEWG), and the characteristics are expressed. At last, to intimate the effectiveness of the suggested approach and explicate the purpose of these operators, a hybrid multi-criteria decision-making problem (MCDM) to select the best risk factor for Tuberculosis (TB) is considered and the result is compared with the outcome of the existing operators and methods. Additionally, a sensitivity analysis was conducted to verify the robustness of the proposed decision-making process.

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.

Particulate matter deposition and its impact on tuberculosis severity: A cross-sectional study in Taipei

The objective of this study was to examine the association between the lung lobe-deposited dose of inhaled fine particulate matter (PM2.5) and chest X-ray abnormalities in different lung lobes of pulmonary tuberculosis (TB), multidrug-resistant tuberculosis (MDR-TB), and non-tuberculosis mycobacteria infections (NTM). A cross-sectional study was conducted between 2014 and 2022, comprising 1073 patients who were recruited from chest department clinic in a tertial refer hospital in Taipei City, Taiwan. Ambient 1-, 7-, and 30-day PM2.5 exposure and the deposition of PM2.5 in different lung lobes were estimated in each subject. The β coefficient for PM2.5 and deposited PM2.5 in lungs with the outcome variables (pulmonary TB, MDR-TB, and NTM infection) was derived through regression analysis and adjusted for age, gender, BMI, smoking status, and family income. We observed that a 1 μg/m3 increase in ambient PM2.5 was associated with an increase of MDR-TB infections of 0.004 times (95%CI: 0.001-0.007). A 1 μg/m3 increase in 1-day and 7-day PM2.5 deposition in left upper lobe and left lower lobe was associated with an increase in chest X-ray abnormalities of 9.19 % and 1.18 % (95%CI: 0.87-17.51 and 95%CI: 0.08-2.28), and 4.52 % and 5.20 % (95%CI: 0.66-8.38 and 95%CI: 0.51-9.89) in left lung of TB patients, respectively. A 1 μg/m3 increase in 30-day PM2.5 deposition in alveolar region was associated with an increase in percent abnormality of 2.50 % (95%CI: 0.65-4.35) in left upper lobe and 3.33 % (95%CI: 0.65-6.01) in right middle lobe, while in total lung was 0.63 % (95%CI: 0.01-1.27) in right upper lobe and 0.37 % (95%CI, 0.06-0.81) in right lung of MDR-TB patients. Inhaled PM2.5 deposition in lungs was associated with an exacerbation of the radiographic severity of pulmonary TB, particularly in pulmonary MDR-TB patients in upper and middle lobes. Particulate air pollution may potentially exacerbate the radiographic severity and treatment resistance in individuals with pulmonary TB.

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.

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.

Associations between air pollutants and acute exacerbation of drug-resistant tuberculosis: evidence from a prospective cohort study

BACKGROUND

Short-term exposure to air pollution may trigger symptoms of drug-resistant tuberculosis (DR-TB) through stimulating lung tissue, damaging tracheobronchial mucosa, the key anti-mycobacterium T cell immune function, and production and release of inflammatory cytokines.

OBJECTIVE

To investigate the association between acute exacerbations of DR-TB and short-term residential exposure to air pollutants (PM10, PM2.5, SO2, NO2, CO and O3) based on a large prospective cohort in Anhui Province, China.

METHOD

Patients were derived from a prospective cohort study of DR-TB in Anhui Province. All DR-TB patients underwent drug-susceptibility testing and prefecture-level reference laboratories confirmed their microbiologies. The case-crossover design was performed to evaluate the association between the risk of acute exacerbations of DR-TB and short-term residential exposure to air pollution.

RESULTS

Short-term NO2 exposure was significantly related to an elevated risk of first-time outpatient visit due to acute exacerbations of DR-TB(relative risk:1.159, 95% confidence interval:1.011 ~ 1.329). Stratification analyses revealed that the relationship between the risk of acute exacerbations and NO2 exposure was stronger in the elderly (age ≥ 65) DR-TB patients, and in individuals with a history of TB treatment.

CONCLUSIONS

NO2 Exposure was significantly associated with an elevated risk of acute exacerbation of DR-TB in Anhui Province, China.

Global, regional and national trends in tuberculosis incidence and main risk factors: a study using data from 2000 to 2021

BACKGROUND

Despite the significant progress over the years, Tuberculosis remains a major public health concern and a danger to global health. This study aimed to analyze the spatial and temporal characteristics of the incidence of tuberculosis and its risk factors and to predict future trends in the incidence of Tuberculosis.

METHODS

This study used secondary data on tuberculosis incidence and tuberculosis risk factor data from 209 countries and regions worldwide between 2000 and 2021 for analysis. Specifically, this study analyses the spatial autocorrelation of Tuberculosis incidence from 2000 to 2021 by calculating Moran's I and identified risk factors for Tuberculosis incidence by multiple stepwise linear regression analysis. We also used the Autoregressive Integrated Moving Average model to predict the trend of Tuberculosis incidence to 2030. This study used ArcGIS Pro, Geoda and R studio 4.2.2 for analysis.

RESULTS

The study found the global incidence of Tuberculosis and its spatial autocorrelation trends from 2000 to 2021 showed a general downward trend, but its spatial autocorrelation trends remained significant (Moran's I = 0.465, P < 0.001). The risk factors for Tuberculosis incidence are also geographically specific. Low literacy rate was identified as the most pervasive and profound risk factor for Tuberculosis.

CONCLUSIONS

This study shows the global spatial and temporal status of Tuberculosis incidence and risk factors. Although the incidence of Tuberculosis and Moran's Index of Tuberculosis are both declining, there are still differences in Tuberculosis risk factors across countries and regions. Even though literacy rate is the leading risk factor affecting the largest number of countries and regions, there are still many countries and regions where gender (male) is the leading risk factor. In addition, at the current rate of decline in Tuberculosis incidence, the World Health Organization's goal of ending the Tuberculosis pandemic by 2030 will be difficult to achieve. Targeted preventive interventions, such as health education and regular screening of Tuberculosis-prone populations are needed if we are to achieve the goal. The results of this study will help policymakers to identify high-risk groups based on differences in TB risk factors in different areas, rationalize the allocation of healthcare resources, and provide timely health education, so as to formulate more effective Tuberculosis prevention and control policies.

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.

Regional and epidemiological characteristics of tuberculosis and treatment outcomes in West China

Objective

To understand the prevalence and treatment outcome of tuberculosis in a typically regional County from 2016 to 2021, so as to provide reference and basis for the prevention and treatment of tuberculosis in this area.

Methods

Descriptive epidemiological methods were used to analyze the population, time and location distribution of pulmonary tuberculosis in Dazhu County from 2016 to 2021. The incidence rates were compared by Chi-square test and trend test, time distribution combined with seasonal index analysis, and the test level was α = 0.05.

Results

A total of 2,899 cases of pulmonary tuberculosis were reported in Dazhu County from 2016 to 2021, with an average annual incidence rate of 44.29/100,000 and standardized reported incidence rate was 36.77/100,000, showing a downward trend year by year (χ2 trend = 124.629, p < 0.001). A total of 955 cases of pathogen positive were reported, showing an increasing trend year by year (χ2 trend = 59.773, p < 0.001). In terms of time distribution, the incidence rate was high in autumn and winter, and September and December were the peak of the disease in the whole year, and the overall trend increased first, then decreased and once again increased (F = 5.861, p < 0.05). In regional distribution, the highest annual average reported incidence rate was in concentrated population. The incidence rate of male was higher than female in population distribution. After standardization, the overall incidence rate increased from 34 to 45 years old (χ2 trend = 6963.101, p < 0.001), and decreased after 45 years old (χ2 trend = 1104.393, p < 0.001). The occupation distribution is mainly farmers (82.75%). The overall arrival rate and cure rate of patients showed an upward trend year by year (χ2 trend = 4.306, χ2 trend = 5.772, p < 0.001).

Conclusion

The incidence rate of pulmonary tuberculosis in this regional county is decreasing year by year. Male patients are higher than female patients and have certain seasonal characteristics. Attention should be paid to male, older adult, farmers and other groups, and corresponding measures should be taken to strengthen the prevention and treatment of tuberculosis in high incidence areas.

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.

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.

Association between long-term exposure to ambient air pollutants and the risk of tuberculosis: A time-series study in Nantong, China

Background

Increasing evidence has shown that the risk of tuberculosis (TB) might be related to the exposure to air pollutants; however, the findings are inconsistent and studies on long-term air pollutant exposure and TB risk are scarce. This study aime to assess the relationship between monthly exposure to air pollution and TB risk in Nantong, China.

Methods

We collected the time series data on the number of TB cases, as well as environmental and socioeconomic covariates from January 2005 to December 2020. The impact of air pollutant exposure on TB risk was evaluated using the distributed lag nonlinear model (DLNM). Stratified analyses were conducted to examine the effect modifications of sex and age on the association between air pollutants and TB risk. Sensitivity analyses were applied to test the stability of the model.

Results

There were a total of 54,096 cases of TB in Nantong during the study period. In the single-pollutant model, for each 10 μg/m³ increase in concentration, the pooled relative risks (RRs) of TB reached the maximum to 1.10 (95% confidence interval (CI): 1.04-1.16, lag 10 months) for particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5), 1.05 (95% CI: 1.01-1.10, lag 9 months) for particulate matter with aerodynamic diameter less than 10 μm (PM₁₀), and 1.11 (95%CI: 1.04-1.19, lag 10 months) for nitrogen dioxide (NO₂). Ozone (O₃) did not show significant effect on TB risk. Effect modifications of sex and age on the association between air pollutants and TB risk were not observed. The multi-pollutant model results showed no significant variation compared with the single-pollutant model.

Conclusions

Our study suggests that air pollutants pose a substantial threat to the TB risk. Reducing air pollution might be crucial for TB prevention and control.

Diabetes and obesity and risk of pyogenic liver abscess

Few literatures discussed the relationship of glycemic control and body mass index (BMI) with the risk of pyogenic liver abscess. We conducted a population-based cohort study using participants of a community-based health screening program in Taiwan from 2005 to 2008 (n = 125,865). Information on fasting plasma glucose (FPG), BMI, and other potential risk factors of liver abscess were collected at baseline. Incidence of pyogenic liver abscess was ascertained using inpatient records from the National Health Insurance database. During a median 8.6 years of followed up, 192 incident cases of pyogenic liver abscess were reported. The incidence rate of pyogenic liver abscess was 70.2 and 14.7 per 100,000 in the diabetic and non-diabetic population respectively. In multivariable Cox regression analysis, the adjusted hazard ratio (HR) was 2.18 (95% confidence interval (CI) 1.22-3.90) in patients with diabetes with good glycemic control (FPG ≤ 130 mg/dl) and 3.34 (95% CI 2.37-4.72) in those with poor glycemic control (FPG > 130 mg/dl), when compared with non-diabetics. In the dose-response analysis, the risk of liver abscess increased monotonically with increasing FPG. After adjusting for diabetes and other comorbidities, overweight (25 ≤ BMI < 30) (adjusted HR: 1.43, 95% CI 1.05-1.95) and obese (BMI ≥ 30) (adjusted HR: 1.75, 95% CI 1.09-2.81) populations had a higher risk of liver abscess when compared to people with normal weight. Diabetes, especially poorly controlled disease, and high BMI were associated with higher risk of pyogenic liver abscess. Improving glycemic control and weight reduction may reduce the risk of developing pyogenic liver abscess.

Long-term exposure to particulate matter on cardiovascular and respiratory diseases in low- and middle-income countries: A systematic review and meta-analysis

Background

Long-term exposure to particulate matter (PM) has essential and profound effects on human health, but most current studies focus on high-income countries. Evidence of the correlations between PM and health effects in low- and middle-income countries (LMICs), especially the risk factor PM1 (particles &lt; 1 μm in size), remains unclear.

Objective

To explore the effects of long-term exposure to particulate matter on the morbidity and mortality of cardiovascular and respiratory diseases in LMICs.

Methods

A systematic search was conducted in the PubMed, Web of Science, and Embase databases from inception to May 1, 2022. Cohort studies and case-control studies that examine the effects of PM1, PM2.5, and PM10 on the morbidity and mortality of cardiovascular and respiratory diseases in LMICs were included. Two reviewers independently selected the studies, extracted the data, and assessed the risk of bias. Outcomes were analyzed via a random effects model and are reported as the relative risk (RR) with 95% CI.

Results

Of the 1,978 studies that were identified, 38 met all the eligibility criteria. The studies indicated that long-term exposure to PM2.5, PM10, and PM1 was associated with cardiovascular and respiratory diseases: (1) Long-term exposure to PM2.5 was associated with an increased risk of cardiovascular morbidity (RR per 1.11 μg/m3, 95% CI: 1.05, 1.17) and mortality (RR per 1.10 μg/m3, 95% CI: 1.06, 1.14) and was significantly associated with respiratory mortality (RR 1.31, 95% CI: 1.25, 1.38) and morbidity (RR 1.08, 95% CI: 1.02, 1.04); (2) An increased risk of respiratory mortality was observed in the elderly (65+ years) (RR 1.21, 95% CI: 1.00, 1.47) with long-term exposure to PM2.5; (3) Long-term exposure to PM10 was associated with cardiovascular morbidity (RR 1.07, 95% CI 1.01, 1.13), respiratory morbidity (RR 1.43, 95% CI: 1.21, 1.69) and respiratory mortality (RR 1.28, 95% CI 1.10, 1.49); (4) A significant association between long-term exposure to PM1 and cardiovascular disease was also observed.

Conclusions

Long-term exposure to PM2.5, PM10 and PM1 was all related to cardiovascular and respiratory disease events. PM2.5 had a greater effect than PM10, especially on respiratory diseases, and the risk of respiratory mortality was significantly higher for LMICs than high-income countries. More studies are needed to confirm the effect of PM1 on cardiovascular and respiratory diseases.

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.

Co-Exposure of Ambient Particulate Matter and Airborne Transmission Pathogens: The Impairment of the Upper Respiratory Systems

Recent evidence has pinpointed the positive relevance between air particulate matter (PM) pollution and epidemic spread. However, there are still significant knowledge gaps in understanding the transmission and infection of pathogens loaded on PMs, for example, the interactions between pathogens and pre-existing atmospheric PM and the health effects of co-exposure on the inhalation systems. Here, we unraveled the interactions between fine particulate matter (FPM) and Pseudomonas aeruginosa (P. aeruginosa) and evaluated the infection and detrimental effects of co-exposure on the upper respiratory systems in both in vitro and in vivo models. We uncovered the higher accessibility and invasive ability of pathogens to epithelial cells after loading on FPMs, compared with the single exposure. Furthermore, we designed a novel laboratory exposure model to simulate a real co-exposure scenario. Intriguingly, the co-exposure induced more serious functional damage and longer inflammatory reactions to the upper respiratory tract, including the nasal cavity and trachea. Collectively, our results provide a new point of view on the transmission and infection of pathogens loaded on FPMs and uncover the in vivo systematic impairments of the inhalation tract under co-exposure through a novel laboratory exposure model. Hence, this study sheds light on further investigations of the detrimental effects of air pollution and epidemic spread.

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.

Investigating Spatial Patterns of Pulmonary Tuberculosis and Main Related Factors in Bandar Lampung, Indonesia Using Geographically Weighted Poisson Regression

Tuberculosis (TB) is a highly infectious disease, representing one of the major causes of death worldwide. Sustainable Development Goal 3.3 implies a serious decrease in the incidence of TB cases. Hence, this study applied a spatial analysis approach to investigate patterns of pulmonary TB cases and its drivers in Bandar Lampung (Indonesia). Our study examined seven variables: the growth rate of pulmonary TB, population, distance to the city center, industrial area, green open space, built area, and slum area using geographically weighted Poisson regression (GWPR). The GWPR model demonstrated excellent results with an R2 and adjusted R2 of 0.96 and 0.94, respectively. In this case, the growth rate of pulmonary TB and population were statistically significant variables. Spatial pattern analysis of sub-districts revealed that those of Panjang and Kedaton were driven by high pulmonary TB growth rate and population, whereas that of Sukabumi was driven by the accumulation of high levels of industrial area, built area, and slums. For these reasons, we suggest that local policymakers implement a variety of infectious disease prevention and control strategies based on the spatial variation of pulmonary TB rate and its influencing factors in each sub-district.

Age-period-cohort analysis of pulmonary tuberculosis reported incidence, China, 2006-2020

Background

Tuberculosis (TB) poses a severe public health challenge in China and worldwide. This study evaluated the effects of age, period, and birth cohort on reported incidence trends of TB based on population and refined the characteristics of high-risk groups.

Methods

Aggregate data that reported pulmonary tuberculosis (PTB) cases from China Tuberculosis Management Information System (TBIMS) from 2006 to 2020 were used to analyze effect coefficients through the age–period–cohort (APC) model based on intrinsic estimator (IE) method, and converted them into relative risk (RR) to estimate trends.

Results

A total of 14.82 million cases of PTB were reported in China from 2006 to 2020, showing a continuous downward trend. The reporting rate increased with age by age group, with 70–74 years old being 2–3 times higher than that in 20–24 years old. APC analysis model showed that age effects were bimodal in 20–24 years old [RR = 2.29, 95% confidence interval (CI): 1.73–3.03] and 70–74 years old (RR = 1.95, 95% CI: 1.67–2.27), and lower than the overall average in the groups under 15 years old. Stratified results showed that the risk was higher for women under age 40 than men and higher for men over 40. The risk was higher in urban than in rural areas under 30 years old and slightly higher in rural than in urban between 30 and 64 years old. The risk for 15–34 years old was significantly higher in the east than in other regions. The period effects showed a decreasing trend, and the risk was higher in rural in recent years. Except for cohorts born in 1961–1965 and 2001–2005, where the RR increased, the later the cohort was born, the lower the risk. The cohort 1926–1930 in eastern had the highest risk (RR = 3.49, 95% CI: 2.44–4.98).

Conclusions

The reported incidence of PTB continued to decline in China from 2006 to 2020. The young (20–24 years old) and the elderly (70–74 years old) were equally at high risk. There were differences in the age, period and cohort effects on PTB incidence among gender, urban–rural and regions. Our findings better reflected the characteristics of high-risk populations, thus contributing to the development of timely and effective intervention strategies, and providing clues for etiological research.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-01009-4.

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.

Spatio-temporal distribution of tuberculosis and the effects of environmental factors in China

Background

Although the World Health Organization reports that the incidence of tuberculosis in China is decreasing every year, the burden of tuberculosis in China is still very heavy. Understanding the spatial and temporal distribution pattern of tuberculosis in China and its influencing environmental factors will provide effective reference for the prevention and treatment of tuberculosis.

Methods

Data of TB incidence from 2010 to 2017 were collected. Time series and global spatial autocorrelation were used to analyze the temporal and spatial distribution pattern of tuberculosis incidence in China, Geodetector and Geographically Weighted Regression model were used to analyze the environmental factors affecting the TB incidence.

Results

In addition to 2007 and 2008, the TB incidence decreased in general. TB has a strong spatial aggregation. Cities in Northwest China have been showing a trend of high-value aggregation. In recent years, the center of gravity of high-value aggregation area in South China has moved further south. Temperature, humidity, precipitation, PM₁₀, PM_2.5, O₃, NO₂ and SO₂ have impacts on TB incidence, and in different regions, the environmental factors show regional differences.

Conclusions

Residents should pay more attention to the risk of developing TB caused by climate change and air pollutant exposure. Increased efforts should be placed on areas with high-value clustering in future public resource configurations.

Association of Daily Exposure to Air Pollutants with the Risk of Tuberculosis in Xuhui District of Shanghai, China

Previous studies have suggested that air pollutant exposure is related to tuberculosis (TB) risk, but results have not been consistent. This study evaluated the relation between daily air pollutant exposure and TB incidence in Shanghai from 2014 to 2019. Overall, there were four pollutants that were positively related to the risk of new TB cases. After a 5 μg/m³ increase, the maximum lag-specific and cumulative relative risk (RR) of SO₂ were 1.081, (95% CI: 1.035–1.129, lag: 3 days) and 1.616 (95% CI: 1.119–2.333, lag: 0–13 days), while for NO₂, they were 1.061 (95% CI: 1.015–1.11, lag: 4 days) and 1.8 (95% CI: 1.113–2.91, lag: 0–15 days). As for PM_2.5, with a 50 μg/m³ increase, the lag-specific and cumulative RR were 1.064 (95% CI: 1–1.132, lag: 6 days) and 3.101 (95% CI: 1.096–8.777, lag: 0–21 days), while for CO, the lag-specific RR was 1.03 (95% CI: 1.005–1.057, lag: 8 days) and the cumulative RR was 1.436 (95% CI: 1.004–2.053, lag: 0–16 days) with a 100 μg/m³ increase. The associations tended to be stronger in male and elderly patients and differed with seasons. Air pollutant exposure may be a risk factor for TB incidence.

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.

Specific urban units identified in tuberculosis epidemic using a geographical detector in Guangzhou, China

BACKGROUND

A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB's spatial features and risk factors in urban areas remain poorly understood. This study aims to identify the spatial differentiations and potential influencing factors of TB in highly urbanized regions on a fine scale.

METHODS

This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou, China. TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention. Before using Pearson correlation and a geographical detector (GD) to identify potential influencing factors, we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales.

RESULTS

Owing to its strong spatial autocorrelation (Moran's I = 0.33, Z = 4.71), the 2 km × 2 km grid was selected as the spatial scale. At this level, TB incidence was closely associated with most socioeconomic variables (0.31 < r < 0.76, P < 0.01). Of five environmental factors, only the concentration of fine particulate matter displayed significant correlation (r = 0.21, P < 0.05). Similarly, in terms of q values derived from the GD, socioeconomic variables had stronger explanatory abilities (0.08 < q < 0.57) for the spatial differentiation of the 2017 incidence of TB than environmental variables (0.06 < q < 0.27). Moreover, a much larger proportion (0.16 < q < 0.89) of the spatial differentiation was interpreted by pairwise interactions, especially those (0.60 < q < 0.89) related to the 2016 incidence of TB, officially appointed medical institutions, bus stops, and road density.

CONCLUSIONS

The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably influenced by several socioeconomic and environmental factors and their pairwise interactions on a fine scale. We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou. Our study provides helpful clues for local authorities implementing more effective intervention measures to reduce TB incidence in China's municipal areas, which are featured by both a high degree of urbanization and a high incidence of TB.

Health Effects of Long-Term Exposure to Ambient PM2.5 in Asia-Pacific: a Systematic Review of Cohort Studies

Abstract

Purpose of Review

Health effects of long-term exposure to ambient PM_2.5 vary with regions, and 75% of the deaths attributable to PM_2.5 were estimated in Asia-Pacific in 2017. This systematic review aims to summarize the existing evidence from cohort studies on health effects of long-term exposure to ambient PM_2.5 in Asia-Pacific.

Recent Findings

In Asia-Pacific, 60 cohort studies were conducted in Australia, Mainland China, Hong Kong, Taiwan, and South Korea. They consistently supported associations of long-term exposure to PM_2.5 with increased all-cause/non-accidental and cardiovascular mortality as well as with incidence of cardiovascular diseases, type 2 diabetes mellitus, kidney diseases, and chronic obstructive pulmonary disease. Evidence for other health effects was limited. Inequalities were identified in PM_2.5-health associations.

Summary

To optimize air pollution control and public health prevention, further studies need to assess the health effects of long-term PM_2.5 exposure in understudied regions, the health effects of long-term PM_2.5 exposure on mortality and risk of type 2 diabetes mellitus, renal diseases, dementia and lung cancer, and inequalities in PM_2.5-health associations. Study design, especially exposure assessment methods, should be improved.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40572-022-00344-w.

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.

Effect modification of greenness on PM2.5 associated all-cause mortality in a multidrug-resistant tuberculosis cohort

RATIONALE

Evidence for the association between fine particulate matter (PM_2.5) and mortality among patients with tuberculosis (TB) is limited. Whether greenness protects air pollution-related mortality among patients with multidrug-resistant tuberculosis (MDR-TB) is completely unknown.

METHODS

2305 patients reported in Zhejiang and Ningxia were followed up from MDR-TB diagnosis until death, loss to follow-up or end of the study (31 December 2019), with an average follow-up of 1724 days per patient. 16-day averages of contemporaneous Normalised Difference Vegetation Index (NDVI) in the 500 m buffer of patient's residence, annual average PM_2.5 and estimated oxidant capacity O_x were assigned to patients regarding their geocoded home addresses. Cox proportional hazards regression models were used to estimate HRs per 10 μg/m³ exposure to PM_2.5 and all-cause mortality among the cohort and individuals across the three tertiles, adjusting for potential covariates.

RESULTS

HRs of 1.702 (95% CI 1.680 to 1.725) and 1.169 (1.162 to 1.175) were observed for PM_2.5 associated with mortality for the full cohort and individuals with the greatest tertile of NDVI. Exposures to PM_2.5 were stronger in association with mortality for younger patients (HR 2.434 (2.432 to 2.435)), female (2.209 (1.874 to 2.845)), patients in rural (1.780 (1.731 to 1.829)) and from Ningxia (1.221 (1.078 to 1.385)). Cumulative exposures increased the HRs of PM_2.5-related mortality, while greater greenness flattened the risk with HRs reduced in 0.188-0.194 on average.

CONCLUSIONS

Individuals with MDR-TB could benefit from greenness by having attenuated associations between PM_2.5 and mortality. Improving greener space and air quality may contribute to lower the risk of mortality from TB/MDR-TB and other diseases.

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.

A scoping review on climate change and tuberculosis

Climate change is a global public health challenge. The changes in climatic factors affect the pattern and burden of tuberculosis, which is a worldwide public health problem affecting low and middle-income countries. However, the evidence related to the impact of climate change on tuberculosis is few and far between. This study is a scoping review following a five-stage version of Arksey and O'Malley's method. We searched the literature using the keywords and their combination in Google scholar, and PubMed. Climate change affects tuberculosis through diverse pathways: changes in climatic factors like temperature, humidity, and precipitation influence host response through alterations in vitamin D distribution, ultraviolet radiation, malnutrition, and other risk factors. The rise in extreme climatic events induces population displacement resulting in a greater number of vulnerable and risk populations of tuberculosis. It creates a conducive environment of tuberculosis transmission and development of active tuberculosis and disrupts tuberculosis diagnosis and treatment services. Therefore, it stands to reasons that climate change affects tuberculosis, particularly in highly vulnerable countries and areas. However, further studies and novel methodologies are required to address such a complex relationship and better understand the occurrence of tuberculosis attributable to climate change.

Effects of Controlled Generator Fume Emissions on the Levels of Troponin I, C-Reactive Protein and Oxidative Stress Markers in Dogs: Exploring Air Pollution-Induced Cardiovascular Disease in a Low-Resource Country

Exhaust fumes from petrol/diesel-powered electric generators contribute significantly to air pollution in many developing countries, constituting health hazards to both humans and animals. This study evaluated the serum concentrations of Troponin I (TnI), C-reactive protein (CRP) and serum levels/activities of oxidative stress markers: catalase (CAT), reduced glutathione (GSH), malondialdehyde (MDA), nitric oxide (NO) and superoxide dismutase (SOD) in dogs experimentally exposed to graded levels of petrol generator exhaust fume (PGEF). Sixteen (16) healthy and adult male Basenji dogs were randomly assigned into four groups (A-D). Group A was the unexposed control while groups B, C and D were exposed to PGEF for 1, 2 and 3 h per day, respectively, for 90 days. Repeated analysis were performed at the baseline, and every thirty days, for a total of 90 days. There was a significant interaction (p < 0.05) between the effects of PGEF exposure level (in h/day) and duration of exposure (in months) on all the tested serum parameters. There was a significant main effect (p < 0.05) for PGEF exposure level on the serum parameters. As the level of PGEF exposure was increased, the serum concentrations of TnI, CRP, CAT, MDA and NO increased, GSH decreased, whereas SOD activity increased by day 30 but declined at the end. Moreover, there was a significant simple main effect (p < 0.05) for duration of PGEF exposure. All the parameters increased as the duration of PGEF exposure was increased to 90 days except GSH concentration which decreased, whereas SOD activity increased initially but declined at the end of the study. Thus, there was increased serum concentrations of TnI, CRP and increased oxidative stress in the PGEF-exposed dogs. These findings are instructive and could be grounds for further studies on air pollutants-induced cardiovascular disease given the widespread use of electricity generators in many low-resource countries.

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.

Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia

Tuberculosis (TB) cases have increased drastically over the last two decades and it remains as one of the deadliest infectious diseases in Malaysia. This cross-sectional study aimed to establish the spatial distribution of TB cases and its association with the sociodemographic and environmental factors in the Gombak district. The sociodemographic data of 3325 TB cases such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from 1st January 2013 to 31st December 2017 in Gombak district were collected from the MyTB web and Tuberculosis Information System (TBIS) database at the Gombak District Health Office and Rawang Health Clinic. Environmental data consisting of air pollution such as air quality index (AQI), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter 10 (PM10,) were obtained from the Department of Environment Malaysia from 1st July 2012 to 31st December 2017; whereas weather data such as rainfall were obtained from the Department of Irrigation and Drainage Malaysia and relative humidity, temperature, wind speed, and atmospheric pressure were obtained from the Malaysia Meteorological Department in the same period. Global Moran's I, kernel density estimation, Getis-Ord Gi* statistics, and heat maps were applied to identify the spatial pattern of TB cases. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to determine the spatial association of sociodemographic and environmental factors with the TB cases. Spatial autocorrelation analysis indicated that the cases was clustered (p<0.05) over the five-year period and year 2016 and 2017 while random pattern (p>0.05) was observed from year 2013 to 2015. Kernel density estimation identified the high-density regions while Getis-Ord Gi* statistics observed hotspot locations, whereby consistently located in the southwestern part of the study area. This could be attributed to the overcrowding of inmates in the Sungai Buloh prison located there. Sociodemographic factors such as gender, nationality, employment status, health care worker status, income status, residency, and smoking status as well as; environmental factors such as AQI (lag 1), CO (lag 2), NO2 (lag 2), SO2 (lag 1), PM10 (lag 5), rainfall (lag 2), relative humidity (lag 4), temperature (lag 2), wind speed (lag 4), and atmospheric pressure (lag 6) were associated with TB cases (p<0.05). The GWR model based on the environmental factors i.e. GWR2 was the best model to determine the spatial distribution of TB cases based on the highest R2 value i.e. 0.98. The maps of estimated local coefficients in GWR models confirmed that the effects of sociodemographic and environmental factors on TB cases spatially varied. This study highlighted the importance of spatial analysis to identify areas with a high TB burden based on its associated factors, which further helps in improving targeted surveillance.

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.

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.

Air pollution exposure-the (in)visible risk factor for respiratory diseases

There is increasing interest in understanding the role of air pollution as one of the greatest threats to human health worldwide. Nine of 10 individuals breathe air with polluted compounds that have a great impact on lung tissue. The nature of the relationship is complex, and new or updated data are constantly being reported in the literature. The goal of our review was to summarize the most important air pollutants and their impact on the main respiratory diseases (chronic obstructive pulmonary disease, asthma, lung cancer, idiopathic pulmonary fibrosis, respiratory infections, bronchiectasis, tuberculosis) to reduce both short- and the long-term exposure consequences. We considered the most important air pollutants, including sulfur dioxide, nitrogen dioxide, carbon monoxide, volatile organic compounds, ozone, particulate matter and biomass smoke, and observed their impact on pulmonary pathologies. We focused on respiratory pathologies, because air pollution potentiates the increase in respiratory diseases, and the evidence that air pollutants have a detrimental effect is growing. It is imperative to constantly improve policy initiatives on air quality in both high- and low-income countries.

Temperature and humidity associated with increases in tuberculosis notifications: a time-series study in Hong Kong

Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13–15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02–1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0–63.6% at lagged 9–11 months expanded to 68.0–71.0% at lagged 12–17 months, reaching the highest risk of 1.06 (95% CI 1.01–1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.

Logistic regression analysis of environmental and other variables and incidences of tuberculosis in respiratory patients

The objective of this study was to examine the association of 14 variables with TB in respiratory patients. The variables included: urban/rural, persons in 1200 sqft area, TB in family, crowding, smoking (family member), gender, age, education, smoking, workplace, kitchen location, cooking fuel, ventilation, and kerosene uses. Eight hundred respiratory patients were tested for sputum positive pulmonary TB; 500 had TB and 300 did not. An analysis of the unadjusted odds ratio (UOR) and adjusted OR (AOR) was undertaken using logistic regression to link the probability of TB incidences with the variables. There was an inconsistency in the significance of variables using UOR and AOR. A subset model of 4 variables (kerosene uses, ventilation, workplace, and gender) based on significant AOR was adjudged acceptable for estimating the probability of TB incidences. Uses of kerosene (AOR 2.62 (1.95, 3.54)) consistently related to incidences of TB. It was estimated that 50% reduction in kerosene uses could reduce the probability of TB by 13.29% in respiratory patients. The major recommendation was to replace kerosene uses from households with a supply of clean fuel like liquid petroleum or natural gas and rural electrification.

Understanding the knowledge gaps between air pollution controls and health impacts including pathogen epidemic

Sustainable development calls for a blue sky with quality air. Encouragingly, the current mass reduction-oriented pollution control is making substantial achievements, as the data from Chinese Environmental Monitoring Stations show a significant drop in the annual average concentrations of particulate matters (i.e., PM₁₀ and PM_2.5) and SO₂. But many challenges and knowledge gaps are still confronted nowadays. On one hand, long-term health impacts of fine air particles have to be closely probed through both epidemiological and laboratory studies, and the toxic effects owing to the interactions between particles and associated chemical pollutants should be differentially teased out. On the other hand, due to sole mass control, there are significant changes of overall pollutant fingerprint, such as the increase of ground-level ozone concentration, which should be taken into account for altered health effects relative to the past. Moreover, the interplays with air pollutants and air-borne pathogens should be scrutinized in more details. In other words, it is worth investigating likely spread of pathogens (even for SARS-CoV-2) with aid of aerosols. Here, we recapitulate the current knowledge gaps between air pollution controls and health impacts including pathogen epidemic, and we also propose future research directions to support policy making in balance mass control and health impacts.

An Opportunity to END TB: Using the Sustainable Development Goals for Action on Socio-Economic Determinants of TB in High Burden Countries in WHO South-East Asia and the Western Pacific Regions

The progress towards ending tuberculosis (TB) by 2035 is less than expected in 11 high TB burden countries in the World Health Organization South-East Asia and Western Pacific regions. Along with enhancing measures aimed at achieving universal access to quality-assured diagnosis, treatment and prevention services, massive efforts are needed to mitigate the prevalence of health-related risk factors, preferably through broader actions on the determinants of the "exposure-infection-disease-adverse outcome" spectrum. The aim of this manuscript is to describe the major socio-economic determinants of TB and to discuss how there are opportunities to address these determinants in an englobing manner under the United Nations Sustainable Development Goals (SDGs) framework. The national TB programs must identify stakeholders working on the other SDGs, develop mechanisms to collaborate with them and facilitate action on social-economic determinants in high TB burden geographical areas. Research (to determine the optimal mechanisms and impact of such collaborations) must be an integral part of this effort. We call upon stakeholders involved in achieving the SDGs and End TB targets to recognize that all goals are highly interlinked, and they need to combine and complement each other's efforts to end TB and the determinants behind this disease.

Association between short-term exposure to ambient air pollutants and the risk of tuberculosis outpatient visits: A time-series study in Hefei, China

BACKGROUND

The current evidence has presented mixed results between air pollutants exposure and the progression of tuberculosis (TB). The purpose of this study was to explore the association between short-term exposure to air pollutants and the risk of TB outpatient visits in Hefei, China.

METHODS

Time-series analysis was used to assess the effect of short-term exposure to ambient air pollutants on the risk of TB outpatient visits. A Poisson generalized linear regression model combined with a distributed lag non-linear model (DLNM) was applied to explore the association. The effects of different gender (male, female), age (≤65 years old, >65 years old) and season (cold season, warm season) on the risk of TB were investigated by stratified analysis. Sensitivity analyses were conducted to test the robustness of our findings.

RESULTS

A total of 22,749 active TB cases were identified from November 1, 2013 to December 31, 2018 in Hefei. The overall exposure-response curve showed that the concentration of particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) and nitrogen dioxide (NO₂) exposure were positively correlated with the risk of TB outpatient visits, while ozone (O₃) and sulfur dioxide (SO₂) exposure were negatively correlated with the risk of TB outpatient visits. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits were 1.057 [95%CI: 1.002-1.115, lag 3 day] and 1.559 (95%CI: 1.057-2.300, lag 13 days) for each 10 μg/m³ increase in PM_2.5; 1.026 (95% CI: 1.008-1.044, lag 0 day) and 1.559 (95%CI: 1.057-2.300, lag 07 days) for each 10 μg/m³ increase in NO₂; 0.866 (95% CI: 0.801-0.935, lag 5 day) and 0.852 (95%CI: 1.01-1.11, lag 0-14 days) for each 10 μg/m³ increase in SO₂ in the single-pollutant model. There was only a negative association between O₃ exposure and the cumulative risk of TB outpatient visits (RR = 0.960, 95%CI: 0.936-0.984, lag 07 days). Stratified analyses showed that the effects of SO₂ and O₃ exposure were different between warm and cold seasons. The effect of NO₂ exposure remained statistically significant in male, younger, and cold season subgroups. Besides, elderly people are more susceptible to PM_2.5 exposure.

CONCLUSION

This study suggests that exposure to PM_2.5, NO₂, SO₂, and O₃ are associated with the risk of TB outpatient visits. Seasonal variation may have a greater impact on the risk of TB outpatient visits compared with gender and age.

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.