Previously, the relationships between air pollutants and TB were explored by many traditional methods, including linear models, conditional logistic regression models, Poisson regression models and hierarchical Bayesian methods [14,15,16, 21, 28]. However, few studies have considered spatial or spatial-temporal interactive effects at the population level. Considering the goodness of fit based on the DIC value, we adopted a Bayesian spatial-temporal interactive model in our study. This model could identify spatial differences and solve problems such as spatial autocorrelation, which is difficult for most traditional statistical methods. Hubei Province is one of the most serious tuberculosis epidemic areas in China. The rates of PTB incidence as well as the annual air pollutant concentrations of PM10, SO2 and NO2 in our study are higher than those in developed countries [4, 20, 21]. Our findings showed that SO2 was positively associated with PTB incidence, with a 4.6% increase in PTB incidence rates per 10 μg/m3 increase in SO2. When stratified by gender, positive associations were noted with exposure to all three air pollutants in females but only to SO2 in males. When stratified by age, positive associations were observed for SO2 in all the age groups and for PM10 only in children under 15 years. Moreover, a significant lag response relationship was also found, with a lag of 0–1 month for SO2.
In our study, the risk of PTB was not significantly associated with exposure to PM10. We noticed that in previous experimental studies, exposure to PM10 was found to enhance intracellular Mycobacterium tuberculosis growth by inducing senescence and downregulating the expression of the antimicrobial peptides human β-defensin2 (HBD-2) and HBD-3, which are important in the early control of TB infection [29, 30]. However, experimental studies cannot reflect the actual association between ambient PM10 and TB incidence at the population level. Although one previous epidemiological study in North Carolina found that exposure to particulate air pollution increased the risk of TB during 1993–2007 [13], the study was based on Poisson regression models with low ambient PM10 levels (19.39–24.63 μg/m3) as well as a low rate of PTB disease incidence (4.41 per 100,000 persons/year); in contrast, in our research, there were high levels of air pollutant concentrations and PTB incidence. However, most recent epidemiologic studies have found no significant associations between PM10 and TB, which is consistent with our results [13,14,15]. To elucidate the possible associations between PM10 and PTB, more research needs to be done in the future.
The associations observed for SO2 were significantly positive, similar to the findings of other studies. Shilova and Glumnaia found that atmospheric pollutants (including SO2) were significantly associated with TB incidence in Russia [31]. Hwang et al. reported that the interquartile increase in the SO2 concentration in outdoor air pollutants could result in a 7% increase in TB incidence in South Korea [15]. The reason for this association may be attributed to the effect of exposure to SO2 on pulmonary defences. A previous study showed that a 30-min exposure to 12.5 ppm SO2 induced 62% death of alveolar macrophages and led to a decrease of 63% in the release of reactive oxygen species, which are crucial for inhibiting or killing Mycobacteria tuberculosis [32]. The researchers also found that exposure to SO2 caused a significant decrease in the production or release of TNF-α and interleukin-1, which can defend against Mycobacterium tuberculosis by regulating the activity of other cytokines and chemokines in early TB infections [27, 33]. Using TNF-neutralizing therapies increases the risk of developing tuberculosis and induces frequent reactivation of latent TB in patients [34,35,36]. However, compared with other studies, the effect size of SO2 in our study seems very small. For example, the interquartile range (IQR = 0.3 ppb) increase in SO2 concentration was associated with a 7% increase in TB incidence rate in South Korea, but only a 4.6% increase in TB incidence rates per 10 μg/m3 increase in SO2 concentration was observed in our study. There may be several reasons for these findings. First, the average SO2 concentrations and IQRs in our study were higher than those in other studies, which caused a smaller variation with the same scale change in concentrations. Second, a higher TB incidence may result in a smaller change in the TB incidence rate ratio if the effect caused the same change size in TB incidence. Third, some potential confounders, which influenced regional TB epidemiology [37], may disturb the effect of SO2, and no adjustments were made for this disturbance in the previous study.
No association was observed between NO2 and PTB, consistent with the findings of some studies. After exploring the impact of outdoor air pollution on TB in South Korea, researchers found that the concentrations of ambient NO2 were not associated with TB incidence15. Another study also showed no significant association between the daily initial TB outpatient visits and daily average concentration of NO2 [38]. However, a recent nested case–control study in northern California found a positive association between TB and NO2 [14]. One thing to note is that the study in northern California assessed average individual-level concentrations of NO2 for only 2 years before the diagnosis of TB; the individual-level exposure depending on only outdoor concentrations may be altered by smoking or using gas appliances indoors.
To investigate the sex-specific associations between air pollution and PTB, the analysis was stratified by gender. Positive relationships were observed for PM10 and NO2 in females but not in males. This result suggested that the effects of PM10 and NO2 on PTB may differ by gender. Other epidemiological studies also found that the effects of air pollutants on respiratory health are much more marked in females [39]. Clougherty et al. also found that increased impact of air pollution on respiratory health in females was linked to their social or behavioural and biological differences [40]. The reason may be that some sex-linked traits impact the biological transport of environmental chemicals, while gender-linked activities (i.e., where and what people spend time doing) determine the distribution of air pollution exposure. The biological sex of females leads to the inhalation of more doses of air pollution, greater deposition and absorption of air pollution and higher gas–blood barrier permeability in the respiratory tract [41, 42]. Another important reason for the sex-specific associations between air pollution and PTB may be related to a prominent feature of smoking habits in China and the substantial male/female difference in the rates of smoking. For example, a recent nationally representative survey showed that the male/female ratio of smoking was 22 in 2010 [43]. The increased relative risk degree of PTB incidence by air pollution exposure may be obscured or weaken partially by heavy smoking in men. Further stratifying the analysis by age, we observed positive associations for PM10 in individuals aged 0–14 years but not in those aged 15 years or older. Evidence from epidemiological studies also found that the effects of air pollution on respiratory health are much more marked in children [44,45,46]. This may be due to the differences in breathing pattern and lung structure between children and adults. The dose of air pollutants deposited the respiratory systems of children is higher than that of adults if they are exposed to the same levels of air pollutants [47, 48]. By spending more time on activities outdoors, children also increased their ventilation rates and exposure to air pollutants [49]. Therefore, we supposed that the gender- and age-related effects of air pollutants on pulmonary TB in our study may be due to some interplay between the above mentioned factors.
As with any statistical modelling study, our study also has some limitations. First, despite the biologic plausibility of a possible association between air pollutants and PTB, our results should be interpreted cautiously, with the inherent limitations of an ecological study design that used population-level data. Second, some key potential confounders to the relationship between air pollution and regional PTB, including household air pollution from the burning of solid fuel and more detailed information on smoking, should be accounted for in future investigations, although city-level tobacco consumption data were collected. Third, exposure to ambient PM2.5 is arguably an equally relevant indicator of air pollution exposure, but is not included given the unavailability of PM2.5 estimates from the Hubei monitoring network before 2012. Last but not least, due to the implementation of the Chinese TB control project and policy shifts, there are also potential issues with the identification of TB, including changes in active TB screening, access to or use of TB treatment, case registration report rate, and others. Future epidemiological cohort studies are needed for the assessment of cause-specific TB disease, especially in females and young people.