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

Abstract

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.

Keywords: Air pollution; Distributed lag non-linear model; Tuberculosis.

Fig. 1

Map of the distribution of tuberculosis surveillance health facilities and meteorological monitoring stations in Nantong city.

Fig. 2

Temporal distribution of reported TB cases in Nantong city from 2005 to 2020. (A) Time-series of monthly TB cases; (B) a long-term trend was decomposed from the time-series of TB cases; (C) a seasonal trend was decomposed from the time-series of TB cases; (D) the residual data after excluding seasonal and long-term trends; (E) the seasonal index of 12 months.

Fig. 3

Boxplots of the number of TB cases, five meteorological factors and six air pollutants in four seasons from 2005 to 2020. (A) The seasonal pattern of TB cases. (B) The seasonal pattern of Meteorological factors. (C) The seasonal pattern of air pollutants. An analysis of variance (ANOVA) test is applied to examine the values or concentrations among the four seasons. A Kruskal-Wallis test is used to examine the TB cases among the four seasons: spring (March to May), summer (June to August), autumn (September to November), and winter (December to February). TB: tuberculosis; RH: Relative humidity; WS: Wind speed; PM_2.5: particulate matter with aerodynamic diameter <2.5 μm; PM₁₀: particulate matter with aerodynamic diameter <10 μm; SO₂: sulfur dioxide; NO₂: nitrogen dioxide; CO: carbon monoxide; O₃: ozone.

Fig. 4

Contour plots of the exposure-response relationship for the association between TB cases and air pollutants in the single-variable model. (A–D) Four air pollutants from 2005 to 2020. In the single-variable model, we further adjust the temporal trend, meteorological factors, Spring-Festival, and socioeconomic covariates. The Y-axis is the lag month ranging from 0 to 18. The X-axis is the range of the observed values of each variable. The color gradient represents the relative risk (RR). The red color gradient represents higher strength of RR, above 1, and the blue gradient represents lower strength of RR, below 1. The white color represents no difference, at RR = 1. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5

The lag-specific relative risks and cumulative relative risks of per 10 μg/m³ increase in four air pollutants on TB cases at different lag months, according to the single-pollutant model. RR: relative risk; PM_2.5: particulate matter with aerodynamic diameter less than 2.5 μm; PM₁₀: particulate matter with aerodynamic diameter less than 10 μm; NO₂: nitrogen dioxide; O₃: ozone.