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. 2024 May 17;24(1):1333.
doi: 10.1186/s12889-024-18475-0.

The effects of meteorological factors and air pollutants on the incidence of tuberculosis in people living with HIV/AIDS in subtropical Guangxi, China

Fengyi Wang #  1   2 , Zongxiang Yuan #  1   2 , Shanfang Qin #  3 , Fengxiang Qin  1   2 , Junhan Zhang  1   2 , Chuye Mo  1   2 , Yiwen Kang  1   2 , Shihui Huang  1   2 , Fang Qin  1   2 , Junjun Jiang  4   5 , Aimei Liu  6 , Hao Liang  7   8 , Li Ye  9   10
Affiliations

The effects of meteorological factors and air pollutants on the incidence of tuberculosis in people living with HIV/AIDS in subtropical Guangxi, China

Fengyi Wang et al. BMC Public Health. .

Abstract

Background: Previous studies have shown the association between tuberculosis (TB) and meteorological factors/air pollutants. However, little information is available for people living with HIV/AIDS (PLWHA), who are highly susceptible to TB.

Method: Data regarding TB cases in PLWHA from 2014 to2020 were collected from the HIV antiviral therapy cohort in Guangxi, China. Meteorological and air pollutants data for the same period were obtained from the China Meteorological Science Data Sharing Service Network and Department of Ecology and Environment of Guangxi. A distribution lag non-linear model (DLNM) was used to evaluate the effects of meteorological factors and air pollutant exposure on the risk of TB in PLWHA.

Results: A total of 2087 new or re-active TB cases were collected, which had a significant seasonal and periodic distribution. Compared with the median values, the maximum cumulative relative risk (RR) for TB in PLWHA was 0.663 (95% confidence interval [CI]: 0.507-0.866, lag 4 weeks) for a 5-unit increase in temperature, and 1.478 (95% CI: 1.116-1.957, lag 4 weeks) for a 2-unit increase in precipitation. However, neither wind speed nor PM10 had a significant cumulative lag effect. Extreme analysis demonstrated that the hot effect (RR = 0.638, 95%CI: 0.425-0.958, lag 4 weeks), the rainy effect (RR = 0.285, 95%CI: 0.135-0.599, lag 4 weeks), and the rainless effect (RR = 0.552, 95%CI: 0.322-0.947, lag 4 weeks) reduced the risk of TB. Furthermore, in the CD4(+) T cells < 200 cells/µL subgroup, temperature, precipitation, and PM10 had a significant hysteretic effect on TB incidence, while temperature and precipitation had a significant cumulative lag effect. However, these effects were not observed in the CD4(+) T cells ≥ 200 cells/µL subgroup.

Conclusion: For PLWHA in subtropical Guangxi, temperature and precipitation had a significant cumulative effect on TB incidence among PLWHA, while air pollutants had little effect. Moreover, the influence of meteorological factors on the incidence of TB also depends on the immune status of PLWHA.

Keywords: Air Pollutant; DLNM; HIV/AIDS; Meteorological factors; Tuberculosis.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Time series of TB cases, meteorological factors (temperature, wind speed, precipitation, sunshine duration, and relative humidity) (A), and air pollutants (CO, O3, NO2, PM2.5, and PM10) (B) in subtropical Guangxi, China, from 2014 to 2020
Fig. 2
Fig. 2
The overall exposure-response impact of temperature (A), wind speed (B), precipitation (C), and PM10 (D) on TB risk in PLWHA
Fig. 3
Fig. 3
Contour plot of the effects of temperature (A), wind speed (B), precipitation (C), and PM10 (D)
Fig. 4
Fig. 4
3D graph of the effects of temperature(A), wind speed (B), precipitation (C), and PM10 (D)
Fig. 5
Fig. 5
Lag-specific response effects for a unit increase in different factors (A); cumulative effects for lag-response incremental cumulative effects for a unit increase in different factors (B). In the model, a 5-unit increase for temperature, a 0.5-unit increase for wind speed, a 2-unit increase for precipitation, and a 15-unit increase for PM10 were used to calculate the relative risk of TB in PLWHA
Fig. 6
Fig. 6
Summary of the overall cumulative association between TB incidence in people living with HIV/AIDS (PLWHA) and meteorological factors (temperature, wind speed, and precipitation) and air pollutants (PM10) in different subgroup, stratified by the CD4(+) T cell count
See this image and copyright information in PMC

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