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

Spatial autocorrelation with environmental factors related to tuberculosis prevalence in Nepal, 2020-2023

BACKGROUND

Despite global efforts to reduce tuberculosis (TB) incidence, Nepal remains burdened by approximately 70,000 new cases annually, with an incidence rate of 229 per 100,000 people in 2022. This study investigated the geographic patterns of TB notifications in Nepal from fiscal year 2020 to 2023, focusing on environmental determinants such as land surface temperature (LST), urbanization, precipitation and cropland coverage.

METHODS

This study examined the spatial association between environmental factors and TB prevalence in Nepal at the district level, utilizing Geographic Information System (GIS) techniques, bivariate Local Indicators of Spatial Association (LISA) and spatial regression analyses. The tuberculosis prevalence data were obtained from the National Tuberculosis Control Center (NTCC) Nepal for the fiscal years (FY) 2020-2023.

RESULTS

Over the three fiscal years, high TB prevalence consistently clustered in districts such as Banke, Parsa, and Rautahat, while low prevalence areas included Mustang and Kaski. Significant positive spatial autocorrelation was found between environmental factors and TB prevalence. Moran's I values were as follows: for LST (day), 0.379, 0.424, and 0.423; for LST (night), 0.383, 0.420, and 0.425; for cropland coverage, 0.325, 0.339, and 0.373; for urbanization, 0.197, 0.245, and 0.246; and for precipitation, 0.222, 0.349, and 0.104 across FY 2020-2021, FY 2021-2022 and FY 2022-2023, respectively. Regression analyses, including Ordinary Least Squares (OLS), Spatial Lag Model (SLM), and Spatial Error Model (SEM), demonstrated that Land Surface Temperature Night (LSTN), urbanization, and precipitation significantly influenced TB prevalence, explaining up to 72.1% of the variance in FY 2021-2022 (R2: 0.721).

CONCLUSIONS

Environmental factors significantly influence the spatial distribution of TB in Nepal. This underscores the importance of integrating disease management strategies with environmental health policies in effectively addressing TB prevalence.

The impact of air pollutants on emergency ambulance dispatches due to mental and behavioral disorders in Shenzhen, China

BACKGROUND

The relationships between air pollutants and mental and behavioral disorders (MBDs) remain unclear. We aimed to identify the primary pollutants affecting mental health and evaluate the short-term effects on emergency ambulance dispatches (EADs) due to MBDs.

METHODS

Time-stratified case-crossover study and conditional logistic regression model were adopted to explore the impact of air pollutants on EADs due to MBDs from 2013 to 2020 in Shenzhen, China. In order to clarify the influence of gender and age on association, subgroup analysis was carried out. We also applied binary response surface model and distributed lag interaction model to examine the interaction effects between pollutants and meteorological factors on EADs due to MBDs.

RESULTS

Nitrogen dioxide (NO2) was the primary pollutant in Shenzhen that affects the EADs due to mental and behavioral disorders, exhibiting significant immediate exposure effects and cumulative lag effects. As NO2 concentration increased, the risk of EADs due to mental and behavioral disorders showed a linear upward trend without a threshold. For each interquartile range (IQR) increase of NO2, the odds ratio (OR) associated with MBDs was highest at lag 2 in the single-day lag pattern (OR = 1.035, 95% CI: 1.012-1.060) and the effect of NO2 reached its maximum at lag 0-6 with OR of 1.078 (95% CI: 1.037-1.122). We did not observe significant associations between PM2.5, PM10, SO2, O3 and CO exposures and EADs due to MBDs. In addition, there was an interaction effect between NO2 and Humidity index (Humidex). Both high and low Humidex would aggravate the influence of pollutants on mental health.

CONCLUSIONS

Short exposure to NO2 was positively associated with acute onset of MBDs in Shenzhen, China. Health departments should take effective measures to raise public awareness of NO2 and Humidex, as well as their interaction effects.

Analysis of epidemiological trends and risk factors in high-risk areas for pulmonary tuberculosis: an observational longitudinal study in Xinjiang, China

OBJECTIVE

To explore the spatial and temporal variations in the long-term risk of developing tuberculosis (TB) and the factors influencing it in order to contribute to the goal of eradicating TB.

DESIGN

Observational longitudinal study.

SETTING

Xinjiang, China, 2005-2019.

PRIMARY AND SECONDARY OUTCOME MEASURES

Comparison of TB incidence across age, period, cohort and space using socioeconomic (including gross domestic product per capita, population density, public budget revenue and total retail sales of consumer goods), public health (including the number of hospital beds, health technicians and basic medical insurance for urban residents) and environmental variables (PM2.5, mean air temperature, mean wind speed, mean relative humidity and precipitation). The relative importance of these variables to pulmonary TB (PTB) is revealed by the Q-value (0, 1), with larger values indicating that the spatial heterogeneity of the explanatory variables to PTB is more pronounced.

PARTICIPANTS

All clinically diagnosed and confirmed cases in Xinjiang, China, were collected. The descriptive analysis included confirmed cases from 2005 to 2019, while cases from various districts and counties between 2011 and 2019 were subjected to further analysis.

RESULTS

From 2005 to 2019, a total of 642 332 cases of PTB were reported in Xinjiang, with an average annual incidence rate of 172/100 000. The age risk of PTB presented a bimodal distribution, namely 20-24 years and the elderly (>60 years). The high prevalence of PTB was distributed in the southern part of Xinjiang. Among the influencing factors that had a greater effect on the incidence of PTB, the lower GDP per capita (Q-value=0.65) had a largest effect on PTB in Xinjiang compared with others factors (higher PM2.5: Q-value=0.56, lower health personnel: Q-value=0.49, higher average temperature: Q-value=0.47 and higher urban residents' health insurance: Q-value=0.46). The main influencing factors were heterogeneous in different regions. Furthermore, the interactions among these factors enhanced the explanatory power regarding the incidence of the disease.

CONCLUSIONS

Identifying the high-risk groups, regions, influencing factors and interactions of PTB in Xinjiang, China, will expand the epidemiological knowledge of PTB in high-risk areas and potentially aid in designing targeted interventions.

Association between ambient particulate matter and latent tuberculosis infection among 198 275 students

Background

Numerous studies have estimated the impact of outdoor particulate matter (PM) on tuberculosis risk. Nevertheless, whether there is an association between ambient PM and latent tuberculosis infection (LTBI) risk remains uncertain.

Methods

We collected the basic information and LTBI test results of students who underwent freshmen enrolment physical examinations in 68 middle schools from six prefecture-level cities located in eastern China between 2018 and 2021. We also extracted data on air pollutant concentrations and meteorological factors in six cities between 2015 and 2021. We applied the generalised additive model (GAM) to assess the effect of PM on LTBI risk.

Results

We included 198 275 students in the final analysis, of whom 11 721 were diagnosed with LTBI. The LTBI group had higher proportions of males (P < 0.001), individuals of Han nationality (P < 0.001), and body mass index compared to the non-LTBI group (P < 0.001). For each 1-μg/m3 increase in PM10 concentration, the LTBI risk increased by 0.82% (95% confidence interval (CI) = 0.65-1.00), 0.90% (95% CI = 0.73-1.08), and 0.86% (95% CI = 0.69-1.03) when lagged at one, two, and three years, respectively. For PM2.5, the LTBI risk increased by 0.91% (95% CI = 0.63-1.20), 1.05% (95% CI = 0.75-1.36), and 1.32% (95% CI = 0.96-1.69) when lagged at one, two, and three years, respectively.

Conclusions

Outdoor PM concentration was positively correlated with LTBI risk. Considering that many developing countries are facing the dual challenges of high LTBI rates and serious ambient air pollution, reducing outdoor PM concentration would contribute to alleviating their tuberculosis burden.

Ambient air pollution contributed to pulmonary tuberculosis in China

Published studies on outdoor air pollution and tuberculosis risk have shown heterogeneous results. Discrepancies in prior studies may be partially explained by the limited geographic scope, diverse exposure times, and heterogeneous statistical methods. Thus, we conducted a multi-province, multi-city time-series study to comprehensively investigate this issue. We selected 67 districts or counties from all geographic regions of China as study sites. We extracted data on newly diagnosed pulmonary tuberculosis (PTB) cases, outdoor air pollutant concentrations, and meteorological factors in 67 sites from January 1, 2014 to December 31, 2019. We utilized a generalized additive model to evaluate the relationship between ambient air pollutants and PTB risk. Between 2014 and 2019, there were 172,160 newly diagnosed PTB cases reported in 67 sites. With every 10-μg/m3 increase in SO2, NO2, PM10, PM2.5, and 1-mg/m3 in CO, the PTB risk increased by 1.97% [lag 0 week, 95% confidence interval (CI): 1.26, 2.68], 1.30% (lag 0 week, 95% CI: 0.43, 2.19), 0.55% (lag 8 weeks, 95% CI: 0.24, 0.85), 0.59% (lag 10 weeks, 95% CI: 0.16, 1.03), and 5.80% (lag 15 weeks, 95% CI: 2.96, 8.72), respectively. Our results indicated that ambient air pollutants were positively correlated with PTB risk, suggesting that decreasing outdoor air pollutant concentrations may help to reduce the burden of tuberculosis in countries with a high burden of tuberculosis and air pollution.

Effects of meteorological factors on tuberculosis and potential modifiers in Zhejiang Province, China

Although some studies have explored the role of meteorological factors in the development of tuberculosis (TB), the majority have been confined to single regions, leading to inconsistent findings. Consequently, we conducted a multi-city study not only to determine whether meteorological factors significantly influence the risk of developing TB but also to assess the magnitude of these effects and explore potential modifying factors. Data on daily reported TB cases and meteorological factors were collected from January 1, 2013, to December 31, 2022, across 11 cities in Zhejiang Province. A distributed lag non-linear model using a quasi-Poisson distribution was employed. Multivariate meta-regression was used to obtain overall pooled estimates and assess heterogeneity. From 2013 to 2022, 267,932 TB cases were reported in Zhejiang Province. Notably, a nonlinear relationship was observed between temperature and TB, with the relative risk (RR) peaking at 1.0 °C (RR = 1.882, 95% CI 1.173-3.020). The effect of low temperature was immediate and significant for a 13-day lag period, with the maximum effect at lag0 (RR = 1.014, 95% CI 1.008-1.021). The exposure-response curve between relative humidity (RH) and TB exhibited an M-shape, with the RR peaking at 47.7% (RR = 1.642, 95% CI 1.044-2.582). The lag effect of low RH was significant at lag 25-59, with the highest RR observed at lag 32 (RR = 1.011, 95% CI 1.001-1.022). Gross domestic product (GDP) per person, population density, and latitude demonstrated significant modification effects. Our study showed that low temperature and RH were associated with an increased risk of TB. Additionally, GDP per person, population density, and latitude may play important roles in explaining the association between RH and TB. These findings provide scientific evidence for the development of geographically specific public health policies.

Long- and short-run asymmetric impacts of climate variation on tuberculosis based on a time series study

Distinguishing between long-term and short-term effects allows for the identification of different response mechanisms. This study investigated the long- and short-run asymmetric impacts of climate variation on tuberculosis (TB) and constructed forecasting models using the autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL). TB showed a downward trend, peaking in March-May per year. A 1 h increment or decrement in aggregate sunshine hours resulted in an increase of 32 TB cases. A 1 m/s increment and decrement in average wind velocity contributed to a decrement of 3600 and 5021 TB cases, respectively (Wald long-run asymmetry test [WLR] = 13.275, P < 0.001). A 1% increment and decrement in average relative humidity contributed to an increase of 115 and 153 TB cases, respectively. A 1 hPa increment and decrement in average air pressure contributed to a decrease of 318 and 91 TB cases, respectively (WLR = 7.966, P = 0.005). ∆temperature(-), ∆(sunshine hours)( -), ∆(wind velocity)(+) and ∆(wind velocity)(-) at different lags had a meaningful short-run effect on TB. The NARDL outperformed the ARDL in forecasting. Climate variation has significant long- and short-run asymmetric impacts on TB. By incorporating both dimensions of effects into the NARDL, the accuracy of the forecasts and policy recommendations for TB can be enhanced.

The association between humidex and tuberculosis: a two-stage modelling nationwide study in China

BACKGROUND

Under a changing climate, the joint effects of temperature and relative humidity on tuberculosis (TB) are poorly understood. To address this research gap, we conducted a time-series study to explore the joint effects of temperature and relative humidity on TB incidence in China, considering potential modifiers.

METHODS

Weekly data on TB cases and meteorological factors in 22 cities across mainland China between 2011 and 2020 were collected. The proxy indicator for the combined exposure levels of temperature and relative humidity, Humidex, was calculated. First, a quasi-Poisson regression with the distributed lag non-linear model (DLNM) was constructed to examine the city-specific associations between humidex and TB incidence. Second, a multivariate meta-regression model was used to pool the city-specific effect estimates, and to explore the potential effect modifiers.

RESULTS

A total of 849,676 TB cases occurred in the 22 cities between 2011 and 2020. Overall, a conspicuous J-shaped relationship between humidex and TB incidence was discerned. Specifically, a decrease in humidex was positively correlated with an increased risk of TB incidence, with a maximum relative risk (RR) of 1.40 (95% CI: 1.11-1.76). The elevated RR of TB incidence associated with low humidex (5th humidex) appeared on week 3 and could persist until week 13, with a peak at approximately week 5 (RR: 1.03, 95% CI: 1.01-1.05). The effects of low humidex on TB incidence vary by Natural Growth Rate (NGR) levels.

CONCLUSION

A J-shaped exposure-response association existed between humidex and TB incidence in China. Humidex may act as a better predictor to forecast TB incidence compared to temperature and relative humidity alone, especially in regions with higher NGRs.

Interaction between air pollutants and meteorological factors on pulmonary tuberculosis in northwest China: A case study of eight districts in Urumqi

Meteorological factors and air pollutants are associated with the spread of pulmonary tuberculosis (PTB), but few studies have examined the effects of their interactions on PTB. Therefore, this study investigated the impact of meteorological factors and air pollutants and their interactions on the risk of PTB in Urumqi, a city with a high prevalence of PTB and a high level of air pollution. The number of new PTB cases in eight districts of Urumqi from 2014 to 2019 was collected, along with data on meteorological factors and air pollutants for the same period. A generalized additive model was applied to explore the effects of meteorological factors and air pollutants and their interactions on the risk of PTB incidence. Segmented linear regression was used to estimate the nonlinear characteristics of the impact of meteorological factors on PTB. During 2014-2019, a total of 14,402 new cases of PTB were reported in eight districts, with March to May being the months of high PTB incidence. The exposure-response curves for temperature (Temp), relative humidity (RH), wind speed (WS), air pressure (AP), and diurnal temperature difference (DTR) were generally inverted "U" shaped, with the corresponding threshold values of - 5.411 °C, 52.118%, 3.513 m/s, 1021.625 hPa, and 8.161 °C, respectively. The effects of air pollutants on PTB were linear and lagged. All air pollutants were positively associated with PTB, except for O3, which was not associated with PTB, and the ER values for the effects on PTB were as follows: 0.931 (0.255, 1.612) for PM2.5, 1.028 (0.301, 1.760) for PM10, 5.061 (0.387, 9.952) for SO2, 2.830 (0.512, 5.200) for NO2, and 5.789 (1.508, 10.251) for CO. Meteorological factors and air pollutants have an interactive effect on PTB. The risk of PTB incidence was higher when in high Temp-high air pollutant, high RH-high air pollutant, high WS-high air pollutant, lowAP-high air pollutant, and high DTR-high air pollutant. In conclusion, both meteorological and pollutant factors had an influence on PTB, and the influence on PTB may have an interaction.

Association of air pollutants and meteorological factors with tuberculosis: a national multicenter ecological study in China

The impact of weather variability and air pollutants on tuberculosis (TB) has been a research hotspot. Previous studies have mostly been limited to a certain area or with a small sample size of cases, and multi-scale systematic studies are lacking. In this study, 14,816,329 TB cases were collected from 31 provinces in China between 2004 and 2018 to estimate the association between TB risk and meteorological factors and air pollutants using a two-stage time-series analysis. The impact and lagged time of meteorological factors and air pollutants on TB risk varied greatly in different provinces and regions. Overall cumulative exposure-response summary associations across 31 provinces suggested that high monthly mean relative humidity (RH) (66.8-82.4%, percentile56-100 (P56-100)), rainfall (316.5-331.1 mm, P96-100), PM2.5 exposure concentration (93.3-145.0 μg/m3, P58-100), and low monthly mean wind speed (1.6-2.1 m/s, P0-38) increased the risk of TB incidence, with a relative risk (RR) of 1.10 (95% CI: 1.04-1.16), 1.10 (95% CI: 1.03-1.16), 2.08 (95% CI: 1.18-3.65), and 2.06 (95% CI: 1.27-3.33), and attributable risk percent (AR%) of 9%, 9%, 52%, and 51%, respectively. Conversely, high monthly average wind speed (2.3-2.9 m/s, P54-100) and mean temperature (20.2-25.3 °C, P79-96), and low monthly average rainfall (2.4-25.2 mm, P0-7) and concentration of SO2 (8.1-21.2 μg/m3, P0-16) exposure decreased the risk of TB incidence, with an overall cumulative RR of 0.92 (95% CI: 0.87-0.98), 0.74 (95% CI: 0.59-0.94), 0.87 (95% CI: 0.79-0.95), and 0.72 (95% CI: 0.56-0.93), respectively. Our study provided insights into future planning of public health interventions for TB.

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.

Interrelationships between tuberculosis and chronic obstructive pulmonary disease

PURPOSE OF REVIEW

Our objective was to review the current literature regarding socioeconomic, environmental, clinical, and immunologic factors common to chronic obstructive pulmonary disease (COPD) and tuberculosis (TB).

RECENT FINDINGS

Recent studies suggest that TB patients might be at increased risk for developing COPD. Conversely, additional prospective cohort studies have determined that COPD patients are at increased risk for active TB: a risk that appears to be partially mediated through inhaled corticosteroid use. Tobacco smoking, poverty, air pollution, and malnutrition are associated with COPD and TB. Vitamin D has been shown to prevent COPD exacerbations, but its use for preventing TB infection remains unclear. Surfactant deficiency, elevated matrix metalloproteinases, and toll-like receptor 4 polymorphisms play key roles in the pathogenesis of both diseases.

SUMMARY

Recent studies have elucidated interrelationships between COPD and TB. Future research is needed to optimize clinical and public health approaches that could mitigate risk factors contributing to both diseases.

Influence and prediction of meteorological factors on brucellosis in a northwest region of China

This paper aims to study the cumulative lag effect of meteorological factors on brucellosis incidence and the prediction performance based on Random Forest model. The monthly number of brucellosis cases and meteorological data from 2015 to 2019 in Yongchang of Gansu Province, northwest China, were used to build distributed lag nonlinear model (DLNM). The number of brucellosis cases of lag 1 month and meteorological data from 2015 to 2018 were used to build RF model to predict the brucellosis incidence in 2019. Meanwhile, SARIMA model was established to compare the prediction performance with RF model according to R² and RMSE. The results indicated that the population had a high incidence risk at temperature between 5 and 13 °C and lag between 0 and 18 days, sunshine duration between 225 and 260 h and lag between 0 and 1 month, and atmosphere pressure between 789 and 793.5 hPa and lag between 0 and 18 days. The R² and RMSE of train set and test set in RF model were 0.903, 1.609, 0.824, and 2.657, respectively, and the R² and RMSE in SARIMA model were 0.530 and 7.008. This study found significant nonlinear and lag associations between meteorological factors and brucellosis incidence. The prediction performance of RF model was more accurate and practical compared with SARIMA model.

PM2.5 and PM10 air pollution peaks are associated with emergency department visits for psychotic and mood disorders

Particulate matters with a diameter of less than 10 µm (PM10) or less than 2.5 µm (PM2.5) are major air pollutants. Their relationship to psychiatric disorders has not yet been extensively studied. We aimed to explore the relationship between PM10 and PM2.5 air pollution peaks and the daily number of emergency visits for psychotic and mood disorders. Clinical data were collected from the Emergency Department of a Paris suburb (Créteil, France) from 2008 to 2018. Air pollution data were measured by the Paris region air quality network (Airparif) and collected from public databases. Pollution peak periods were defined as days for which the daily mean level of PM was above nationally predefined warning thresholds (20 µg/m3 for PM2.5, and 50 µg/m3 for PM10), and the 6 following days. Multivariable analyses compared the number of daily visits for psychotic and mood (unipolar and bipolar) disorders according to pollution peak, using negative binomial regression. After adjustment on meteorological variables (temperature, humidity, amount of sunshine in minutes), the daily number of emergency visits for psychotic disorders was significantly higher during PM2.5 and PM10 air pollution peak periods; while the number of visits for unipolar depressive disorders was higher only during PM10 peak periods (β = 0.059, p-value = 0.034). There were no significant differences between peak and non-peak periods for bipolar disorders. Differences in the effects of PM air pollution on psychotic and mood disorders should be analyzed in further studies.

Time series analysis on association between ambient air pollutants and orofacial clefts during pregnancy in Lanzhou, China

Current studies on air pollutant exposure during pregnancy and orofacial clefts (OFCs) have inconsistent results, and few studies have investigated refined susceptible windows for OFCs. We aim to estimate association between air pollution and OFCs during the first trimester of pregnancy and identify specific susceptible windows. Birth data was obtained from Birth Defects Surveillance Network in Lanzhou from 2014 to 2019. Air pollution data and temperature data were obtained from ambient air monitoring stations and China Meteorological Data Network, respectively. A distribution lag nonlinear model (DLNM) was applied to estimate weekly-exposure-lag-response association between air pollutant levels and OFCs. The study included 320,787 perinatal infants from 2014 to 2019, of which 685 (2.14‰) were OFCs. The results demonstrated that exposure of pregnant women to aerodynamic diameter ≤ 10 μm (PM₁₀) at lag 4-5 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 4 week (RR = 1.029, 95% CI = 1.001-1.057). Exposure to sulfur dioxide (SO₂) at lag 2-4 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 3 week (RR = 1.096, 95% CI = 1.041-1.177). This study provides further evidence that exposure to air pollution increases the risk of OFCs in the first trimester of pregnancy.

Contributions of ambient temperature and relative humidity to the risk of tuberculosis admissions: A multicity study in Central China

BACKGROUND

As a communicable disease and major public health issue, many studies have quantified the associations between tuberculosis (TB) and meteorological factors with inconsistent results. The purpose of this multicenter study was to characterize the associations between ambient temperature, humidity and the risk of TB hospitalizations and to investigate potential heterogeneity.

METHOD

Data on daily hospitalizations for TB, meteorological factors and ambient air pollutants for 16 cities in Anhui Province were collected from 2015 to 2020. A distributed lag nonlinear model (DLNM) was performed to obtain the estimates of meteorological-TB relationships by cities. Then, we used the multivariate meta-regression model to pool the city-specific estimates with air pollution, demographic indicators, medical resource and latitude as potential modifiers to explore the sources of heterogeneity. Finally, we divided the whole province into three regions to validate the meteorological-TB relationships by regions.

RESULTS

The overall pooled temperature-TB association presented an approximate S-shaped curve, with relative risk (RR) peaking at 5 °C (RR = 1.536, 95% CI: 1.303-1.811) compared to the reference temperature (27 °C). Lag-response curve suggested that low temperature exposure increased the risk of TB hospitalizations at lag 0 and 1 day (lag0 day: RR = 1.136, 95% CI: 1.048-1.231, lag1 day: RR = 1.052, 95% CI: 1.023-1.082). However, the overall exposure-response curve between relative humidity and TB showed almost horizontal line with reference relative humidity to 78%. The residual heterogeneity ranged from 27.1% to 36.9%, with air pollution, latitude and medical resource explained the largest proportion.

CONCLUSION

We found that low temperature exposure is associated with an acute increased risk of TB hospitalizations in Anhui Province. The association between temperature and TB admission varies depending on air pollution, latitude, and medical resources. Since the effect of short-term exposure to humidity is not significant, further studies are supposed to focus on the long-term effect of humidity.

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

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