Exposure-response Curves Research Articles

Association of Long-Term Exposure to PM2.5 Constituents and Green Space With Arthritis and Rheumatoid Arthritis.

There is limited evidence regarding the effects of long-term exposure to PM2.5 constituents on the risk of arthritis and rheumatoid arthritis, and the interaction between PM2.5 and green space remains unclear. This study examined the relationship between long-term exposure to PM2.5 constituents and the risk of arthritis and rheumatoid arthritis, with the exposure period extending from recruitment until self-reported outcomes, death, loss to follow-up, or end of follow-up. Additionally, the study assessed whether there was an interactive effect between PM2.5 and green space on these risks. We gathered cohort data on 18,649 individuals aged ≥45years. We applied generalized linear mixed-effects models to estimate the effects of PM2.5 constituents, NDVI, and their interaction on arthritis and rheumatoid arthritis. The quantile g-computation and weighted quantile sum regression model were applied to estimate the combined effect of PM2.5 constituents. Our results showed that exposure to single and mixed PM2.5 constituents adversely affected arthritis and rheumatoid arthritis, and was mainly attributed to the black carbon component. We observed "U" or "J" shaped exposure-response curves for the effects of PM2.5, OM, NO3 - and NH4 + exposure on the development of arthritis/rheumatoid arthritis. Additionally, the odds ratio of arthritis for per interquartile range (IQR) increase in PM2.5 was 1.209 (95% CI:1.198, 1.221), per 0.1-unit decrease in NDVI was 1.091 (95% CI:1.033, 1.151), and the interaction term was 1.005 (95% CI:1.002, 1.007). These findings flesh out the existing evidence for PM2.5 constituents, NDVI and arthritis, rheumatoid arthritis, but the underlying mechanisms still require further exploration.

High sodium intake increases interstitial lung disease and pulmonary sarcoidosis based on the Global Burden of Disease study 1999–2019

This study investigated the relationships between dietary sodium intake and the incidence and prevalence of interstitial lung disease (ILD) and pulmonary sarcoidosis using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. This study assessed the strength of the abovementioned relationships via LASSO analysis and a generalized additive model with Poisson regression and determined the nonlinear and lagged effects via a distributed lag nonlinear model (DLNM). In the past three decades, global dietary sodium intake has decreased gradually. Two LASSO and generalized additive analyses both suggested that dietary sodium intake is obviously correlated with the incidence and prevalence of ILD and pulmonary sarcoidosis. The overall exposure‒response curve revealed a dose‒effect relationship between dietary sodium intake and the incidence and prevalence of ILD and pulmonary sarcoidosis. The maximum lag-specific RR of extremely high dietary sodium intake was 1.75 (95% CI: 1.61–1.91, lag 0 year) for incidence and 3.19 (95% CI: 2.24–4.53, lag 0 year) for prevalence relative to the reference. Our study suggests that dietary sodium intake is positively associated with the incidence and prevalence of ILD and pulmonary sarcoidosis. These findings may have important policy implications for dietary sodium intake-reduction strategies to decrease the burden of respiratory diseases and promote public health.

Nocturnal Artificial Light Exposure in Expectant Mothers and Risk of Congenital Glaucoma

Abstract Background While the impact of light pollution on human health is gaining recognition, its role in transmitting the effects of maternal exposure to the fetus remains unclear. This study is to investigate the association between exposure to artificial light at night (ALAN) during pregnancy and risk of congenital glaucoma. Methods All birth cohorts spanning from 2008 to 2011 in urban areas of South Korea, comprising over 90% of the total population, were identified in the Korean National Health Insurance database. Average levels of ALAN at the residential addresses of mothers during pregnancy were estimated using time-varying satellite data for a composite view of persistent night-time illumination at ∼1 km2 scale.The odd ratios (ORs) and 95% confidence intervals (CIs) of the association between residential ALAN and risk of congenital glaucoma - was computed using logistic regression. These calculations were adjusted for socio-demographic factors and area-level risk factors (night-time traffic noise and particulate matter with an aerodynamic diameter ≤ 10 μm). Results A total of 745,458 mother-father-child trios (mean [SD] age of the mothers, 32.4 [3.8] years; 387,275 [52.0%] boy) were included in the study. In fully adjusted models, an IQR (21.8 nW/cm2/sr) increase in ALAN level was associated with an OR of 1.12 (95% CI: 1.05, 1.19) for incident congenital glaucoma. The exposure-response curve demonstrated an upward slope with a threshold at approximately 62 nW/cm2/sr. Conclusions In this nationwide population-based case-control study, higher levels of residential ALAN during pregnancy were associated with increased risk of congenital glaucoma. Future studies with more detailed information on exposure, individual adaptive behaviors and potential mediators are warranted. Key messages • This study indicates an association between elevated levels of ALAN exposure in pregnant women and a heightened risk of congenital glaucoma in their offspring. • These results are consistent with a growing body of evidence underscoring the detrimental effects of ALAN on health, reinforcing its potential role as a risk factor for congenital glaucoma.

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.

Neurotransmitter Metabolism in Arsenic Exposure-Induced Cognitive Impairment: Emerging Insights and Predictive Implications.

Scholars have long been interested in the association between arsenic (As) exposure and neurological disorders; however, existing systematic epidemiological investigations are insufficient and lack the inclusion of diagnostic or predictive biological markers. This study sought to evaluate the association between As exposure and cognitive impairment and identify potential biomarkers by developing predictive models. Here, we found that logarithm (Ln)-transformed urinary As concentrations were negatively linearly related to the mini-mental state examination (MMSE) score exposure-response curves. Subsequently, we identified a unique plasma neurometabolite profile in subjects exposed to As compared with the reference group. Further analyses showed that tryptophan, tyrosine, dopamine, epinephrine, and homovanillic acid were all significantly associated with both urinary As concentrations and MMSE scores. Notably, the association between As exposure and MMSE scores was partly mediated by tryptophan, tyrosine, dopamine, and epinephrine. Importantly, an unprecedented prediction model utilizing neurotransmitters was established to assess the risk of cognitive impairment due to As exposure. A 91.1% consistency rate was found between the predicted and the actual probabilities. Additionally, machine learning models also produced highly accurate predictions. Overall, this study revealed a dose-dependent cognitive decline in As-exposed adults accompanied by a disturbance in the signature of neurotransmitter metabolites, offering new predictive insights.

Lagged effects of climate factors on bacillary dysentery in western China.

Evidence has shown that the incidence of bacillary dysentery (BD) is associated with climatic factors. However, the lagged effects of climatic factors on BD are still unclear, especially lacking research evidence from arid and semi-arid regions. Therefore, this study aims to add new insights into this research field. Spatial autocorrelation, time series analysis and spatiotemporal scans were used to perform descriptive analyses of BD cases from 2009 to 2019. On the basis of monthly data from 2015 to 2019, multivariable distributed lag non-linear models were used to investigate the lagged effects of climatic factors on BD. The hot spots for BD incidence are gradually decreasing and becoming increasingly concentrated in the southern part of Gansu Province. The maximum cumulative relative risks for monthly average temperature, sunshine duration, average relative humidity and precipitation were 3.21, 1.64, 1.55 and 1.41, respectively. The lagged effects peaked either in the current month or with a 1-month lag, and the shape of the exposure-response curve changed with the increase in maximum lag time. After stratification by per capita gross domestic product, there were differences in the effects. Climatic factors can influence the incidence of BD, with effects varying across different lag times. It is imperative to vigilantly track the disparities in the incidence of BD attributable to economic factors.

The effect of air pollutants on COPD-hospitalized patients in Lanzhou, China (2015-2019).

Lanzhou is the largest heavy industrial city in northwest China and it is a typical geographical valley-like city. However, there are few studies on the relationship between air pollutants and COPD, and their respective sample sizes are small, resulting in inconsistent results. The aim of this study is to analyze the effects of air pollutants on COPD hospitalizations in Lanzhou, China. An ecological time series study with distributed lag non-linear model (DLNM) was used for analysis. Daily COPD hospitalization data in Lanzhou from 1 January 2015 to 31 December 2019 were collected from 25 hospitals, as well as air pollutant data and meteorological data. A total of 18,275 COPD hospitalizations were enrolled. For 10 μg/m3 increase in PM2.5, PM10, SO2, NO2, and 1 mg/m3 increase in CO at lag 07 day, the RR95%CI of COPD hospitalizations were 1.048 (1.030, 1.067), 1.008 (1.004, 1.013), 1.091 (1.048, 1.135), 1.043 (1.018, 1.068), and 1.160 (1.084, 1.242), respectively. The exposure-response curves between air pollutants (except O3-8h) and COPD hospitalizations were approximately linear with no thresholds. Female, and the harmful effect of PM on aged <65 years, the effect of gaseous pollutant on those aged ≥65 years, were stronger, particularly in the cold season. Exposure to air pollutants (except O3-8h) might increase the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD. Exposure to air pollutants (except O3-8h) increases the risk of COPD hospitalizations. O3-8h has a weak and unstable effect on COPD hospital admissions. The harmful effect of gaseous pollutants (except O3-8h) on COPD-hospitalized patients was stronger than that of PM.

A time-stratified, case–crossover study of heat exposure and perinatal mortality from 16 hospitals in sub-Saharan Africa

Growing evidence suggests that extreme heat events affect both pregnant women and their infants, but few studies are available from sub-Saharan Africa. Using data from 138,015 singleton births in 16 hospitals in Benin, Malawi, Tanzania and Uganda, we investigated the association between extreme heat and early perinatal deaths, including antepartum and intrapartum stillbirths, and deaths within 24 h after birth using a time-stratified case–crossover design. We observed an association between an increase from the 75th to the 99th percentile in mean temperature 1 week (lag 0–6 d) before childbirth and perinatal mortality (odds ratio (OR) = 1.34 (95% confidence interval (CI) 1.01–1.78)). The estimates for stillbirths were similarly positive, but CIs included unity: OR = 1.29 (95% CI 0.95–1.77) for all stillbirths, OR = 1.18 (95% CI 0.71–1.95) for antepartum stillbirths and OR = 1.64 (95% CI 0.74–3.63) for intrapartum stillbirths. The cumulative exposure–response curve suggested that the steepest slopes for heat for intrapartum stillbirths and associations were stronger during the hottest seasons. We conclude that short-term heat exposure may increase mortality risks, particularly for intrapartum stillbirths, raising the importance of improved intrapartum care.

Association between long-term PM1 exposure and cognition in middle-aged and older adults: Evidence from China and the United Kingdom

Early risk detection and management are essential for cognitive preservation. While particulate matters of diameter small than 2.5 μm (PM2.5) is considered harmful to cognition, the effect of smaller, more penetrative particulate matters of diameter small than 1 μm (PM1) requires further evidence and explicit safety thresholds. In this study, we explored the effects of long-term PM1 exposure on early cognitive impairment and longitudinal cognitive changes in middle-aged and older populations. This study assessed data from two large-scale longitudinal surveys: the China Health and Retirement Longitudinal Study (CHARLS) and UK Biobank (UKB). Cross-sectional, longitudinal, and trajectory analyses were conducted to investigate the association between long-term PM1 exposure and cognition. Additionally, the exposure–response curves were fitted to determine the customized thresholds. The findings indicated that sustained PM1 exposure may lead to mild cognitive impairment, particularly at concentrations exceeding 30 and 5.6 μg·m−3 in CHARLS and UKB participants, respectively. Furthermore, we found that long-term PM1 exposure can contribute to rapid cognitive decline at concentrations exceeding 23 and 5.5 μg·m−3 in CHARLS and UKB participants, respectively. In conclusion, reducing PM1 exposure can improve the cognitive health of middle-aged and older adults.

Long-term effect of fine particulate matter constituents on reproductive hormones homeostasis in women attending assisted reproductive technologies: A population-based longitudinal study

Fine particulate matter (PM2.5) may disrupt women's reproductive hormones, posing potential reproductive risks. However, the exact compositions of PM2.5 responsible for these effects remain unclear. Our investigation explored the long-term impacts of PM2.5 constituents on reproductive hormones, based on a large longitudinal assisted reproductive cohort study in Anhui, China. We included 24,396 reproductive hormone samples from 19,845 women attending assisted reproductive technologies (ART) between 2014 and 2020. Using high-resolution gridded data (1-km resolution), we calculated the residence-specified PM2.5 constituents during the year before the month of hormone testing. Relationships between PM2.5 constituents [organic matter (OM), chloride (Cl-), sulfate (SO42-), ammonium (NH4+), black carbon, and nitrate] and reproductive hormones were investigated using the linear mixed model with subject-specific intercepts. The constituent-proportion model and the constituent-residual model were also constructed. Additionally, cubic spline analysis was used to examine the potential non-linear exposure-response relationship. We found that per interquartile range (IQR) increment in OM was associated with a 5.31 % (3.74 %, 6.89 %) increase in estradiol, and per IQR increment in Cl- and NH4+ were associated with 13.56 % (7.63 %, 19.82 %) and 9.07 % (4.35 %, 14.01 %) increases in luteinizing hormone. Conversely, per IQR increment in OM and Cl- were associated with −7.27 % (-9.34 %, −5.16 %) and −8.52 % (-10.99 %, −5.98 %) decreases in progesterone, and per IQR increment in SO42- was associated with a −9.15 % (-10.31 %, −7.98 %) decrease in testosterone. These associations were held in both proportional and residual models. Moreover, exposure-response curves for estradiol and progesterone with PM2.5 constituents exhibited approximately U-shaped. These results suggested that specific PM2.5 constituents might disrupt reproductive hormone homeostasis in women attending ART, providing new evidence for formulating PM2.5 pollution reduction strategies that could benefit women's reproductive health.

Nationwide Analysis of the Relationship Between Low Ambient Temperature and Acute Aortic Dissection-related Hospitalizations.

Acute aortic dissection (AAD) is a life-threatening cardiovascular emergency. Therefore, identifying modifiable risk factors for AAD is of great public health significance. An association between ambient temperature (AT) and AAD has been reported; however, not all findings have been elucidated. This study examined the association between AAD-related hospitalization and AT using data from the Japanese Registry of All Cardiac and Vascular Diseases Diagnostic Procedure Combination (JROAD-DPC), which is a nationwide claims-based database. This nationwide time-stratified case-crossover study evaluated data of hospitalized patients with AAD from 1,119 certified hospitals between 2012 and 2020 using the JROAD-DPC database. Conditional logistic regression and distributed lag non-linear models were used to investigate the association between average daily temperature and AAD-related hospitalization. Among the 96,812 cases analyzed. The exposure-response curve between AT and AAD-related hospitalization showed an increase in the odds ratio for lower temperatures, with a peak at timed -10°C (odds ratio: 2.28, 95% confidence interval: 1.92-2.71, compared with that at 20°C). The effects of temperature on lag days 0 and 1 were also significant.Stratified analyses showed a greater association between AT and AAD-related hospitalization for the following variables: older age (≥75 years), female sex (44.4%, the mean age ± SD was 76 ± 12 years), low body mass index (<22), winter season, and warmer regions. Low AT is associated with an increased risk of AAD-related hospitalization. Several susceptible groups are affected by cold temperatures and have a higher risk of hospitalization.

A Study of the Influence of Meteorological and Environmental Factors on Otitis Media with Effusion in Lanzhou.

In observational studies, a possible correlation between atmospheric environmental factors and the number of daily outpatient visits by Otitis media with effusion(OME) patients has been observed. However, the causal relationship is not clear.To study the relationship between the incidence of OME and meteorological factors and air pollutants in the main urban areas of Lanzhou, it is helpful to further understand the health effects of meteorological and environmental factors on OME and to prevent and treat the disease, it is of great academic and practical significance to the prevention, treatment and prognosis of diseases. The levels of AQI、PM2.5、PM10、NO2、O3、SO2、CO、AP、RH、W and T were obtained from local monitor stations. Data of patients with OME were collected from two Grade A Level hospitals in Lanzhou from January 1, 2014 to December 31, 2016. Descriptive analysis of data was carried out for the study subjects. Spearman correlation coefficients between atmospheric environmental factors and daily visits of patients with OME were calculated by SPSS statistical software. Lag effects, relative risks(RR) and exposure-response curves were calculated by generalized additive model (GAM) with R software. (1) The incidence of OME in winter and spring was more than that in summer and autumn, which was consistent with the seasonal variation of meteorological environmental factors of Lanzhou. That was, the meteorological conditions and air quality in winter and spring were poor, while in summer and autumn they were relatively good. (2) The number of male outpatients were 1.05, 1.08 and 1.09 times of female outpatients during the period 2014-2016, respectively. And aged 0-10 years old outpatients accounted for 31% of the total OME outpatients. (3) Exposure-response curve showed that PM2.5, PM10, NO2 and SO2 were positively correlated with OME, T was negatively correlated with OME. When concentration < 1mg/m3, CO was positively correlated with OME. When concentration>1mg/m3, CO was negatively correlated with OME. When concentration<30 ug/m3, O3 was positively correlated with OME. When concentration>30ug/m3, O3 was negatively correlated with OME. (4) The factors we studied could significantly affect the number of OME outpatients within 2-3 days of single lag effects, and 3-4 days of cumulative lag effects.(5) The influential factors on OME were as follows: PM2.5、NO2、SO2、O3、 CO and T. The daily average number of OME patients in different seasons was different in major region of Lanzhou city, with more in winter、spring and fewer in summer、autumn. Age and sex were the important factors affecting the daily average number of OME patients. Males were more susceptible to OME than females and children awere moresusceptible to OME than adults. The change of OME patients was related to air quality, air pressure and temperature. The worse the air quality, the higher the air pressure, the lower the temperature, the more the average daily number of OME patients. Meteorological environmental factors affected the visits of OME, and the lagging effect time of different factors were different. Most of the research factors within 3-4 days had a significant impact on the number of patients of OME. 1.The number of OME visits in the Lanzhou was more seasonal in winter and spring than in summer and fall. 2.Age and sex were the most important factors affecting the number of patients with OME. According to the prevalence of OME in Lanzhou, children were more likely to have OME than adults and men were more likely to have OME than women. 3.The number of OME patients was related to air quality, air pressure and temperature. 4.The meteorological factors have a delayed effect on the onset of OME, and the time of delayed effect is different for different factors. The single delayed effect of 2-3 days and the cumulative delayed effect of 3-4 days have a significant effect on the change of the number of patients with OME. To study the relationship between the incidence of OME and meteorological factors and air pollutants in the main urban areas of Lanzhou, it is helpful to further understand the health effects of meteorological and environmental factors on OME and to prevent and treat the disease, it is of great academic and practical significance to the prevention, treatment and prognosis of diseases.

Short-term exposure to ambient fine particulate matter constituents and myocardial infarction mortality

Short-term ambient fine particulate matter (PM2.5) exposure has been related to an increased risk of myocardial infarction (MI) death, but which PM2.5 constituents are associated with MI death and to what extent remain unclear. We aimed to explore the associations of short-term exposure to PM2.5 constituents with MI death and evaluate excess mortality. We conducted a time-stratified case-crossover study on 237,492 MI decedents in Jiangsu province, China during 2015–2021. Utilizing a validated PM2.5 constituents grid dataset at 1 km spatial resolution, we estimated black carbon (BC), organic carbon (OC), sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and chloride (Cl−) exposure by extracting daily concentrations grounding on the home address of each subject. We employed conditional logistic regression models to evaluate the exposure-response relationship between PM2.5 constituents and MI death. Overall, per interquartile range (IQR) increase of BC (lag 06-day; IQR: 1.75 μg/m3) and SO42− (lag 04-day; IQR: 5.06 μg/m3) exposures were significantly associated with a 3.91% and 2.94% increase in odds of MI death, respectively, and no significant departure from linearity was identified in the exposure-response curves for BC and SO42−. If BC and SO42− exposures were reduced to theoretical minimal risk exposure concentration (0.89 μg/m3 and 1.51 μg/m3), an estimate of 4.55% and 4.80% MI deaths would be avoided, respectively. We did not find robust associations of OC, NO3−, NH4+, and Cl− exposures with MI death. Individuals aged ≥80 years were more vulnerable to PM2.5 constituent exposures in MI death (p for difference <0.05). In conclusion, short-term exposure to PM2.5-bound BC and SO42− was significantly associated with increased odds of MI death and resulted in extensive excess mortality, notably in older adults. Our findings emphasized the necessity of reducing toxic PM2.5 constituent exposures to prevent deaths from MI and warranted further studies on the relative contribution of specific constituents.

Ambient particulate matter and chronic obstructive pulmonary disease mortality: a nationwide, individual-level, case-crossover study in China

Short-term exposure to particulate matter air pollution has been associated with the exacerbations of COPD, but its association with COPD mortality was not fully elucidated. We aimed to assess the association between short-term particulate matter exposure and the risk of COPD mortality in China using individual-level data. We derived 2.26 million COPD deaths from a national death registry database in Chinese mainland between 2013 and 2019. Exposures to fine particulate matter (PM2.5) and coarse particulate matter (PM2.5-10) were assessed by satellite-based models of a 1×1km resolution and assigned to each individual based on residential address. The associations of PM2.5 and PM2.5-10 with COPD mortality were examined using a time-stratified case-crossover design and conditional logistic regressions with distributed lag models. We further conducted stratified analyses by age, sex, education level, and season. Short-term exposures to both PM2.5 and PM2.5-10 were associated with increased risks of COPD mortality. These associations appeared and peaked on the concurrent day, attenuated and became nonsignificant after 5 or 7 days, respectively. The exposure-response curves were approximately linear without discernible thresholds. An interquartile range increase in PM2.5 and PM2.5-10 concentrations was associated with 4.23% (95% CI: 3.75%, 4.72%) and 2.67% (95% CI: 2.18%, 3.16%) higher risks of COPD mortality over lag 0-7d, respectively. The associations of PM2.5 andPM2.5-10 attenuated slightly but were still significant in the mutual-adjustment models. A larger association of PM2.5-10 was observed in the warm season. This individual-level, nationwide, case-crossover study suggests that short-term exposure to PM2.5 and PM2.5-10 might act as one of the environmental risk factors for COPD mortality. This study is supported by the National Key Research and Development Program of China (2023YFC3708304 and 2022YFC3702701), the National Natural Science Foundation of China (82304090 and 82030103), the 3-year Action Plan for Strengthening the Construction of the Public Health System in Shanghai (GWVI-11.2-YQ31), and the Science and Technology Commission of Shanghai Municipality (21TQ015).

Time series analysis of the interaction between ambient temperature and air pollution on hospitalizations for AECOPD in Ganzhou, China

This study aimed to investigate the univariate and bivariate effects of ambient temperature and air pollutants on 57,251 inpatients with AECOPD (Acute Exacerbation of Chronic Obstructive Pulmonary Disease) in Ganzhou from January 1, 2016, to December 31, 2019. We categorized the daily mean temperature and air pollutant variables based on the exposure–response curve of the Distributed Lag Non-Linear Model. Poisson regression model was used for interaction and stratification analysis. The Relative Excess Risk due to Interaction (RERI) with 95% confidence intervals (95% CI) between daily mean temperature (Tmean) and air pollutants including NO2, PM2.5, and PM10 were − 0.428 (95% CI − 0.637, − 0.218), -− 0.227 (95% CI − 0.293, − 0.161), and − 0.119 (95% CI − 0.159, − 0.079). Further stratification analysis showed the relative risk (RR) (95% CI) of high NO2 (> 33 μg/m3) at low Tmean (≤ 28 °C) was 1.119 (95% CI 1.096, 1.142). Low temperatures with high PM10 in men and high PM2.5 in women were associated with a higher risk of AECOPD hospitalization. The results indicate a higher risk of hospitalization for AECOPD when there is with high concentrations of air pollution at low temperatures.

Emergency room visits (ERVs) among occupational groups associated with ambient conditions in Taiwan.

This population-based study explored emergency room visits (ERVs) from all-causes, circulatory and respiratory diseases among different occupational groups in Taiwan associated with ambient average temperature. Daily area-age-sex specific ERVs records were obtained from the Taiwan's Ministry of Health and Welfare from 2009 to 2018. Distributed lag-nonlinear model (DLNM) was used to estimate the exposure-response relationships between daily average temperature and ERVs for all-causes, circulatory and respiratory diseases by occupational groups. Random-effects meta-analysis was used to pool the overall cumulative relative risk (RR) and 95% confidence interval (CI). The exposure-response curves showed ERVs of all-cause and respiratory diseases increased with rising temperature across all occupational groups. These effects were consistently stronger among younger (20-64 years old) and outdoor workers. In contrast, ERVs risk from circulatory diseases increased significantly during cold snaps, with a substantially higher risk for female workers. Interestingly, female workers, regardless of indoor or outdoor work, consistently showed a higher risk of respiratory ERVs during hot weather compared to males. Younger workers (20-64 years old) exhibited a higher risk of ERVs, likely due to job profiles with greater exposure to extreme temperatures. Notably, the highest risk of all-causes ERVs was observed in outdoor male laborers (union members), followed by farmers and private employees, with the lowest risk among indoor workers. Conversely, female indoor workers and female farmers faced the highest risk of respiratory ERVs. Again, female farmers with consistent outdoor exposure had the highest risk of circulatory ERVs during cold conditions. Our findings highlighted the complexity of temperature-related health risks associated with different occupational contexts. The population-level insights into vulnerable occupational groups could provide valuable comprehension for policymakers and healthcare practitioners.

Ambient air pollution and daily mortality in ten cities of India: a causal modelling study

The evidence for acute effects of air pollution on mortality in India is scarce, despite the extreme concentrations of air pollution observed. This is the first multi-city study in India that examines the association between short-term exposure to PM2·5 and daily mortality using causal methods that highlight the importance of locally generated air pollution. We applied a time-series analysis to ten cities in India between 2008 and 2019. We assessed city-wide daily PM2·5 concentrations using a novel hybrid nationwide spatiotemporal model and estimated city-specific effects of PM2·5 using a generalised additive Poisson regression model. City-specific results were then meta-analysed. We applied an instrumental variable causal approach (including planetary boundary layer height, wind speed, and atmospheric pressure) to evaluate the causal effect of locally generated air pollution on mortality. We obtained an integrated exposure-response curve through a multivariate meta-regression of the city-specific exposure-response curve and calculated the fraction of deaths attributable to air pollution concentrations exceeding the current WHO 24 h ambient PM2·5 guideline of 15 μg/m3. To explore the shape of the exposure-response curve at lower exposures, we further limited the analyses to days with concentrations lower than the current Indian standard (60 μg/m3). We observed that a 10 μg/m3 increase in 2-day moving average of PM2·5 was associated with 1·4% (95% CI 0·7-2·2) higher daily mortality. In our causal instrumental variable analyses representing the effect of locally generated air pollution, we observed a stronger association with daily mortality (3·6% [2·1-5·0]) than our overall estimate. Our integrated exposure-response curve suggested steeper slopes at lower levels of exposure and an attenuation of the slope at high exposure levels. We observed two times higher risk of death per 10 μg/m3 increase when restricting our analyses to observations below the Indian air quality standard (2·7% [1·7-3·6]). Using the integrated exposure-response curve, we observed that 7·2% (4·2%-10·1%) of all daily deaths were attributed to PM2·5 concentrations higher than the WHO guidelines. Short-term PM2·5 exposure was associated with a high risk of death in India, even at concentrations well below the current Indian PM2·5 standard. These associations were stronger for locally generated air pollutants quantified through causal modelling methods than conventional time-series analysis, further supporting a plausible causal link. Swedish Research Council for Sustainable Development.

Assessing the role of socio-economic factors in shaping the temperature-mortality exposure-response relationship in China

Non-optimal temperatures significantly influence public health. However, the role of socio-economic factors in modulating health risks associated with non-optimal temperatures varies geographically and among different populations. Thus, the meteorological, air quality, health data, and socio-economic indicators were obtained from 23 districts in North and 48 districts in East China, respectively. Employing a two-stage meta-analysis, the exposure-response relationship was constructed for temperature against mortality from non-accidental causes, cardiovascular and cerebrovascular diseases, and respiratory illnesses. Furthermore, a non-linear spline regression was applied to assess the impact of socio-economic indicators on the exposure-response relationship and predicted future risks under various Shared Socioeconomic Pathways. The results revealed that the influence of socio-economic factors on the exposure-response curve showed heterogeneity in East China and North China. In North China, the shape of the exposure-response curve changed greatly under different socio-economic levels, while it remained similar in East China. In East China, the relative risk of heat and cold exposure was reduced in regions with high GDP, high levels of public finance, good medical services, and a low proportion of the elderly population. Specifically, the risk of non-accidental deaths due to heat shows a nearly linear negative correlation with per capita GDP in East China, with a decrease of the relative risk by 0.075 for every 10 thousand yuan increase in per capita GDP. Future projections indicate that population aging plays a decisive role in shaping the exposure-response curves. Although economic growth can reduce the risk of heat-related mortality, the combined effect of population aging and economic increase results in steeper exposure-response curves in both hot and cold temperature ranges in the future. In conclusion, although spatial variations in relative risk changes still exist, enhancing the adaptive capacity of populations can mitigate health risks associated with future climate change.

Ambient temperature and cardiovascular disease-related emergency room visits in Lanzhou, China from 2013 to 2019: A time-series study.

This study assessed the links between daily mean temperature and emergency room (ER) admissions for total and cause-specific cardiovascular diseases (CVD) in Lanzhou, China from 2013 to 2019. A quasi-Poisson Generalized Additive Model (GAM) and a Distributed Lag Non-Linear Model (DLNM) were used to determine the effects of temperature on total and cause-specific cardiovascular emergency visits. The relative risks (RR) at cold (hot) temperatures were calculated by comparing the 5th (95th) centile of temperature with the minimum morbidity temperature (MMT). Exposure-response curves demonstrating an inverted U-shape or an irregular M-shape association were observed between temperature and total and cause-specific CVD. The study found that both cold and hot temperatures had negative impacts on emergency room visits for various cardiovascular diseases. For people with total CVD, heart rhythm disturbances (HRD), or cerebrovascular diseases (CD), females were more sensitive to temperature than males, while for ischemic heart disease (IHD) and heart failure (HF), males were more vulnerable to temperature. The < 65 years old with total CVD, IHD, HRD, or CD was more susceptible to the effects of temperature. The results indicated that the relationship between temperature and total and cause-specific CVD was nonlinear, and susceptibility to temperature varied across disease subtype, gender, and age.

Coarse particulate air pollution and mortality in a multidrug-resistant tuberculosis cohort

RationaleThe association between ambient coarse particulate matter (PM2.5–10) and mortality in multi-drug resistant tuberculosis (MDR-TB) patients has not yet been studied. The modifying effects of temperature and humidity on this association are completely unknown. ObjectivesTo evaluate the effects of long-term PM2.5–10 exposures, and their modifications by temperature and humidity on mortality among MDR-TB patients. MethodsA Chinese cohort of 3469 MDR-TB patients was followed up from diagnosis until death, loss to follow-up, or the study's end, averaging 2567 days per patient. PM2.5–10 concentrations were derived from the difference between PM10 and PM2.5. Cox proportional hazard models estimated hazard ratios (HRs) per 3.74 μg/m3 (interquartile range, IQR) exposure to PM2.5–10 and all-cause mortality for the full cohort and individuals at distinct long-term and short-term temperature and humidity levels, adjusting for other air pollutants and potential covariates. Exposure-response relationships were quantified using smoothed splines. ResultsHazard ratios of 1.733 (95% CI, 1.407, 2.135) and 1.427 (1.114, 1.827) were observed for mortality in association with PM2.5–10 exposures for the full cohort under both long-term and short-term exposures to temperature and humidity. Modifying effects by temperature and humidity were heterogenous across sexes, age, treatment history, and surrounding environment measured by greenness and nighttime light levels. Nonlinear exposure-response curves suggestes a cumulative risk of PM2.5–10-related mortality starting from a low exposure concentration around 15 μg/m3. ConclusionLong-term exposure to PM2.5–10 poses significant harm among MDR-TB patients, with effects modified by temperature and humidity. Immediate surveillance of PM2.5–10 is crucial to mitigate the progression of MDR-TB severity, particularly due to co-exposures to air pollution and adverse weather conditions.