Association of Ambient Particulate Matter Pollution of Different Sizes With In-Hospital Case Fatality Among Stroke Patients in China

Air pollution associated with cardiopulmonary disease and mortality among participants with preserved ratio impaired spirometry

BACKGROUND

Epidemiological evidence regarding the association between air pollutants and cardiopulmonary disease, mortality in individuals with preserved ratio impaired spirometry (PRISm), and their combined effects remains unclear.

METHODS

We followed 36,149 participants with PRISm in the UK Biobank study. Annual concentrations of PM2.5, PM10, NO2, NOx, and SO2 at residential addresses were determined using a bilinear interpolation method, accounting for address changes. A multistate model assessed the dynamic associations between air pollutants and cardiopulmonary diseases and mortality in PRISm. Quantile g-computation was used to investigate the joint effects of air pollutants.

RESULTS

Long-term exposure to PM2.5, PM10, NO2, NOx, and SO2 was significantly associated with the risk of cardiopulmonary disease in PRISm. The corresponding hazard ratios (HRs) [95 % confidence intervals (95 % CIs)] per interquartile range (IQR) were 1.49 (1.43, 1.54), 1.52 (1.46, 1.57), 1.34 (1.30, 1.39), 1.30 (1.26, 1.34), and 1.44 (1.41, 1.48), respectively. For mortality, the corresponding HRs (95 % CIs) per IQR were 1.36 (1.25, 1.47), 1.35 (1.24, 1.46), 1.27 (1.18, 1.36), 1.23 (1.15, 1.31), and 1.29 (1.20, 1.39), respectively. In PRISm, quantile g-computation analysis demonstrated that a quartile increase in exposure to a mixture of all air pollutants was positively associated with the risk of cardiopulmonary disease and mortality, with HRs (95 % CIs) of 1.84 (1.76, 3.84) and 1.45 (1.32, 1.57), respectively.

CONCLUSION

Long-term individual and joint exposure to air pollutants (PM2.5, PM10, NO2, NOx, and SO2) might be an important risk factor for cardiopulmonary disease and mortality in high-risk populations with PRISm.

Air pollutants and the risk of incident hepatobiliary diseases: A large prospective cohort study in the UK Biobank

The association between air pollutants and hepatobiliary pancreatic diseases remains inconclusive. This study analyzed up to 247,091 participants of White European ancestry (aged 37 to 73 years at recruitment) from the UK Biobank, a large-scale prospective cohort with open access. An air pollution score was utilized to assess the combined effect of PM2.5, PM2.5-10, PM10, NO2, and NOX on total hepatobiliary pancreatic diseases, liver diseases, cholecyst diseases, and pancreatic diseases. Cox proportional hazard models were employed to evaluate the relationships between air pollutants and the incidence of these diseases. Restricted cubic spline regressions were used to examine the dose-response association between air pollutants and the risk of hepatobiliary pancreatic diseases. We identified 4865 cases of total hepatobiliary pancreatic diseases, over a median follow-up of 10.86 years. The air pollution scores were moderately associated with increased liver disease risk (HR = 1.009, 95 % CI: 1.004, 1.014), but not with cholecyst and pancreatic diseases. Among the individual air pollutants, PM2.5 (HR = 1.069, 95 % CI: 1.025, 1.115) and PM10 (HR = 1.036, 95 % CI: 1.011, 1.061) significantly increased liver disease risk. Males showed a higher risk of liver diseases with PM2.5 (HR = 1.075, 95 % CI: 1.015, 1.139). Additionally, individuals with overweight (HR = 1.125, 95 % CI: 1.052, 1.203), age ≥ 60 and ≤73 (HR = 1.098, 95 % CI: 1.028, 1.172), and alcohol intake ≥ 14 unit/week (HR = 1.078, 95 % CI: 1.006, 1.155) had a higher risk of developing liver diseases at high expose to PM2.5. This study suggests that prolonged exposure to ambient air pollutants may elevate the risk of liver diseases.

Daily diurnal temperature range associated with emergency ambulance calls: a nine-year time-series study

Background

Diurnal temperature range (DTR) is associated with the increased risk of morbidity and mortality. However, the relationship between DTR and emergency ambulance calls (EACs), which more accurately and immediately reflect the health impacts of temperature changes, remains underexplored in China.

Methods

We collected daily data on EACs and meteorological factors from 2009 to 2017 in Guangzhou, China. DTR, representing the temperature range within a day, was calculated by subtracting the minimum temperature from the maximum temperature for each day. Generalized additive models were used to estimate the association between DTR and EACs for all-cause, cardiovascular diseases, and respiratory diseases. Additionally, subgroup and sensitivity analyses were conducted in our study.

Results

We found significant associations between daily DTR and EACs. The excess risks (ERs) were 0.47% (95% CI: 0.14, 0.81%) for all-cause EACs, 0.94% (95% CI: 0.46, 1.43%) for cardiovascular-related EACs, and 1.31% (95% CI: 0.76, 1.86%) for respiratory -related EACs at lag01, respectively. Subgroup analyses indicated that these associations were notably stronger among the older, males, and during the warm season. Specifically, there was an increase of 1.16% (95% CI: 0.59, 1.74%) in cardiovascular-related EACs among the older adult, compared to 0.45% (95% CI: -0.21, 1.12%) among those younger than 65 years. Among males, the increase was 1.39% (95% CI: 0.79, 1.99%), compared to 0.13% (95% CI: -0.53, 0.79%) among females. During the warm season, the increase was 1.53% (95% CI: 0.74, 2.34%), compared to 0.75% (95% CI: 0.14, 1.37%) during the cold season.

Conclusion

DTR might increase the risk of daily all-cause, cardiovascular-related, and respiratory-related EACs in Guangzhou, China. The associations were particularly strong among older adults, males, and during the warm season. Implementing public health policies is essential to mitigate the adverse health effects of DTR.

PM2.5 chemical components are associated with in-hospital case fatality among acute myocardial infarction patients in China

Recent studies have linked the cardiovascular events with the exposure to ambient fine particulate matter (PM2.5); however, the impact of PM2.5 chemical components on acute myocardial infarction (AMI) case fatality remains poorly understood. To address this gap, we included 178,340 hospitalised patients with AMI utilising the inpatient discharge database from Sichuan, Shanxi, Guangxi, and Guangdong, China spanning 2014-2019. We evaluated exposure to PM2.5 and its components (black carbon (BC), organic matter (OM), sulphate (SO42-), nitrate (NO3-), and ammonium (NH4+)) using bilinear interpolation based on the patient's residential address. We used mixed-effects logistic regression models to investigate the associations of PM2.5 and its five components with in-hospital AMI case fatality. Per interquartile range (IQR) increment in short-term exposure (7-day average) to overall PM2.5 (odds ratio (OR): 1.086, 95 % confidence interval (CI): 1.045-1.128), SO42-(1.063, 1.024-1.104), BC (1.055, 1.023-1.089), OM (1.052, 1.019-1.086, and NO3- (1.045, 1.003-1.089) were significantly associated with high risk of in-hospital AMI case fatality. The ORs per IQR increment in long-term exposure (annual average) were 1.323 (95 % CI: 1.255-1.394) for PM2.5, followed by BC (1.271, 1.210-1.335), OM (1.243, 1.188-1.300), SO42- (1.212, 1.157-1.270), NO3- (1.116, 1.075-1.159), and NH4+ (1.068, 1.031-1.106). Our study suggests that PM2.5 chemical components might be important risk factors for in-hospital AMI case fatality, highlighting the importance of targeted reduction of PM2.5 emissions, particularly BC, OM, and SO42-.

Analysis of readmission and hospitalization expenditures of patients with ischemic stroke suffering from different comorbidities

Background

The comorbidities of ischemic stroke (IS) are increasing worldwide. This study aimed to quantitatively assess the effect of different types of comorbidity on readmission and hospitalization expenditures of patients with IS.

Methods

A retrospective observational study was conducted from the basic insurance claims database of a large city in China, between January 1, 2018, and May 31, 2022. We identified patients with IS aged 18 years and over, who experienced the first episode of IS and had one-year follow-up records. This study divided eighteen different comorbid conditions into two categories (concordant comorbidity and discordant comorbidity) and the IS patients were further categorized into four groups. Multivariable logistic regression models and generalized linear models with log-link and gamma distribution were to estimate the effect of different comorbidity groups on one-year readmission rates and annual hospitalization expenditures.

Results

In total, 99,649 adult patients with IS were identified. Approximately 94.0 % of patients with IS had at least one comorbidity, and 63.8 % reported concordant comorbidity only. Patients with IS had a readmission rate of 26.7 %, and the mean of annual hospitalization expenditure and annual hospitalization out-of-pocket expenditure (OOPE) were 28086.6 Chinese Yuan (CNY) and 8267.3 CNY, respectively. After adjustment for covariates, the concordant comorbidity-only group had the highest readmission rate, annual hospitalization expenditure, and OOPE compared with the other groups, furthermore, these results increased as the number of comorbidity increased and had statistically significant positive associations.

Conclusions

The readmission and annual hospitalization expenditures of patients with IS were associated with different comorbidities. Concordant comorbidity increased hospital readmission risk and health expenditures. To better manage the comorbidities of patients with IS, especially concordant comorbidities, it is necessary to establish a routine care strategy specifically for comorbid conditions.

Estimation of couple fecundity in the general population and the association with monthly time-varying ambient particulate matter exposure in low- and middle-income countries: A population-based multi-center epidemiological study

BACKGROUND

Declining total fertility rates have been observed in low- and middle-income countries (LMICs). However, it remains unclear if this trend is related to a reduction in fecundity of general population. Research evidence on contributing factors to fecundity reduction is also limited. We aimed to first estimate couple fecundity in LMICs and then investigate its association with ambient particulate matter (PM) exposure.

METHODS

Using the information from Demographic and Health Surveys between 2003 and 2019, we estimated median time to pregnancy (TTP) and infertility prevalence across 30 LMICs, by employing a current duration approach. Individual PM (PM1, PM2.5, and PM10) exposure during the period of 'at risk' of pregnancy was assessed by months. An accelerated failure model was used to elucidate the association between monthly time-varying PM exposure and TTP. Subsequently, we estimated the prolonged TTP attributable to PM exposures above the World Health Organization (WHO)'s recommended air quality level in 2021.

RESULTS

Within the study regions, median TTP ranged from 6.90 (95 % CI 6.02-7.87) months in Latin America & Caribbean to 10.29 (95 % CI 9.28-11.36) months in East Asia & Pacific, with corresponding infertility prevalence varying from 33 % (95 % CI 29 %-36 %) to 44 % (95 % CI 41 %-48 %). Our estimations indicated that TTP was 1.08 (95 % CI: 0.99-1.18), 1.12 (95 % CI 1.06-1.19), and 1.05 (95 % CI 1.03-1.07) times longer for every 10 μg/m3 increment in PM1, PM2.5, and PM10, respectively. The prolonged TTP attributable to PM exposures surpassing the WHO guideline ranged from 0.11 to 2.81 months across the studied regions.

DISCUSSION

Ambient particulate matter is identified as a potential contributing factor to impaired fecundity in general population of LMICs. The findings underscore the importance of coordinated efforts to control ambient air pollution to mitigate the risk of fecundity reduction among the general population.

Association between long-term ozone exposure and readmission for chronic obstructive pulmonary disease exacerbation

The relationship between long-term ozone (O₃) exposure and readmission for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) remains elusive. In this study, we collected individual-level information on AECOPD hospitalizations from a standardized electronic database in Guangzhou from January 1, 2014, to December 31, 2015. We calculated the annual mean O₃ concentration prior to the dates of the index hospitalization for AECOPD using patients' residential addresses. Employing Cox proportional hazards models, we assessed the association between long-term O₃ concentration and the risk of AECOPD readmission across several time frames (30 days, 90 days, 180 days, and 365 days). We estimated the disease and economic burden of AECOPD readmissions attributable to O₃ using a counterfactual approach. Of the 4574 patients included in the study, 1398 (30.6%) were readmitted during the study period, with 262 (5.7%) readmitted within 30 days. The annual mean O₃ concentration was 90.3 μg/m3 (standard deviation [SD] = 8.2 μg/m3). A 10-μg/m3 increase in long-term O₃ concentration resulted in a hazard ratio (HR) for AECOPD readmission within 30 days of 1.28 (95% confidence interval [CI], 1.09 to 1.49), with similar results for readmission within 90, 180, and 365 days. Older patients (aged 75 years or above) and males were more susceptible (HR, 1.33; 95% CI, 1.10-1.61 and HR, 1.29; 95% CI, 1.09-1.53, respectively). The population attributable fraction for 30-day readmission due to O₃ exposure was 29.0% (95% CI, 28.4%-30.0%), and the attributable mean cost per participant was 362.3 USD (354.5-370.2). Long-term exposure to elevated O₃ concentrations is associated with an increased risk of AECOPD readmission, contributing to a significant disease and economic burden.

A stronger association of mental disorders with smaller particulate matter and a modifying effect of air temperature

Mental disorders (MDs) can be triggered by adverse weather conditions and particulate matter (PM) such as PM2.5 and PM10 (aerodynamic diameter ≤2.5 μm and ≤10 μm). However, there is a dearth of evidence on the role of smaller PM (e.g. PM1, aerodynamic diameter ≤1 μm) and the potential modifying effects of weather conditions. We aimed to collect daily data on emergency department visits and hospitalisations for schizophrenia-, mood-, and stress-related disorders in a densely populated Chinese city (Hefei) between 2016 and 2019. A time-stratified case-crossover analysis was used to examine the short-term association of MDs with PM1, PM2.5, and PM10. The potential modifying effects of air temperature conditions (cold and warm days) were also explored. The three size-fractioned PMs were all associated with an increased risk of MDs; however, the association differed between emergency department visit and hospitalisation. Specifically, PM1 was primarily associated with an increased risk of emergency department visit, whereas PM2.5 was primarily associated with an increased risk of hospitalisation, and PM10 was associated with an increased risk of both emergency department visit and hospitalisation. The PM-MD association appeared to be greatest (although not significant) for PM1 (odds ratio range: 1.014-1.055), followed by PM2.5 (odds ratio range: 1.001-1.009) and PM10 (odds ratio range: 1.001-1.006). Furthermore, the PM-MD association was observed on cold days; notably, the association between PM and schizophrenia-related disorders was significant on both cold and warm days. Our results suggest that the smaller the PM, the greater the risk of MDs, and that the PM-MD association could be determined by air temperature conditions.

Associations between air pollution and the risk of first admission and multiple readmissions for cardiovascular diseases

OBJECTIVES

We aimed to investigate the associations between air pollutants and the risk of admission and multiple readmission events for cardiovascular disease (CVD).

METHODS

A total of 285 009 participants free of CVD at baseline from the UK Biobank were included in this analysis. Four major cardiovascular admission events were identified during the follow-up: chronic ischaemic heart disease (CIHD), cerebrovascular disease, atrial fibrillation and heart failure. We used Prentice, Williams and Peterson-Total Time model to examine the association between ambient air pollution and first admission, as well as multiple readmissions for these CVDs.

RESULTS

During a median follow-up of 12 years, 17 176 (6.03%) participants were hospitalised with CVDs, and 6203 (36.11%) patients with CVD had subsequent readmission events for CVDs. We observed significant associations between air pollution and both first admission and readmission for CVDs, with generally stronger associations on readmission for cardiovascular events. For example, the adjusted HRs for the first admission and subsequent readmission for cerebrovascular disease were 1.130 (95% CI 1.070 to 1.194) and 1.270 (95% CI 1.137 to 1.418) for each IQR increase of particulate matter with a diameter ≤2.5 µm. The corresponding HRs for CIHD were 1.060 (95% CI 1.008 to 1.114) and 1.120 (95% CI 1.070 to 1.171). Sex stratified analyses showed that the associations were generally more pronounced among females than males.

CONCLUSION

This study provides evidence that ambient air pollutants might play an important role in both first admission and readmission for cardiovascular events. In addition, patients with pre-existing CVDs may be more vulnerable to air pollution compared with healthy population.

Ambient fine particulate matter chemical composition associated with in-hospital case fatality, hospital expenses, and length of hospital stay among patients with heart failure in China

*Joint senior authorship.

BACKGROUND

Previous studies have observed the adverse effects of ambient fine particulate matter pollution (PM2.5) on heart failure (HF). However, evidence regarding the impacts of specific PM2.5 components remains scarce.

METHODS

We included 58 129 patients hospitalised for HF between 2013 and 2017 in 11 cities of Shanxi, China from inpatient discharge database. We evaluated exposure to PM2.5 and its components ((sulphate (SO42-), nitrate (NO3-), ammonium (NH4+), organic matter (OM) and black carbon (BC)), along with meteorological factors using bilinear interpolation at each patients' residential address. We used multivariable logistic and linear regression models to assess the associations of these components with in-hospital case fatality, hospital expenses, and length of hospital stay.

RESULTS

Increase equivalents to the interquartile range (IQR) in OM (odds ratio (OR) = 1.13; 95% confidence interval (CI) = 1.02, 1.26) and BC (OR = 1.14; 95% CI = 1.02, 1.26) were linked to in-hospital case fatality. Per IQR increments in PM2.5, SO42-, NO3-, OM, and BC were associated with cost increases of 420.62 (95% CI = 285.75, 555.49), 221.83 (95% CI = 96.95, 346.71), 214.93 (95% CI = 68.66, 361.21), 300.06 (95% CI = 176.96, 423.16), and 303.09 (95% CI = 180.76, 425.42) CNY. Increases of 1 IQR in PM2.5, SO42-, OM, and BC were associated with increases in length of hospital stay of 0.10 (95% CI = 0.02, 0.19), 0.09 (95% CI = 0.02, 0.17), 0.10 (95% CI = 0.03, 0.17), and 0.16 (95% CI = 0.08, 0.23) days.

CONCLUSIONS

Our findings suggest that ambient SO42-, OM, and BC might be significant risk factors for HF, emphasising the importance of formulating customised guidelines for the chemical constituents of PM and controlling the emissions of the most dangerous components.

Predicting preterm birth using auto-ML frameworks: a large observational study using electronic inpatient discharge data

Background

To develop and compare different AutoML frameworks and machine learning models to predict premature birth.

Methods

The study used a large electronic medical record database to include 715,962 participants who had the principal diagnosis code of childbirth. Three Automatic Machine Learning (AutoML) were used to construct machine learning models including tree-based models, ensembled models, and deep neural networks on the training sample (N = 536,971). The area under the curve (AUC) and training times were used to assess the performance of the prediction models, and feature importance was computed via permutation-shuffling.

Results

The H2O AutoML framework had the highest median AUC of 0.846, followed by AutoGluon (median AUC: 0.840) and Auto-sklearn (median AUC: 0.820), and the median training time was the lowest for H2O AutoML (0.14 min), followed by AutoGluon (0.16 min) and Auto-sklearn (4.33 min). Among different types of machine learning models, the Gradient Boosting Machines (GBM) or Extreme Gradient Boosting (XGBoost), stacked ensemble, and random forrest models had better predictive performance, with median AUC scores being 0.846, 0.846, and 0.842, respectively. Important features related to preterm birth included premature rupture of membrane (PROM), incompetent cervix, occupation, and preeclampsia.

Conclusions

Our study highlights the potential of machine learning models in predicting the risk of preterm birth using readily available electronic medical record data, which have significant implications for improving prenatal care and outcomes.

Effect modification of dietary diversity on the association of air pollution with incidence, complications, and mortality of type 2 diabetes: Results from a large prospective cohort study

BACKGROUND

It remains unknown whether the dietary diversity score (DDS) could modify the association of long-term exposure to individual air pollutants and the mixture of various pollutants with the incidence, complications, and mortality of type 2 diabetes (T2D).

METHODS

We included 162,579 participants from the UK Biobank who had ≥ one 24-h dietary assessment and were free of diabetes or diabetes complications before their last response date of the 24-h dietary assessment. Exposure to benzene, NOx, NO2, SO2, PM10, and PM2.5 was estimated at each participant's residential location using a bilinear interpolation algorithm based on air dispersion models on a 1 km × 1 km grid. The DDS was calculated based on repeated 24-h dietary assessments. The outcomes were the incidence, complications, and mortality of T2D. Associations of individual pollutants and multiple pollutants mixtures with outcomes were assessed using Cox proportional hazards regression models and the quantile g-computation approach, respectively. We further stratified these analyses by DDS.

RESULTS

During a median of 10.1 years of follow-up, 2978 participants developed incident T2D, 1181 developed T2D complications, and 242 died due to T2D. Long-term single-pollutant and multi-pollutant exposure were associated with elevated risk of incidence, complications, and mortality of T2D. For example, for incident T2D, the hazard ratio and 95 % confidence interval for each quantile increase were 1.155 (1.095, 1.215) for the air pollution mixture. We observed significant interactions between air pollution (benzene, NOx, NO2, PM10, PM2.5, and the air pollution mixture) and DDS (P-interaction <0.05), with the corresponding associations being significantly weaker in adults with high DDS than in those with low DDS.

CONCLUSION

Higher dietary diversity may attenuate the harmful impacts of air pollution on T2D-related outcomes. A higher diversity diet could be used to prevent the onset and progression of T2D induced by long-term exposure to various air pollutants.

Ambient particulate matter and in-hospital case fatality of acute myocardial infarction: A multi-province cross-sectional study in China

The acute myocardial infarction (AMI) outcomes have been extensively linked with ambient particulate matter (PM). However, whether a smaller particle has greater impact and the consequent attributable burden associated with PM of different sizes remain unclear. We conducted a multi-province cross-sectional study among AMI patients using the inpatient discharge datasets from four Chinese provinces (Shanxi, Sichuan, Guangxi, and Guangdong) from 2014 to 2019. Ambient PM exposure for each patient was assessed using the ChinaHighAirPollutants dataset. We employed the mixed-effects logistic regression models to evaluate the association of PM of different sizes (PM1, PM2.5, PM10) on in-hospital case fatality. The potential reducible fractions in in-hospital case fatality were estimated through counterfactual analyses. Of 177,749 participants, 125,501 (70.6 %) were male and the in-hospital case fatality rate was 4.9%. For short-term (7-day average) exposure, the odds ratios (ORs) for PM1, PM2.5, and PM10 (per 10 µg/m3) were 1.052 (95 % confidence interval [CI], 1.032-1.071), 1.026 (95 % CI, 1.014-1.037), and 1.016 (95% CI, 1.008-1.024), respectively. The estimated ORs for long-term exposure (annual average) were 1.303 (95 % CI, 1.252-1.356) for PM1, 1.209 (95 % CI, 1.178-1.241) for PM2.5, 1.157 (95 % CI, 1.134-1.181) for PM10. Short-term exposure to PM1 showed the highest potential reducible fraction (8.5 %, 95 % CI, 5.0-11.7 %), followed by PM2.5 and PM10, while the greatest potential reducible fraction of long-term exposure was observed in PM10 (30.9 %, 95 % CI, 27.2-34.4%), followed by PM2.5 and PM1. In summary, PM with smaller size had a more pronounced impact on in-hospital AMI case fatality, with PM1 exhibiting greater effects than PM2.5 and PM10. Substantial health benefits for AMI patients could be achieved by mitigating ambient PM exposure.

Short-Term Ambient Air Pollution and Urticaria in Guangzhou, China: Estimating the Association and Population Attributable Fraction

Limited evidence is available regarding the association between acute exposure to ambient air pollutants and the risk of urticaria, even though the skin is an organ with direct contact with the external environment. This study utilized generalized additive models to investigate the association between particulate matter with an aerodynamic diameter smaller than 10 μm (PM10) and 2.5 μm (PM2.5), nitrogen dioxide (NO2) and sulfur dioxide (SO2), and daily outpatient visits for urticaria in Guangzhou, China from 2013 to 2017. We also estimated the attributable fraction of urticaria outpatient visits due to air pollution. A total of 216,648 outpatient visits due to urticaria occurred during the study period. All air pollutants were significantly associated with an increased excess risk of urticaria. Each 10 μg/m3 increase in PM2.5, PM10, NO2, and SO2 was associated with an increase of 1.23% (95% CI: 0.42%, 2.06%), 0.88% (95% CI: 0.28%, 1.49%), 3.09% (95% CI: 2.16%, 4.03%), and 2.82% (95% CI: 0.93%, 4.74%) in hospital visits for urticaria at lag05, respectively. It was estimated that 3.77% (95% CI: 1.26%, 6.38%), 1.91% (95% CI: 0.60%, 3.26%), 6.36% (95% CI: 4.38%, 8.41%), and 0.08% (95% CI: 0.03%, 0.14%) of urticaria outpatient visits were attributable to PM2.5, PM10, NO2, and SO2 using the World Health Organization's air quality guideline as the reference. Relatively stronger associations were observed during the cold season. This study indicates that short-term air pollution may play a significant role in outpatient visits for urticaria, and that such relationships could be modified by season.

Ambient air pollution associated with incident asthma, subsequent cardiovascular disease and death: A trajectory analysis of a national cohort

No previous study has examined the impact of air pollution on the cardiovascular disease (CVD) trajectory, especially among asthmatic subjects. Based on the UK Biobank cohort, we retrieved 292,227 adults free of asthma and CVD aged 37-73 years at recruitment (2006-2010). Annual mean concentrations of particulate matter (PM10 and PM2.5) and nitrogen oxides (NO2 and NOx) were assessed at each individual's addresses. We used multi-state models to estimate the associations of air pollution with the trajectory from healthy to incident asthma, subsequent CVD, and death. During a median follow-up of 11.7 years, a total of 6338 (2.2%) participants developed asthma, among which, 638 (10.1%) subsequently proceeded to CVD. We observed significant impacts of various air pollutants on the CVD dynamic transitions, with a more substantial effect of particulate matter pollutants than gaseous air pollutants. For example, the hazard ratios (95% confidence intervals) for per interquartile range increase in PM2.5 and PM10 were 1.28 (1.13, 1.44) and 1.27 (1.13, 1.43) for transitions from incident asthma to subsequent CVD. In conclusion, long-term air pollution exposure could affect the CVD trajectory. Distinguishing the effect of air pollutants on CVD transition stages has great significance for CVD health management and clinical prevention, especially among asthma patients.

Dynamic association of ambient air pollution with incidence and mortality of pulmonary hypertension: A multistate trajectory analysis

BACKGROUND

There is little evidence regarding the association between ambient air pollution and incidence and the mortality of pulmonary hypertension (PH).

METHODS

We included 494,750 participants at baseline in the UK Biobank study. Exposures to PM2.5, PM10, NO2, and NOx were estimated at geocoded participants' residential addresses, utilizing pollution data provided by UK Department for Environment, Food and Rural Affairs (DEFRA). The outcomes were the incidence and mortality of PH. We used multivariate multistate models to investigate the impacts of various ambient air pollutants on both incidence and mortality of PH.

RESULTS

During a median follow-up of 11.75 years, 2517 participants developed incident PH, and 696 died. We observed that all ambient air pollutants were associated with increased incidence of PH with different magnitudes, with adjusted hazard ratios (HRs) [95% confidence intervals (95% CIs)] for each interquartile range (IQR) increase of 1.73 (1.65, 1.81) for PM2.5, 1.70 (1.63, 1.78) for PM10, 1.42 (1.37, 1.48) for NO2, and 1.35 (1.31, 1.40) for NOx. Furthermore, PM2.5, PM10, NO2 and NO2 influenced the transition from PH to death, and the corresponding HRs (95% CIs) were 1.35 (1.25, 1.45), 1.31 (1.21, 1.41), 1.28 (1.20, 1.37) and 1.24 (1.17, 1.32), respectively.

CONCLUSION

The results of our study indicate that exposure to various ambient air pollutants might play key but differential roles in both the incidence and mortality of PH.

Stroke burden and attributable risk factors in China, 1990-2019

Background and purpose

Understanding the temporal trends of stroke burden and its attributable risk factors are essential for targeted prevention strategies. We aimed to describe the temporal trends and attributable risk factors of stroke in China.

Methods

Data on the stroke burden [incidence, prevalence, mortality, and disability-adjusted life years (DALYs)] and the population-attributable fraction for stroke risk factors from 1990 to 2019 were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We analyzed trends in the burden of stroke and its attributable risk factors from 1990 to 2019, and the characteristics of stroke-attributable risk factors by sex, age group, and stroke subtype.

Results

From 1990 to 2019, the age-standardized incidence, mortality, and DALY rates for total stroke decreased by 9.3% (3.3, 15.5), 39.8% (28.6, 50.7), and 41.6% (30.7, 50.9) respectively. The corresponding indicators all decreased for intracerebral hemorrhage and subarachnoid hemorrhage. The age-standardized incidence rate of ischemic stroke increased by 39.5% (33.5 to 46.2) for male patients and by 31.4% (24.7 to 37.7) for female patients, and the age-standardized mortality and DALY rates remained almost unchanged. The three leading stroke risk factors were high systolic blood pressure, ambient particulate matter pollution, and smoking. High systolic blood pressure has remained the leading risk factor since 1990. The attributable risk of ambient particulate matter pollution shows a clear upward trend. Smoking and alcohol consumption were important risk factors for men.

Conclusion

This study reinforced the findings of an increased stroke burden in China. Precise stroke prevention strategies are needed to reduce the disease burden of stroke.

Dietary Diversity and Inflammatory Diet Associated with All-Cause Mortality and Incidence and Mortality of Type 2 Diabetes: Two Prospective Cohort Studies

A higher dietary diversity score (DDS) and a lower energy-adjusted dietary inflammatory index (E-DII) may be associated with lower risks of type 2 diabetes (T2D) and mortality. This cohort study aimed to investigate the associations of DDS and E-DII with all-cause mortality, incidence of T2D, and mortality of T2D, as well as the joint effects of these two dietary factors. A total of 181,360 participants without all types of diabetes at baseline from the UK Biobank and 42,139 participants from the US NHANES were included. Cox proportional hazards models were used to assess the associations of DDS and E-DII with outcomes. In the UK Biobank data, 8338 deaths, 3416 incident T2D cases, and 353 T2D deaths occurred during a median follow-up of 12.5 years. In the US NHANES data, 6803 all-cause deaths and 248 T2D-specific deaths were recorded during a median follow-up of 9.6 years. We observed that higher DDS and lower E-DII were significantly associated with lower risks of total mortality and incident T2D. Compared with low DDS, the hazard ratios (HRs) and 95% confidence intervals (CIs) of high DDS were 0.69 (0.64, 0.74) for all-cause mortality, 0.79 (0.70, 0.88) for incident T2D in the UK Biobank, and 0.69 (0.61, 0.78) for all-cause mortality in the US NHANES. Compared with participants in tertile 3 of E-DII, those in tertile 1 had a lower risk of overall death [HR 0.86 (95% CI: 0.81, 0.91) in UK Biobank; 0.83 (0.77, 0.88) in US NHANES] and incident T2D [0.86 (0.79, 0.94)] in UK Biobank. No evidence was observed of the interactive effects of DDS and E-DII on either all-cause mortality or the incidence and mortality of T2D. There was no significant association found between any exposure and T2D mortality in this study. In conclusion, our results revealed that higher DDS and lower E-DII were associated with both total mortality and incident T2D in UK and US adults.

Air pollution and stroke hospitalization in the Beibu Gulf Region of China: A case-crossover analysis

BACKGROUND

The relationship between air pollution and stroke has been extensively studied, however, the evidence regarding the association between air pollution and hospitalization due to stroke and its subtypes in coastal areas of China is limited.

OBJECTIVE

To estimate the associations between air pollution and hospitalizations of stroke and its subtypes in the Beibu Gulf Region of China.

METHODS

We conducted a time-stratified case-crossover study in 15 cities in Beibu Gulf Region in China from 2013 to 2016. Exposures to PM₁, PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO on the case and control days were assessed at residential addresses using bilinear interpolation. Conditional logistic regressions were constructed to estimate city-specific associations adjusting for meteorological factors and public holidays. Meta-analysis was further conducted to pool all city-level estimates.

RESULTS

There were 271,394 case days and 922,305 control days. The odds ratios (ORs) for stroke hospitalizations associated with each interquartile range (IQR) increase in 2-day averages of SO₂ (IQR: 10.8 µg/m³), NO₂ (IQR: 11.2 µg/m³), and PM₁₀ (IQR: 37 µg/m³) were 1.047 (95 % CI [confidence interval]: 1.015-1.080), 1.040 (95 % CI: 1.027-1.053), and 1.018 (95 % CI: 1.004-1.033), respectively. The associations with hospitalizations of ischemic stroke were significant for all seven pollutants, while the association with hemorrhagic stroke was significant only for CO. The associations of SO₂, NO₂, and O₃ with stroke hospitalization were significantly stronger in the cool season.

CONCLUSIONS

Short-term increase in SO₂, NO₂, and PM₁₀ might be important triggers of stroke hospitalization. All seven air pollutants were associated with ischemic stroke hospitalization, while only CO was associated with hemorrhagic stroke hospitalization. These results should be considered in public health policy.

Cold spells linked with respiratory disease hospitalization, length of hospital stay, and hospital expenses: Exploring cumulative and harvesting effects

BACKGROUND

Previous studies have revealed the relationship between cold spells and morbidity and mortality due to respiratory diseases, while the detrimental effects of cold spells on the length of hospital stay and hospitalization expenses remain largely unknown.

METHODS

We collected hospitalization data for respiratory diseases in 11 cities of Shanxi, China during 2017-2019. In each case, exposure to meteorological variables and air pollution was estimated by the bilinear interpolation approach and inverse distance weighting method, respectively, and then averaged at the city level. Cold spells were defined as the daily mean temperature below the 10^th, 7.5^th, or 5^th percentiles for at least 2 to 5 consecutive days. We applied distributed lag non-linear models combined with generalized additive models to assess cumulative effects and harvesting effects.

RESULTS

There were significant associations between cold spells and hospital admissions, length of hospital stay, and hospital expenses for respiratory diseases. Compared with the non-cold spell period, the overall (lag 0-21) cumulative risk of hospitalization for total respiratory diseases was 1.232 (95 % CI: 1.090, 1.394) on cold spell days, and the increased length of hospital stay and hospitalization expenses were 112.793 (95 % CI: 10.755, 214.830) days and 127.568 (95 % CI: 40.513, 214.624) thousand Chinese yuan. The overall cumulative risks of cold spells on total respiratory diseases and pneumonia were statistically significant. We further observed harvesting effects in the associations between cold spells and hospital admission, length of hospital stay, and hospitalization expenses for respiratory diseases.

CONCLUSIONS

Cumulative cold-spell exposure for up to three weeks is associated with hospitalization, length of hospital stay, and hospital expenses for respiratory diseases. The observed harmful effects of cold spells on respiratory diseases can be partly attributable to harvesting effects.

Long-term impacts of non-occupational wildfire exposure on human health: A systematic review

The intensity and frequency of wildfires is increasing globally. The systematic review of the current evidence on long-term impacts of non-occupational wildfire exposure on human health has not been performed yet. To provide a systematic review and identify potential knowledge gaps in the current evidence of long-term impacts of non-occupational exposure to wildfire smoke and/or wildfire impacts on human health. We conducted a systematic search of the literature via MEDLINE, Embase and Scopus from the database inception to July 05, 2022. References from the included studies and relevant reviews were also considered. The Newcastle-Ottawa Scale (NOS) and a validated quality assessment framework were used to evaluate the quality of observational studies. Study results were synthesized descriptively. A total of 36 studies were included in our systematic review. Most studies were from developed countries (11 in Australia, 9 in Canada, 7 in the United States). Studies predominantly focused on mental health (21 studies, 58.33%), while evidence on long-term impacts of wildfire exposure on health outcomes other than mental health is limited. Current evidence indicated that long-term impacts of non-occupational wildfire exposure were associated with mortality (COVID-19 mortality, cardiovascular disease mortality and acute myocardial disease mortality), morbidity (mainly respiratory diseases), mental health disorders (mainly posttraumatic stress disorder), shorter height of children, reduced lung function and poorer general health status. However, no significant associations were observed for long-term impacts of wildfire exposure on child mortality and respiratory hospitalizations. The population-based high-quality evidence with quantitative analysis on this topic is still limited. Future well-designed studies considering extensive wildfire smoke air pollutants (e.g., particulate matter, ozone, nitrogen oxides) and estimating risk coefficient values for extensive health outcomes (e.g., mortality, morbidity) are warranted to fill current knowledge gaps.

Ambient air pollution associated with incidence and progression trajectory of cardiometabolic diseases: A multi-state analysis of a prospective cohort

BACKGROUND

Previous studies on the association between ambient air pollution and cardiometabolic diseases (CMDs) focused on a single disease, without considering cardiometabolic multimorbidity (CMM) and the progression trajectory of CMDs.

METHODS

Based on the UK Biobank cohort, we included 372,530 participants aged 37-73 years at baseline (2006-2010) with follow-up until September 2021. Incident CMDs cases were identified based on self-reported information and multiple health-related records in the UK Biobank. CMM was defined as the occurrence of at least two CMDs, including ischemic heart disease (IHD), stroke and type 2 diabetes (T2D). Exposure to ambient air pollutants, including particulate matter (PM) with aerodynamic diameter ≤2.5 μm (PM_2.5), ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), and nitrogen oxides (NO_x) were estimated at participants' geocoded residential addresses based on the high-resolution (1 × 1 km) pollution data from 2001 to 2021 provided by UK Department for Environment, Food and Rural Affairs. Multi-state models with adjustment for potential confounders were used to examine the impact of long-term exposure to ambient air pollution on transitions from healthy to first CMD (FCMD), subsequently to CMM, and further to death.

RESULTS

During a median follow-up of 12.6 years, 40,112 participants developed at least one CMD, 3896 developed CMM, and 21,739 died. Among the four pollutants, PM_2.5 showed the strongest associations with all transitions from healthy to FCMD, to CMM, and then to death [hazard ratios (95 % confidence intervals) per interquartile range (IQR) increment: 1.62 (1.60, 1.64) and 1.68 (1.61, 1.76) for transitions from healthy to FCMD and from FCMD to CMM, and 1.62 (1.59, 1.66), 1.67 (1.61, 1.73), and 1.52 (1.38, 1.67) for death risk from healthy, FCMD, and CMM, respectively]. After dividing FCMDs into three specific CMDs, we found that ambient air pollution had differential impacts on disease-specific transitions within the same transition phase.

CONCLUSIONS

Our findings indicate that there is potential for air pollution mitigation in contributing to the prevention of the development and progression of CMDs.

Short-term air pollution exposure associated with death from kidney diseases: a nationwide time-stratified case-crossover study in China from 2015 to 2019

BACKGROUND

Long-term exposure to air pollution has been associated with the onset and progression of kidney diseases, but the association between short-term exposure to air pollution and mortality of kidney diseases has not yet been reported.

METHODS

A nationally representative sample of 101,919 deaths from kidney diseases was collected from the Chinese Center for Disease Control and Prevention from 2015 to 2019. A time-stratified case-crossover study was applied to determine the associations. Satellite-based estimates of air pollution were assigned to each case and control day using a bilinear interpolation approach and geo-coded residential addresses. Conditional logistic regression models were constructed to estimate the associations adjusting for nonlinear splines of temperature and relative humidity.

RESULTS

Each 10 µg/m3 increment in lag 0-1 mean concentrations of air pollutants was associated with a percent increase in death from kidney disease: 1.33% (95% confidence interval [CI]: 0.57% to 2.1%) for PM1, 0.49% (95% CI: 0.10% to 0.88%) for PM2.5, 0.32% (95% CI: 0.08% to 0.57%) for PM10, 1.26% (95% CI: 0.29% to 2.24%) for NO2, and 2.9% (95% CI: 1.68% to 4.15%) for SO2.  CONCLUSIONS: Our study suggests that short-term exposure to ambient PM1, PM2.5, PM10, NO2, and SO2 might be important environmental risk factors for death due to kidney diseases in China.

Ambient particulate matter pollution of different sizes associated with recurrent stroke hospitalization in China: A cohort study of 1.07 million stroke patients

BACKGROUND

To estimate the associations between ambient particulate matter (PM) pollution of different sizes (PM₁, PM_2.5, and PM₁₀) and risk of rehospitalization among stroke patients, as well as the attributable burden in China.

METHODS

We built a cohort of 1,066,752 participants with an index stroke hospitalization in Sichuan, China from 2017 to 2019. Seven-day and annual average exposures to PM pollution prior to the date of the index hospitalization were linked with residential address using a bilinear interpolation approach. Cox proportional hazard models were constructed to assess the association between ambient PM and the risk of rehospitalization. The burden of stroke rehospitalization was estimated using a counterfactual approach.

RESULTS

245,457 (23.0 %) participants experienced rehospitalization during a mean of 1.15 years (SD: 0.90 years) of follow-up. Seven-day average concentrations of PM were associated with increased risk of rehospitalization: the hazard ratios (HRs) per 10 μg/m³ were 1.034 (95 % confidence interval [CI]: 1.029-1.038) for PM₁, 1.033 (1.031-1.036) for PM_2.5, and 1.030 (1.028-1.031) for PM₁₀; the hazard ratios were larger for annual average concentrations: 1.082 (1.074-1.090) for PM₁, 1.109 (1.104-1.114) for PM_2.5, and 1.103 (1.099-1.106) for PM₁₀. The associations were stronger in participants who were female, of minority ethnicity (non-Han Chinese), who suffered from an ischemic stroke, and those admitted under normal conditions. Population attributable fractions for stroke rehospitalization ranged from 4.66 % (95 % CI: 1.69 % to 7.63 %) for the 7-day average of PM₁ to 17.05 % (14.27 % to 19.83 %) for the annual average of PM₁₀; the reducible average cost of rehospitalization per participant attributable to PM ranged from 492.09 (178.19 to 806) RMB for the 7-day average of PM₁ to 1801.65 (1507.89 to 2095.41) RMB for the annual average of PM₁₀.

CONCLUSIONS

Ambient PM pollution may increase the risk of rehospitalization in stroke patients and is responsible for a significant burden of stroke rehospitalization.

Long-term exposure to ambient fine particulate matter chemical composition and in-hospital case fatality among patients with stroke in China

Background

There is little evidence on the association between PM_2.5 chemical components and fatality among hospitalized stroke patients.

Methods

This study used an inpatient discharge database from 2013 to 2019 in four provinces (Sichuan, Shanxi, Guangxi, and Guangdong) in China. Annual average exposure to PM_2.5 and its five chemical components [black carbon (BC), organic matter (OM), sulphate ( S O 4 2 - ), nitrate ( N O 3 - ), and ammonium ( N H 4 + )] were estimated using bilinear interpolation at patient's residential address. Mixed-effects logistic regression models were conducted to estimate the odds ratios (ORs). Counterfactual analyses were used to estimate the population attributable burden (PAF).

Findings

Among 3,069,093 hospitalized patients with stroke, each interquartile (IQR) increment in PM_2.5 and its chemical components was significantly associated with stroke fatality: the ORs were 1.137 [95% confidence interval (CI): 1.118-1.157; IQR: 15.14 μg/m³] for PM_2.5, 1.108 (95% CI: 1.091-1.126; IQR: 0.71 μg/m³) for BC, 1.086 (95% CI: 1.069-1.104; IQR: 3.47 μg/m³) for OM, and 1.065 (95% CI: 1.048-1.083; IQR: 2.81 μg/m³) for S O 4 2 - . We did not find significant associations for N O 3 - (OR: 0.991, 95% CI: 0.975-1.008; IQR: 3.30 μg/m³). The associations were larger among patients with ischemic stroke than those with hemorrhagic stroke. The PAFs were 10.6% (95% CI: 9.1-12.2%) for BC, 9.9% (95% CI: 8.2-11.7%) for OM, and 6.6% (4.9-8.3%) for S O 4 2 - .

Interpretation

Ambient BC, OM, and S O 4 2 - might be important risk factors for stroke fatality. The findings advocate the need to develop tailored guidelines for PM chemical components and curb the emissions of the most hazardous chemical components.

Funding

Bill & Melinda Gates Foundation (INV-016826).

Green space, air pollution and gestational diabetes mellitus: A retrospective cohort study in central China

Emerging evidence suggests residential surrounding green space is beneficial for human health. The association between green space and GDM showed inconsistent results, and potential effect modification of green space with air pollution is still unclear. This study aims to evaluate the association between green space and GDM, and further explore potential interaction and medication effects. Participants were recruited from a retrospective cohort study between 2015 and 2020 in Henan, China. Residential green space based on normalized difference vegetation index (NDVI) and air pollution exposure were estimated using spatial-statistical models. Multivariate logistic regression was applied to evaluate the association between per 0.1 unit increase in NDVI with 4 buffer sizes (250 m, 500 m, 1000 m, 2000 m) and GDM. We examined potential interaction of green space and air pollutants on GDM. Mediating effects of air pollution associated with green space exposure on GDM were also investigated by causal mediation analyses. A total of 46,665 eligible pregnant women were identified. There were 4092 (8.8 %) women diagnosed with GDM according to the IADPSG criteria. We found that per 0.1-unit increment in NDVI250 m, NDVI500 m, NDVI1000 m and NDVI2000 m in second trimester were associated with the decreased risk of GDM, with adjusted OR of 0.921(95 %CI: 0.890-0.953), 0.922 (95 %CI: 0.891-0.953), 0.921 (95 %CI: 0.892-0.952) and 0.921 (95 %CI: 0.892-0.951), respectively. We identified significant interactions between second trimester PM2.5 and O3 exposure and NDVI for GDM (Pinteraction < 0.001). The causal mediation analysis showed that PM2.5 mediated approximately 2.5-5.5 % of the association between green space and GDM, while the estimated mediating effect of O3 was approximately 30.1-38.5 %. In conclusion, our study indicates that residential green space was associated with a reduced risk of GDM, particularly second trimester. Green space may benefit to GDM partly mediated by a reduction in PM2.5 and O3.

Ambient air pollution, bone mineral density and osteoporosis: Results from a national population-based cohort study

Evidence concerning the associations of ambient air pollution exposure with bone mineral density and osteoporosis has been mixed. We conducted cross-sectional and prospective analysis of the associations between air pollution exposure and osteoporosis using data from UK Biobank study. Estimated bone mineral density (eBMD) of each participant at baseline survey was calculated using quantitative ultrasound data, and incident osteoporosis cases were identified during the follow-up period according to health-related records. Air pollution concentrations were assessed using land use regression models. We fitted multivariable linear and logistic regression models to estimate the associations of air pollution with eBMD and osteoporosis prevalence at baseline. We applied cox proportional hazard regression models to assess the relationships between air pollution and osteoporosis incidence. Among the 341,311 participants at baseline, higher air pollution exposure was associated with lower eBMD levels and increased odds of osteoporosis prevalence. For example, an IQR increase in PM_2.5, PM_2.5 absorbance, PM₁₀, NO₂ and NO_x levels were associated with 0.0018 (95% CI: 0.0012, 0.0023) to 0.0052 (95% CI: 0.0046, 0.0058) g/cm² decrease in eBMD. A total of 330,988 participants without osteoporosis were followed up for an average of 12.0 years. We identified 8105 incident osteoporosis cases (456 cases with pathological fracture and 7634 cases without pathological fracture) during the follow-up. The hazard ratios for an interquartile range increase in PM_2.5, PM_2.5 absorbance, PM₁₀, NO₂ and NO_x were 1.09 (95% CI: 1.06, 1.12), 1.04 (95% CI: 1.02, 1.07), 1.04 (95% CI: 1.01, 1.07), 1.07 (95% CI: 1.04, 1.10), and 1.06 (95% CI: 1.03, 1.09), respectively. Our study suggests that ambient air pollution might be a risk factor of decreased bone mineral density and osteoporosis incidence.

Particulate matter pollution and asthma mortality in China: A nationwide time-stratified case-crossover study from 2015 to 2020

BACKGROUND

A national and comprehensive evaluation is lacking on the relationship between short-term exposure to submicron particulate matter (PM₁) pollution and asthma mortality.

METHODS

Data was obtained from 29,553 asthma deaths from the China National Mortality Surveillance System from 2015 to 2020. We used a bilinear interpolation approach to estimate each participant's daily ambient particulate matter pollution and meteorological variables exposure based on their geocoded residential address and a 10 km × 10 km grid from China High Air Pollutants and the fifth generation of European ReAnalysis-Land reanalysis data set. The associations were estimated using a time-stratified case-crossover design and conditional logistic regressions.

RESULTS

Our results revealed significant associations between short-term exposure to various particulate matter and asthma mortality. The 5-day moving average of particulate matter exposure produced the most pronounced effect. Compared to fine particulate matter (PM_2.5) and inhalable particulate matter (PM₁₀), significantly stronger effects on asthma mortality related to PM₁ pollution were noted. The ERs% for asthma mortality associated with each interquartile range (IQR) increase of exposures to PM₁ (IQR: 19.2 μg/m³) was 5.59% (95% CI: 2.11-9.19), which is 14% and 22% higher than that for PM_2.5 (IQR: 32.0 μg/m³, 4.82% (95% CI: 1.84-7.90)) and PM₁₀ (IQR: 52.2 μg/m³, 4.37% (95% CI: 1.16-7.69)), respectively. The estimates remained consistent in various sensitivity analyses.

CONCLUSIONS

Our study provided national evidence that acute exposures to various ambient particulate matter pollution can increase mortality due to asthma in China, highlighting stronger associations with ambient PM₁ than PM_2.5 and PM₁₀. China needs to adjust the current ambient air quality standards urgently and pay greater attention to the adverse health effects of PM₁.

Daily diurnal temperature range associated with outpatient visits of acute lower respiratory infection in children: A time-series study in Guangzhou, China

Background

Diurnal temperature range (DTR) has been increasingly recognized as a risk factor for mortality and morbidity, but the association between DTR and acute lower respiratory infection (ALRI) outpatient visits has not been examined among children in China.

Methods

A total of 79,416 ALRI outpatient visits among children were obtained from the Guangdong Second Provincial General Hospital between 2013 and 2019. DTR was calculated by taking the difference between the maximum and the minimum temperatures. Generalized additive models using a quasi-Poisson distribution were used to model the relationship between DTR and ALRI outpatient visits.

Results

Diurnal temperature range was significantly associated with elevated risks of ALRI outpatient visits: the excess risks (ERs) and 95% confidence intervals (CIs) were 2.31% (1.26, 3.36%) for ALRI, 3.19% (1.86, 4.54%) for pneumonia, and 1.79% (0.59, 3.01%) for bronchiolitis, respectively. Subgroup analyses suggested that the associations were significantly stronger during rainy seasons (ER for ALRI: 3.02%, 95% CI: 1.43, 4.64%) than those in dry seasons (ER for ALRI: 2.21%, 95% CI: 0.65, 3.81%), while no significant effect modifications were found in sex and age groups.

Conclusion

Diurnal temperature range may elevate the risk of ALRI outpatient visits among children in China, especially during rainy seasons. Public health policies are needed to mitigate the adverse health impacts of DTR on children.