Hospital Admissions For Respiratory Diseases Research Articles

Short-term effects of ambient PM1 and PM2.5 air pollution on hospital admission for respiratory diseases: Case-crossover evidence from Shenzhen, China.

Ambient PM1 (particulate matter with aerodynamic diameter ≤1 μm) is an important contribution of PM2.5 mass. However, little is known worldwide regarding the PM1-associated health effects due to a wide lack of ground-based PM1 measurements from air monitoring stations. We collected daily records of hospital admission for respiratory diseases and station-based measurements of air pollution and weather conditions in Shenzhen, China, 2015-2016. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate hospitalization risks associated with short-term exposures to PM1 and PM2.5. PM1 and PM2.5 showed significant adverse effects on respiratory disease hospitalizations, while no evident associations with PM1-2.5 were identified. Admission risks for total respiratory diseases were 1.09 (95% confidence interval: 1.04 to 1.14) and 1.06 (1.02 to 1.10), corresponding to per 10 μg/m3 rise in exposure to PM1 and PM2.5 at lag 0-2 days, respectively. Both PM1 and PM2.5 were strongly associated with increased admission for pneumonia and chronic obstructive pulmonary diseases, but exhibited no effects on asthma and upper respiratory tract infection. Largely comparable risk estimates were observed between male and female patients. Groups aged 0-14 years and 45-74 years were significantly affected by PM1- and PM2.5-associated risks. PM-hospitalization associations exhibited a clear seasonal pattern, with significantly larger risks in cold season than those in warm season among some subgroups. Our study suggested that PM1 rather than PM1-2.5 contributed to PM2.5-induced risks of hospitalization for respiratory diseases and effects of PM1 and PM2.5 mainly occurred in cold season.

Statistical Behavior of Hospital Admissions for Respiratory Diseases by Probability Distribution Functions

Statistical Behavior of Hospital Admissions for Respiratory Diseases by Probability Distribution Functions

Ensemble method based on Artificial Neural Networks to estimate air pollution health risks

Estimating of daily hospital admissions due to air pollution is a leading issue in environmental science. To better understand this problem, it is essential to improve the applied methodologies. The use of Generalized Linear Models (GLM) is well known. However, they may be improved using different methods to coefficients estimation and to consider seasonality. Alternative methodologies, rarely applied in such topic, are Artificial Neural Networks (ANN), efficient to solve non-linear problems and; ensembles, which combine various models outputs. This research aims to apply 10 distinct ANN and 4 ensemble to estimate hospital admissions for respiratory diseases caused by particulate matter and meteorological variables of Campinas and São Paulo cities, Brazil. In addition, a new proposal of GLM was introduced, considering coefficients calculation via particle swarm optimization and seasonality via normalization procedure. ANN and ensembles use showed significant improvements and may allow studies into areas with flawing database, developing countries reality.

Ambient Air Pollution and Daily Hospital Admissions for Respiratory Disease in Children in Guiyang, China.

Objectives: To investigate the association between ambient air pollutant exposure and daily hospital admissions for respiratory diseases in children in Guiyang.Methods: Clinical data of pediatric inpatients with respiratory disease from 2009 to 2016 in Guizhou Provincial People's Hospital and PM2.5, NO2, PM10, and SO2 concentration data were retrieved. A canonical correlation analysis (CCA) was applied to analyse the association between air pollutants and daily hospital admissions for respiratory diseases. A reproducibility analysis was applied to analyse the association between air pollution and the duration and direct cost of hospitalization. The support vector regression (SVR) method was applied to determine whether air pollution data could predict the daily hospital admissions for the upcoming day.Results: A total of 10,876 inpatients with respiratory diseases were included between January 1, 2009 and December 31, 2016. The CCA showed significant correlations between air pollution and daily hospital admissions (r = 0.3564, p < 0.001), the duration of hospitalization (r = 0.2911, p < 0.001) and the economic cost of hospitalization (r = 0.2933, p < 0.001) for respiratory disease. PM10 contributed most to daily hospital admissions for respiratory disease; the concentration the day before hospitalization contributed most to the daily hospital admissions for respiratory disease. There was a slightly stronger correlation between air pollution and respiratory disease in children aged 2–18 years (R = 0.36 vs. R = 0.31 in those under 2 years old). No significant difference was found between male and female patients. The prediction analysis showed that air pollution could successfully predict daily pediatric inpatient hospital admissions (R = 0.378, permutation p < 0.001).Conclusions: Air pollution was significantly associated with hospital admissions, hospitalization duration and the economic cost of hospitalization in children with respiratory diseases. The maximum effect occurred on the day before hospitalization. The effect of PM10 on daily pediatric inpatient hospital admissions for respiratory disease was the greatest among the pollutants evaluated.

Effect modification of temperature on air pollution associated with hospital admission for respiratory diseases in Cape Town, South Africa

PDS 72: Environmental health issues in LMIC, Exhibition Hall (PDS), Ground floor, August 28, 2019, 10:30 AM - 12:00 PM Background: Global warming is impacting ambient temperature with subsequent increased risks for adverse human health impacts. Temperature and air pollution are often treated as separate risk factors and few studies have investigated effect modification by temperature on the association between air pollution and human health outcomes in Africa. Methods: Individual level respiratory disease (ICD10: J00-J99) hospital admission data for 1 January 2011 to 31 October 2016 were obtained from seven private hospitals located in Cape Town, South Africa. NO2, SO2, PM10, temperature (converted to Apparent Temperature, Tapp) and relative humidity data for 2011 to 2016 were obtained from the South African Weather Services and the City of Cape Town. A case-crossover epidemiological study design was applied. The average air pollutant level on the day and the day before respiratory disease hospital admission (Lag0-1) was investigated. Models were adjusted for confounders. Days with Tapp below and above the median value were classified as cold and warm days, respectively. Results: Stratified analysis showed higher modification of air pollution effect on hospital admission for respiratory disease when the ambient temperature increases. Warmer days indicated strong modification effect for PM10: 5.4% (3.3%, 7.6%), NO2: 16.1% (11.1%, 21.4%) and SO2: 17.5% (11.2%, 24.0%). The interaction effect between temperature and air pollution was higher during warm days. Higher modification effect occurred in ages < 65 years old for hospital admission for respiratory disease. Conclusion: The findings are important to direct future research and to inform public health interventions.

Spatial analysis of hospital admissions for respiratory disease and the relationship with air pollution sources in Rio de Janeiro, Brazil

Spatial analysis of hospital admissions for respiratory disease and the relationship with air pollution sources in Rio de Janeiro, Brazil

Short-Term Effects of Temperature on Peadiatric Hospital Admissions for Respiratory Diseases in Italy

Short-Term Effects of Temperature on Peadiatric Hospital Admissions for Respiratory Diseases in Italy

An evaluation of the Air Quality Health Index Program on respiratory diseases in Hong Kong

TPS 683: Short-term health effects of air pollutants 2, Exhibition Hall, Ground floor, August 28, 2019, 3:00 PM - 4:30 PM Background: On December 30th, 2013, the Hong Kong government implemented the Air Quality Health Index (AQHI) to reduce short-term impacts of air pollution on the population. However, whether air quality alert programs, such as the AQHI, reduce morbidity is still questionable. Using a quasi-experimental design, we conducted the first evaluation of the AQHI in Hong Kong focusing on respiratory morbidity. Method: Interrupted time series with Poisson segmented regression from 2010 to 2016 were used to detect any sudden or gradual changes in emergency respiratory hospital admissions, adjusted for air pollutants (NO2, SO2, PM10, O3), temperature and humidity, when the AQHI policy was implemented. Findings were validated using three false policy periods. We also assessed changes by specific respiratory diseases respiratory tract infections (RTI), asthma, chronic obstructive pulmonary disease and pneumonia) and by age. Results: From January 1st, 2010- December 31st, 2016, 10576.98 deseasonalized, age- and sex-standardized hospital admissions for respiratory diseases occurred in Hong Kong. On implementation of the AQHI, RTI admissions immediately dropped by 14% (relative risk (RR) 0.86 95% confidence interval (CI) 0.76-0.98). In age specific analysis, immediate reductions in hospital admissions, were only apparent in children for RTI (RR 0.84, 95% CI 0.74-0.96) and pneumonia (RR 0.88, 95% CI 0.60-0.96). Conclusion: Hong Kong’s AQHI helped reduced hospital admissions in children, particularly for RTI and pneumonia. To maximize the health benefits of the policy, at risk groups need to be able to follow the behavioral changes recommended by the AQHI index. Keywords: AQHI; Respiratory diseases; Interrupted time series; Segmented regression

Apparent temperature as a modifier of the effects of air pollution on respiratory disease hospital admissions in Secunda, South Africa

TPS 681: Short-term health effects of air pollutants 1, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM Background: Due to climate change, an increase of 34°C in ambient temperature is projected along the South African coast and 6-7°C inland during the next 80 years. Very few studies in Africa investigated effect modification by a temperature indicator (e.g. apparent temperature, Tapp) on the human health effects of air pollution. Methods: Respiratory disease (RD) admission data (ICD10 J00-J99) were obtained from MediClinic for the two hospitals located in Secunda; after ethics approval. The study period is 1 January 2011 to 31 October 2016. NO2, SO2, PM10, PM2.5, temperature and relative humidity data were obtained from the South African Weather Services. A case-crossover epidemiological study design was applied. The present study focused on lag0-1; as most other studies. Models were adjusted for public holidays and Tapp. Days with Tapp below and above/equal the median (14.9C) were classified as cold and warm days, respectively. Results: Of the 14 568 RD admissions, approximately equal number of females and males were admitted. 47%, 45% and 8% of the admissions were from 0-14, 15-64 and >=65 year olds, respectively. The daily NO2, SO2, PM2.5 and PM10 levels were 12.4, 8.5, 32.3 and 68.6 μm/m3, respectively. Daily air pollutant levels regularly exceeded the WHO guidelines. On cold days there were no significant associations between the air pollutants and RD admissions, but there were strong associations on warm days, except for NO2. On warm days, 0-14 year olds and females were more susceptible to PM2.5, PM10 and SO2, e.g. RR 1.12 95%CI 1.02-1.23 for 14 year olds and PM2.5 compared to the unstratified analyses RR 1.01 95%CI 1.00-1.02. Conclusions: These results indicate that the risk of RD hospital admission due to ambient air pollution exposure is different on cold and warm days in Secunda.

Association between ambient PM2.5 and children’s hospital admissions for respiratory diseases in Jinan, China

To determine the association between daily air pollution and the hospital admissions for respiratory diseases in children aged from 0 to 17 years in Jinan, China. Generalized linear models were used to explore the acute effects of ambient fine particulate matter (PM2.5) on the children's hospital admissions for respiratory diseases. We evaluated the lag associations (including lag 0 to lag 3, lag 01, and lag 03) between daily PM2.5 and the number of children's hospital admissions for respiratory diseases, and stratified by gender, age group (baby group: age 0-1 years; child group: age 1-5 years; student group: age 6-17 years), and cause-specific disease (including upper infection, pneumonia, and acute bronchitis) during 2011-2015. PM2.5 had significant positive impacts on the number of children's hospital admissions for respiratory disease. The results showed that per 10 μg/m3 increase of PM2.5 at lag 1 was associated with an increase in total and male hospital admissions of 0.23% (95% CI, 0.02%-0.45%) and 0.32% (95% CI, 0.04%-0.06%). The corresponding risk of the student group (age 6-17 years) hospital admissions was increased 0.90% (95% CI, 0.39%-1.42%) at lag 1 day. The corresponding risk of the upper infection was increased 0.96% (95% CI, 0.37-1.55%) at lag 1 day. Males and student groups (age 6-17 years) were more vulnerable to PM2.5 exposure. Upper infection admission was identified as the sensitive disease for children. It is a better way to reduce children's outdoor activities to avoid health effects when the air pollution increases.

Temporal changes in the effects of ambient temperatures on hospital admissions in Spain.

BackgroundThe exposure to extreme ambient temperatures has been reported to increase mortality, although less is known about its impact on morbidity. The analysis of temporal changes in temperature-health associations has also focused on mortality with no studies on hospitalizations worldwide. Studies on temporal variations can provide insights on changes in susceptibility or on effectiveness of public health interventions. We aimed to analyse the effects of temperature on cause-specific hospital admissions in Spain and assess temporal changes using two periods, the second one characterized by the introduction of a heat health prevention plan.MethodsDaily counts of non-scheduled hospital admissions for cardiovascular, cerebrovascular and respiratory diseases and daily maximum temperature were obtained for each Spanish province for the period 1997–2013. The relationship between temperature and hospitalizations was estimated using distributed lag non-linear models. We compared the risk of hospitalization due to temperatures (cold, heat and extreme heat) in two periods (1997–2002 and 2004–2013).ResultsCold temperatures were associated with increased risk of cardiovascular, cerebrovascular and respiratory hospital admissions. Hot temperatures were only associated with higher hospital admissions for respiratory causes while hospitalizations for cardiovascular and cerebrovascular diseases did not increase with heat. There was a small reduction in heat-related respiratory admissions in period 2. Whereas cold-related hospitalizations for cardiovascular and cerebrovascular diseases increased in period 2, a significant reduction for respiratory hospitalizations was reported.ConclusionsOur results suggested that heat had an adverse impact on hospital admissions for respiratory diseases, while cold increased the risk of the three studied cause-specific hospitalizations. Public health interventions should also focus on morbidity effects of temperature.

An evaluation of the air quality health index program on respiratory diseases in Hong Kong: An interrupted time series analysis

BackgroundOn December 30th, 2013, the Hong Kong government implemented the Air Quality Health Index (AQHI) alert programme warnings designed to reduce short-term effects of air pollution on population health. However, whether air quality alert programme warnings, such as the AQHI, reduce morbidity is still questionable. Using a quasi-experimental design, we conducted the first evaluation of the AQHI in Hong Kong focusing on respiratory morbidity. MethodInterrupted time series with Poisson segmented regression from 2010 to 2016 was used to detect any sudden or gradual changes in emergency respiratory hospital admissions, adjusted for air pollutants (NO2, SO2, PM10, O3), temperature and humidity, when the AQHI policy was implemented. The findings were validated using three false policy study periods and digestive diseases as a control. We also assessed effects on specific respiratory diseases (respiratory tract infections (RTI), asthma, chronic obstructive pulmonary disease and pneumonia) and by age. ResultsFrom January 1st, 2010 to December 31st, 2016, 10576.98 deseasonalized, age-standardized hospital admissions for respiratory disease occurred in Hong Kong. On implementation of the AQHI, RTI admissions immediately dropped by 14% (relative risk (RR) 0.86 95% confidence interval (CI) 0.76–0.98). In age specific analysis, immediate reductions in hospital admissions were only apparent in children for RTI (RR 0.84, 95% CI 0.74–0.96) and pneumonia (RR 0.88, 95% CI 0.60–0.96). ConclusionHong Kong's AQHI helped reduced hospital admissions in children, particularly for RTI and pneumonia. To maximize health benefits of the policy, at risk groups need to be able to follow the behavioral changes recommended by the AQHI warnings.

Bayesian modelling for spatially misaligned health and air pollution data through the INLA-SPDE approach

In air pollution studies a key issue concerns the change of support: pollutant concentrations are continuous phenomena in space but their measurements are typically available at a finite number of point-referenced monitoring stations or result from numerical models. When linking exposure to health outcomes, the latter are usually available at administrative level, hence on an irregular lattice, providing challenges in terms of data misalignment.In this paper we tackle the change of support problem for air pollution and health studies through a two-stage Bayesian approach; in the first stage our model estimates the air pollution concentration at the area level and then in the second stage it links the exposure to the health outcome, accounting for the uncertainty on the exposure estimates. We show through an extensive and realistic simulation that our model is able to predict the concentration accurately at the administrative level as well as estimate the association between exposure and health outcome. We use the Integrated Nested Laplace Approximation, coupled with the Stochastic Partial Differential Equation method for model implementation. Finally we apply the proposed model to evaluate the effect of NO2 concentration on hospital admissions for respiratory diseases in the Piemonte region (Italy). We found that the upscaling method and the approach used to propagate uncertainty from the first to the second stage have an impact on the posterior distribution of the relative risk. Moreover, we found a significant increased risk of 1.6% and 1.8% associated with an increase of 10 μg∕m3 in NO2 concentration.

Contribution of transregional transport to particle pollution and health effects in Shanghai during 2013–2017

Transregional transport plays an important role in air pollution. This study investigated the impact of transregional transport on particle pollution in Shanghai from 2013 to 2017. A conditional potential source contribution function (CPSCF) method with high time resolution (1 h) PM2.5 and PM10 data was used to quantify the contribution of transregional transport. The corresponding health impact was also assessed. The average annual contribution of transregional transport to PM2.5 (PM2.5_CTRT) and PM10 (PM10_CTRT) was 22 and 30 μg/m3, 18 and 24 μg/m3, 19 and 24 μg/m3, 14 and 19 μg/m3, and 14 and 19 μg/m3, for 2013 to 2017, respectively, thus accounting for 31–37% of total PM2.5 and PM10. As PM2.5_CTRT is a dominant component of PM10_CTRT, the health effects related to PM2.5_CTRT were assessed to avoid double counting. The number of annual deaths associated with PM2.5_CTRT in Shanghai during the study period ranged from 636 (95% confidence intervals: 350, 936) to 1039 (573, 1530), among which cardiovascular disease and respiratory disease accounted for 62.8–67.6% and 16.6–19.5% of mortality, respectively. PM2.5_CTRT-related deaths accounted for 5.3–8.2‰ of the total mortality in Shanghai during the study period. Between 9764 (9251, 10,277) and 12,190 (11,549, 12,830) cases of all-cause hospital admissions were attributable to PM2.5_CTRT in Shanghai in one year, among which cardiovascular disease and respiratory disease hospital admissions accounted for 15.9–20.0% and 7.9–9.2%, respectively. Internal medicine and pediatrics outpatient visits related to PM2.5_CTRT ranged from 70,684 (39,009, 100,829) to 97,380 (53,788, 138,793) cases and 23,185 (8302, 37,173) to 32,702 (11,726, 52,361) cases, respectively. The current work provides scientific evidence of the impact of transregional transport on air pollution and its health burden in Shanghai.

Increased susceptibility to heat for respiratory hospitalizations in Hong Kong

BackgroundEmerging studies have shown temperature-mortality association is changing over time, but little is known about the temporal changes of the temperature-morbidity association. ObjectivesWe aimed to evaluate the temporal variations in both temperature-respiratory hospitalizations associations and temperature-related attributable risks in Hong Kong. MethodsWe collected 17-year time-series data on daily ambient temperature and emergency hospital admissions for respiratory diseases between 2000 and 2016 in Hong Kong. Quasi-Poisson regression with a time-varying distributed lag nonlinear model was used to estimate the year-specific association between temperature and respiratory hospitalizations [total respiratory, pneumonia, and chronic obstructive pulmonary disease (COPD)] and the year-specific attributable fraction (AF) for heat and cold (defined as above/below the optimum temperature, respectively). ResultsHeat-related risks and AFs increased continuously for total respiratory, pneumonia and COPD hospitalizations during the past 17 years, respectively. Cold-hospitalization associations and cold-related AFs showed heterogeneous patterns, showing a decreasing trend for pneumonia but a general increasing trend for COPD for both the associations and AFs. The total temperature-related AFs remained stable for total respiratory (p for trend = 0.136) and pneumonia (p for trend = 0.406), but showed an increasing trend for COPD (p for trend < 0.001) from 10% (95% empirical CI: 2%, 17%) in 2000 to 17% (95% empirical CI: 11%, 22%) in 2016. ConclusionsOur findings indicate an increased susceptibility to heat but a decreased susceptibility to cold for respiratory hospitalizations during the past 17 years. The overall temperature-related hospitalization burden for respiratory diseases was generally stable in Hong Kong.

Respiratory morbidity in children with cerebral palsy: an overview

Respiratory problems have a significant impact on morbidity and mortality in patients with cerebral palsy (CP). In particular, recurrent aspiration, impaired airway clearance, spinal and thoracic deformity, impaired lung function, poor nutritional status, and recurrent respiratory infections negatively affect respiratory status. Bronchopulmonary dysplasia may contribute to pulmonary problems, but asthma is not more common in CP than in the general population. We discuss treatment options for each of these factors. Multiple coexisting and interacting factors that influence the respiratory status of patients with CP should be recognized and effectively addressed to reduce respiratory morbidity and mortality. WHAT THIS PAPER ADDS: Respiratory problems are a significant cause of morbidity in patients with cerebral palsy (CP). Respiratory status in patients with CP is influenced by recurrent aspiration and impaired airway clearance. Spinal and thoracic deformity, impaired lung function, poor nutrition, and respiratory infections also negatively affect respiratory status. These factors should all be addressed to reduce respiratory problems in patients with CP.

Seasonal association between ambient ozone and hospital admission for respiratory diseases in Hanoi, Vietnam.

BackgroundMany studies have indicated the detrimental effect of ambient ozone to respiratory health in different countries. The levels of ozone in Hanoi, Vietnam are frequently above the WHO guideline but very few studies on the effects of ambient ozone on human health have been conducted in this location. This study aimed to examine the effects of ozone on hospital admission for respiratory diseases in Hanoi, by diseases, ages and seasons.MethodsHospital admissions, air pollutants and meteorological data were collected from January 2010 to June 2014. We used generalized linear models and distributed lag linear model to assess the association. In addition to full year analysis, we conducted restricted analysis of the data for two summer (from June-August) and winter (from December-February) seasons and grouped hospital admissions by diseases and ages (all ages, children 0 to 5 years and elderly >65 years). The delayed effect of ozone was assessed using lags of up to 5 days.ResultsOzone has a stronger effect on the risk of hospital admission for respiratory diseases and wheeze-associated disorders in the winter. For respiratory diseases, children were affected by ozone more than other age groups in both winter and summer. Each increase of 10 μg/m3 of ozone is associated with an increase of 6.2% risk of admission for respiratory disease among children in the winter and 1.2% in the summer. For wheeze-associated disorders, the elderly group seemed to be more affected by ozone in full year and winter but no significant association was found between ozone and admission for wheeze-associated diseases in any age group.ConclusionsOzone is a risk factor for respiratory admission, especially amongst children under 5 years old in Hanoi, and ozone has a stronger effect in the winter than in the summer in this city.

An Exploratory Analysis of the Effect of Regulatory Policies for Pre-Harvesting Sugarcane Straw Burning on Hospital Admissions for Respiratory Diseases in the State of S&amp;#227;o Paulo, Brazil

Emissions generated by sugarcane burning have been associated with acute respiratory effects and increase in hospital admissions, among other health effects. In 2002 the State of Sao Paulo (SP...

Seasonal Association between Ambient Ozone and Hospital Admission for Respiratory in Hanoi, Vietnam

Background: While the level of air pollutants in Hanoi is frequently above the World Health Organization suggested level, few studies on the effects of ambient air pollution on health have been conducted in Vietnam. This study aimed to examine the effects of ozone on hospital admissions for respiratory diseases in Hanoi.Methods: Hospital admissions data were collected from three hospitals in Hanoi from January 2010 to June 2014. Air pollutants data were collected from Centre for Environmental Monitoring Portal for the same period of time. We used Generalized Linear Models and Distributed lag Linear Model to assess the association. We restricted analysis the data to two summer and winter season and grouped hospital admissions by diseases and ages.Results: Ozone was associated with the risk of admission for respiratory among group of children and all ages combined at lag 5 but not for older adults. For each increase of 10 µg/m3 of ozone, the risk of admissions for respiratory disease at lag 5 increased 3.6% among children and 3.3% for all ages. The overall cumulative lag effects were statistically significant in both winter and summer. No significant association was found for wheeze-associated diseases in any age group.Conclusions: Ozone is a risk factor for respiratory admission, especially amongst children aged &amp;lt; 5 years old.

The burden of overall and cause-specific respiratory morbidity due to ambient air pollution in Sichuan Basin, China: A multi-city time-series analysis

Few studies have investigated the respiratory morbidity burden due to ambient air pollution in China, especially in a multi-city setting. This study aimed to estimate the short-term effects of ambient air pollutants (PM10, PM2.5, NO2 and SO2) on hospital admissions (HAs) for overall and cause-specific respiratory diseases, as well as the associated burden in 17 cities of Sichuan Basin, China during 2015–2016. Firstly, city-specific effect estimates for each pollutant on respiratory HAs were obtained using generalized additive model with quasi-Poisson link, and then random- or fixed-effects meta-analysis was applied to pool the effect estimates at the regional level. Subgroup analyses by sex, age, season and region were also performed. A total of 757,712 respiratory HAs were collected from all the tertiary and secondary hospitals located in the 17 cities. Risks of HAs for overall and cause-specific respiratory diseases were elevated following increased PM10, PM2.5, NO2 and SO2 exposure. An increase of 10 μg/m3 in PM10 at lag01, PM2.5 at lag01, NO2 at lag0 and SO2 at lag02 was associated with a 0.43% (95% CI: 0.33%, 0.53%), 0.53% (95% CI: 0.39%, 0.68%), 2.36% (95% CI: 1.75%, 2.98%) and 2.54% (95% CI: 1.51%, 3.59%) increases in total respiratory HAs, respectively. Children (≤ 14 years) and elderly (≥ 65 years) appeared to be more vulnerable to the effects of ambient air pollutants. Comparing to the WHO's air quality guidelines, we estimated that 1.84% (95%CI: 1.42%, 2.25%), 1.73% (95%CI: 1.27%, 2.19%) and 0.34% (95%CI: 0.21%, 0.48%) of respiratory HAs were due to PM10, PM2.5 and SO2 exposure, respectively. This study suggests that air pollution might be an important trigger of respiratory admissions, and result in substantial burden of HAs for respiratory diseases in Sichuan Basin.