scholarly journals Assessing the impact of long-term exposure to nine outdoor air pollutants on spatial spread of Covid-19: evidence from 107 Italian provinces

2021 ◽  
Author(s):  
Gaetano Perone
Keyword(s):  
Heavy Metals ◽  
Air Pollutants ◽  
Negative Binomial ◽  
Ordinary Least Squares ◽  
Air Pollutant ◽  
Outdoor Air ◽  
Italian Provinces ◽  
Spatial Autoregressive ◽  
The Impact

Abstract The coronavirus (COVID-19) pandemic has dramatically changed every aspect of people’s lives around the world over the past year and a half. Although the global vaccination campaign is progressing worldwide, new variants of COVID-19 have emerged, driving many countries into a fourth wave of COVID-19 contagion. This paper investigates the air quality in 107 Italian provinces in the period 2014–2019 and the association between long-term exposure to nine outdoor air pollutants and the prevalence of COVID-19 in the same areas. The methods used were negative binomial (NB) regressions, ordinary least squares (OLS) models, and spatial autoregressive models with autoregressive disturbances (SARAR). The air pollutants examined were common air pollutants (NO2, O3, PM2.5, PM10), polycyclic aromatic hydrocarbons (PAHs) (benzene and BaP), and heavy metals (As, Cd, and Ni). The results showed that i) common air pollutants were generally highly and positively correlated with density of large firms, energy and gas consumption, public transport, and the livestock sector; and ii) long-term exposure to NO2, PM2.5, PM10, benzene, BaP, and Cd was positively and significantly correlated with the spread of COVID-19, even after controlling for cofactors and spatial effects. This outcome seems of interest and relevance because PAHs and heavy metals have not been considered at all in recent literature. It also seems to suggest the need for a national strategy to drive down air pollutant concentrations in order to cope better with possible future pandemics.

scholarly journals Spatio-temporal associations of air pollutant concentrations, GP respiratory consultations and respiratory inhaler prescriptions: a 5-year study of primary care in the borough of Lambeth, South London

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Mark Ashworth ◽  
◽  
Antonis Analitis ◽  
David Whitney ◽  
Evangelia Samoli ◽  
...  
Keyword(s):  
Primary Care ◽  
Negative Binomial ◽  
Hospital Admissions ◽  
Air Pollutant ◽  
Respiratory Morbidity ◽  
Short Term ◽  
Short Term Exposure ◽  
Short And Long Term ◽  
Spatio Temporal

Abstract Background Although the associations of outdoor air pollution exposure with mortality and hospital admissions are well established, few previous studies have reported on primary care clinical and prescribing data. We assessed the associations of short and long-term pollutant exposures with General Practitioner respiratory consultations and inhaler prescriptions. Methods Daily primary care data, for 2009–2013, were obtained from Lambeth DataNet (LDN), an anonymised dataset containing coded data from all patients (1.2 million) registered at general practices in Lambeth, an inner-city south London borough. Counts of respiratory consultations and inhaler prescriptions by day and Lower Super Output Area (LSOA) of residence were constructed. We developed models for predicting daily PM2.5, PM10, NO2 and O3 per LSOA. We used spatio-temporal mixed effects zero inflated negative binomial models to investigate the simultaneous short- and long-term effects of exposure to pollutants on the number of events. Results The mean concentrations of NO2, PM10, PM2.5 and O3 over the study period were 50.7, 21.2, 15.6, and 49.9 μg/m3 respectively, with all pollutants except NO2 having much larger temporal rather than spatial variability. Following short-term exposure increases to PM10, NO2 and PM2.5 the number of consultations and inhaler prescriptions were found to increase, especially for PM10 exposure in children which was associated with increases in daily respiratory consultations of 3.4% and inhaler prescriptions of 0.8%, per PM10 interquartile range (IQR) increase. Associations further increased after adjustment for weekly average exposures, rising to 6.1 and 1.2%, respectively, for weekly average PM10 exposure. In contrast, a short-term increase in O3 exposure was associated with decreased number of respiratory consultations. No association was found between long-term exposures to PM10, PM2.5 and NO2 and number of respiratory consultations. Long-term exposure to NO2 was associated with an increase (8%) in preventer inhaler prescriptions only. Conclusions We found increases in the daily number of GP respiratory consultations and inhaler prescriptions following short-term increases in exposure to NO2, PM10 and PM2.5. These associations are more pronounced in children and persist for at least a week. The association with long term exposure to NO2 and preventer inhaler prescriptions indicates likely increased chronic respiratory morbidity.

scholarly journals Long-Term Exposure to Fine and Coarse Particulate Matter and COVID-19 Incidence and Mortality Rate in Chile during 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7409
Author(s):  
Macarena Valdés Salgado ◽  
Pamela Smith ◽  
Mariel Opazo ◽  
Nicolás Huneeus
Keyword(s):  
Mortality Rate ◽  
Incidence Rate ◽  
Air Pollutants ◽  
Negative Binomial ◽  
Transport Model ◽  
Surface Concentration ◽  
Mortality Rates ◽  
Incidence And Mortality ◽  
Pm2.5 And Pm10

Background: Several countries have documented the relationship between long-term exposure to air pollutants and epidemiological indicators of the COVID-19 pandemic, such as incidence and mortality. This study aims to explore the association between air pollutants, such as PM2.5 and PM10, and the incidence and mortality rates of COVID-19 during 2020. Methods: The incidence and mortality rates were estimated using the COVID-19 cases and deaths from the Chilean Ministry of Science, and the population size was obtained from the Chilean Institute of Statistics. A chemistry transport model was used to estimate the annual mean surface concentration of PM2.5 and PM10 in a period before the current pandemic. Negative binomial regressions were used to associate the epidemiological information with pollutant concentrations while considering demographic and social confounders. Results: For each microgram per cubic meter, the incidence rate increased by 1.3% regarding PM2.5 and 0.9% regarding PM10. There was no statistically significant relationship between the COVID-19 mortality rate and PM2.5 or PM10. Conclusions: The adjusted regression models showed that the COVID-19 incidence rate was significantly associated with chronic exposure to PM2.5 and PM10, even after adjusting for other variables.

FRI0531 AIR POLLUTANTS AND DEVELOPMENT OF INTERSTITIAL LUNG DISEASE IN PATIENTS WITH AUTOIMMUNE DISEASES

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 865.1-865
Author(s):  
H. H. Chen ◽  
W. C. Chao ◽  
Y. H. Chen ◽  
D. Y. Chen ◽  
C. H. Lin
Keyword(s):  
Air Quality ◽  
Autoimmune Diseases ◽  
Air Pollutants ◽  
Air Pollutant ◽  
Air Quality Monitoring ◽  
Newly Diagnosed ◽  
Science Technology ◽  
Air Quality Monitoring Stations ◽  
The Impact ◽  
Modest Level

Background:Interstitial lung disease (ILD) is characterized by progressive inflammation and fibrosis, and accumulating evidence have shown that exposure to air pollutants was associated with the development of ILD. Autoimmune diseases are highly correlated with ILD, including connective tissue disease-associated ILD (CTD-ILD) as well as interstitial pneumonia with autoimmune features (IPAF), and the development of ILD is a crucial cause of morbidity and mortality in patients with autoimmune diseases. One recent Taiwanese study reported that exposure to air pollutants was associated with incident systemic lupus erythematosus (SLE). However, the impact of air pollutants on the development of ILD among patients with autoimmune diseases remains unknown.Objectives:The study aimed to address the impact of accumulating exposure to air pollutant above moderate level, defined by Air Quality Index (AQI) value higher than 50, on the development of ILD in patients with autoimmune diseases including SLE, rheumatoid arthritis (RA) and primary Sjögren’s syndrome (SS).Methods:We used a National Health Insurance Research Database in Taiwan to enroll patients with SLE (International Classification of Diseases (ICD)-9 code 710.0, n=13,211), RA (ICD-9 code 714.0 and 714.30–714.33, n=32,373), and primary SS (ICD-9 code, 710.0, n=15,246) between 2001 and 2013. We identified newly diagnosed ILD cases (ICD-code 515) between 2012 and 2013 and selected age, sex, disease duration and index-year matched (1:4) patients as non-ILD controls. The hourly levels of air pollutants one year prior to the index-date were obtained from 60 air quality monitoring stations across Taiwan, and the air pollutants in the present study consisted of particulate matter <2.5 μm in size (PM2.5), particulate matter <10 μm in size (PM10), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2) and ozone (O3). We used a spatio-temporal model built by a deep-learning mechanism to estimate levels of air pollutants at 374 residential locations based on data of 3 air quality monitoring stations near the location (8). Notably, we used cumulative exposed hours to air pollutants higher than modest level, defined by AQI criteria, given that daily mean level of air pollutants might possibly underestimate the triggered inflammatory effect by a temporary exposure of high-level air pollutant. A conditional logistic regression was used to determine the association between exposure to air pollutant and the development of ILD, adjusting age, gender, Charlson Comorbidity Index (CCI), urbanization, family income, and medications for autoimmune diseases.Results:A total of 272 patients with newly diagnosed ILD were identified among patients with autoimmune diseases, including 39 with SLE, 135 with RA, and 98 with primary SS. We found that the duration of exposure to PM 2.5 higher than modest level was associated with the risk of ILD development in patients with SS (adjOR 1.07, 95% CI 1.01–1.13), and similar trends were also found in patients with SLE (adjOR 1.03, 95% CI 0.95–1.12) and RA (adjOR 1.03, 95% CI 0.99–1.07). Intriguingly, we observed an inverse correlation between the duration of exposure to O3 and the development of ILD in patients with SS (adjOR 0.83, 95% CI 0.70–0.99); however, the finding was not found in patients with SLE (adjOR 1.13, 95% CI 0.92–1.37) and RA (adjOR 0.98, 95% CI 0.87–1.11).Conclusion:In conclusion, we identified that longer exposure to PM2.5 higher than modest level tended to be associated with the development of ILD in patients with autoimmune diseases, mainly SS.References:[1] Araki T, Putman RK, Hatabu H, Gao W, Dupuis J, Latourelle JC, et al. Development and Progression of Interstitial Lung Abnormalities in the Framingham Heart Study. Am J Respir Crit Care Med 2016;194:1514-1522.[2] Tang KT, Tsuang BJ, Ku KC, Chen YH, Lin CH, Chen DY. Relationship between exposure to air pollutants and development of systemic autoimmune rheumatic diseases: a nationwide population-based case-control study. Ann Rheum Dis 2019;78:1288-1291.Disclosure of Interests:Hsin-Hua Chen: None declared, Wen-Cheng Chao: None declared, Yi-Hsing Chen Grant/research support from: Taiwan Ministry of Science and Technology, Taiwan Department of Health, Taichung Veterans General Hospital, National Yang-Ming University, GSK, Pfizer, BMS., Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead., Paid instructor for: Pfizer, Novartis, Johnson & Johnson, Roche, Lilly, Astra& Zeneca, Sanofi, Astellas, Agnitio Science Technology, United Biopharma., Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead., Der-Yuan Chen: None declared, Ching-Heng Lin: None declared

The impact of gender inequality in education and employment on economic performance in Turkey: evidence from a cointegration approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ömer Esen ◽  
Gamze Yıldız Seren
Keyword(s):  
Least Squares ◽  
Economic Performance ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Content Type ◽  
Cointegration Tests ◽  
Johansen Cointegration ◽  
Education And Employment ◽  
The Impact

PurposeThis study aims to empirically examine the impact of gender-based inequalities in both education and employment on economic performance using the dataset of Turkey for the period 1975–2018.Design/methodology/approachThis study employs Johansen cointegration tests to analyze the existence of a long-term relation among variables. Furthermore, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) estimation methods are performed to determine the long-run coefficients.FindingsThe findings from the Johansen cointegration analysis confirm that there is a long-term cointegration relation between variables. Moreover, DOLS and FMOLS results reveal that improvements in gender equality in both education and employment have a strong and significant impact on real gross domestic product (GDP) per capita in the long term.Originality/valueThe authors expect that this study will make remarkable contributions to the future academic studies and policy implementation, as it examines the relation among the variables by including the school life expectancy from primary to tertiary based on the gender parity index (GPI), the gross enrollment ratio from primary to tertiary based on GPI and the ratio of female to male labor force participation (FMLFP) rate.

scholarly journals Model research on the influence of green roofs on environmental parameters in urban agglomerations

2018 ◽  
Vol 45 ◽  
pp. 00094 ◽  
Author(s):  
Dariusz Suszanowicz
Keyword(s):  
Heavy Metals ◽  
Urban Areas ◽  
Air Pollutants ◽  
Green Roof ◽  
Soil Layer ◽  
Environmental Parameters ◽  
Green Roofs ◽  
Field Studies ◽  
Air Pollutant ◽  
Laboratory Scale

This study presents features of green roofs in urban areas with a particular emphasis on the filtration of air pollutants, heavy metals removal, reduction of rainwater runoff from roof surfaces and thermal insulation. To carry out field studies on the influence of green roofs on the environment in urban areas, two green roof models on a laboratory scale were used. The observations of the prepared green roof models made during the summer, autumn and winter confirmed the extremely beneficial effect of this type of roof for the elimination of air pollutant, heavy metals, and particulate matter. The observations also confirmed that plants on a green roof growing on a soil layer absorb an average of 74% of rain water and then allow it to evaporate. The selection of plants for green roofs should mainly focus on how effectively they improve urban environmental parameters and remove air pollutants. The results of the study of the two green roof models on a laboratory scale are necessary to work out the parameters of layers of the roof and select the most appropriate plants for the reference research object on the roof of one of buildings of the University of Opole.

scholarly journals Measuring the Effect of the Internet on Economic Growth: The Case of Saudi Arabia

2020 ◽  
Vol 12 (12) ◽  
pp. 61
Author(s):  
Hisham J. Bardesi
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Saudi Arabia ◽  
Internet Access ◽  
Ordinary Least Squares ◽  
The Internet ◽  
Macroeconomic Performance ◽  
The Impact

The purpose of this study is to examine and assess the impact of the Internet on economic growth in Saudi Arabia. Various studies show that there is a relationship between the growth rate of GDP and the Internet, as estimated by Internet user numbers. In this paper, the ordinary least squares (OLS) model is utilized to study the economic impact of Internet Access from 1994 to 2018, which has had a profound effect on the market structure of many sectors and Saudi&rsquo;s global macroeconomic performance. The study constructs a model to investigate any significant impact of the Internet on the Saudi economy. Finally, this paper suggests that an understanding of the role of the Internet is essential for policymakers who plan to promote new forms of economic growth in the future. To take a long-term view implies working on technologies that could improve the economy and people&rsquo;s lives by creating a technological ecosystem in and around Saudi Arabia, along with other major economies.

scholarly journals Public health air pollution impacts of pathway options to meet the 2050 UK Climate Change Act target: a modelling study

2018 ◽  
Vol 6 (7) ◽  
pp. 1-124
Author(s):  
Martin L Williams ◽  
Sean Beevers ◽  
Nutthida Kitwiroon ◽  
David Dajnak ◽  
Heather Walton ◽  
...  
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Air Pollution ◽  
Great Britain ◽  
Road Transport ◽  
Air Pollutant ◽  
Life Years ◽  
The Uk ◽  
The Impact

BackgroundThe UK’sClimate Change Act 2008(CCA; Great Britain.Climate Change Act 2008. Chapter 27. London: The Stationery Office; 2008) requires a reduction of 80% in carbon dioxide-equivalent emissions by 2050 on a 1990 base. This project quantified the impact of air pollution on health from four scenarios involving particulate matter of ≤ 2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Two scenarios met the CCA target: one with limited nuclear power build (nuclear replacement option; NRPO) and one with no policy constraint on nuclear (low greenhouse gas). Another scenario envisaged no further climate actions beyond those already agreed (‘baseline’) and the fourth kept 2011 concentrations constant to 2050 (‘2011’).MethodsThe UK Integrated MARKAL–EFOM System (UKTM) energy system model was used to develop the scenarios and produce projections of fuel use; these were used to produce air pollutant emission inventories for Great Britain (GB) for each scenario. The inventories were then used to run the Community Multiscale Air Quality model ‘air pollution model’ to generate air pollutant concentration maps across GB, which then, combined with relationships between concentrations and health outcomes, were used to calculate the impact on health from the air pollution emitted in each scenario. This is a significant improvement on previous health impact studies of climate policies, which have relied on emissions changes. Inequalities in exposure in different socioeconomic groups were also calculated, as was the economic impact of the pollution emissions.ResultsConcentrations of NO2declined significantly because of a high degree of electrification of the GB road transport fleet, although the NRPO scenario shows large increases in oxides of nitrogen emissions from combined heat and power (CHP) sources. Concentrations of PM2.5show a modest decrease by 2050, which would have been larger if it had not been for a significant increase in biomass (wood burning) use in the two CCA scenarios peaking in 2035. The metric quantifying long-term exposure to O3is projected to decrease, while the important short-term O3exposure metric increases. Large projected increases in future GB vehicle kilometres lead to increased non-exhaust PM2.5and particulate matter of ≤ 10 µm emissions. The two scenarios which achieve the CCA target resulted in more life-years lost from long-term exposures to PM2.5than in the baseline scenario. This is an opportunity lost and arises largely from the increase in biomass use, which is projected to peak in 2035. Reduced long-term exposures to NO2lead to many more life-years saved in the ‘CCA-compliant’ scenarios, but the association used may overestimate the effects of NO2itself. The more deprived populations are estimated currently to be exposed to higher concentrations than those less deprived, the contrast being largest for NO2. Despite reductions in concentrations in 2050, the most socioeconomically deprived are still exposed to higher concentrations than the less deprived.LimitationsModelling of the atmosphere is always uncertain; we have shown the model to be acceptable through comparison with observations. The necessary complexity of the modelling system has meant that only a small number of scenarios were run.ConclusionsWe have established a system which can be used to explore a wider range of climate policy scenarios, including more European and global scenarios as well as local measures. Future work could explore wood burning in more detail, in terms of the sectors in which it might be burned and the spatial distribution of this across the UK. Further analyses of options for CHP could also be explored. Non-exhaust emissions from road transport are an important source of particles and emission factors are uncertain. Further research on this area coupled with our modelling would be a valuable area of research.FundingThe National Institute for Health Research Public Health Research programme.

scholarly journals Merging ground-based sunshine duration observations with satellite cloud and aerosol retrievals to produce high-resolution long-term surface solar radiation over China

2021 ◽  
Vol 13 (3) ◽  
pp. 907-922
Author(s):  
Fei Feng ◽  
Kaicun Wang
Keyword(s):  
Standard Deviation ◽  
High Resolution ◽  
Solar Radiation ◽  
Spatial Resolution ◽  
Sunshine Duration ◽  
Ordinary Least Squares ◽  
Cloud Fraction ◽  
Surface Solar Radiation ◽  
The Impact

Abstract. Although great progress has been made in estimating surface solar radiation (Rs) from meteorological observations, satellite retrieval, and reanalysis, getting best-estimated long-term variations in Rs are sorely needed for climate studies. It has been shown that Rs data derived from sunshine duration (SunDu) can provide reliable long-term variability, but such data are available at sparsely distributed weather stations. Here, we merge SunDu-derived Rs with satellite-derived cloud fraction and aerosol optical depth (AOD) to generate high-spatial-resolution (0.1∘) Rs over China from 2000 to 2017. The geographically weighted regression (GWR) and ordinary least-squares regression (OLS) merging methods are compared, and GWR is found to perform better. Based on the SunDu-derived Rs from 97 meteorological observation stations, which are co-located with those that direct Rs measurement sites, the GWR incorporated with satellite cloud fraction and AOD data produces monthly Rs with R2=0.97 and standard deviation =11.14 W m−2, while GWR driven by only cloud fraction produces similar results with R2=0.97 and standard deviation =11.41 W m−2. This similarity is because SunDu-derived Rs has included the impact of aerosols. This finding can help to build long-term Rs variations based on cloud data, such as Advanced Very High Resolution Radiometer (AVHRR) cloud retrievals, especially before 2000, when satellite AOD retrievals are not unavailable. The merged Rs product at a spatial resolution of 0.1∘ in this study can be downloaded at https://doi.org/10.1594/PANGAEA.921847 (Feng and Wang, 2020).

scholarly journals Long-term trends of hospital admissions among patients with cancer following the 2015 earthquake: a single institution observational study in Kathmandu, Nepal

BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e026746 ◽  
Author(s):  
Anup Uprety ◽  
Akihiko Ozaki ◽  
Asaka Higuchi ◽  
Bikal Ghimire ◽  
Toyoaki Sawano ◽  
...  
Keyword(s):  
Cancer Patient ◽  
Low Income ◽  
Negative Binomial ◽  
Hospital Admissions ◽  
Patients With Cancer ◽  
Nepal Earthquake ◽  
Patient Admissions ◽  
The Impact ◽  
2015 Nepal Earthquake

ObjectivesLittle is known regarding how natural disasters affect patients with cancer in low-income and middle-income countries. The objective of the present study was to assess the impact of the 2015 Nepal earthquake on the admission of patients with cancer at a core medical institution in Kathmandu.Design, setting and participantsWe considered all 3520 cancer patient admissions to Tribhuvan University Teaching Hospital, from 25 April 2013 to 24 April 2017 (2 years before and 2 years after the earthquake).Outcome measuresThe number of cancer patient admissions was calculated for each month. Using a negative binomial model, we estimated the incidence rate ratio (IRR) for admission numbers each month after the earthquake compared with the pre-earthquake baseline and investigated chronological change.ResultsThe total admission number in the first month after the earthquake was decreased compared with that of the predisaster baseline (IRR=0.66, 95% CI 0.43 to 1.00), which largely reflected decreased admissions of patients from outside of the most disaster-affected districts. From the second month, the admission number consistently exceeded the predisaster baseline for the remaining postdisaster period. In contrast to the month of the disaster, the continuation of increased admissions was most prominent among those from outside of the most affected districts.ConclusionsAfter a transient decrease immediately following the 2015 Nepal earthquake, there was a long-term increase in cancer patient admissions in a core hospital in Kathmandu. These changes were seen most prominently in patients from outside the most disaster affected areas.

scholarly journals Air pollutants and outpatient visits for cardiovascular disease in a severe haze-fog city: Shijiazhuang, China

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Fengzhu Tan ◽  
Weijie Wang ◽  
Sufen Qi ◽  
Haidong Kan ◽  
Xinpei Yu ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Air Pollutants ◽  
Attributable Risk ◽  
Air Pollutant ◽  
Outpatient Visits ◽  
Pollutant Concentrations ◽  
Main Factors ◽  
High Concentrations ◽  
Air Pollutant Concentrations ◽  
The Impact

Abstract Background Many studies have reported the impact of air pollution on cardiovascular disease (CVD), but few of these studies were conducted in severe haze-fog areas. The present study focuses on the impact of different air pollutant concentrations on daily CVD outpatient visits in a severe haze-fog city. Methods Data regarding daily air pollutants and outpatient visits for CVD in 2013 were collected, and the association between six pollutants and CVD outpatient visits was explored using the least squares mean (LSmeans) and logistic regression. Adjustments were made for days of the week, months, air temperature and relative humidity. Results The daily CVD outpatient visits for particulate matter (PM10 and PM2.5), sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) in the 90th-quantile group were increased by 30.01, 29.42, 17.68, 14.98, 29.34%, and − 19.87%, respectively, compared to those in the <10th-quantile group. Odds ratios (ORs) and 95% confidence intervals (CIs) for the increase in daily CVD outpatient visits in PM10 300- and 500-μg/m3, PM2.5 100- and 300-μg/m3 and CO 3-mg/m3 groups were 2.538 (1.070–6.020), 7.781 (1.681–36.024), 3.298 (1.559–6.976), 8.72 (1.523–49.934), and 5.808 (1.016–33.217), respectively, and their corresponding attributable risk percentages (AR%) were 60.6, 87.15, 69.68, 88.53 and 82.78%, respectively. The strongest associations for PM10, PM2.5 and CO were found only in lag 0 and lag 1. The ORs for the increase in CVD outpatient visits per increase in different units of the six pollutants were also analysed. Conclusions All five air pollutants except O3 were positively associated with the increase in daily CVD outpatient visits in lag 0. The high concentrations of PM10, PM2.5 and CO heightened not only the percentage but also the risk of increased daily CVD outpatient visits. PM10, PM2.5 and CO may be the main factors of CVD outpatient visits.

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