A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, Iran
Background and Objective: This study aimed to evaluate the correlation between climatic parameters and air pollution with cardiovascular disease and its associated death during 2014 in Mashhad by time series model. Materials and Methods: Patient data (including outpatient and hospitalization) and ca...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | fas |
| Published: |
Tehran University of Medical Sciences
2020-11-01
|
| Series: | سلامت و محیط |
| Subjects: | |
| Online Access: | http://ijhe.tums.ac.ir/article-1-6473-en.html |
| _version_ | 1818590108478078976 |
|---|---|
| author | Sara Manochehrneya Mitra Mohammadi Reza Esmaeili Ahmad Vahdani |
| author_facet | Sara Manochehrneya Mitra Mohammadi Reza Esmaeili Ahmad Vahdani |
| author_sort | Sara Manochehrneya |
| collection | DOAJ |
| description | Background and Objective: This study aimed to evaluate the correlation between climatic parameters and air pollution with cardiovascular disease and its associated death during 2014 in Mashhad by time series model.
Materials and Methods: Patient data (including outpatient and hospitalization) and cardiovascular mortality were obtained from the emergency medical center and Ferdowsi organization of Mashhad. Climatic parameters such as temperature, pressure, relative humidity, wind speed, and rainfall were gathered from meteorological organization. Air pollutants data were collected from Mashhad environmental pollutants monitoring center for the statistical period of 2014-2015. In this study, Jenkins Box time series model (combined model of autoregression and moving average known as ARIMA) with significance level of 5% was used to investigate the effect of climatic parameters and air pollution values on cardiovascular disease and daily, weekly and monthly excess mortality rate. Then, the effect of various seasons on the total number of patients with cardiac issues and the resulting death was investigated by Kruskal-Wallis nonparametric test.
Results: The final model for determination of monthly correlation between climatic elements and air pollutants with the number of cardiovascular patients and its corresponding death was found to be best fitted by ARIMA (0,0,0). The monthly survey revealed that humidity (positive correlation), temperature (positive correlation), wind speed (negative correlation), and PM2.5 (negative correlation) with average values of 16.2471, 48.1628, 122.38, and 7.3905, respectively, had significant effects on the number of people experiencing cardiovascular disease. However, the monthly survey of mortality rate due to cardiovascular disease exhibited significant correlation (p < 0.05) with pressure (positive correlation), temperature (negative correlation), and rainfall (negative correlation) with average values of 6.5904, 1.5728, and 1.1704, respectively. The results showed a significant difference between the numbers of patients experiencing cardiovascular diseases in different seasons of the year with the highest recorded number of 3778 in autumn.
Conclusion: The results suggest moderate correlation between atmospheric elements and air pollutants with the numbers of people experiencing cardiovascular diseases in short periods; however, in the case of long-term mortality, the correlation was strong. This study showed that climatic elements and air pollutants effectively affect cardiovascular diseases, while only climatic elements played a significant role in mortality. The main challenge of the present study is that cardiovascular disease and its resulting death may be influenced by parameters other than those considered in this study, such as multiple individual and environmental confounding variables. |
| first_indexed | 2024-12-16T09:51:18Z |
| format | Article |
| id | doaj.art-54078c1489e7444e92905b68f8f0ef35 |
| institution | Directory Open Access Journal |
| issn | 2008-2029 2008-3718 |
| language | fas |
| last_indexed | 2024-12-16T09:51:18Z |
| publishDate | 2020-11-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | سلامت و محیط |
| spelling | doaj.art-54078c1489e7444e92905b68f8f0ef352022-12-21T22:36:03ZfasTehran University of Medical Sciencesسلامت و محیط2008-20292008-37182020-11-01133545558A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, IranSara Manochehrneya0Mitra Mohammadi1Reza Esmaeili2Ahmad Vahdani3 Department of Environmental Science, Faculty of Environmental Science, Kheradgarayn Motahar Institute of Higher Education, Mashhad, Iran Department of Environmental Science, Faculty of Environmental Science, Kheradgarayn Motahar Institute of Higher Education, Mashhad, Iran Deputy of Urban Services of Mashhad Municipality, Environmental Pollutants Monitoring Center, Mashhad, Iran Department of Environmental Science, Faculty of Environmental Science, Kheradgarayn Motahar Institute of Higher Education, Mashhad, Iran AND Laboratory Experts of the General Department of Environmental Protection of North Khorasan Province, Bojnourd, Iran Background and Objective: This study aimed to evaluate the correlation between climatic parameters and air pollution with cardiovascular disease and its associated death during 2014 in Mashhad by time series model. Materials and Methods: Patient data (including outpatient and hospitalization) and cardiovascular mortality were obtained from the emergency medical center and Ferdowsi organization of Mashhad. Climatic parameters such as temperature, pressure, relative humidity, wind speed, and rainfall were gathered from meteorological organization. Air pollutants data were collected from Mashhad environmental pollutants monitoring center for the statistical period of 2014-2015. In this study, Jenkins Box time series model (combined model of autoregression and moving average known as ARIMA) with significance level of 5% was used to investigate the effect of climatic parameters and air pollution values on cardiovascular disease and daily, weekly and monthly excess mortality rate. Then, the effect of various seasons on the total number of patients with cardiac issues and the resulting death was investigated by Kruskal-Wallis nonparametric test. Results: The final model for determination of monthly correlation between climatic elements and air pollutants with the number of cardiovascular patients and its corresponding death was found to be best fitted by ARIMA (0,0,0). The monthly survey revealed that humidity (positive correlation), temperature (positive correlation), wind speed (negative correlation), and PM2.5 (negative correlation) with average values of 16.2471, 48.1628, 122.38, and 7.3905, respectively, had significant effects on the number of people experiencing cardiovascular disease. However, the monthly survey of mortality rate due to cardiovascular disease exhibited significant correlation (p < 0.05) with pressure (positive correlation), temperature (negative correlation), and rainfall (negative correlation) with average values of 6.5904, 1.5728, and 1.1704, respectively. The results showed a significant difference between the numbers of patients experiencing cardiovascular diseases in different seasons of the year with the highest recorded number of 3778 in autumn. Conclusion: The results suggest moderate correlation between atmospheric elements and air pollutants with the numbers of people experiencing cardiovascular diseases in short periods; however, in the case of long-term mortality, the correlation was strong. This study showed that climatic elements and air pollutants effectively affect cardiovascular diseases, while only climatic elements played a significant role in mortality. The main challenge of the present study is that cardiovascular disease and its resulting death may be influenced by parameters other than those considered in this study, such as multiple individual and environmental confounding variables.http://ijhe.tums.ac.ir/article-1-6473-en.htmlair pollutionclimate elementscardiovascular diseasemortalitytime series model |
| spellingShingle | Sara Manochehrneya Mitra Mohammadi Reza Esmaeili Ahmad Vahdani A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, Iran سلامت و محیط air pollution climate elements cardiovascular disease mortality time series model |
| title | A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, Iran |
| title_full | A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, Iran |
| title_fullStr | A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, Iran |
| title_full_unstemmed | A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, Iran |
| title_short | A time series approach to estimate the association between health effects, climate factors and air pollution, Mashhad, Iran |
| title_sort | time series approach to estimate the association between health effects climate factors and air pollution mashhad iran |
| topic | air pollution climate elements cardiovascular disease mortality time series model |
| url | http://ijhe.tums.ac.ir/article-1-6473-en.html |
| work_keys_str_mv | AT saramanochehrneya atimeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran AT mitramohammadi atimeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran AT rezaesmaeili atimeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran AT ahmadvahdani atimeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran AT saramanochehrneya timeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran AT mitramohammadi timeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran AT rezaesmaeili timeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran AT ahmadvahdani timeseriesapproachtoestimatetheassociationbetweenhealtheffectsclimatefactorsandairpollutionmashhadiran |