Forecasting number of diabetes type ii patients
Impact of chronic diseases like diabetes on quality of human life is widely known and studies on it will help people living to their fullest life potential, but little or no studies were focused on diabetes among United Arab Emirates (UAE) residents. Forecasting the number of diabetes cases in the U...
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my-utm-ep.813982019-08-23T04:07:05Z Forecasting number of diabetes type ii patients 2017 Haroun, Suheer QA Mathematics Impact of chronic diseases like diabetes on quality of human life is widely known and studies on it will help people living to their fullest life potential, but little or no studies were focused on diabetes among United Arab Emirates (UAE) residents. Forecasting the number of diabetes cases in the UAE are explored in this thesis. A suitable ARIMA model for forecasting mortality rates due to diabetic was determined. Random samples of 524 diabetic patients from a medical clinic in UAE were collected. Controllable factors that can prevent or delay the onset of Type-2 diabetes were identified. Further analysis using logistic regression model was carried out. A secondary data of diabetes mortalities obtained from the Ministry of Health of UAE representing the whole country were used to forecast diabetes mortality rates. This research investigated the factors associated with Type-2 diabetes patients that may help to reduce number of diabetics’ patients in the future. Other statistical analysis explored includes Chi Square, Correlations, Analysis of variance which is used to determine the significant factors contributing to Type-2 diabetes patients. The result shows that the method used has successfully determined the significant risk factors associated with Type-2 diabetes which was marital status, waist size, intake of vegetables, blood pressure, and family history of Type-2 diabetes. This research shows that the best fitted model for the UAE-Citizens data is ARIMA (2, 2, 1) with MAPE 8.894 percent. This model forecast the number of diabetics for 2017 and 2018 to be (157.3879) and (165.0415) respectively, showing an increase rate trend. The best fitted model in this study for the UAE-Residents data is ARIMA (1, 1, 1) with MAPE 4.218 percent. This model successfully forecast the number of diabetics for 2017 and 2018 to be (240.26) and (229.10) respectively, showing a fluctuating rate trend. This study has enriched the pool of data for diabetics’ research for the UAE and the findings are substantial for the planning and preventive strategy for Type-2 diabetes and identifying the pre-diabetics. 2017 Thesis http://eprints.utm.my/id/eprint/81398/ http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:124913 masters Universiti Teknologi Malaysia Mathematics |
| institution |
Universiti Teknologi Malaysia |
| collection |
UTM Institutional Repository |
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QA Mathematics |
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QA Mathematics Haroun, Suheer Forecasting number of diabetes type ii patients |
| description |
Impact of chronic diseases like diabetes on quality of human life is widely known and studies on it will help people living to their fullest life potential, but little or no studies were focused on diabetes among United Arab Emirates (UAE) residents. Forecasting the number of diabetes cases in the UAE are explored in this thesis. A suitable ARIMA model for forecasting mortality rates due to diabetic was determined. Random samples of 524 diabetic patients from a medical clinic in UAE were collected. Controllable factors that can prevent or delay the onset of Type-2 diabetes were identified. Further analysis using logistic regression model was carried out. A secondary data of diabetes mortalities obtained from the Ministry of Health of UAE representing the whole country were used to forecast diabetes mortality rates. This research investigated the factors associated with Type-2 diabetes patients that may help to reduce number of diabetics’ patients in the future. Other statistical analysis explored includes Chi Square, Correlations, Analysis of variance which is used to determine the significant factors contributing to Type-2 diabetes patients. The result shows that the method used has successfully determined the significant risk factors associated with Type-2 diabetes which was marital status, waist size, intake of vegetables, blood pressure, and family history of Type-2 diabetes. This research shows that the best fitted model for the UAE-Citizens data is ARIMA (2, 2, 1) with MAPE 8.894 percent. This model forecast the number of diabetics for 2017 and 2018 to be (157.3879) and (165.0415) respectively, showing an increase rate trend. The best fitted model in this study for the UAE-Residents data is ARIMA (1, 1, 1) with MAPE 4.218 percent. This model successfully forecast the number of diabetics for 2017 and 2018 to be (240.26) and (229.10) respectively, showing a fluctuating rate trend. This study has enriched the pool of data for diabetics’ research for the UAE and the findings are substantial for the planning and preventive strategy for Type-2 diabetes and identifying the pre-diabetics. |
| format |
Thesis |
| qualification_level |
Master's degree |
| author |
Haroun, Suheer |
| author_facet |
Haroun, Suheer |
| author_sort |
Haroun, Suheer |
| title |
Forecasting number of diabetes type ii patients |
| title_short |
Forecasting number of diabetes type ii patients |
| title_full |
Forecasting number of diabetes type ii patients |
| title_fullStr |
Forecasting number of diabetes type ii patients |
| title_full_unstemmed |
Forecasting number of diabetes type ii patients |
| title_sort |
forecasting number of diabetes type ii patients |
| granting_institution |
Universiti Teknologi Malaysia |
| granting_department |
Mathematics |
| publishDate |
2017 |
| _version_ |
1747818322155536384 |