Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors
碩士 === 中原大學 === 工業與系統工程研究所 === 104 === This study is to establish a multivariate-time-series model for Framingham coronary-heart-disease (CHD) risk factors, which are age, total cholesterol, high density lipoprotein (HDL) cholesterol, systolic blood pressure, smoking, and the presence/absence of dia...
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ndltd-TW-104CYCU50300572017-08-27T04:30:05Z http://ndltd.ncl.edu.tw/handle/33221741199825165202 Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors Framingham冠狀動脈心臟病風險因子之建模及敏感度分析 Cheng-En Lee 李承恩 碩士 中原大學 工業與系統工程研究所 104 This study is to establish a multivariate-time-series model for Framingham coronary-heart-disease (CHD) risk factors, which are age, total cholesterol, high density lipoprotein (HDL) cholesterol, systolic blood pressure, smoking, and the presence/absence of diabetes. To investigate effects of the six risk factors, we performed a sensitivity analysis via conducting simulation experiments of the proposed probability model. Our proposed probability model is based on the VARTA multivariate time series model by Biller and Nelson (2003). We arbitrarily set the lag to 1 (with time unit being year). We used the LIONS data from Years 2006 to 2011, provided by Landseed Hospital in Chungli County, Taoyuan City in Taiwan. Since the VARTA model assumes that the marginal distributions for different years are the same, we conducted the Friedman test; such hypothesis is accepted. Therefore, the marginal distributions and the lag-0 and lag-1 autocorrelation matrices can be modeled with the LIONS data. To determine the effects of the six risk factors on the probability of CHDs, we conducted simulation experiments of the VARTA model. For each simulated case, a 10-year probability of CHD is evaluated based on Framingham risk scores. The distributions of the CHD probability for different levels of each risk factor are then compared. Sensitivity analysis shows that higher probability of coronary diseases is found in males than females. Besides, increasing values of factors in age, total cholesterol and systolic blood pressure results in a larger mode of the CHD probability. Furthermore, people with HDL cholesterol below 60 mg/dl have a higher CHD probability than people with HDL cholesterol above 60 mg/dl. In addition, people with diabetes have a higher CHD probability than people without diabetes; people with smoking habit have a higher CHD probability than people without. We further divided the CHD probability into three intervals: <10%、[10%,20%), and ≧20%, indicating low, medium, and high risk, respectively. The sensitivity analysis shows that the increase in age and/or presence of diabetes decrease the proportion of people with low risk and increases the proportion of people with high risk. Furthermore, the increase in total cholesterol, increases in high blood pressure, and presence of smoke decreases the proportion of people with low risk and increases the proportion of people with medium risk. Finally, for both males and females, the CHD probability is more sensitive to the age, systolic blood pressure, and diabetes than the other factors. Hui-Fen Chen 陳慧芬 2016 學位論文 ; thesis 82 zh-TW |
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碩士 === 中原大學 === 工業與系統工程研究所 === 104 === This study is to establish a multivariate-time-series model for Framingham coronary-heart-disease (CHD) risk factors, which are age, total cholesterol, high density lipoprotein (HDL) cholesterol, systolic blood pressure, smoking, and the presence/absence of diabetes. To investigate effects of the six risk factors, we performed a sensitivity analysis via conducting simulation experiments of the proposed probability model.
Our proposed probability model is based on the VARTA multivariate time series model by Biller and Nelson (2003). We arbitrarily set the lag to 1 (with time unit being year). We used the LIONS data from Years 2006 to 2011, provided by Landseed Hospital in Chungli County, Taoyuan City in Taiwan. Since the VARTA model assumes that the marginal distributions for different years are the same, we conducted the Friedman test; such hypothesis is accepted. Therefore, the marginal distributions and the lag-0 and lag-1 autocorrelation matrices can be modeled with the LIONS data.
To determine the effects of the six risk factors on the probability of CHDs, we conducted simulation experiments of the VARTA model. For each simulated case, a 10-year probability of CHD is evaluated based on Framingham risk scores. The distributions of the CHD probability for different levels of each risk factor are then compared.
Sensitivity analysis shows that higher probability of coronary diseases is found in males than females. Besides, increasing values of factors in age, total cholesterol and systolic blood pressure results in a larger mode of the CHD probability. Furthermore, people with HDL cholesterol below 60 mg/dl have a higher CHD probability than people with HDL cholesterol above 60 mg/dl. In addition, people with diabetes have a higher CHD probability than people without diabetes; people with smoking habit have a higher CHD probability than people without. We further divided the CHD probability into three intervals: <10%、[10%,20%), and ≧20%, indicating low, medium, and high risk, respectively. The sensitivity analysis shows that the increase in age and/or presence of diabetes decrease the proportion of people with low risk and increases the proportion of people with high risk. Furthermore, the increase in total cholesterol, increases in high blood pressure, and presence of smoke decreases the proportion of people with low risk and increases the proportion of people with medium risk. Finally, for both males and females, the CHD probability is more sensitive to the age, systolic blood pressure, and diabetes than the other factors.
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author2 |
Hui-Fen Chen |
author_facet |
Hui-Fen Chen Cheng-En Lee 李承恩 |
author |
Cheng-En Lee 李承恩 |
spellingShingle |
Cheng-En Lee 李承恩 Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors |
author_sort |
Cheng-En Lee |
title |
Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors |
title_short |
Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors |
title_full |
Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors |
title_fullStr |
Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors |
title_full_unstemmed |
Modeling and Sensitivity Analysis for Framingham Coronary-Heart-Disease Risk Factors |
title_sort |
modeling and sensitivity analysis for framingham coronary-heart-disease risk factors |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/33221741199825165202 |
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