Application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease
Our research goal was to perform a comparative analysis of regression analysis application and tree classification appli-cation in calculating additional population risk on the example of ischemic heart diseases (IHD). Our research object was a random population sample comprising both male and femal...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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FBSI “Federal Scientific Center for Medical and Preventive Health Risk Management Technologies”
2017-09-01
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| Series: | Analiz Riska Zdorovʹû |
| Subjects: | |
| Online Access: | http://journal.fcrisk.ru/eng/2017/3/4 |
| _version_ | 1818344754398625792 |
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| author | S.A. Maksimov D.P. Tsygankova G.V. Artamonova |
| author_facet | S.A. Maksimov D.P. Tsygankova G.V. Artamonova |
| author_sort | S.A. Maksimov |
| collection | DOAJ |
| description | Our research goal was to perform a comparative analysis of regression analysis application and tree classification appli-cation in calculating additional population risk on the example of ischemic heart diseases (IHD). Our research object was a random population sample comprising both male and female population aged 25-64 in Kemerovo region (1,628 people) within ESSE-RF multi-centered epidemiologic research. We considered the following IHD risk factors: lipid metabolism parameters, arterial hypertension, lifestyle factors, psychoemotional peculiarities, and social parameters. IHD occurrence was assessed as per sum of 3 epidemiologic criteria: on the basis of ECG changes coding as per Minnesota code, Rose questionnaire, and car-diac infarction in case history. We calculated additional population IHD risk determined by risk factors as per unified original algorithms, but with various statistic analysis techniques: logistic regression analysis and classification trees.
We built up mathematic models for IHD probability as per risk factors, with predictive significance equal to 83.8% for logistic regression analysis and to 71.9% for classification trees. The applied statistical analysis techniques show different contributions made by risk factors into IHD prevalence which results from absence of correlation between them.
IBD risk additional to population one and determined by risk factors as per both statistical analysis techniques in sex-age groups changed from negative values in age groups younger than 45 to positive values in older people. Increase in addi-tional IHD risk in aged groups as per both techniques was practically linear with slight deviations. Difference in additional population risk calculated as per two statistical analysis techniques was insignificant and as a rule it didn't exceed 1.5%. Consequently, both techniques give similar results and can be equally used in calculating IHD population risk. |
| first_indexed | 2024-12-13T16:51:30Z |
| format | Article |
| id | doaj.art-2fb041cff2904e4c8d7bee0e42415ca5 |
| institution | Directory Open Access Journal |
| issn | 2308-1155 2308-1163 |
| language | English |
| last_indexed | 2024-12-13T16:51:30Z |
| publishDate | 2017-09-01 |
| publisher | FBSI “Federal Scientific Center for Medical and Preventive Health Risk Management Technologies” |
| record_format | Article |
| series | Analiz Riska Zdorovʹû |
| spelling | doaj.art-2fb041cff2904e4c8d7bee0e42415ca52022-12-21T23:38:01ZengFBSI “Federal Scientific Center for Medical and Preventive Health Risk Management Technologies”Analiz Riska Zdorovʹû2308-11552308-11632017-09-013313910.21668/health.risk/2017.3.04.engApplication of regression analysis and classification trees in calculating additional population risk of ischemic heart diseaseS.A. Maksimov0D.P. Tsygankova1G.V. Artamonova2Scientific Institution Research Institute for Complex Issues of Cardiovascular DiseasesScientific Institution Research Institute for Complex Issues of Cardiovascular DiseasesScientific Institution Research Institute for Complex Issues of Cardiovascular DiseasesOur research goal was to perform a comparative analysis of regression analysis application and tree classification appli-cation in calculating additional population risk on the example of ischemic heart diseases (IHD). Our research object was a random population sample comprising both male and female population aged 25-64 in Kemerovo region (1,628 people) within ESSE-RF multi-centered epidemiologic research. We considered the following IHD risk factors: lipid metabolism parameters, arterial hypertension, lifestyle factors, psychoemotional peculiarities, and social parameters. IHD occurrence was assessed as per sum of 3 epidemiologic criteria: on the basis of ECG changes coding as per Minnesota code, Rose questionnaire, and car-diac infarction in case history. We calculated additional population IHD risk determined by risk factors as per unified original algorithms, but with various statistic analysis techniques: logistic regression analysis and classification trees. We built up mathematic models for IHD probability as per risk factors, with predictive significance equal to 83.8% for logistic regression analysis and to 71.9% for classification trees. The applied statistical analysis techniques show different contributions made by risk factors into IHD prevalence which results from absence of correlation between them. IBD risk additional to population one and determined by risk factors as per both statistical analysis techniques in sex-age groups changed from negative values in age groups younger than 45 to positive values in older people. Increase in addi-tional IHD risk in aged groups as per both techniques was practically linear with slight deviations. Difference in additional population risk calculated as per two statistical analysis techniques was insignificant and as a rule it didn't exceed 1.5%. Consequently, both techniques give similar results and can be equally used in calculating IHD population risk.http://journal.fcrisk.ru/eng/2017/3/4regression analysisrisk factorischemic heart diseasepopulation riskpredictive models |
| spellingShingle | S.A. Maksimov D.P. Tsygankova G.V. Artamonova Application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease Analiz Riska Zdorovʹû regression analysis risk factor ischemic heart disease population risk predictive models |
| title | Application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease |
| title_full | Application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease |
| title_fullStr | Application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease |
| title_full_unstemmed | Application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease |
| title_short | Application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease |
| title_sort | application of regression analysis and classification trees in calculating additional population risk of ischemic heart disease |
| topic | regression analysis risk factor ischemic heart disease population risk predictive models |
| url | http://journal.fcrisk.ru/eng/2017/3/4 |
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