Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis
Diabetes is one of the most common chronic diseases in the world. Incidence and prevalence of diabetes are increasing in developing countries as well as in Iran. Retinopathy is the most common chronic disorder in diabetic patients. In this study, we used the information of diabetic patients' re...
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Veröffentlicht in: | Journal of Education and Health Promotion 2014, Vol.3 (1), p.85 |
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description | Diabetes is one of the most common chronic diseases in the world. Incidence and prevalence of diabetes are increasing in developing countries as well as in Iran. Retinopathy is the most common chronic disorder in diabetic patients.
In this study, we used the information of diabetic patients' reports that refer to endocrine and metabolism research center of Isfahan University of Medical Sciences to determine diabetic retinopathy risk factors. We used factor analysis to extract retinopathy's factors. Factor analysis is using to analyze multivariate data, in which a large number of dependent variables summarize into the fewer independent factors. Factor analysis is applied, in both diabetic and nondiabetic patients, separately. To investigate the efficacy of factor analysis, we used discriminant analysis.
We investigated 3535 diabetic patients whose prevalence of retinopathy was 53.4%. Six factors were extracted in each group (i.e. diabetic and nondiabetic groups). These six factors were explained 69.5% and 69.6% of total variance in diabetic and nondiabetic groups, respectively. Using original variables such as sex, weight, blood sugar control method, and some laboratory variables, the correct classification rate of discriminant analysis was identified as 67.4%. However, it decreased to 49.5% by using extracted factors.
Retinopathy is one of the important disorders in diabetic patients that involves a large number of variables and can affect its incidence. By the method of factor analysis, we summarize diabetic retinopathy risk factors. Factor analysis is applied separately, in two diabetic and nondiabetic group. In this way, 10 variables were summarized into the six factors. Discriminant analysis was used to investigate the efficacy of factor analysis.
Although factor analysis is a powerful way to reduce the number of variables, in this study did not worked very well. |
doi_str_mv | 10.4103/2277-9531.139251 |
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In this study, we used the information of diabetic patients' reports that refer to endocrine and metabolism research center of Isfahan University of Medical Sciences to determine diabetic retinopathy risk factors. We used factor analysis to extract retinopathy's factors. Factor analysis is using to analyze multivariate data, in which a large number of dependent variables summarize into the fewer independent factors. Factor analysis is applied, in both diabetic and nondiabetic patients, separately. To investigate the efficacy of factor analysis, we used discriminant analysis.
We investigated 3535 diabetic patients whose prevalence of retinopathy was 53.4%. Six factors were extracted in each group (i.e. diabetic and nondiabetic groups). These six factors were explained 69.5% and 69.6% of total variance in diabetic and nondiabetic groups, respectively. Using original variables such as sex, weight, blood sugar control method, and some laboratory variables, the correct classification rate of discriminant analysis was identified as 67.4%. However, it decreased to 49.5% by using extracted factors.
Retinopathy is one of the important disorders in diabetic patients that involves a large number of variables and can affect its incidence. By the method of factor analysis, we summarize diabetic retinopathy risk factors. Factor analysis is applied separately, in two diabetic and nondiabetic group. In this way, 10 variables were summarized into the six factors. Discriminant analysis was used to investigate the efficacy of factor analysis.
Although factor analysis is a powerful way to reduce the number of variables, in this study did not worked very well.</description><identifier>ISSN: 2277-9531</identifier><identifier>EISSN: 2319-6440</identifier><identifier>DOI: 10.4103/2277-9531.139251</identifier><identifier>PMID: 25250351</identifier><language>eng</language><publisher>India: Medknow Publications & Media Pvt. Ltd</publisher><subject>Blindness ; Blood pressure ; Developed Nations ; Diabetes ; Diabetic retinopathy ; Discriminant analysis ; Disease ; Environmental Influences ; Error of Measurement ; Factor Analysis ; Hypertension ; Industrialized nations ; Insulin ; Original ; Patients ; Principals ; Risk factors ; Smoking ; Statistical Analysis ; Studies ; Variables</subject><ispartof>Journal of Education and Health Promotion, 2014, Vol.3 (1), p.85</ispartof><rights>Copyright Medknow Publications & Media Pvt Ltd Aug 2014</rights><rights>Copyright: © 2014 Tazhibi M. 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2691-584c9412fa243b633d0b4b7d14f1f41da4ef6e022b0bd860dff3f96864dc50083</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165112/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165112/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,4010,27904,27905,27906,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25250351$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tazhibi, Mahdi</creatorcontrib><creatorcontrib>Sarrafzade, Sheida</creatorcontrib><creatorcontrib>Amini, Masoud</creatorcontrib><title>Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis</title><title>Journal of Education and Health Promotion</title><addtitle>J Educ Health Promot</addtitle><description>Diabetes is one of the most common chronic diseases in the world. Incidence and prevalence of diabetes are increasing in developing countries as well as in Iran. Retinopathy is the most common chronic disorder in diabetic patients.
In this study, we used the information of diabetic patients' reports that refer to endocrine and metabolism research center of Isfahan University of Medical Sciences to determine diabetic retinopathy risk factors. We used factor analysis to extract retinopathy's factors. Factor analysis is using to analyze multivariate data, in which a large number of dependent variables summarize into the fewer independent factors. Factor analysis is applied, in both diabetic and nondiabetic patients, separately. To investigate the efficacy of factor analysis, we used discriminant analysis.
We investigated 3535 diabetic patients whose prevalence of retinopathy was 53.4%. Six factors were extracted in each group (i.e. diabetic and nondiabetic groups). These six factors were explained 69.5% and 69.6% of total variance in diabetic and nondiabetic groups, respectively. Using original variables such as sex, weight, blood sugar control method, and some laboratory variables, the correct classification rate of discriminant analysis was identified as 67.4%. However, it decreased to 49.5% by using extracted factors.
Retinopathy is one of the important disorders in diabetic patients that involves a large number of variables and can affect its incidence. By the method of factor analysis, we summarize diabetic retinopathy risk factors. Factor analysis is applied separately, in two diabetic and nondiabetic group. In this way, 10 variables were summarized into the six factors. Discriminant analysis was used to investigate the efficacy of factor analysis.
Although factor analysis is a powerful way to reduce the number of variables, in this study did not worked very well.</description><subject>Blindness</subject><subject>Blood pressure</subject><subject>Developed Nations</subject><subject>Diabetes</subject><subject>Diabetic retinopathy</subject><subject>Discriminant analysis</subject><subject>Disease</subject><subject>Environmental Influences</subject><subject>Error of Measurement</subject><subject>Factor Analysis</subject><subject>Hypertension</subject><subject>Industrialized nations</subject><subject>Insulin</subject><subject>Original</subject><subject>Patients</subject><subject>Principals</subject><subject>Risk factors</subject><subject>Smoking</subject><subject>Statistical Analysis</subject><subject>Studies</subject><subject>Variables</subject><issn>2277-9531</issn><issn>2319-6440</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpVkctLAzEQxoMottTePUnA89ZMXrt7EaT4KBQE0XPIbpI22u6uyVbof29KH-gpA99vvnwzg9A1kAkHwu4ozfOsFAwmwEoq4AwNKYMyk5yT81Qf5QEax-grwgtZClHISzSgggrCBAyRfbO9b9pO98stDj5-Yafrvg0R-wb3287i2Qwbr6uE1Thh3jZ9xJvom8UBxbrRq230MRUmsbEOfu0b3fQn5QpdOL2Kdnx4R-jj6fF9-pLNX59n04d5VlNZQiYKXpccqNOUs0oyZkjFq9wAd-A4GM2tk5ZQWpHKFJIY55grZSG5qQUhBRuh-71vt6nW1tQpa9Ar1aVAOmxVq736rzR-qRbtj-IgBQBNBrcHg9B-b2zs1We7CWmKqCAnUHIucpIosqfq0MYYrDv9AETtbqN2y1e75av9bVLLzd9kp4bjJdgvmuqLXQ</recordid><startdate>2014</startdate><enddate>2014</enddate><creator>Tazhibi, Mahdi</creator><creator>Sarrafzade, Sheida</creator><creator>Amini, Masoud</creator><general>Medknow Publications & Media Pvt. 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Incidence and prevalence of diabetes are increasing in developing countries as well as in Iran. Retinopathy is the most common chronic disorder in diabetic patients.
In this study, we used the information of diabetic patients' reports that refer to endocrine and metabolism research center of Isfahan University of Medical Sciences to determine diabetic retinopathy risk factors. We used factor analysis to extract retinopathy's factors. Factor analysis is using to analyze multivariate data, in which a large number of dependent variables summarize into the fewer independent factors. Factor analysis is applied, in both diabetic and nondiabetic patients, separately. To investigate the efficacy of factor analysis, we used discriminant analysis.
We investigated 3535 diabetic patients whose prevalence of retinopathy was 53.4%. Six factors were extracted in each group (i.e. diabetic and nondiabetic groups). These six factors were explained 69.5% and 69.6% of total variance in diabetic and nondiabetic groups, respectively. Using original variables such as sex, weight, blood sugar control method, and some laboratory variables, the correct classification rate of discriminant analysis was identified as 67.4%. However, it decreased to 49.5% by using extracted factors.
Retinopathy is one of the important disorders in diabetic patients that involves a large number of variables and can affect its incidence. By the method of factor analysis, we summarize diabetic retinopathy risk factors. Factor analysis is applied separately, in two diabetic and nondiabetic group. In this way, 10 variables were summarized into the six factors. Discriminant analysis was used to investigate the efficacy of factor analysis.
Although factor analysis is a powerful way to reduce the number of variables, in this study did not worked very well.</abstract><cop>India</cop><pub>Medknow Publications & Media Pvt. Ltd</pub><pmid>25250351</pmid><doi>10.4103/2277-9531.139251</doi><oa>free_for_read</oa></addata></record> |
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subjects | Blindness Blood pressure Developed Nations Diabetes Diabetic retinopathy Discriminant analysis Disease Environmental Influences Error of Measurement Factor Analysis Hypertension Industrialized nations Insulin Original Patients Principals Risk factors Smoking Statistical Analysis Studies Variables |
title | Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis |
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