Cargando…

Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis

INTRODUCTION: 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. MATERIALS AND METHODS: In this study, we used the info...

Descripción completa

Detalles Bibliográficos
Autores principales: Tazhibi, Mahdi, Sarrafzade, Sheida, Amini, Masoud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165112/
https://www.ncbi.nlm.nih.gov/pubmed/25250351
http://dx.doi.org/10.4103/2277-9531.139251
_version_ 1782335060688502784
author Tazhibi, Mahdi
Sarrafzade, Sheida
Amini, Masoud
author_facet Tazhibi, Mahdi
Sarrafzade, Sheida
Amini, Masoud
author_sort Tazhibi, Mahdi
collection PubMed
description INTRODUCTION: 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. MATERIALS AND METHODS: 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. RESULTS: 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. DISCUSSION: 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. CONCLUSION: Although factor analysis is a powerful way to reduce the number of variables, in this study did not worked very well.
format Online
Article
Text
id pubmed-4165112
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Medknow Publications & Media Pvt Ltd
record_format MEDLINE/PubMed
spelling pubmed-41651122014-09-23 Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis Tazhibi, Mahdi Sarrafzade, Sheida Amini, Masoud J Educ Health Promot Original Article INTRODUCTION: 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. MATERIALS AND METHODS: 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. RESULTS: 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. DISCUSSION: 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. CONCLUSION: Although factor analysis is a powerful way to reduce the number of variables, in this study did not worked very well. Medknow Publications & Media Pvt Ltd 2014-08-28 /pmc/articles/PMC4165112/ /pubmed/25250351 http://dx.doi.org/10.4103/2277-9531.139251 Text en Copyright: © 2014 Tazhibi M. http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Original Article
Tazhibi, Mahdi
Sarrafzade, Sheida
Amini, Masoud
Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis
title Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis
title_full Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis
title_fullStr Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis
title_full_unstemmed Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis
title_short Retinopathy risk factors in type II diabetic patients using factor analysis and discriminant analysis
title_sort retinopathy risk factors in type ii diabetic patients using factor analysis and discriminant analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165112/
https://www.ncbi.nlm.nih.gov/pubmed/25250351
http://dx.doi.org/10.4103/2277-9531.139251
work_keys_str_mv AT tazhibimahdi retinopathyriskfactorsintypeiidiabeticpatientsusingfactoranalysisanddiscriminantanalysis
AT sarrafzadesheida retinopathyriskfactorsintypeiidiabeticpatientsusingfactoranalysisanddiscriminantanalysis
AT aminimasoud retinopathyriskfactorsintypeiidiabeticpatientsusingfactoranalysisanddiscriminantanalysis