Volume 1, Issue 1 (3-2015)
J Jiroft Univ Med Sci 2015, 1(1): 9-19 |
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Ranjbaran M, Soori H, Etemad K, Khodadost M. Relationship between Socioeconomic Status and Health Status and Application of Principal Component Analysis. J Jiroft Univ Med Sci 2015; 1 (1) :9-19
URL: http://journal.jmu.ac.ir/article-1-22-en.html
URL: http://journal.jmu.ac.ir/article-1-22-en.html
1- Department of Epidemiology, Faculty of Health
2- Safety Promotion and Injury Prevention Research Center , hsoori@yahoo.com
2- Safety Promotion and Injury Prevention Research Center , hsoori@yahoo.com
Abstract: (6433 Views)
Introduction: Nowadays, socioeconomic status (SES) is an important predictor of morbidity and mortality and also is very important for disease prevention and intervention efforts in health policy activities. In this article, while reviewing the history, different levels and techniques of measuring socioeconomic status, the application of "Principal component analysis" in studies of the relationship between socioeconomic status and health status was investigated.
Methods: To search for articles in this review study, the databases PubMed, Science Direct, Google scholar and inside the country databases used. Search by key words: Principal component analysis, Socioeconomic status, Health status was conducted. Finally, the 36 references between the years of 2000 and 2014 and four relevant and valid references before 2000 which were more consistent with the subject and objectives of the study selected for report and presented in form of a review article.
Results: Review of existing evidence indicates that SES is a very complex and multidimensional issue and there is no gold standard method for its measuring and because some of this measurement such as income, occupation, consumption or expenditure is not simply possible or reliable, therefore researchers use other proxies as alternate representative. To accumulate a large number of variables in one or more proxies, different methods can be used. The most common of them is principal component analysis (PCA) that is a multivariate statistical technique for reducing the number of variables in a data set without losing too much information.
Conclusion: Socioeconomic status is associated with a broad range of health outcomes and Principal component analysis is a good way for weighting the SES variables in studies of SES and Health.
Methods: To search for articles in this review study, the databases PubMed, Science Direct, Google scholar and inside the country databases used. Search by key words: Principal component analysis, Socioeconomic status, Health status was conducted. Finally, the 36 references between the years of 2000 and 2014 and four relevant and valid references before 2000 which were more consistent with the subject and objectives of the study selected for report and presented in form of a review article.
Results: Review of existing evidence indicates that SES is a very complex and multidimensional issue and there is no gold standard method for its measuring and because some of this measurement such as income, occupation, consumption or expenditure is not simply possible or reliable, therefore researchers use other proxies as alternate representative. To accumulate a large number of variables in one or more proxies, different methods can be used. The most common of them is principal component analysis (PCA) that is a multivariate statistical technique for reducing the number of variables in a data set without losing too much information.
Conclusion: Socioeconomic status is associated with a broad range of health outcomes and Principal component analysis is a good way for weighting the SES variables in studies of SES and Health.
Type of Study: Review |
Subject:
Health Sciences / Epidemiology
Received: 2014/07/26 | Accepted: 2014/07/26 | Published: 2014/07/26
Received: 2014/07/26 | Accepted: 2014/07/26 | Published: 2014/07/26
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