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Showing 1 results for Unvariate Logistic Regression Analysis

Ataollah Hashemian, Ashraf Direkvand-Moghadam, Ali Delpisheh, Azadeh Direkvand-Moghadam,
Volume 2, Issue 1 (3-2015)
Abstract

Introduction: Adolescents are the important portions of the Iranian population. Adolescents health status has a critical role in their learning ability and their performance. The present study aimed to determine the predictive factors for general health status in Iranian high school students in 2014. Materials and methods: In a cross-sectional study evaluated the predictive factors for general health status among 381 high school students in Ilam, west of Iran in 2014. The samples were selected by a multi-stage sampling method. Data was collected by a two-part questionnaire. The first part of the questionnaire was included the personal characteristics. Second part of the questionnaire was General Health Questionnaire- 28 (GHQ-28). SPSS software Package 16 was used to analyze the data. Results: Overall 236 (61.9%) students put into the health status and 145 (38.1%) of all have disorders in one or more dimensions of their general health status. The univariate logistic regression analysis shows that the gender, mother´s occupation, father education and school grade are the main predictive factors of general health status. With the multivariate logistic regression analysis school grade was considered as independent predictive variable for students’ health status (OR = 0.761, P= 0.016). Conclusion: There are several risk factors for students’ general health disorder. It seems that gender, mother´s occupation, father education and school grade are some suitable independent predictive factors for students’ general health disorder. It is concluded that high school students at risk of health disorder could be diagnosed using some predictive analysis models allowing timely interventions to be performed.

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مجله ی تحقیقات پایه در علوم پزشکی Journal of Basic Research in Medical Sciences
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