Volume 24, Issue 165 (3-2018)                   RJMS 2018, 24(165): 93-103 | Back to browse issues page

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Hosseinzadeh Z, Bakhshi E, Jashni Motlagh A, Biglarian A. Application of quantile regression to identify of risk factors in infant’s growth parameters. RJMS. 2018; 24 (165) :93-103
URL: http://rjms.iums.ac.ir/article-1-5024-en.html
Associate Professor, Department of Biostatistics, Social Determinants of Health Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
Abstract:   (501 Views)
Background: Evolutional failure can happen in various dimensions of infant’s growth consisting in word, act and behaviour and lead to appear difficults as delay in speaking, brain paralysis, mental lag etc. The purpose of this study is determination and identification of risk factors in infant’s growth parameters using quantile regression analysis.
Methods: In this cross-sectional study, growth information of 224 infants including height, weight and head circumference, in Karaj health centers (in 2015-2016), were collected and analyzed. The data analysis was carried out using R 3.2.2 software.
Results: According to the results, maternal age had a significant effect on boy’s weight, family members had a significant effect on boy’s height and mother’s education had a significant effect on boy’s head circumference. In addition, mother’s BMI and maternal age had a significant effect on girl’s weight, mother’s education had a significant effect on girl’s height and maternal age and family members had a significant effect on girl’s head circumference in various quantiles.
Conclusion: Quantile regression, due to fit of various regression lines, was identified significant variables. The findings showed that maternal age and mother’s education were important factors affecting the infant’s growth parameters. Therefore, it is recommended that the authorities of the child and maternal health care be policed to improve it.
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Type of Study: Research | Subject: Biostatistics

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