An investigation of effective factors on children’s growth failure in Iran using multilevel models

A. Azarbar, Y. Zhang and S. Nadarajah ()
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A. Azarbar: AmirKabir University of Technology
Y. Zhang: University of Manchester
S. Nadarajah: University of Manchester

Quality & Quantity: International Journal of Methodology, 2019, vol. 53, issue 2, No 1, 553-560

Abstract: Abstract Delay or stop in children’s growth is referred to as failure to thrive (abbreviated as FTT) which leads to adverse effects such as increased mortality, reduced learning, cognitive, physical, and emotional disability, and other related illnesses. To date, different studies have been carried out in this field and factors affecting growth failure have been identified. Stopping breast feeding, teething, urinary and respiratory tract infection, fever, diarrhea, and malnutrition are identified as the most important factors affecting failure to thrive. Most of these studies apply common regression models; however, multilevel regression models involve the random effects model which allows taking genetic and individual factors into account. In the present study, given that the data were longitudinal, multilevel regression models were used for data analysis, the individual characteristics of children were identified as being among the factors affecting failure to thrive. Accordingly, it can be argued that, in identical conditions, children develop different levels of growth disorder.

Keywords: Growth failure; Longitudinal data; Regression model (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11135-018-0774-x

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