![](/images/graphics-bg.png)
Application of bayesian hierarchical model for detecting effective factors on growth failure of infants less than two years of age a multi-center longitudinal study
Joint Authors
Amini, Maedeh
Moghimbeigi, Abbas
Soltanian, Ali Reza
Kholdi, Nahid
Fesharaki, Muhammad Gholami
Zayeri, Farid
Source
Iranian Red Crescent Medical Journal
Issue
Vol. 18, Issue 5 (31 May. 2016), pp.1-8, 8 p.
Publisher
Publication Date
2016-05-31
Country of Publication
United Arab Emirates
No. of Pages
8
Main Subjects
Abstract EN
Background: Nowadays, one of the major public health problems among children is growth failure.
It can be characterized in terms of either inadequate growth or the inability to maintain growth.
Objectives: The main objective of this study was to examine the effects of some factors on growth failure among a sample of infants less than two years old.
Materials and Methods: The present longitudinal archival study relied on data gathered from health files from February 2007 to July 2010 for 1,358 children under two years of age, selected from eight health centers in the east and northeast parts of Tehran, Iran.
In the present study, growth failure refers to at least a 50 g decrease in an infant’s weight as recorded at each attendance in comparison to the previous measurement.
The impacts of risk indicators were assessed using the Bayesian hierarchical logistic regression modeling technique.
Results: The highest and lowest percentage of growth failure was 5.8% and 0.1%, respectively, in the eleventh and the first month after birth.
The obtained results from the Bayesian hierarchical modeling revealed that diarrhea (95% credible interval (CrI): 0.70 - 3.31), discontinuation of breastfeeding (95% CrI: 0.77 - 5.96), and respiratory infections (95% CrI: 2.07 - 4.61) were significant risk factors for growth failure.
The random term at the child level was significant (95% CrI: 0.74 - 7.82), while the variation in centers was extremely small (95% CrI: 0.004 - 4.22).
Conclusions: It was noted that a relatively high prevalence of growth failure was observed in the study sample.
For minimizing the impact of significant risk factorsongrowthfailure, the early detection of growthfailureandits risk indicators is of great importance.
In addition, when the focus of the analysis is on the different nested sources of variability and the data has a hierarchical structure, using a hierarchical modeling approach is recommended to achieve more accurate results.
American Psychological Association (APA)
Zayeri, Farid& Amini, Maedeh& Moghimbeigi, Abbas& Soltanian, Ali Reza& Kholdi, Nahid& Fesharaki, Muhammad Gholami. 2016. Application of bayesian hierarchical model for detecting effective factors on growth failure of infants less than two years of age a multi-center longitudinal study. Iranian Red Crescent Medical Journal،Vol. 18, no. 5, pp.1-8.
https://search.emarefa.net/detail/BIM-694814
Modern Language Association (MLA)
Moghimbeigi, Abbas…[et al.]. Application of bayesian hierarchical model for detecting effective factors on growth failure of infants less than two years of age a multi-center longitudinal study. Iranian Red Crescent Medical Journal Vol. 18, no. 5 (May. 2016), pp.1-8.
https://search.emarefa.net/detail/BIM-694814
American Medical Association (AMA)
Zayeri, Farid& Amini, Maedeh& Moghimbeigi, Abbas& Soltanian, Ali Reza& Kholdi, Nahid& Fesharaki, Muhammad Gholami. Application of bayesian hierarchical model for detecting effective factors on growth failure of infants less than two years of age a multi-center longitudinal study. Iranian Red Crescent Medical Journal. 2016. Vol. 18, no. 5, pp.1-8.
https://search.emarefa.net/detail/BIM-694814
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 7-8
Record ID
BIM-694814