Application of Bayesian Hierarchical Model for Detecting Effective Factors on Growth Failure of Infants Less Than Two Years of Age in a Multicenter Longitudinal Study
نویسندگان
1 Department of Biostatistics and Epidemiology, Modeling of Noncommunicable Disease Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, IR Iran
2 Department of Biostatistics and Epidemiology, Modeling of Noncommunicable Disease Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, IR Iran
3 Department of Biostatistics, Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, IR Iran
4 Department of Biostatistics and Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, IR Iran
5 Department of Health and Social Medicine, Shahed University Faculty of Medicine, Tehran, IR Iran
6 Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, IR Iran
doi
چکیده
Nowadays, one of the major public health problems among children is growth failure. It can be characterized interms 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 infantsless than two years old.Materials and Methods: The present longitudinal archival study relied on data gathered from health files from February 2007 toJuly 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 incomparison to the previous measurement. The impacts of risk indicators were assessed using the Bayesian hierarchical logisticregression modeling technique.Results: The highest and lowest percentage of growth failure was 5.8% and 0.1%, respectively, in the eleventh and the first monthafter 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 riskfactors for growth failure. The random term at the child level was significant (95% CrI: 0.74 - 7.82), while the variation in centers wasextremely 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 theimpact 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.
