Background: The evidence indicates a high prevalence of malnutrition, such as stunting and overweight, among Iranian children. Yet, this prevalence may not be equally distributed across socioeconomic groups, so that non-targeted policies may be ineffective. This paper aimed to measure the socioeconomic patterning of children's stunting and overweight status, and the mediating role of nutrition patterns.
Methods: The data were derived from the 2017 Demography and Health Survey (DHS) and the Multiple Indicator Cluster Survey (MICS), which were conducted in Iran. A sample of 19,270 children under the age of five was selected through a two-stage random sampling process. Children aged between 2 and 5 years were selected for the study (n=11,147). The probability of stunting and overweight was modeled using logistic regressions. The parental education and occupation and living conditions (areas and assets of the household) were considered as explanatory variables. The Diet Diversity Score was then factored in as mediation factor. Analyses were adjusted for age and sex.
Results: The odds of stunting were more than 1.7 times greater among children whose father only completed primary school and more than twice higher among children whose mother was illiterate. Children of unemployed fathers had a 1.69-fold greater risk of stunting, while the risk was almost 1.5 higher in children living in smaller houses. Finally, a gradient was also observed related to poor living resources, with 2.01 times greater odds of stunting for children from families without assets. The results were less socially patterned for overweight, which was still significantly lower among children from low-educated fathers. Although a higher Diet Diversity Score (DDS) was associated with a decrease in stunting and an increase in overweight, these associations did not modify the link between socioeconomic status and stunting and overweight.
Discussion: Malnutrition, especially stunting, more severely affects children from Iranian households with a lower socioeconomic background. Parental education, unemployment of father, area and assets were the most accurate factors for disentangling these inequalities, suggesting policies targeting more vulnerable groups.