A Systematic Review and Meta‑Analysis of the Prevalence of Malnutrition Among 6‑14‑Year‑Old Children in Iran

Malnutrition is a major public health issue worldwide. It has significant consequences, including weakened immune systems, which may lead to increased incidences of infectious disease and higher mortality, particularly in children. A systematic review and meta‑analysis were conducted to estimate the overall prevalence of malnutrition (wasting, underweight, and stunting) among children of 6–14 years of age in Iran.

Data were collected in 2018 based on searches of the PubMed, Science Direct, Scopus, Google Scholar, Science Information Database (SID), Magiran, Irandoc, and Iranmedex databases using the following keywords: childhood, childhood malnutrition, children, nutrition, malnutrition, wasting, underweight, stunting, child, student, boy, girl, cause, prevalence, and Iran, in order to identify studies eligible for inclusion in the review. Comprehensive Meta‑Analysis, version 2 (CMA: 2) was used to estimate the overall prevalence of malnutrition.

Nine out of 328 articles were included in our analyses. The overall of wasting among children of 6–14 years of age in Iran based on the random‑effects model (according to nine studies and 18,296 participants) was 12.5% (95% Confidence Interval, 7.1‑21.2). The overall prevalence of underweight based on the random‑effects model (according to 10 studies and 19,185 participants) was 19% (95% CI, 8.1‑38.6). Also, the overall prevalence of stunting based on the random‑effects model (according to 10 studies and 19,185 participants) was 20% (95% CI, 9.4‑37.8).

The results of this study show that the prevalence of malnutrition among 6–14‑year‑old children in Iran is similar to the global average. We need solutions that can be used for both prevention and reduction of malnutrition, especially in areas with middle or low socioeconomic status. It is necessary to identify factors associated with malnutrition in various geographic regions in order to implement appropriate programs based on factors with the highest impact in each region.