Prevalence and Predictors of Under Nutrition among Under-Five Children in Peshawar District, Khyber Pakhtunkhwa, Pakistan
DOI:
https://doi.org/10.52206/jsmc.2024.14.1.818Abstract
Background: Malnutrition is a pressing public health crisis in Pakistan that requires immediate attention. The prevalence of
malnutrition is on the rise due to various factors including social and economic factors.
Objectives: To find out the prevalence and causative factors of under nutrition in district Peshawar.
Material and Methods: A cross-sectional study was conducted between January 2022 and December 2022, in the Peshawar district of Khyber Pakhtunkhwa. A sample size of 400 children under the age of five years using a multistage stratified cluster sampling technique. A structured questionnaire was used to collect data, Anthropometric measures were taken to determine the
children's nutritional status. Data collected was analyzed using SPSS version 23 for Windows.
Results: The study found that 39.3% of children were suffering from stunting, 16% from wasting, and 22.3% from underweight. Under nutrition was significantly associated with factors such as urban/rural areas, parents' education, maternal factors, family income, gender, and weight at birth (p-value < 0.05). However, there was no statistically significant difference found between family type, maternal television watching, and under nutrition. The study also revealed that children aged =5 months were more likely to
be undernourished than older children.
Conclusion: Undernourishment is a critical issue in district Peshawar Khyber Pakhtunkhwa. The prevalence of undernourishment
is alarmingly high in rural areas as compared to urban areas.
Keywords: Anthropometric, Stunting, Under nutrition, Underweight, Wasting.
Additional Files
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 The authors retain the copyrights. Authors are permitted and encouraged to post their work online (e.g. in institutional repositories or on their website), as it can lead to productive exchanges, as well as greater citation of published work.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Readers may “Share-copy and redistribute the material in any medium or format” and “Adapt-remix, transform, and build upon the material”. The readers must give appropriate credit to the source of the material and indicate if changes were made to the material. Readers may not use the material for commercial purpose. The readers may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
