A Systematic Review and Meta-Analysis on Employment Status of Mothers and Acute Malnutrition among Under Five Children in Ethiopia
Received Date: May 28, 2021 / Accepted Date: Jun 11, 2021 / Published Date: Jun 18, 2021
Abstract
The objective of this meta-analysis was to determine the association between Employment status of mothers and acute malnutrition among under five children in Ethiopia.Using data from 11 studies in Ethiopia we performed a meta- analysis with a specific focus on acute malnutrition among under five children.
We applied a random effects analytic model and calculated a pooled odds ratio.Electronic databases were searched on reference manager software and quality assessment of the included studies was performed. using assessment of risk of bias tool. The funnel plot shows that there is no publication bias as Egger Regression p value is 0.882 and Begg and Mazumdar p-value is 0.815. The odds ratios for all studies revealed no statistically significant association of Acute Malnutrition among under five children with employed mothers compared to house wife mothers OR MH, Random, 95% CI, 0.93, (0.66, 1.32) Heterogeneity Tau²=0.26; Chi²=50.14, DF=10 (P<0.00001); I²=80% Test for overall effect: Z=0.39 (P=0.70) A total of 5301 under five children included in our systematic review and meta-analysis. The proportion of acute malnutrition among employed mothers is 26.1% (484) and among house wife mothers is 24% (825). Our findings suggest that employment status of mothers has not statistically significant association with acute malnutrition among under five children in Ethiopia.
Keywords: Acute malnutrition ; Employment ; Children ; Electronic databases
Citation: Tegegne KT, Tegegne ET, Tessema MK (2021) A Systematic Review and Meta-Analysis on Employment Status of Mothers and Acute Malnutrition among Under Five Children in Ethiopia. Neonat Pediatr Med 7:216. Doi: 10.4172/2572-4983.1000216
Copyright: © 2021 Tegegne KT, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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