Individual and community level factors associated with household level food insecurity of Ethiopia: multilevel mixed effects analysis of 2021 Performance Monitoring for Action Ethiopia (PMA-ET).

Abstract

Background: People who face restricted or uncertain physical and economic access to safe, sufficient, and nutritious food to suit their dietary needs or food choices for a productive, healthy, and active life are said to be in a state or situation of food insecurity. There is a dearth of evidence of individual and community-level factors associated with household-level food insecurity in Ethiopia. Thus, this study aimed to assess individual and community-level factors associated with household-level food insecurity to fill the aforementioned gap.

Methods: This study analyzed the 2021 Performance Monitoring for Action Ethiopia (PMA-ET) datasets. A total of 24,965 participants in the 2021 Performance Monitoring for Action Ethiopia (PMA-ET) datasets were included in the analysis. STATA version 17.0 was used to analyze the data. A multi-level mixed-effects logistic regression analysis was used to assess the individual and community-level factors associated with household-level food insecurity. An adjusted odds ratio with a 95% confidence interval was used to show the strength and direction of the association, and statistical significance was declared at a P value less than 0.05.

Results: The prevalence of household-level food insecurity in Ethiopia based on 2021 PMA-ET data was 40.9%. Households who have not been educated (AOR: 5.62 with 95% CI: 2.74, 11.5), having primary educational status (AOR: 2.58 with 95% CI: 1.35, 4.92), having secondary educational status (AOR: 2.20 with 95% CI: 1.17, 4.14), households having middle wealth status (AOR: 3.00 with 95% CI: 1.05, 8.50), households having poor wealth status (AOR: 5.18 with 95% CI: 2.00, 13.4), households doesn't owned any livestock (AOR: 1.68 with 95% CI: 1.09, 2.84), and complete household income loss since COVID-19 restrictions began (AOR: 3.63 with 95% CI: 1.76, 7.50) were statistically associated with household-level food insecurity.

Conclusion: The prevalence of household-level food insecurity in Ethiopia was high. Hence, governmental and non-governmental organizations should focus on increasing the literacy status of the community since having low literacy status, including being not educated, has been found to contribute to food insecurity. The link between households that have not owned any livestock and food insecurity is one of our findings, suggesting that there is a need to participate in nonagricultural enterprises, including livestock production. Furthermore, besides government support, households should better to develop an emergency response plan for food security during any emergency including pandemics by increasing their source of income to avert the impact of different socioeconomic derangements.