Background: Measuring household food insecurity in specific geographic areas provides vital information that enables appropriate and effective intervention measures to be taken. To that end, this study aimed to assess the prevalence of food insecurity and associated factors among Urban Productive Safety Net Program (UPSNP) beneficiary households in Addis Ababa, Ethiopia's capital city.
Methods: A community-based cross-sectional study was conducted among 624 UPSNP beneficiary households in nine districts of Addis Ababa from June to July 2019. A multi-stage sampling method was used; study participants were selected using a simple random sampling technique after establishing the proportionally allocated sample size for 9 districts. Data were collected by trained personnel using a pretested, structured questionnaire. The outcome variable was food insecurity as measured by Household Food Insecurity Access Scale (HFIAS), a tool developed by the Food and Nutrition Technical Assistance Scale (FANTA) and validated for developing countries, including Ethiopia. A binary (crude odds ratio [COR]) and multivariable (adjusted odds ratio [AOR]) logistic regression analysis were employed at 95% CI (confidence interval). From the bivariate analysis, factors having a p-value<0.25 were included in the multivariable analysis. From the multivariable analysis, any variable at p-value < 0.05 at 95% CI was declared significantly associated with household food insecurity. Model fitness was also checked using the Hosmer-Lemeshow test with p-value>0.05.
Results: The prevalence of household food insecurity was 77.1% [95%CI:73.8-80.7] during the month prior to the survey. Illiteracy of household head [AOR: 2.56; 95%CI:1.08-6.07], family size of 4 or more [AOR: 1.87, 95%CI:1.08-3.23], high dependency ratio [AOR: 3.95; 95%CI:1.31-11.90], household lack of access to credit [AOR:2.85; 95%CI:1.25-6.49], low household income [AOR: 4.72; 95%CI:2.32-9.60] and medium household income [AOR: 9.78; 95%CI:4.29-22.35] were significantly associated with household food insecurity.
Conclusion: We found that three in four of Addis Ababa's UPSNP beneficiary households were food-insecure. Implementation of measures to improve household income, minimize the dependency ratio of households, and arrange access to credit services are paramount ways to tackle food insecurity problems in Addis Ababa.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476016 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0256634 | PLOS |
Heliyon
January 2025
Institute of Statistical Research and Training, University of Dhaka, Bangladesh.
This paper examines the current state of food insecurity in Bangladesh and its socio-economic drivers using data from the latest Household Income and Expenditure Survey (HIES 2022). Unlike previous studies that relied on less precise measures of food insecurity, such as food expenditure, diversity, and calorie intake, this study employs the internationally recognized Food Insecurity Experience Scale (FIES) and Rasch model-based thresholds to classify households as food secure or insecure. Multilevel logistic regression is used to identify significant predictors of moderate and severe food insecurity, considering the hierarchical structure of the data, with households nested within geographical clusters.
View Article and Find Full Text PDFCurr Dev Nutr
January 2025
UNICEF Nigeria, Abuja, Nigeria.
Background: Nigerian pregnant and lactating women continue to experience high rates of malnutrition and Nigerian women experience long-term discrimination in the allocation and control of productive resources. Nigeria has policies and a governance architecture in place to advance nutrition, but these commitments lack recognition of how gender equity and nutrition are interwoven.
Objective: To address this gap, this study sought to identify and analyze the influence of gender dynamics and gender norms on nutrition and health-related practices in Nigeria.
Sci Rep
January 2025
Division of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, 622 West 168th Street, Ste. 876, New York, NY, 10032, USA.
The COVID-19 pandemic may have exacerbated mental health conditions by introducing and/or modifying stressors, particularly in university populations. We examined longitudinal patterns, time-varying predictors, and contemporaneous correlates of moderate-severe psychological distress (MS-PD) among college students. During 2020-2021, participants completed self-administered questionnaires quarterly (T1 = 562, T2 = 334, T3 = 221, and T4 = 169).
View Article and Find Full Text PDFAnimal
December 2024
Venn Research Association for the Promotion of Virtual Fencing in Tyrol and the Alpine region. Brixnerstraße 1, 6020 Innsbruck, Austria.
Virtual fencing (VF) is a modern fencing technology using Global Positioning System-enabled collars which emit acoustic signals and, if the animal does not respond, electric pulses. Studies with cattle indicate successful learning and no distinct negative impact on the animals' behaviours and stress level. However, the number of studies testing VF with goats is relatively small.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!