Food Insecurity and Its Association With School Absenteeism Among Rural School Adolescents in Jimma Zone, Ethiopia

Asia Pac J Public Health. 2017 Mar;29(2):114-121. doi: 10.1177/1010539517691606. Epub 2017 Feb 15.

Abstract

Studies showed that poor health and nutrition among school adolescents are major barriers to educational access and achievements in low-income countries. This school-based study was aimed to assess the association of school absenteeism and food insecurity among rural school adolescents from grades 5 to 8 in Jimma zone, Ethiopia. Regression analyses were used to see the strength of association between dependent and independent variables using odds ratio and 95% confidence intervals. Multivariable logistic regression analysis was used to identify the predictor of school absenteeism. Validated tools are used to collect household food insecurity data. Results showed that school absenteeism is significantly high among adolescents from food insecure households when compared to adolescents from food secure households ( P <.001). School absenteeism was negatively associated with male sex (adjusted odds ratio [AOR] = -0.91, 95% CI -1.85 to -0.03), household food security (adjusted odds ratio = -1.85, 95% CI -3.11 to -0.59), being an elder sibling (AOR = -0.37, 95% CI, -0.62 to -0.12), and mother involvement in decision making (AOR = -0.68, 95% CI, -1.33 to -0.03) while male-headed household was positively associated (AOR = 2.46, 95% CI, 1.37 to 4.56). Generally, this study showed that household food insecurity has significant contribution to school absenteeism among rural adolescents. Therefore, efforts should be made to improve household income earning capacity to reduce the prevalence of school absenteeism among rural school adolescents.

Keywords: Jimma; absenteeism; adolescents; food insecurity; rural.

MeSH terms

  • Absenteeism*
  • Adolescent
  • Cross-Sectional Studies
  • Ethiopia
  • Female
  • Food Supply / statistics & numerical data*
  • Humans
  • Male
  • Rural Population / statistics & numerical data*
  • Schools*