Psycho-Social Predictors of Eating Disorders Among Female Students of Higher Institutions in Makurdi Metropolis Benue State-Nigeria

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@article{1711987,
      author = {Ungwa Emmanuel Vandekan PhD, Terhemba Ephraim Tuluma, Fate Jirgba Justin},
      title = {Psycho-Social Predictors of Eating Disorders Among Female Students of Higher Institutions in Makurdi Metropolis Benue State-Nigeria},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {932-937},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1711987.pdf},
      abstract = {This study investigated on the psycho-social predictors of eating disorder among female students of higher Institutions in Makurdi metropolis. The study employed ex-post factor cross sectional survey method where 382 students consisting of 257167.3%) students from Benue State University Makurdi and 125(32.7%) students from University of Agriculture Makurdi were randomly drawn through purposive sampling method: Rosenberg self-esteem scale (Rosenberg, 1965) and Eating attitude test (EAT-26) (Garner, Olmstead, Bohr and Garfinkel, 1982) were used for data collection. Findings showed that self-esteem (?=-.42, p<.001), age (?=-.01, p>.05), socio-economic status (?=-.5, p>.05), ethnicity (?=-.17, p<.001) and place of residence (?=-.03. p>.05) significantly predicted eating disorder, whereas independently, only self-esteem and ethnicity significantly predicted eating disorder among female undergraduate students. Finally, no significant difference was found between Benue State University students and University of Agriculture Makurdi t (380 df) =1.64, p>.0.5. It was therefore recommended that mental health studies be included in Primary and post primary school curriculum to create awareness on eating disorders and other variables that affect normal functioning in daily life. It was also recommended that further researches be conducted on eating disorders using larger population to enhance generalization of research findings.},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1711987}
  }