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Research Article Open access CC BY 3.0

Demographic Characteristics and Dietary Pattern of the Elderly in Ondo State, Nigeria

I. O. Olayiwola, C. A. Olarewaju, D. A. Adelekan, M. Arigbede

Journal of Advances in Medicine and Medical Research · pp. 2173–2188 · Published 18 Jul 2013

10.9734/BJMMR/2013/4111

Abstract

Objective: To investigate the demographic characteristics and dietary patterns of elderly adults (>60 years) in Ondo State, Nigeria. Methodology: This was a random sampling of 400 elderly individuals (>60 years) living in Ondo State, Nigeria. Data on demographic and non-demographic variable characteristics, including food habits, dietary patterns and food frequency, were collected using an open-ended and structured questionnaire. Most individuals aged 60–69 years were married, with fewer than 25% having primary education and the majority of the remainder having no formal education. Most were employed in farming and their income was low (<200 USD per month). About 80% ate three meals daily, 25% skipped meals, and 39% avoid certain foods and 87% had favorite food which relates significantly with gender (=7.2; p<0.05) marital status (=5.7; p<0.05) and health (rate of falling sick). Dietary pattern was significantly associated with body ailments (=51.9; p<0.05). Certain habits, such as alcohol ingestion, influenced the number of meals (=10; p<0.05). Memory loss was significantly associated with skipping meals (=7.2; p<0.05), whereas depression was significantly associated with the number of meals (=6.2; p<0.05). A logistic regression model found that educational level, occupation and gender were significant independent predictors of dietary pattern. Conclusion: Most elderly individuals in Ondo State, Nigeria, were of low socioeconomic level and illiterate, with dietary patterns influenced by age, education, occupation and gender. Age correlated inversely with bone mass, body mass index, body fat and body water.

Demography pattern Nigeria dietary elderly.

Cited by 1

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Bidemi Emmanuel, Ogechi Nzeagwu, Gideon Iheme · Human Nutrition & Metabolism · 2022

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