ABSTRACT

The quality of health of older persons is strongly tied to their nutritional status. Therefore, thorough nutritional assessment is necessary for both successful diagnosis and development of appropriate and comprehensive treatment plans for under nutrition in this sub-population. The study was descriptive and cross-sectional in design. A two-stage sampling technique was used to select 305 respondents. A structured questionnaire was used to elicit information on the socio-economic status, food frequency consumption and anthropometric status. Mini Nutritional Assessment (MNA) form and, Malnutrition Universal Screening Tools (MUST) was used to categorize the respondents’ nutritional risk. Anthropometric measurements of (Calf circumference, waist-hip ratio, Mid-upper arm circumference and Body mass index) were determined and compared with their standard. Descriptive statistics such as frequencies and percentages were used to analyze the data. Binary Logistic Regression was used to determine the significant relationship between socio-economic and nutritional risk, and significance was judged at P<0.05. The study findings revealed that a good number (43%) of the older persons in the study area were between 60-64years. Most (59%) of the respondents’ family size were between 4-6. The source of income/allowance was majorly (49%) pension allowance. The highest range of monthly income or allowance of the older persons fell between N30,000 – N50,000 (51%).Majority (59%) of older persons ate twice daily. The older persons’ majorly skipped breakfasts which represent (59%). The study findings using MNA revealed that (89%) of the respondents were normal, (8%) were at risk while 3% were malnourished. MUST reveal that majority (93%) had low nutritional risk, (5%) had medium nutritional risk and (2%) had high nutritional risk. Most male (67%) had normal BMI, (22%) were overweight while few (8%) were obese. For the females, majority (86%) had normal BMI, (6%) were overweight while few (3%) were obese. More (59%) of the respondents has waist-hip ratio at safe level. The study further revealed that there is a significant (P<0.05) risk between education and nutritional risk (in low education, p=0.036; High education p=0.000). Income class was also found to significantly (High income, p= 0.001; low income p=0.000) influence the older person’s nutritional risk. Based on the findings of the study, it is recommended among others that the government and other stakeholders should be monitoring the health of elderly persons periodically to identify those at risk for prompt action to be taken and a social security system to cater for the income.