The increasing elderly population creates a multitude of challenges for nurses. Nutrition in the elderly population is a critical research area. The purpose of this descriptive correlational study was to ascertain the relationship between specified components of nutritional assessment (anthropometric measures and nutritional patterns) and nutritional risk factors in non-institutionalized elderly persons.

The study consisted of 81 subjects, 65 years of age or older, who were living in housing facilities within the Southeastern United States. The Nutrition Risk Index, a 16-item instrument, was used to determine whether an individual was considered at high or low risk for malnutrition. The Health Habits and History Questionnaire measured nutritional patterns through dietary intake from 60 line-item foods. Demographic variables and anthropometric measures were calculated using an instrument developed by the researcher.

Chi-square, t-tests, logistical regression, and multiple regression were calculated for data analysis. The sample of 66 females and 15 males ranged in age from 65 to 91 years. Analysis indicated that triceps skinfold thickness was found to be the highest discriminator for determining nutritional risk and that protein was the only nutrient which differed significantly between the high and low risk groups for malnutrition. The study also sought to determine which combination of anthropometric measures best predicts nutritional risk. Weight and elbow breadth were determined to be the best combination of predictors within this population; however, this was a low level of predictability. An improved, but still low level of predictability was found when combining anthropometric measures and nutritional patterns to predict nutritional risk.

Based upon the findings, it was concluded that anthropometric measures and nutritional patterns can be useful in determining nutritional risk among non-institutionalized elderly persons. Additional findings indicated non of the anthropometric measures and nutritional patterns are high predictors of nutritional risk for this population. Future research is needed to determine additional variables which may assist in determining nutritional risk for this age group.