Factors Related to Functional Status of Those Over 70 Years of Age

Abstract

As the population of individuals aged 65 and older in the United States is projected to be approximately 65 million by the year 2050, it is increasingly important to understand functional status (FS). PURPOSE: To achieve this aim, we are conducting a longitudinal study assessing both physiological and psychological variables. METHODS: Second year data for all subjects includes, body mass index (BMI), socioeconomic status, nutritional status (MNA), number of diagnosed diseases, and number of prescription medications. Further, the Physical Activity Scale (PASE) for the Elderly and the Instrumental Activities of Daily Living (IADL) questionnaires were administered. The Center for Epidemiological Studies Depression Scale (CES-D) and Mini-Mental State Exam (MMSE) were administered to assess the psychological variables. The Fullerton Senior Fitness Tests (FSFT) were used to assess the following physiological parameters: 1. lower body strength; 2. upper body strength; 3. lower body flexibility 4. upper body flexibility; 5. aerobic capacity; and 6. motor agility/ dynamic balance. For the purposes of statistical analysis, FS was denned as the mean percentile ranking for the FSFT. Data are presented as means ± SEM. A Pearson Product Moment was calculated and analyzed to determine bivariate relationships. RESULTS: Data were collected from 46 subjects (30 females and 16 males), with a mean age of 79.80±0.74 years, a mean BMI of 26.08±0.80, income range of <$10,000 to >$50,000, mean MNA score of 27.51±0.22, mean number of diseases of 2.63±0.24, mean number of prescription medications of 2.98±0.29, mean PASE score of 102.05±7.33, mean IADL score of 7.96±0.04, mean CES-D score of 4.83±0.71, mean MMSE score of 27.89±0.30, and mean FS percentile ranking of 45.76±2.62. Of the variables examined only two variables reached statistical significance: 1. number of prescription medications and 2. number of diseases. The number of prescription medications explained 21% of the variance and the number of diseases explained 16% of the variance of FS. CONCLUSION: Of the variables examined, only two correlated with FS. The amount of the variance explained was minimal. With the second year data, the same two variables reached statistical significance as the first year. The number of prescription medications explained 18% of the variance with the first year data and 21% of the variance with second year data. The number of diseases explained 15% of the variance with the first year data and 16% of the variance with the second year data.