INTRODUCTION: The oldest old adults, aged 80 years and above, is the fastest growing age group in the world. In this section of the population, functional disability (FD) is more prevalent compared to other age groups.
OBJECTIVE: To characterize functional capacity and analyze potential associations in the oldest old from a Brazilian capital city, based on a decision model.
METHODS: Cross-sectional study of 100 non-institutionalized oldest old participants assisted at the Family Health Strategy of Recife, in the Brazilian northeastern state of Pernambuco, selected by probabilistic sample. Sociodemographic, economic, and clinical data were collected by means of home interviews, anthropometric measurements, and medical records. For bivariate analysis, Pearson’s chi-square test was used, establishing significance at p < 0.05. For the multivariate analysis, a decision tree was built from the Exhaustive CHAID algorithm.
RESULTS: The prevalence of FD in the sample corresponded to 67.0%. In the bivariate analysis, the following data contributed to this outcome: income (p = 0.032), social security status (p < 0.01), nutritional status (p = 0.010), neurological diseases (p < 0.01), neoplasms (p < 0.01), self-perceived health (p = 0.025) and social support network (p = 0.032), remaining in the multivariate analysis: income (p = 0.003), social support network (p = 0.032), and nutritional status (p = 0.040). The decision tree allowed the identification of the variables most strongly associated with the outcome, being able to adequately predict moderate dependence, with 72.1% assertiveness.
CONCLUSION: The decision model proved to be a timely tool in deducing the most relevant determinants of FD. Its use potentially contributes to increase the accuracy of the diagnosis and to identify populations at risk.
