The association between hypertension and frailty syndrome in older adults remains unclear. There is scarce information about the prevalence of hypertension among frail elderly patients or on its relationship with frailty. Up to one quarter of frail elderly patients present without comorbidity or disability, yet frailty is a leading cause of death. The knowledge and better control of frailty risk factors could influence prognosis. The present study evaluated: (1) the prevalence of hypertension in robust, prefrail, and frail elderly; and (2) factors that might be associated with frailty including hypertension. A cross-sectional study was conducted in 619 older adults at a universitybased outpatient center. Study protocol included sociodemographic data, measures of blood pressure and body mass index, frailty screening according to the internationally validated FRAIL (fatigue, resistance, ambulation, illnesses, and loss of weight) scale, number of comorbidities, drug use assessment, physical activity, cognitive status, and activities of daily living. Ordinal logistic regression was used to evaluate factors associated with frailty. Prevalence of hypertension and frailty was 67.3% and 14.8%, respectively, in the total sample. Hypertension was more prevalent in the prefrail (72.5%) and frail (83%) groups than among controls (51.7%). Hypertension, physical activity, number of prescribed drugs, and cognitive performance were significantly associated with frailty status. Hypertension presented an odds ratio of 1.77 towards frailty (95% confidence interval, 1.21-2.60; P = .002). Hypertension was more prevalent in frail elderly patients and was significantly associated with frailty. Intensive control of hypertension could influence the trajectory of frailty, and this hypothesis should be explored in future prospective clinical trials.

We presented normative data for the MoCA and the MoCA-MIS that will facilitate the use of the test in Brazil and, potentially, in other populations with substantial proportions of low-educated individuals. Moreover, we described a systematic approach for adjusting the effects of age and education using fractional polynomials and provided suggestions on how to account for the nonlinear relationship that is frequently encountered between demographic factors and measures of cognitive performance.