Risk of Frailty Prediction Among Institutionalized Older Adults

Abstract

Background: Frailty is a state of the decreased physiological reserve, inability to maintain homeostasis manifested by weakness, weight loss, reduced gait speed, exhaustion, and increased vulnerability to adverse health outcomes. It is commonly associated with aging and is considered as a predictor of hospitalization, morbidity, and mortality, thereby increasing the economic burden on the nation. Early identification of people who are at risk for frailty is vital in prevention and minimizing its socio-economic consequences. Objective: To develop a prediction model for the risk of frailty among institutionalized older adults. Methods: This study adopted a case-control design, wherein older adults categorized into frail and non-frail, using Fried's criteria were considered as cases and controls respectively. Individuals above 55 years of age, who could follow instructions; without severe motor and cognitive impairment and severe terminal illness were recruited from nine conveniently selected institutions for older adults. Socio-demographic details like age, gender, BMI, marital status and duration of institutionalization; lifestyle and behavioral factors like comorbidities, history of fall, smoking, alcohol consumption status, economic dependability, depression and cognition and; physical performance factors like physical activity, functional mobility, gait speed, and grip strength were evaluated. Binary logistic regression was performed to identify the odds ratio between the independent variables and frailty and to develop a prediction model. Results: Hundred elderly were recruited and analyzed from nine different institutions. Among the fourteen identified independent variables female gender (OR=1.038), cognition (OR=1.477), smoking (OR=1.907), vegetarian diet (OR=0.016), presence of more than 3 co-morbidities (OR=8.840), gait speed (OR=0.000) and grip strength (OR=0.575) showed a statistically significant odds ratio (r 2 = 0.883) and were used for developing a prediction model for risk of frailty. Conclusion: Risk factors for frailty among institutionalized older adults have been identified and a prediction model for risk frailty has been developed. This model could be used for the early identification of frailty during community-level screening programs.