Defining Optimal Timed Up and Go Test Cut-Offs for Fall Risk in Older Adults in Institutional Care in Malaysia - Zohari, Zahira; Rahim, Azliza; Mat Din, Hazwan; Saibul, Nurfaizah; Jafri, Asiah; Rahim, Shafikah; Nasir, Faizah; Salleh, Sri Saliza; Wan Rosdi, Wan Rabiatul Adawiah; Mohammad Sallehuddin, Hakimah (Malaysian Journal of Medical Sciences, 2025)
Background: The Timed Up and Go (TUG) test effectively identifies risk of fall, especially in institutional care settings with limited resources. This is the first Malaysian study assessing the validity of the TUG test against the Downton Fall Risk Index (DFRI) and establishing an optimal TUG cut-off for institutional settings. Methods: This cross-sectional study included residents aged > 60 years who could ambulate independently with or without aid from Rumah Seri Kenangan Cheras. Demographic data, TUG test scores, and DFRI scores were collected for fall risk assessment. Receiver operating characteristic (ROC) analysis was used to assess the validity of TUG, with the area under the curve (AUC) measuring sensitivity and specificity, and the Youden Index identifying the optimal cut-off. Results: Of the 192 residents, 92 (47.9%) fulfilled the inclusion and exclusion criteria. The mean age was 72.24 years (standard deviation, SD = 8.42), and 33.7% were classified as having a high risk of falling (DFRI >= 3). The TUG test showed an AUC of 0.65 (95% Confidence Interval [CI]: 0.54–0.77, P = 0.018), indicating moderate validity. A cut-off of 12.5 s achieved high sensitivity (93.5%) and low specificity (34.4%). Conclusion: The TUG test cut-off point identified was 12.5 s, which is lower than the standard 13.5 s reported for community-dwelling older adults. This difference reflects the unique characteristics of institutionalised older adults, who often experience greater physical and cognitive impairments. Environmental factors and methodological variations may contribute to this discrepancy, emphasising the need to set specific cut-off points to assess risk of fall in this population accurately.