Mini Nutritional Assessment and short-form Mini Nutritional Assessment can predict the future risk of falling in older adults - results of a national cohort study.
OBJECTIVE
Falling is a major issue in geriatric health. Tools that identify individuals at risk of falling can help reduce the risk of falling. The study aimed to determine whether the full and short-form Mini Nutritional Assessment (MNAs) have the ability to predict the risk of falling in older adults.


METHODS
Subjects were 3118 ≥ 53-year old Taiwanese who completed both the 1999 and 2003 "Taiwan Longitudinal Study on Aging" surveys. We rated these subjects with normalized versions of the MNA and applied the standard cut-offs to define under-nutrition (≤23.5 and ≤11 points, respectively). We used multivariate logistic regression analysis and receiver operating characteristics to evaluate the ability of these tools in predicting the risk of falling three years later.


RESULTS
Older adults rated as at risk of malnutrition with the full MNA (OR = 1.87, 95% confidence interval = 1.33-2.63, p < 0.001) or the short-form (1.39, 1.07-1.80, p = 0.014) were associated with increased risk of falling three years later. Both versions significantly predicted the risk of falling and performed slightly better in ≥65-year old persons than in younger (53-64-year old) persons. The short-form performed relatively well compared to the full scale.


CONCLUSIONS
Results suggest that the full and short-form MNAs, in addition to rating the risk of malnutrition, also predict the risk of falling in older adults. Although the short-form is slightly less effective than the full scale in predicting the future risk of falling, its simplicity, effectiveness and efficiency make it ideal as a multipurpose screening tool in clinical settings.
Department of Healthcare Administration, Asia University, 500 Liufeng Road, Wufeng, Taichung 41354, Taiwan, ROC; Department of Health Services Management, School of Public Health, China Medical University, Taichung 40402, Taiwan, ROC. Electronic address: atsai@umich.edu.
Alan C
AC
Tsai
Department of Healthcare Administration, Asia University, 500 Liufeng Road, Wufeng, Taichung 41354, Taiwan, ROC; Nursing Department, Taichung Veterans General Hospital, Taichung, Taiwan, ROC. Electronic address: bs88877@yahoo.com.tw.
Mei-Yen
MY
Lai
D000058:Accidental Falls; D000368:Aged; D000375:Aging; D044466:Asian People; D015992:Body Mass Index; D015331:Cohort Studies; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D044342:Malnutrition / Q000453:epidemiology*; D008875:Middle Aged; D009043:Motor Activity; D015999:Multivariate Analysis; D015596:Nutrition Assessment; D009752:Nutritional Status; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013624:Taiwan / Q000453:epidemiology
Elderly; Falling; Malnutrition; Mini Nutritional Assessment; Predicting falls