K Wei1, F S Thein, M S Z Nyunt, Q Gao, S L Wee, T P Ng. 1. A/P Tze-Pin Ng, Gerontology Research Programme, National University of Singapore, Department of Psychological Medicine, NUHS Tower Block, 9th Floor, 1E Kent Ridge Road, Singapore 119228 Fax: 65-67772191, Tel: 65-67723478, Email: pcmngtp@nus.edu.sg.
Abstract
BACKGROUND: Malnutrition is a major determinant of the physical frailty syndrome. Dynamic transitions in frailty states over time is well documented, but few studies have documented temporal changes in nutritional states and whether they influence frailty outcomes. DESIGN: Longitudinal cohort study. SETTING AND PARTICIPANTS: Community-dwelling older Singaporeans aged ≥55y with a 5-year follow-up (n=1162) in the Singapore Longitudinal Ageing Study 2 (SLAS-2). MEASUREMENTS: The Mini Nutritional Assessment Short-Form (MNA-SF) was used to determine nutritional status, and the Fried's criteria (shrinking, weakness, slowness, exhaustion and inactivity) was used to assess physical frailty phenotype at both baseline and follow-up. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were adjusted for multiple baseline co-variables. RESULTS: At baseline, being at risk of malnutrition/malnourished was associated with increased odds of prevalent pre-frailty (OR=2.76, 95% CI=1.86-4.10) and frailty (OR=4.10, 95% CI=1.41-11.9). Baseline robust individuals who were persistently at risk of malnutrition/malnourished showed an increased odds of conversion to being pre-frail/frail at follow-up (OR=3.45, 95% CI=1.00-11.9). Among baseline pre-frail/frail individuals, reversion to being robust were significantly less likely among those who were persistently at risk of malnutrition/malnourished (OR=0.26, 95% CI=0.10-0.67) and those whose baseline normal nutrition worsened at follow-up (OR=0.20, 95% CI=0.06-0.74). CONCLUSION: Changes in nutritional states are associated with frailty state transitions, and monitoring changes in nutritional status is recommended for the prevention and severity reduction of frailty among older people in the community.
BACKGROUND:Malnutrition is a major determinant of the physical frailty syndrome. Dynamic transitions in frailty states over time is well documented, but few studies have documented temporal changes in nutritional states and whether they influence frailty outcomes. DESIGN: Longitudinal cohort study. SETTING AND PARTICIPANTS: Community-dwelling older Singaporeans aged ≥55y with a 5-year follow-up (n=1162) in the Singapore Longitudinal Ageing Study 2 (SLAS-2). MEASUREMENTS: The Mini Nutritional Assessment Short-Form (MNA-SF) was used to determine nutritional status, and the Fried's criteria (shrinking, weakness, slowness, exhaustion and inactivity) was used to assess physical frailty phenotype at both baseline and follow-up. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were adjusted for multiple baseline co-variables. RESULTS: At baseline, being at risk of malnutrition/malnourished was associated with increased odds of prevalent pre-frailty (OR=2.76, 95% CI=1.86-4.10) and frailty (OR=4.10, 95% CI=1.41-11.9). Baseline robust individuals who were persistently at risk of malnutrition/malnourished showed an increased odds of conversion to being pre-frail/frail at follow-up (OR=3.45, 95% CI=1.00-11.9). Among baseline pre-frail/frail individuals, reversion to being robust were significantly less likely among those who were persistently at risk of malnutrition/malnourished (OR=0.26, 95% CI=0.10-0.67) and those whose baseline normal nutrition worsened at follow-up (OR=0.20, 95% CI=0.06-0.74). CONCLUSION: Changes in nutritional states are associated with frailty state transitions, and monitoring changes in nutritional status is recommended for the prevention and severity reduction of frailty among older people in the community.
Authors: M Bonnefoy; G Berrut; B Lesourd; M Ferry; T Gilbert; O Guérin; O Hanon; C Jeandel; E Paillaud; A Raynaud-Simon; G Ruault; Y Rolland Journal: J Nutr Health Aging Date: 2015-03 Impact factor: 4.075
Authors: Tze Pin Ng; Liang Feng; Ma Shwe Zin Nyunt; Lei Feng; Mathew Niti; Boon Yeow Tan; Gribson Chan; Sue Anne Khoo; Sue Mei Chan; Philip Yap; Keng Bee Yap Journal: Am J Med Date: 2015-07-06 Impact factor: 4.965
Authors: M J Kaiser; J M Bauer; C Ramsch; W Uter; Y Guigoz; T Cederholm; D R Thomas; P Anthony; K E Charlton; M Maggio; A C Tsai; D Grathwohl; B Vellas; C C Sieber Journal: J Nutr Health Aging Date: 2009-11 Impact factor: 4.075