New evidence shows that older adults need more dietary protein than do younger adults to support good health, promote recovery from illness, and maintain functionality. Older people need to make up ...for age-related changes in protein metabolism, such as high splanchnic extraction and declining anabolic responses to ingested protein. They also need more protein to offset inflammatory and catabolic conditions associated with chronic and acute diseases that occur commonly with aging. With the goal of developing updated, evidence-based recommendations for optimal protein intake by older people, the European Union Geriatric Medicine Society (EUGMS), in cooperation with other scientific organizations, appointed an international study group to review dietary protein needs with aging (PROT-AGE Study Group). To help older people (>65 years) maintain and regain lean body mass and function, the PROT-AGE study group recommends average daily intake at least in the range of 1.0 to 1.2 g protein per kilogram of body weight per day. Both endurance- and resistance-type exercises are recommended at individualized levels that are safe and tolerated, and higher protein intake (ie, ≥1.2 g/kg body weight/d) is advised for those who are exercising and otherwise active. Most older adults who have acute or chronic diseases need even more dietary protein (ie, 1.2–1.5 g/kg body weight/d). Older people with severe kidney disease (ie, estimated GFR <30 mL/min/1.73m2), but who are not on dialysis, are an exception to this rule; these individuals may need to limit protein intake. Protein quality, timing of ingestion, and intake of other nutritional supplements may be relevant, but evidence is not yet sufficient to support specific recommendations. Older people are vulnerable to losses in physical function capacity, and such losses predict loss of independence, falls, and even mortality. Thus, future studies aimed at pinpointing optimal protein intake in specific populations of older people need to include measures of physical function.
OBJECTIVE
To determine the correlates of the “metabolically healthy obese” (MHO) phenotype and the longitudinal risks of diabetes and cardiovascular disease (CVD)/stroke associated with this ...phenotype.
RESEARCH DESIGN AND METHODS
The North West Adelaide Health Study is a prospective cohort study of 4,056 randomly selected adults aged ≥18 years. Participants free of CVD/stroke and not underweight (n = 3,743) were stratified by BMI categories and metabolic risk, defined as having two or more International Diabetes Federation metabolic syndrome criteria, excluding waist circumference.
RESULTS
Correlates of the MHO (n = 454 12.1%) included smoking, socioeconomic disadvantage, and physical inactivity. Compared with metabolically healthy normal-weight subjects (n = 1,172 31.3%), the MHO were more likely to develop metabolic risk (15.5 vs. 33.1%, P < 0.001) and incident diabetes (odds ratio 2.09 95% CI 0.87–5.03) but not CVD/stroke (1.16 0.58–2.29) during 5.5–10.3 years of follow-up. These risks were not seen in MHO subjects maintaining metabolic health (n = 188 67%). Sustained metabolic health in obese participants was associated with age ≤40 years and lower waist circumference. Compared with the metabolically at-risk obese, MHO women demonstrated a significantly higher (mean SE) percentage of leg fat (49.9 0.5 vs. 53.2 0.7) and lower waist circumference (104 0.6 vs. 101 cm 0.8), despite no significant differences in overall adiposity.
CONCLUSIONS
“Healthy” obesity was a transient state for one-third of subjects. Persistence of a MHO phenotype, which was associated with favorable outcomes, was related to younger age and a more peripheral fat distribution. The MHO phenotype may be sustained by promoting lower waist circumferences.
Frailty is a biological syndrome that is associated with increased risks of morbidity and mortality. To assess the value of interventions to prevent or manage frailty, all important impacts on costs ...and outcomes should be estimated. The aim of this study is to describe the development and validation of an individual-based state transition model that predicts the incidence and progression of frailty and frailty-related events over the remaining lifetime of older Australians. An individual-based state transition simulation model comprising integrated sub models that represent the occurrence of seven events (mortality, hip fracture, falls, admission to hospital, delirium, physical disability, and transitioning to residential care) was developed. The initial parameterisation used data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). The model was then calibrated for an Australian population using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey. The simulation model established internal validity with respect to predicting outcomes at 24 months for the SHARE population. Calibration was required to predict longer terms outcomes at 48 months in the SHARE and HILDA data. Using probabilistic calibration methods, over 1,000 sampled sets of input parameter met the convergence criteria across six external calibration targets. The developed model provides a tool for predicting frailty and frailty-related events in a representative community dwelling Australian population aged over 65 years and provides the basis for economic evaluation of frailty-focussed interventions. Calibration to outcomes observed over an extended time horizon would improve model validity.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
4.
Falls in the Aging Population Khow, Kareeann S F; Visvanathan, Renuka
Clinics in geriatric medicine,
08/2017, Volume:
33, Issue:
3
Journal Article
Peer reviewed
The number of people living beyond 65 years of age is increasing rapidly, and they are at increased risk of falls. Falls-related injuries and hospitalizations are steadily increasing. Falls can lead ...to fear of falling, loss of independence, institutionalization, and death, inevitably posing a significant burden to the health care system. Therefore, screening of people at risk of falls and comprehensive assessment of older people at high risk of falls are critical steps toward prevention. This review evaluates the current knowledge relating to falls, with particular focus on rapid screening, assessment, and strategies to prevent falls in the community.
Anorexia of Aging Visvanathan, Renuka
Clinics in geriatric medicine,
08/2015, Volume:
31, Issue:
3
Journal Article
Peer reviewed
The anorexia of aging is common, leading to adverse health consequences. As populations age, the impacts from anorexia in the older population are set to increase. Only greater awareness will allow ...for prevention or early intervention. This article discusses the physiologic anorexia of aging, highlights contributing factors, and proposes management strategies, including screening, especially in primary care. Many neuroendocrine factors have been implicated in the pathophysiology; it is clear that further human research is necessary if there is to be a pharmacologic breakthrough. There are currently no approved pharmacologic treatment strategies to prevent or treat the anorexia of aging.
Abstract
Background
Rapid frailty screening remains problematic in primary care. The diagnostic test accuracy (DTA) of several screening instruments has not been sufficiently established. We ...evaluated the DTA of several screening instruments against two reference standards: Fried’s Frailty Phenotype FP and the Adelaide Frailty Index AFI), a self-reported questionnaire.
Methods
DTA study within three general practices in South Australia. We randomly recruited 243 general practice patients aged 75+ years. Eligible participants were 75+ years, proficient in English and community-dwelling. We excluded those who were receiving palliative care, hospitalized or living in a residential care facility.
We calculated sensitivity, specificity, predictive values, likelihood ratios, Youden Index and area under the curve (AUC) for: Edmonton Frail Scale EFS, FRAIL Scale Questionnaire FQ, Gait Speed Test GST, Groningen Frailty Indicator GFI, Kihon Checklist KC, Polypharmacy POLY, PRISMA-7 P7, Reported Edmonton Frail Scale REFS, Self-Rated Health SRH and Timed Up and Go TUG) against FP 3+ criteria and AFI >0.21.
Results
We obtained valid data for 228 participants, with missing scores for index tests multiply imputed. Frailty prevalence was 17.5% frail, 56.6% prefrail FP, and 48.7% frail, 29.0% prefrail AFI. Of the index tests KC (Se: 85.0% 70.2–94.3; Sp: 73.4% 66.5–79.6) and REFS (Se: 87.5% 73.2–95.8; Sp: 75.5% 68.8–81.5), both against FP, showed sufficient diagnostic accuracy according to our prespecified criteria.
Conclusions
Two screening instruments—the KC and REFS, show the most promise for wider implementation within general practice, enabling a personalized approach to care for older people with frailty.
Frailty in nursing homes: the FRAIL-NH Scale Kaehr, Ellen; Visvanathan, Renuka; Malmstrom, Theodore K ...
Journal of the American Medical Directors Association,
02/2015, Volume:
16, Issue:
2
Journal Article
OBJECTIVES
Frailty places individuals at greater risk of adverse health outcomes. However, it is a dynamic condition and may not always lead to decline. Our objective was to determine the ...relationship between frailty status (at baseline and follow‐up) and mortality using both the frailty phenotype (FP) and frailty index (FI).
DESIGN
Population‐based cohort.
SETTING
Community‐dwelling older adults.
PARTICIPANTS
A total of 909 individuals aged 65 years or older (55% female), mean age 74.4 (SD 6.2) years, had frailty measurement at baseline. Overall, 549 participants had frailty measurement at two time points.
MEASUREMENTS
Frailty was measured using the FP and FI, with a mean 4.5 years between baseline and follow‐up. Mortality was matched to official death records with a minimum of 10 years of follow‐up.
RESULTS
For both measures, baseline frailty was a significant predictor of mortality up to 10 years, with initially good predictive ability (area under the curve AUC = .8‐.9) decreasing over time. Repeated measurement at follow‐up resulted in good prediction compared with lower (AUC = .6‐.7) discrimination of equivalent baseline frailty status. In a multivariable model, frailty measurement at follow‐up was a stronger predictor of mortality compared with baseline. Frailty change for the Continuous FI was a significant predictor of decreased or increased mortality risk based on corresponding improvement or worsening of score (hazard ratio = 1.04; 95% confidence interval = 1.02‐1.07; P = .001).
CONCLUSIONS
Frailty measurement is a good predictor of mortality up to 10 years; however, recency of frailty measurement is important for improved prediction. A regular review of frailty status is required in older adults. J Am Geriatr Soc 67:2311–2317, 2019
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Objectives
To compare the FRAIL‐NH scale with the Frailty Index in assessing frailty in residential aged care facilities.
Design
Cross‐sectional.
Setting
Six Australian residential aged care ...facilities.
Participants
Individuals aged 65 and older (N = 383, mean aged 87.5 ± 6.2, 77.5% female).
Measurements
Frailty was assessed using the 66‐item Frailty Index and the FRAIL‐NH scale. Other measures examined were dementia diagnosis, level of care, resident satisfaction with care, nurse‐reported resident quality of life, neuropsychiatric symptoms, and professional caregiver burden.
Results
The FRAIL‐NH scale was significantly associated with the Frailty Index (correlation coefficient = 0.81, P < .001). Based on the Frailty Index, 60.8% of participants were categorized as frail and 24.4% as most frail. Based on the FRAIL‐NH, 37.5% of participants were classified as frail and 35.9% as most frail. Women were assessed as being frailer than men using both tools (P = .006 for FI; P = .03 for FRAIL‐NH). Frailty Index levels were higher in participants aged 95 and older (0.39 ± 0.13) than in those aged younger than 85 (0.33 ± 0.13; P = .008) and in participants born outside Australia (0.38 ± 0.13) than in those born in Australia (0.34 ± 0.13; P = .01). Both frailty tools were associated with most characteristics that would indicate higher care needs, with the Frailty Index having stronger associations with all of these measures.
Conclusion
The FRAIL‐NH scale is a simple and practical method to screen for frailty in residential aged care facilities.
Full text
Available for:
BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Aim
Frailty is a state of decreased physiological reserve and vulnerability to stressors. Understanding the characteristics of those most at risk of worsening, or likely to improve their frailty ...status, are key elements in addressing this condition. The present study measured frailty state transitions and factors associated with improvement or worsening frailty status in the North West Adelaide Health Study.
Methods
Frailty was measured using the frailty phenotype (FP) and a 34‐item frailty index (FI) for 696 community‐dwelling participants aged ≥65 years, with repeated measures at 4.5‐year follow up.
Results
Improvement in frailty state was common for both tools (FP 15.5%; FI 7.9%). The majority remained stable (FP 44.4%; FI 52.6%), and many transitioned to a worse level of frailty (FP 40.1%; FI 39.5%). For both measures, multimorbidity was associated with worsening frailty among non‐frail participants. Among pre‐frail participants, normal waist circumference was associated with improvement, whereas older age was associated with worsening of frailty status. Among frail individuals, younger age was associated with improvement, and male sex and older age were associated with worsening frailty status.
Conclusions
Frailty is a dynamic process where improvement is possible. Multimorbidity, obesity, age and sex were associated with frailty transitions for both tools. Geriatr Gerontol Int 2018; 18: 1549–1555.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
PDF
