Lay Summary Older adults who are prefrail (an intermediate, potentially reversible stage between robustness and frailty) with early symptoms of cognitive impairment are a segment of the population that have hitherto remained "silent" and are currently not targets for screening and intervention. These individuals require early identification for preventive interventions to reduce disability, dependency and improve quality of life. To date, there is still no accepted definition of individuals upstream in the spectrum of physical frailty and cognitive impairment. Determining the prevalence and predictive ability of various definitions of co-existent frailty and cognitive impairment could identify older adults at greatest risk of adverse health outcomes. Therefore, the researchers aim to examine and compare (1) the prevalence of cognitive-prefrailty, prefrailty (IANA/IAGG consensus definition) and MCR syndromes, (2) the incidence and predictive ability of these three syndromes for adverse health outcomes including cognitive impairment and decline, dementia, physical functional impairment and decline, falls, hospitalization and mortality in older Quebec community dwellers.
Scientific Summary Background Cognitive frailty is the simultaneous presence of both physical frailty and cognitive impairment, excluding concurrent dementia. This condition confers a greater risk of incident cognitive impairment and decline, dementia, falls and disabilities compared to either condition alone. Current definitions of co-existent frailty and cognitive impairment exist, including the International Academy on Nutrition and Aging (IANA) and the International Association of Gerontology and Geriatrics (IAGG) consensus for cognitive frailty. There is also an analogous construct known as the motoric cognitive risk syndrome (MCR) associating slow gait speed and subjective cognitive impairment (SCI). Current operational criteria identify individuals later in the trajectory of frailty and cognitive decline, which may be too late for effective interventions. The researchers propose to define a new and early condition in the spectrum of Cognitive frailty known as "cognitive-prefrailty", which is a combination of prefrailty stage and SCI. Overall objective This study aims to determine and compare (1) the prevalence of cognitive-prefrailty, cognitive frailty (IANA/IAGG consensus definition) and MCR syndromes, (2) the incidence and predictive ability of these three syndromes for adverse health outcomes including cognitive impairment and decline, dementia, physical functional impairment and decline, falls, hospitalization and mortality in older community dwellers. Methods This study will use the database of the "Nutrition as a determinant of successful aging: The Quebec longitudinal study" (NuAge) study, which is a population-based observational cohort hat recruited healthy community-dwellers with age ranged from 67 to 84 years (51.8% women) between November 2003 and June 2005, and followed them during 4 years. Cognitive-prefrailty, prefrailty and MCR will be defined using information collected at the baseline assessment. Incident adverse health outcomes including cognitive impairment and decline, dementia, physical functional impairment and decline, falls, hospitalization and mortality have been recorded during the 4-years follow-up period. Anticipated results Prefrailty (an intermediate and potentially reversible stage between robust and frailty) and SCI occur upstream in the continuum of frailty and cognitive decline and hence constitute more suitable targets for screening and early intervention in older adults.
Study Type
OBSERVATIONAL
Enrollment
1,741
The NuAge study has been designed to investigate nutrition as a determinant of successful aging in older men and women in Quebec. This study is based on a population-based observational cohort design that initially recruited healthy community-dwellers with age ranged from 67 to 82 years (51.8% women) between January 2004 and April 2005. All participants lived in the areas of Montreal, Laval, and Sherbrooke in the Province of Quebec, Canada. After recruitment, they have been followed for 3 years with one clinical follow-up assessment each year (i.e.; 4 data collection time). A previous analysis performed on the NuAge study database has shown a significant decline of physical and cognitive performances with time (respectively an average of 10% and 2%), participants with lower physical performance showing lower cognitive performance.
Jewish General Hospital
Montreal, Quebec, Canada
Cognitive impairment
Cognitive status has been measured using the Modified Mini-Mental State (3MS)17 in the NuAge study. The 3MS test has a score range of 1-100. Baseline value and change over the three years of follow-up will be used. Cognitive impairment will be considered when 3MS score \< 79.
Time frame: 1 day
Cognitive decline
From T2 to T4 annual variation of 3MS score expressed in percentage between T1-T2, T2-T3 and T3-T4 will be calculated using the formula: ((3MS Tn+1 - 3MS Tn+1) / ((3MS Tn+1 + 3MS Tn+1) / 2)) x 100.
Time frame: 1 day
Incident dementia
From T2 to T4, incident dementia will be considered if 3MS score is ≤79/100 and simplified instrumental activity daily living score is \<4
Time frame: 1 day
Physical functional impairment
A sex-specific global measure of physical performance will be computed as the sum of scores in four tests: standing balance, walking speed (normal and fast), chair stands, and timed "Up \& Go" according to a slightly modified method proposed by Guralnik and colleagues.18 The validity of this global measure has been previously reported in this population.19 Four levels of physical performance will be created for each of the five tests. A score from 1 (slowest) to 4 (fastest) is assigned according to the quartile of time needed to carry out the test. With the exception of standing balance, the lowest quartile indicates the best (shorter duration) score. The reverse is true with respect to standing balance. A score of 0 was assigned to those who could not do or did not complete the test because they felt unable to do so. Possible scores range from 0 (worst) to 20 (best).
Time frame: 1 day
Physical functional Decline
From T2 to T4 annual variation of Physical functional score expressed in percentage between T1-T2, T2-T3 and T3-T4 were calculated using the formula: ((score Tn+1 - score Tn+1) / ((score Tn+1 + score Tn+1) / 2)) x 100
Time frame: 1 day
Falls
number of falls
Time frame: 1 day
Hospitalizations
Number of hospitalization
Time frame: 1 day
Mortality
Time frame: 1 day
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