Gerontology · 2023
Association of Physical Frailty and Cognitive Function in a Population-Based Cross-Sectional Study of American Older Adults.
СтатьяПоддержка исследования: вне правительства СШАПоддержка службы здравоохранения СШАНазвание и аннотация: Перевод пока не подготовлен
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Karanth Shama, Braithwaite Dejana, Katsumata Yuriko, Duara Ranjan, Norrod Paul, Aukhil Ikramuddin, Abner Erin
Аннотация
INTRODUCTION: Cognitive impairment and frailty are prevalent in older persons. Physical frailty is associated with cognitive decline; however, the role of effect modifiers such as age, sex, race/ethnicity, and cognitive reserve is not well understood.
METHODS: Cross-sectional data from the National Health and Nutrition Examination Survey (2011-2014) were obtained for participants aged ≥60 years. Complete availability of cognitive scores was an inclusion criterion. Physical frailty was defined by the presence of exhaustion, weakness, low body mass, and/or low physical activity, and categorized into three groups: robust (0 present), pre-frail (1-2 present), or frail (3-4 present). Four cognitive test scores were converted to z-scores, and global cognition (composite z-score) was calculated by averaging the four-individual z-scores. Multivariable linear regression models were fit to estimate the associations between frailty and cognitive function. Frailty was also evaluated as a risk factor for self-reported subjective memory complaint (SMC) using logistic regression. All models were adjusted for age, sex, race/ethnicity, education, alcohol use, income, marital status, diabetes, hypertension, and history of stroke. Effect measure modification analyses were conducted by age, sex, race/ethnicity, education, and occupational cognitive demand.
RESULTS: The study population comprised 2,863 participants aged ≥60 years. 50.6% of the participants were categorized into robust, 43.2% pre-frail, and 6.2% frail. After adjusting for covariates, compared to robust participants, frail and prefrail participants had lower adjusted mean global cognitive z-scores, <inline-formula><mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mover accent="true"><mml:mi>β</mml:mi><mml:mo>^</mml:mo></mml:mover></mml:mrow></mml:math></inline-formula> = -0.61, 95% CI: -0.83, -0.38 and <inline-formula><mml:math id="m2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mover accent="true"><mml:mi>β</mml:mi><mml:mo>^</mml:mo></mml:mover></mml:mrow></mml:math></inline-formula> = -0.21, 95% CI: -0.30, -0.12, respectively. Both prefrail and frail participants had higher odds of SMC compared to the robust participants. We did not see strong evidence that the association between frailty and cognition was modified by the factors we studied.
DISCUSSION/CONCLUSION: Both pre-frailty and frailty were associated with lower cognitive performance and were more likely to report subjective memory complaints relative to persons without frailty. These findings provide additional evidence that physical frailty may serve as a prognostic factor for cognitive deterioration or dementia, and prevention of frailty may be an important public health strategy.
METHODS: Cross-sectional data from the National Health and Nutrition Examination Survey (2011-2014) were obtained for participants aged ≥60 years. Complete availability of cognitive scores was an inclusion criterion. Physical frailty was defined by the presence of exhaustion, weakness, low body mass, and/or low physical activity, and categorized into three groups: robust (0 present), pre-frail (1-2 present), or frail (3-4 present). Four cognitive test scores were converted to z-scores, and global cognition (composite z-score) was calculated by averaging the four-individual z-scores. Multivariable linear regression models were fit to estimate the associations between frailty and cognitive function. Frailty was also evaluated as a risk factor for self-reported subjective memory complaint (SMC) using logistic regression. All models were adjusted for age, sex, race/ethnicity, education, alcohol use, income, marital status, diabetes, hypertension, and history of stroke. Effect measure modification analyses were conducted by age, sex, race/ethnicity, education, and occupational cognitive demand.
RESULTS: The study population comprised 2,863 participants aged ≥60 years. 50.6% of the participants were categorized into robust, 43.2% pre-frail, and 6.2% frail. After adjusting for covariates, compared to robust participants, frail and prefrail participants had lower adjusted mean global cognitive z-scores, <inline-formula><mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mover accent="true"><mml:mi>β</mml:mi><mml:mo>^</mml:mo></mml:mover></mml:mrow></mml:math></inline-formula> = -0.61, 95% CI: -0.83, -0.38 and <inline-formula><mml:math id="m2" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mover accent="true"><mml:mi>β</mml:mi><mml:mo>^</mml:mo></mml:mover></mml:mrow></mml:math></inline-formula> = -0.21, 95% CI: -0.30, -0.12, respectively. Both prefrail and frail participants had higher odds of SMC compared to the robust participants. We did not see strong evidence that the association between frailty and cognition was modified by the factors we studied.
DISCUSSION/CONCLUSION: Both pre-frailty and frailty were associated with lower cognitive performance and were more likely to report subjective memory complaints relative to persons without frailty. These findings provide additional evidence that physical frailty may serve as a prognostic factor for cognitive deterioration or dementia, and prevention of frailty may be an important public health strategy.