Background: the aim of this study was to examine the cross-sectional and longitudinal associations of different multimorbidity patterns with physical frailty in older adults. Methods: we used data from the Swedish National study on Aging and Care in Kungsholmen to generate a physical frailty measure, and clusters of participants with similar multimorbidity patterns were identified through fuzzy c-means cluster analyses. The cross-sectional association (n = 2,534) between multimorbidity clusters and physical frailty was measured through logistic regression analyses. Six- (n = 2,122) and 12-year (n = 2,140) longitudinal associations were determined through multinomial logistic regression analyses. Results: six multimorbidity patterns were identified at baseline: psychiatric diseases; cardiovascular diseases, anaemia and dementia; sensory impairments and cancer; metabolic and sleep disorders; musculoskeletal, respiratory and gastrointestinal diseases; and an unspecific pattern lacking any overrepresented diseases. Cross-sectionally, each pattern was associated with physical frailty compared with the unspecific pattern. Over 6 years, the psychiatric diseases (relative risk ratio [RRR]: 3.04; 95% confidence intervals [CI]: 1.59-5.79); cardiovascular diseases, anaemia and dementia (RRR 2.25; 95% CI: 1.13-4.49) and metabolic and sleep disorders (RRR 1.99; 95% CI: 1.25-3.16) patterns were associated with incident physical frailty. The cardiovascular diseases, anaemia and dementia (RRR: 4.81; 95% CI: 1.59-14.60); psychiatric diseases (RRR 2.62; 95% CI: 1.45-4.72) and sensory impairments and cancer (RRR 1.87; 95% CI: 1.05-3.35) patterns were more associated with physical frailty, compared with the unspecific pattern, over 12 years. Conclusions: we found that older adults with multimorbidity characterised by cardiovascular and neuropsychiatric disease patterns are most susceptible to developing physical frailty.

Multimorbidity patterns and risk of frailty in older community-dwelling adults: A population-based cohort study

Trevisan C.
Penultimo
;
2021

Abstract

Background: the aim of this study was to examine the cross-sectional and longitudinal associations of different multimorbidity patterns with physical frailty in older adults. Methods: we used data from the Swedish National study on Aging and Care in Kungsholmen to generate a physical frailty measure, and clusters of participants with similar multimorbidity patterns were identified through fuzzy c-means cluster analyses. The cross-sectional association (n = 2,534) between multimorbidity clusters and physical frailty was measured through logistic regression analyses. Six- (n = 2,122) and 12-year (n = 2,140) longitudinal associations were determined through multinomial logistic regression analyses. Results: six multimorbidity patterns were identified at baseline: psychiatric diseases; cardiovascular diseases, anaemia and dementia; sensory impairments and cancer; metabolic and sleep disorders; musculoskeletal, respiratory and gastrointestinal diseases; and an unspecific pattern lacking any overrepresented diseases. Cross-sectionally, each pattern was associated with physical frailty compared with the unspecific pattern. Over 6 years, the psychiatric diseases (relative risk ratio [RRR]: 3.04; 95% confidence intervals [CI]: 1.59-5.79); cardiovascular diseases, anaemia and dementia (RRR 2.25; 95% CI: 1.13-4.49) and metabolic and sleep disorders (RRR 1.99; 95% CI: 1.25-3.16) patterns were associated with incident physical frailty. The cardiovascular diseases, anaemia and dementia (RRR: 4.81; 95% CI: 1.59-14.60); psychiatric diseases (RRR 2.62; 95% CI: 1.45-4.72) and sensory impairments and cancer (RRR 1.87; 95% CI: 1.05-3.35) patterns were more associated with physical frailty, compared with the unspecific pattern, over 12 years. Conclusions: we found that older adults with multimorbidity characterised by cardiovascular and neuropsychiatric disease patterns are most susceptible to developing physical frailty.
2021
Tazzeo, C.; Rizzuto, D.; Calderon-Larranaga, A.; Roso-Llorach, A.; Marengoni, A.; Welmer, A. -K.; Onder, G.; Trevisan, C.; Vetrano, D. L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2481734
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