TY - JOUR
PY - 2022//
TI - Association between cognitive frailty and falls among older community dwellers in China: a Chinese longitudinal healthy longevity survey-based study
JO - Frontiers in aging neuroscience
A1 - Chen, Huihe
A1 - Huang, Lanhui
A1 - Xiang, Wei
A1 - Liu, Yu
A1 - Xu, Jian-Wen
SP - e1048961
EP - e1048961
VL - 14
IS -
N2 - BACKGROUND: The combined effect of cognitive impairment (CoI) and frailty on falls is controversial. This study aimed to explore whether older adults with cognitive frailty (CF) were at a higher risk of falls than those with only CoI or frailty and to present a fall prediction model based on CF.
METHODS: A total of 4,067 adults aged ≥ 60 years were included from the Chinese Longitudinal Healthy Longevity Survey through face-to-face interviews. Cognitive function and frailty were assessed using the mini-mental state examination scale and frailty index, respectively. Logistic regression was used to determine fall-associated risk factors and develop a fall prediction model. A nomogram was then plotted. The model performance was evaluated using the area under the curve (AUC), concordance index (C-index), and calibration curve. All analyses were performed using SPSS and R statistical packages.
RESULTS: The prevalence of CF and falls were 1.4 and 19.4%, respectively. After adjusting for covariates, the odds ratio of CF, frailty only, and CoI only for falls were 2.27 (95% CI: 1.29-3.97), 1.41 (95% CI: 1.16-1.73), and 0.99 (95% CI: 0.43-2.29), respectively. CF, sex, age, hearing difficulty, depression, anxiety, disability in instrumental activities of daily living, and serious illness in the past 2 years were independently associated with falls. A prediction model based on these factors yielded an AUC of 0.646 and a C-index of 0.641.
CONCLUSION: Cognitive frailty (CF) exerted a cumulative effect on falls than did CoI or frailty alone. Joint assessments of cognitive function and frailty status may be beneficial for fall risk screening in community. A prediction model using CF as a factor could be helpful for this process.
Language: en
LA - en SN - 1663-4365 UR - http://dx.doi.org/10.3389/fnagi.2022.1048961 ID - ref1 ER -