Dataset Information

Association between cognitive frailty and falls among older community dwellers in China: A Chinese longitudinal healthy longevity survey-based study.

ABSTRACT:

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.

SUBMITTER: Chen H

PROVIDER: S-EPMC9880264 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association between cognitive frailty and falls among older community dwellers in China: A Chinese longitudinal healthy longevity survey-based study.

Chen Huihe H Huang Lanhui L Xiang Wei W Liu Yu Y Xu Jian-Wen JW

Frontiers in aging neuroscience 20230113

<h4>Background</h4>The combined effect of cognitive impairment (CoI) and frailty on falls is controversial. This study aimed to explore whether older adults with cognitive frailty (<i>CF</i>) were at a higher risk of falls than those with only CoI or frailty and to present a fall prediction model based on <i>CF.</i><h4>Methods</h4>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 fr ...[more]

PMID: 36711208

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Project description:Background and Objective: Few studies have explored the relationship between malnutrition measured by the Geriatric Nutritional Risk Index (GNRI) and cognitive performance. This study aimed to investigate the association of malnutrition with cognitive function in the Chinese population. Methods: It was a prospective longitudinal study and used three waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) data in 2011-2012, 2014, and 2017-2018. Participants aged 60 years or older without mental illness and cerebrovascular diseases were eligible. The GNRI was used to assess nutritional status as follows: normal nutrition (a GNRI > 98), mild malnutrition (92 ≤ a GNRI ≤ 98), and moderate-to-severe malnutrition (a GNRI < 92). Cognitive performance was evaluated by the Mini-Mental State Examination (MMSE) scores. The relationship between the GNRI and cognitive function was analyzed using a linear mixed-effects model. Results: A total of 1,632 subjects were analyzed, including 741 males and 891 females. Of these, 65.0, 19.4, and 15.6% of subjects were at normal nutritional status, mild, and moderate-to-severe malnutrition, respectively. After adjusting for potential confounders, participants under mild and moderate-to-severe malnutrition status have a lower MMSE score [β (95% CI): -0.95 (-1.60, -0.25) and -1.39 (-2.21, -0.57), respectively], compared with those having normal nutrition. Also, there was a linear trend in the association of malnutrition risk with cognitive function in the total population [β (95% CI): -0.74 (-1.13, -0.35)]. However, a significant association of malnutrition with cognitive function was observed only among illiterate females aged above 90 years. Conclusion: This study suggested that there was a significant relationship between the GNRI and cognitive function in the Chinese elderly. Furthermore, subjects with more serious malnutrition have a worse cognitive function, especially in the oldest illiterate females. Clinicians should put more emphasis on assessing the nutritional and cognitive status of the elderly to timely intervene and prevent cognitive impairment.

Project description:AimsTo identify the risk factors associated with frailty among older adults in China and develop a predictive model for assessing their frailty risk.DesignSecondary cross-sectional analysis.MethodsThe 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) provided data for this study. A total of 9006 participants were included in the analysis. Their general demographic, socioeconomic status and health behaviour risk factors were collected in the CLHLS. Frailty was assessed using the Frailty Index. A visual nomogram model was constructed based on independent predictors identified using multivariate analysis. The nomogram's discrimination and calibration capabilities were evaluated using the C-statistics and calibration curves. A 1000-times resampling enhanced bootstrap method was performed for internal validation of the nomogram.ResultsThe results showed that living in rural settings, having a primary education level, having a spouse, having basic living security, smoking, drinking, exercising and social activities were protective factors against frailty. Increasing age, being underweight or obese, adverse self-assessed economic status and poor sleep quality were risk factors of frailty. The AUC values of the internal validation set were 0.830. The calibration curve was close to ideal. The Brier score was 0.122. The above results showed that the nomogram model had a good predictive performance.ConclusionsA simple and fast frailty risk prediction model was developed in this study to help healthcare professionals screen older adults at high risk of frailty in China.ImpactThe frailty risk prediction model will assist healthcare professionals in risk management and decision-making and provide targeted frailty prevention interventions. Screening high-risk older adults and early intervention can reduce the risk of adverse outcomes and save medical expenses for older adults and society, thereby realising cost-effective planning of health resources and healthy ageing.Patient or public contributionNo patient or public contribution. This study was a cross-sectional, secondary analysis of the CLHLS data.

Dataset Information

Association between cognitive frailty and falls among older community dwellers in China: A Chinese longitudinal healthy longevity survey-based study.

Background

Methods

Results

Conclusion

Publications

Association between cognitive frailty and falls among older community dwellers in China: A Chinese longitudinal healthy longevity survey-based study.

Similar Datasets

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