A Cross-section study of 299 community-dwelling frail older people with mean age of 79.5 participated in this study. They must be identified to be either pre-frail or frail based on Fred Frailty index. Their level of participation restriction was assessed based on Chinese Reintegration to Nursing Living Index (C-RNLI). All other independent variables were identified and systematically linked to the different components in the WHO-ICF model which included
1) personal and health factors (such as their age, gender, levels of frailty, numbers of disease, prescribed medication, hospitalization and falls in the past 12 months. Chinese version of Charlson comorbidity index (C-CCI) was used to assess participants’ levels of comorbidity)
2) environmental factors (such as self-perceived socioeconomic status, living alone or with family and social network)
3) body fuctions and structures (such as level fatigue, nutrition status, sleep quality, depressive mood, pain level)
4) activity level (such as instrumental activity of daily living, mobility, physical activiy level)
IBM SPSS Version 23.0 was used to run the statistical data analysis. The chi-squares tests were used to compare proportions. Student’s t tests were used to compare means so as to examine the associated risk factors among participants with or without participation restriction. Multiple logistic regression analysis was performed. Regression coefficients, adjusted odds ratios (ORs) with corresponding 95 % confidence intervals (CIs) and p-values are presented. ORs were used to evaluate risk factors associated with or without participation restriction. Demographic and health condition related variables such as age, sex, number of diseases suffered as well as number of medications taken, and falling history were included in the model. In addition, model also includes variables related to environmental factors, body functions and structures (impairment) and activity limitation. All statistical tests were two-tailed and variables were considered significant at a significance level of 0.05.
The results have shown that among all participants, 207 participants (69.2%) were identified of having participation restriction in at least one aspect of their life with the mean C-RNLI score of 68.3 (SD 19.43). Multivariate regression analysis showed that participants’ status of frailty, self-perceived social status, level of exhibited depressive mood, sleep quality, mobility, level of fear of falling and physical activity levels have significant association with participation restriction. When including all variables regardless of their significance, all factors explain 67.1% of variance in participation restriction.
In conclusion, participation restriction is common among community-dwelling frail older people. It was associated with risk factors across different components in the WHO-ICF model. This finding supports the fact that participation restriction is multifactorial in nature. In view of some modifiable risk factors were identified in this study, multifactorial interventions targeting the modifiable risk factors should be developed and evaluated in the future studies so as to reduce participation restriction among frail older people.
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