INTRODUCTION: The 30-day readmission rate for chronic obstructive pulmonary disease (COPD) is a common performance metric but may be confounded by factors unrelated to quality of care. Our aim was to assess how sociodemographic factors, multimorbidity and frailty impact 30-day readmission risk after COPD hospitalisation, and whether risk adjustment alters interpretation of temporal trends. METHOD: This is a retrospective analysis of administra-tive data from October 2017 to June 2023 from Changi General Hospital, Singapore. Multivariable mixed-effects logistic regression models were used to estimate unadjusted and risk-adjusted 30-day readmission odds. Covariates included age, sex, race, Charlson Comorbidity Index (CCI), Hospital Frailty Risk Score (HFRS) and year. Temporal trends in readmission risk were compared across unadjusted and adjusted models. RESULTS: Of the 2774 admissions, 749 (27%) resulted in 30-day readmissions. Higher CCI (CCI≥4 versus [vs] CCI=1: adjusted odds ratio [aOR] 2.00, 95% confidence interval [CI] 1.33-2.99, P=0.003; CCI 2-3 vs CCI=1: aOR 1.50, 95% CI 1.15-1.96, P=0.001) and higher HFRS (≥5 vs <5: aOR 1.29, 95% CI 1.01-1.65, P=0.04) were independently associated with increased readmission risk. While unadjusted analyses showed no significant temporal trends, the risk-adjusted model revealed a 32-35% reduction in readmission odds in 2021-2023 compared to baseline. CONCLUSION Multimorbidity and frailty significantly impact COPD readmissions. Risk adjustment revealed improvements in readmission risk not evident in unadjusted analyses, emphasising the importance of applying risk adjustments to ensure valid performance metrics.
Humans ; Pulmonary Disease, Chronic Obstructive/therapy* ; Patient Readmission/trends* ; Male ; Female ; Retrospective Studies ; Aged ; Singapore/epidemiology* ; Multimorbidity ; Frailty/epidemiology* ; Middle Aged ; Risk Adjustment ; Aged, 80 and over ; Logistic Models ; Risk Factors

OBJECTIVE: Burning solid cooking fuel contributes to household air pollution and is associated with frailty. However, how solid cooking fuel use contributes to the development of frailty has not been well illustrated. METHODS: This study recruited 8,947 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study, 2011-2018. Group-based trajectory modeling was employed to identify frailty trajectories. Multinomial logistic regression was used to assess the association between solid cooking fuel use and frailty trajectories. Population-attributable fractions were used to estimate the frailty burden from solid fuel use. RESULTS: We identified three frailty trajectories: low-stable ( n = 5,789), moderate-increasing ( n = 2,603), and fast-increasing ( n = 555). Solid fuel use was associated with higher odds of being in the moderate-increasing ( OR: 1.24, 95% CI: 1.08-1.42) and fast-increasing ( OR: 1.48, 95% CI: 1.14-1.92) trajectories. These associations were strengthened by longer solid fuel use ( P for trend < 0.001). Switching to clean fuel significantly reduced the risk of being in these trajectories compared with persistent solid fuel users. Without solid fuel, 8% of moderate- and 19% of fast-increasing trajectories demonstrated frailty development like the low-stable group. CONCLUSION Solid cooking fuel use is associated with frailty trajectories in middle-aged and older Chinese populations.
Humans ; China/epidemiology* ; Cooking ; Male ; Female ; Middle Aged ; Aged ; Air Pollution, Indoor/adverse effects* ; Frailty/etiology* ; Longitudinal Studies ; Cohort Studies

INTRODUCTION: Our aim was to study the prevalence of frailty and its associated factors in a subacute geriatric ward. METHODS: This was a cross-sectional study of 167 participants between June 2018 and June 2019. Baseline demographics and participants' Mini Nutritional Assessment, Geriatric Depression Scale, Mini Mental State Examination, Charlson's Comorbidity Index and LACE index scores were obtained. Functional measurements such as modified Barthel's Index scores and hand grip strength (HGS) were taken. Frailty was assessed using the Clinical Frailty Scale (CFS) and the FRAIL scale. Data on history of healthcare utilisation, medications, length of stay, selected blood investigations and presence of geriatric syndromes were also collected. RESULTS: The prevalence of pre-frailty (CFS 4) and frailty (CFS ≥ 5) was 16.2% and 63.4%, respectively. There were significant associations between CFS and age (pre-frail vs. non-frail: odds ratio [OR] 1.14, 95% confidence interval [CI] 1.04-1.25, P = 0.006; frail vs. non-frail: OR 1.08, 95% CI 1.01-1.15, P = 0.021), HGS at discharge (frail vs. non-frail: OR 0.90, 95% CI 0.82-0.99, P = 0.025), serum albumin (frail vs. non-frail: OR 0.90, 95% CI 0.82-0.99, P = 0.035) and the presence of urinary incontinence (frail vs. non-frail: OR 3.03, 95% CI 1.19-7.77, P = 0.021). CONCLUSION Frailty is highly prevalent in the subacute geriatric setting and has many associated factors. In this study, independent factors associated with frailty were age, HGS at discharge, serum albumin and urinary incontinence. This has implications for future resource allocation for frail older inpatients and may help direct further research to study the effectiveness of frailty-targeted interventions.
Humans ; Aged ; Frailty/epidemiology* ; Frail Elderly ; Hand Strength ; Prevalence ; Singapore/epidemiology* ; Cross-Sectional Studies ; Fatigue Syndrome, Chronic ; Geriatric Assessment ; Urinary Incontinence ; Serum Albumin

With the rapid aging of the global population posing a serious problem, frailty, a non-specific state that reflects physiological senescence rather than aging in time, has become more widely addressed by researchers in various medical fields. A high prevalence of frailty is found among kidney transplant (KT) candidates and recipients. Therefore, their frailty has become a research hotspot in the field of transplantation. However, current studies mainly focus on the cross-sectional survey of the incidence of frailty among KT candidates and recipients and the relationship between frailty and transplantation. Research on the pathogenesis and intervention is scattered, and relevant review literature is scarce. Exploring the pathogenesis of frailty in KT candidates and recipients and determining effective intervention measures may reduce waiting list mortality and improve the long-term quality of life of KT recipients. Therefore, this review explains the pathogenesis and intervention measures for frailty in KT candidates and recipients to provide a reference for the formulation of effective intervention strategies.
Humans ; Frailty/epidemiology* ; Risk Factors ; Quality of Life ; Kidney Failure, Chronic ; Kidney Transplantation/adverse effects* ; Cross-Sectional Studies ; Transplant Recipients

Objective: To explore the association between sleep duration and the risk of frailty among the elderly over 80 years old in China. Methods: Using the data from five surveys of the China Elderly Health Influencing Factors Follow-up Survey (CLHLS) (2005, 2008-2009, 2011-2012, 2014, and 2017-2018), 7 024 elderly people aged 80 years and above were selected as the study subjects. Questionnaires and physical examinations were used to collect information on sleep time, general demographic characteristics, functional status, physical signs, and illness. The frailty state was evaluated based on a frailty index that included 39 variables. The Cox proportional risk regression model was used to analyze the correlation between sleep time and the risk of frailty occurrence. A restricted cubic spline function was used to analyze the dose-response relationship between sleep time and the risk of frailty occurrence. The likelihood ratio test was used to analyze the interaction between age, gender, sleep quality, cognitive impairment, and sleep duration. Results: The age M (Q₁, Q₃) of 7 024 subjects was 87 (82, 92) years old, with a total of 3 435 (48.9%) patients experiencing frailty. The results of restricted cubic spline function analysis showed that there was an approximate U-shaped relationship between sleep time and the risk of frailty. When sleep time was 6.5-8.5 hours, the elderly had the lowest risk of frailty; Multivariate Cox proportional risk regression model analysis showed that compared to 6.5-8.5 hours of sleep, long sleep duration (>8.5 hours) increased the risk of frailty by 13% (HR: 1.13; 95%CI: 1.04-1.22). Conclusion: There is a nonlinear association between sleep time and the risk of frailty in the elderly.
Aged ; Humans ; Aged, 80 and over ; Frailty/epidemiology* ; Sleep Duration ; Prospective Studies ; Sleep/physiology* ; China/epidemiology*

Objective: To investigate the association of the levels of high sensitivity C-reactive protein (hs-CRP) with frailty and its components among the elderly over 65 years old in 9 longevity areas of China. Methods: Cross-sectional data from the Health Ageing and Biomarkers Cohort Study (HABCS, 2017-2018) were used and the elderly over 65 years old were included in this study. Through questionnaire interview and physical examination, the information including demographic characteristics, behavior, diet, daily activity, cognitive function, and health status was collected. The association between hs-CRP and frailty and its components in the participants was analyzed by multivariate logistic regression model and restrictive cubic spline. Results: A total of 2 453 participants were finally included, the age was (84.8±19.8) years old. The median hs-CRP level was 1.13 mg/L and the prevalence of frailty was 24.4%. Compared with the low-level group (hs-CRP<1.0 mg/L), the OR (95%CI) value of the high-level group (hs-CRP>3.0 mg/L) was 1.79 (1.35-2.36) mg/L. As for the components, the hs-CRP level was also positively associated with ADL disability, IADL disability, functional limitation and multimorbidity. After adjusting for confounding factors, compared with the low-level group, the OR (95%CI) values of the high-level group for the four components were 1.68 (1.25-2.27), 1.88 (1.42-2.50), 1.68 (1.31-2.14) and 1.39 (1.12-1.72), respectively. Conclusion: There is a positive association between the levels of hs-CRP and the risk of frailty among the elderly over 65 years old in 9 longevity areas of China. The higher hs-CRP level may increase the risk of frailty by elevating the risk of four physical functional disabilities, namely ADL disability, IADL disability, functional limitation and multimorbidity.
Humans ; Aged ; Aged, 80 and over ; C-Reactive Protein/analysis* ; Frailty/epidemiology* ; Cohort Studies ; Cross-Sectional Studies ; China/epidemiology*

Objective: To examine the association of body mass index (BMI) and waist circumference (WC) with frailty among oldest-old adults in China. Methods: A total of 7 987 people aged 80 years and older (oldest-old) who participated in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2017-2018 were included. Information on demographic characteristics, behavior pattern, diet, activities of daily living, cognitive function, health status, disease condition were collected by questionnaire and physical examination. Generalized linear mixed model and restricted cubic splines (RCS) were used to analyze the association of BMI and WC with frailty. Results: The mean age of all participants was 91.7 years, and their mean BMI and WC were (21.3±3.5) kg/m² and (82.9±10.5) cm, respectively. The proportion of male was 42.3% (3 377/7 987), and the proportion of people with frailty was 33.7% (2 664/7 987). After controlling confounding factors, compared with T₂ (19.1-22.1 kg/m²) of BMI, the OR (95%CI) of the female T₁ (<19.1 kg/m²) and T₃ (≥22.2 kg/m²) group was 1.39 (1.17-1.65) and 1.27 (1.07-1.52), respectively. Compared with T₂ (77-85 cm) of WC, the OR (95%CI) of female T₁ (<77 cm) and T₃ (≥86 cm) group was 1.20 (1.01-1.42) and 1.10 (0.93-1.31), respectively. The results of multiple linear regression model with restrictive cubic spline showed that there was a non-linear association of BMI and WC with frailty in female. Conclusion: There is a U-shaped association of BMI and WC with frailty in female participants.
Adult ; Male ; Female ; Humans ; Aged, 80 and over ; Waist Circumference ; Body Mass Index ; Frailty/epidemiology* ; Activities of Daily Living ; China/epidemiology* ; Risk Factors

Objective: To explore the correlation between sleep status and frailty in adults aged 30-79 years in China, and explore the potential effect modification of general and central obesity. Methods: Based on the baseline data of the China Kadoorie Biobank, we used multinomial logistic regression to analyze the correlation between long and short sleep duration, insomnia disorder, snoring, and unhealthy sleep score with risks of pre-frailty and frailty. Both overall and obesity-stratified analyses were performed. Result: Among the 512 724 participants, 2.3% had frailty and 40.1% had pre-frailty. There was a U-shaped relationship between sleep duration and frailty score. Short (OR=1.21, 95%CI: 1.19-1.23) or long sleep duration (OR=1.19, 95%CI: 1.17-1.21), insomnia disorder (OR=2.09, 95%CI: 2.02-2.17), and snoring (OR=1.61, 95%CI: 1.59-1.63) were all positively correlated with pre-frailty, and dose-response relationships were observed between unhealthy sleep score and pre-frailty (P for trend<0.001), with OR values of 1.46 (1.44-1.48), 1.97 (1.93-2.00) and 3.43 (3.21-3.67) respectively for those having unhealthy sleep score of 1 to 3. These sleep problems were also positively correlated with frailty. Compared with the overweight or obesity group, stronger relationships were observed between short sleep duration and frailty or pre-frailty and between insomnia disorder and pre-frailty, while the relationships between snoring and frailty and pre-frailty were weaker in the participants with normal weight (P for interaction <0.007 for all). We also observed similar effect modification by central obesity. Conclusion: Long or short sleep duration, insomnia disorder, snoring and higher unhealthy sleep scores were positively correlated with pre-frailty or frailty, general and central obesity status could modify the relationships.
Adult ; China/epidemiology* ; Frailty/epidemiology* ; Humans ; Obesity ; Obesity, Abdominal ; Sleep/physiology* ; Sleep Initiation and Maintenance Disorders/epidemiology* ; Sleep Wake Disorders ; Snoring/epidemiology*

Objective: To identify distinct frailty trajectories in a cohort of nationwide community adults aged 50 years and above, and explore the relationship between frailty trajectories and their socioeconomic characteristics and behavioral factors at baseline survey. Methods: Data were from the three waves of "Global Ageing and Adult Health Research" (SAGE) by World Health Organization in China. The frailty index is generated from 32 items. Group-based trajectory modeling using a censored normal model was conducted to identify the patterns in frailty progression over time. Multinomial logistic regression model was used to examine the effect of socioeconomic status and behavioral factors on the frailty trajectories. Results: A total of 4 303 adults aged 50 years and above with complete data from all three rounds of project were included in the final analysis. Three frailty trajectories were identified: low and stable trajectory (LT) (56.8%), moderately increased trajectory (MT) (34.4%) and highly increased trajectory (HT) (8.8%). The results of the multinomial logistic regression analysis showed that the HT group was more likely to be women (OR=1.88, 95%CI:1.22-2.92) and rural residents (OR=1.87, 95%CI:1.29-2.70) compared with the LT group. In terms of household wealth per capita, there was a clear gradient in ORs, the people with lower household wealth were more likely to be classified in the HT group. Conclusion: This study identified three patterns of progression of frailty trajectories in population aged 50 years and above in China and highlighted that interventions should target those vulnerable populations with rapid progression of frailty.
Adult ; Humans ; Female ; Male ; Frailty/epidemiology* ; China/epidemiology* ; Aging ; Logistic Models ; Social Class

Objective: To understand the transition rules of cognitive frailty and its influencing factors in the elderly in China and provide evidence for the early intervention of cognitive frailty. Methods: Data were retrospectively collected from China Health and Retirement Longitudinal Study with 3 round consecutive survey (2011, 2013, 2015) and the state of the subjects were classified into four categories: robust-normal cognitive, cognitive impairment, physical frailty, and cognitive frailty. A multi-state Markov model was established to explore the transition rules of cognitive frailty and its influencing factors. Results: A total of 3 470 older adults were included, and 350 (10.09%) had cognitive frailty at baseline. After two years, the probability of cognitive frailty in the cognitive impairment population was higher than that in people with physical frailty (31.6% vs. 7.6%). Persons with cognitive frailty were more likely to become physical frailty (29.7% vs. 15.6%). Being women (HR=1.599, 95%CI: 1.058-2.417), comorbidity (HR=3.035, 95%CI: 1.090-8.450), and depression (HR=1.678, 95%CI: 1.153-2.441) were the risk factors associated with cognitive frailty in the elderly, while being educated (HR=2.367, 95%CI: 1.567-3.575) was a protective factor for the transition of cognitive frailty to physical frailty. Conclusions: The prevalence of cognitive frailty is relatively high in the elderly in China. Those with cognitive impairment have a higher probability of cognitive frailty. Gender, education level, comorbidity, and depression are the main influencing factors for the occurrence and transition of cognitive frailty.
Aged ; China/epidemiology* ; Cognition ; Cognitive Dysfunction/epidemiology* ; Female ; Frail Elderly ; Frailty/epidemiology* ; Geriatric Assessment ; Humans ; Longitudinal Studies ; Male ; Retrospective Studies