Background The impact of multimorbidity (≥ 2 chronic diseases) on the well-being of older adults is substantial but variable. The burden of multimorbidity varies by the number and kinds of conditions, and timing of onset. The impact varies by age, race, ethnicity, socioeconomic status, and health indicators. Large scale longitudinal surveys linked to medical claims provide unique opportunities to characterize this variability. Methods We analyzed Medicare-linked Health and Retirement Study data for respondents 65 and older with 3 or more years of fee-for-service coverage (n = 17,199; 2000–2016). We applied standardized claims algorithms for operationalizing 21 chronic diseases. We compared multimorbidity levels, demographics, and outcomes at baseline and over time and escalation to high multimorbidity levels (≥ 5 conditions). Results At baseline, 51.2% had no multimorbidity, 36.5% had multimorbidity, and 12.4% had high multimorbidity. Loss of function, cognitive decline, and higher hea

Background The impact of multimorbidity (≥ 2 chronic diseases) on the well-being of older adults is substantial but variable. The burden of multimorbidity varies by the number and kinds of conditions, and timing of onset. The impact varies by age, race, ethnicity, socioeconomic status, and health indicators. Large scale longitudinal surveys linked to medical claims provide unique opportunities to characterize this variability. Methods We analyzed Medicare-linked Health and Retirement Study data for respondents 65 and older with 3 or more years of fee-for-service coverage (n = 17,199; 2000–2016). We applied standardized claims algorithms for operationalizing 21 chronic diseases. We compared multimorbidity levels, demographics, and outcomes at baseline and over time and escalation to high multimorbidity levels (≥ 5 conditions). Results At baseline, 51.2% had no multimorbidity, 36.5% had multimorbidity, and 12.4% had high multimorbidity. Loss of function, cognitive decline, and higher hea

Background Chronic pain is a major health issue and rapid population ageing exacerbates the burden to health systems in countries like Germany. Nonpharmacological interventions (NPIs) are essential in pain care and the prioritization of active NPIs is emphasized in guidelines. This paper examines the utilization of NPIs for chronic pain management in community-dwelling older adults with a certified need of care in Berlin, Germany. Methods Cross-sectional data was collected through standardized face-to-face surveys with older adults (≥65 years), using validated instruments (e.g., Brief Pain Inventory), and structured lists for NPI utilization. Categorization into active and passive NPIs was performed through a literature-based, iterative process by an interdisciplinary team. For not normally distributed data, non-parametric tests were used as appropriate. Logistic regression was conducted for multivariate analysis. Results In total, 250 participants were included in this analysis (aged

Background Creatinine-to-cystatin C ratio (CCR) has been associated with multiple adverse outcomes. However, little is known about its relationship with frailty. We aimed to explore the association between CCR and frailty among older adults. Methods A total of 2599 participants aged ≥ 60 years (mean age 67.9 ± 6.0 years, 50.4% males) were included from the China Health and Retirement Longitudinal Study (2011–2015). Baseline CCR was calculated as plasma creatinine (mg/dL) / cystatin C (mg/L) × 10 and was grouped by quartiles. Frailty was evaluated by the validated physical frailty phenotype (PFP) scale and was defined as PFP score ≥ 3. The generalized estimating equations model was used to explore the relationship between CCR and frailty. Results The frailty risk decreased gradually with increasing CCR in the quartiles (P for trend = 0.002), and the fourth CCR quartile was associated with a significantly lower risk of frailty compared with the lowest quartile (odds ratio [OR] 0.37, 95%

Aim The aim of the present study was to examine the relationship between anemia and basic and instrumental activities of daily living in older female patients. Methods 540 older female outpatients were included in this cross-sectional study. Anemia was defined as a hemoglobin below 12 g/dL. Patients’ demographic characteristics, comorbidities, Geriatric Depression Scale, Mini Nutritional Assessment, and Mini-Mental State Examination (MMSE) were also recorded. Handgrip strength (HGS) was measured with a hand dynamometer to detect dynapenia. Basic Activities of Daily Living (BADL) and Instrumental Activities of Daily Living (IADL) questionnaires were used to evaluate functional capacity. Results The mean age of the participants was 77.42 ± 7.42 years. The prevalence of patients with anemia was 35%. A significant difference was observed between anemic and non-anemic groups in terms of age, presence of diabetes mellitus (DM), hypertension, coronary artery disease (CAD), chronic kidney dise

Background Low physical activity among older adults is related to adverse health outcomes such as depression and loneliness, poor physical function and increased risk of falls. This study was designed to increase physical activity through a digital, group-based, physical activity and music intervention and to examine its effectiveness on social, mental and physical health outcomes. Methods Participants were 34 older adults (65 years +) recruited across four care homes in Scotland to a pilot study. Surveys were administered at baseline and post-intervention, comprising measures of fear of falling, depression and anxiety, loneliness, sleep satisfaction and quality of life. A battery of physical function tests and saliva sampling for cortisol and dehydroepiandrosterone hormone analysis were also conducted at each time point. Additionally, process evaluation measures (recruitment, intervention fidelity, attendance, retention rates and safety) were monitored. The intervention comprised 12 w

Objective To identify white matter fiber injury and network changes that may lead to mild cognitive impairment (MCI) progression, then a joint model was constructed based on neuropsychological scales to predict high-risk individuals for Alzheimer’s disease (AD) progression among older adults with MCI. Methods A total of 173 MCI patients were included from the Alzheimer’s Disease Neuroimaging Initiative(ADNI) database and randomly divided into training and testing cohorts. Forty-five progressed to AD during a 4-year follow-up period. Diffusion tensor imaging (DTI) techniques extracted relevant DTI quantitative features for each patient. In addition, brain networks were constructed based on white matter fiber bundles to extract network property features. Ensemble dimensionality reduction was applied to reduce both DTI quantitative features and network features from the training cohort, and machine learning algorithms were added to construct white matter signature. In addition, 52 patient

Background Due to the high prevalence of multimorbidity and realistic health service demands for fall prevention, there is growing interest in the association between multimorbidity and falls. Our study aimed to identify multimorbidity patterns among Chinese older adults and explore the association between multimorbidity patterns and falls. Methods Data from 4,579 Chinese community-dwelling older adults was included in this analysis. Information regarding falls and 10 chronic conditions was collected. An exploratory factor analysis was performed to determine multimorbidity patterns. Regression models were fitted to explore the associations of individual chronic disease or multimorbidity patterns with falls. Results Among 4,579 participants, 368 (8.0%) were defined as fallers, including 92 (2.0%) frequent fallers, and multimorbidity affected 2,503 (54.7%) participants. Older adults with multimorbidity were more likely to be fallers [odds ratio (OR) = 1.3, P = 0.02] and frequent fallers