BMC Geriatrics最新文献

Background: With the trend of digitalization, social activities among the older population are becoming more diverse as they increasingly adopt technology-based alternatives. To gain a comprehensive understanding of social activities, this study aimed to identify the patterns of digital and in-person social activities among community-dwelling older adults in South Korea, examine the associated factors, and explore the difference in depressive symptoms by the identified latent social activity patterns.

Methods: Data were extracted from a nationwide survey conducted with 1,016 community-dwelling older adults (mean age 68.0 ± 6.5 years, 47.8% male). The main variables assessed were digital social activities (eight items), in-person social activities (six items), and depressive symptoms (20 items). Data were analyzed using latent class analysis, multinomial logistic regression, and multiple linear regression.

Results: We identified four distinct social activity patterns: "minimal in both digital and in-person" (22.0%), "moderate in both digital and in-person" (46.7%), "moderate in digital & very high in in-person" (14.5%), and "high in both digital and in-person" (16.8%). Younger age, living in multi-generational households, and higher digital literacy were associated with a higher likelihood of being in the "moderate in both digital and in-person" than the "minimal in both digital and in-person" group. Younger age, male, living in multi-generational households, residing in metropolitan areas, no dependency on IADL items, doing daily physical exercise, and higher digital literacy were associated with a higher likelihood of being in the "moderate in digital & very high in in-person" than the "minimal in both digital and in-person" group. Younger age, living in multi-generational households, no dependency on IADL items, doing daily physical exercise, and higher digital literacy were associated with a higher likelihood of being in the "high in both digital and in-person" than the "minimal in both digital and in-person" group. Depressive symptoms were significantly higher in the group with minimal engagement in both digital and in-person activities, compared to other three groups.

Conclusions: This study highlights distinct patterns of social activities among Korean community-dwelling older adults. Since older adults with minimal social activity engagement can be more vulnerable to depressive symptoms, interventions that address modifiable attributes, such as supporting digital literacy and facilitating physical activity of older adults, could serve as potential strategies to enhance their social activity engagement and, consequently, their mental well-being.

Background: Older adults requiring care often have multiple morbidities that lead to polypharmacy, including the use of potentially inappropriate medications (PIMs), leading to increased medical costs and adverse drug effects. We conducted a cross-sectional study to clarify the actual state of drug prescriptions and the background of polypharmacy and PIMs.

Methods: Using long-term care (LTC) and medical insurance claims data in the Ibaraki Prefecture from April 2018 to March 2019, we included individuals aged ≥ 65 who used LTC services. The number of drugs prescribed for ≥ 14 days and the number of PIMs were counted. A generalized linear model was used to analyze the association between the backgrounds of individuals and the number of drugs; logistic regression analysis was used for the presence of PIMs. PIMs were defined by STOPP-J and Beers Criteria.

Results: Herein, 67,531 older adults who received LTC services were included. The median number of total prescribed medications and PIMs was 7(IQR 5-9) and 1(IQR 0-1), respectively. The main PIMs were loop diuretics/aldosterone antagonists (STOPP-J), long-term use of proton pump inhibitors (Beers Criteria), benzodiazepines/similar hypnotics (STOPP-J and Beers Criteria), and nonsteroidal anti-inflammatory drugs (STOPP-J and Beers Criteria). Multivariate analysis revealed that the number of medications and presence of PIMs were significantly higher in patients with comorbidities and in those visiting multiple medical institutions. However, patients requiring care level ≥1, nursing home residents, users of short-stay service, and senior daycare were negatively associated with polypharmacy and PIMs.

Conclusions: Polypharmacy and PIMs are frequently observed in older adults who require LTC. This was prominent among individuals with comorbidities and at multiple consulting institutions. Utilization of nursing care facilities may contribute to reducing polypharmacy and PIMs.

Background: Physical inactivity is common among older adults and is associated with poor health outcomes. Medical fitness facilities provide a medically focused approach to physical fitness and can improve physical activity in their communities. This study aimed to assess the relationship between membership in the medical fitness model and all-cause mortality, health care utilization, and major adverse cardiac events in older adults.

Methods: A propensity weighted retrospective cohort study linked individuals that attended medical fitness facilities to provincial health administrative databases. Older adults who had at least 1 year of health coverage from their index date between January 1st, 2005 to December 31st 2015 were included. Controls were assigned a pseudo-index date at random based on the frequency distribution of index dates in members. Members were stratified into low frequency attenders (< 1 Weekly Visits) and regular frequency attenders (> 1 Weekly Visits). Time to event models estimated the hazard ratios (HRs) for risk of all-cause mortality and major adverse cardiac event. Negative binomial models estimated the risk ratios (RRs) for risk of hospitalizations, outpatient primary care visits and emergency department visits.

Results: Among 3,029 older adult members and 91,734 controls, members had a 45% lower risk of all-cause mortality (HR: 0.55, 95% CI: 0.50 - 0.61), 20% lower risk of hospitalizations (RR: 0.80, 95% CI: 0.75 - 0.84), and a 27% (HR: 0.72, 95% CI: 0.66 - 0.77), lower risk of a major adverse cardiovascular event. A dose-response effect with larger risk reductions was associated with more frequent attendance as regular frequency attenders were 4% more likely to visit a general practitioner for a routine healthcare visit (RR: 1.04, 95% CI: 1.01 - 1.07), but 23% less likely to visit the emergency department (RR: 0.87, 95% CI: 0.82 - 0.92).

Conclusions: Membership at a medical fitness facility was associated with a decreased risk of mortality, health care utilization and cardiovascular events. The medical fitness model may be an alternative approach for public health strategies to promote positive health behaviors in older adult populations.

Background: This study conducted in-depth interviews to explore the factors that influence the adoption of fall detection technology among older adults and their families, providing a valuable evaluation framework for healthcare providers in the field of fall detection, with the ultimate goal of assisting older adults immediately and effectively when falls occur.

Methods: The method employed a qualitative approach, utilizing semi-structured interviews with 30 older adults and 29 families, focusing on their perspectives and expectations of fall detection technology. Purposive sampling ensured representation from older adults with conditions such as Parkinson's, dementia, and stroke.

Results: The results reveal key considerations influencing the adoption of fall-detection devices, including health factors, reliance on human care, personal comfort, awareness of market alternatives, attitude towards technology, financial concerns, and expectations for fall detection technology.

Conclusions: This study identifies seven key factors influencing the adoption of fall detection technology among older adults and their families. The conclusion highlights the need to address these factors to encourage adoption, advocating for user-centered, safe, and affordable technology. This research provides valuable insights for the development of fall detection technology, aiming to enhance the safety of older adults and reduce the caregiving burden.

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 patients from the National Alzheimer's Coordinating Center (NACC) database were used for external validation of white matter signature. A joint model was subsequently generated by combining with scale scores, and its performance was evaluated using data from the testing cohort.

Results: Based on multivariate logistic regression, clinical dementia rating and Alzheimer's disease assessment scales (CDRS and ADAS, respectively) were selected as independent predictive factors. A joint model was constructed in combination with the white matter signature. The AUC, sensitivity, and specificity in the training cohort were 0.938, 0.937, and 0.91, respectively, and the AUC, sensitivity, and specificity in the test cohort were 0.905, 0.923, and 0.872, respectively. The Delong test showed a statistically significant difference between the joint model and CDRS or ADAS scores (P < 0.05), yet no significant difference between the joint model and the white matter signature (P = 0.341).

Conclusion: The present results demonstrate that a joint model combining neuropsychological scales can be constructed by using machine learning and DTI technology to identify MCI patients who are at high-risk of progressing to AD.

Background: Under the background of the increasing trend of population aging, the health and quality of life of older adults have become the focus of social concern. As an important part of older adults' daily life, the design and configuration of the built environment may positively or negatively affect older adults' health behaviors. Therefore, this study aims to explore the relationship between older adults' perceived built environments and health behaviors, which is the association between perceived built environments and older adults' physical activity (PA) and social interactions. This is important for optimizing the community built environment and improving the quality of life of older adults.

Methods: In this study, a questionnaire was surveyed on 916 Chinese older adults aged 60 and above. The questionnaire was used to collect demographic information and social interaction from the participants, and the Physical Activity Neighborhood Environment Scale (PANES) and the Physical Activity Scale for the Elderly (PASE) were used to assess older adults' subjective perceptions of the built environment in their neighborhoods and their levels of PA, respectively. In data analysis, ANOVA and chi-square tests were used to compare the significance of differences between groups, and multiple linear regression model were used to estimate the association between older adults' perceived characteristics of the built environment and their PA and social interaction.

Results: After controlling for confounders such as gender, age, BMI, and education level, the multiple linear regression model showed that perceived destination accessibility, neighborhood infrastructure, aesthetic qualities, and neighborhood environment indices were significantly correlated with PA (β = 0.083 ~ 0.095, P < 0.05) and social interaction (β = 0.087 ~ 0.144, P < 0.05) among older adults. In addition, neighborhood safety (β = -0.084, P < 0.05), social environment (β = 0.091, P < 0.01), and street connectivity (β = 0.112, P < 0.001) were also strongly associated with older adults' social interaction.

Conclusions: Different perceived built environment attributes are correlated with the health behaviors of Chinese older adults to different degrees. This finding helps to guide community planning and construction, provides an empirical basis for improving health behaviors of older adults, and provides an important reference for building healthy communities for older adults and realizing comprehensive healthy development of older adults.

Trial registration: There was no trial registration for this study, but the study was approved by the Institutional Review Board of Tsinghua University (No. THU0120230196).

Background: One way of standardizing practice and improving patient safety is by introducing clinical care pathways; however, such pathways are typically geared towards assisting clinicians and healthcare organizations with evidence-based practice. Many dementia care pathways exist with no agreed-upon version of a care pathway and with little data on experiences about their use or outcomes. The objectives of the review were: (1) to identify the dementia care pathway's purpose, methods used to deploy the pathway, and expected user types; (2) to identify the care pathway's core components, expected outcomes, and implications for persons with dementia and their care partners; and (3) determine the extent of involvement by persons with dementia and/or their care partners in developing, implementing, and evaluating the care pathways.

Methods: We systematically searched six literature databases for published literature in the English language in September 2023 utilizing Arskey and O'Malley's scoping review framework.

Results: The findings from the dementia care pathways (n = 13) demonstrated assistance in dementia diagnostic and management practices for clinicians and offered structured care processes in clinical settings. For this reason, these pathways emphasized assessment and interventional post-diagnostic support, with less emphasis on community-based integrated dementia care.

Conclusion: Future dementia care pathway development can seek the involvement of persons with dementia and care partners in designing, implementing and evaluating such pathways, ensuring that outcome measures properly reflect the impact on persons with lived dementia experience and their care partners.

Objective: Frailty and hypoproteinaemia are common in older individuals. Although there is evidence of a correlation between frailty and hypoproteinaemia, the relationship between frailty and hypoproteinaemia in hospitalized/critically ill and older community residents has not been clarified. Therefore, the aim of our meta-analysis was to evaluate the associations between frailty and hypoproteinaemia in different types of patients.

Methods: A systematic retrieval of articles published in the PubMed, Embase, Medline, Web of Science, Cochrane, Wanfang, and CNKI databases from their establishment to April 2024 was performed to search for studies on the associations between severity of frailty or prefrailty and hypoproteinaemia in older adults. The Newcastle‒Ottawa Scale and the Agency for Healthcare Research and Quality Scale were used to assess study quality.

Results: Twenty-two studies were included including 90,351 frail older people were included. Meta-analysis revealed an association between frailty or prefrailty and hypoproteinaemia (OR = 2.37, 95% CI: 1.47, 3.83; OR = 1.62, 95% CI: 1.23, 2.15), there was no significant difference in the risk of hypoproteinaemia between patients with severe frailty and those with low or moderate frailty (OR = 0.62, 95% CI:0.44, 0.87). The effect of frailty on the occurrence of hypoproteinaemia was more obvious in hospitalized patients/critically ill patients than in surgical patients (OR = 3.75, 95% CI: 2.36, 5.96), followed by older community residents (OR = 2.30, 95% CI: 1.18, 4.49).

Conclusion: Frailty is associated with hypoproteinaemia in surgical patients, hospitalized older patients and older community residents. Future studies should focus on the benefits of albumin supplementation in preventing or alleviating frailty and related outcomes in the future.

Background: Social environment may broadly impact multifaceted frailty; however, how environmental differences influence frailty in older adults with diabetes remains unclear. This study aimed to investigate regional differences in frailty in urban and rural areas among older adults with diabetes.

Methods: This cross-sectional study was conducted as part of the frailty prevention program for older adults with diabetes study. Older adults aged 60-80 years who could independently perform basic activities of daily living (ADLs) were enrolled sequentially. Trained nurses obtained patient background, complications, body weight, body composition, blood tests, grip strength, frailty assessment, and self-care score results. Regional differences in frailty were evaluated using logistic and multiple linear regression analyses.

Results: This study included 417 participants (269 urban and 148 rural). The prevalence of robustness was significantly lower in rural areas than in urban areas (29.7% vs. 43.9%, p = 0.018). Living in rural areas was associated with frailty (odds ratio [OR] 2.55, 95% confidence interval [CI] 1.38-4.71) and pre-frailty (OR 2.10, 95%CI 1.30-3.41). Lower instrumental ADL (B 0.28, standard error [SE] 0.073) and social ADL (B 0.265, SE 0.097) were characteristics of rural residents.

Conclusions: Regional differences in frailty were observed. Older adults with diabetes living in rural areas have a higher risk of frailty owing to a decline in instrumental and social ADLs. Social environment assessment and intervention programs that include communication strategies to enable care and social participation across environments are crucial to the effective and early prevention of frailty.