Journal of Aging Research最新文献

Objectives: This study investigated gender disparity in quality of life (QOL) and social support among older adults in West Bengal, India.

Methods: The study was conducted among 200 older people. The WHOQOL-BREF questionnaire and the MSPSS scale were used to measure the respondents' QOL and social support, respectively. Bivariate correlation and binary logistic regression were performed.

Result: This study showed that being female (AOR: 2.53; CI: 1.32-4.86), low social support (AOR: 5.18; CI: 1.98-13.57), moderate social support (AOR: 4.17; CI: 2.05-8.49), functionally impaired (AOR: 2.25; CI: 1.04-4.86), and being widowed (AOR: 2.95; CI: 1.29-6.73) were significantly associated with poorer QOL of older adults. The interaction effect showed that the QOL of older men would experience a greater improvement than that of older women as a result of increased social support.

Conclusion: Due to inadequate research on the relationship between QOL and social support with special emphasis on gender in India, this study will provide insight for planning interventions to improve older individuals' QOL.

Background: Nutritional assessment during the perioperative period is critical, particularly for older patients at high risk for complications. Bioelectrical impedance analysis (e.g., InBody) is commonly used to assess skeletal muscle mass via the skeletal muscle index (SMI). However, its use is limited in patients with contraindications, including implantable cardiac devices.

Objective: Therefore, this study explored a noninvasive alternative: assessing the relationship between salivary metabolites and SMI to identify potential biomarkers associated with muscle mass.

Methods: This retrospective study analyzed data from male preoperative patients who had both InBody analysis and salivary metabolomics data collected between January 2021 and March 2024. Salivary metabolites, including butyrate and hexanoate, were quantified using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF MS). Body composition parameters, including SMI, and blood nutritional indicators, were obtained. Volcano plot analysis identified metabolites significantly differing between patients with SMI ≥ 7.0 and < 7.0 kg/m². Receiver operating characteristic (ROC) curve analysis evaluated the discriminatory ability of individual variables. Univariate and multivariate logistic regression analyses identified factors associated with SMI status.

Results: Patients with low SMI were significantly older than those with high SMI. While body composition indices differed significantly, general nutritional blood markers remained comparable. Volcano plot analysis showed significantly higher salivary butyrate and hexanoate levels in patients with SMI ≥ 7.0 kg/m² compared to those with SMI < 7.0 kg/m². ROC curve analysis demonstrated significant discriminatory ability for butyrate, hexanoate, and age. Univariate analysis identified age as significantly associated with SMI status based on odds ratio. Multivariate analysis using stepwise variable selection retained age (OR: 1.155, p-value = 0.070) and hexanoate (OR: 0.980, p-value = 0.269) in the final model.

Conclusions: This exploratory study suggests that salivary metabolites, particularly butyrate and hexanoate, along with age, may serve as potential indicators for discriminating SMI status. These findings suggest the potential utility of salivary metabolites as noninvasive biomarkers for assessing muscle mass in the perioperative setting. This could enable early sarcopenia detection and enhanced nutritional management in older patients, particularly those with contraindications. Trial Registration: UMIN Clinical Trials Registry: UMIN000057185.

Background: Dual-task and single-task interventions are strategies to enhance physical and cognitive function in older adults, but their effectiveness in comparison is not well understood. Understanding their effects on cognitive benefits, balance, and overall physical performance is important for developing effective interventions to support aging populations.

Objective: This scoping review aims to identify and synthesize current evidence on dual-task and single-task interventions for older adults, categorizing intervention types, study populations, and measured outcomes.

Methods: PubMed, MEDLINE, Scopus, and Web of Science databases were searched. A comprehensive literature search identified studies involving dual-task and single-task interventions from 2014 to July 2024 involving adults aged 60 and older. The methodological quality of the included studies was assessed using the Mixed-Methods Appraisal Tool (MMAT). Studies were categorized based on task type: motor-cognitive dual-task, motor-motor dual-task, single-motor task, or single cognitive task. Extracted data included intervention characteristics, outcome measures, and key findings.

Results: A total of 31 studies met the inclusion criteria with participants being community-dwelling older adults aged 60 and above. Intervention durations ranged from 6 weeks to 12 months, with most studies implementing sessions 2-3 times per week. Outcome measures commonly included assessments of balance, cognitive function, and gait performance. Dual-task interventions demonstrated greater improvements in gait, dynamic balance, and cognitive function compared to single-task interventions with motor-cognitive dual-task training being particularly effective in enhancing balance and mobility in older adults.

Conclusion: This review provides a comprehensive comparison of dual-task and single-task interventions, highlighting the superior efficacy of dual-task training in improving both cognitive and physical outcomes. While single-task interventions offer benefits, they lack the comprehensive improvements observed in dual-task training. Future research should explore long-term outcomes, refine intervention protocols, and assess the applicability of combined approaches to maximize benefits for aging populations. And, studies must prioritize reporting effect sizes and minimum clinically important differences (MCID) to ensure findings are clinically relevant.

Background: The global population of older adults is expanding in developing nations. According to the WHO, elder abuse is defined as "a single or repeated act, or lack of appropriate action, occurring within any relationship where there is an expectation of trust, which causes harm or distress to an older person." Such abuse is a global concern. This study aimed to find the prevalence, contributing factors, and impacts to inform effective prevention and intervention strategies.

Methods: A community-based cross-sectional study was conducted via face-to-face interviews with elderly individuals aged 60 years and above. The study was conducted among participants from the Kathmandu Valley, Nepal. The sample size was 385 with a prevalence of 50.3%. A multistage sampling technique was employed to select the sample. The first household was chosen randomly, and subsequent households were selected using the calculated sampling interval.

Results: Psychological/emotional abuse was the most common (18.7%), followed by financial abuse, physical abuse, and neglect with sexual abuse reported rarely. The most frequently reported health problem was hypertension (21.4%) followed by osteoarthritis/osteoporosis and diabetes. Gender shows a significant association with emotional abuse (p = 0.02), where females (24.4%) experience higher rates compared to males (14.8%). Physical abuse is more common among females (16.7%) than males (10.0%), though the difference is marginally insignificant (p = 0.06).

Conclusions: Elderly abuse has been increasingly recognized as a serious global issue, warranting urgent attention from healthcare systems and national authorities.

Background: Aging is a gradual decline in physiological and functional capacities that leads to an exponentially increasing risk of death. Although aging is universal, the rate of aging differs substantially between individuals. Biomarkers of aging are being developed to improve the prediction of a person's susceptibility to disease onset, disease course, and complications, as well as to estimate lifespan and healthspan.

Objective: The primary aim of this study was to develop and evaluate machine-learning models that estimate chronological age from routinely measured blood biomarkers in a large Central European population. A secondary aim was to characterize the relative contribution of individual biomarkers and to discuss the resulting index as a potential biological age marker.

Methods: We modeled chronological age as a regression problem using four algorithms: a multilayer neural network, Extreme Gradient Boosting (XGBoost), Random Forest, and Ridge Regression. The dataset comprised more than 26 million anonymized laboratory results from over 3 million individuals. Model performance was assessed using mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and epsilon-accuracy. We also examined feature importance to identify the most informative biomarkers.

Results: XGBoost achieved the best performance, with an MAE of 8.73 years across all ages. The 10 most influential predictors were alanine aminotransferase (ALT), creatinine, alkaline phosphatase (ALP), glucose, mean corpuscular volume (MCV), thrombocytes, albumin, mean corpuscular hemoglobin (MCH), urea, and aspartate aminotransferase (AST). These markers span hepatic, renal, metabolic, and hematological domains.

Conclusion: Using easily accessible blood biomarkers, it is possible to estimate chronological age with an MAE of 8.73 years in a large Central European population. Because the present work does not include validation against clinical outcomes, the resulting index should be regarded as a potential biological age marker. Future studies are needed to test its association with morbidity, mortality, and established biological age measures in independent cohorts.

[This corrects the article DOI: 10.1155/jare/1053086.].

Background and objective: Alzheimer's disease and related dementias (ADRDs) are progressive conditions that substantially impact individuals and families. Timely diagnosis and early support are critical for long-term adjustment. However, current dementia care models do not meet needs of patients and families. Dementia care specialists treating individuals with dementia offer unique insight into care needs of diverse groups of patients, families, and healthcare systems that can be used to identify opportunities to improve care. To understand dementia care specialists' impressions of factors impacting ADRD diagnosis and postdiagnosis support, we aimed to identify factors that impact (1) timely and accurate diagnosis, (2) diagnostic disclosure and provision of postdiagnosis support, and (3) patient and care-partner adjustment after diagnosis.

Research design and methods: We recruited dementia care specialists treating persons living with dementia (n = 19) from two academic medical centers. Participants completed 60-min qualitative focus groups or individual interviews. Data were analyzed using a hybrid inductive-deductive approach to thematic analysis.

Results: We identified subthemes within three overarching a priori determined themes. Participants highlighted the presence of delays in referrals, time constraints, specialist discomfort, and lack of training as factors impacting the timeliness and accuracy of diagnosis. They also highlighted information needed in disclosure visits, ways of coordinating care, and identifying early support needs. Finally, participants highlighted factors impacting adjustment including families' insight and acceptance, distress, and available resources.

Discussion and implications: Our study highlights the challenges dementia care specialist specialists face in delivering early support for individuals and families impacted by ADRDs and suggests avenues for revising existing care models.

Background: As global populations age, promoting the health and well-being of older adults has become a public health priority. Green spaces-such as parks, gardens, and forests-offer numerous health benefits, including enhanced physical activity, mental well-being, and social interaction. This study employs a bibliometric analysis to explore global research trends on the relationship between green spaces and older adults' health.

Methods: Data were collected from the Web of Science Core Collection (WoSCC) and Scopus databases, covering the period from 2004 to 2025. A total of 2066 relevant studies were identified and analyzed in terms of publication trends, geographical contributions, key research themes, and influential works.

Results: Results indicate a growing body of research, with the United States, China, and Australia emerging as leading contributors. Keyword clustering highlights major research themes, including mental health, built environment, aging in place, and urban planning. Despite increasing recognition of the importance of green spaces for older adults, gaps remain in equitable access, longitudinal studies, and intervention-based research.

Conclusion: The findings emphasize the need for policy-driven urban planning that not only prioritizes green space accessibility but also addresses equity and supports healthy aging.

Introduction: As people age, they increasingly face physical and cognitive decline, which can negatively affect their subjective health experience. To improve subjective health experience among older adults, it is crucial to understand its key predictors. Current literature points to frailty and vitality from geriatric research as well as acceptance and control from psychological science as key predictors. However, until now, they have never been incorporated in one composite model. Therefore, this study aims to develop, validate and differentiate a composite model integrating these predictors.

Methods: An online questionnaire covering sample characteristics and instruments on frailty, vitality, acceptance, control and subjective health experience was distributed among a sample of 753 older adults recruited from a research panel. Data were analysed using descriptive, reliability, validity and model statistics.

Results: Frailty shows modest to moderate negative relationships with acceptance, control and subjective health experience and a stronger negative relationship with vitality. Vitality relates moderately positively to control and subjective health experience and modestly to acceptance. Control has a strong positive relationship with acceptance and a modest one with subjective health experience. Acceptance shows a moderate positive relationship with subjective health experience. Frailty has a moderate significant negative indirect relationship with subjective health experience, through several modest but significant pathways involving vitality, acceptance and control combined or alone. Pathways with control alone are modest and nonsignificant. The models explain 41.5%-52.6% of the variance in subjective health experience.

Conclusion: It might be worthwhile to consider deploying the key concepts of the model, such as frailty, vitality, acceptance or control, as starting points for the development of future interventions concerning the subjective health experience of older adults. Such interventions may target frailty and promote vitality through tailored support, while aligning delivery with older adults' needs for control and acceptance.

Background: Thailand has aged fast, becoming a superaging society. Simultaneously, ongoing rapid digital transformation puts older people at risk of being left behind. Research assessing the digital skills of older people and their application of digital technology for health is a literature gap.

Method: This study is an explanatory-sequential design mixed-method study. Community survey of 500 community older adults in Northern Thailand applied London School of Economics and Political Science (LSE) digital skills instrument to measure "operational internet skills," "information navigation skills," "social skills," "creative skills," and "mobile skills" and perceived health and technology use for health promotion. Quantitatively, Kruskal-Wallis and Mann-Whitney U tests identified differences in the digital skills across sociodemographic and internet use characteristics, while multivariable ordinal logistic regressions analyzed types of digital skills associated with health outcomes. Qualitatively, thematic analyses explained the quantitative findings in detail.

Results: The mean age of the participants was 68.36 years, of which 69% were female. Ordinal logistic regression identified that higher "social skills" positively influenced self-rated health (β = 0.32, 95% CI = 0.11-0.52), while 'Information navigation skills' affected internet use to access healthcare (β = 0.20, 95% CI = 0.04-0.36). Older adults with higher levels of 'operational skills' and 'social skills' positively associated with application of technology for health promotion in terms of improving eating habits ('operational skills', β = 0.54, 95% CI = 0.28-0.79; 'social skills', β = 0.64, 95% CI = 0.45-0.83); accessing healthcare ('operational skills,' β = 0.49, 95% CI = 0.23-0.75 'social skills' β = 0.74, 95% CI = 0.55-0.93) and accessing long-term care services ('operational internet skills,' β = 0.47, 95% CI = 0.21-0.73; 'social skills' β = 0.66, 95% CI = 0.47-0.85). Multiple focus-group interviews of older persons revealed how smart phone apps enabled them to stay connected, seek care and help others.

Conclusion: Therefore, it is urgent to enhance digital skills and internet use among older populations to promote healthy aging.