To identify risk and protective factors associated with anxiety and depression symptoms in older adult women, considering clinical, functional, and electrophysiological parameters.
This cross-sectional observational study involved 91 women aged 65 or older. Assessments included EEG-derived valence and excitation levels, motor reaction time, body composition, and functional performance. Anxiety and depression were screened using the mind over mood anxiety inventory and the geriatric depression scale, respectively.
Anxiety symptoms were present in 28.6% of participants and depressive symptoms in 27.5%. Risk factors for anxiety included fear of falling (OR = 2.023, 95% CI = 1.554–2.944, p = 0.007), presence of depressive symptoms (OR = 2.254, 95% CI = 1.983–3.085, p = 0.008), and body fat percentage (OR = 1.543, 95% CI = 1.253–3.111, p = 0.011). Protective factors included valence (OR = 0.311, 95% CI = 0.272–0.544, p = 0.003), gait speed (OR = 0.674, 95% CI = 0.482–0.782, p = 0.023), and maximal expiratory pressure (OR = 0.755, 95% CI = 0.693–0.823, p = 0.027). For depressive symptoms, risk factors included fear of falling (OR = 1.983, 95% CI = 1.865–3.801, p = 0.023) and anxiety symptoms (OR = 1.765, 95% CI = 1.563–1.983, p = 0.008), while protective factors were cortical excitation (OR = 0.523, 95% CI = 0.425–0.693, p = 0.023) and expiratory pressure (OR = 0.635, 95% CI = 0.491–0.723, p = 0.021).
Functional and emotional parameters, particularly valence and gait performance, suggest a potential protective role against anxiety and depression in aging women. The findings reinforce the importance of integrated assessments to support early detection and guide intervention planning, while further studies are recommended to strengthen these observations.
Artificial Intelligence (AI) has emerged as a transformative tool in medication management, particularly for older adults who are vulnerable to adverse drug events, polypharmacy, and medication non-adherence. This narrative review explores the utilization of AI-driven interventions in low and middle-income countries (LMICs) to enhance medication safety, adherence, and prescribing practices. The review synthesizes existing studies on AI applications, including automated drug interaction detection, machine learning models for adverse event prediction, and AI-supported decision-making tools for healthcare professionals. Findings suggest that AI has demonstrated significant potential in reducing inappropriate medication use and improving patient adherence through mobile applications and electronic health record (EHR) integration. However, AI adoption in LMICs remains limited despite its benefits due to high implementation costs, insufficient digital infrastructure, low AI literacy among healthcare providers, and ethical concerns related to data privacy and algorithm bias. Addressing these barriers requires strategic policy reforms, investment in AI education, and improved regulatory frameworks to ensure responsible and equitable AI deployment. Future research should focus on evaluating the long-term effectiveness of AI interventions in real-world settings and developing scalable solutions tailored to LMICs. With the right support, AI has the potential to revolutionize medication management, improving the quality of care and health outcomes for older adults globally.
This study aimed to investigate the role of the body mass index (BMI) as a mediator between gout and hypertension in older adults.
A total of 33,778 older adults (aged 65 years and over) in Wuhan, China, were surveyed. The propensity score matching (PSM) method was used to control for confounding factors, and logistic regression was performed on the above three variables using the mediation package in the R language program.
The PSM method successfully matched 14,717 pairs. Mediation analysis revealed that, when controlling for the mediating variable “BMI”, the association coefficients of the independent variable “gout” on the dependent variable “hypertension” and of the mediating variable were statistically significant. This indicates the existence of a mediating association. Bootstrapping was used to quantify the stability of the observed indirect association, but temporal precedence or causality could not be established in this cross-sectional study.
Gout is associated with hypertension, both directly and indirectly through BMI-related pathways. Therefore, monitoring and controlling the BMI of elderly gout patients to improve the progression of hypertension is of great significance.
With an aging population, more elderly individuals are facing the decision to undergo complex surgeries, such as pancreaticoduodenectomy (PD). This study evaluates the safety and feasibility of PD in patients aged 80 and above.
We conducted a retrospective analysis of 422 patients who underwent PD between August 2011 and January 2024. The patients were categorized into three age groups: < 60 years, 60–79 years, and ≥ 80 years. We adjusted for baseline characteristics using inverse probability of treatment weighting (IPTW) and compared postoperative complications, hospital stay durations, 90-day mortality, and long-term survival across the groups. A subgroup analysis identified factors associated with complications and 90-day mortality.
After IPTW adjustment, no significant differences in complications or long-term survival were observed between the groups. However, the ≥ 80-year group had a significantly higher 90-day mortality rate (13.64%) compared to the 60–79 years group (2.00%) and the < 60 years group (1.46%) (p = 0.002). Subgroup analysis identified hypertension, coronary artery disease (CAD), and nutritional risk (NRS ≥ 3) as independent risk factors for complications, while age ≥ 80 and CAD were associated with higher 90-day mortality.
Age does not significantly impact postoperative complications or long-term survival following PD. While PD is safe and feasible for the elderly, those with cardiovascular comorbidities or poor nutritional status face higher risks of complications and mortality. A comprehensive preoperative assessment is critical to minimizing these risks.
As we approach the mid-21st century, more developing countries are progressing towards becoming developed nations. Advances in medical technology have resulted in the prolonged human lifespan and a sustained decline in birth rates, leading to a growing proportion of the population being aged 65 and above. The aging process is associated with organ function deterioration, increased risks of age-related diseases, and a decrease in the quality of life for older adults. While there is ongoing debate about whether aging should be considered a disease or a natural physiological process, understanding the reasons for aging, identifying and measuring aging, and intervening in the aging process have become key topics in current medical research. Recent studies indicate that the rate of organ aging varies among individuals, with blood vessels being one of the organs that age first. Vascular aging increases the risk of cardiovascular diseases, overall mortality, and shortens lifespan. Therefore, in-depth research on vascular aging is crucial for understanding its impact on vascular and multi-organ function. In this review, we discuss the phenotypes caused by vascular aging, mechanisms of aging in various vascular cells, and potential therapeutic strategies for vascular aging.
The burden of diabetes in the elderly is becoming increasingly severe due to the aging population. Elderly patients with diabetes face unique challenges due to multiple comorbidities, atypical symptoms, an increased risk of hypoglycemia, and limited self-management capabilities. The Guidelines for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition) advocate for a stratified, individualized approach that addresses the heterogeneous pathophysiologic profiles of these patients. Recent technological advances, including continuous glucose monitoring, smart insulin pens, needle-free injection systems, and new insulin pumps, have significantly improved glycemic management. The updated guidelines systematically review evidence-based recommendations for managing diabetes in the elderly, emphasizing the benefits of modern monitoring and insulin delivery technologies. This article interprets the updated guidelines with a focus on the technical principles, clinical benefits, and application dilemmas to ultimately improve long-term outcomes among elderly patients with diabetes.
We aimed to examine the dose–response associations of grip strength and gait speed with multidimensional mental health among Chinese adults.
Cross-sectional data on 661 adults from the ZheJiang longitudinal Study of Healthy Aging (JASHA) were utilized. Grip strength and gait speed were measured during physical examinations. Multidimensional mental health, covering cognitive function (the Auditory Verbal Learning Test (AVLT), the Montreal Cognitive Assessment (MoCA) test, and the Digit Symbol Substitution Test (DSST)), depressive symptoms (the Center for Epidemiologic Studies Depression (CES-D) Scale), and psychological distress (the Perceived Stress Scale (PSS)), were assessed via standard questionnaires. Multivariable linear regression models and restricted cubic splines were applied to examine these associations.
We found linear dose–response associations of grip strength and gait speed with most dimensions of mental health. For instance, higher grip strength was positively associated with higher cognitive function scores (AVLT_N3: β = 0.084, standard error (SE) = 0.032; DSST: β = 0.246, SE = 0.073 for per unit increase in grip strength) and lower CES-D scores (β = −1.265, SE = 0.626). Similarly, higher gait speed was associated with higher cognitive function scores (AVLT_N3: β = 2.882, SE = 0.860; MoCA: β = 0.996, SE = 0.499 for per unit increase in gait speed), lower CES-D scores (β = −1.448, SE = 0.692), and lower PSS scores (β = −2.808, SE = 0.938). Notably, the associations were more pronounced in females and older adults.
In this sample spanning a wide range of ages, we found linear significant associations of grip strength and gait speed with most dimensions of mental health. The finding unveils the intrinsic connections between musculoskeletal function and mental health, highlighting the potential of preserving musculoskeletal function, such as via maintaining regular physical exercise, to prevent mental health disorders, especially for females and older adults.
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