Middle-aged Adults Research Articles

Remnant cholesterol and cognitive function: Evidence from the China health and retirement longitudinal study.

Evidence on associations of remnant cholesterol (RC) and its variability with cognitive function is still lacking. To explore the association of RC and its variability with cognitive function. Participants were recruited from a population-based cohort, the China Health and Retirement Longitudinal Study (CHARLS). Cognitive function was assessed by a standardized questionnaire from CHARLS, with domains of episodic memory and mental intactness. A linear mixed effects model was used to analyze the association of RC with cognitive function, along with its variability (calculated as standard deviation [SD], coefficient of variation [CV], variability independent of the mean [VIM]), with results expressed as β (95%CI). Potential subgroup differences in the association of RC and its variability with cognitive function were also explored. 4234 participants were eventually included, with mean (SD) age of 57.4 (8.0) years. Each 10 mg/dL increase in RC was associated with 0.053 (95%CI: 0.096, 0.009) points, 0.021 (95%CI: 0.042, 0.000) points, 0.032 (95%CI: 0.064, 0.001) points decrease in global cognitive function, episodic memory, and mental intactness scores, respectively. Compared with the first tertile (T1) group of RC variability (calculated as SD, VIM), T3 showed a lower level in global cognition and episodic memory after multivariate adjustment. The potential modification effects of educational level on RC and its variability in relation to cognitive function were also identified. Among Chinese middle-aged and older adults, higher RC level were associated with worse cognitive function. Greater RC variability was also associated with worse cognitive performance, especially in memory function.

The association between sleep duration trajectories and successful aging: a population-based cohort study

BackgroundInsufficient or excessive sleep duration are associated with increased risk of individual adverse outcomes. However, it remains largely unknown whether sleep duration trajectories are associated with overall health among older adults. This study aimed to examine the association between sleep duration trajectories and successful aging.MethodsIn the China Health and Retirement Longitudinal Study (CHARLS), 3,306 participants without major chronic diseases at baseline and survived to aged 60 years and older at the end of follow-up were potentially eligible participants. Total sleep duration was assessed in 2011, 2013, and 2015, and successful aging was evaluated in 2020 and was defined as being free of major chronic diseases, no physical impairment, high cognitive function, good mental health, and active engagement with life. Latent class mixed model (LCMM) was used to identify sleep duration trajectories and logistic regression was performed to explore the association between these trajectories and successful aging.ResultsDuring the 9-year follow-up, 455 individuals (13.8%) met the criteria for successful aging. Five sleep duration trajectories were identified: normal stable, long stable, decreasing, increasing, and short stable. Compared with the normal stable trajectory, the adjusted ORs (95% CI) for achieving successful aging for participants with long stable, decreasing, increasing, and short stable trajectories were 1.00 (0.77, 1.30), 0.64 (0.40, 1.03), 0.64 (0.45, 0.92), and 0.48 (0.35, 0.66), respectively. The stratified and sensitivity analyses were generally consistent with the main results.ConclusionsIncreasing and short stable trajectories of sleep duration are associated with lower odds of successful aging relative to participants in the normal stable trajectory. The findings underscore the critical importance of monitoring dynamic changes in sleep duration in middle-aged and older Chinese adults.

REAL AD-Validation of a realistic screening approach for early Alzheimer's disease.

Early diagnosis is crucial to treatment success. This is especially relevant for Alzheimer's disease (AD), with its protracted preclinical phase. Most health care systems do not have the resources to conduct large-scale AD screenings in middle-aged individuals in need of novel AD treatment options and early, accurate diagnosis. Recent developments in blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods to detect cognitive and biomarker changes that may indicate early AD. In research cohorts, promising results have been reported, but these modalities have not been validated in population-based settings. The validation of a realistic screening approach for early Alzheimer's disease (REAL AD) study aims to validate the diagnostic and prognostic performance of the combined use of blood-based biomarkers and remote cognitive testing as a screening approach for early AD employing an existing health care infrastructure (the Swedish Västra Götaland Region Primary Healthcare). REAL AD aims to provide a concrete, individualized diagnostic framework, which could significantly improve AD prognosis. HIGHLIGHTS: In Sweden, most Alzheimer's disease (AD) diagnoses are made in primary care, where access to AD biomarkers is almost non-existent. Most health care systems have limited resources for the screening of middle-aged adults for early evidence of AD pathology. Blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods for detecting cognitive and biomarker changes that may indicate early AD. The REAL AD study aims to validate the diagnostic and prognostic performance of blood-based biomarkers and remote cognitive testing as a screening approach for early AD in an existing primary health care infrastructure in the Västra Götaland Region in Sweden. Studies such as REAL AD will play a vital role in helping to move the field toward concrete implementation of biomarkers in AD diagnostic workup at all care levels, eventually providing more comprehensive treatments options for the large and growing AD population, and for those at risk.

A Qualitative Study of Type 2 Diabetes Mellitus Outpatients' Perspectives on Readiness, Acceptance and Barriers of Mobile Apps for Medication Adherence

ObjectivesThis qualitative phenomenological study explored the perspectives of type 2 diabetes mellitus (T2DM) outpatients in adopting mobile apps for medication adherence management. MethodsThrough 25 semi-structured in-depth interviews, themes were identified using thematic analysis, guided by the Technology Readiness and Acceptance Model (TRAM). ResultsAnticipated convenience and benefits, openness to new technologies acted as drivers, while limited digital literacy and concerns about data privacy and security served as inhibitors of readiness to adopt health apps. Acceptance was influenced by elements related to medication, patient, healthcare professional, family and app aspects. The identified barriers were related to patient, smartphone and monetary factors. Patients perceived the need to adopt digital apps were for those with poor adherence, complex medication regimen and forgetfulness issues. However, concerns about effectively implementing this approach were noted as T2DM patients were predominantly late middle-aged adults who faced technical challenges, leading to combination approach between digital technology and conventional patient education and counselling. ConclusionThe findings highlighted the factors influencing patient's readiness, acceptance, and barriers on effective utilisation of digital health solutions in managing adherence issues. Practical implicationsThe elements of TRAM provide guidance for strategic actions to enhance digital health technology adoption among T2DM patients.

Creation and Validation of the MMQ-9: A Short Version of the Multifactorial Memory Questionnaire for Middle-Aged and Older Adults

ABSTRACT Objectives Memory concerns are common among older adults. The Multifactorial Memory Questionnaire (MMQ) is a well-validated participant-reported measure consisting of 57 items across three subscales assessing satisfaction with memory, self-perceived memory ability, and memory strategy use, respectively. Because short scales are often desired to accommodate clinical time constraints and reduce respondent burden, we created and evaluated 9-item versions of each subscale (MMQ-9). Methods In Study 1, we used an optimization strategy to identify subsets of items that maximized subscale reliability in a sample of 560 adults ages 50–90. In Study 2, we examined psychometric properties of the MMQ-9 in an independent sample of 638 adults ages 51–95. Results Internal consistency, test–retest reliability, and convergent and discriminant validity of each subscale met published criteria for good measurement properties. Confirmatory factor analysis validated the original factor structure. A hierarchical series of invariance models showed excellent fit, confirming robust measurement invariance across age, gender, and education. Conclusions The shortened MMQ-9 is a reliable, valid, and invariant measure of metamemory in middle-aged and older adults. Clinical Implications The MMQ-9 is a reasonable instrument of choice when brief yet psychometrically strong measures of participant-reported memory are required for clinical assessment of patients with memory concerns.

Erythematous indurated plaques on the palate in a middle-aged adult.

A 45-year-old male presented with a 2-year history of erythematous indurated plaques on the right palate and adjacent palatobuccal mucosa, accompanied by dull pain and loosening of the third molar, necessitating extraction. Radiological imaging revealed soft tissue density with cortical bony erosions in the bilateral upper alveolar ridge. A single sub-centimetric right cervical lymph node was palpable. Biopsy showed an upper dermal infiltrate composed of cells with nuclear grooving and abundant eosinophilic cytoplasm. Through this case, we highlight a rare manifestation of a systemic disease.

Integrated bagging-RF learning model for diabetes diagnosis in middle-aged and elderly population

As the population ages, the increase in the number of middle-aged and older adults with diabetes poses new challenges to the allocation of resources in the healthcare system. Developing accurate diabetes prediction models is a critical public health strategy to improve the efficient use of healthcare resources and ensure timely and effective treatment. In order to improve the identification of diabetes in middle-aged and older patients, a Bagging-RF model is proposed. In the study, two diabetes datasets on Kaggle were first preprocessed, including unique heat coding, outlier removal, and age screening, after which the data were categorized into three age groups, 50–60, 60–70, and 70–80, and balanced using the SMOTE technique. Then, the machine learning classifiers were trained using the Bagging-RF integrated model with eight other machine learning classifiers. Finally, the model’s performance was evaluated by accuracy, F1 score, and other metrics. The results showed that the Bagging-RF model outperformed the other eight machine learning classifiers, exhibiting 97.35%, 95.55%, 95.14% accuracy and 97.35%, 97.35%, 95.14% F1 Score at the Diabetes Prediction Dataset for diabetes prediction for the three age groups of 50–60, 60–70, and 70–80; and 97.03%, 94.90%, 93.70% accuracy and 97.03%, 94.90%, 93.70% F1 Score at the Diabetes Prediction Dataset. 95.55%, 95.13% F1 Score; and 97.03%, 94.90%, 93.70% accuracy; and 97.03%, 94.89%, 93.70% F1 Score at Diabetes Prediction Dataset. In addition, while other integrated learning models, such as ET, RF, Adaboost, and XGB, fail to outperform Bagging-RF, they also show excellent performance.

Burden and causes of anemia in Vietnam: insights from the global burden of disease data

BackgroundAnemia is a significant global health issue, impacting 1.92 billion people and ranking as a leading cause of disability. It is marked by low hemoglobin levels, which hinder oxygen delivery to vital organs and result from causes such as nutritional deficiencies and chronic diseases. Despite some progress, anemia remains a major concern in Southeast Asia, including Vietnam. Although the country has reduced its anemia rates, the progress is insufficient to achieve the WHO’s 2030 targets for anemia reduction among women of reproductive age. This study explores anemia trends and socio-economic determinants in Vietnam, with a focus on age and gender differences, to inform targeted interventions and policy development.MethodsThis study used the Global Burden of Diseases, Injuries, and Risk Factors (GBD) dataset to explore the burden of anemia and its causes in Vietnam from 1990 to 2021. The GBD study provides data on anemia prevalence and years lived with disability (YLD) by age, sex, and 37 causes across 204 countries and territories. Further, this study employed a regression model to examine how the anemia burden (i.e., prevalence rate and YLD rate) relates to socio-economic factors such as the Human Development Index (HDI), gender disparities in human development achievement, and gender-based inequalities in reproductive health, empowerment, and economic status in Vietnam over this period.ResultsIn 1990, there were 16.30 million anemia cases in Vietnam, decreasing slightly to 16.05 million by 2021. Male prevalence dropped from 34.90 to 26.58%, while female prevalence increased from 65.10 to 73.42%. Iron deficiency was the main cause, affecting 68.35% of cases in 1990 and 68.84% in 2021, with 24.96% in males and 75.04% in females in 2021. While anemia has decreased among infants, young children, and adolescents due to improved healthcare, it has increased among middle-aged and older adults, especially females. Regression analysis shows that higher human development and gender equality reduce anemia prevalence and disability, whereas gender inequality worsens the issue.ConclusionsThe study underscores that anemia remains a major health concern in Vietnam, marked by significant gender and age disparities. Despite a decrease in overall anemia rates and the effectiveness of specific interventions like iron-folic acid supplementation, females, particularly those of reproductive age and older adults, continue to face higher rates. Socio-economic improvements, including higher income and better human development, are linked to lower anemia rates, though the impact differs by gender. The persistent gender disparity and the shift in burden to older adults highlight the need for more comprehensive, gender-sensitive interventions. Future efforts should integrate nutritional support with broader socio-economic enhancements to effectively address anemia and improve public health in Vietnam.

The Mediating Effect of Efficacy in Using Digital Devices on the Relationships between Digital Support and Qualitative Use of Digital Information in Middle-aged and Older Adults: Multi-Group Comparison among Age Groups

The Mediating Effect of Efficacy in Using Digital Devices on the Relationships between Digital Support and Qualitative Use of Digital Information in Middle-aged and Older Adults: Multi-Group Comparison among Age Groups

Impact of virtual reality immersion on exercise performance and perceptions in young, middle-aged and older adults.

This study compared the effect of high and low levels of virtual reality (VR) immersion during moderate and high intensity cycling-exercise in younger (18-35 years), middle-aged (36-50 years), and older (51-69 years) adults. Thirty participants (5 female and 5 males per age group) completed moderate (steady state: 15 minutes at 60-75% maximum heart rate (MHR)) and high (sprint: 10 x 30 second sprints at 75-85% MHR) intensity cycling in four conditions: VR using a head-mounted display (High HMD), room-projector (Low Room), screen-projector (Low Screen) and No VR. Exercise performance measures (cadence, distance, power output) were recorded. Following each VR condition, exercise enjoyment (PACES) and exercise engagement (Flow State Scale) were measured. Results showed that exercise intensity had a significant effect of age on; heart rate (steady state and sprint), cadence (sprint) and distance (sprint) (p's <0.05). A significant effect of condition was observed during the sprint exercise for heart rate (p < 0.05). No other significant condition effects were observed for exercise performance. Significant effects of condition were identified for exercise engagement relating to sense of control (p < 0.01) and loss of self-consciousness (p < 0.05) with the highest values occurring in the Low Screen condition for all age groups, while transformation of time was significantly different (p < 0.05) for the middle-aged adults (highest during High VR and Low Screen). These results indicate that irrespective of age, participants found themselves in control and immersed more during the Low Screen VR condition than the other VR and No VR conditions. The findings indicate that VR immersion impacts exercise performance and exercise engagement in different age-groups and therefore should be considered when using VR to promote exercise behaviour.

A Study to Assess the Effectiveness of Video Assisted Teaching Programme on Knowledge Regarding Prevention of Coronary Artery Disease among Students In A Selected Arts College of Durg, Chhattisgarh (State)

Coronary artery disease is an obstructed blood flow through the coronary arteries to the heart muscles. The primary cause of coronary artery disease is atherosclerosis. The term acute coronary syndrome is used to encompass the continuum of coronary artery disease. Coronary artery disease is most prevalent type of cardiovascular disease in adults, more death occurs in middle aged adults. In India, even younger age group are prone to get heart disease due to their health damaging life style. This study was conducted to assess the effectiveness of video assisted teaching programme on knowledge regarding prevention of coronary artery disease among students in a selected arts college of Durg, Chhattisgarh (State) The conceptual framework used in this study was based on J.W.Kenney’s open system model. A quantitative approach was used for the present study. Using purposive sampling technique,60 arts students were selected and video assisted teaching given after pre-test. Followed by that post test was conducted on day 7, the collected data was analyzed using descriptive and inferential statistics. The overall analysis of prevention of coronary artery disease the mean post-test knowledge score of the subjects 28.07 is higher than the mean pre-test knowledge score 18.17. Thecalculated‘t’ value 19.769nis greater than of table value (1.984) at 0.001 level of significance. This indicates that video assited teaching programme was effective in gaining knowledge regarding the prevention of coronary artery disease. The association between socio demographic variables with pre-test knowledge score significance (p&lt;0.001) was tested. Based on the findings indicate that there is a significant difference between pre-test and post-test knowledge score on prevention of coronary artery disease in a selected arts college students at Durg.

Acceleration of Brain Atrophy and Progression From Normal Cognition to Mild Cognitive Impairment

It remains unclear which risk factors accelerate brain atrophy along with a progression from normal cognition to mild cognitive impairment (MCI). To examine risk factors associated with the acceleration of brain atrophy and progression from normal cognition to MCI based on long-term longitudinal data for middle-aged and older adults. Data for this cohort study were extracted from the Biomarkers for Older Controls at Risk for Dementia (BIOCARD) cohort, initiated at the National Institutes of Health from January 1, 1995, to December 31, 2005, and continued at Johns Hopkins University from January 1, 2015, to October 31, 2023. All participants were cognitively normal at baseline. The participants whose structural magnetic brain imaging (MRI) of the brain and cerebrospinal fluid (CSF) measures were available for over 10 years were included. Longitudinal structural MRI of the brain and measurement of CSF biomarkers for Alzheimer disease pathology (ratio of amyloid β peptide 42 [Aβ42] to Aβ40, tau phosphorylated at threonine 181, and total tau). Annual change rates of segmental brain volumes, Kaplan-Meier survival curves plotting time to event for progression to MCI symptom onset, and hazard ratios (HRs) determined by Cox proportional hazards regression models. A total of 185 participants (mean [SD] age, 55.4 [8.4] years; 116 women [63%]) were included and followed up for a maximum of 27 years (median, 20 [IQR, 18-22] years). The groups with high levels of atrophy in the white matter and enlargement in the ventricles had an earlier progression from normal cognition to MCI symptom onset (HR for white matter, 1.86 [95% CI, 1.24-2.49]; P = .001; HR for ventricles, 1.71 [95% CI, 1.19-2.24]; P = .009). Diabetes was associated with progression to MCI (HR, 1.41 [95% CI, 1.06-1.76]; P = .04), as was a low CSF Aβ42:Aβ40 ratio (HR, 1.48 [95% CI, 1.09-1.88]; P = .04), and their combination had a higher HR of 1.55 (95% CI, 1.13-1.98]; P = .03), indicating a synergic association of diabetes and amyloid pathology with MCI progression. In this cohort study of middle-aged and older adults, higher rates of volume change in the white matter and ventricles, along with the presence of diabetes and a low CSF Aβ42:Aβ40 ratio, were identified as important risk factors for the progression to MCI. These results support the importance of identifying individuals who have accelerated brain atrophy to optimize preventive strategies for progression to MCI.

Impact of covid-19 on family dynamics in relation to age: A comparative study

This study examines the differential impact of COVID-19 on family dynamics across two distinct age groups: young adults (20-40 years) and middle-aged adults (41-60 years). The primary aim is to assess how the pandemic affected family interactions and emotional well-being in relation to age. A sample of 100 participants was selected, with 50 individuals from each age group. Data was collected using a validated questionnaire designed to measure the pandemic's impact on family dynamics through a Likert-type scale. Descriptive statistics, including mean and standard deviation, were calculated for each group, followed by a t-test to compare the two age groups. The results indicate a statistically significant difference in the impact on family dynamics, with a t-value of -2.15 and a p-value of 0.034, suggesting that middle-aged adults experienced more significant changes in family dynamics compared to young adults. This study contributes to understanding the age-related psychological and emotional responses to the COVID-19 pandemic and highlights the need for targeted interventions based on age-specific challenges.

Translational horizons in stem cell therapy for osteonecrosis of the femoral head: a journey from basic research to clinical practice through bibliometric insights

BackgroundOsteonecrosis of the femoral head (ONFH) significantly impacts young and middle-aged adults, with steroid use implicated in many cases. Traditional treatments have limited efficacy, prompting a shift towards innovative approaches, such as stem cell therapy, offering less invasive regenerative solutions.MethodsUsing bibliometric analysis from 1997 to 2023, we identified 392 articles on stem cell therapy for ONFH from the Web of Science Core Collection and analysed them using VOSviewer and CiteSpace to identify key trends and research directions.ResultsFrom 1997 to 2023, stem cell therapy for ONFH research expanded significantly, with 392 articles evidencing global collaboration, particularly from China, the United States and South Korea. The field is characterised by 158 core authors across 26 clusters and contributions from 417 institutions in 104 research clusters, with Shanghai Jiao Tong University as a notable leader. This research is disseminated through 23 journal clusters, emphasising interdisciplinary work, with Clinical Orthopaedics and Related Research among the most influential journals. Key findings include the identification of the most influential papers, highlighting advances, such as use of autologous mesenchymal stem cells (MSCs) and innovative delivery mechanisms. High-frequency keyword analysis further mapped the evolution of the field, from basic mechanisms to advanced therapies, underscoring a trend towards more targeted stem cell treatments for ONFH.ConclusionStem cell therapy for ONFH has advanced significantly, showcasing a successful transition from basic research to clinical practice, particularly highlighted by developments in use of autologous MSCs and delivery methods. Future research will focus on refining therapies through exosome technology, targeted modulation of stress and inflammation and integration with surgical techniques, with the aim of tailored patient care and improved ONFH outcomes.

Development and validation of a machine learning-based diagnostic model for Parkinson's disease in community-dwelling populations: Evidence from the China health and retirement longitudinal study (CHARLS)

BackgroundParkinson's disease (PD) is a major neurodegenerative disorder in Middle-aged and elderly people.There is a pressing need for effective predictive models, particularly in chinese population. Objective:This study aims to develop and validate a machine learning-based diagnostic model to identify individuals with PD in community-dwelling populations using data from the China Health and Retirement Longitudinal Study (CHARLS). MethodsWe utilized data from 19,134 individuals aged 45 and above from the CHARLS dataset, with 265 adults reported to have PD. The external validation cohort included 1500 individuals, with 21 (1.4 %) having PD.The random forest (RF) algorithm was used to develop an interpretable PD prediction model, which was internally validated using 10-fold cross-validation and externally validated with a dataset from Northern Jiangsu People's Hospital. SHapley Additive exPlanation (SHAP) values were employed to elucidate the model's predictions. ResultsThe RF model demonstrated robust performance with an Area Under the Curve (AUC) of 0.884 and high sensitivity, specificity, and F1 scores. The model's performance in external validation cohort, highlighting an AUC of 0.82 and an accuracy of 0.99. The model's performance remained consistent across internal and external validation cohorts. SHAP analysis provided insights into the importance and interaction of various predictors, enhancing model interpretability. ConclusionThe study presents a highly accurate and interpretable machine learning-based diagnostic model to identify individuals with PD in middle-aged and older Chinese adults. By combined with predictive risk factors and chronic disease information, the model offers valuable insights for early identification and intervention, potentially mitigating PD progression.

Cumulative Socioeconomic Status Risk is Associated with Greater Increase in Serum Neurofilament Light Chain Levels Among Middle-Aged Black Adults.

This study examined the longitudinal relationship between cumulative socioeconomic status (SES) risk and serum neurofilament light chain (NfL) levels to better understand the association between social factors and a biomarker of neurodegeneration. We used data from the Family and Community Health Study (FACHS), collecting psychosocial and blood data at two waves (2008) and (2019) from 254 Black Americans (43 males and 211 females). Blood samples were analyzed at each wave for serum NfL concentrations. Regression analysis and mixed-effect modeling examined relationships between cumulative SES risk and serum NfL, controlling for covariates and assessing time effects. Utilizing 11-year longitudinal data, serum NfL levels increased with age. Higher cumulative SES risk at baseline correlated with elevated serum NfL at the 11-year follow-up and predicted a greater increase in NfL levels. Clinically, NfL is a sensitive biomarker for axonal injury and neurodegeneration, commonly used to detect early and preclinical stages of conditions such as Alzheimer's disease (AD), multiple sclerosis, and other neurodegenerative disorders. Our results suggest that exposure to cumulative SES risk among Black adults may contribute to elevated levels of NfL, indicating potential early neurodegeneration. Given the established role of NfL in detecting neurodegenerative processes, these findings underscore the importance of interventions that bolster social safety nets and social connectedness to enhance brain health and mitigate neurodegenerative risks.

Did internet usage reduce the impact of COVID-19 on the mental health of middle-aged and older adults? A difference-in-differences study based on CFPS data.

Mental health is the cornerstone of public health, especially where middle-aged and older adults during the COVID-19 pandemic were concerned. The impact of Internet usage on mental health in the time of the crisis still presents a mixed picture. This study employs the PSM-DID method according to longitudinal data (CFPS) to explore whether Internet usage reduced the impact of COVID-19 on the mental health of middle-aged and older adults. The results reveal that Internet use improves the mental health of middle-aged and older adults during the pandemic in China, but that the impact varies between urban and rural residents. Furthermore, the moderator effects model shows that people's perceptions of the Internet have an impact upon the length of time spent online and its consequent effect on mental health. These findings suggested that Internet use had a significant effect on alleviating the levels of depression in middle-aged and older adults. Greater marginal gains may be realized by enhancing the digital capacity of and narrowing the digital divide that exists among rural residents. The enhancement of digital capacity and proper guidance in digital education should be taken into consideration where the mental health of middle-aged and older adults is at issue.

Late-life psychiatric factors and life satisfaction are associated with cognitive errors: evidence from an experimental module of a large-scale survey in India

Older adults are at risk of committing cognitive and decision-making errors due to the decline in cognitive functions. However, the understanding of the determining factors of cognitive errors among ageing adults is limited. In this study, we explored the role of various psychiatric factors, life satisfaction, and other socioeconomic, health and behavioural risk factors of committing cognitive errors among middle-aged and older adults in India. The study utilized the data from the experimental module of the Longitudinal Ageing Study in India (LASI) Wave-1 (2017–2018) with a sample of 12,754 adults aged 45 years and above. The cognitive error was measured using logical fallacies committed in the activity-based experiments. The study employed descriptive, bivariate statistics and multivariable logistic regression models to identify the factors associated with cognitive errors among the study participants. Depression (aOR = 1.28, 99%, CI: 1.16–1.41), life satisfaction (aOR = 0.99, 99%, CI: 0.98–1.00), and cognitive impairment (aOR = 1.13, 90% CI: 1.00–1.30) self-reported psychiatric) were significantly associated with higher odds of committing cognitive errors among the middle-aged and older adults. Also, ageing adults with low educational levels, functional limitations, sleep disturbances, smoking history, living in rural areas and belonging to scheduled tribes had a higher probability of committing cognitive errors. However, involvement in physical activity, reading habits and social interactions reduced the odds of cognitive errors among this sample. Mental health and well-being indicators, including depression, life satisfaction, cognitive impairment, and other health and behavioural health factors, determine cognitive errors among ageing adults. Programs and policies should be initiated to address these factors, reduce cognitive errors, and ensure active ageing.

Sleep Health Patterns in Romania: Insights from a Nationwide Cross-Sectional Online Survey

Background: Sleep is one of the most essential processes for sustaining cognitive, emotional, and physical health across all age groups. Insomnia or inadequate sleep significantly impacts health and poses economic burdens due to increased healthcare costs and reduced productivity. Objectives and Methods: This study aimed to investigate sleep quality in the Romanian active population using an online survey incorporating the Pittsburgh Sleep Quality Index (PSQI). Conducted over four months in 2023, the survey gathered 2243 complete responses from urban and rural residents over the age of 18. Results: The results highlight gender and urban–rural disparities in sleep quality, revealing that females and urban residents experienced poorer sleep compared to their counterparts. Additionally, sleep quality was found to significantly worsen with age, with elders (56+ years) reporting the highest PSQI scores, indicating greater sleep difficulties compared to middle-aged adults and youngsters. A high prevalence of sleep disturbances, daytime dysfunctions, and sleep medication use was reported. Common pre-sleep activities included using electronic devices and watching TV, while fewer participants engaged in reading books or consuming alcohol and caffeine. Additionally, participants’ bedding preferences were documented. Conclusions: Our study highlights the influence of various factors on sleep quality and emphasizes the need for targeted public health interventions to improve sleep health in Romania.

Factors Influencing Suicidal Ideation in Young and Middle-aged Adults in Korea: A Nationwide Study

Abstract Objectives This study aims to analyze various factors influencing suicidal ideation among young (19-39 years) and middle-aged (40-64 years) adults using nationwide longitudinal data in South Korea, which has the highest suicide rate among OECD countries for more than 20 years. Methods An analysis was conducted using the WAVE II data (2016-2017) from a nationwide longitudinal study on the mental health of suicide survivors (LoSS). The sample included 2,002 participants (1,290 young adults, 712 middle-aged adults) recruited through stratified proportional quota sampling. Multiple regression analysis was performed to identify factors influencing suicidal ideation in each age group. Results In young adults, being female, having a high school education or lower, being unmarried/divorced/widowed, and having higher levels of depression were positively associated with suicidal ideation. Higher levels of social support and better subjective physical health were negatively associated with suicidal ideation. In middle-aged adults, being unemployed, living alone, drinking alcohol more than once a week, and having higher levels of depression were positively associated with suicidal ideation, while higher levels of social support were negatively associated with suicidal ideation. Conclusions Factors influencing suicidal ideation differ between young and middle-aged adults. Age-specific suicide prevention strategies considering these factors are needed to promote social health and stability in South Korea. Key messages • Different factors influence suicidal ideation in young and middle-aged adults in South Korea. • Age-specific suicide prevention strategies are necessary to effectively address suicidal ideation and promote social health and stability in South Korea.