Large household reduces dementia mortality: A cross-sectional data analysis of 183 populations

Social isolation and mental well-being among Korean older adults: a focus on living arrangements

Introduction

The aging population in South Korea, characterized by an increasing number of older adults living alone, has raised concerns about its implications on mental health, specifically social isolation and loneliness that accompanies solitary living arrangements. This study explores the impact of living arrangements on the mental well-being of Korean older adults by focusing on the prevalence of depression and the role of social isolation in the context of evolving family structures and the COVID-19 pandemic.

Methods

This cross-sectional study analyzed the responses of older adults aged 65 years and above (mean: 73.1, SD: 5.1) by using data from the Korea National Health and Nutrition Examination Survey conducted in 2018 and 2020. In total, responses from 3,365 older adults (1,653 in 2018 and 1,712 in 2020) were employed in this research. The participants' mental health status was assessed using the Patient Health Questionnaire-9, with living arrangements categorized by household size. A zero-inflated Poisson regression analysis was employed to investigate the relationship between living arrangements and depression severity, controlling for demographic, socioeconomic, and psychological factors.

Results

The study found that older adults living with others exhibited a lower depression severity than those living alone. Notably, the severity of depression decreased as the number of household members increased up to a certain threshold. Socio-economic factors, such as income level, marital status, and psychological stress were also identified as significant predictors of depression severity. However, the COVID-19 pandemic did not have a statistically significant impact on depression rates among older adults during the study period.

Conclusion

Living arrangements play a critical role in the mental health of Korean older adults, with solitary living being associated with higher levels of depression. These findings underscore the importance of social support systems and suggest the need for policies and interventions that promote social connectivity and address the challenges of loneliness faced by them. Future research should explore longitudinal and qualitative studies to further understand causal relationships and develop targeted interventions to improve the mental well-being of the aging population.

Smaller household size and higher prevalence of serious psychological distress in younger people and never-married people: a nationwide cross-sectional survey in Japan

Background

Small-member households are increasing worldwide. However, most previous studies have focused on older people and living alone. Using the latest national survey data, we investigated a dose-response relationship between household size and serious psychological distress (SPD).

Methods

We analyzed data from the 2019 Comprehensive Survey of Living Conditions in Japan. The study participants were 405,560 community-dwelling adults aged 20 or older. Household size was classified into 5 or more, 3 or 4, two, and one (i.e., living alone). SPD was defined as ≥13 points based on the Kessler 6-item Psychological Distress Scale. We used multivariable logistic regressions and included age, education, equivalent household expenditures, housing tenure, employment contract, smoking, and illness under treatment as covariates.

Results

After stratified analyses by age and gender, a dose-response relationship between smaller household size and more common SPD was significant for younger, but not for older people (p-trend was <0.001 in men aged 20-59 and women aged 20-39). After stratified analyses by gender and marital status, a dose-response relationship was significant only for the never-married group in both genders (p-trend was <0.001 in never-married men and women).

Conclusion

Smaller households were associated with higher prevalence of SPD in younger adults and in never-married individuals, regardless of gender. Our findings suggest a need to focus on younger people and never-married people to reduce the mental health risks due to small household sizes.

Nursing workforce plays a significant role in reducing COVID-19 deaths worldwide: A cross-sectional analysis of data from 178 countries

Worldwide, the role of nursing workforce in reducing COVID-19 case fatality ratio (CFR) is analyzed with scatter plots, Pearson's r and nonparametric, partial correlation and multiple linear regression models. The potential confounders, median age, health expenditure, physician density, and urbanization were incorporated for calculating the independent role of nursing workforce in protecting against COVID-19 CFR. The study findings suggested that (1) the nursing workforce inversely and significantly correlates with COVID-19 CFR; (2) this relationship remained independent of the confounding effects of each individual confounder or their combination; (3) Nursing workforce was the only variable identified as a significant contributor for reducing COVID-19 CFR, when it was incorporated into stepwise regression model with health expenditure, median age, physician density, and urbanization for analyzing their individual predicting effects on COVID-19 CFR. A strong message for the health authorities is that, although in shortage, nursing workforce showed their significant role in reducing COVID-19 deaths worldwide. This study highlights that the role of nursing workforce should be incorporated into population health research.

A global comparison of nursing and midwifery's and medical efficacy in preventing COVID-19 deaths 2019-2022

AIM

Compare roles of nurses and midwives and physicians in reducing COVID-19 deaths measured with a case fatality ratio.

BACKGROUND

The roles and responsibilities of different health disciplines to the COVID-19 pandemic vary. While more difficult to measure, objective assessments of discipline contributions of nurses and midwives and physicians can be viewed through statistical analysis.

METHODS

Population-level data are analysed with scatter plots, bivariate correlations, partial correlation and multiple linear regression models to illustrate the contributions of nurses and midwives and physicians in reducing COVID-19 deaths. The role of nurses and midwives and physicians in protecting the community against COVID-19 deaths is explored and compared using competing effects of affluence, age and urbanization. Data analysis software programs include Excel v.2016, SPSS v.28 and Fisher r-to-z transformation.

RESULTS

Nurses and midwives reduce COVID-19 deaths significantly more than physicians. This difference remains while controlling for physician care, economic affluence, median age and urbanization individually or in combination. In contrast, the role of physicians in reducing COVID-19 deaths is less independent than nurses and midwives. Linear regression results insinuate when nursing and physician care are collated together with other predicting factors, physicians' contribution to community protection against COVID-19 case fatality ratio is statistically explained by nursing and midwifery care.

DISCUSSION

Unlike physicians, the nursing and midwifery workforce is bigger and located throughout all healthcare system levels and, therefore, is more accessible to the community. This is an important point in explaining the contribution of nurses and midwives to reducing COVID-19 deaths when compared with physicians.

CONCLUSION

This study suggests that, worldwide, the nursing and midwifery workforce may play a more significant role in protecting the community against COVID-19 deaths than physicians.

IMPLICATIONS FOR HEALTH POLICY, NURSING AND MIDWIFERY PRACTICE

The findings from this study offer a unique perspective for health authorities to further understand the complementary and independent role of the nursing and midwifery workforce in respect of the healthcare team. This study suggests the importance of a broader range of healthcare services, especially during the pandemic, for example, COVID-19. With the permission of health authorities, the nursing and midwifery workforce should have further extension of their scope of practice in situations such as pandemics due to their broader access to the community.

The Role of Oxytocin in Alzheimer's Disease and Its Relationship with Social Interaction

Alzheimer's disease (AD)-the most common cause of dementia in the elderly-is characterized by progressive memory loss and β-amyloid protein (Aβ) accumulation in the brain. Recently, loneliness was found to be a high risk factor for AD, and social isolation has become a major cause of AD. AD. Oxytocin (OXT), the main hormone involved in social bonding, has been implicated in social interactions, notably in building trust and relationships. Moreover, social isolation or social enrichment modulates the activation of neurons related to OXT. Recently, we reported that OXT reverses learning and memory impairment in AD animal models. Based on the limited number of studies currently available, OXT might be a therapeutic target for AD. Further studies are necessary in order to better understand the role of oxytocin in AD. In this review, we described the relationships between OXT, AD, and social interaction.

Greater nurse density correlates to higher level of population ageing globally, but is more prominent in developed countries

BACKGROUND

Representing over 50% of the healthcare workforce, nurses provide care to people at all ages. This study advances, at a population level, that high levels of nursing services, measured by nurse density may significantly promote population ageing measured by the percentage of a population over 65 years of age (65yo%).

METHODS

Population level data was examined to explore the correlation between nurse density and 65yo%. The confounding impacts on ageing such as the effects of economic affluence, physician density, fertility rate, obesity and urban advantages were also considered. Scatter plots, bivariate correlation, partial correlation and multiple linear regression analyses were performed for examining the correlations.

RESULTS

Nurse density correlated to 65yo%; this relationship was independent of other influences such as fertility rate, economic affluence, obesity prevalence, physician density and urban advantages. Second to fertility rate, nursing density had the greatest influence on 65yo%. The predicting and confounding variables explain 74.4% of the total 65yo% variance. The universal correlations identified in country groupings suggest that low nurse density may be a significant global concern.

CONCLUSIONS

While nurse density might contribute significantly to 65yo% globally, the effect was more prominent in developed countries. Ironically, countries with higher nurse densities and therefore greater levels of 65yo%, were countries with an increased need for more nursing staff. To highlight the profound implications for the role the nursing profession plays especially at a time of global nursing shortage, further study into the effects of long-run elasticity of nurse staffing level on population ageing may be needed. For instance, what percentage of nursing staff increase would be required to meet every 1% increase of an ageing population.

Total meat (flesh) supply may be a significant risk factor for cardiovascular diseases worldwide

Consumption of red meat instead of white meat has typically been associated with cardiovascular diseases (CVDs). Reflecting actual diet patterns, this study explored the role of total meat (red + white) in predicting CVD incidence. Data from 217 countries were extracted from United Nations agencies for the analyses in five steps. Bivariate correlations were applied to examine the relationship between total meat and CVD incidence globally and regionally. Partial correlation was applied to identify that total meat was an independent predictor of CVD incidence while socioeconomic status, obesity, and urbanization were statistically constant. Stepwise linear regression was conducted for selecting the significant predictor of CVD incidence. SPSS 28 and Microsoft Excel were used for correlation analyses. Globally, total meat correlated to CVD incidence strongly and significantly in bivariate correlation models. This relationship remained significant in partial correlation when socioeconomic status, obesity, and urbanization were statistically kept constant. Stepwise multiple regression identified that, second to socioeconomic status, total meat was a significant predictor of CVD incidence. Total meat correlated to CVD incidence in different country groupings. However, the correlations between total meat and CVD incidence were significantly stronger in developing countries than in developed countries. Worldwide, total meat (flesh) consumption correlated to CVD incidence independently, but significantly stronger in developing countries than in developed countries. This correlation is worth exploring further in longitudinal cohort studies.

Biomarkers and Risk Assessment of Alzheimer's Disease in Low- and Middle-Income Countries

Dementia is a chronic syndrome which is common among the elderly and is associated with significant morbidity and mortality for patients and their caregivers. Alzheimer's disease (AD), the most common form of clinical dementia, is biologically characterized by the deposition of amyloid-β plaques and neurofibrillary tangles in the brain. The onset of AD begins decades before manifestation of symptoms and clinical diagnosis, underlining the need to shift from clinical diagnosis of AD to a more objective diagnosis using biomarkers. Having performed a literature search of original articles and reviews on PubMed and Google Scholar, we present this review detailing the existing biomarkers and risk assessment tools for AD. The prevalence of dementia in low- and middle-income countries (LMICs) is predicted to increase over the next couple of years. Thus, we aimed to identify potential biomarkers that may be appropriate for use in LMICs, considering the following factors: sensitivity, specificity, invasiveness, and affordability of the biomarkers. We also explored risk assessment tools and the potential use of artificial intelligence/machine learning solutions for diagnosing, assessing risks, and monitoring the progression of AD in low-resource settings. Routine use of AD biomarkers has yet to gain sufficient ground in clinical settings. Therefore, clinical diagnosis of AD will remain the mainstay in LMICs for the foreseeable future. Efforts should be made towards the development of low-cost, easily administered risk assessment tools to identify individuals who are at risk of AD in the population. We recommend that stakeholders invest in education, research and development targeted towards effective risk assessment and management.

Progress in Dementia Care

Effective drug therapy remains elusive but new approaches to care show promise.

Healthcare services relaxing natural selection may contribute to increase of dementia incidence

Ageing and genetic traits can only explain the increasing dementia incidence partially. Advanced healthcare services allow dementia patients to survive natural selection and pass their genes onto the next generation. Country-specific estimates of dementia incidence rates (all ages and 15-49 years old), Biological State Index expressing reduced natural selection (I_s), ageing indexed by life expectancy e₍₆₅₎, GDP PPP and urbanization were obtained for analysing the global and regional correlations between reduced natural selection and dementia incidence with SPSS v. 27. Worldwide, I_s significantly, but inversely, correlates with dementia incidence rates for both all ages and 15-49 years old in bivariate correlations. These relationships remain inversely correlated regardless of the competing contributing effects from ageing, GDP and urbanization in partial correlation model. Results of multiple linear regression (enter) have shown that I_s is the significant predictor of dementia incidence among all ages and 15-49 years old. Subsequently, I_s was selected as the variable having the greatest influence on dementia incidence in stepwise multiple linear regression. The I_s correlated with dementia incidence more strongly in developed population groupings. Worldwide, reduced natural selection may be yet another significant contributor to dementia incidence with special regard to developed populations.