Exploring Subjective Mental Health Change in Older Adults after Experiencing an Immersive Virtual Reality (IVR) -Based Natural Environment.

The study explored subjective mental health change in adults aged 60 to 100 by experiencing immersive virtual reality (IVR)-based on the natural environment. It investigated changes in thinking, behaviour, and emotions from a socioecological perspective. The study conducted quantitative surveys of 540 older adults via IVR who lived in 20 longevity villages in South Korea from Dec. 2022 to Nov. 2023. It also paralleled a qualitative study with 38 of the 540. Study results predicting subjective mental health changes after experiencing IVR in those over 70 showed the highest gladness and happiness. In over 70 compared with 60 to 69 ages, the study found that relieving stress and depression, gladness and happiness, and relaxing the mind have about two-fold subjective mental health changes after experiencing IVR. The study suggests that it can be utilized to promote subjective mental health through the experience of an IVR-based natural environment for older adults.

Evaluation of health factors on artificial intelligence and the internet of things-based older adults healthcare programmes.

Objective: This study evaluates Artificial intelligence and the Internet of Things-based older adults' healthcare programmes (AI·IoT-OAHPs), which offer non-face-to-face and face-to-face health management to older adults for health promotion. Methods: The study involved 146 participants, adults over 60 who had registered in AI·IoT-OAHPs. This study assessed the health factors as the outcome of pre- and post-health screening and health management through AI·IoT-OAHPs for six months. Results: Preand post-health screening and management through AI·IoT-OAHPs were evaluated as significant outcomes in 14 health factors. Notably, the benefits of post-cognitive function showed a twofold increase in older female adults through AI·IoT-OAHPs. Adults over 70 showed a fourfold increase in post-walking days, a threefold in post-dietary practice, and a twofold in post-cognitive function in the post-effects compared with pre via AI·IoT-OAHPs. Conclusions: AI·IoT-OAHPs seem to be an effective program in the realm of face-to-face and non-face-to-face AI·IoT-based older adults' healthcare initiatives in the era of COVID-19. Consequently, the study suggests that AI·IoT-OAHPs contribute to the upgrade in health promotion of older adults. In future studies, the effectiveness of AI·IoT-OAHPs can be evaluated as a continuous project every year in the short term and every two years in the long term.

Effects of air pollution on children from a socioecological perspective.

BACKGROUND: Country-level inequality in life expectancy (ILE) and deaths of children under age five due to air pollution (DCAP) can be influenced by country-level income per capita, solid fuel, electrification, and natural resource depletion. The ILE and DCAP in the short-term are useful indicators that can help in developing ways to reduce environmental threats. This study confirms evidence for ILE and DCAP as the effects of environmental threats by country-level income, energy, and natural resource levels from a socioecological approach. METHODS: This study based on life expectancy and children data on 164 countries acquired from the United Nations Development Programme. We obtained the country-level socioecological data from the United Nations and the World Bank database. We assessed the associations between ILE, DCAP, and the country-level indicators applying correlations coefficient and the regression models. RESULTS: These study findings showed considerable correlations between ILE and country-level socioecological indicators: gross national income per capita (GNI), non-solid fuel (NSF), electrification rate (ER), and natural resource depletion (NRD). The DCAP in short-term predictors were low NSF and low ER (R2 = 0.552), and ILE predictors were low GNI, NSF, and ER and higher NRD (R2 = 0.816). Thus, the countries with higher incomes and electrification rates and more sustainable natural resources had lower expected DCAP in the short-term and ILE in the long-term. CONCLUSIONS: Based on our results, we confirmed that country-level income, energy, and natural resource indicators had important effects on ILE in long-term and DCAP in short-term. We recommend that countries consider targeting high standards of living and national incomes, access to non-solid fuel and electricity as energy sources, and sustainable natural resources to reduce ILE and DCAP in short-term.

Effects on inequality in life expectancy from a social ecology perspective.

BACKGROUND: Inequality in life expectancy (ILE) is defined as inequality in the distribution of expected span of life-based on data from survival tables estimated using the Atkinson inequality index. ILE can be influenced by socio-ecological indicators including the Gini coefficient, secondary education, output per worker, and old age pension. This study examined the effects on ILE from a social ecology perspective. METHODS: This analysis is based on ILE data from 108 countries obtained from the United Nations Development Programme. Data on socio-ecological indicators were obtained from the United Nations database. The associations between socio-ecological indicators and ILE were assessed using correlation coefficients and multiple regression models. RESULTS: Significant correlations were evident between ILE and the following indicators from a socio-ecological perspective: Gini coefficient (GC: r = 0.335, p = 0.001) as an indicator of income inequality, female population with at least some secondary education (FSE: r = - 0.757, p = 0.001), male population with at least some secondary education (MSE: r = - 0.741, p = 0.001), output per worker as a measure of labor productivity (OPW: r = - 0.714, p = 0.001), and number of old age pension recipients (OPR: r = - 0.641, p = 0.001). In multivariate regression, the ILE predictors were higher GC and lower levels of FSE, MSE, OPW, and OPR (R2 = 0.648, p < 0.001). CONCLUSIONS: Socio-ecological factors have an important effect on ILE. Policies that address ILE should consider targeted socio-ecological factors, such as the Gini coefficient of income inequality, that give a personal perspective of economic deprivation, attainment of at least a secondary education by both females and males that gives a social environment perspective, output per worker that indicates labor productivity, and the number of old age pension recipients that indicates social security from a public policy perspective.

Socio-ecological perspective of older age life expectancy: income, gender inequality, and financial crisis in Europe.

BACKGROUND: Population is aging rapidly in Europe. Older age life expectancy (OLE) can be influenced by country-level depth of credit information (DCI) as an indicator of financial crisis, gross national income (GNI) per capita, and gender inequality index (GII). These factors are key indicators of socio-ecological inequality. They can be used to develop strategies to reduce country-level health disparity. The objective of this study was to confirm the relationship between socio-ecological factors and OLE in Europe. METHODS: Data were obtained from World Bank, WHO, and UN database for 34 Europe countries. Associations between socio-ecological factors and OLE were assessed with Pearson correlation coefficients and three regression models. These models assumed that appropriate changes in country-level strategies of healthy aging would produce changes in GNI per capital as personal perspective, GII in social environment perspective, and DCI in public policy perspective to implement socio-ecological changes. Hierarchal linear regression was used for final analysis. RESULTS: Although OLE (women and men) had significant negative correlation with GII (gender inequality index, r = - 0.798, p = 0.001), it had positive correlations with GNI (gross national income per capita, r = 0.834, p = 0.001) and DCI (depth of credit information index, r = 0.704, p = 0.001) levels caused by financial crisis. Higher levels GNI and DCI but lower GII were found to be predictors of OLE (women and men) (R2 = 0.804, p < 0.001). CONCLUSIONS: Factors affecting older age life expectancy in Europe were identified from socio-ecological perspective. Socio-ecological indicators (GII, GNI, and DCI) in Europe appear to have a latent effect on OLE levels. Thus, country-level strategies of successful aging in Europe should target socio-ecological factors such as GII, GNI, and DCI value.

COUNTRY-LEVEL SOCIOECONOMIC INDICATORS ASSOCIATED WITH SURVIVAL PROBABILITY OF BECOMING A CENTENARIAN AMONG OLDER EUROPEAN ADULTS: GENDER INEQUALITY, MALE LABOUR FORCE PARTICIPATION AND PROPORTIONS OF WOMEN IN PARLIAMENTS.

This study confirms an association between survival probability of becoming a centenarian (SPBC) for those aged 65 to 69 and country-level socioeconomic indicators in Europe: the gender inequality index (GII), male labour force participation (MLP) rates and proportions of seats held by women in national parliaments (PWP). The analysis was based on SPBC data from 34 countries obtained from the United Nations (UN). Country-level socioeconomic indicator data were obtained from the UN and World Bank databases. The associations between socioeconomic indicators and SPBC were assessed using correlation coefficients and multivariate regression models. The findings show significant correlations between the SPBC for women and men aged 65 to 69 and country-level socioeconomic indicators: GII (r=-0.674, p=0.001), MLP (r=0.514, p=0.002) and PWP (r=0.498, p=0.003). The SPBC predictors for women and men were lower GIIs and higher MLP and PWP (R 2=0.508, p=0.001). Country-level socioeconomic indicators appear to have an important effect on the probability of becoming a centenarian in European adults aged 65 to 69. Country-level gender equality policies in European counties may decrease the risk of unhealthy old age and increase longevity in elders through greater national gender equality; disparities in GII and other country-level socioeconomic indicators impact longevity probability. National longevity strategies should target country-level gender inequality.

Relationship Between the Remaining Years of Healthy Life Expectancy in Older Age and National Income Level, Educational Attainment, and Improved Water Quality.

The remaining years of healthy life expectancy (RYH) at age 65 years can be calculated as RYH (65) = healthy life expectancy-aged 65 years. This study confirms the associations between socioeconomic indicators and the RYH (65) in 148 countries. The RYH data were obtained from the World Health Organization. Significant positive correlations between RYH (65) in men and women and the socioeconomic indicators national income, education level, and improved drinking water were found. Finally, the predictors of RYH (65) in men and women were used to build a model of the RYH using higher socioeconomic indicators (R(2 )= 0.744, p < .001). Overall country-level educational attainment, national income level, and improved water quality influenced the RYH at 65 years. Therefore, policymaking to improve these country-level socioeconomic factors is expected to have latent effects on RYH in older age.

Social Structural Influences on Healthy Aging: Community-Level Socioeconomic Conditions and Survival Probability of Becoming a Centenarian for Those Aged 65 to 69 in South Korea.

This study estimated the associations between community-level socioeconomic conditions and survival probability of becoming a centenarian (SPBC) for those aged 65 to 69 in South Korea to determine the social structural influences on healthy aging. The indicators of socioeconomic and data of centenarians were obtained from Statistics Korea database 2014: population census and social survey. Significant positive correlations were found between SPBC and community-level socioeconomic conditions (minimum cost of living and economically active population, water supply and sewerage, pave a road with asphalt, and urbanization). SPBC male and female predictors had higher economic level and base facilities (R2)=0.578, p<.001). The study provides evidence that community-level socioeconomic conditions are important correlates of SPBC for those aged 65 to 69 in South Korea. These strategies should include social structural influences on successful aging in the overall socioeconomic conditions.

Labor force participation and secondary education of gender inequality index (GII) associated with healthy life expectancy (HLE) at birth.

BACKGROUND: What is the factor that affects healthy life expectancy? Healthy life expectancy (HLE) at birth may be influenced by components of the gender inequality index (GII). Notably, this claim is not tested on the between components of the GII, such as population at least secondary education (PLSE) with ages 25 and older, labor force participation rate (LFPR) with ages 15 and older, and the HLE in the world's countries. Thus, this study estimates the associations between the PLSE, LFPR of components of the GII and the HLE. METHODS: The data for the analysis of HLE in 148 countries were obtained from the World Health Organization. Information regarding the GII indicators for this study was obtained from the United Nations database. Associations between these factors and HLE were assessed using Pearson correlation coefficients and regression models. RESULTS: Although significant negative correlations were found between HLE and the LFPR, positive correlations were found between HLE and PLSE. Finally, the HLE predictors were used to form a model of the components of the GII, with higher PLSE as secondary education and lower LFPR as labor force (R(2) = 0.552, P <0.001). CONCLUSIONS: Gender inequality of the attainment secondary education and labor force participation seems to have an important latent effect on healthy life expectancy at birth. Therefore, in populations with high HLE, the gender inequalities in HLE are smaller because of a combination of a larger secondary education advantage and a smaller labor force disadvantage in male-females.

Factors affecting the survival probability of becoming a centenarian for those aged 70, based on the human mortality database: income, health expenditure, telephone, and sanitation.

BACKGROUND: What are the factors that affect the survival probability of becoming a centenarian for those aged 70? Do the factors include income, health expenditure, the use of mobile telephones, or sanitation? The survival probability of becoming a centenarian (SPBC) is defined as an estimate of the production of centenarians by a population. The SPBC (70) is the survival probability of becoming a centenarian for those aged 70. This study estimates the associations between the SPBC (70), and the gross national income, health expenditure, telecommunications, and sanitation facilities in 32 countries. METHODS: The socioeconomic indicators for this study were obtained from the database of the United Nations Development Programme. In addition, the data for the analysis of centenarians in 32 countries were obtained from the Human Mortality Database, which is maintained by the Department of Demography at the University of California, Berkeley, USA, and the Max Planck Institute for Demographic Research in Rostock, Germany. Associations between socioeconomic indicators and SPBC (70) were assessed using Pearson's correlation coefficients and multiple regression models. RESULTS: Significant positive correlations were found between the SPBC (70), and the socioeconomic factors of gross national income (GNI), public expenditure on health as a percentage of gross domestic product (PEHGDP), fixed and mobile telephone subscribers (FMTS) as the standard of living, and improved sanitation facilities (ISF). Overall, the SPBC (70) of female and male predictors were used, in order to form a model production of centenarians, with higher GNI and PEHGDP, as well as higher FMTS and ISF as the socioeconomic factors (R²= 0.422, P< 0.001). CONCLUSIONS: The socioeconomic level in all 32 countries appears to have an important latent effect on the production of centenarians in both females and males. This study has identified the following four important aspects of socioeconomic indicators in the survival probability of becoming a centenarian for those aged 70: higher overall economic development level, public expenditure on health, mobile telephone subscribers as the standard of living, and the use of improved sanitation facilities for healthy aging. Thus, the socioeconomic level seems to affect an important on the survival probability of becoming a centenarian.