Background: Due to the rapid aging of the South Korean population, neurological diseases such as dementia are increasing. Many studies have reported that the incidence of dementia is associated with environmental factors along with age. Objectives: This study analyzed the association between cognitive function and ten heavy metals in the body: arsenic, aluminum, chromium, manganese, cobalt, nickel, iron, copper, zinc, and lead. Methods: From 2018 to 2019, a total of 120 participants who suffered from cognitive impairment were recruited for this study. Blood and urine samples were collected and analyzed for heavy metal concentrations using an inductively coupled plasma mass spectrometer. Demographic information was obtained through face-to-face questionnaires completed by a trained investigator. Cognitive function was evaluated with the Korean version of the Mini-Mental State Examination and the Korean version of the Boston Name Waiting Test. The associations between cognitive function scores and heavy metal concentrations were analyzed using multiple logistic regression analysis. Results: The average age of the 120 participants was 72.7 years, and 69.2% were female. The mean of the MMSE-K and K-BNT scores were 22.9 and 37.9, respectively. The geometric mean of aluminum (Al) was 8.42 ㎍/L. MMSE-K was associated with iron (Fe), but the significance was removed in the logistic regression based on 24 points. K-BNT was significantly associated with aluminum and the odds ratio for K-BNT above 38 decreased by 45% as the aluminum concentration increased. Conclusions: The association between aluminum and the K-BNT score indicated that aluminum is associated with language-related cognitive decline. Based on this result, further study will be conducted by considering co-exposure effects of heavy metals including aluminum.
Objective : This study analyzed the correlation between cognitive function and oral health-related quality of life (OHQoL). Methods : Demographic and clinical characteristics were extracted and utilized for subjects aged 45 years or older who participated in the 8th Korean Longitudinal Study on Aging in 2020. The dependent variable was the Geriatric Oral Health Assessment Index, and the independent variable was the level of cognitive function classified by the Mini-Mental State Examination scores. The analysis method used inverse probability of treatment weighting (IPTW). Then, the association between cognitive function and OHQoL was analyzed by multiple regression analysis. Results : Among the participants, 4,367 (71.40%) had normal cognition, 1,155 (18.89%) had moderate cognitive impairment, and 594 (9.71%) had severe cognitive impairment. As a result of analysis by applying IPTW, there was a negative correlation between the cognitive function group and OHQoL (normal vs. moderate: β = -2.534, p < .0001; normal vs. severe: β = -2.452, p < .0001). Conclusion : After propensity score matching, mild cognitive impairment showed a more negative association than severe cognitive impairment. Therefore, patients with cognitive impairment require oral health management education to improve OHQoL regardless of the level of cognitive impairment.
Personal service robots, a type of social robot that has emerged with the aging population and technological advancements, are undergoing a transformation centered around technologies that can extend independent living for older adults in their homes. For older adults to accept and use social robot innovations in their daily lives on a long-term basis, it is crucial to have a deeper understanding of user perspectives, contexts, and emotions. This research aims to comprehensively understand older adults by utilizing a mixed-method approach that integrates quantitative and qualitative data. Specifically, we employ the Van Kaam phenomenological methodology to group conversations into nine categories based on emotional cues and conversation participants as key variables, using voice conversation records between older adults and social robots. We then personalize the conversations based on frequency and weight, allowing for user segmentation. Additionally, we conduct profiling analysis using demographic data and health indicators obtained from pre-survey questionnaires. Furthermore, based on the analysis of conversations, we perform K-means cluster analysis to classify older adults into three groups and examine their respective characteristics. The proposed model in this study is expected to contribute to the growth of businesses related to understanding users and deriving insights by providing a methodology for segmenting older adult s, which is essential for the future provision of social robots with caregiving functions in everyday life.
The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.
Marital status has drawn much attention as previous studies have been pointed it out as a key factor of health. Nonetheless, systematic studies on elderly marital status and health have been quite limited, for most researches have neglected the varying effects of marital status on health over the lifespan and mainly focused on midlife. This study, using nationwide survey on elderly population, attempts to discover the health differentials between widowed and married elderly and explain the differences though the structure and function of their social network. The results reveal that the magnitudes of marital status effects were differed by dimensions of health. The widowed were more likely to be unhappy than married, even after controlling the socio-demographic characteristics. In physical health, however, the health differences between widowed and married were less noticeable or disappeared, as sex, age and other structure factors were considered. Furthermore, the strength of social network factors affecting the physical and mental health of elderly turned out to be different between married and widowed: widowed were more likely than married to be affected by the contact with children and less likely to be affected by contact with friends/relatives. Such results had both positive and negative impact on physical and mental health of widowed. This may imply the difference in pathways of regulating health among the married and widowed elderly.
This study examines the impact of retirement on psychological well-being of the elderly and identifies whether associative factors of psychological well-being differ between retired and non-retired persons. Psychological well-being is measured by the PGCMS developed by Lawton. The sample includes 1,625 older adults aged 60 and over, which derived from the cross-sectional data of the "Aging and the Quality of Life of the Elderly in Korea: A Longitudinal Study" living in Seoul and Chuncheon in 2003. Multivariate OLS regression results show that retirement is not associated with psychological well-being after controlling socio-demographic characteristics, economic status, health status, family and social relations, participation in social activities, and satisfaction with hobbies and learning needs. Also, associative factors of psychological well-being differ between retired and non-retired persons. For retired persons, greater social activities and higher satisfaction with hobbies are associated with the higher level of psychological well-being whereas higher satisfaction with learning needs has a positive relationship with the higher level of psychological well-being for non-retired persons. Discussion and implications of the findings are presented, and limitations of this study are acknowledged.
The purpose of this study was to examine and compare factors affecting the subjective life expectancy among the elderly, and to suggest health practice and social welfare service implications for later life. A total of 4,483 seniors from the 6th wave(2016) of the Korean Longitudinal Study on Aging (KLoSA) were used for analysis. The subjects were divided into three age groups: the young-old (n=2,106, 65~74 years), middle-old (n=1,803, 75~84 years), and oldest-old (n=574, 85 years and older). Control variables were sociodemographic factors and health status factors. Independent variables were health promotion behavior, cognition of public care, participating social activity, economic activity, and receiving basic pension. The data were analyzed using hierarchical multiple regression. The main results were as follows. Health promotion behavior was associated with the young-old. Social activities and economic activity were associated with the young-old and middle-old. Receiving basic pension had a significant impact on all age groups. In the middle-old, significant results were focused on socio-demographic and health status factors compared to other groups. The results of this study will provide basic data for the elderly policy and welfare service and will help to find and improve the important factors for the life of the elderly.
Journal of the Korean Association of Geographic Information Studies
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제26권4호
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pp.97-115
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2023
In recent years, the structure of the population has been changing rapidly, with a declining birthrate and aging population, and the inequality of population distribution is expanding. At this point, changes in population estimation methods are required, and more accurate estimates are needed at the subregional level. This study aims to estimate the population in 2040 at the 500m grid level by applying an explainable machine learning to Busan in order to respond to this need for a change in population estimation method. Comparing the results of population estimation by applying the explainable machine learning and the cohort component method, we found that the machine learning produces lower errors and is more applicable to estimating areas with large population changes. This is because machine learning can account for a combination of variables that are likely to affect demographic change. Overestimated population values in a declining population period are likely to cause problems in urban planning, such as inefficiency of investment and overinvestment in certain sectors, resulting in a decrease in quality in other sectors. Underestimated population values can also accelerate the shrinkage of cities and reduce the quality of life, so there is a need to develop appropriate population estimation methods and alternatives.
Demographic and socio-structural information is useful to identify potential welfare recipients who are in need of disease-prevention and intervention services. Thus, the present study aims to explore the differences in grip strength among middle and old-aged adults by living conditions and by living area. The 5th wave data of Korean Longitudinal Study of Aging was utilized. The dependent variable was grip strength, and the independent variables were living alone (living alone or not) and living area (city or non-city). Covariates were age, education, log-transformed household income, spouse existence, body mass index, self-rated health conditions, depressive symptoms, cognitive function, smoking, regular exercise, frequency of meeting with friends, and the number of social participation. Regression analysis was performed for middle-aged men, middle-aged women, old-aged men, and old-aged women, respectively. ANOVA and Chi-test were additionally used to specifically discuss significant results. Cross-sectional weight was applied to all analyses. According to the results, living alone and living area did not have significant effects on grip strength among middle-aged men, old-aged men, and old-aged women. In middle-aged women, however, living alone and living area were significantly associated with grip strength. To be specific, middle-aged women who lived alone in rural areas had the lowest grip strength compared to other middle-aged women. Additional analysis showed that middle-aged women who lived alone in rural areas had risk factors, such as low education level, low income, or high depressive symptoms. It implies that middle-aged women living alone in rural areas may have physical health risks, so they might be in need of disease prevention. This study is meaningful in that it can provide reliable information on the latent welfare recipients by using representative panel data and applying weight values.
Since the early 2000s, Korea has continued to increase the proportion of the elderly population due to low fertility and increased life expectancy. As a result, Korea has now entered the aging society. Because of this demographic change, proportion of active elderly have increased, and many academics, such as sociology, economics, and psychology, have conducted various studies on the active elderly. This study focused on active elderly based on the activity theory of old age and the positive effect of small community participation activity on the elderly. The purpose of this study is to examine whether active elderly' participation in everyday activities, small community participation of the elderly affect citizen participation actively in society as a citizen, and in the process, mediates the effect of small community cohesion and the moderating effect of small community selfishness. This study performed a stepwise regression analysis and a hierarchical regression analysis of 700 elderly people who are participated actively in various small communities. As a result, the partial mediating effect of small community cohesion was shown in the relationship between participation in everyday activities and citizen participation, and the moderating effect of small community selfishness was also shown. These findings suggest that government and interested parties need to develop and implement policies for the small community participation of elderly citizens in consideration of their small community activities, small community cohesion and small community egoism.
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