Dataset Information

Applying Latent Profile Analysis to Identify Lifestyle Profiles and Their Association with Loneliness and Quality of Life among Community-Dwelling Middle- and Older-Aged Adults in South Korea.

ABSTRACT: This study aimed to examine the multi-faceted lifestyle profiles of community-dwelling middle- and older-aged adults based on their physical activity, participation in various activities, and nutrition. It identified the association of lifestyle profiles with demographic variables, quality of life, and mental health. The analysis included 569 participants (mean age = 60.2; SD = 4.3). Latent profile analysis identified three distinctive lifestyle profiles: "inactive and unbalanced" (36.4%), "basic life maintenance" (54.6%), and "active and balanced" (9.1%). Sex (p < 0.001), age (p < 0.001), and regular medication intake (p < 0.01) were statistically significantly different among the three profiles. Of the "inactive and unbalanced" lifestyle group, 63.3% of it was comprised of by females, and a relatively large distribution was aged over 65. In the "basic life maintenance" subgroup, males showed a relatively large distribution, and 92.6% of participants were aged 55-64. People with active and balanced lifestyles demonstrated high quality of life levels (p < 0.001) and low loneliness levels (p < 0.01). Multinomial logistic regression revealed a statistically significant positive association between lifestyle profiles and quality of life (p < 0.001) as well as mental health (p < 0.01). Therefore, health promotion that considers multi-faceted lifestyle factors would need to improve health and quality of life among community-dwelling middle- and older-aged adults in South Korea.

SUBMITTER: Park KH

PROVIDER: S-EPMC8656840 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Sleep misperception has long been a major issue in the field of insomnia research. Most studies of sleep misperception examine sleep underestimation by comparing the results of polysomnography conducted in a laboratory environment with patients' sleep diary entries. We aimed to investigate psychosocial characteristics of adults who underestimated or overestimated sleep time in a nonclinical, middle-aged community-dwelling population. We collected one week of sleep data with wrist-worn accelerometers. We used egocentric social network analysis to analyze the effects of psychosocial factors. Among 4,060 study participants, 922 completed the accelerometer substudy. Underestimation was defined as an accelerometer-measured sleep time ≥ 6 h and a subjective sleep time < 6 h. Overestimation was defined as an objective sleep time < 6 h and a subjective sleep time ≥ 6 h. Psychosocial characteristics of the sleep misperception group were evaluated using multivariate regression analysis. A total of 47 participants underestimated sleep time, and 420 overestimated sleep time. Regression analysis revealed that women, living with spouse, economic satisfaction, and bridging potential had protective effects against sleep underestimation. Blame from a spouse involved a 3.8-times higher risk of underestimation than the control group (p = 0.002). In men, discussing concerns with a spouse had a protective effect against underestimation (p < 0.001). Economic satisfaction, feeling social network-based intimacy, and support from a spouse were associated with overestimation in women. In men, feeling social network-based intimacy was also associated with overestimation (p < 0.001). We found that social relationship quality was related to sleep overestimation and underestimation. This association was marked in women. Good social relationships may have positive effects on sleep misperception via attenuation of negative emotional reactions and effects on emotional regulation.

Project description:BackgroundDigital technology has dramatically changed the world in which we live, and the ability to access and understand information through these new technologies is becoming increasingly important. eHealth literacy is closely related to digital literacy, and some concepts may overlap to a certain extent. Identifying personal and digital-related factors related to eHealth literacy levels in middle-aged adults would be useful for planning tailored interventions and health promotion strategies.ObjectiveWe aimed to identify the differences in digital literacy and eHealth literacy levels according to demographic features, and to elucidate the factors associated with eHealth literacy in the middle-aged population.MethodsWe conducted a cross-sectional, observational study from 4th to 8th February 2021. A total of 320 South Korean participants aged 40-64 years were recruited and completed an online questionnaire, where demographic features, chronic disease status, frequency of Internet use, digital skills, digital competence, and eHealth literacy were measured. eHealth literacy was measured with the eHEALS. We used multiple regression analysis to elucidate the factors associated with eHealth literacy.ResultsMultiple regression analysis revealed that digital competence was the highest contributor to an individual's eHealth literacy (β = 0.330, P < 0.001), while digital skills was not significantly associated with eHealth literacy (β = 0.086, P = 0.267). In addition, eHealth literacy was positively associated with increasing age (β = 0.258, P < 0.001), female gender (β = -0.118, P = 0.022), and higher education levels (β = 0.114, P = 0.041), while marital state, chronic disease, and frequency of internet use were not significantly associated with eHealth literacy.ConclusionsOur study provides valuable information on digital literacy and eHealth literacy in middle-aged adults and may be used to guide tailored interventions for improving eHealth literacy. Future studies should consider the differences in digital literacy levels across generations when assessing eHealth literacy or planning digital health interventions.

Project description:Sarcopenia is defined as the age-related decline in skeletal muscle mass and function. The risk factors and causes of sarcopenia must be identified to develop prevention and treatment strategies for this syndrome. Our aim was to examine the association between sarcopenia with lifestyle and family function among community-dwelling Chinese people aged 60 years and older.We conducted this study to evaluate sarcopenia among 834 community-dwelling Chinese individuals aged ≥60 years using the Asian Working Group for Sarcopenia (AWGS) criteria. The sociodemographic characteristics, food consumption patterns, habits of smoking, and alcohol consumption of the participants were collected using a general questionnaire, whereas physical activity was assessed using the International Physical Activity Questionnaire (IPAQ; long-form version). Family function was assessed using the Family APGAR scale. In addition, the association of sarcopenia with lifestyle and family function was examined using univariate and multivariate analyses.The total prevalence rate of sarcopenia was 10.6%. Female participants with sarcopenia had a lower frequency per week of nut consumption than those without sarcopenia (p < 0.05), whereas, for male participants, the differences in food consumption patterns of those with sarcopenia versus those without sarcopenia were not significant. Among the participants, the mean Family APGAR score was 8 (standard deviation [SD] = 0.92). For both sexes, participants with sarcopenia had lower family function scores than those without sarcopenia. In the multivariate model, after adjustment for all covariates, frequency per week of nut consumption (adjusted OR 0.724, 95% CI 0.532-0.985, P < 0.05) and Family APGAR score (adjusted OR 0.683, 95% CI 0.496-0.940, P = 0.019) were statistically significantly associated with sarcopenia. The relationship between other lifestyle habits and sarcopenia was not significant.There was significant association between sarcopenia with intake of nuts and family function. Further studies should evaluate if adequate intake of nuts and a well-functioning family may be effective in lowering the risk of sarcopenia.

Dataset Information

Applying Latent Profile Analysis to Identify Lifestyle Profiles and Their Association with Loneliness and Quality of Life among Community-Dwelling Middle- and Older-Aged Adults in South Korea.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets