Socioeconomic status and physical activity disparities in older adults: Implications for COVID-19 related diabetes cognitive dysfunction.

Objectives: This study aims to investigate the influence of socioeconomic status (SES) on variations in physical activity (PA) levels and diabetes-related cognitive dysfunction and impairment amidst disruptions caused by the COVID-19 pandemic. Methods: With the sample of old population, comprising about 20 thousand from the Fact-Finding Survey on the Status of Senior Citizens (FSSSC) released by Ministry of Health and Welfare of South Korea in 2017 and 2020, we empirically tested the direct and indirect effects of SES on cognitive dysfunction using structural equation modeling (SEM). Two SEMs provided the comparison on the effects of COVID-19. Results: Household income had a negative impact on the likelihood of dementia diagnosis via PA related diabetes during the pandemic (p < 0.001), whereas no effects of household income on dementia diagnosis were found in 2017, due to no direct effect of PA on diabetes confirmation in 2017. The disparity in PA based on SES becomes more prominent among the older individuals during the pandemic (z = 11.7) than 2017 (z = 6.0), emphasizing the significance of PA in mitigating diabetes-induced cognitive dysfunction during the pandemic. SES affects access to PA, contributing to diabetes-induced cognitive dysfunctions in the older population with lower SES during the pandemic. Conclusion: PA may serve as a preventive measure against diabetes-induced cognitive dysfunction and dementia in the older population. Thorough investigation of these mechanisms is imperative to establish the role of PA in preventing diabetes-induced cognitive impairment, particularly among the older population with lower SES.

Apple Watch 6 vs. Galaxy Watch 4: A Validity Study of Step-Count Estimation in Daily Activities.

The purpose of this study was to examine the validity of two wearable smartwatches (the Apple Watch 6 (AW) and the Galaxy Watch 4 (GW)) and smartphone applications (Apple Health for iPhone mobiles and Samsung Health for Android mobiles) for estimating step counts in daily life. A total of 104 healthy adults (36 AW, 25 GW, and 43 smartphone application users) were engaged in daily activities for 24 h while wearing an ActivPAL accelerometer on the thigh and a smartwatch on the wrist. The validities of the smartwatch and smartphone estimates of step counts were evaluated relative to criterion values obtained from an ActivPAL accelerometer. The strongest relationship between the ActivPAL accelerometer and the devices was found for the AW (r = 0.99, p < 0.001), followed by the GW (r = 0.82, p < 0.001), and the smartphone applications (r = 0.93, p < 0.001). For overall group comparisons, the MAPE (Mean Absolute Percentage Error) values (computed as the average absolute value of the group-level errors) were 6.4%, 10.5%, and 29.6% for the AW, GW, and smartphone applications, respectively. The results of the present study indicate that the AW and GW showed strong validity in measuring steps, while the smartphone applications did not provide reliable step counts in free-living conditions.

Effects of socioeconomic status on physical activity and cardiovascular diseases prior to and during the COVID-19 pandemic in the older adults.

Purpose: This research seeks to evaluate the repercussions of socioeconomic status (SES) on physical activity (PA) among the older population, both pre and intra-COVID-19 pandemic. The study aims to scrutinize whether alteration in PA behaviors based on SES impacts cardiovascular diseases (CVDs). It is well established that PA has a significant association with CVDs and the pandemic has restricted PA in the older population. We endeavor to discern whether SES modulates PA levels and whether these levels of PA behavior subsequently influence the incidence of CVDs among older adults. Methods: The analytical framework of this study relies on the data procured from the Fact-Finding on the Status of Senior Citizens (FSSSC) survey conducted in 2017 and 2020, involving 10,299 (75 ± 6 years) and 10,097 (74 ± 6 years) participants, respectively. We employ Structural Equation Modeling (SEM) to elucidate the ramification of the COVID-19 pandemic on CVDs while accommodating potential mediating and confounding variables, including socioeconomic status, PA levels, body mass index (BMI), and gender, in the context of the pandemic and CVDs. Results: Our empirical models indicated a tendency for older adults of lower socioeconomic status (SES) to exhibit diminished levels of physical activity (PA) compared to their counterparts of higher SES, particularly considering the influence of the COVID-19 pandemic. Furthermore, prolonged engagement in PA is associated with a reduced risk of hypertension (p = 0.010), and congestive heart failure & arrhythmia (p < 0.001), when accounting for confounding factors. Conclusion: The COVID-19 pandemic has generated an SES-based disparity in PA among older adults, despite PA time being greater in older individuals with higher SES. Interestingly, this did not result in a reduction in CVDs. Therefore, the study emphasizes the need for targeted exercise programs may be necessary to mitigate health inequality among the older population.

Association between smartphone overdependency and mental health in Korean adolescents during the COVID pandemic; Age-and gender-matched study.

Purpose: This study aimed to examine the relationship between smartphone dependency (SD) and mental health (MH) in adolescents in order to develop and implement plans pertaining to SD control. Methods: Raw data from the 16th Online Adolescent Health Behavior Survey in 2020 were analyzed. A total of 482 respondents were selected as study subjects based on their experience of smartphone overdependence (SO), specifically, 241 participants whose score for SO was 37 or higher (Group 2) and age- and gender-matched 241 participants whose score was lower than 10 (Group 1). Results: Frequency analysis, cross-tab analysis (χ2 test), and multinomial logistic regression were performed Analysis shows that the MH affecting the increase in SO is the subjective perception of happiness, subjective perception of stress, sadness and despair, and experience of Loneliness. But, the variable affecting the reduction is the subjective evaluation of sleep quality. The likelihood of SO increased as adolescents felt unhappier [Exp (ß) = 2.408] and more stressed [Exp (ß) = 4.453] and more often felt lonely [Exp (ß) = 8.149], but the likelihood decreased as they had neither sufficient nor insufficient sleep duration [Exp (ß) = 0.344]. The findings suggest that it is necessary to develop aggressive measures for the prevention and management of MH in adolescents showing SO because mental health is closely linked to SD. In developing the measures, realistic approaches to widely pervasive SO among adolescents should be explored by taking into account MH factors, that is, predictors of SO, and the characteristics of youths, such that they can self-control smartphone use and form desirable life habits.