ABSTRACT
BACKGROUND: Despite the potential benefits of using eHealth, sociodemographic disparities exist in eHealth use, which threatens to further widen health equity gaps. The literature has consistently shown age and education to be associated with eHealth use, while the findings for racial and ethnic disparities are mixed. However, previous disparities may have narrowed as health care interactions shifted to web-based modalities for everyone because of the COVID-19 pandemic. OBJECTIVE: This study aims to provide an updated examination of sociodemographic disparities that contribute to the health equity gap related to using eHealth for information seeking using 3 time points. METHODS: Data for this study came from the nationally representative 2018 (n=3504), 2020 (n=3865), and 2022 (n=6252) time points of the Health Information National Trends Survey. Logistic regression was used to regress the use of eHealth for information seeking on race and ethnicity, sex, age, education, income, health status, and year of survey. Given the consistent association of age with the dependent variable, analyses were stratified by age cohort (millennials, Generation X, baby boomers, and silent generation) to compare individuals of similar age. RESULTS: For millennials, being female, attaining some college or a college degree, and reporting an annual income of US $50,000-$74,999 or >US $75,000 were associated with the use of eHealth for information seeking. For Generation X, being female, having attained some college or a college degree, reporting an annual income of US $50,000-$74,999 or >US $75,000, better self-reported health, and completing the survey in 2022 (vs 2018; odds ratio [OR] 1.80, 95% CI 1.11-2.91) were associated with the use of eHealth for information seeking. For baby boomers, being female, being older, attaining a high school degree, attaining some college or a college degree, reporting an annual income of US $50,000-$74,999 or >US $75,000, and completing the survey in 2020 (OR 1.56, 95% CI 1.15-2.12) and 2022 (OR 4.04, 95% CI 2.77-5.87) were associated with the use of eHealth for information seeking. Among the silent generation, being older, attaining some college or a college degree, reporting an annual income of US $50,000-$74,999 or >US $75,000, and completing the survey in 2022 (OR 5.76, 95% CI 3.05-10.89) were associated with the use of eHealth for information seeking. CONCLUSIONS: Baby boomers may have made the most gains in using eHealth for information seeking over time. The race and ethnicity findings, or lack thereof, may indicate a reduction in racial and ethnic disparities. Disparities based on sex, education, and income remained consistent across all age groups. This aligns with health disparities literature focused on individuals with lower socioeconomic status, and more recently on men who are less likely to seek health care compared to women.
Subject(s)
COVID-19 , Information Seeking Behavior , Sociodemographic Factors , Telemedicine , Humans , United States , Female , Telemedicine/statistics & numerical data , Male , Cross-Sectional Studies , Adult , Middle Aged , COVID-19/epidemiology , Aged , Young Adult , Adolescent , Socioeconomic Factors , SARS-CoV-2ABSTRACT
INTRODUCTION: Transportation barriers can affect travel needs and quality of life. METHODS: This survey examined transportation, routine activities, and unmet travel needs among older Vietnamese immigrants, focusing on gender differences. RESULTS: Women were more likely to ride with others, less likely to drive, had fewer types of routine activities, and went out for activities less than men. Over 1/4 of the sample had at least one unmet travel need in the previous month (the most common was for visiting family and friends). DISCUSSION: Interventions to enhance mobility should address age- and gender-based transportation differences and assess for unmet travel needs.
ABSTRACT
BACKGROUND: Social determinants of health (SDoH) have been described by the World Health Organization as the conditions in which individuals are born, live, work, and age. These conditions can be grouped into 3 interrelated levels known as macrolevel (societal), mesolevel (community), and microlevel (individual) determinants. The scope of SDoH expands beyond the biomedical level, and there remains a need to connect other areas such as economics, public policy, and social factors. OBJECTIVE: Providing a computable artifact that can link health data to concepts involving the different levels of determinants may improve our understanding of the impact SDoH have on human populations. Modeling SDoH may help to reduce existing gaps in the literature through explicit links between the determinants and biological factors. This in turn can allow researchers and clinicians to make better sense of data and discover new knowledge through the use of semantic links. METHODS: An experimental ontology was developed to represent knowledge of the social and economic characteristics of SDoH. Information from 27 literature sources was analyzed to gather concepts and encoded using Web Ontology Language, version 2 (OWL2) and Protégé. Four evaluators independently reviewed the ontology axioms using natural language translation. The analyses from the evaluations and selected terminologies from the Basic Formal Ontology were used to create a revised ontology with a broad spectrum of knowledge concepts ranging from the macrolevel to the microlevel determinants. RESULTS: The literature search identified several topics of discussion for each determinant level. Publications for the macrolevel determinants centered around health policy, income inequality, welfare, and the environment. Articles relating to the mesolevel determinants discussed work, work conditions, psychosocial factors, socioeconomic position, outcomes, food, poverty, housing, and crime. Finally, sources found for the microlevel determinants examined gender, ethnicity, race, and behavior. Concepts were gathered from the literature and used to produce an ontology consisting of 383 classes, 109 object properties, and 748 logical axioms. A reasoning test revealed no inconsistent axioms. CONCLUSIONS: This ontology models heterogeneous social and economic concepts to represent aspects of SDoH. The scope of SDoH is expansive, and although the ontology is broad, it is still in its early stages. To our current understanding, this ontology represents the first attempt to concentrate on knowledge concepts that are currently not covered by existing ontologies. Future direction will include further expanding the ontology to link with other biomedical ontologies, including alignment for granular semantics.
ABSTRACT
OBJECTIVES: Companions (i.e., friends who spend time together) are important for the well-being of older adults. Senior centers in the United States are places for older adults to participate in group activities and form and maintain companionships. However, differences in mobility and transportation may affect the ability of older adults to leverage senior center activities into actual companionships. METHODS: This social network analysis was conducted to characterize the companionship network among members of a senior center in relation to their life-space mobility and transportation resources. An exponential random graph model was estimated to identify mobility- and transportation-related correlates of the likelihood of a companionship tie among senior center members (Nâ =â 42). RESULTS: Members had an average of 2 companionships with one another (Mâ =â 2.2, SDâ =â 2.7). Companionships were more likely for members with greater life-space mobility (pâ =â .009), who attended the senior center more frequently (pâ =â .004), with automobile ownership in their households (pâ =â .034), and who were not transportation cost-burdened (i.e., spent less than 15% of their income on transportation, pâ =â .005). Demographic characteristics, limitations on instrumental activities of daily living, and being at risk for depression were not significantly associated with the likelihood of companionships. DISCUSSION: These findings extend previous knowledge of the role of life-space mobility and transportation in supporting general social participation for older adults to include the importance of transportation and mobility for having companions within a senior center.