The Association between Gender and Physical Activity Was Partially Mediated by Social Network Size during COVID-19.

The COVID-19 pandemic has disrupted physical activity, particularly among women. Limited research has explored how social network support may explain gender-based variations in physical activity during COVID-19. The purpose of this study was to examine the mediating role of social networks in the association between gender and physical activity during a pandemic. This cross-sectional survey assessed whether social network characteristics (i.e., in-person social network size, frequency of in-person social network interactions, and online friend network size) mediate the relationship between gender and either past-week or past-year physical activity. Multiple mediation analyses were conducted to determine the indirect effect of gender on physical activity through social networks. Among 205 participants, women (n = 129) were significantly less physically active (ß = -73.82; p = 0.02) than men (n = 76) and reported significantly more Facebook friends (ß = 0.30; p < 0.001) than men, which was inversely associated with past-week physical activity (ß = -64.49; p = 0.03). Additionally, the indirect effect of gender on past-week physical activity through Facebook friends was significant (ß = -19.13; 95% CI [-40.45, -2.09]). Findings suggest that social media sites such as Facebook could be used to encourage physical activity among women during a pandemic.

The Nepali-speaking Bhutanese Immigrants: A Population Overlooked amidst the COVID-19 Crisis.

The Nepali-speaking Bhutanese (NSB) community living in Central Pennsylvania has been significantly affected by COVID-19 due to various biopsychosocial determinants of health. In this paper, we discuss interventions developed by a tertiary care health system in Central Pennsylvania to provide immediate support to the NSB community.

Telehealth Interventions and Outcomes Across Rural Communities in the United States: Narrative Review.

BACKGROUND: In rural communities, there are gaps in describing the design and effectiveness of technology interventions for treating diseases and addressing determinants of health. OBJECTIVE: The aim of this study is to evaluate literature on current applications, therapeutic areas, and outcomes of telehealth interventions in rural communities in the United States. METHODS: A narrative review of studies published on PubMed from January 2017 to December 2020 was conducted. Key search terms included telehealth, telemedicine, rural, and outcomes. RESULTS: Among 15 included studies, 9 studies analyzed telehealth interventions in patients, 3 in health care professionals, and 3 in both patients and health care professionals. The included studies reported positive outcomes and experiences of telehealth use in rural populations including acceptability and increased satisfaction; they also noted that technology is convenient and efficient. Other notable benefits included decreased direct and indirect costs to the patient (travel cost and time) and health care service provider (staffing), lower onsite health care resource utilization, improved physician recruitment and retention, improved access to care, and increased education and training of patients and health care professionals. CONCLUSIONS: Telehealth models were associated with positive outcomes for patients and health care professionals, suggesting these models are feasible and can be effective. Future telehealth interventions and studies examining these programs are warranted, especially in rural communities, and future research should evaluate the impact of increased telehealth use as a result of the COVID-19 pandemic.

Associations of Race/Ethnicity and Food Insecurity With COVID-19 Infection Rates Across US Counties.

Importance: Food insecurity is prevalent among racial/ethnic minority populations in the US. To date, few studies have examined the association between pre-COVID-19 experiences of food insecurity and COVID-19 infection rates through a race/ethnicity lens. Objective: To examine the associations of race/ethnicity and past experiences of food insecurity with COVID-19 infection rates and the interactions of race/ethnicity and food insecurity, while controlling for demographic, socioeconomic, risk exposure, and geographic confounders. Design, Setting, and Participants: This cross-sectional study examined the associations of race/ethnicity and food insecurity with cumulative COVID-19 infection rates in 3133 US counties, as of July 21 and December 14, 2020. Data were analyzed from November 2020 through March 2021. Exposures: Racial/ethnic minority groups who experienced food insecurity. Main Outcomes and Measures: The dependent variable was COVID-19 infections per 1000 residents. The independent variables of interest were race/ethnicity, food insecurity, and their interactions. Results: Among 3133 US counties, the mean (SD) racial/ethnic composition was 9.0% (14.3%) Black residents, 9.6% (13.8%) Hispanic residents, 2.3% (7.3%) American Indian or Alaska Native residents, 1.7% (3.2%) Asian American or Pacific Islander residents, and 76.1% (20.1%) White residents. The mean (SD) proportion of women was 49.9% (2.3%), and the mean (SD) proportion of individuals aged 65 years or older was 19.3% (4.7%). In these counties, large Black and Hispanic populations were associated with increased COVID-19 infection rates in July 2020. An increase of 1 SD in the percentage of Black and Hispanic residents in a county was associated with an increase in infection rates per 1000 residents of 2.99 (95% CI, 2.04 to 3.94; P < .001) and 2.91 (95% CI, 0.39 to 5.43; P = .02), respectively. By December, a large Black population was no longer associated with increased COVID-19 infection rates. However, a 1-SD increase in the percentage of Black residents in counties with high prevalence of food insecurity was associated with an increase in infections per 1000 residents of 0.90 (95% CI, 0.33 to 1.47; P = .003). Similarly, a 1-SD increase in the percentage of American Indian or Alaska Native residents in counties with high levels of food insecurity was associated with an increase in COVID-19 infections per 1000 residents of 0.57 (95% CI, 0.06 to 1.08; P = .03). By contrast, a 1-SD increase in Hispanic populations in a county remained independently associated with a 5.64 (95% CI, 3.54 to 7.75; P < .001) increase in infection rates per 1000 residents in December 2020 vs 2.91 in July 2020. Furthermore, while a 1-SD increase in the proportion of Asian American or Pacific Islander residents was associated with a decrease in infection rates per 1000 residents of -1.39 (95% CI, -2.29 to 0.49; P = .003), the interaction with food insecurity revealed a similar association (interaction coefficient, -1.48; 95% CI, -2.26 to -0.70; P < .001). Conclusions and Relevance: This study sheds light on the association of race/ethnicity and past experiences of food insecurity with COVID-19 infection rates in the United States. These findings suggest that the channels through which various racial/ethnic minority population concentrations were associated with COVID-19 infection rates were markedly different during the pandemic.