COVID-19 Vaccination Among US-Born and Non-US-Born Residents of the United States From a Nationally Distributed Survey: Cross-sectional Study.

BACKGROUND: Extended literature has demonstrated that COVID-19 vaccination is crucial for the health of all individuals, regardless of age. Research on vaccination status in the United States (US) among US-born and non-US-born residents is limited. OBJECTIVE: The objective of our study was to examine COVID-19 vaccination during the pandemic among US-born and non-US-born people, while accounting for sociodemographic and socioeconomic factors gathered through a nationally distributed survey. METHODS: A descriptive analysis was conducted on a comprehensive 116-item survey distributed between May 2021 and January 2022 across the US by self-reported COVID-19 vaccination and US/non-US birth status. For participants that responded that they were not vaccinated, we asked if they were "not at all likely," "slightly to moderately likely," or "very to extremely likely" to be vaccinated. Race and ethnicity were categorized as White, Black or African American, Asian, American Indian or Alaskan Native, Hawaiian or Pacific Islander, African, Middle Eastern, and multiracial or multiethnic. Additional sociodemographic and socioeconomic variables included gender, sexual orientation, age group, annual household income, educational attainment, and employment status. RESULTS: The majority of the sample, regardless of whether they were US-born or non-US-born, reported being vaccinated (3639/5404, 67.34%). The US-born participants with the highest proportion of COVID-19 vaccination self-identified as White (1431/2753, 51.98%), while the highest proportion of vaccination among non-US-born participants was found among participants who self-identified as Hispanic/Latino (310/886, 34.99%). Comparing US-born and non-US-born participants showed that among those who were not vaccinated, the highest self-reported sociodemographic characteristics by proportion were similar between the groups, and included identifying as a woman, being straight or heterosexual, being aged 18 to 35 years, having an annual household income <$25,000, and being unemployed or taking part in nontraditional work. Among the 32.66% (1765/5404) of participants that reported not being vaccinated, 45.16% (797/1765) stated that they were not at all likely to seek vaccination. Examining US/non-US birth status and the likelihood to be vaccinated for COVID-19 among nonvaccinated participants revealed that the highest proportions of both US-born and non-US-born participants reported being not at all likely to seek vaccination. Non-US-born participants, however, were almost proportionally distributed in their likelihood to seek vaccination; they reported to be "very to extremely likely" to vaccinate (112/356, 31.46%); compared to 19.45% (274/1409) of US-born individuals reporting the same. CONCLUSIONS: Our study highlights the need to further explore factors that can increase the likelihood of seeking vaccination among underrepresented and hard-to-reach populations, with a particular focus on tailoring interventions for US-born individuals. For instance, non-US-born individuals were most likely to vaccinate when reporting COVID-19 nonvaccination than US-born individuals. These findings will aid in identifying points of intervention for vaccine hesitancy and promoting vaccine adoption during current and future pandemics.

A Time-Varying Effect Model (TVEM) of the Complex Association of Tobacco Use and Smoke Exposure on Mean Telomere Length: Differences between Racial and Ethnic Groups Assessed in the National Health and Nutrition Examination Survey.

Telomere length is affected by lifestyle and environmental factors and varies between racial and ethnic groups; however, studies are limited, with mixed findings. This study examined the effects of tobacco use and smoke exposure on mean telomere length to identify critical age periods by race/ethnicity. We used time-varying effect modeling on the National Health and Nutrition Examination Survey for continuous years 1999-2002 to observe the effects of active tobacco use and environmental tobacco smoke-measured through serum cotinine-and mean telomere length for adults 19 to 85 and older (N = 7826). Models were run for Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other/multi-race categories to allow for time-varying group differences, and controlled for biological sex, socioeconomic status, education, and ever-smoker status. Serum cotinine was found to have an increasing effect on telomere length from age 37 to approximately age 74 among Mexican Americans. Among other/multi-race individuals serum cotinine was found to have a decreasing effect at approximately age 42, and among Blacks, it had an overall decreasing effect from age 61 to 78. Findings reveal a further need to focus additional support and resources to intervene regarding disparate health effects from tobacco use and environmental smoke exposure for already vulnerable groups at particular ages.

The Associations Between Racially/Ethnically Stratified COVID-19 Tweets and COVID-19 Cases and Deaths: Cross-sectional Study.

BACKGROUND: The COVID-19 pandemic exacerbated existing racial/ethnic health disparities in the United States. Monitoring nationwide Twitter conversations about COVID-19 and race/ethnicity could shed light on the impact of the pandemic on racial/ethnic minorities and help address health disparities. OBJECTIVE: This paper aims to examine the association between COVID-19 tweet volume and COVID-19 cases and deaths, stratified by race/ethnicity, in the early onset of the pandemic. METHODS: This cross-sectional study used geotagged COVID-19 tweets from within the United States posted in April 2020 on Twitter to examine the association between tweet volume, COVID-19 surveillance data (total cases and deaths in April), and population size. The studied time frame was limited to April 2020 because April was the earliest month when COVID-19 surveillance data on racial/ethnic groups were collected. Racially/ethnically stratified tweets were extracted using racial/ethnic group-related keywords (Asian, Black, Latino, and White) from COVID-19 tweets. Racially/ethnically stratified tweets, COVID-19 cases, and COVID-19 deaths were mapped to reveal their spatial distribution patterns. An ordinary least squares (OLS) regression model was applied to each stratified dataset. RESULTS: The racially/ethnically stratified tweet volume was associated with surveillance data. Specifically, an increase of 1 Asian tweet was correlated with 288 Asian cases (P<.001) and 93.4 Asian deaths (P<.001); an increase of 1 Black tweet was linked to 47.6 Black deaths (P<.001); an increase of 1 Latino tweet was linked to 719 Latino deaths (P<.001); and an increase of 1 White tweet was linked to 60.2 White deaths (P<.001). CONCLUSIONS: Using racially/ethnically stratified Twitter data as a surveillance indicator could inform epidemiologic trends to help estimate future surges of COVID-19 cases and potential future outbreaks of a pandemic among racial/ethnic groups.