Quantifying and Benchmarking Disparities in COVID-19 Vaccination Rates by Race and Ethnicity.
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ABSTRACT:
SUBMITTER: Reitsma MB
PROVIDER: S-EPMC8529412 | biostudies-literature | 2021 Oct
REPOSITORIES: biostudies-literature
Publications
Quantifying and Benchmarking Disparities in COVID-19 Vaccination Rates by Race and Ethnicity.
Reitsma Marissa B MB Goldhaber-Fiebert Jeremy D JD Salomon Joshua A JA
JAMA network open 20211001 10
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Project description:BackgroundVaccination plays an important role in preventing COVID-19 infection and reducing the severity of the disease. There are usually differences in vaccination rates between urban and rural areas. Measuring these differences can aid in developing more coordinated and sustainable solutions. This information also serves as a reference for the prevention and control of emerging infectious diseases in the future.ObjectiveThis study aims to assess the current coverage rate and influencing factors of COVID-19 (second booster) vaccination among Chinese residents, as well as the disparities between urban and rural areas in China.MethodsThis cross-sectional study used a stratified random sampling approach to select representative samples from 11 communities and 10 villages in eastern (Changzhou), central (Zhengzhou), western (Xining), and northeast (Mudanjiang) Mainland China from February 1 to February 18, 2023. The questionnaires were developed by experienced epidemiologists and contained the following: sociodemographic information, health conditions, vaccine-related information, information related to the Protective Motivation Theory (PMT), and the level of trust in the health care system. Vaccination rates among the participants were evaluated based on self-reported information provided. Binary logistic regression models were performed to explore influencing factors of vaccination among urban and rural participants. Urban-rural disparities in the vaccination rate were assessed using propensity score matching (PSM).ResultsA total of 5780 participants were included, with 53.04% (3066/5780) being female. The vaccination rate was 12.18% (704/5780; 95% CI 11.34-13.02) in the total sample, 13.76% (341/2478; 95% CI 12.40-15.12) among the rural participants, and 10.99% (363/3302; 95% CI 9.93-12.06) among the urban participants. For rural participants, self-reported health condition, self-efficacy, educational level, vaccine knowledge, susceptibility, benefits, and trust in the health care system were independent factors associated with vaccination (all P＜.05). For urban participants, chronic conditions, COVID-19 infection, subjective community level, vaccine knowledge, self-efficacy, and trust in the health care system were independent factors associated with vaccination (all P＜.05). PSM analysis uncovered a 3.42% difference in vaccination rates between urban and rural participants.ConclusionsThe fourth COVID-19 vaccination coverage rate (second booster) among the Chinese population was extremely low, significantly lower than the previous vaccine coverage rate. Given that COVID-19 infection is still prevalent at low levels, efforts should focus on enhancing self-efficacy to expand the vaccine coverage rate among the Chinese population. For rural residents, building awareness of the vaccine's benefits and improving their overall health status should be prioritized. In urban areas, a larger proportion of people with COVID-19 and patients with chronic illness should be vaccinated.
| S-EPMC11297372 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic disproportionately impacts youth and young adults (YYA) and YYA with multiple marginalized identities, yet little is known about differences in uptake, testing access, and vaccine concerns among YYA by diverse demographic identities.MethodsBetween 2/2021 and 2/2022, we conducted a national, cross-sectional online survey focused on diverse YYA ages 14 to 24 (n = 983). We explored the prevalence of COVID-19 testing and vaccination among YYA by age, race/ethnicity, and sexual and gender identities. Bivariate and multivariable logistic regression models were developed to estimate associations between individual variables and COVID-19 testing and vaccination.ResultsThe overall COVID-19 testing and vaccination rates in our sample were high (75.99% and 69.07%, respectively). No differences in testing by demographics were found. Compared to individuals aged 14 to 17 years, those aged 18 to 21 years and 22 to 24 years were over 2 times and 4 times as likely to report receiving a vaccine, respectively. All race/ethnicity groups except for Asian individuals were more likely to report being vaccinated compared to their white peers.ConclusionsOur findings showed critical disparities in COVID-19 vaccination among YYA with marginalized identities and emphasized the urgency for data collection and research on pandemic prevention for vulnerable YYA populations.
| S-EPMC10925914 | biostudies-literature
Project description:BackgroundExisting studies have elucidated racial and ethnic disparities in COVID-19 hospitalizations, but few have examined disparities at the intersection of race and ethnicity and income.MethodsWe used a population-based probability survey of non-institutionalized adults in Michigan with a polymerase chain reaction-positive SARS-CoV-2 test before November 16, 2020. We categorized respondents by race and ethnicity and annual household income: low-income (< $50,000) Non-Hispanic (NH) Black, high-income (≥ $50,000) NH Black, low-income Hispanic, high-income Hispanic, low-income NH White, and high-income NH White. We used modified Poisson regression models, adjusting for sex, age group, survey mode, and sample wave, to estimate COVID-19 hospitalization prevalence ratios by race and ethnicity and income.ResultsOver half of the analytic sample (n = 1593) was female (54.9%) and age 45 or older (52.5%), with 14.5% hospitalized for COVID-19. Hospitalization was most prevalent among low-income (32.9%) and high-income (31.2%) Non-Hispanic (NH) Black adults, followed by low-income NH White (15.3%), low-income Hispanic (12.9%), high-income NH White (9.6%), and high-income Hispanic adults (8.8%). In adjusted models, NH Black adults, regardless of income (low-income prevalence ratio [PR]: 1.86, 95% CI: 1.36-2.54; high-income PR: 1.57, 95% CI: 1.07-2.31), and low-income NH White adults (PR: 1.52, 95% CI: 1.12-2.07), had higher prevalence of hospitalization compared to high-income NH White adults. We observed no significant difference in the prevalence of hospitalization among Hispanic adults relative to high-income NH White adults.ConclusionsWe observed disparities in COVID-19 hospitalization at the intersection of race and ethnicity and income for NH Black adults and low-income NH White adults relative to high-income NH White adults, but not for Hispanic adults.
| S-EPMC10103660 | biostudies-literature
Project description:The authors provide the first age-standardized race/ethnicity-specific, state-specific vaccination rates for the United States. Data encompass all states reporting race/ethnicity-specific vaccinations and reflect vaccinations through mid-October 2021, just before eligibility expanded below age 12. Using indirect age standardization, the authors compare racial/ethnic state vaccination rates with national rates. The results show that white and Black state median vaccination rates are, respectively, 89 percent and 76 percent of what would be predicted on the basis of age; Hispanic and Native rates are almost identical to what would be predicted; and Asian American/Pacific Islander rates are 110 percent of what would be predicted. The authors also find that racial/ethnic vaccination rates are associated with state politics, as proxied by 2020 Trump vote share: for each percentage point increase in Trump vote share, vaccination rates decline by 1.08 percent of what would be predicted on the basis of age. This decline is sharpest for Native American vaccinations, although these are reported for relatively few states.
| S-EPMC9128071 | biostudies-literature
Project description:ObjectivesDisaggregated data on Asian ethnic groups are needed to identify health disparities among Asian people. We examined COVID-19 incidence, deaths, and vaccinations among Asian ethnic groups in Santa Clara County, California.MethodsWe extracted data on SARS-CoV-2 infections and COVID-19 vaccinations from December 15, 2020, through August 6, 2021, from the California Reportable Diseases Information Exchange and the California Immunization Registry. We assigned Asian ethnic group based on name for missing self-reported information. We calculated age-adjusted rates and rate ratios of infections and deaths and percentages of vaccinations by race and ethnicity and Asian ethnic group. We conducted multivariable logistic regression to examine factors associated with COVID-19 deaths.ResultsAlthough Asian residents had the lowest rate of SARS-CoV-2 infections per 100 000 people (1801.9; 95% CI, 1771.5-1832.7) among all racial and ethnic groups, when disaggregated by Asian ethnicity, Filipino (3169.0; 95% CI, 3049.1-3292.4) and Vietnamese (3008.4; 95% CI, 2916.9-3102.1) residents had the highest age-adjusted rates. Asian (38.7; 95% CI, 33.7-44.3) and non-Hispanic White (42.3; 95% CI, 37.5-47.5) residents had the lowest rate of COVID-19 deaths compared with all other racial and ethnic groups; however, Filipino (67.6; 95% CI, 49.1-90.8) and Vietnamese (63.7; 97% CI, 48.9-81.6) residents had significantly higher rates than the aforementioned groups did. Among all racial and ethnic groups, Asian residents had the highest completion rate of primary COVID-19 vaccine series by August 6, 2021 (87.0%; 95% CI, 86.8%-87.3%). Within Asian ethnic groups, Filipino residents had the lowest vaccination rate (65.0%; 95% CI, 64.4%-65.6%).ConclusionsDifferences in COVID-19 incidence, deaths, and vaccinations among Asian ethnic groups highlight the importance of data collection of ethnic groups as a standard practice.
| S-EPMC11760075 | biostudies-literature
Project description:Purpose Telehealth may remain an integral part of cancer survivorship care after the SARS-CoV-2 pandemic. While telehealth may reduce travel/waiting times and costs for many patients, it may also create new barriers that could exacerbate care disparities in historically underserved populations, manifesting as differences in overall care participation, and in differential video versus phone use for telehealth. Methods We reviewed visits by cancer survivors between January and December 2020 at a designated cancer center in Minnesota. We used descriptive statistics, data visualization, and generalized estimating equation logistic regression models to compare visit modalities and trends over time by age, urban/rural status, and race/ethnicity. Results Among 159,301 visits, including 33,242 telehealth visits, older and rural-dwelling individuals were underrepresented in telehealth compared with in-person care. Non-Hispanic White individuals, those aged 18–69 years, and urban residents used video for > 50% of their telehealth visits. In contrast, those aged ≥ 70 years, rural residents, and most patient groups of color used video for only 33–43% of their telehealth visits. Video use increased with time for everyone, but relative differences in telehealth modalities persisted. Visits of Black/African American patients temporarily fell in spring/summer 2020. Conclusions Our findings underscore reduced uptake of telehealth, especially video, among potentially vulnerable patient populations. Future research should evaluate reasons for differential telehealth utilization and whether visit modality (in-person versus video versus phone) affects cancer outcomes. Implications for Cancer Survivors A long-term cancer care model with integrated telehealth elements needs to account for specific barriers for vulnerable populations. Supplementary Information The online version contains supplementary material available at 10.1007/s11764-021-01133-4.
| S-EPMC8605776 | biostudies-literature
Project description:BackgroundMeta-analyses have investigated associations between race and ethnicity and COVID-19 outcomes. However, there is uncertainty about these associations' existence, magnitude, and level of evidence. We, therefore, aimed to synthesize, quantify, and grade the strength of evidence of race and ethnicity and COVID-19 outcomes in the US.MethodsIn this umbrella review, we searched four databases (Pubmed, Embase, the Cochrane Database of Systematic Reviews, and Epistemonikos) from database inception to April 2022. The methodological quality of each meta-analysis was assessed using the Assessment of Multiple Systematic Reviews, version 2 (AMSTAR-2). The strength of evidence of the associations between race and ethnicity with outcomes was ranked according to established criteria as convincing, highly suggestive, suggestive, weak, or non-significant. The study protocol was registered with PROSPERO, CRD42022336805.ResultsOf 880 records screened, we selected seven meta-analyses for evidence synthesis, with 42 associations examined. Overall, 10 of 42 associations were statistically significant (p ≤ 0.05). Two associations were highly suggestive, two were suggestive, and two were weak, whereas the remaining 32 associations were non-significant. The risk of COVID-19 infection was higher in Black individuals compared to White individuals (risk ratio, 2.08, 95% Confidence Interval (CI), 1.60-2.71), which was supported by highly suggestive evidence; with the conservative estimates from the sensitivity analyses, this association remained suggestive. Among those infected with COVID-19, Hispanic individuals had a higher risk of COVID-19 hospitalization than non-Hispanic White individuals (odds ratio, 2.08, 95% CI, 1.60-2.70) with highly suggestive evidence which remained after sensitivity analyses.ConclusionIndividuals of Black and Hispanic groups had a higher risk of COVID-19 infection and hospitalization compared to their White counterparts. These associations of race and ethnicity and COVID-19 outcomes existed more obviously in the pre-hospitalization stage. More consideration should be given in this stage for addressing health inequity.
| S-EPMC10513444 | biostudies-literature
Project description:ImportanceFood 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.ObjectiveTo 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 participantsThis 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.ExposuresRacial/ethnic minority groups who experienced food insecurity.Main outcomes and measuresThe dependent variable was COVID-19 infections per 1000 residents. The independent variables of interest were race/ethnicity, food insecurity, and their interactions.ResultsAmong 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 relevanceThis 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.
| S-EPMC8188266 | biostudies-literature
Project description:BackgroundCriteria for low-dose CT scan lung cancer screening vary across guidelines. Knowledge of the eligible pool across demographic groups can enable policy and programmatic decision-making, particularly for disproportionately affected populations.Research questionWhat are the eligibility rates for low-dose CT scan screening according to sex and race or ethnicity and how do these rates relate to corresponding lung cancer incidence rates?Study design and methodsThis was a cross-sectional study using data from the 2015 National Health Interview Survey adult and cancer control supplement files. In addition to eligibility rates, the ratio of the eligibility rate to the lung cancer incidence rate in a given population group (eligibility to incidence [E-I] ratio) also was determined. Guidelines assessed were: Centers for Medicare and Medicaid Services, National Comprehensive Cancer Network, and US Preventive Services Task Force current or with expansion of age and smoking or quit thresholds. We also assessed a risk model (PLCOM2012 risk model).ResultsTotal numbers eligible based on current guidelines ranged from 8.3 to 13.3 million, representing 8.3% to 13.4% of the US population 50 to 80 years of age, and up to 17.5 million with expanded criteria. Overall eligibility rates on average were about 10 percentage points higher for men than women. For both men and women, and both overall and among ever smokers, non-Hispanic Whites had the highest eligibility rates across all guidelines, followed generally by non-Hispanic Blacks, and then Asians and Hispanics. Among both men and women, non-Hispanic Whites had the highest E-I ratios across all guidelines; non-Hispanic Black men had higher lung cancer incidence, but 30% to 50% lower E-I ratios, than non-Hispanic White men.InterpretationScreening eligibility rates vary widely across guidelines, with disparities evident in E-I ratios, including among non-Hispanic Black men, despite higher lung cancer burden. Consideration of smoking duration in risk assessment criteria may address current disparities.
| S-EPMC8411441 | biostudies-literature
Project description:ObjectiveCOVID-19 and associated morbidity and mortality has disproportionately affected minoritized populations. The epidemiology of spread of COVID-19 among pregnant women by race/ethnicity is not well described. Using data from a large healthcare system in California, we estimated prevalence and spread during pregnancy and recommend a vaccination approach based on minimizing adverse outcomes.MethodsPatients delivering at Sutter Health are tested (molecular) for COVID-19. These results were combined with antibody test results, using samples drawn at delivery. For each racial/ethnic group, we estimated prevalence of COVID-19, using logistic regression to adjust for known sociodemographic and comorbid risk factors. Testing for immunoglobulin G and immunoglobulin M provided insight into timing of infections.ResultsAmong 17,446 women delivering May-December, 460 (2.6%) tested positive (molecular). Hispanic women were at 2.6 times the odds of being actively infected as White women (odds ratio = 2.6, 95% confidence interval = 2.0-3.3). August and December were the highest risk periods for active infection (odds ratio = 3.5, 95% confidence interval = 2.1-5.7 and odds ratio = 6.1, 95% confidence interval = 3.8-9.9, compared with May, respectively). Among 4500 women delivering October-December, 425 (9.4%) had positive molecular or antibody tests, ranging from 4.0% (Asian) to 15.7% (Hispanic). Adjusting for covariables, compared with White patients, odds of infection was similar for Black and Asian patients, with Hispanic at 2.4 (1.8-3.3) times the odds.ConclusionCOVID-19 prevalence was higher among Hispanic women at delivery and in the last trimester than their White counterparts. Higher rates in Black patients are explained by other risk factors. Resources should be directed to increase vaccination rates among Hispanic women in early stages of pregnancy.
| S-EPMC8669880 | biostudies-literature