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.
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.
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.
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.
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.
Project description:This study examined the association between preferences for being informed about the COVID-19 vaccine and where to receive it with vaccination intent and race/ethnicity. We conducted an online survey, oversampling Black and Latino panel members. The 1668 participants were 53.2% female, 34.8% White, 33.3% Black, and 31.8% Latino. Participants who were vaccine hesitant (answered "not sure" or "no" to vaccination intent) were more likely to prefer a conversation with their doctor compared to those who answered "yes" (25.0% and 23.4% vs 7.8%, P < .001, respectively). Among participants who responded "not sure", 61.8% prefer to be vaccinated at a doctor's office, compared with 35.2% of those who responded "yes" (P < .001). Preferred location differed by race/ethnicity (P < .001) with 67.6% of Black "not sure" participants preferring a doctor's office compared to 60.2% of Latino and 54.9% of White "not sure" participants. These findings underscore the need to integrate healthcare providers into COVID-19 vaccination programs.
Project description:ImportanceCOVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.ObjectiveTo evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.Data sourcesA systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021.Study selectionStudies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria.Data extraction and synthesisPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model.Main outcomes and measuresThe main measures were RRs, ORs, and combined prevalence values.ResultsA total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals (P < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals (P < .001) and African American individuals (P < .001).Conclusions and relevanceIn this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.
Project description:ObjectivesAlthough racial/ethnic disparities in healthcare have long been recognized, recent discourse around structural racism will hopefully lead to improved transparency surrounding these issues. Despite the disproportionate impact of COVID-19 on racial/ethnic minorities, the extent and reliability of race reporting in COVID research is unclear.MethodsCOVID-19 research published in three top medical journals during the first wave of the COVID-19 pandemic was reviewed and assessed for race reporting and proportional representation.ResultsOf the 95 manuscripts that were identified, 56 reporting on 252,262 patients met eligibility. Thirty-five (62.5%) did not report race distribution and 15 (26.7%) did not report ethnicity. There was no difference based on journal (P = 0.87), study sponsor (P = 0.41), whether the study was retrospective or prospective (P = 0.33), or observational vs interventional (P = 0.11). Studies with ≥250 patients were more likely to report on race (OR 4.01, 95% CI: 1.12-14.37, P = 0.027), and North American (USA and Canada) studies were more likely than European studies (OR 7.88, 95% CI: 1.73-37.68, P = 0.006) to report on race. COVID-19 research mirrored USA COVID-19 racial incidence; however, both showed higher distribution of COVID-19 infection among Blacks and a smaller proportion of Whites compared to the USA population. This suggests that research is broadly representing infection rates and that social determinants of health are impacting racial distribution of infection.ConclusionsDespite increasing awareness of racial disparities and inequity, COVID-19 research during the first wave of the pandemic lacked appropriate racial/ethnicity reporting. However, research mirrored COVID-19 incidence in the USA, with an increased burden of infection among Black individuals.
Project description:BackgroundDementia is often underdiagnosed and this problem is more common among some ethnoracial groups.ObjectiveThe objective of this study was to examine racial and ethnic disparities in the timeliness of receiving a clinical diagnosis of dementia.Research designThis was a prospective cohort study.SubjectsA total of 3966 participants age 70 years and above with probable dementia in the Health and Retirement Study, linked with their Medicare and Medicaid claims.MeasuresWe performed logistic regression to compare the likelihood of having a missed or delayed dementia diagnosis in claims by race/ethnicity. We analyzed dementia severity, measured by cognition and daily function, at the time of a dementia diagnosis documented in claims, and estimated average dementia diagnosis delay, by race/ethnicity.ResultsA higher proportion of non-Hispanic Blacks and Hispanics had a missed/delayed clinical dementia diagnosis compared with non-Hispanic Whites (46% and 54% vs. 41%, P<0.001). Fully adjusted logistic regression results suggested more frequent missed/delayed dementia diagnoses among non-Hispanic Blacks (odds ratio=1.12; 95% confidence interval: 0.91-1.38) and Hispanics (odds ratio=1.58; 95% confidence interval: 1.20-2.07). Non-Hispanic Blacks and Hispanics had a poorer cognitive function and more functional limitations than non-Hispanic Whites around the time of receiving a claims-based dementia diagnosis. The estimated mean diagnosis delay was 34.6 months for non-Hispanic Blacks and 43.8 months for Hispanics, compared with 31.2 months for non-Hispanic Whites.ConclusionsNon-Hispanic Blacks and Hispanics may experience a missed or delayed diagnosis of dementia more often and have longer diagnosis delays. When diagnosed, non-Hispanic Blacks and Hispanics may have more advanced dementia. Public health efforts should prioritize racial and ethnic underrepresented communities when promoting early diagnosis of dementia.
Project description:To efficiently estimate race/ethnicity using administrative records to facilitate health care organizations' efforts to address disparities when self-reported race/ethnicity data are unavailable.Surname, geocoded residential address, and self-reported race/ethnicity from 1,973,362 enrollees of a national health plan.We compare the accuracy of a Bayesian approach to combining surname and geocoded information to estimate race/ethnicity to two other indirect methods: a non-Bayesian method that combines surname and geocoded information and geocoded information alone. We assess accuracy with respect to estimating (1) individual race/ethnicity and (2) overall racial/ethnic prevalence in a population.The Bayesian approach was 74 percent more efficient than geocoding alone in estimating individual race/ethnicity and 56 percent more efficient in estimating the prevalence of racial/ethnic groups, outperforming the non-Bayesian hybrid on both measures. The non-Bayesian hybrid was more efficient than geocoding alone in estimating individual race/ethnicity but less efficient with respect to prevalence (p<.05 for all differences).The Bayesian Surname and Geocoding (BSG) method presented here efficiently integrates administrative data, substantially improving upon what is possible with a single source or from other hybrid methods; it offers a powerful tool that can help health care organizations address disparities until self-reported race/ethnicity data are available.