Dataset Information

Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California.

ABSTRACT: With a population of forty million and substantial geographic variation in sociodemographics and health services, California is an important setting in which to study disparities. Its population (37.5 percent White, 39.1 percent Latino, 5.3 percent Black, and 14.4 percent Asian) experienced 59,258 COVID-19 deaths through April 14, 2021-the most of any state. We analyzed California's racial/ethnic disparities in COVID-19 exposure risks, testing rates, test positivity, and case rates through October 2020, combining data from 15.4 million SARS-CoV-2 tests with subcounty exposure risk estimates from the American Community Survey. We defined "high-exposure-risk" households as those with one or more essential workers and fewer rooms than inhabitants. Latino people in California are 8.1 times more likely to live in high-exposure-risk households than White people (23.6 percent versus 2.9 percent), are overrepresented in cumulative cases (3,784 versus 1,112 per 100,000 people), and are underrepresented in cumulative testing (35,635 versus 48,930 per 100,000 people). These risks and outcomes were worse for Latino people than for members of other racial/ethnic minority groups. Subcounty disparity analyses can inform targeting of interventions and resources, including community-based testing and vaccine access measures. Tracking COVID-19 disparities and developing equity-focused public health programming that mitigates the effects of systemic racism can help improve health outcomes among California's populations of color.

SUBMITTER: Reitsma MB

PROVIDER: S-EPMC8458028 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California.

Reitsma Marissa B MB Claypool Anneke L AL Vargo Jason J Shete Priya B PB McCorvie Ryan R Wheeler William H WH Rocha David A DA Myers Jennifer F JF Murray Erin L EL Bregman Brooke B Dominguez Deniz M DM Nguyen Alyssa D AD Porse Charsey C Fritz Curtis L CL Jain Seema S Watt James P JP Salomon Joshua A JA Goldhaber-Fiebert Jeremy D JD

Health affairs (Project Hope) 20210512 6

With a population of forty million and substantial geographic variation in sociodemographics and health services, California is an important setting in which to study disparities. Its population (37.5 percent White, 39.1 percent Latino, 5.3 percent Black, and 14.4 percent Asian) experienced 59,258 COVID-19 deaths through April 14, 2021-the most of any state. We analyzed California's racial/ethnic disparities in COVID-19 exposure risks, testing rates, test positivity, and case rates through Octob ...[more]

PMID: 33979192

Similar Datasets

Project description:BackgroundIn California, >29,000 residents in skilled nursing facility (SNFs) were diagnosed with novel coronavirus disease 2019 (COVID-19) between March 2020 and November 2020. Prior research suggests that SNFs serving racially and ethnically minoritized residents often have fewer resources and lower quality of care. We performed a cross-sectional analysis of COVID-19 incidence among residents in California SNFs, assessing the association of SNF-level racial and ethnic compositions and facility- and neighborhood-level (census tract- and county-level) indicators of socioeconomic status (SES).MethodsSNFs were grouped based on racial and ethnic composition using data from the Centers for Medicare and Medicaid Services; categories included SNFs with ≥88% White residents, SNFs with ≥32% Black or Latinx residents, SNFs with ≥32% Asian residents, or SNFs not serving a high proportion of any racial and ethnic composition (mixed). SNF resident-level COVID-19 infection data were obtained from the National Healthcare Safety Network from May 25, 2020 to August 16, 2020. Multilevel mixed-effects negative binomial regressions were used to estimate incidence rate ratios (IRR) for confirmed COVID-19 infections among residents.ResultsAmong 971 SNFs included in our sample, 119 (12.3%) had ≥88% White residents; 215 (22.1%) had ≥32% Black or Latinx residents; 78 (8.0%) had ≥32% Asian residents; and 559 (57.6%) were racially and ethnically mixed. After adjusting for confounders, SNFs with ≥32% Black or Latinx residents (IRR = 2.40 [95% CI = 1.56, 3.68]) and SNFs with mixed racial and ethnic composition (IRR = 2.12 [95% CI = 1.49, 3.03]) both had higher COVID-19 incidence rates than SNFs with ≥88% White residents. COVID-19 incidence rates were also found to be higher in SNFs with low SES neighborhoods compared to those in high SES neighborhoods.ConclusionPublic health personnel should consider SNF- and neighborhood-level factors when identifying facilities to prioritize for COVID-19 outbreak prevention and control.

Project description:BackgroundMechanisms underlying racial and ethnic disparities in robot-assisted radical prostatectomy (RARP) vs open radical prostatectomy (ORP) are unclear. We sought to test 2 physician-level hypotheses: 1) Segregated Treatment and 2) Differential Treatment.MethodsThis observational study used the New York State Cancer Registry linked to discharge records and included patients undergoing radical prostatectomy for localized prostate cancer from October 1, 2008 to December 31, 2018. For hypothesis 1, we examined the association between patient race and ethnicity and treating surgeon RARP use (high-use surgeons, low-use surgeons, and surgeons at non-RARP facilities). For hypothesis 2, we determined the association between patient race and ethnicity and receipt of RARP when matching on treating surgeon, age, year of procedure, and Gleason group. We explored the role of insurance in both analyses.ResultsThis study included 18 926 patients (8.0% Hispanic, 16.9% non-Hispanic Black, 75.1% non-Hispanic White), with a mean age of 60.4 ± 7.1 years. Compared with non-Hispanic White patients, Hispanic and non-Hispanic Black patients had higher odds of being treated by low-RARP-use surgeons (odds ratio [OR] = 2.16, 95% confidence interval [CI] = 1.20 to 3.88; OR = 1.76, 95% CI = 1.06 to 2.94, respectively) and by surgeons at non-RARP facilities (OR = 4.19, 95% CI = 2.18 to 8.07; OR = 4.60, 95% CI = 2.58 to 8.23, respectively). In the matched cohorts, Hispanic and non-Hispanic Black patients were less likely to receive RARP than non-Hispanic White patients (OR = 0.78, 95% CI = 0.62 to 0.98; OR = 0.75, 95% CI = 0.57 to 1.00, respectively). These associations were partially attenuated after accounting for insurance.ConclusionsRacial and ethnic disparities in RARP use are related to patients being treated by different surgeons and treated differently by the same surgeons. Identifying and addressing multilevel barriers to equitable surgical treatment is needed to reduce disparities among prostate cancer patients.

Project description:ImportanceThe US aging population is rapidly becoming more racially and ethnically diverse. Early diagnosis of dementia is a health care priority.ObjectiveTo examine the associations between race/ethnicity and timeliness of dementia diagnosis and comprehensiveness of diagnostic evaluation.Design, setting, and participantsThis retrospective cross-sectional study used 2013-2015 California Medicare fee-for-service data to examine the associations of race/ethnicity, individual factors, and contextual factors with the timeliness and comprehensiveness of dementia diagnosis. Data from 10 472 unique beneficiaries were analyzed. The sample was selected on the basis of the following criteria: presence of 1 or more claims; no diagnoses of dementia or mild cognitive impairment in 2013 to 2014; continuous enrollment in Medicare Parts A and B; Asian, Black, Hispanic, or White race/ethnicity; and incident diagnoses of dementia or mild cognitive impairment in January through June 2015. Data analyses were conducted from November 1, 2019, through November 10, 2020.Main outcomes and measuresTimeliness of diagnosis, defined as incident diagnosis of mild cognitive impairment vs dementia, and comprehensiveness of diagnostic evaluation, defined as presence of the following services in claims within 6 months before or after the incident diagnosis date: specialist evaluation, laboratory testing, and neuroimaging studies.ResultsThe sample comprised 10 472 unique Medicare beneficiaries with incident diagnoses of dementia or mild cognitive impairment (6504 women [62.1%]; mean [SD] age, 82.9 [8.0] years) and included 993 individuals who identified as Asian (9.5%), 407 as Black (3.9%), 1255 as Hispanic (12.0%), and 7817 as White (74.6%). Compared with White beneficiaries, those who identified as Asian (odds ratio, 0.46; 95% CI, 0.38-0.56), Black (odds ratio, 0.73; 95% CI, 0.56-0.94), or Hispanic (odds ratio, 0.62; 95% CI, 0.52-0.72) were less likely to receive a timely diagnosis. Asian beneficiaries (incidence rate ratio, 0.81; 95% CI, 0.74-0.87) also received fewer diagnostic evaluation elements. These associations remained significant after adjusting for age, sex, comorbidity burden, neighborhood disadvantage, and rurality.Conclusions and relevanceThese findings highlight substantial disparities in the timeliness and comprehensiveness of dementia diagnosis. Public health interventions are needed to achieve equitable care for people living with dementia across all racial/ethnic groups.

Project description:BackgroundPostpartum readmission is an important indicator of postpartum morbidity. The likelihood of postpartum readmission is highest for Black individuals. However, it is unclear whether the likelihood of postpartum readmission has changed over time according to race/ethnicity. Little is also known about the factors that contribute to these trends.ObjectiveThis study aimed to: (1) examine trends in postpartum readmission by race/ethnicity, (2) examine if prenatal or clinical factors explain the trends, and (3) investigate if racial/ethnic disparities changed over time.Study designWe examined trends in postpartum readmission, defined as hospitalization within 42 days after birth hospitalization discharge, using live birth and fetal death certificates linked to delivery discharge records from 10,711,289 births in California from 1997 to 2018. We used multivariable logistic regression models that included year and year-squared (to allow for nonlinear trends), overall and stratified by race/ethnicity, to estimate the annual change in postpartum readmission during the study period, represented by odds ratios and 95% confidence intervals. We then adjusted models for prenatal (eg, patient demographics) and clinical (eg, gestational age, mode of birth) factors. To determine whether racial/ethnic disparities changed over time, we calculated risk ratios for 1997 and 2018 by comparing the predicted probabilities from the race-specific, unadjusted logistic regression models.ResultsThe overall incidence of postpartum readmission was 10 per 1000 births (17.4/1000 births for non-Hispanic Black, 10/1000 for non-Hispanic White, 7.9/1000 for non-Hispanic Asian/Pacific Islander, and 9.6/1000 for Hispanic individuals). Odds of readmission increased for all groups during the study period; the increase was greatest for Black individuals (42% vs 21%-29% for the other groups). After adjustment for prenatal and clinical factors, the increase in odds was similar for Black and White individuals (12%). The disparity in postpartum readmission rates relative to White individuals increased for Black individuals (risk ratio, 1.68 in 1997 and 1.90 in 2018) and more modestly for Hispanic individuals (risk ratio, 1.02 in 1997 and 1.05 in 2018) during the study period. Asian/Pacific Islander individuals continued to have lower risk than White individuals during the study period (risk ratio, 0.87 in 1997 and 0.82 in 2018).ConclusionThe rate of postpartum readmissions increased from 1997 to 2018 in California across all racial/ethnic groups, with the greatest increase observed for Black individuals. Racial/ethnic differences in the trend were more modest after adjustment for prenatal and clinical factors. It is important to find ways to prevent further increases in postpartum readmission, especially among groups at highest risk.

Dataset Information

Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California.

Publications

Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets