Skin Deep: Enhanced Variable May Help Explain Racial Disparities in Type 2 Diabetes and Prediabetes.
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ABSTRACT:
SUBMITTER: Lo CC
PROVIDER: S-EPMC5544614 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:PurposeTumors of the inner quadrants of the breast are associated with poorer survival than those of the upper-outer quadrant. It is unknown whether racial differences in breast cancer outcomes are modified by breast quadrant, in addition to comparisons among Asian subgroups.MethodsUsing the Surveillance, Epidemiology, and End Results database, we analyzed data among women diagnosed with non-metastatic invasive breast cancer between 1990 and 2014. We performed Cox proportional hazards regression models to assess the associations of race with breast cancer-specific survival and overall survival, stratified by breast quadrants. The models were adjusted for age, year of the diagnosis, tumor size, grade, histological type, tumor laterality, lymph node, estrogen receptor, progesterone receptor, and treatments.ResultsAmong 454,154 patients (73.0% White, 10.0% Black, 7.8% Asian/PI, and 9.2% Hispanic), 54.3% had tumors diagnosed in the upper-outer quadrant of the breast. Asian/PI women were more likely than White to have tumors diagnosed in the nipple/central portion of the breast and were less likely to have diagnosed in the upper-outer quadrant (P < 0.001), despite a similar distribution of breast quadrant between Black, Hispanic, and White women. Compared with White women, the multivariable-adjusted hazard ratios of breast cancer-specific mortality were 1.41 (95% CI 1.37-1.44) in Black women, 0.82 (95% CI 0.79-0.85) in Asian women, and 1.05 (95% CI 1.02-1.09) in Hispanic women. Among Asian subgroups, Japanese American women had a lower risk of breast cancer-specific mortality (HR = 0.68, 95% CI 0.62-0.74) compared with White women. Overall survival was similar to breast cancer-specific survival in each race group. The race-associated risks did not vary significantly by breast quadrants for breast cancer-specific mortality and all-cause mortality.ConclusionsDifferences in breast cancer survival by race could not be attributed to tumor locations. Understanding the cultural, biological, and lifestyle factors that vary between White, African American, and ethnic subgroups of Asian American women may help explain these survival differences.
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Project description:ObjectiveTo estimate the impact of different forms of Medicaid managed care (MMC) delivery on racial and ethnic disparities in utilization.Data sourceLongitudinal, administrative data on 101,649 children in Kentucky continuously enrolled in Medicaid between January 1997 and June 1999. Outcomes considered are monthly professional, outpatient, and inpatient utilization.Study designWe apply an intent-to-treat, instrumental variables analysis using the staggered geographic implementation of MMC to create treatment and control groups of children.Principal findingsThe implementation of MMC reduced monthly professional visits by a smaller degree for non-whites than whites (3.8 percentage points vs. 6.2 percentage points), thereby helping to equalize the initial racial/ethnic disparity in utilization. The Passport MMC program in the Louisville-centered region statistically significantly reduced disparities for professional visits (closing the gap by 8.0 percentage points), while the Kentucky Health Select MMC program in the Lexington-centered region did not. No substantive impact on disparities was found for either outpatient or inpatient utilization in either program.ConclusionsWe find evidence that MMC has the possibility to reduce racial/ethnic disparities in professional utilization. More work is needed to determine which managed care program characteristics drive this result.
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Project description:BACKGROUND: Primary-care clinicians can play an important role in reducing racial disparities in diabetes care. OBJECTIVE: The objective of the study is to determine the views of primary-care clinicians regarding racial disparities in diabetes care. DESIGN: The design of the study is through a survey of primary-care clinicians (response rate = 86%). PARTICIPANTS: The participants of the study were 115 physicians and 54 nurse practitioners and physician assistants within a multisite group practice in 2007. MEASUREMENTS AND MAIN RESULTS: We identified sociodemographic characteristics of each clinician's diabetic patient panel. We fit multivariable logistic regression models to identify predictors of supporting the collection of data on patients' race and acknowledging the existence of racial disparities among patients personally treated. Among respondents, 79% supported the collection of data on patients' race. Whereas 88% acknowledged the existence of racial disparities in diabetes care within the U.S. health system, only 40% reported their presence among patients personally treated. Clinicians caring for greater than or equal to 50% minority patients were more likely to support collection of patient race data (adjusted odds ratio [OR] 9.0; 95% confidence interval [CI] 1.2-65.0) and report the presence of racial disparities within their patient panel (adjusted OR 12.0; 95% CI 2.5-57.7). Clinicians were more likely to perceive patient factors than physician or health system factors as mediators of racial disparities; however, most supported interventions such as increasing clinician awareness (84%) and cultural competency training (88%). CONCLUSIONS: Most primary-care clinicians support the collection of data on patients' race, but increased awareness about racial disparities at the local level is needed as part of a targeted effort to improve health care for minority patients.
| S-EPMC2324133 | biostudies-other
Project description:Racial/ethnic minorities have experienced higher COVID-19 infection rates than whites, but it is unclear how individual-level housing, occupational, behavioral, and socioeconomic conditions contribute to these disparities in a nationally representative sample. In this study, we assess the extent to which social determinants of health contribute to racial/ethnic differences in COVID-19 infection. Data are from the Understanding America Study's Understanding Coronavirus in America survey (UAS COVID-19 waves 7-29). UAS COVID-19 is one of the only nationally representative longitudinal data sources that collects information on household, work, and social behavioral context during the pandemic. We analyze onset of COVID-19 cases, defined as a positive test or a diagnosis of COVID-19 from a healthcare provider since the previous survey wave, over a year of follow-up (June 2020-July 2021). We consider educational attainment, economic resources, work arrangements, household size, and social distancing as key social factors that may be structured by racism. Cox hazard models indicate that Hispanic people have 48% higher risk of experiencing a COVID-19 infection than whites after adjustment for age, sex, local infection rate, and comorbidities, but we do not observe a higher risk of COVID-19 among Black respondents. Controlling for engagement in any large or small social gathering increases the hazard ratio for Hispanics by 9%, suggesting that had Hispanics had the same social engagement patterns as whites, they may have had even higher risk of COVID-19. Other social determinants-lower educational attainment, working away from home, and number of coresidents-all independently predict higher risk of COVID-19, but do not explain why Hispanic Americans have higher COVID-19 infection risk than whites.
| S-EPMC9162789 | biostudies-literature
Project description:Despite ethical and historical arguments for removing race from clinical algorithms, the consequences of removal remain unclear. Here, we highlight a largely undiscussed consideration in this debate: varying data quality of input features across race groups. For example, family history of cancer is an essential predictor in cancer risk prediction algorithms but is less reliably documented for Black participants and may therefore be less predictive of cancer outcomes. Using data from the Southern Community Cohort Study, we assessed whether race adjustments could allow risk prediction models to capture varying data quality by race, focusing on colorectal cancer risk prediction. We analyzed 77,836 adults with no history of colorectal cancer at baseline. The predictive value of self-reported family history was greater for White participants than for Black participants. We compared two cancer risk prediction algorithms-a race-blind algorithm which included standard colorectal cancer risk factors but not race, and a race-adjusted algorithm which additionally included race. Relative to the race-blind algorithm, the race-adjusted algorithm improved predictive performance, as measured by goodness of fit in a likelihood ratio test (P-value: <0.001) and area under the receiving operating characteristic curve among Black participants (P-value: 0.006). Because the race-blind algorithm underpredicted risk for Black participants, the race-adjusted algorithm increased the fraction of Black participants among the predicted high-risk group, potentially increasing access to screening. More broadly, this study shows that race adjustments may be beneficial when the data quality of key predictors in clinical algorithms differs by race group.
| S-EPMC11348319 | biostudies-literature
Project description:BackgroundInvasive community-associated methicillin-resistant Staphylococcus aureus (MRSA) incidence in the United States is higher among black persons than white persons. We explored the extent to which socioeconomic factors might explain this racial disparity.MethodsA retrospective cohort was based on the Centers for Disease Control and Prevention's Emerging Infections Program surveillance data for invasive community-associated MRSA cases (isolated from a normally sterile site of an outpatient or on hospital admission day ≤3 in a patient without specified major healthcare exposures) from 2009 to 2011 in 33 counties of 9 states. We used generalized estimating equations to determine census tract-level factors associated with differences in MRSA incidence and inverse odds ratio-weighted mediation analysis to determine the proportion of racial disparity mediated by socioeconomic factors.ResultsAnnual invasive community-associated MRSA incidence was 4.59 per 100000 among whites and 7.60 per 100000 among blacks (rate ratio [RR], 1.66; 95% confidence interval [CI], 1.52-1.80). In the mediation analysis, after accounting for census tract-level measures of federally designated medically underserved areas, education, income, housing value, and rural status, 91% of the original racial disparity was explained; no significant association of black race with community-associated MRSA remained (RR, 1.05; 95% CI, .92-1.20).ConclusionsThe racial disparity in invasive community-associated MRSA rates was largely explained by socioeconomic factors. The specific factors that underlie the association between census tract-level socioeconomic measures and MRSA incidence, which may include modifiable social (eg, poverty, crowding) and biological factors (not explored in this analysis), should be elucidated to define strategies for reducing racial disparities in community-associated MRSA rates.
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Project description:PurposeRacism, whether defined at individual, interpersonal, or structural levels, is associated with poor health among Blacks. This association may arise because exposure to racism causes poor health, but geographic mobility patterns pose an alternative explanation-namely, Black individuals with better health and resources can move away from racist environments.MethodsWe examine the evidence for selection effects using nationally representative, longitudinal data (1990-2009) from the Panel Study on Income Dynamics (n = 33,852). We conceptualized state-level racial animus as an ecologic measure of racism and operationalized it as the percent of racially-charged Google search terms in each state.ResultsAmong those who move out of state, Blacks reporting good self-rated health (SRH) are more likely to move to a state with less racial animus than Blacks reporting poor SRH (P = .01), providing evidence for at least some selection into environments with less racial animus. However, among Blacks who moved states, over 80% moved to a state within the same quartile of racial animus, and fewer than 5% resided in states with the lowest level of racial animus.ConclusionsGeographic mobility patterns are therefore likely to explain only a small part of the relationship between racial animus and SRH. These results require replication with alternative measures of racist attitudes and health outcomes.
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Project description:ObjectiveTo examine racial/ethnic disparities in the prevalence of diabetes and prediabetes by BMI category.Research design and methodsIn a consortium of three U.S. integrated health care systems, 4,906,238 individuals aged ≥20 years during 2012-2013 were included. Diabetes and prediabetes were ascertained by diagnosis and laboratory results; antihyperglycemic medications were also included for diabetes ascertainment.ResultsThe age-standardized diabetes and prediabetes prevalence estimates were 15.9% and 33.4%, respectively. Diabetes but not prediabetes prevalence increased across BMI categories among all racial/ethnic groups (P for trend < 0.001). Racial/ethnic minorities reached a given diabetes prevalence at lower BMIs than whites; Hawaiians/Pacific Islanders and Asians had a diabetes prevalence of 24.6% (95% CI 24.1-25.2%) in overweight and 26.5% (26.3-26.8%) in obese class 1, whereas whites had a prevalence of 23.7% (23.5-23.8%) in obese class 2. The age-standardized prediabetes prevalence estimates in overweight among Hispanics (35.6% [35.4-35.7%]), Asians (38.1% [38.0-38.3%]), and Hawaiians/Pacific Islanders (37.5% [36.9-38.2%]) were similar to those in obese class 4 among whites (35.3% [34.5-36.0%]), blacks (36.8% [35.5-38.2%]), and American Indians/Alaskan Natives (34.2% [29.6-38.8%]). In adjusted models, the strength of association between BMI and diabetes was highest among whites (relative risk comparing obese class 4 with normal weight 7.64 [95% CI 7.50-7.79]) and lowest among blacks (3.16 [3.05-3.27]). The association between BMI and prediabetes was less pronounced.ConclusionsRacial/ethnic minorities had a higher burden of diabetes and prediabetes at lower BMIs than whites, suggesting the role of factors other than obesity in racial/ethnic disparities in diabetes and prediabetes risk and highlighting the need for tailored screening and prevention strategies.
| S-EPMC6868463 | biostudies-literature
Project description:Background: Recent studies highlight racial-ethnic disparities in insulin pump and continuous glucose monitor (CGM) use in people with type 1 diabetes (T1D), but drivers of disparities remain poorly understood beyond socioeconomic status (SES). Methods: We recruited a diverse sample of young adults (YA) with T1D from six diabetes centers across the United States, enrolling equal numbers of non-Hispanic (NH) White, NH Black, and Hispanic YA. We used multivariate logistic regression to examine to what extent SES, demographics, health care factors (care setting, clinic attendance), and diabetes self-management (diabetes numeracy, self-monitoring of blood glucose, and Self-Care Inventory score) explained insulin pump and CGM use in each racial-ethnic group. Results: We recruited 300 YA with T1D, aged 18-28 years. Fifty-two percent were publicly insured, and the mean hemoglobin A1c was 9.5%. Large racial-ethnic disparities in insulin pump and CGM use existed: 72% and 71% for NH White, 40% and 37% for Hispanic, and 18% and 28% for NH Black, respectively. After multiple adjustment, insulin pump and CGM use remained disparate: 61% and 53% for NH White, 49% and 58% for Hispanic, and 20 and 31% for NH Black, respectively. Conclusions: Insulin pump and CGM use was the lowest in NH Black, intermediate in Hispanic, and highest in NH White YA with T1D. SES was not the sole driver of disparities nor did additional demographic, health care, or diabetes-specific factors fully explain disparities, especially between NH Black and White YA. Future work should examine how minority YA preferences, provider implicit bias, systemic racism, and mistrust of medical systems help to explain disparities in diabetes technology use.
| S-EPMC7994432 | biostudies-literature