Glossary of terms relating to ethnicity and race: for reflection and debate.
Ontology highlight
ABSTRACT:
SUBMITTER: Bhopal R
PROVIDER: S-EPMC1732794 | biostudies-literature | 2004 Jun
REPOSITORIES: biostudies-literature
Publications
Glossary of terms relating to ethnicity and race: for reflection and debate.
Journal of epidemiology and community health 20040601 6
This glossary focuses on the concepts and terminology used in the study of the health of minority ethnic and racial groups. It is hoped that it will stimulate debate on this subject so that an internationally applicable glossary may emerge. ...[more]
Similar Datasets
Project description:ObjectiveTo improve an existing method, Medicare Bayesian Improved Surname Geocoding (MBISG) 1.0 that augments the Centers for Medicare & Medicaid Services' (CMS) administrative measure of race/ethnicity with surname and geographic data to estimate race/ethnicity.Data sources/study settingData from 284 627 respondents to the 2014 Medicare CAHPS survey.Study designWe compared performance (cross-validated Pearson correlation of estimates and self-reported race/ethnicity) for several alternative models predicting self-reported race/ethnicity in cross-sectional observational data to assess accuracy of estimates, resulting in MBISG 2.0. MBISG 2.0 adds to MBISG 1.0 first name, demographic, and coverage predictors of race/ethnicity and uses a more flexible data aggregation framework.Data collection/extraction methodsWe linked survey-reported race/ethnicity to CMS administrative and US census data.Principal findingsMBISG 2.0 removed 25-39 percent of the remaining MBISG 1.0 error for Hispanics, Whites, and Asian/Pacific Islanders (API), and 9 percent for Blacks, resulting in correlations of 0.88 to 0.95 with self-reported race/ethnicity for these groups.ConclusionsMBISG 2.0 represents a substantial improvement over MBISG 1.0 and the use of CMS administrative data on race/ethnicity alone. MBISG 2.0 is used in CMS' public reporting of Medicare Advantage contract HEDIS measures stratified by race/ethnicity for Hispanics, Whites, API, and Blacks.
| S-EPMC6338295 | biostudies-literature
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.
| S-EPMC2653886 | biostudies-other
Project description:ObjectiveWe aimed to address deficiencies in structured electronic health record (EHR) data for race and ethnicity by identifying black and Hispanic patients from unstructured clinical notes and assessing differences between patients with or without structured race/ethnicity data.Materials and methodsUsing EHR notes for 16 665 patients with encounters at a primary care practice, we developed rule-based natural language processing (NLP) algorithms to classify patients as black/Hispanic. We evaluated performance of the method against an annotated gold standard, compared race and ethnicity between NLP-derived and structured EHR data, and compared characteristics of patients identified as black or Hispanic using only NLP vs patients identified as such only in structured EHR data.ResultsFor the sample of 16 665 patients, NLP identified 948 additional patients as black, a 26%increase, and 665 additional patients as Hispanic, a 20% increase. Compared with the patients identified as black or Hispanic in structured EHR data, patients identified as black or Hispanic via NLP only were older, more likely to be male, less likely to have commercial insurance, and more likely to have higher comorbidity.DiscussionStructured EHR data for race and ethnicity are subject to data quality issues. Supplementing structured EHR race data with NLP-derived race and ethnicity may allow researchers to better assess the demographic makeup of populations and draw more accurate conclusions about intergroup differences in health outcomes.ConclusionsBlack or Hispanic patients who are not documented as such in structured EHR race/ethnicity fields differ significantly from those who are. Relatively simple NLP can help address this limitation.
| S-EPMC6696506 | biostudies-literature
Project description:To investigate race differences in retrospectively-reported early smoking experiences, we studied African-American (n=48) and Caucasian (n=155) current smokers who participated in a study designed to identify phenotypic and genotypic factors associated with smoking. Compared with Caucasian smokers, African-American smokers were less educated (mean+/-s.e.m.: 13.3+/-0.25 vs. 14.3 +/- 0.16; p<.01), had higher BMI (28.9+/-1.06 vs. 26.7+/-0.52; p<.05), and smoked significantly fewer cigarettes/day (14.1+/-1.00 vs. 18.4+/-0.74; p<.01). Ninety percent of African-American smokers consumed menthol cigarettes, as opposed to 25% of Caucasian smokers. African-American smokers were significantly older than Caucasian smokers upon initial smoking experimentation (17.4+/-1.1 vs. 14.7+/-0.3; p<.05) and onset of regular smoking (19.7+/-0.9 vs. 17.4+/-0.4; p<.05). African-American smokers were significantly more likely than Caucasian smokers to endorse global pleasurable sensations (48% vs. 30%; p<.05), "pleasurable rush or buzz" (62% vs. 43%; p<.05), and "relaxing" (45% vs. 27%; p<.05) as early experiences with smoking, whereas Caucasian smokers were marginally more likely to report dizziness and difficulty inhaling (61% vs. 45%; p<.10 and 48% vs. 31%; p<.10, respectively). Caucasian smokers were significantly more likely to endorse friends (6.9+/-0.2 vs. 4.8+/-0.4; p<.0001) and "perk me up" (4.2+/-0.3 vs. 3.1+/-0.4; p<.05) and marginally more likely to endorse buzz (4.2+/-0.2 vs. 3.4+/-0.5; p<.10) as reasons for starting to smoke. Further research is needed to determine the relative contributions of genetic, developmental, and socio-cultural factors to these findings.
| S-EPMC2753519 | biostudies-literature
Project description:Over 80% of bias-motivated violent victimization is motivated by race or ethnicity and over 50% of bias victimization occurs in non-Hispanic Whites (NHW). Our aim was to determine the risk and health impacts of race/ethnicity-motivated violent victimization by victim race/ethnicity. We examined data from the National Crime Victimization Survey (2003-2015) to estimate violent victimization risk by victim race/ethnicity across race/ethnicity bias victimization, other types of bias victimizations, and non-bias violent victimizations. We examined incident and offender characteristics for race/ethnicity-motivated victimization by victim race/ethnicity. The risk of race/ethnicity-motivated violent victimization was greater for non-Hispanic Blacks (NHB) and Hispanics than for NHWs (incidence rate ratios [IRR] = 1.4; 95% confidence interval [CI] = [1.0, 2.0], and IRR = 1.6; 95% CI = [1.2, 2.1]). This translates into an additional 46.7 incidents per 100,000 person-years (95% CI = [1.4, 92.1]) for the NHB population and an additional 60.3 incidents per 100,000 person-years (95% CI = [20.3, 100.4]) for the Hispanic population. Violent incidents for NHB victims more frequently resulted in injury or medical care. Nearly 40% of NHB victims reported difficulties at school or work related to the incident where only 21.5% of NHWs and 11.7% of Hispanic victims reported similar problems. Roughly 37% of NHB victims identified a NHW offender and 45% of NHW victims identified a NHB offender. Hispanic victims identified NHB or NHW offenders in over 70% of incidents. Although literature suggests that NHWs account for the majority of bias victimizations, the risk of non-fatal violent victimization motivated by race/ethnicity is greater for NHBs and Hispanics. Crimes perpetrated against NHBs are likely more severe and victim/offender racial incongruity is common. Findings provide empiric evidence on race/ethnicity-related structural disadvantage with adverse health consequences.
| S-EPMC6579725 | biostudies-literature
Project description:We investigated the association between a U.S. National Institutes of Health (NIH) R01 applicant's self-identified race or ethnicity and the probability of receiving an award by using data from the NIH IMPAC II grant database, the Thomson Reuters Web of Science, and other sources. Although proposals with strong priority scores were equally likely to be funded regardless of race, we find that Asians are 4 percentage points and black or African-American applicants are 13 percentage points less likely to receive NIH investigator-initiated research funding compared with whites. After controlling for the applicant's educational background, country of origin, training, previous research awards, publication record, and employer characteristics, we find that black applicants remain 10 percentage points less likely than whites to be awarded NIH research funding. Our results suggest some leverage points for policy intervention.
| S-EPMC3412416 | biostudies-literature
Project description:Study objectivesGrowing evidence indicates sleep is a major public health issue. Race/ethnicity and socioeconomics may contribute to sleep problems. This study assessed whether sleep symptoms were more prevalent among minorities and/or the socioeconomically disadvantaged.DesignCross-sectional.SettingEpidemiologic survey.Patients or participants2007-2008 National Health and Nutrition Examination Survey (N = 4,081).InterventionsNone.Measurements and resultsSociodemographics included age, sex, race/ethnicity, marital status, and immigration. Socioeconomics included poverty, education, private insurance, and food insecurity. Sleep symptoms assessed were sleep latency > 30 min, difficulty falling asleep, sleep maintenance difficulties, early morning awakenings, non-restorative sleep, daytime sleepiness, snorting/gasping, and snoring. Decreased reported problems for most symptoms were found among minorities, immigrants, and lower education levels. In general, in fully adjusted models, long sleep latency was associated with female gender, being black/African American, lower education attainment, no private insurance, and food insecurity. Difficulty falling asleep, sleep maintenance difficulties, early morning awakenings, and non-restorative sleep were also associated with female gender and food insecurity. Daytime sleepiness was seen in female and divorced respondents. Snorting/gasping was more prevalent among male, other-Hispanic/Latino, and 9(th)- to 11(th)-grade-level respondents. Snoring was prevalent among male, other-Hispanic/Latino, less-educated, and food-insecure respondents.ConclusionsSleep symptoms were associated with multiple sociodemographic and economic factors, though these relationships differed by predictor and sleep outcome. Also, reports depended on question wording.
| S-EPMC3746717 | biostudies-literature
Project description:Importance:Severe morbidity in very preterm infants is associated with profound clinical implications on development and life-course health. However, studies of racial/ethnic disparities in severe neonatal morbidities are scant and suggest that these disparities are modest or null, which may be an underestimation resulting from the analytic approach used. Objective:To estimate racial/ethnic differences in severe morbidities among very preterm infants. Design, Setting, and Participants:This population-based retrospective cohort study was conducted in New York City, New York, using linked birth certificate, mortality data, and hospital discharge data from January 1, 2010, through December 31, 2014. Infants born before 24 weeks' gestation, with congenital anomalies, and with missing data were excluded. Racial/ethnic disparities in very preterm birth morbidities were estimated through 2 approaches, conventional analysis and fetuses-at-risk analysis. The conventional analysis used log-binomial regression to estimate the relative risk of 4 severe neonatal morbidities for the racial/ethnic groups. For the fetuses-at-risk analysis, Cox proportional hazards regression with death as competing risk was used to estimate subhazard ratios associating race/ethnicity with each outcome. Estimates were adjusted for sociodemographic factors and maternal morbidities. Data were analyzed from September 5, 2017, to May 21, 2018. Main Outcomes and Measures:Four morbidity outcomes were defined using International Classification of Diseases, Ninth Revision, diagnosis and procedure codes: necrotizing enterocolitis, intraventricular hemorrhage, bronchopulmonary dysplasia, and retinopathy of prematurity. Results:In total, 582 297 infants were included in this study. Of these infants, 285 006 were female (48.9%) and 297 291 were male (51.0%). Using the conventional approach in the very preterm birth subcohort, black compared with white infants had an increased risk of only bronchopulmonary dysplasia (adjusted risk ratio [aRR], 1.34; 95% CI, 1.09-1.64) and a borderline increased risk of necrotizing enterocolitis (aRR, 1.39; 95% CI, 1.00-1.93). Hispanic infants had a borderline increased risk of necrotizing enterocolitis (aRR, 1.39; 95% CI, 0.98-1.96), and Asian infants had an increased risk of retinopathy of prematurity (aRR, 1.85; 95% CI, 1.15-2.97). In the fetuses-at-risk analysis, black infants had a 4.40 times higher rate of necrotizing enterocolitis (95% CI, 2.98-6.51), a 2.73 times higher rate of intraventricular hemorrhage (95% CI, 1.63-4.57), a 4.43 times higher rate of bronchopulmonary dysplasia (95% CI, 2.88-6.81), and a 2.98 times higher rate of retinopathy of prematurity (95% CI, 2.01-4.40). Hispanic infants had an approximately 2 times higher rate for all outcomes, and Asian infants had increased risk only for retinopathy of prematurity (adjusted hazard ratio, 2.43; 95% CI, 1.43-4.11). Conclusions and Relevance:In this study, racial/ethnic disparities in neonatal morbidities among very preterm infants appear to be sizable, but may have been underestimated in previous studies, and may have implications for the future. Understanding these racial/ethnic disparities is important, as they may contribute to inequalities in health and development later in the child's life.
| S-EPMC6248139 | biostudies-other
Project description:The Centers for Medicare and Medicaid Services recently released a five star rating system as part of 'Dialysis Facility Compare' to help patients identify and choose high performing clinics in the US. Eight dialysis-related measures determine ratings. Little is known about the association between surrounding community sociodemographic characteristics and star ratings. Using data from the U.S. Census and over 6000 dialysis clinics across the country, we examined the association between dialysis clinic star ratings and characteristics of the local population: 1) proportion of population below the federal poverty level (FPL); 2) proportion of black individuals; and 3) proportion of Hispanic individuals, by correlation and regression analyses. Secondary analyses with Quality Incentive Program (QIP) scores and population characteristics were also performed. We observed a negligible correlation between star ratings and the proportion of local individuals below FPL; Spearman coefficient, R = -0.09 (p<0.0001), and a stronger correlation between star ratings and the proportion of black individuals; R = -0.21 (p<0.0001). Ordered logistic regression analyses yielded adjusted odds ratio of 0.91 (95% confidence interval [0.80-1.30], p = 0.12) and 0.55 ([0.48-0.63], p<0.0001) for high vs. low level of proportion below FPL and proportion of black individuals, respectively. In contrast, a near-zero correlation was observed between star ratings and the proportion of Hispanic individuals. Correlations varied substantially by country region, clinic profit status and clinic size. Analyses using clinic QIP scores provided similar results. Sociodemographic characteristics of the surrounding community, factors typically outside of providers' direct control, have varying levels of association with clinic dialysis star ratings.
| S-EPMC5645143 | biostudies-literature
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.
| S-EPMC8221824 | biostudies-literature