RACE'' TO PROBE WHITE ADVANTAGES
Camara Phyllis JonesBenedict I. TrumanLaurie D. Elam–EvansCamille A. JonesClara Y. JonesRuth JilesSusan F. RumishaGeraldine S. Perry
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Objectives: We explore the relationships be tween socially assigned race (‘‘How do other people usually classify you in this country?’’), selfidentified race/ethnicity, and excellent or very good general health status. We then take advantage of subgroups which are discordant on self-identified race/ethnicity and socially assigned race to examine whether being classified by others as White conveys an advantage in health status, even for those who do not self-identify as White. Methods: Analyses were conducted using pooled data from the eight states that used the Reactions to Race module of the 2004 Behavioral Risk Factor Surveillance System. Results: The agreement of socially assigned race with self-identified race/ethnicity varied across the racial/ethnic groups currently defined by the United States government. Included among those usually classified by others as White were 26.8% of those who self-identified as Hispanic, 47.6% of those who self-identified as American Indian, and 59.5% of those who self-identified with More than one race.Keywords:
Race and health
White (mutation)
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We explore the relationships between socially assigned race ("How do other people usually classify you in this country?"), self-identified race/ethnicity, and excellent or very good general health status. We then take advantage of subgroups which are discordant on self-identified race/ethnicity and socially assigned race to examine whether being classified by others as White conveys an advantage in health status, even for those who do not self-identify as White.Analyses were conducted using pooled data from the eight states that used the Reactions to Race module of the 2004 Behavioral Risk Factor Surveillance System.The agreement of socially assigned race with self-identified race/ethnicity varied across the racial/ethnic groups currently defined by the United States government. Included among those usually classified by others as White were 26.8% of those who self-identified as Hispanic, 47.6% of those who self-identified as American Indian, and 59.5% of those who self-identified with More than one race. Among those who self-identified as Hispanic, the age-, education-, and language-adjusted proportion reporting excellent or very good health was 8.7 percentage points higher for those socially assigned as White than for those socially assigned as Hispanic (P=.04); among those who self-identified as American Indian, that proportion was 15.4 percentage points higher for those socially assigned as White than for those socially assigned as American Indian (P=.05); and among those who self-identified with More than one race, that proportion was 23.6 percentage points higher for those socially assigned as White than for those socially assigned as Black (P<.01). On the other hand, no significant differences were found between those socially assigned as White who self-identified as White and those socially assigned as White who self-identified as Hispanic, as American Indian, or with More than one race.Being classified by others as White is associated with large and statistically significant advantages in health status, no matter how one self-identifies.
Race and health
White (mutation)
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Odds
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Race/ethnicity information is vital for measuring disparities across groups, and self-report is the gold standard. Many surveys assign simplified race/ethnicity based on responses to separate questions about Hispanic ethnicity and race and instruct respondents to "check all that apply." When multiple races are endorsed, standard classification methods either create a single heterogenous multiracial group, or attempt to impute the single choice that would have been selected had only one choice been allowed.To compare 3 options for classifying race/ethnicity: (a) hierarchical, classifying Hispanics as such regardless of racial identification, and grouping together all non-Hispanic multiracial individuals; (b) a newly proposed additive model, retaining all original endorsements plus a multiracial indicator; (c) an all-combinations approach, separately categorizing every observed combination of endorsements.Cross-sectional comparison of racial/ethnic distributions of patient experience scores; using weighted linear regression, we model patient experience by race/ethnicity using 3 classification systems.In total, 259,763 Medicare beneficiaries age 65+ who responded to the 2017 Medicare Consumer Assessments of Healthcare Providers and Systems Survey and reported race/ethnicity.Self-reported race/ethnicity, 4 patient experience measures.Additive and hierarchical models produce similar classifications for non-Hispanic single-race respondents, but differ for Hispanic and multiracial respondents. Relative to the gold standard of the all-combinations model, the additive model better captures ratings of health care experiences and response tendencies that differ by race/ethnicity than does the hierarchical model. Differences between models are smaller with more specific measures.Additive models of race/ethnicity may afford more useful measures of disparities in health care and other domains. Our results have particular relevance for populations with a higher prevalence of multiracial identification.
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This study examined the difference between the relationship of socio-demographic variables as well as the intersection between race/ethnicity and gender on nine indicators of social distance from people with mental health conditions (MHC). Secondary analysis of a randomized telephone survey drawn from the Missouri Institute of Mental Health and the Missouri Mental Health Foundation in the spring of 2013 was conducted. The sample included 2,244 Midwestern respondents. Multivariate logistic regressions were utilized. The sample was mostly White (91.7%) and female (59.8%), with a mean age of 57.1 years. Being female, 65+ years of age, and having a higher annual income ($50,000+) was associated with a lower preference for social interactions with individuals experiencing MHC. Black males, however, had an increased willingness to interact with this population. Findings suggest that it may be beneficial for anti-stigma programs to target populations that seem to be consistently less willing to interact with individuals experiencing MHC (e.g., individuals who are older or who have a higher annual income). Additional research is needed to explore why Black men may be more willing to interact with people with MHC.
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The 1997 standard for race and ethnicity data from the Office of Management and Budget requires the collection of data for multiple race groups. The aims of this study were to compare characteristics of multiple race children and describe race reporting for children within interracial and multiple race families. Descriptive statistics were estimated using the 1993-1995 National Health Interview Surveys. In this time period, 2.6% of children had more than one race reported. Multiple race children were a diverse group who differed from each other and their single race counterparts. For example, the percent of children reported as both Black and White who lived in a two-parent household (58.9%), was significantly less than the corresponding percents for other multiple race children (65.8%-79.6%), and between the corresponding percents for single race Black (42.7%) and single race White children (83.2%). The relationships between parental race and child's race varied. Although 3.1% of children in two-parent households lived with interracial parents, fewer than half of these children had more than one race reported. Sociodemographic variables were not associated with child's reported race among interracial families. These findings indicate that generalizations about multiple race children for research or policy purposes will be problematic.
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Our objective was to compare patients' health care experiences, related to their weight, across racial and ethnic groups. In Summer 2015, we distributed a written survey with telephone follow-up to a random sample of 5400 racially/ethnically and geographically diverse U.S. adult health plan members with overweight or obesity. The survey assessed members' perceptions of their weight-related healthcare experiences, including their perception of their primary care provider, and the type of weight management services they had been offered, or were interested in. We used multivariable multinomial logistic regression to examine the relationship between race/ethnicity and responses to questions about care experience. Overall, 2811 members (53%) responded to the survey and we included 2725 with complete data in the analysis. Mean age was 52.7 years (SD 15.0), with 61.7% female and 48.3% from minority racial/ethnic groups. Mean BMI was 37.1 kg/m2 (SD 8.0). Most (68.2%) respondents reported having previous discussions of weight with their provider, but interest in such counseling varied by race/ethnicity. Non-Hispanic blacks were significantly less likely to frequently avoid care (for fear of discussing weight/being weighed) than whites (OR 0.49, 95% CI 0.26–0.90). Relative to whites, respondents of other race/ethnicities were more likely to want weight-related discussions with their providers. Race/ethnicity correlates with patients' perception of discussions of weight in healthcare encounters. Clinicians should capitalize on opportunities to discuss weight loss with high-risk minority patients who may desire these conversations.
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Objective Numerous articles have identified that medical technologies diffuse more rapidly among non-Latino whites compared with other racial-ethnic groups. However, whether health risk warnings also diffuse differentially across racial-ethnic minority groups is uncertain. This study assessed racial-ethnic variation in children's antidepressant use before and after the 2004 black-box warning concerning risks of antidepressants for youths. Methods Data consisted of responses for white, black, and Latino youths ages five through 17 from the 2002–2008 Medical Expenditure Panel Survey (N=44,422). The dependent variable was any antidepressant use in the prior year. Independent variables were race-ethnicity, year, psychological impairment, income, insurance status, region, and parents' education level. Logistic regression models were used to assess antidepressant use conditional on race-ethnicity, time, interaction between race-ethnicity and time, need, socioeconomic status, and Institute of Medicine–concordant estimates of disparities in predicted antidepressant use before and after the warning. Results The warnings affected antidepressant use differentially for whites, blacks, and Latinos. Usage rates among whites decreased from 3.3 to 2.1 percentage points between prewarning and postwarning, whereas usage rates remained steady among Latinos and increased among blacks. Findings were significant in multiple regression analyses, in which predictions were adjusted for need. Conclusions The findings indicate that health safety information on antidepressant usage among children diffused faster among whites than nonwhites, suggesting the need to improve infrastructure for delivering important health messages to racial-ethnic minority populations.
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The purpose of the present study was to evaluate the effects of race/ethnicity and socioeconomic status on consumer health care satisfaction ratings. The authors analyzed national data from the 2001 National Research Corporation Healthcare Market Guide Survey (N = 99 102). Four global and 3 composite ratings were examined. In general, satisfaction ratings were high across all global and composite measures; however, Asian/Pacific Islanders and Hispanics gave lower ratings than did whites, and African Americans gave a mix of higher and lower ratings (vs whites). Among the lowest ratings were those given by American Indians/Alaska Natives living in poverty. Race/ethnicity effects were independent of education and income. These findings are consistent with reports of continuing racial/ethnic disparities in both coverage and care. Programs to improve quality of care must specifically address these well-documented, severe, and persistent disparities.
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We examined how traditional (income, education) and nontraditional (public assistance, material deprivation, subjective social standing) socioeconomic status (SES) indicators were associated with self-rated health, physical functioning, and depression in ethnically diverse pregnant women. Using multiple regression, we estimated the association of race/ethnicity (African American, Latino, Asian/Pacific Islander (PI) and white) and sets of SES measures on each health measure. Education, material deprivation, and subjective social standing were independently associated with all health measures. After adding all SES variables, race/ethnic disparities in depression remained for all minority groups; disparities in self-rated health remained for Asian/Pacific Islanders. Few race/ethnic differences were found in physical functioning. Our results contribute to a small literature on how SES might interact with race/ethnicity in explaining health.
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