Occupational Segregation and Racial Health Disparities K Chung-Bridges, C Muntaner, LE Fleming, DJ Lee, KL Arheart, WG LeBlanc, AJ Caban Martinez, SL Christ, KE McCollister, T Pitman (University of Miami Miller School of Medicine, Departments of Epidemiology & Public Health and Family Medicine, Miami, FL; Departments of Behavioral & Community Health and Epidemiology & Preventive Medicine, University of Maryland, Baltimore, MD; Department of Sociology and Odum Institute for Research in Social Science, University of North Carolina, Chapel Hill, NC) Funding provided in part by NIOSH Grant number 1 R01 0H ; Worker Photographs by Dr. David Parker ABSTRACT Racial segregation provides a potential mechanism linking occupations with adverse health outcomes. Using an African-American Segregation Index for US worker groups from the nationally-representative pooled National Health Interview Survey (n=449,281). Multivariable logistic regression analyses documented consistent positive associations between employment in segregated occupations and poor worker health, regardless of covariate adjustment (e.g., race, income, education). Thus, occupational racial segregation negatively affects both African-American and White workers. Potential mechanisms of this effect need to be identified. RESULTS Occupational Group Rankings: The ten occupations with the highest rates of reported fair/poor health also had high I AA, while the ten occupations with the lowest rates of fair/poor health had low I AA (Table 1). The point biserial correlation between I AA and the health score was (p<0.0001). Multivariable Logistic Regression: There was a positive association between the I AA and poor worker health in all subgroups, regardless of adjustment for age, education, income, race, or gender (Table 2). In fact, the magnitude of the effect was similar to the magnitude of the effect of age, a factor known to be strongly associated with health. The saturated model (adjusted for age, education, income, gender, and race) demonstrated a 4% increased risk of fair or poor health for each unit increase in the I AA (Odds Ratio (OR)=1.041; 95% Confidence Interval (CI)= ). In subgroup analyses, this association was strongest in White males (1.04 [ ]), and weakest, but still significant among African-American males (1.021 [ ]). CONCLUSIONS Self-reported health has been shown in numerous studies to be an excellent indicator of overall health status. Fair and poor health status has even been shown to predict mortality risk. We found that employment in US occupations with high concentrations of African-Americans was associated with higher rates of reported fair/poor health status among workers employed in these occupations, even after adjustment for worker income and education. This association was present regardless of the race and gender of the worker, although effects appeared to be strongest in White male workers. One possible explanation is that Whites who work in jobs with higher proportions of African- Americans are subject to deleterious environmental/occupational conditions that exist in such settings, which would predict poor outcomes for all workers. Our study finds support for the proposition that occupational racial segregation has negative consequences for the health of both African-American and White workers. Because segregated occupations tend to be “working class” occupations, working class Whites will be the most affected among Whites. Occupational segregation may be hazardous for the majority of the workforce. Although no inference of causality should be made given the cross-sectional design of the NHIS, potential mechanisms through which occupational segregation may be associated with worker health need to be identified. METHODS The dataset was the nationally representative sample of US workers 18 yrs and older in the National Health Interview Survey (NHIS), pooled for Each individual worker in our database was assigned an African-American segregation index (I AA ) representing the average percentage of African-Americans in the given occupation. SAS was used for all analyses, including regression modeling with Proc Survey Logistic, with adjustment for case weights and design effects. Occupational Group Rankings: The 206 occupational groups, each consisting of at least 100,000 US workers, were ranked according to the proportion of workers reporting fair or poor health status. In each occupational group, the estimated number of US workers, number of workers reporting fair/poor health status, and average age were also calculated. Multivariable Logistic Regression: We constructed multivariable logistic regression models with fair/poor versus good/excellent subjective health as the dependent variable. The independent variable of interest was the I AA, and the models were adjusted for varying combinations of age, race, education, income, and gender. Subgroup analyses were also performed (e.g., African-American males). BACKGROUND Racial segregation at work may result from several factors, including self-selection due to geographical segregation, history of racial discrimination, segregation within trade unions, differential educational credentials, or discrimination in training and hiring practices. Racial segregation may have an impact on disparities in pay, promotion, and managerial mobility. It could also result in differential exposure to job hazards and differential access to health and safety training, occupational health services, and workers’ compensation. Occupational segregation may provide a mechanism linking occupation with health outcomes, and its impact may vary based on worker race or gender. Two traditional functionalist hypotheses regarding the impact of occupational segregation have dominated the literature. One postulates that racial segregation impairs the lot of African-American workers only; the other that racial segregation, by dividing the workforce into opposing racialized groups, results in harm to both types of workers (i.e. lower wages, more hazardous working conditions). In the present study, we were able to examine the merit of these two explanations with regard to health outcomes. Table 1: Occupations with the Lowest and Highest Proportions of Workers Reporting Fair/Poor Health Status KEY Occupational Groups: 206 categories I AA : African American segregation index Table 2: Association between Degree of Occupational Segregation and Worker-Reported Fair or Poor Health Status KEY All models adjusted for income and education **Further adjusted for race and gender IAA: African American segregation index Health status: 0 = fair or poor; 1= good, very good, or excellent