1. Role of racism on cancer behavioral risk profiles: a focus on secondary prevention (screening behaviors) Salma Shariff-Marco, PhD, MPH Cancer Prevention Fellow Health Services and Economics Branch, Applied Research Program Division of Cancer Control and Population Sciences This is a cross-sectional study using data from the 2003 California Health Interview Survey, 2000 US Census, Area Resource File and United States Department of Agriculture (N=35,203) Exclusion criteria: having a prior cancer diagnosis, being pregnant, belonging to some other or multi-racial groups, missing responses to key variables, and males 18-49 years (leaving n=26,172) Outcome: Profile of screening behaviors (breast, cervical, colorectal and prostate cancers) – Based on recommendations from evidence-based guidelines, each individual received a score for each eligible screening behavior ranging from 1 (recent), 2 (ever), 3 (never) – Age- and gender-specific risk profiles were calculated for each individual by averaging across scores for each eligible screening behavior – Range is 1 to 3  1=lowest behavioral risk profile (recently screened across all eligible screenings)  3=highest behavioral risk profile (never screened across all eligible screenings) Exposure: Racism – Perceived Racism  In General: “Thinking about your race or ethnicity, how often have you felt treated badly or unfairly because of your race or ethnicity?” (never, rarely, ≥ sometimes)  In Health Care: “Was there ever a time when you would have gotten better medical care if you had belonged to a different race or ethnic group?” (no, yes)  Any Perceived Racism = either exposure in general or in health care (no, yes) –Race-based Residential Segregation  Dissimilarity Index: measure of (un)evenness of the distribution of a group between census tracts within the county (0, 1)  Interaction Index: measure of the probability of interaction with another group (0, 1)  Each measure was recoded to classify counties as having low, moderate, or high levels of segregation Statistical analyses included univariate and bivariate analyses, multivariate and multi-level linear regression. The estimates for individual level analyses were calculated using SAS-Callable SUDAAN (applying weights and adjusting for survey design) Racial/ethnic disparities in cancer continue to persist: –Mortality rates (all site)  Males: 148.0 (Asian) – 339.4 (African-American)  Females: 99.4 (Asian) – 194.3 (African-American) –Mortality trends, 1995-2003  Males: decreases in lung, prostate and colorectal cancer were experienced by all groups except Asian and AI/AN groups for whom colorectal cancer rates were stable  Females: declines in breast cancer were experienced by all groups except Asian and AI/AN for whom rates were stable; declines in colorectal cancer were experienced by all except Latina and Asian groups –Screening Behaviors (% recent)  Breast cancer (mammography):58.8 (Asian) – 70.4 (Whites/African-Americans)  Cervical cancer (Pap smear): 68.4 (Asian) – 86.0 (AI/AN)  Colorectal cancer (FOBT and/or endoscopy): ~30 (Asian, Latino, AI/AN) – 44.2 (White) Racism (perceived and segregation) has been hypothesized as a contributor to these disparities –In the public health literature, racism has been predominantly studied with respect to African-Americans and increasingly Latinos. Most of the literature has examined mental health outcomes and cardiovascular disease and its risk factors with little literature on the effect of racism on cancer-related health behaviors across racial/ethnic groups –Pathways through which racism may affect behaviors include:  Individual level: socioeconomic status, health care access, stress  Environmental level: social/material deprivation, health care access, political and physical environments BACKGROUND METHODS RESULTS Figure 2. Unadjusted Odds Ratios of Any Perceived Racism on Secondary Risk RACISM Perceived racism varied with all racial/ethnic minority groups reporting higher prevalence of perceived racism than Whites regardless of measure Residential segregation –Distribution varies by measure (Dissimilarity Index or Interaction Index) –Area level may be influencing lack of high segregation for APIs (e.g., county vs. Metropolitan Statistical Area) INDIVIDUAL-LEVEL ANALYSES Perceived racism in general was inversely associated with cancer risk (i.e., with increased exposure to racism there were decreased risk profiles) Perceived racism in health care was moderated by gender and education –Health care context: avenue for intervention, particularly for Asian Americans and Pacific Islanders and Latinos MULTI-LEVEL ANALYSES Higher levels of segregation among Latinos and African-Americans were associated with decreased risk profiles. Further studies are required to understand these findings and investigating the following hypotheses: –Successful outreach efforts of existing state and federally funded screening programs –Communication and social support moderating the effect of segregation on health behaviors LIMITATIONS Cross-sectional study, thus causal inferences are not possible Data are self-reported data Validity of the perceived racism measures is unknown across cultural groups Inadequate sample size for American Indian/Alaska Natives for multivariate analyses (n=306/226) CONCLUSIONS RESULTS (CONT.) Figure 4. Residential Segregation Maps of California Counties LatinosAPIs African-Americans Whites Figure 1. Prevalence of perceived racism by race/ethnicity Interaction Index Dissimilarity Index MULTIVARIATE LINEAR REGRESSION ‡ * I. Total Sample (N=26,172) Perceived racism in general: decreased risk profiles were associated with increased frequency of racism (b rarely = -0.01; b ≥sometimes = -0.04*) Perceived racism in health care was moderated by –Gender (see Figure 3) –Education (see Figure 3) II. Stratified Analyses by race/ethnicity Among Asian Americans and Pacific Islanders –Perceived Racism in General: decreased risk profiles were associated with increased frequency of racism –Perceived Racism in Health Care was moderated by gender  Males: there was no difference in risk profiles between those who did and did not report racism;  Females: increased risk profiles were associated with those who reported racism Among Latinos –Perceived Racism in Health Care was moderated by gender and education  Males had a greater increase in risk profiles between those who did and did not report racism compared to females  Among those who attended graduate school, there was a much greater increase in risk profile between those who did and did not report racism compared to those who had a BA/BS, some college, or less than HS education  Among those who completed HS/GED, there was a decrease in risk profile between those who did and did not report racism ‡These models were adjusted for the following covariates: (race/ethnicity,) gender, age, marital status, heavy cigarette smoking, insurance coverage, usual source of care, doctor visit, satisfaction with health care, citizenship/ immigration status, length of residency, language at home *p<0.05 MULITLEVEL ANALYSES ‡ * Hierarchical random intercept linear regression models by racial/ethnic groups: Main effects of segregation Latinos: those living in a county with high segregation (Dissimilarity Index) had decreased risk profiles (b= -0.14) African-Americans: those living in a county with moderate and high segregation (Dissimilarity Index) had decreased risk profiles (b moderate = -0.05*, b high = -0.31*) None of the models had statistically significant random intercepts ‡In addition to the individual-level correlates, these models were also adjusted for county correlates including poverty, health professionals shortage area and urban/rural continuum *p <0.05 Acknowledgements: Dissertation Committee Members: Dr.’s Ann Klassen (advisor), Thomas Louis (chair), Darrell Gaskin, Janice Bowie; Dissertation Funding Sources: JHBSPH Cancer Epidemiology Training Grant and Department of Health, Behavior and Society; Data: 2003 California Health Interview Survey, http://www.chis.ucla.edu/. Figure 3. Fixed effects of perceived racism in health care on secondary risk profile