title: Integrating multiple social statuses in health disparities research: the case of lung cancer.
abstract: OBJECTIVE
  To illustrate the complex patterns that emerge when race/ethnicity, socioeconomic status (SES), and gender are considered simultaneously in health care disparities research and to outline the needed research to understand them by using disparities in lung cancer risks, treatment, and outcomes as an example.
  
  
  RESULTS
  SES, gender, and race/ethnicity are social categories that are robust predictors of variations in health and health services utilization. These are usually considered separately, but intersectionality theory indicates that the impact of each depends on the others. Each reflects historically and culturally contingent variations in social, economic, and political status. Distinct patterns of risk and resilience emerge at the intersections of multiple social categories and shape the experience of health, health care access, utilization, quality, and outcomes where these categories intersect. Intersectional approaches call for greater attention to understand social processes at multiple levels of society and require the collection of relevant data and utilization of appropriate analytic approaches to understand how multiple risk factors and resources combine to affect the distribution of disease and its management.
  
  
  CONCLUSIONS
  Understanding how race/ethnicity, gender, and SES are interactive, interdependent, and social identities can provide new knowledge to enhance our efforts to effectively address health disparities.
authors.affiliation: Department of Society, Human Development and Health, Harvard University, School of Public Health, 677 Huntington Avenue, 6th Floor, Boston, MA, 02215, USA. ekontos@hsph.harvard.edu
authors.forename: David R
authors.initials: DR
authors.lastname: Williams
authors.forename: Emily Z
authors.initials: EZ
authors.lastname: Kontos
authors.forename: K
authors.initials: K
authors.lastname: Viswanath
authors.forename: Jennifer S
authors.initials: JS
authors.lastname: Haas
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Lathan
authors.forename: Laura E
authors.initials: LE
authors.lastname: MacConaill
authors.forename: Jarvis
authors.initials: J
authors.lastname: Chen
authors.forename: John Z
authors.initials: JZ
authors.lastname: Ayanian
mesh_terms: D003469:Culture; D004641:Emigration and Immigration; D005006:Ethnicity / Q000706:statistics & numerical data*; D020022:Genetic Predisposition to Disease; D006302:Health Services Research / Q000706:statistics & numerical data; D054625:Healthcare Disparities / Q000208:ethnology / Q000706:statistics & numerical data*; D006801:Humans; D008175:Lung Neoplasms / Q000208:ethnology* / Q000401:mortality; D011287:Prejudice; D044469:Racial Groups / Q000706:statistics & numerical data*; D012107:Research Design / Q000706:statistics & numerical data; D012307:Risk Factors; D012737:Sex Factors; D012907:Smoking / Q000208:ethnology; D012923:Social Class; D012933:Social Identification; D012959:Socioeconomic Factors