History, biology, and health inequities: emergent embodied phenotypes and the illustrative case of the breast cancer estrogen receptor

Theorizing epidemiology, the stories bodies tell, and embodied truths: a status update on contending 21st c CE epidemiological theories of disease distribution

This critical review considers the status of 21st-century epidemiological theories of disease distribution, updating to 2024 prior analyses published up through 2014, and discusses the implications of these theories for research, practice, and pedagogy. Three key trends stand out: (a) the continued dominance of individualistic biomedical and lifestyle theories; (b) growth and elaboration of social epidemiological alternatives; and (c) the ongoing inattention to epidemiologic theories of disease distribution in the training of epidemiologists and public health professionals and in current efforts to improve the rigor of epidemiological research and causal inference. In a context of growing global political polarization, climate crisis, broader environmental and ecological crises, and stubbornly persistent health inequities within and between nations, producing actionable knowledge relevant to improving the people's health and advancing health justice will require much greater engagement with social epidemiologic theories of disease distribution in research, pedagogy, and practice. At issue is critically engaging with the embodied truths manifested in the stories bodies tell in population patterns of health, disease, and well-being.

Advancing gender transformative intersectional science for health justice: An ecosocial analysis

At a time when health-oriented institutions both globally and nationally are increasingly recognizing the need to support research, interventions and training that engage with analysis of how gendered social systems shape population health, independent of and in conjunction with sex-linked biology, it is essential that this work reject biological essentialism and instead embrace embodied integration. In this essay, guided by the ecosocial theory of disease distribution, I clarify connections and distinctions between biological versus social reproduction and inheritance, underscore the non-equivalence of the categories "sex" and "race," and offer a set of examples analyzing the production of gendered health inequities and who needs to do what to address them. The examples concern the worlds of work (sexual harassment; breastfeeding; sex work), ecologic environments (water access; fracking, sexually transmitted infections, & sexual violence); sexual reproduction and reproductive justice (gender stereotyping of reproductive biology; sterilization abuse and abortion bans); and (4) gender transformative initiatives (violence; health interventions). To advance gender transformative intersectional science for health justice, I offer recommendations regarding requirements for justifying data conceptualization, analysis and governance that can be implemented by institutions with the power to shape the funding, translation, and publication of science involving gender, sex-linked biology, and the people's health.

Historical Redlining, Persistent Mortgage Discrimination, and Race in Breast Cancer Outcomes

Importance

Inequities created by historical and contemporary mortgage discriminatory policies have implications for health disparities. The role of persistent mortgage discrimination (PMD) in breast cancer (BC) outcomes has not been studied.

Objective

To estimate the race-specific association of historical redlining (HRL) with the development of BC subtypes and late-stage disease and a novel measure of PMD in BC mortality.

Design, Setting, and Participants

This population-based cohort study used Georgia Cancer Registry data. A total of 1764 non-Hispanic Black and White women with a BC diagnosis and residing in an area graded by the Home Owners' Loan Corporation (HOLC) in Georgia were included. Patients were excluded if they did not have a known subtype or a derived American Joint Committee on Cancer stage or if diagnosed solely by death certificate or autopsy. Participants were diagnosed with a first primary BC between January 1, 2010, to December 31, 2017, and were followed through December 31, 2019. Data were analyzed between May 1, 2022, and August 31, 2023.

Exposures

Scores for HRL were examined dichotomously as less than 2.5 (ie, nonredlined) vs 2.5 or greater (ie, redlined). Contemporary mortgage discrimination (CMD) scores were calculated, and PMD index was created using the combination of HRL and CMD scores.

Main Outcomes and Measures

Estrogen receptor (ER) status, late stage at diagnosis, and BC-specific death.

Results

This study included 1764 women diagnosed with BC within census tracts that were HOLC graded in Georgia. Of these, 856 women (48.5%) were non-Hispanic Black and 908 (51.5%) were non-Hispanic White; 1148 (65.1%) were diagnosed at 55 years or older; 538 (30.5%) resided in tracts with HRL scores less than 2.5; and 1226 (69.5%) resided in tracts with HRL scores 2.5 or greater. Living in HRL areas with HRL scores 2.5 or greater was associated with a 62% increased odds of ER-negative BC among non-Hispanic Black women (odds ratio [OR], 1.62 [95% CI, 1.01-2.60]), a 97% increased odds of late-stage diagnosis among non-Hispanic White women (OR, 1.97 [95% CI, 1.15-3.36]), and a 60% increase in BC mortality overall (hazard ratio, 1.60 [95% CI, 1.17-2.18]). Similarly, PMD was associated with BC mortality among non-Hispanic White women but not among non-Hispanic Black women.

Conclusions and Relevance

The findings of this cohort study suggest that historical racist policies and persistent discrimination have modern-day implications for BC outcomes that differ by race. These findings emphasize the need for a more nuanced investigation of the social and structural drivers of disparate BC outcomes.

Stressful Life Events, Social Support, and Incident Breast Cancer by Estrogen Receptor Status

Chronic stress affects immune function and hormonal signaling and has been hypothesized to be associated with breast cancer, although results from the few prior studies are mixed and have not examined potential differences by estrogen receptor (ER) status. Using the Women's Health Initiative study, we included 76,951 postmenopausal women followed for events for a median of 16.7 years to investigate the association between baseline self-reported stressful life events and incident breast cancer by ER status and whether the association was modified by social support. We generated Cox proportional hazards models adjusting for demographic, clinical, lifestyle/behavioral, and social factors to estimate HRs and 95% confidence intervals (95%CI). The mean age was 63 (SD, 7.3), and majority of participants were White race (83.5%) and married or in a marriage-like relationship (63.0%). In analyses stratified by ER status, there was no relationship between stressful life events and ER-positive breast cancer. In contrast, compared with women in the lowest quartile, those in higher quartiles had an increased risk of ER-negative breast cancer, where those in quartile 4 had the highest risk (Quartile 4 vs. Quartile 1; HR = 1.30; 95%CI, 1.01-1.68; Ptrend = 0.050). Moreover, associations were stronger for the highest versus lowest quartile of stressful life events among widowed women (HR = 2.39; 95%CI, 1.29-4.44; Pinteraction<0.001). Association between stressful life events and ER-negative breast cancer was not modified by social support. In this cohort of postmenopausal women, higher experiences of prediagnostic stressful life events were associated with increased risk of ER-negative breast cancer.

PREVENTION RELEVANCE

Epidemiologic studies on the association between psychosocial stress and breast cancer risk remain inconsistent, while investigation of whether the association differs by ER status is limited. In this prospective cohort of postmenopausal women, high experiences of stressful life events were positively associated with ER-negative disease but not ER-positive.

Home mortgage discrimination and incidence of triple-negative and Luminal A breast cancer among non-Hispanic Black and non-Hispanic White females in California, 2006-2015

Purpose

In the United States, Black females are burdened by more aggressive subtypes and increased mortality from breast cancer compared to non-Hispanic (NH) White females. Institutional racism may contribute to these inequities. We aimed to characterize the association between home mortgage discrimination, a novel measure of institutional racism, and incidence of Luminal A and triple-negative breast cancer (TNBC) subtypes among NH Black and NH White females in California metropolitan areas.

Methods

We merged data from the California Cancer Registry on females aged 20 + diagnosed with primary invasive breast cancer between 2006 and 2015 with a census tract-level index of home mortgage lending bias measuring the odds of mortgage loan denial for Black versus White applicants, generated from the 2007–2013 Home Mortgage Disclosure Act database. Poisson regression estimated cross-sectional associations of census tract-level racial bias in mortgage lending with race/ethnicity- and Luminal A and TNBC-specific incidence rate ratios, adjusting for neighborhood confounders.

Results

We identified n = 102,853 cases of Luminal A and n = 15,528 cases of TNBC over the study period. Compared to NH Whites, NH Black females had higher rates of TNBC, lower rates of Luminal A breast cancer, and lived in census tracts with less racial bias in home mortgage lending. There was no evidence of association between neighborhood racial bias in mortgage lending at the time of diagnosis and either subtype among either racial/ethnic group.

Conclusion

Future research should incorporate residential history data with measures of institutional racism to improve estimation and inform policy interventions.

OUP accepted manuscript

Background

Methods

Results

Conclusion

Associations between neighborhood disinvestment and breast cancer outcomes within a populous state registry

BACKGROUND

Breast cancer (BrCa) outcomes vary by social environmental factors, but the role of built-environment factors is understudied. The authors investigated associations between environmental physical disorder-indicators of residential disrepair and disinvestment-and BrCa tumor prognostic factors (stage at diagnosis, tumor grade, triple-negative [negative for estrogen receptor, progesterone receptor, and HER2 receptor] BrCa) and survival within a large state cancer registry linkage.

METHODS

Data on sociodemographic, tumor, and vital status were derived from adult women who had invasive BrCa diagnosed from 2008 to 2017 ascertained from the New Jersey State Cancer Registry. Physical disorder was assessed through virtual neighborhood audits of 23,276 locations across New Jersey, and a personalized measure for the residential address of each woman with BrCa was estimated using universal kriging. Continuous covariates were z scored (mean ± standard deviation [SD], 0 ± 1) to reduce collinearity. Logistic regression models of tumor factors and accelerated failure time models of survival time to BrCa-specific death were built to investigate associations with physical disorder adjusted for covariates (with follow-up through 2019).

RESULTS

There were 3637 BrCa-specific deaths among 40,963 women with a median follow-up of 5.3 years. In adjusted models, a 1-SD increase in physical disorder was associated with higher odds of late-stage BrCa (odds ratio, 1.09; 95% confidence interval, 1.02-1.15). Physical disorder was not associated with tumor grade or triple-negative tumors. A 1-SD increase in physical disorder was associated with a 10.5% shorter survival time (95% confidence interval, 6.1%-14.6%) only among women who had early stage BrCa.

CONCLUSIONS

Physical disorder is associated with worse tumor prognostic factors and survival among women who have BrCa diagnosed at an early stage.

Theory, methods, and operational results of the Young Women's Health History Study: a study of young-onset breast cancer incidence in Black and White women

Purpose

The etiology of young-onset breast cancer (BC) is poorly understood, despite its greater likelihood of being hormone receptor-negative with a worse prognosis and persistent racial and socioeconomic inequities. We conducted a population-based case–control study of BC among young Black and White women and here discuss the theory that informed our study, exposures collected, study methods, and operational results.

Methods

Cases were non-Hispanic Black (NHB) and White (NHW) women age 20–49 years with invasive BC in metropolitan Detroit and Los Angeles County SEER registries 2010–2015. Controls were identified through area-based sampling from the U.S. census and frequency matched to cases on study site, race, and age. An eco-social theory of health informed life-course exposures collected from in-person interviews, including socioeconomic, reproductive, and energy balance factors. Measured anthropometry, blood (or saliva), and among cases SEER tumor characteristics and tumor tissue (from a subset of cases) were also collected.

Results

Of 5,309 identified potentially eligible cases, 2,720 sampled participants were screened and 1,812 completed interviews (682 NHB, 1140 NHW; response rate (RR): 60%). Of 24,612 sampled control households 18,612 were rostered, 2,716 participants were sampled and screened, and 1,381 completed interviews (665 NHB, 716 NHW; RR: 53%). Ninety-nine% of participants completed the main interview, 82% provided blood or saliva (75% blood only), and SEER tumor characteristics (including ER, PR and HER2 status) were obtained from 96% of cases.

Conclusions

Results from the successfully established YWHHS should expand our understanding of young-onset BC etiology overall and by tumor type and identify sources of racial and socioeconomic inequities in BC.

Supplementary Information

The online version of this article contains supplementary material available (10.1007/s10552-021-01461-x).

Sustaining planetary health through systems thinking: Public health's critical role

Understanding and responding to adverse human health impacts of global environmental change will be a major priority of 21st century public health professionals. The emerging field of planetary health aims to face this challenge by studying and promoting policies that protect the health of humans and of the Earth's natural systems that support them. Public health, drawing on its experience of guiding policies to improve population health, has contributed to planetary health's development. Yet, few public health practitioners are familiar with planetary health's systems-oriented approaches for understanding relationships between economic development, environmental degradation, and human health. In this narrative review, we present key planetary health concepts and show how systems thinking has guided its development. We discuss historical approaches to studying impacts of economic development on human health and the environment. We then review novel conceptual frameworks adopted by planetary health scientists to study and forecast impacts of policies that influence human health and Earth's natural systems at varying spatiotemporal scales. We conclude by presenting examples of how applying the "Doughnut" model (an economic framework where the needs of people are met without overshooting the world's ecological limits) could guide policies for promoting health co-benefits to humans and natural systems.

Visual cues of the built environment and perceived stress among a cohort of black breast cancer survivors

We investigated relationships between independently observed, visual cues of residential environments and subsequent participant-reported stress within a population-based cohort of Black breast cancer survivors (n = 476). Greater visual cues of engagement - presence of team sports, yard decorations, outdoor seating - (compared to less engagement) was marginally associated with lower perceived stress in univariate models, but attenuated towards null with adjustment for socio-demographic, behavioral, and health-related covariates. Similarly, physical disorder and perceived stress were not associated in adjusted models. Relationships between observed built environment characteristics and perceived stress might be influenced by socioeconomic and health behavior factors, which longitudinal studies should investigate.

A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model

BACKGROUND

The etiology of breast cancer is a complex system of interacting factors from multiple domains. New knowledge about breast cancer etiology continues to be produced by the research community, and the communication of this knowledge to other researchers, practitioners, decision makers, and the public is a challenge.

METHODS

We updated the previously published Paradigm model (PMID: 25017248) to create a framework that describes breast cancer etiology in four overlapping domains of biologic, behavioral, environmental, and social determinants. This new Paradigm II conceptual model was part of a larger modeling effort that included input from multiple experts in fields from genetics to sociology, taking a team and transdisciplinary approach to the common problem of describing breast cancer etiology for the population of California women in 2010. Recent literature was reviewed with an emphasis on systematic reviews when available and larger epidemiologic studies when they were not. Environmental chemicals with strong animal data on etiology were also included.

RESULTS

The resulting model illustrates factors with their strength of association and the quality of the available data. The published evidence supporting each relationship is made available herein, and also in an online dynamic model that allows for manipulation of individual factors leading to breast cancer (https://cbcrp.org/causes/).

CONCLUSIONS

The Paradigm II model illustrates known etiologic factors in breast cancer, as well as gaps in knowledge and areas where better quality data are needed.

IMPACT

The Paradigm II model can be a stimulus for further research and for better understanding of breast cancer etiology.

Breast Cancer Estrogen Receptor Status According to Biological Generation: US Black and White Women Born 1915-1979

Evidence suggests that contemporary population distributions of estrogen-receptor (ER) status among breast cancer patients may be shaped by earlier major societal events, such as the 1965 abolition of legal racial discrimination in the United States (state and local "Jim Crow" laws) and the Great Famine in China (1959-1961). We analyzed changes in ER status in relation to Jim Crow birthplace among the 46,417 black and 339,830 white US-born, non-Hispanic women in the Surveillance, Epidemiology, and End Results (SEER) 13 Registry Group who were born between 1915 and 1979 and diagnosed (ages 25-84 years, inclusive) during 1992-2012. We grouped the cases according to birth cohort and quantified the rate of change using the haldane (which scales change in relation to biological generation). The percentage of ER-positive cases rose according to birth cohort (1915-1919 to 1975-1979) only among women diagnosed before age 55. Changes according to biological generation were greater among black women than among white women, and among black women, they were greatest among those born in Jim Crow (versus non-Jim Crow) states, with this group being the only group to exhibit high haldane values (>|0.3|, indicating high rate of change). Our study's analytical approach and findings underscore the need to consider history and societal context when analyzing ER status among breast cancer patients and racial/ethnic inequities in its distribution.

The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology

'Causal inference', in 21st century epidemiology, has notably come to stand for a specific approach, one focused primarily on counterfactual and potential outcome reasoning and using particular representations, such as directed acyclic graphs (DAGs) and Bayesian causal nets. In this essay, we suggest that in epidemiology no one causal approach should drive the questions asked or delimit what counts as useful evidence. Robust causal inference instead comprises a complex narrative, created by scientists appraising, from diverse perspectives, different strands of evidence produced by myriad methods. DAGs can of course be useful, but should not alone wag the causal tale. To make our case, we first address key conceptual issues, after which we offer several concrete examples illustrating how the newly favoured methods, despite their strengths, can also: (i) limit who and what may be deemed a 'cause', thereby narrowing the scope of the field; and (ii) lead to erroneous causal inference, especially if key biological and social assumptions about parameters are poorly conceived, thereby potentially causing harm. As an alternative, we propose that the field of epidemiology consider judicious use of the broad and flexible framework of 'inference to the best explanation', an approach perhaps best developed by Peter Lipton, a philosopher of science who frequently employed epidemiologically relevant examples. This stance requires not only that we be open to being pluralists about both causation and evidence but also that we rise to the challenge of forging explanations that, in Lipton's words, aspire to 'scope, precision, mechanism, unification and simplicity'.

Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old?

PURPOSE

The purpose of the study was to assess the feasibility of quantifying long-term trends in breast tumor DNA copy number variation (CNV) profiles.

METHODS

We evaluated CNV profiles in formalin-fixed paraffin-embedded (FFPE) tumor specimens from 30 randomly selected Kaiser Permanente Northern California health plan women members diagnosed with breast cancer from 1950 to 2010. Assays were conducted for five cases per decade who had available tumor blocks and pathology reports.

RESULTS

As compared to the tumors from the 1970s to 2000s, the older tumors dating back to the 1950s and 1960s were much more likely to (1) fail quality control, and (2) have fewer CNV events (average 23 and 31 vs. 58 to 69), fewer CNV genes (average 5.1 and 3.7k vs. 8.1 to 10.3k), shorter CNV length (average 2,440 and 3,300k vs. 5,740 to 9,280k), fewer high frequency Del genes (37 and 25% vs. 54 to 76%), and fewer high frequency high_Amp genes (20% vs. 56 to 73%). On average, assay interpretation took an extra 60 min/specimen for cases from the 1960s versus 20 min/specimen for the most recent tumors.

CONCLUSIONS

Assays conducted in the mid-2010s for CNVs may be feasible for FFPE tumor specimens dating back to the 1980s, but less feasible for older specimens.

Tumor Specimen Biobanks: Data Gaps for Analyzing Health Inequities-the Case of Breast Cancer

Biobanks are increasingly recognized to be vital for analyzing tumor properties, treatment options, and clinical prognosis, yet few data exist on whether they are equipped to enable research on cancer inequities, that is, unfair and unnecessary social group differences in health. We conducted a systematic search of global biobanks, identified 46 that have breast tumor tissue and share data externally with academic researchers, and e-mailed and called to obtain data on the sociodemographic, socioeconomic, and geospatial data included, plus time span encompassed. Among the 32 biobank respondents, 91% housed specimens solely from the Global North, only 31% obtained socioeconomic data, 63% included racial/ethnic data (of which 55% lacked socioeconomic data), 44% included limited geographic data, and 55% had specimens dating back at most to 2000. To enable research to address cancer inequities, including trends over time, biobanks will need to address the data gaps documented by our study.

Jim Crow and estrogen-receptor-negative breast cancer: US-born black and white non-Hispanic women, 1992-2012

PURPOSE

It is unknown whether Jim Crow-i.e., legal racial discrimination practiced by 21 US states and the District of Columbia and outlawed by the US Civil Rights Act in 1964-affects US cancer outcomes. We hypothesized that Jim Crow birthplace would be associated with higher risk of estrogen-receptor-negative (ER-) breast tumors among US black, but not white, women and also a higher black versus white risk for ER- tumors.

METHODS

We analyzed data from the SEER 13 registry group (excluding Alaska) for 47,157 US-born black non-Hispanic and 348,514 US-born white non-Hispanic women, aged 25-84 inclusive, diagnosed with primary invasive breast cancer between 1 January 1992 and 31 December 2012.

RESULTS

Jim Crow birthplace was associated with increased odds of ER- breast cancer only among the black, not white women, with the effect strongest for women born before 1965. Among black women, the odds ratio (OR) for an ER- tumor, comparing women born in a Jim Crow versus not Jim Crow state, equaled 1.09 (95% confidence interval [CI] 1.06, 1.13), on par with the OR comparing women in the worst versus best census tract socioeconomic quintiles (1.15; 95% CI 1.07, 1.23). The black versus white OR for ER- was higher among women born in Jim Crow versus non-Jim Crow states (1.41 [95% CI 1.13, 1.46] vs. 1.27 [95% CI 1.24, 1.31]).

CONCLUSIONS

The unique Jim Crow effect for US black women for breast cancer ER status underscores why analysis of racial/ethnic inequities must be historically contextualized.

Understanding and effectively addressing breast cancer in African American women: Unpacking the social context

Black women have a higher incidence of breast cancer before the age of 40 years, more severe disease at all ages, and an elevated mortality risk in comparison with white women. There is limited understanding of the contribution of social factors to these patterns. Elucidating the role of the social determinants of health in breast cancer disparities requires greater attention to how risk factors for breast cancer unfold over the lifecourse and to the complex ways in which socioeconomic status and racism shape exposure to psychosocial, physical, chemical, and other individual and community-level assaults that increase the risk of breast cancer. Research that takes seriously the social context in which black women live is also needed to maximize the opportunities to prevent breast cancer in this underserved group. Cancer 2016;122:2138-49. © 2016 American Cancer Society.

Accounting for Complexity: Gene-environment Interaction Research and the Moral Economy of Quantification

Scientists now agree that common diseases arise through interactions of genetic and environmental factors, but there is less agreement about how scientific research should account for these interactions. This paper examines the politics of quantification in gene-environment interaction (GEI) research. Drawing on interviews and observations with GEI researchers who study common, complex diseases, we describe quantification as an unfolding moral economy of science, in which researchers collectively enact competing ''virtues.'' Dominant virtues include molecular precision, in which behavioral and social risk factors are moved into the body, and ''harmonization,'' in which scientists create large data sets and common interests in multisited consortia. We describe the negotiations and trade-offs scientists enact in order to produce credible knowledge and the forms of (self-)discipline that shape researchers, their practices, and objects of study. We describe how prevailing techniques of quantification are premised on the shrinking of the environment in the interest of producing harmonized data and harmonious scientists, leading some scientists to argue that social, economic, and political influences on disease patterns are sidelined in postgenomic research. We consider how a variety of GEI researchers navigate quantification's productive and limiting effects on the science of etiological complexity.

Latent class model characterization of neighborhood socioeconomic status

PURPOSE

Neighborhood-level socioeconomic status (NSES) can influence breast cancer mortality and poorer health outcomes are observed in deprived neighborhoods. Commonly used NSES indexes are difficult to interpret. Latent class models allow for alternative characterization of NSES for use in studies of cancer causes and control.

METHODS

Breast cancer data was from a cohort of women diagnosed at an academic medical center in Philadelphia, PA. NSES variables were defined using Census data. Latent class modeling was used to characterize NSES.

RESULTS

Complete data was available for 1,664 breast cancer patients diagnosed between 1994 and 2002. Two separate latent variables, each with 2-classes (LC2) best represented NSES. LC2 demonstrated strong associations with race and tumor stage and size.

CONCLUSIONS

Latent variable models identified specific characteristics associated with advantaged or disadvantaged neighborhoods, potentially improving our understanding of the impact of socioeconomic influence on breast cancer prognosis. Improved classification will enhance our ability to identify vulnerable populations and prioritize the targeting of cancer control efforts.

Public Health, Embodied History, and Social Justice: Looking Forward

This essay was delivered as a commencement address at the University of California-Berkeley School of Public Health on May 17, 2015. Reflecting on events spanning from 1990 to 1999 to 2015, when I gave my first, second, and third commencement talks at the school, I discuss four notable features of our present era and offer five insights for ensuring that health equity be the guiding star to orient us all. The four notable features are: (1) growing recognition of the planetary emergency of global climate change; (2) almost daily headlines about armed conflicts and atrocities; (3) growing public awareness of and debate about epic levels of income and wealth inequalities; and (4) growing activism about police killings and, more broadly, "Black Lives Matter." The five insights are: (1) public health is a public good, not a commodity; (2) the "tragedy of the commons" is a canard; the lack of a common good is what ails us; (3) good science is not enough, and bad science is harmful; (4) good evidence--however vital--is not enough to change the world; and (5) history is vital, because we live our history, embodied. Our goal: a just and sustainable world in which we and every being on this planet may truly thrive.

The socioeconomic gradient in all-cause mortality for women with breast cancer: findings from the 1998 to 2006 National Cancer Data Base with follow-up through 2011

PURPOSE

To analyze the association between socioeconomic status (SES) and all-cause mortality among women diagnosed with breast cancer before and after controlling for insurance status, race and ethnicity, stage, treatment modalities, and other demographic and hospital characteristics.

METHODS

Data analyzed included follow-up through 2011 for 582,396 patients diagnosed between 1998 and 2006 with ductal carcinoma in situ or invasive (stage I-IV) breast cancer from the National Cancer Data Base. SES was measured by grouping patients into six income and education-level ZIP code categories. Hierarchical Cox regression models were used to analyze SES survival differences.

RESULTS

Five- and 10-year survival probabilities for the highest SES group were 87.8% and 71.5%, versus 79.5% and 61.5% for the lowest SES group. Controlling for all covariates reduced the highest-to-lowest SES hazard ratio from 1.69 (95% confidence interval: 1.64-1.74) to 1.27 (95% confidence interval: 1.24-1.31). Results were virtually identical in models that included comorbidity and invasive cancer patients only.

CONCLUSIONS

Differences in insurance status, race, and stage at diagnosis are important components of SES disparities and explain about two-thirds of the initial SES survival disparity. The residual SES effect likely mirrors underlying social determinants of health for all American women.

Homogeneity and heterogeneity as situational properties: producing--and moving beyond?--race in post-genomic science

In this article, we explore current thinking and practices around the logics of difference in gene-environment interaction research in the post-genomic era. We find that scientists conducting gene-environment interaction research continue to invoke well-worn notions of racial difference and diversity, but use them strategically to try to examine other kinds of etiologically significant differences among populations. Scientists do this by seeing populations not as inherently homogeneous or heterogeneous, but rather by actively working to produce homogeneity along some dimensions and heterogeneity along others in their study populations. Thus we argue that homogeneity and heterogeneity are situational properties--properties that scientists seek to achieve in their study populations, the available data, and other aspects of the research situation they are confronting, and then leverage to advance post-genomic science. Pointing to the situatedness of homogeneity and heterogeneity in gene-environment interaction research underscores the work that these properties do and the contingencies that shape decisions about research procedures. Through a focus on the situational production of homogeneity and heterogeneity more broadly, we find that gene-environment interaction research attempts to shift the logic of difference from solely racial terms as explanatory ends unto themselves, to racial and other dimensions of difference that may be important clues to the causes of complex diseases.