Abstract
Black women have higher incidence of breast cancer before the age of 40, more severe disease at all ages, and elevated mortality risk compared to 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 the complex ways that 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 among this underserved group.
Despite historically having lower incidence rates of breast cancer than white women, African American (or Black) women have had markedly higher death rates from breast cancer relative to any other racial or ethnic group in the U.S.1 Yet these poor outcomes remain largely unexplained. While much recent research has focused on genetic factors associated with increased risk of disease, we argue that social contextual factors associated with breast cancer risk have been understudied, particularly as they relate to Black women. Understanding and effectively addressing Black-white disparities in breast cancer will require rigorously understanding Black women's lived experiences of racism, segregation, psychosocial stress, and the cumulative stress of living amidst a disproportionate burden of social and environmental assaults, and how these experiences undermine health and contribute to breast cancer risk and mortality.
This article reviews the epidemiological literature on breast cancer among Black women and addresses the contribution of social factors to racial inequities across the continuum of breast cancer. We begin with a description of the patterns of racial disparities in breast cancer. We then address three essential areas in which social-contextual factors have been undervalued in efforts to understand breast cancer disparities. The first area we address is the importance of the lifecourse perspective, examining data on how low socioeconomic status (SES), psychosocial stress, and other adverse exposures in early childhood and continuing through adulthood accumulate to increase breast cancer risk. The second area encompasses the multiple risks and resources in the social environment linked to race, and we empirically examine how these are likely related to each other and combine with biological factors to contribute to racial disparities in breast cancer. Finally, we argue for a renewed look at the science of breast cancer prevention, and how prevention efforts might be improved of breast cancer so that opportunities to reduce breast cancer risks can be maximized.
Black-White Disparities in Breast Cancer
Historically, Black women in the U.S. have had a lower overall age-adjusted breast cancer incidence rate than their non-Hispanic white counterparts,2 but a higher incidence of breast cancer than their white peers under age 40.3 However, in recent years, when as incidence rates have remained stable for whites but continue to increase for Blacks, Black-white breast cancer incidence rates converged in 2012.1 At the same time, Black women had a breast cancer mortality rate that was 42% higher than that of whites in 2012, this mortality rate has been consistently higher than that any other racial or ethnic group.1
The pattern of breast cancer mortality among Black women is complex (Table 1). In 2010, the age-adjusted breast cancer death rate for Black women was 40% higher than for their white peers.2 Although Black women had lower age-adjusted mortality than their white peers in 1950, their death rates have been on a small but consistent upward trajectory through 1980, with a marked increase in 1990 and a declining trend since then. White women, on the other hand, have had fairly stable death rates through 1990, with declining mortality rates in recent decades. This widening absolute and relative disparity since 1990 reflects larger declines in mortality for white than for Black women in recent decades.
Table 1. Age-adjusted and Age-Specific Death Rates for Breast Cancer for Black and Non-Hispanic White Women, 1950 to 2010.
1950 | 1960 | 1970 | 1980 | 1990 | 2000 | 2010 | |
---|---|---|---|---|---|---|---|
All ages, age-adjusted | |||||||
White (W) | 32.4 | 32.0 | 32.5 | 32.1 | 33.2 | 26.3 | 21.5 |
Black (B) | 25.3 | 27.9 | 28.9 | 31.7 | 38.1 | 34.5 | 30.3 |
B-W Difference | -7.1 | -4.1 | -3.6 | -0.4 | 4.9 | 8.2 | 8.8 |
B/W Ratio | 0.8 | 0.9 | 0.9 | 1.0 | 1.1 | 1.3 | 1.4 |
| |||||||
35-44 years | |||||||
White (W) | 20.8 | 19.7 | 20.2 | 17.3 | 17.1 | 11.3 | 8.8 |
Black (B) | 21.0 | 24.8 | 24.4 | 24.1 | 25.8 | 20.9 | 18.3 |
B-W Difference | 0.2 | 5.1 | 4.2 | 6.8 | 8.7 | 9.6 | 9.5 |
B/W Ratio | 1.0 | 1.3 | 1.2 | 1.4 | 1.5 | 1.8 | 2.1 |
| |||||||
45 -54 years | |||||||
White (W) | 47.1 | 51.2 | 53.0 | 48.1 | 44.3 | 31.2 | 23.9 |
Black (B) | 46.5 | 54.4 | 52.0 | 52.7 | 60.5 | 51.5 | 40.9 |
B-W Difference | -0.6 | 3.2 | -1.0 | 4.6 | 16.2 | 20.3 | 17.0 |
B/W Ratio | 1.0 | 1.1 | 1.0 | 1.1 | 1.4 | 1.7 | 1.7 |
| |||||||
55-64 years | |||||||
White (W) | 70.9 | 71.8 | 79.3 | 81.3 | 78.5 | 57.9 | 45.9 |
Black (B) | 64.3 | 63.2 | 64.7 | 79.9 | 93.1 | 80.9 | 70.5 |
B-W Difference | -6.6 | -8.6 | -14.6 | -1.4 | 14.6 | 23.0 | 24.6 |
B/W Ratio | 0.9 | 0.9 | 0.8 | 1.0 | 1.2 | 1.4 | 1.5 |
| |||||||
65-74 years | |||||||
White (W) | 96.3 | 91.6 | 95.9 | 103.7 | 113.3 | 89.3 | 73.2 |
Black (B) | 67.0 | 72.3 | 77.3 | 84.3 | 112.2 | 98.6 | 97.4 |
B-W Difference | -29.3 | -19.3 | -18.6 | -19.4 | -1.1 | 9.3 | 24.2 |
B/W Ratio | 0.7 | 0.8 | 0.8 | 0.8 | 1.0 | 1.1 | 1.3 |
| |||||||
75-84 years | |||||||
White (W) | 143.6 | 132.8 | 129.6 | 128.4 | 148.2 | 130.2 | 110.2 |
Black (B) | 81.0 | 87.5 | 101.8 | 114.1 | 140.5 | 139.6 | 123.2 |
B-W Difference | -62.6 | -45.3 | -27.8 | -14.3 | -7.7 | 9.4 | 13.0 |
B/W Ratio | 0.6 | 0.7 | 0.8 | 0.9 | 0.9 | 1.1 | 1.1 |
| |||||||
85 years or over | |||||||
White (W) | 204.2 | 199.7 | 161.9 | 171.7 | 198.0 | 205.5 | 186.8 |
Black (B) | N/A | 92.1 | 112.1 | 149.9 | 201.5 | 238.7 | 214.6 |
B-W Difference | ---- | -107.6 | -49.8 | -21.8 | 3.5 | 33.2 | 27.8 |
B/W Ratio | ---- | 0.5 | 0.7 | 0.9 | 1.0 | 1.2 | 1.1 |
National Center for Health Statistics, 2014
Age standardization, a useful strategy that provides an equal basis for comparing populations that differ in age structure, can obscure an accurate picture of the nature and extent of racial differences in health because an age-adjusted rate is not an accurate measure of actual risk.2,4 Age-adjusted rates are typically calculated using the age structure of a standard population. However, the choice of a standard is arbitrary and the age structure of a standard population can introduce biases that favor one population over another.5 Age standardization can thus lead to under-estimation of racial disparities in mortality risks, including breast cancer.4,5
The age-specific mortality rates in Table 1 provide a picture of the actual racial gap in breast cancer mortality for specific age groups. In 2010, the Black/white ratio shows that in contrast to the 40% higher overall age-adjusted mortality rate, Black women had a death rate for breast cancer that is more than twice as high as whites at ages 35-44, 70% higher at ages 45-54, and 50% higher at ages 55-64. The absolute Black-white difference is also markedly larger at all age groups than the age-adjusted overall 8.8 deaths per 100,000 population. With the exception of the 35-44 and the 75-84 age groups, the difference is twice as large. In terms of trends over time, the age-specific rates show that for the two youngest age groups, a racial disparity in breast cancer mortality is evident as early as 1960.
Racial differences in the severity, course and treatment of breast cancer contribute to these racial differences in mortality. Compared to their white peers, Black women are more likely to be diagnosed at a later stage, less likely to receive stage-appropriate treatment, and are more likely to have lower stage-for-stage survival rates.3,6 Black women also have a higher risk of poor prognosis types of cancer. Compared to white women, Black women, especially premenopausal women, are more likely to be diagnosed with estrogen receptor negative (ERneg) tumors and ERneg subtypes, including “triple negative” (TN).3 They are also more likely to be negative for the progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) tumors. Basal-like tumors are another subtype of breast tumors that are also high-grade cancers with poor survival. The joint ER/PR status of tumors is a stronger predictor of mortality than either status considered alone, and kinetic measures of breast cancer are also better predictors of treatment response and outcome than the more traditional static measures.7,8 Importantly, Black women are more likely than their white counterparts to have subtypes of breast cancer tumors that are more aggressive, more resistant to treatment, and that do not have clear molecular targets for treatment. These differences in the prevalence of breast cancer subtypes are directly related to differential outcomes.3,9 For example, the poor-prognosis tumors more common among premenopausal Black women have higher proliferation rates, poorer differentiation, greater lymph node involvement and larger tumor size.
The reasons underlying the higher prevalence of poor prognosis cancers among Black women are not fully understood. Reproductive factors that protect against ER/PR-positive breast cancers in Black women, including multi-parity, younger age at menarche, and early age at first pregnancy also increase the risk of ERneg and PRneg breast cancer.3 Premenopausal aggressive subtypes of breast cancer are also common in Black women in West Africa (although overall breast cancer rates are low), Great Britain, and the Caribbean.3,9 Compared to non-Hispanic white women, Hispanic Black women have patterns of late stage diagnosis and breast cancer mortality that is similar in magnitude to those of non-Hispanic Black women, unlike the pattern of Hispanic white women.10 These patterns suggest that genetic risks linked to African ancestry may play some role. An alternative hypothesis is that populations of African ancestry in different geographic contexts, may face common exposures linked to social and economic adversity due to skin color or discrimination that may increase breast cancer risks through poor access to health care, exposure to social and environmental assaults, or increased psychosocial stress. Many biological features of breast cancer are historically contingent and context dependent in this way. Variations in breast cancer incidence by age and the association of ER negative tumors with race and SES have varied over time, and even the ER status of a tumor is not a fixed characteristic.11
A Lifecourse Approach: The Link between Cumulative Adversity and Disease
Advancing our understanding of the environmental contribution to breast cancer risk and to potential levers for intervention requires greater attention to capturing pathogenic exposures over the lifecourse. Very limited evidence suggests that early life stressors may increase the risk of breast cancer, as well as other chronic illnesses, and some have argued that a perspective that emphasizes early life exposures can integrate the diverse risk factors for breast cancer that have emerged in the epidemiologic literature.12 The early onset, severity, and poorer survival of breast cancer among Black women must be understood within the context of an emerging body of scientific evidence that has documented dramatic earlier onset of disease across multiple health conditions (including cardiovascular and kidney disease) for Blacks compared to whites. This highlights the central role that racial differences in exposures over the lifecourse in family, neighborhood and occupational environments may play in racial disparities in health.13 The terms accelerated aging, premature age and biological weathering are used in the literature to describe this phenomenon of the earlier onset and poorer prognosis of illness across multiple chronic diseases.
Geronimus and colleagues term this greater physiological wear and tear of U.S. Blacks and the more rapid biological aging that they experience relative to whites as “weathering.”14 This accelerated aging, in turn, leads to the early incidence of multiple chronic illnesses. Such weathering among African Americans and other disadvantaged communities is driven by the cumulative impact of repeated exposures to psychological, social, physical and chemical stressors in their residential, occupational and other environments, and by coping with these stressors. Thus, for groups living in adverse living conditions, chronological age captures the cumulative impact of exposure to these risks.
The concept of allostatic load (AL) has been used to capture the biological dysregulation across multiple physiological systems that results from the cumulative burden of repeated stressors. In a national study by Geronimus and colleagues, AL increased with age for both Blacks and whites, but the mean score of AL for whites aged 55-64 years old was identical to that of Blacks who were 10 years younger.15 Data from two national studies also reveal that elevated AL scores capture exposure to adversity over the lifecourse. One study found that economic adversity during childhood and at two points in adulthood, individually and cumulatively, predicted elevated AL scores in later life.16 The other documented that neighborhood SES was inversely related to AL and that Blacks who lived in low SES neighborhood environments had a 200% increased odds of having high AL compared to those in high SES neighborhood.17
A review of studies using national data also revealed that elevated AL is associated with poor health.17 Individuals with high AL had a life expectancy that was 6 years shorter than those with low AL scores and both Blacks and whites under the age of 65 with high AL scores, had mortality rates more than twice that of those with low AL scores. Another study found that elevated AL scores were associated with a history of breast cancer for Black women but unrelated for white women.18 It was unclear if AL scores reflected a greater biological burden of breast cancer or captured a risk factor for the incidence of the disease. Telomere length is another indicator of biological aging that captures, at least in part, adversity and stress experienced by the individual. A study of middle-aged women found that at the same chronological age, Black women had shorter telomeres than white women; this difference was equivalent to accelerated biological aging of about 7.5 years.15
Finally, there is a burgeoning body of epigenetics research investigating on the impact of early life stressors on disease via dysregulation of the stress pathway (i.e., the hypothalamic–pituitary–adrenal (HPA) axis). DNA methylation at various points along NR3C1, the gene that codes for the glucocorticoid receptor (GR) on the HPA axis, has been associated with early childhood history of social adversity (e.g., childhood loss of a parent,19 childhood abuse,19-21 psychological trauma and stressors,22 or anxiety23), even if the stressful event occurred decades before the DNA was analyzed. These data have established that blood DNA methylation throughout NR3C1 represents a unique record of past adverse psychosocial experience. Increased methylation of NR3C1, in turn, has been associated with increased risk of a many illnesses. In a recent case-control study of NR3CI methylation and breast cancer, the authors found 15% of breast cancer tumors to be methylated, while no samples of the normal breast tissue were methylated.24 These emerging data offer a preliminary suggestion that psychosocial stress, operating via the stress pathway, may contribute to breast cancer risk.
As the next several sections will show, using a lifecourse approach to understand how socioeconomic status, psychosocial stress or adversity and other prenatal and early life exposures come together to increase risk of breast cancer later in life is especially important for trying to understand the development of current disparities in breast cancer incidence and mortality. That is, given that minority and underserved populations in the U.S. are more likely suffer from greater poverty and various psychosocial stressors early in life, particular attention needs to be paid towards how these early life exposures contribute to disease risk later in life, and only a lifecourse perspective can help to elucidate this.
Socioeconomic Status and Breast Cancer
SES is a social factor that is a strong predictor of variation in health for a broad range of outcomes. However, the association between SES and breast cancer is complex. Breast cancer incidence rates, for all racial/ethnic groups, tend to be positively associated with SES.25 At the same time, low SES is associated with increased risk of aggressive premenopausal breast cancers as well as late-stage of diagnosis and poorer survival.3,26 However, future research needs to better incorporate SES into studies of breast cancer since there are large racial differences in SES and SES is a likely contributor to the elevated risk of aggressive cancers among young Black women. For example, in 2013, Black households in the U.S. earned 59 cents for every dollar of income earned by white households -- identical to the racial gap in income in 1978.27 Most large scale studies of SES and breast cancer in the U.S. have used area-based measures of SES that imperfectly capture variation at the household level. However, individual or household levels of income, education or occupational status understate racial differences in SES because they do not capture the striking racial differences in economic assets and wealth. For example, in 2011, for every dollar of wealth that white households had, Latino households had 7 cents and Black households had only 6 cents.27
The ways in which lower SES shapes the trajectory of breast cancer risk factors over the lifecourse are complex and multifactorial. The influence of early childhood exposures on breast cancer risk later in life is particularly complex. Inadequate attention has been paid to the various ways that SES may contribute to breast cancer risk over the lifecourse, but especially in the early childhood period, via many pathways that are associated with specific risk factors. The association of low SES with early menarche, which is also associated with an increased risk of breast cancer,28 is one example. Over the last 50 years, average age of menarche has declined in the U.S. for both Black and white women, but there has consistently been an almost two-fold greater risk of early menarche for Black versus white females.29 Several environmental factors, patterned by SES, have been linked to increased risk of early menarche. These include prenatal smoke exposure,30 obesity and higher rates of change in childhood BMI,31 excessive weight gain in the first 9 months of life,32 low fruit and vegetable intake,33 chronic stress in the family,34 and characteristics of the neighborhood environment, such as the absence of recreational outlets.35 Research also reveals that childhood SES may be directly associated with age at menarche, with one study finding that for Blacks, whites and Hispanics, low SES (a composite measure of parental income, education and occupation) at age 7, as well as reductions in SES between birth and age 7, were associated with earlier age at menarche.36 Future research needs to better assess how early childhood SES combines with SES in later life to predict risks of breast cancer.
Stress and Breast Cancer: Timing is (almost) Everything
A second social factor that could potentially contribute to breast cancer risk that needs to be considered from a lifecourse perspective is psychosocial stress. Prior research on stress in relation to both breast cancer incidence and relapse provides little consistent evidence that exposure to stressors is a risk factor,37,38 but existing studies are limited by an over-reliance on measures that assess exposure to only a few recent stressors in adulthood.13
Scientific evidence suggests that childhood exposures, however, may shape adult health risks through processes of biological embedding or developmental programming in which early life experiences can trigger long-term changes in biological processes in stable and predictable ways that lead to elevated health risks over the lifecourse.39 In addition, severe and/or enduring forms of early life physical and psychosocial exposures can shape adult risks through their effects on adult health behaviors (smoking, alcohol use, nutrition).40 These complex processes may produce epigenetic changes that span both an individual's lifetime and across generations.41
Some limited evidence suggests that severe stressors in early life are specifically associated with increased risk of cancer in adults. A study of Canadian adults found that physical abuse as a child by someone close to the respondent was associated with higher odds of cancer.42 A national study in the U.S. also found that among men and women, parental emotional and physical abuse were associated with increased cancer risk.43 Another study found that stressors that occurred at least 20 years prior to breast cancer hospitalization (maternal death in childhood and chronic depression with severe episodes) predicted increased risk of breast cancer.44 Importantly, recent life events and depression and anxiety disorders were not associated with breast cancer risk, suggesting that only certain severe distal conditions were pathogenic.
Limited evidence also suggests that prenatal stress may be associated with increased risk of cancer. A study of children born in Denmark and Sweden found that children born to women who lost a child or spouse (but not other relatives), during the year before pregnancy, or during pregnancy, had a 30% increased risk of any childhood cancer.45 The hazard ratios (HR) were largest for non-Hodgkin disease (HR=3.40), hepatic cancer (HR=5.51) and testicular cancer (HR = 8.52). Future research needs to better elucidate the conditions under which a broader range of maternal psychosocial stressors and other exposures may be associated with the subsequent risk of breast cancer.
Behavioral pathways are one way that such psychosocial stressors may affect cancer risks. Obesity is a major risk factor for breast cancer, although the risk may be greater in postmenopausal breast cancer, suggesting that increased caloric intake and reduced physical activity leading to obesity is likely to be important for breast cancer. Research reveals that severe childhood adversity (emotional and physical abuse from parents and penetrative childhood sexual abuse) has been associated with being obese or overweight as an adult.46,47 Research also reveals that excessive pregnancy weight gain is associated with increased risk of breast cancer, independent of the mother's weight at the time of diagnosis.48
Finally, some very limited research does suggest that early life stressors may be directly associated with the progression of breast cancer specifically. A small study of women who had had surgery for breast cancer found that early life abuse and neglect was associated with higher levels of perceived stress, poorer quality of life, and elevated IL-6.49 Similarly, early childhood abuse, neglect, and residence in a chaotic home environment were associated with elevated markers of inflammation among women who had completed primary treatment for breast cancer.50
This emerging body of literature suggesting that early life stressors leave a biological imprint that last decades into adulthood, and which subsequently increase risk of cancer and other chronic illnesses, emphasizes the importance of racial differences in exposures to early life stressors, and thus the social context of disease. It is well documented, for example, that Black children experience higher rates of abuse and neglect than whites.51 Child abuse and neglect in the U.S. has in turn been tied to poverty, and Black children suffer from a rate of poverty three times higher than white children.52 Furthermore, Black children are twice as likely as white children to witness domestic violence and 20 times more likely to witness a murder.53 The critical role of psychosocial stress in early childhood at the individual and community levels in shaping the trajectory of breast cancer risk for Black women cannot be ignored if we are to have a full appreciation for the social context and its impact on health over the lifecourse. Our current knowledge is fairly limited, however, about which specific markers of childhood adversity are most pathogenic, the length of exposure necessary to trigger adverse health effects, and the pathways (psychological, behavioral and physiological) that link early childhood exposures to breast cancer risk.40
Other Prenatal and Early Life Exposures
Nutrition and other related factors in early life and into adulthood also affect breast cancer risk. In contrast to CVD, lower birthweight (BW) tends to be associated with lower risk of breast cancer.54,55 Risk of breast cancer increases in a graded manner with increasing birthweight, and cancer risk linked to BW is often strongest for pre-menopausal breast cancer. Higher BW likely reflects abundance of prenatal nutrition and the relative amount of specific nutrients in the maternal diet. Other recent evidence suggests that while red meat consumption in midlife is not a consistent predictor of breast cancer risk, red meat in early adulthood and especially in adolescence is associated with breast cancer overall and premenopausal breast cancer in particular.56 Research also documents the importance of a lifecourse perspective in understanding the effects of alcohol on breast cancer: the more alcohol a woman drinks between puberty and her first full-term pregnancy, the greater her risk of developing breast cancer.57 A priority for future research should be a more systematic examination of how social contexts shape access to healthy foods, and how the prenatal and early nutritional environment may be associated with breast cancer risk through epigenetic changes that increase health risks over the life course.54,55
Comprehensively Assessing Environmental Exposures
Research seeking to shed light on racial differences in breast cancer should begin with a clear recognition that self-identified racial categories capture simultaneous confounding for unmeasured social, biological and environmental factors.13,58 Contemporary racial categories vary on a broad range of social, behavioral, nutritional, psychological, residential, occupational and other variables. However, most of the specific environmental factors have not been identified. Research is needed to comprehensively characterize the multiple exposures in the social psychological, physical, chemical and built environment that can contribute to breast cancer risk, and to assess potential interactions between the social environment and both inherited and acquired biological factors.
Research on stress indicates that failure to measure stressors comprehensively can dramatically understate the effects of stress on health.59 It has also been noted that the measures of stress in prior research on breast cancer fail to capture the full range of acute and chronic stressful experiences.37 Compared to whites, Blacks experience higher levels of stressors in multiple domains of life, greater clustering of stressors, and probably greater duration and intensity of stressors.60 Large racial differences in income and wealth suggests that greater attention should be given to capturing all of the stressors linked to social and material deprivation and the extent to which their greater clustering could lead to more adverse effects on minorities than on whites. Compared to whites, Blacks and Hispanics receive less income at the same education levels, have markedly less wealth at equivalent income levels, have less purchasing power due to higher costs of goods and services in the residential environments where they are disproportionately located, and live in more disadvantaged neighborhoods at the same income level.13 Middle class Black women make larger contributions to the financial and social well-being of poorer relatives than their white counterparts; they are also more likely to live in neighborhoods with higher poverty, more female-headed households, and fewer college graduates.61 It is important for future research to capture the duration and intensity of poverty and other economic and social stressors.
The comprehensive assessment of stressors in future research also needs to include measures of discrimination -- a distinctive social exposure experienced by racial minorities. A recent review documented that self-reported measures of discrimination were adversely related to multiple disease conditions, early indicators of clinical disease potentially relevant for breast cancer (e.g., inflammation, visceral fat, obesity, AL, oxidative stress, shorter telomeres and cortisol dysregulation), and health behaviors (e.g., poor sleep, cigarette smoking, and substance use).62 In the Black Women's Health Study, the largest cohort of Black women in the U.S., racial discrimination was recently associated with increased incidence of breast cancer.63 This association was stronger among women aged 50 years or younger and among those who reported discrimination in multiple contexts. Discrimination was also associated with increased incidence of obesity.64 Discrimination should be assessed over the lifecourse, as a recent study documented that diurnal cortisol rhythms at age 32 were predicted by experiences of discrimination in the prior 20 years.65
Residential segregation by race has created pathogenic neighborhood conditions with African Americans in the U.S. living in markedly health-damaging environments.13 Accordingly, the neighborhoods where Black women live have more adverse environmental conditions, including lower income, education and home ownership rates and higher rates of poverty, crime, residential instability, overcrowding and unemployment compared to those of whites.66 Neighborhood conditions are also associated with access to a broad range of exposures that are related to health, including medical care, the quality and availability of nutritious food, safe places to exercise, access to and quality of public services and environmental pollutants.66 Future research needs to elucidate how all of these exposures may combine to determine breast cancer risk.
Residential and occupational segregation are also distinctive in triggering exposure to toxic substances in the physical, built and chemical environment. More research attention should also be given to the potential contribution of chemical exposures to breast cancer risk and to racial disparities in breast cancer. Laboratory studies reveal that hundreds of common chemicals activate biological pathways and cause mammary tumors, that hormone disrupters interact with the estrogen receptor and promote tumor proliferation, and that developmental toxicants alter mammary gland development and cancer susceptibility in rodents.67 These chemicals are widespread in air and water pollution, consumer products, house, dust and human tissues. These environmental factors could directly relate to breast cancer risks and could also interact with psychosocial factors to influence risk. Given the disproportionate poverty of African Americans, and the accompanying poor quality housing and neighborhood conditions, the role of the home and residential environment in breast cancer risk remains a strikingly understudied area of research.
There has also been a lack of study of positive influences within the social context of African Americans that may contribute to resiliency and health. Supportive influences, such as psychosocial support and emotional and religious coping, for example, may attenuate the negative consequences of psychosocial stress by modifying the reaction to stress.68,69 Religious coping/religiosity has been associated inversely with ambulatory blood pressure, colon cancer risk, and overall mortality.70-72 Religious women with breast cancer were found to have a decreased risk of death from breast cancer relative to nonreligious women.73
Genomic research in the area of breast cancer disparities is also needed that would give increased attention to the comprehensive, detailed, and rigorous characterization of the risk factors/resources in the psychological, social, chemical and physical environment that may interact with genetic factors to predict health risks. That is, we need an integrated science to give systematic attention to understanding the contribution of epigenetics and somatic mutations to disease risk.
Enhancing the Science of Prevention
Research is also needed to strengthen the science base that would identify optimal strategies to increase awareness of behavioral risk factors for breast cancer, and that could be used to effectively intervene on the social factors that often initiate and sustain these risk behaviors. Some of the key behavioral areas for primary prevention that are applicable to breast cancer are physical activity, alcohol consumption, breastfeeding, early life conditions, dietary factors and overweight and obesity.74 Social and behavioral research can also contribute to maximizing the contribution of medical care to reduce breast cancer risks through secondary prevention (early diagnosis and screening) and by reducing racial disparities in treatment.
Need for Primary Prevention
A meta-analysis of prospective studies on the association between physical activity and breast cancer documented an inverse association between both occupational and non- occupational physical activity and breast cancer risk.75 Increased physical activity in early life and adulthood could contribute to reducing obesity in early and adult life, and physical activity may be an especially potent prevention strategy for African American women, given that the protective effect was more marked among premenopausal women and for ER negative and PR negative breast cancer tumors.
Alcohol is a human carcinogen,76 and a dose-response relationship exists between alcohol consumption and breast cancer, as well as certain other cancers.76 One drink of alcohol per day, regardless of type, is associated with about a 10% increase in breast cancer, with three drinks a day associated with about a 40% increase.77 The extent to which alcohol use contributes to racial disparities in breast cancer is not clearly understood. Black women tend to have lower consumption of alcohol than their white peers, but alcohol has more negative effects on Blacks than on whites, with the cardiovascular benefits of moderate alcohol consumption evident in research for whites being non-existent for Blacks.13 Evidence of confounding in research on moderate alcohol use and CVD, as well as methodological limitations of this literature, raise questions about the extent of the moderate alcohol benefit to CVD.78-81 Public health experts emphasize that reducing alcohol use is a vital and neglected cancer prevention strategy, and that greater attention should be given to effectively communicating the role of alcohol as a risk factor for breast cancer.76
Breastfeeding, including duration and the number of children breastfed, is associated with reduced risk of aggressive premenopausal breast cancer.3,82 White women have higher levels of breastfeeding and longer breastfeeding duration than Black women.83 One population-based study estimated that increasing breastfeeding and reducing abdominal obesity could eliminate 68% of basal-like breast cancers in young Black women, and over half of breast cancer in the general population.82 Research reveals that experiences during hospitalization for childbirth are important for initiating breastfeeding, and that hospitals in areas with a higher percentage of Black residents are less likely to offer their patients recommended practices supportive of breast feeding.83 The use of community doulas (trained professionals who provide non-medical support to mothers) can lead to marked increases in breastfeeding.84
For all of these different risk factors, considerable evidence highlights the need to start prevention early. Data from a prebirth cohort found that by age seven, Black and Hispanic children were twice as likely as whites to be overweight and obese.85 Infancy and childhood risk factors contributing to this pattern included early feeding behaviors (non-optimal breast feeding, early solid foods), accelerated weight gain and obesity-related risk factors (TV in child's bedroom, inadequate sleep, sugar-sweetened drinks, fast food). Other research reveals that maternal economic disadvantage (reflected in low education, minority racial status, and being unmarried) during the prenatal period is adversely related to health at birth and has long-term negative associations with adult health and SES.86 Interventions, including some that begin before birth, can have positive effects on maternal and child health. These include reductions in negative health behaviors (e.g., smoking during pregnancy), enhanced environments (e.g., policies that lead to lower pollution and reduced violence exposure), increased access to medical care and family planning, nutritional supplements, early childhood enrichment programs (especially programs that start before the age of 3), and post-natal programs that provide additional income.86
Data also emphasize the need to appreciate the fact that prevention does not take place in a vacuum. Cancer prevention efforts are received by communities that are differentially burdened by stress, and this stress can affect individuals' capacity to respond and change health behaviors. For example, a recent study found that chronic stress alters energy homeostasis by activating peripheral mechanisms in fat tissue that augments the negative effects of sugar and fat on visceral tissue accumulation.87 Women who ate an unhealthy diet and scored high on chronic stress had larger increases in waist circumference than those who ate the same diet but had less stress.87 Other research indicates that addressing stress can facilitate behavioral change.88
Prevention science must also take a more nuanced approach in tackling health disparities. Often, such efforts focus solely on specific racial/ethnic communities, without taking into account the important dimension of socioeconomic position or the heterogeneity within racial and ethnic groups. Such approaches often assume that improving overall health within a minority group is the only valid goal, ignoring the fact that higher status groups within a particular community typically have greater knowledge about and access to interventions, higher levels of utilization, and often receive greater benefit from the intervention. Reducing child and adolescent obesity is a recent example. Although national data show a plateauing of the increases in adolescent obesity, for whites, Blacks and Hispanics, adolescent obesity is increasing for children of parents with a high school education or less, but declining for children of parents with a college degree or more education.89 Accordingly, we need intervention strategies that improve the health and health enhancing behaviors of Black women more rapidly than the rest of the population. Research is needed to identify the conditions under which interventions on behavioral risk factors have the greatest effect on socially marginalized and vulnerable populations who tend to have the highest levels and greatest clustering of risk factors. We also need a better understanding of how we can best remove the social, economic and psychological barriers that need to be addressed to ensure that historically disadvantaged populations experience the maximum benefits from interventions.
Health Care System Interventions
Interventions within the healthcare system can also play a critical role in the secondary prevention of breast cancer. The failure of Black women to receive timely diagnosis and optimal treatment for breast cancer, including the aggressive subtypes, is likely to be a major contributor to their elevated mortality risk.90 Disparities in the quality and intensity of care exist along the continuum of breast cancer; interventions for patients, providers and the health care system to reduce disparities have been identified.90,91 Evidence suggesting that equal treatment is associated with equal outcomes highlights the need for improvements in health care quality for Black women with breast cancer.6 Research reveals that many healthcare providers are unaware that racial disparities in healthcare treatment exist, and that some still question the existence of disparities.92 Research is needed to identify the optimal strategies for raising awareness regarding provider bias and the ways such bias influences clinical decision-making, and generating the motivation and commitment among healthcare providers to tackle such bias.
Lessons can be learned from a concerted and comprehensive Colorectal Cancer (CRC) initiative in the state of Delaware.93 This screening and treatment program covered the costs of cancer care for uninsured residents, and involved a nurse navigator system and special outreach efforts to African Americans. Within 8 years, the program eliminated disparities in screening and equalized incidence rates. The mortality gap was almost eliminated with a mortality decline of 42% for Blacks and 13% for whites. Furthermore, a Metropolitan Task Force established in 2007 in Chicago to address barriers in access to quality mammography screening and recommended treatment for breast cancer shows promise and illustrates how multiple sectors of a community (74 area organizations) can come together to improve breast cancer care.94
Conclusions
Black women are disadvantaged on multiple dimensions of access to economic and social resources in society. We need to better understand the ways in which these risk factors, at multiple levels of exposure, combine over the lifecourse with social and psychological resources or exposures to predict the development and course of breast cancer. Effectively reducing breast cancer disparities for Black women will thus require disentangling risk factors driven by racism versus those driven by socioeconomic status at these multiple levels (e.g., individual, neighborhood, health system). As discussed above, some social exposures associated with being Black in America, such as racism or SES, will be associated directly with breast cancer risk. In other cases, Black race or SES will mediate breast cancer risk through another variable (e.g., childhood adversity leading to adult obesity46,47). In investigating the social context of Black women and their risk for Breast cancer, however, it must be remembered that Black women are not a monolithic category. Rather, they are a varied and diverse group that encompasses many cultural communities and socioeconomic strata. Being Black in America is therefore not a risk category for developing breast cancer a priori, but rather makes up an “intersectionality,” as Kimberlé Crenshaw95 writes, of various cultural, social, economic and biological factors that together give shape to risk for breast cancer. Only when we can disaggregate the influences of the social factors affecting breast cancer risk related to race, SES and other relevant dimensions of identity will we be able to develop truly effective interventions.
Acknowledgments
Preparation of this paper was supported by grants P50 CA 148596 from the National Cancer Institute and grant #48424 from The John Templeton Foundation. We wish to thank Maria Simoneau, Liying Shen, and Bobak Seddighzadeh for their assistance with preparing the manuscript.
Footnotes
The authors report no conflicts of interest.
Author Contributions: David R. Williams: Conceptualization, methodology, investigation, original draft, writing – review and editing, project administration, and funding acquisition. Selina A. Mohammed: Conceptualization, methodology, investigation, data curation, writing – original draft, and writing – review and editing. Alexandra E. Shields: Conceptualization, methodology, investigation, data curation, writing – original draft, writing – review and editing, visualization, supervision, and project administration.
Conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing – original draft, writing – review and editing, visualization, supervision, project administration, funding acquisition
References
- 1.DeSantis CE, Fedewa SA, Goding Sauer A, Kramer JL, Smith RA, Jemal A. Breast cancer statistics, 2015: Convergence of incidence rates between black and white women. CA: A Cancer Journal for Clinicians. 2016;66(1):31–42. doi: 10.3322/caac.21320. [DOI] [PubMed] [Google Scholar]
- 2.National Center for Health Statistics. Health, United States, 2013. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2014. [Google Scholar]
- 3.Dunn BK, Agurs-Collins T, Browne D, Lubet R, Johnson KA. Health disparities in breast cancer: Biology meets socioeconomic status. Breast cancer research and treatment. 2010;121(2):281–292. doi: 10.1007/s10549-010-0827-x. [DOI] [PubMed] [Google Scholar]
- 4.Williams DR. The health of U.S. Racial and ethnic populations. Journals of Gerontology: Series B. 2005;60B(Special Issue II):53–62. doi: 10.1093/geronb/60.special_issue_2.s53. [DOI] [PubMed] [Google Scholar]
- 5.Fu M, Todem D, Fu WJ, Ma S. A millennium bug still bites public health - an illustration using cancer mortality. [Accessed April 8th, 2015];2014 Available at: http://arxiv.org/abs/1401.7686.
- 6.Brawley OW. Health disparities in breast cancer. Obstetrics and Gynecology Clinics North America. 2013;40(3):513–523. doi: 10.1016/j.ogc.2013.06.001. [DOI] [PubMed] [Google Scholar]
- 7.Dunnwald L, Rossing M, Li C. Hormone receptor status, tumor characteristics, and prognosis: A prospective cohort of breast cancer patients. Breast Cancer Res. 2007;9(1):1–10. doi: 10.1186/bcr1639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Dunnwald LK, Doot RK, Specht JM, et al. Pet tumor metabolism in locally advanced breast cancer patients undergoing neoadjuvant chemotherapy: Value of static versus kinetic measures of fluorodeoxyglucose uptake. Clinical Cancer Research. 2011;17(8):2400–2409. doi: 10.1158/1078-0432.CCR-10-2649. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Newman LA. Breast cancer disparities. Surgical Oncology Clinics. 2014;23(3):579–592. doi: 10.1016/j.soc.2014.03.014. [DOI] [PubMed] [Google Scholar]
- 10.Banegas M, Li C. Breast cancer characteristics and outcomes among hispanic black and hispanic white women. Breast cancer research and treatment. 2012;134(3):1297–1304. doi: 10.1007/s10549-012-2142-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Krieger N. History, biology, and health inequities: Emergent embodied phenotypes and the illustrative case of the breast cancer estrogen receptor. American Journal of Public Health. 2012;103(1):22–27. doi: 10.2105/AJPH.2012.300967. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Trichopoulos D, Adami HO, Ekbom A, Hsieh CC, Lagiou P. Early life events and conditions and breast cancer risk: From epidemiology to etiology. International Journal of Cancer. 2008;122(3):481–485. doi: 10.1002/ijc.23303. [DOI] [PubMed] [Google Scholar]
- 13.Williams DR, Mohammed SA, Leavell J, Collins C. Race, socioeconomic status, and health: Complexities, ongoing challenges, and research opportunities. Annals of the New York Academy of Sciences. 2010;1186(1):69–101. doi: 10.1111/j.1749-6632.2009.05339.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Geronimus AT, Hicken MT, Pearson JA, Seashols SJ, Brown KL, Cruz TD. Do US black women experience stress-related accelerated biological aging?: A novel theory and first population-based test of black-white differences in telomere length. Human nature. 2010;21(1):19–38. doi: 10.1007/s12110-010-9078-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Geronimus AT, Hicken M, Keene D, Bound J. “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States. Am J Public Health. 2006;96(5):826–833. doi: 10.2105/AJPH.2004.060749. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Gruenewald TL, Karlamangla AS, Hu P, et al. History of socioeconomic disadvantage and allostatic load in later life. Social Science and Medicine. 2012;74(1):75–83. doi: 10.1016/j.socscimed.2011.09.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Beckie TM. A systematic review of allostatic load, health, and health disparities. Biological Research For Nursing. 2012;14(4):311–346. doi: 10.1177/1099800412455688. [DOI] [PubMed] [Google Scholar]
- 18.Parente V, Hale L, Palermo T. Association between breast cancer and allostatic load by race: National Health and Nutrition Examination Survey 1999–2008. Psycho-Oncology. 2013;22(3):621–628. doi: 10.1002/pon.3044. [DOI] [PubMed] [Google Scholar]
- 19.Tyrka AR, Price LH, Marsit C, Walters OC, Carpenter LL. Childhood adversity and epigenetic modulation of the leukocyte glucocorticoid receptor: Preliminary findings in healthy adults. PLoS One. 2012;7(1):e30148. doi: 10.1371/journal.pone.0030148. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Romens SE, McDonald J, Svaren J, Pollak SD. Associations between early life stress and gene methylation in children. Child Dev. 86(1):303–309. doi: 10.1111/cdev.12270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Perroud N, Paoloni-Giacobino A, Prada P, et al. Increased methylation of glucocorticoid receptor gene (nr3c1) in adults with a history of childhood maltreatment: A link with the severity and type of trauma. Transl Psychiatry. 1:e59. doi: 10.1038/tp.2011.60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Steiger H, Labonte B, Groleau P, Turecki G, Israel M. Methylation of the glucocorticoid receptor gene promoter in bulimic women: Associations with borderline personality disorder, suicidality, and exposure to childhood abuse. Int J Eat Disord. 2013;46(3):246–255. doi: 10.1002/eat.22113. [DOI] [PubMed] [Google Scholar]
- 23.Hompes T, Izzi B, Gellens E, et al. Investigating the influence of maternal cortisol and emotional state during pregnancy on the DNA methylation status of the glucocorticoid receptor gene (nr3c1) promoter region in cord blood. J Psychiatr Res. 2013 Jul;47(7):880–91. doi: 10.1016/j.jpsychires.2013.03.009. Epub 2013 Apr 6. [DOI] [PubMed] [Google Scholar]
- 24.Nesset KA, Perri AM, Mueller CR. Frequent promoter hypermethylation and expression reduction of the glucocorticoid receptor gene in breast tumors. Epigenetics. 9(6):851–859. doi: 10.4161/epi.28484. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Yin D, Morris C, Allen M, Cress R, Bates J, Liu L. Does socioeconomic disparity in cancer incidence vary across racial/ethnic groups? Cancer causes & control : CCC. 2010;21(10):1721–1730. doi: 10.1007/s10552-010-9601-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Andaya AA, Enewold L, Horner MJ, Jatoi I, Shriver CD, Zhu K. Socioeconomic disparities and breast cancer hormone receptor status. Cancer causes & control : CCC. 2012;23(6):951–958. doi: 10.1007/s10552-012-9966-1. [DOI] [PubMed] [Google Scholar]
- 27.Williams DR, Priest N, Anderson NB. Understanding associations between race, socioeconomic status and health: Patterns and prospects. Health Psychology. doi: 10.1037/hea0000242. In Press. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Anderson BM, MacLennan MB, Hillyer LM, Ma DWL. Lifelong exposure to n-3 PUFA affects pubertal mammary gland development. Applied Physiology, Nutrition, and Metabolism. 2014;39(6):699–706. doi: 10.1139/apnm-2013-0365. [DOI] [PubMed] [Google Scholar]
- 29.Krieger N, Kiang MV, Kosheleva A, Waterman PD, Chen JT, Beckfield J. Age at menarche: 50-year socioeconomic trends among US-born black and white women. American Journal of Public Health. 2014;105(2):388–397. doi: 10.2105/AJPH.2014.301936. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Behie AM, O'Donnell MH. Prenatal smoking and age at menarche: Influence of the prenatal environment on the timing of puberty. Human Reproduction. 2015;30(4):957–962. doi: 10.1093/humrep/dev033. [DOI] [PubMed] [Google Scholar]
- 31.Lee JM, Appugliese D, Kaciroti N, Corwyn RF, Bradley RH, Lumeng JC. Weight status in young girls and the onset of puberty. Pediatrics. 2007;119(3):e624–e630. doi: 10.1542/peds.2006-2188. [DOI] [PubMed] [Google Scholar]
- 32.Ong KK, Emmett P, Northstone K, et al. Infancy weight gain predicts childhood body fat and age at menarche in girls. The Journal of Clinical Endocrinology & Metabolism. 2009;94(5):1527–1532. doi: 10.1210/jc.2008-2489. [DOI] [PubMed] [Google Scholar]
- 33.Mervish NA, Gardiner EW, Galvez MP, et al. Dietary flavonol intake is associated with age of puberty in a longitudinal cohort of girls. Nutrition Research. 2013;33(7):534–542. doi: 10.1016/j.nutres.2013.04.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Walvoord EC. The timing of puberty: Is it changing? Does it matter? Journal of Adolescent Health. 2010;47(5):433–439. doi: 10.1016/j.jadohealth.2010.05.018. [DOI] [PubMed] [Google Scholar]
- 35.Deardorff J, Fyfe M, Ekwaru JP, Kushi LH, Greenspan LC, Yen IH. Does neighborhood environment influence girls' pubertal onset? Findings from a cohort study. BMC Pediatrics. 2012;12(1):27. doi: 10.1186/1471-2431-12-27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.James-Todd T, Tehranifar P, Rich-Edwards J, Titievsky L, Terry MB. The impact of socioeconomic status across early life on age at menarche among a racially diverse population of girls. Annals of Epidemiology. 2010;20(11):836–842. doi: 10.1016/j.annepidem.2010.08.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Nielsen NR, Gronbaek M. Stress and breast cancer: A systematic update on the current knowledge. Nature clinical practice Oncology. 2006;3(11):612–620. doi: 10.1038/ncponc0652. [DOI] [PubMed] [Google Scholar]
- 38.Heikkilä K, Nyberg ST, Theorell T, et al. Work stress and risk of cancer: Meta-analysis of 5700 incident cancer events in 116 000 European men and women. BMJ. 2013;346 doi: 10.1136/bmj.f165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Hertzman C, Boyce T. How experience gets under the skin to create gradients in developmental health. Annual review of public health. 2010;31:329–347. doi: 10.1146/annurev.publhealth.012809.103538. [DOI] [PubMed] [Google Scholar]
- 40.Cohen S, Janicki-Deverts D, Chen E, Matthews KA. Childhood socioeconomic status and adult health. Annals of the New York Academy of Sciences. 2010;1186(1):37–55. doi: 10.1111/j.1749-6632.2009.05334.x. [DOI] [PubMed] [Google Scholar]
- 41.Kuzawa CW, Sweet E. Epigenetics and the embodiment of race: Developmental origins of US racial disparities in cardiovascular health. Am J Hum Biol. 2009;21(1):2–15. doi: 10.1002/ajhb.20822. [DOI] [PubMed] [Google Scholar]
- 42.Fuller-Thomson E, Brennenstuhl S. Making a link between childhood physical abuse and cancer. Cancer. 2009;115(14):3341–3350. doi: 10.1002/cncr.24372. [DOI] [PubMed] [Google Scholar]
- 43.Morton PM, Schafer MH, Ferraro KF. Does childhood misfortune increase cancer risk in adulthood? Journal of aging and health. 2012;24(6):948–984. doi: 10.1177/0898264312449184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Jacobs JR, Bovasso GB. Early and chronic stress and their relation to breast cancer. Psychological medicine. 2000;30(3):669–678. doi: 10.1017/s0033291799002020. [DOI] [PubMed] [Google Scholar]
- 45.Li J, Vestergaard M, Obel C, et al. Antenatal maternal bereavement and childhood cancer in the offspring: A population-based cohort study in 6 million children. British Journal of Cancer. 2012;107(3):544–548. doi: 10.1038/bjc.2012.288. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Greenfield EA, Marks NF. Violence from parents in childhood and obesity in adulthood: Using food in response to stress as a mediator of risk. Social science & medicine. 2009;68(5):791–798. doi: 10.1016/j.socscimed.2008.12.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Mamun AA, Lawlor DA, O'Callaghan MJ, Bor W, Williams GM, Najman JM. Does childhood sexual abuse predict young adult's BMI? A birth cohort study. Obesity. 2007;15(8):2103–2110. doi: 10.1038/oby.2007.250. [DOI] [PubMed] [Google Scholar]
- 48.Kinnunen TI, Luoto R, Gissler M, Hemminki E, Hilakivi-Clarke L. Pregnancy weight gain and breast cancer risk. BMC Women's Health. 2004;4(1):1–10. doi: 10.1186/1472-6874-4-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Witek Janusek L, Tell D, Albuquerque K, Mathews HL. Childhood adversity increases vulnerability for behavioral symptoms and immune dysregulation in women with breast cancer. Brain, Behavior, and Immunity. 2013;30(Supplement):S149–S162. doi: 10.1016/j.bbi.2012.05.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Crosswell AD, Bower JE, Ganz PA. Childhood adversity and inflammation in breast cancer survivors. Psychosomatic Medicine. 2014;76(3):208–214. doi: 10.1097/PSY.0000000000000041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Wildeman C, Emanuel N, Leventhal JM, Putnam-Hornstein E, Waldfogel J, Lee H. The prevalence of confirmed maltreatment among US children, 2004 to 2011. JAMA pediatrics. 2014;168(8):706–713. doi: 10.1001/jamapediatrics.2014.410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Lanier P, Maguire-Jack K, Walsh T, Drake B, Hubel G. Race and ethnic differences in early childhood maltreatment in the United States. J Dev Behav Pediatr. 2014;35(7):419–426. doi: 10.1097/DBP.0000000000000083. [DOI] [PubMed] [Google Scholar]
- 53.Finkelhor D, Ormrod R, Turner H, Hamby SL. The victimization of children and youth: A comprehensive, national survey. Child maltreatment. 2005;10(1):5–25. doi: 10.1177/1077559504271287. [DOI] [PubMed] [Google Scholar]
- 54.Burdge GC, Lillycrop KA, Jackson AA. Nutrition in early life, and risk of cancer and metabolic disease: Alternative endings in an epigenetic tale? The British journal of nutrition. 2009;101(5):619–630. doi: 10.1017/S0007114508145883. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Xue F, Michels KB. Intrauterine factors and risk of breast cancer: A systematic review and meta-analysis of current evidence. The Lancet Oncology. 2007;8(12):1088–1100. doi: 10.1016/S1470-2045(07)70377-7. [DOI] [PubMed] [Google Scholar]
- 56.Farvid MS, Cho E, Chen WY, Eliassen AH, Willett WC. Dietary protein sources in early adulthood and breast cancer incidence: Prospective cohort study. 2014;348 doi: 10.1136/bmj.g3437. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Liu Y, Colditz GA, Rosner B, et al. Alcohol intake between menarche and first pregnancy: A prospective study of breast cancer risk. Journal of the National Cancer Institute. 2013 doi: 10.1093/jnci/djt213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Shields AE, Fortun M, Hammonds EM, et al. The use of race variables in genetic studies of complex traits and the goal of reducing health disparities: A transdisciplinary perspective. The American psychologist. 2005;60(1):77–103. doi: 10.1037/0003-066X.60.1.77. [DOI] [PubMed] [Google Scholar]
- 59.Thoits PA. Personal agency in the stress process. Journal of health and social behavior. 2006;47(4):309–323. doi: 10.1177/002214650604700401. [DOI] [PubMed] [Google Scholar]
- 60.Sternthal MJ, Slopen N, Williams DR. Racial disparities in health: How much does stress really matter? Du Bois Review. 2011;8(1):95–113. doi: 10.1017/S1742058X11000087. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Thomas CS. A new look at the black middle class: Research trends and challenges. Sociological Focus. 2015;48(3):191–207. [Google Scholar]
- 62.Lewis TT, Cogburn CD, Williams DR. Self-reported experiences of discrimination and health: Scientific advances, ongoing controversies, and emerging issues. Annual review of clinical psychology. 2015;11:407–440. doi: 10.1146/annurev-clinpsy-032814-112728. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Taylor TR, Williams CD, Makambi KH, et al. Racial discrimination and breast cancer incidence in US black women: The Black Women's Health Study. American Journal of Epidemiology. 2007;166(1):46–54. doi: 10.1093/aje/kwm056. [DOI] [PubMed] [Google Scholar]
- 64.Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the Black Women's Health Study. American Journal of Epidemiology. 2014;179(7):875–883. doi: 10.1093/aje/kwu004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Adam EK, Heissel JA, Zeiders KH, et al. Developmental histories of perceived racial discrimination and diurnal cortisol profiles in adulthood: A 20-year prospective study. Psychoneuroendocrinology. 2015;62:279–291. doi: 10.1016/j.psyneuen.2015.08.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Miranda ML, Maxson P, Edwards S. Environmental contributions to disparities in pregnancy outcomes. Epidemiologic Reviews. 2009 doi: 10.1093/epirev/mxp011. [DOI] [PubMed] [Google Scholar]
- 67.Brody JG, Kripke ML, Kavanaugh-Lynch MH, Rizzo J, Forman MR. Breast cancer and environmental research. Science. 2014;344(6184):577. doi: 10.1126/science.344.6184.577-a. [DOI] [PubMed] [Google Scholar]
- 68.Antonovsky A. Health, stress, and coping. Jossey-Bass; 1979. [Google Scholar]
- 69.Pargament KI, Smith BW, Koenig HG, Perez L. Patterns of positive and negative religious coping with major life stressors. Journal for the Scientific Study of Religion. 1998:710–724. [Google Scholar]
- 70.Chida Y, Steptoe A, Powell LH. Religiosity/spirituality and mortality. A systematic quantitative review. Psychotherapy and psychosomatics. 2009;78(2):81–90. doi: 10.1159/000190791. [DOI] [PubMed] [Google Scholar]
- 71.Kinney AY, Bloor LE, Dudley WN, et al. Roles of religious involvement and social support in the risk of colon cancer among blacks and whites. American Journal of Epidemiology. 2003;158(11):1097–1107. doi: 10.1093/aje/kwg264. [DOI] [PubMed] [Google Scholar]
- 72.Steffen PR, Hinderliter AL, Blumenthal JA, Sherwood A. Religious coping, ethnicity, and ambulatory blood pressure. Psychosomatic medicine. 2001;63(4):523–530. doi: 10.1097/00006842-200107000-00002. [DOI] [PubMed] [Google Scholar]
- 73.Van Ness PH, Kasl SV, Jones BA. Religion, race, and breast cancer survival. International journal of psychiatry in medicine. 2003;33(4):357–375. doi: 10.2190/LRXP-6CCR-G728-MWYH. [DOI] [PubMed] [Google Scholar]
- 74.Holman DM, Grossman M, Henley SJ, Peipins LA, Tison L, White MC. Opportunities for cancer prevention during midlife. American Journal of Preventive Medicine. 2014;46(3):S73–S80. doi: 10.1016/j.amepre.2013.10.030. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 75.Wu Y, Zhang D, Kang S. Physical activity and risk of breast cancer: A meta-analysis of prospective studies. Breast cancer research and treatment. 2013;137(3):869–882. doi: 10.1007/s10549-012-2396-7. [DOI] [PubMed] [Google Scholar]
- 76.Nelson DE, Jarman DW, Rehm J, et al. Alcohol-attributable cancer deaths and years of potential life lost in the United States. American Journal of Public Health. 2013;103(4):641–648. doi: 10.2105/AJPH.2012.301199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 77.Yang S, Lynch JW, Raghunathan TE, Kauhanen J, Salonen JT, Kaplan GA. Socioeconomic and psychosocial exposures across the life course and binge drinking in adulthood: Population-based study. American Journal of Epidemiology. 2007;165(2):184–193. doi: 10.1093/aje/kwj357. [DOI] [PubMed] [Google Scholar]
- 78.Naimi TS, Brown DW, Brewer RD, et al. Cardiovascular risk factors and confounders among nondrinking and moderate-drinking U.S. Adults. American Journal of Preventive Medicine. 2005;28(4):369–373. doi: 10.1016/j.amepre.2005.01.011. [DOI] [PubMed] [Google Scholar]
- 79.Fillmore KM, Kerr WC, Stockwell T, Chikritzhs T, Bostrom A. Moderate alcohol use and reduced mortality risk: Systematic error in prospective studies. Addiction Research and Theory. 2006;14(2):101–132. doi: 10.1016/j.annepidem.2007.01.005. [DOI] [PubMed] [Google Scholar]
- 80.Holmes MV, Dale CE, Zuccolo L, et al. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data. BMJ. 2014;349(g4164) doi: 10.1136/bmj.g4164. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Knott CS, Coombs N, Stamatakis E, Biddulph JP. All cause mortality and the case for age specific alcohol consumption guidelines: Pooled analyses of up to 10 population based cohorts. BMJ. 2015;350 doi: 10.1136/bmj.h384. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 82.Millikan RC, Newman B, Tse CK, et al. Epidemiology of basal-like breast cancer. Breast cancer research and treatment. 2008;109(1):141–141. doi: 10.1007/s10549-007-9632-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 83.Lind JN, Perrine CG, Li R, Scanlon KS, Grummer-Strawn LM. Racial disparities in access to maternity care practices that support breastfeeding — United States, 2011. Morbidity and Mortality Weekly Report (MMWR) 2014;63(33):725–728. [PMC free article] [PubMed] [Google Scholar]
- 84.Edwards RC, Thullen MJ, Korfmacher J, Lantos JD, Henson LG, Hans SL. Breastfeeding and complementary food: Randomized trial of community doula home visiting. Pediatrics. 2013;132(Supplement 2):S160–S166. doi: 10.1542/peds.2013-1021P. [DOI] [PubMed] [Google Scholar]
- 85.Taveras EM, Gillman MW, Kleinman KP, Rich-Edwards JW, Rifas-Shiman SL. Reducing racial/ethnic disparities in childhood obesity: The role of early life risk factors. JAMA pediatrics. 2013;167(8):731–738. doi: 10.1001/jamapediatrics.2013.85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Aizer A, Currie J. The intergenerational transmission of inequality: Maternal disadvantage and health at birth. Science. 2014;344(6186):856–861. doi: 10.1126/science.1251872. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 87.Aschbacher K, Kornfeld S, Picard M, et al. Chronic stress increases vulnerability to diet-related abdominal fat, oxidative stress, and metabolic risk. Psychoneuroendocrinology. 2014;46:14–22. doi: 10.1016/j.psyneuen.2014.04.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Williams DR, Mohammed SA. Racism and health II: A needed research agenda for effective interventions. American Behavioral Scientist. 2013;57(8):1200–1226. doi: 10.1177/0002764213487341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 89.Frederick CB, Snellman K, Putnam RD. Increasing socioeconomic disparities in adolescent obesity. Proceedings of the National Academy of Sciences of the United States of America. 2014;111(4):1338–1342. doi: 10.1073/pnas.1321355110. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Wheeler SB, Reeder-Hayes KE, Carey LA. Disparities in breast cancer treatment and outcomes: Biological, social, and health system determinants and opportunities for research. The Oncologist. 2013;18(9):986–993. doi: 10.1634/theoncologist.2013-0243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Roberts MC, Wheeler SB, Reeder-Hayes K. Racial/ethnic and socioeconomic disparities in endocrine therapy adherence in breast cancer: A systematic review. American Journal of Public Health. 2015;105(S3):e4–e15. doi: 10.2105/AJPH.2014.302490. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 92.van Ryn M, Burgess DJ, Dovidio JF, et al. The impact of racism on clinician cognition, behavior, and clinical decision making. Du Bois Review. 2011;8(1):199–218. doi: 10.1017/S1742058X11000191. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Grubbs SS, Polite BN, Carney JJ, et al. Eliminating racial disparities in colorectal cancer in the real world: It took a village. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2013;31(16):1928–1930. doi: 10.1200/JCO.2012.47.8412. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 94.Ansell D, Grabler P, Whitman S, et al. A community effort to reduce the black/white breast cancer mortality disparity in chicago. Cancer Causes and Control. 2009;20(9):1681–1688. doi: 10.1007/s10552-009-9419-7. [DOI] [PubMed] [Google Scholar]
- 95.Crenshaw K. Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. The University of Chicago Legal Forum. 1989:139–167. [Google Scholar]