Abstract
Background
The objective of this study was to examine the association between racialized economic segregation, allostatic load (AL), and all-cause mortality in patients with breast cancer.
Patients and Methods
Women aged 18+ years with stage I–III breast cancer diagnosed between 01/01/2012 and 31/12/2020 were identified in the Ohio State University cancer registry. Racialized economic segregation was measured at the census tract level using the index of concentration at the extremes (ICE). AL was calculated with biomarkers from the cardiac, metabolic, immune, and renal systems. High AL was defined as AL greater than the median. Univariable and multivariable regression analyses using restricted cubic splines examined the association between racialized economic segregation, AL, and all-cause mortality.
Results
Among 4296 patients, patients residing in neighborhoods with the highest racialized economic segregation (Q1 versus Q4) were more likely to be Black (25% versus 2.1%, p < 0.001) and have triple-negative breast cancer (18.2% versus 11.6%, p < 0.001). High versus low racialized economic segregation was associated with high AL [adjusted odds ratio (aOR) 1.40, 95% confidence interval (CI) 1.21–1.61] and worse all-cause mortality [adjusted hazard ratio (aHR) 1.41, 95% CI 1.08–1.83]. In dose–response analyses, patients in lower segregated neighborhoods (relative to the 95th percentile) had lower odds of high AL, whereas patients in more segregated neighborhoods had a non-linear increase in the odds of high AL.
Discussion
Racialized economic segregation is associated with high AL and a greater risk of all-cause mortality in patients with breast cancer. Additional studies are needed to elucidate the causal pathways and mechanisms linking AL, neighborhood factors, and patient outcomes.
Similar content being viewed by others
References
Ooi SL, Martinez ME, Li CI. Disparities in breast cancer characteristics and outcomes by race/ethnicity. Breast Cancer Res Treat. 2011;127(3):729–38. https://doi.org/10.1007/s10549-010-1191-6.
Yedjou CG, Sims JN, Miele L, et al. Health and racial disparity in breast cancer. Adv Exp Med Biol. 2019;1152:31–49. https://doi.org/10.1007/978-3-030-20301-6_3.
Cheng E, Soulos PR, Irwin ML, et al. Neighborhood and individual socioeconomic disadvantage and survival among patients with nonmetastatic common cancers. JAMA Netw Open. 2021;4(12):e2139593. https://doi.org/10.1001/jamanetworkopen.2021.39593.
Williams DR, Collins C. Racial residential segregation: a fundamental cause of racial disparities in health. Public Health Rep. 2001;116(5):404–16. https://doi.org/10.1093/phr/116.5.404.
Larrabee Sonderlund A, Charifson M, Schoenthaler A, Carson T, Williams NJ. Racialized economic segregation and health outcomes: a systematic review of studies that use the index of concentration at the extremes for race, income, and their interaction. PloS ONE. 2022;17(1):e0262962. https://doi.org/10.1371/journal.pone.0262962.
Massey DS, Stefanie B. Spheres of influence: the social ecology of racial and class inequality. New York: Russell Sage Foundation; 2014.
Booth A, Crouter A. Does it take a village? The prodigal paradigm returns: ecology comes back to sociology. Psychology Press; 2011.
Krieger N, Waterman PD, Spasojevic J, Li W, Maduro G, Van Wye G. Public health monitoring of privilege and deprivation with the index of concentration at the extremes. Am J Public Health. 2016;106(2):256–63. https://doi.org/10.2105/ajph.2015.302955.
Krieger N, Singh N, Waterman PD. Metrics for monitoring cancer inequities: residential segregation, the Index of Concentration at the Extremes (ICE), and breast cancer estrogen receptor status (USA, 1992–2012).
Wiese D, Stroup AM, Crosbie A, Lynch SM, Henry KA. The Impact of Neighborhood Economic and Racial Inequalities on the Spatial Variation of Breast Cancer Survival in New Jersey.
Shen J, Fuemmeler BF, Sheppard VB, et al. Neighborhood disadvantage and biological aging biomarkers among breast cancer patients. Sci Rep. 2022;12(1):11006. https://doi.org/10.1038/s41598-022-15260-0.
McEwen BS. Stress, adaptation, and disease. Allostasis and allostatic load. Ann N Y Acad Sci. 1998;840:33–44. https://doi.org/10.1111/j.1749-6632.1998.tb09546.x.
Seeman T, Epel E, Gruenewald T, Karlamangla A, McEwen BS. Socio-economic differentials in peripheral biology: cumulative allostatic load. Ann N Y Acad Sci. 2010;1186:223–39. https://doi.org/10.1111/j.1749-6632.2009.05341.x.
Thomas MD, Michaels EK, Reeves AN, et al. Differential associations between everyday versus institution-specific racial discrimination, self-reported health, and allostatic load among black women: implications for clinical assessment and epidemiologic studies. Ann Epidemiol. 2019;35:20-28.e3. https://doi.org/10.1016/j.annepidem.2019.05.002.
Robinette JW, Charles ST, Almeida DM, Gruenewald TL. Neighborhood features and physiological risk: An examination of allostatic load. Health Place. 2016;41:110–8. https://doi.org/10.1016/j.healthplace.2016.08.003.
Bellatorre A, Finch BK, Phuong Do D, Bird CE, Beck AN. Contextual predictors of cumulative biological risk: segregation and allostatic load. Soc Sci Q. 2011;92:1338–62. https://doi.org/10.1111/j.1540-6237.2011.00821.x.
McEwen BS, Seeman T. Protective and damaging effects of mediators of stress. Elaborating and testing the concepts of allostasis and allostatic load. Ann N Y Acad Sci. 1999;896:30–47. https://doi.org/10.1111/j.1749-6632.1999.tb08103.x.
Parente V, Hale L, Palermo T. Association between breast cancer and allostatic load by race: National Health and Nutrition Examination Survey 1999–2008. Psychooncology. 2013;22(3):621–8. https://doi.org/10.1002/pon.3044.
Akinyemiju T, Wilson LE, Deveaux A, et al. Association of Allostatic Load with all-cause and cancer mortality by race and body mass index in the REGARDS Cohort. Cancers (Basel). 2020. https://doi.org/10.3390/cancers12061695.
Zhao H, Song R, Ye Y, Chow WH, Shen J. Allostatic score and its associations with demographics, healthy behaviors, tumor characteristics, and mitochondrial DNA among breast cancer patients. Breast Cancer Res Treat. 2021;187(2):587–96. https://doi.org/10.1007/s10549-021-06102-0.
Xing CY, Doose M, Qin B, et al. Prediagnostic allostatic load as a predictor of poorly differentiated and larger sized breast cancers among black women in the women’s circle of health follow-up study. Cancer Epidemiol Biomarkers Prev. 2020;29(1):216–24. https://doi.org/10.1158/1055-9965.Epi-19-0712.
Obeng-Gyasi S, Li Y, Carson WE, et al. Association of allostatic load with overall mortality among patients with metastatic non-small cell lung cancer. JAMA Netw Open. 2022;5(7):e2221626. https://doi.org/10.1001/jamanetworkopen.2022.21626.
Obeng-Gyasi S, Graham N, Kumar S, et al. Examining allostatic load, neighborhood socioeconomic status, symptom burden and mortality in multiple myeloma patients. Blood Cancer J. 2022;12(4):53. https://doi.org/10.1038/s41408-022-00648-y.
Obeng-Gyasi S, Elsaid MI, Lu Y, et al. Association of allostatic load with all-cause mortality in patients with breast cancer. JAMA Netw Open. 2023;6(5):e2313989. https://doi.org/10.1001/jamanetworkopen.2023.13989.
Giaquinto AN, Sung H, Miller KD, et al. Breast cancer statistics, 2022. CA Cancer J Clin. 2022;72(6):524–41. https://doi.org/10.3322/caac.21754.
Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration. Int J Surg. 2014;12(12):1500–24. https://doi.org/10.1016/j.ijsu.2014.07.014.
Kittles RA, Weiss KM. Race, ancestry, and genes: implications for defining disease risk. Annu Rev Genomics Hum Genet. 2003;4:33–67. https://doi.org/10.1146/annurev.genom.4.070802.110356.
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83. https://doi.org/10.1016/0021-9681(87)90171-8.
Perou CM, Sørlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–52. https://doi.org/10.1038/35021093.
Axelsson CK, Mouridsen HT, Zedeler K. Axillary dissection of level I and II lymph nodes is important in breast cancer classification. The Danish Breast Cancer Cooperative Group (DBCG). Eur J Cancer (Oxford, England: 1990). 1992;28(8–9):1415–8. https://doi.org/10.1016/0959-8049(92)90534-9.
Seeman TE, Singer BH, Rowe JW, Horwitz RI, McEwen BS. Price of adaptation—allostatic load and its health consequences. MacArthur studies of successful aging. Arch Intern Med. 1997;157(19):2259–68.
Wiley JF, Gruenewald TL, Karlamangla AS, Seeman TE. Modeling multisystem physiological dysregulation. Psychosom Med. 2016;78(3):290–301. https://doi.org/10.1097/psy.0000000000000288.
United States Census Bureau DoC. American Community Survey, 2008–2012 American Community Survey 5-Year Estimates. 2022.
S M, J S, D VR, S R. IPUMS national historical geographic information system: Version 14.0. Minneapolis, MN: IPUMS; 2019.
United States Census Bureau DoC. Topologically integrated geographic encoding and referencing (TIGER) system. Washington: U.S. Census Bureau; 2010.
Liu Y, De A. Multiple imputation by fully conditional specification for dealing with missing data in a large epidemiologic study. Int J Stat Med Res. 2015;4(3):287–95. https://doi.org/10.6000/1929-6029.2015.04.03.7.
Rubin DB. Inference and missing data. Biometrika. 1976;63(3):581–92. https://doi.org/10.2307/2335739.
Harrell FE. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. Berlin: Springer-Verlag; 2001.
Lee EW, Wei LJ, Amato DA, Leurgans S. Cox-type regression analysis for large numbers of small groups of correlated failure time observations. In: JP Klein, PK Goel, editors. Survival analysis: state of the art. Dordrecht: Springer; 1992.
Zhang L, Gong R, Shi L, et al. Association of residential racial and economic segregation with cancer mortality in the US. JAMA Oncol. 2023;9(1):122–6. https://doi.org/10.1001/jamaoncol.2022.5382.
Connor AE, Kaur M, Dibble KE, Visvanathan K, Dean LT, Hayes JH. Racialized economic segregation and breast cancer mortality among women in Maryland.
Goel N, Westrick AC, Bailey ZD, et al. Structural racism and breast cancer-specific survival impact of economic and racial residential segregation.
Saini G, Ogden A, McCullough LE, Torres M, Rida P, Aneja R. Disadvantaged neighborhoods and racial disparity in breast cancer outcomes: the biological link. Cancer Causes Control. 2019;30(7):677–86. https://doi.org/10.1007/s10552-019-01180-4.
Miller-Kleinhenz JM, Moubadder L, Beyer KM, et al. Redlining-associated methylation in breast tumors: the impact of contemporary structural racism on the tumor epigenome. Front Oncol. 2023. https://doi.org/10.3389/fonc.2023.1154554.
Ennour-Idrissi K, Têtu B, Maunsell E, et al. Association of Telomere length with breast cancer prognostic factors. PLoS ONE. 2016;11(8):e0161903. https://doi.org/10.1371/journal.pone.0161903.
Brody GH, Yu T, Beach SR. Resilience to adversity and the early origins of disease. Dev Psychopathol. 2016;28(4pt2):1347–65. https://doi.org/10.1017/S0954579416000894.
Allen AM, Wang Y, Chae DH, et al. Racial discrimination, the superwoman schema, and allostatic load: exploring an integrative stress-coping model among African American women. Ann N Y Acad Sci. 2019;1457(1):104–27. https://doi.org/10.1111/nyas.14188.
Mitchell UA, Dellor ED, Sharif MZ, Brown LL, Torres JM, Nguyen AW. When is hope enough? Hopefulness, discrimination and racial/ethnic disparities in allostatic load. Behav Med. 2020;46(3–4):189–201. https://doi.org/10.1080/08964289.2020.1729086.
DeAngelis R, Upenieks L, Louie P. Correction to: religious involvement and allostatic resilience: Findings from a community study of Black and white Americans. J Racial Ethn Health Disparities. 2023. https://doi.org/10.1007/s40615-023-01535-3.
Acknowledgements
This project is funded by The Ohio State University Comprehensive Cancer Center Pelotonia Grant. Samilia Obeng-Gyasi is funded by the Paul Calabresi Career Development Award (K12 CA133250), Conquer Cancer Breast Cancer Research Foundation Advanced Clinical Research Award for Diversity and Inclusion in Breast Cancer Research, The Society of University Surgeons, and The American Cancer Society (RSG-22-106-01-CSCT).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ruth Carlos: ECOG-ACRIN grant funding, paid to department; NCI grant funding, paid to department; JACR, salary support as editor-in-chief, paid to department; GERRAF and Academy of Radiology and Biomedical Imaging Research, travel reimbursement for leadership roles.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Chen, J.C., Handley, D., Elsaid, M.I. et al. The Implications of Racialized Economic Segregation and Allostatic Load on Mortality in Patients with Breast Cancer. Ann Surg Oncol 31, 365–375 (2024). https://doi.org/10.1245/s10434-023-14431-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1245/s10434-023-14431-1