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Mapping hot spots of breast cancer mortality in the United States: place matters for Blacks and Hispanics

Abstract

Purpose

The goals of this study were to identify geographic and racial/ethnic variation in breast cancer mortality, and evaluate whether observed geographic differences are explained by county-level characteristics.

Methods

We analyzed data on breast cancer deaths among women in 3,108 contiguous United States (US) counties from years 2000 through 2015. We applied novel geospatial methods and identified hot spot counties based on breast cancer mortality rates. We assessed differences in county-level characteristics between hot spot and other counties using Wilcoxon rank-sum test and Spearman correlation, and stratified all analysis by race/ethnicity.

Results

Among all women, 80 of 3,108 (2.57%) contiguous US counties were deemed hot spots for breast cancer mortality with the majority located in the southern region of the US (72.50%, p value < 0.001). In race/ethnicity-specific analyses, 119 (3.83%) hot spot counties were identified for NH-Black women, with the majority being located in southern states (98.32%, p value < 0.001). Among Hispanic women, there were 83 (2.67%) hot spot counties and the majority was located in the southwest region of the US (southern = 61.45%, western = 33.73%, p value < 0.001). We did not observe definitive geographic patterns in breast cancer mortality for NH-White women. Hot spot counties were more likely to have residents with lower education, lower household income, higher unemployment rates, higher uninsured population, and higher proportion indicating cost as a barrier to medical care.

Conclusions

We observed geographic and racial/ethnic disparities in breast cancer mortality: NH-Black and Hispanic breast cancer deaths were more concentrated in southern, lower SES counties.

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References

  1. Richardson LC et al (2016) Patterns and trends in age-specific black-white differences in breast cancer incidence and mortality: United States, 1999–2014. MMWR Morb Mortal Wkly Rep 65(40):1093–1098

    Article  PubMed  Google Scholar 

  2. Jemal A et al (2017) Annual Report to the Nation on the Status of Cancer, 1975–2014, featuring survival. J Natl Cancer Inst. https://doi.org/10.1093/jnci/djx030

    PubMed Central  Article  PubMed  Google Scholar 

  3. Carey LA et al (2006) Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 295(21):2492–2502

    Article  PubMed  CAS  Google Scholar 

  4. Barry J, Breen N (2005) The importance of place of residence in predicting late-stage diagnosis of breast or cervical cancer. Health Place 11(1):15–29

    Article  PubMed  Google Scholar 

  5. Wang F et al (2008) Late-stage breast cancer diagnosis and health care access in Illinois. Prof Geogr 60(1):54–69

    Article  PubMed  PubMed Central  Google Scholar 

  6. Akinyemiju T et al (2016) Racial disparities in individual breast cancer outcomes by hormone-receptor subtype, area-level socio-economic status and healthcare resources. Breast Cancer Res Treat 157(3):575–586

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Bradley CJ, Given CW, Roberts C (2001) Disparities in cancer diagnosis and survival. Cancer 91(1):178–188

    Article  PubMed  CAS  Google Scholar 

  8. Bradley CJ, Given CW, Roberts C (2002) Race, socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst 94(7):490–496

    Article  PubMed  Google Scholar 

  9. Meliker JR et al (2009) Breast and prostate cancer survival in Michigan: can geographic analyses assist in understanding racial disparities? Cancer 115(10):2212–2221

    Article  PubMed  PubMed Central  Google Scholar 

  10. Pruitt SL et al (2015) Residential racial segregation and mortality among black, white, and Hispanic urban breast cancer patients in Texas, 1995 to 2009. Cancer 121(11):1845–1855

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ward E et al (2004) Cancer disparities by race/ethnicity and socioeconomic status. CA Cancer J Clin 54(2):78–93

    Article  PubMed  Google Scholar 

  12. Dai D (2010) Black residential segregation, disparities in spatial access to health care facilities, and late-stage breast cancer diagnosis in metropolitan Detroit. Health Place 16(5):1038–1052

    Article  PubMed  Google Scholar 

  13. Haas JS et al (2008) Racial segregation and disparities in breast cancer care and mortality. Cancer 113(8):2166–2172

    Article  PubMed  PubMed Central  Google Scholar 

  14. Kuo TM, Mobley LR, Anselin L (2011) Geographic disparities in late-stage breast cancer diagnosis in California. Health Place 17(1):327–334

    Article  PubMed  Google Scholar 

  15. Gumpertz ML et al (2006) Geographic patterns of advanced breast cancer in Los Angeles: associations with biological and sociodemographic factors (United States). Cancer Causes Control 17(3):325–339

    Article  PubMed  Google Scholar 

  16. Baquet CR, Commiskey P (2000) Socioeconomic factors and breast carcinoma in multicultural women. Cancer 88(5 Suppl):1256–1264

    Article  PubMed  CAS  Google Scholar 

  17. Li CI, Malone KE, Daling JR (2003) Differences in breast cancer stage, treatment, and survival by race and ethnicity. Arch Intern Med 163(1):49–56

    Article  PubMed  Google Scholar 

  18. McBride R et al (2007) Within-stage racial differences in tumor size and number of positive lymph nodes in women with breast cancer. Cancer 110(6):1201–1208

    Article  PubMed  Google Scholar 

  19. Canto MT, Anderson WF, Brawley O (2001) Geographic variation in breast cancer mortality for white and black women: 1986–1995. CA Cancer J Clin 51(6):367–370

    Article  PubMed  CAS  Google Scholar 

  20. Chien LC, Yu HL, Schootman M (2013) Efficient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S. Spat Spatiotemporal Epidemiol 5:27–37

    Article  PubMed  Google Scholar 

  21. Grann V et al (2006) Regional and racial disparities in breast cancer-specific mortality. Soc Sci Med 62(2):337–347

    Article  PubMed  Google Scholar 

  22. Markossian TW, Hines RB, Bayakly R (2014) Geographic and racial disparities in breast cancer-related outcomes in Georgia. Health Serv Res 49(2):481–501

    Article  PubMed  Google Scholar 

  23. Mobley LR et al (2017) Modeling geospatial patterns of late-stage diagnosis of breast cancer in the US. Int J Environ Res Public Health 14(5):484

    Article  PubMed Central  Google Scholar 

  24. Mokdad AH et al (2017) Trends and patterns of disparities in cancer mortality among US Counties, 1980–2014. JAMA 317(4):388–406

    Article  PubMed  PubMed Central  Google Scholar 

  25. Scott L, Mobley LR, Il’yasova D (2017) Geospatial analysis of inflammatory breast cancer and associated community characteristics in the United States. Int J Environ Res Public Health 14(4):404

    Article  PubMed Central  Google Scholar 

  26. Tatalovich Z et al (2015) Geographic disparities in late stage breast cancer incidence: results from eight states in the United States. Int J Health Geogr 14:31

    Article  PubMed  PubMed Central  Google Scholar 

  27. Tian N, Wilson JG, Zhan FB (2011) Spatial association of racial/ethnic disparities between late-stage diagnosis and mortality for female breast cancer: where to intervene? Int J Health Geogr 10:24

    Article  PubMed  PubMed Central  Google Scholar 

  28. CDC (2016) Wide-ranging online data for epidemiologic research (CDC-Wonder). http://wonder.cdc.gov Accessed 15 May 2016

  29. Manson S et al (2017) Minnesota population center: national historical geographic information system: version 2.0. University of Minnesota, Minneapolis

    Google Scholar 

  30. University of Wisconsin Population Health Institute (2016) County health rankings & roadmaps

  31. Kirchhoff AC, Hart G, Campbell EG (2014) Rural and urban primary care physician professional beliefs and quality improvement behaviors. J Rural Health 30(3):235–243

    Article  PubMed  Google Scholar 

  32. Gruca TS, Pyo TH, Nelson GC (2016) Improving rural access to orthopaedic care through visiting consultant clinics. J Bone Joint Surg Am 98(9):768–774

    Article  PubMed  Google Scholar 

  33. Census (2016) Geographic terms and concepts: census divisions and census regions. https://www.census.gov/geo/reference/gtc/gtc_census_divreg.html Accessed 15 May 2016

  34. Wartenberg D (2001) Investigating disease clusters: why, when, and how? J R Stat Soc A 164(Part 1):13–22

    Article  Google Scholar 

  35. Moore JX, Donnelly JP, Griffin R, Howard G, Safford MM, Wang HE (2016) Defining sepsis mortality clusters in the United States. Crit Care Med 44(7):1380–1387

    Article  PubMed  PubMed Central  Google Scholar 

  36. Anselin L (1995) Local indicators of spatial association: LISA. Geogr Anal 27:93–115

    Article  Google Scholar 

  37. Getis A, Ord K (1992) The analysis of spatial association by use of distance statistics. Geogr Anal 24:189–206

    Article  Google Scholar 

  38. Nassel AF, Root ED, Haukoos JS, McVaney K, Colwell C, Robinson J, Eigel B, Magid DJ, Sasson C (2014) Multiple cluster analysis for the identification of high-risk census tracts for out-of-hospital cardiac arrest (OHCA) in Denver, Colorado. Resuscitation 85:1667–1673

    Article  PubMed  PubMed Central  Google Scholar 

  39. Anselin L (2004) Exploring spatial data with GeoDa: a workbook. University of Illinois, Urbana-Champaign

    Google Scholar 

  40. Li H, Calder CA, Cressie NAC (2007) Beyond Moran’s I: testing for spatial dependence based on the spatial autoregressive model. Geogr Anal 39:357–375

    Article  Google Scholar 

  41. Li H, Calder CA, Cressie NAC (2012) One-step estimation of spatial dependence parameters: properties and extensions of the APLE statistic. J Multivariate Anal 105:68–84

    Article  Google Scholar 

  42. Schootman M et al (2009) The role of poverty rate and racial distribution in the geographic clustering of breast cancer survival among older women: a geographic and multilevel analysis. Am J Epidemiol 169(5):554–561

    Article  PubMed  Google Scholar 

  43. Schootman M et al (2010) Temporal trends in geographic disparities in small-area breast cancer incidence and mortality, 1988 to 2005. Cancer Epidemiol Biomarkers Prev 19(4):1122–1131

    Article  PubMed  PubMed Central  Google Scholar 

  44. Akinyemiju T, Meng Q, Vin-Raviv N (2016) Race/ethnicity and socio-economic differences in colorectal cancer surgery outcomes: analysis of the nationwide inpatient sample. BMC Cancer 16:715

    Article  PubMed  PubMed Central  Google Scholar 

  45. Akinyemiju TF et al (2013) Individual and neighborhood socioeconomic status and healthcare resources in relation to black-white breast cancer survival disparities. J Cancer Epidemiol 2013:490472

    Article  PubMed  PubMed Central  Google Scholar 

  46. Akinyemiju TF et al (2015) Race/ethnicity and socio-economic differences in breast cancer surgery outcomes. Cancer Epidemiol 39(5):745–751

    Article  PubMed  Google Scholar 

  47. Damle RN et al (2016) Examination of racial disparities in the receipt of minimally invasive surgery among a national cohort of adult patients undergoing colorectal surgery. Dis Colon Rectum 59(11):1055–1062

    Article  PubMed  Google Scholar 

  48. Fedewa SA et al (2011) Race and ethnicity are associated with delays in breast cancer treatment (2003–2006). J Health Care Poor Underserved 22(1):128–141

    PubMed  Google Scholar 

  49. Fedewa SA et al (2010) Delays in adjuvant chemotherapy treatment among patients with breast cancer are more likely in African American and Hispanic populations: a national cohort study 2004–2006. J Clin Oncol 28(27):4135–4141

    Article  PubMed  Google Scholar 

  50. Freedman RA et al (2011) The association of race/ethnicity, insurance status, and socioeconomic factors with breast cancer care. Cancer 117(1):180–189

    Article  PubMed  Google Scholar 

  51. Hershman DL et al (2015) Household net worth, racial disparities, and hormonal therapy adherence among women with early-stage breast cancer. J Clin Oncol 33(9):1053–1059

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Schmid M et al (2016) Racial Differences in the surgical care of medicare beneficiaries with localized prostate cancer. JAMA Oncol 2(1):85–93

    Article  PubMed  PubMed Central  Google Scholar 

  53. Shavers VL, Brown ML (2002) Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst 94(5):334–357

    Article  PubMed  Google Scholar 

  54. Sheppard VB et al (2015) Disparities in breast cancer surgery delay: the lingering effect of race. Ann Surg Oncol 22(9):2902–2911

    Article  PubMed  Google Scholar 

  55. Wang EH et al (2016) Disparities in treatment of patients with high-risk prostate cancer: results from a population-based cohort. Urology 95:88–94

    Article  PubMed  Google Scholar 

  56. Torre LA, Siegel RL, Jemal A (2016) Lung cancer statistics. Adv Exp Med Biol 893:1–19

    Article  PubMed  Google Scholar 

  57. Casper ML, Wing S, Anda RF, Knowles M, Pollard RA (1995) The shifting stroke belt: changes in the geographic pattern of stroke mortality in the United States, 1962 to 1988. Stroke 26(5):755–760

    Article  PubMed  CAS  Google Scholar 

  58. Moore JX et al (2016) Defining sepsis mortality clusters in the United States. Crit Care Med 44(7):1380–1387

    Article  PubMed  PubMed Central  Google Scholar 

  59. Chang BA, Pearson WS, Owusu-Edusei K Jr (2017) Correlates of county-level nonviral sexually transmitted infection hot spots in the US: application of hot spot analysis and spatial logistic regression. Ann Epidemiol 27(4):231–237

    Article  PubMed  Google Scholar 

  60. Moore JX, Akinyemiju T, Wang HE (2017) Pollution and regional variations of lung cancer mortality in the United States. Cancer Epidemiol 49:118–127

    Article  PubMed  PubMed Central  Google Scholar 

  61. Karp DN et al (2016) Reassessing the Stroke belt: using small area spatial statistics to identify clusters of high stroke mortality in the United States. Stroke 47(7):1939–1942

    Article  PubMed  PubMed Central  Google Scholar 

  62. Aschengrau A, Paulu C, Ozonoff D (1998) Tetrachloroethylene-contaminated drinking water and the risk of breast cancer. Environ Health Perspect 106(Suppl 4):947–953

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Terry PD, Miller AB, Rohan TE (2002) Cigarette smoking and breast cancer risk: a long latency period? Int J Cancer 100(6):723–728

    Article  PubMed  CAS  Google Scholar 

  64. Petralia SA et al (1999) Risk of premenopausal breast cancer in association with occupational exposure to polycyclic aromatic hydrocarbons and benzene. Scand J Work Environ Health 25(3):215–221

    Article  PubMed  CAS  Google Scholar 

  65. Akinyemiju T et al (2016) Disparities in the prevalence of comorbidities among US adults by state Medicaid expansion status. Prev Med 88:196–202

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

Funding was provided by National Cancer Institute (Grant Nos. R25 CA47888, U54 CA118948, and T32190194), Foundation for Barnes-Jewish Hospital, and National Institute for Nursing Research ( Grant No R01-NR012726).

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Correspondence to Justin Xavier Moore.

Electronic supplementary material

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Supplementary Tables 1 and 2 (DOCX 15 KB)

Supplementary Table 3 (DOCX 176 KB)

Supplementary Table 4 (DOCX 180 KB)

Supplementary Table 5 (DOCX 175 KB)

Supplementary Table 6 (DOCX 164 KB)

Supplemental Figure 1

: Getis-Ord (Gi*) for breast cancer mortality hot spots, among all women in the contiguous United States, years 2000 – 2015. (TIF 4934 KB)

Supplemental Figure 2

: Local indicators of spatial association (LISA) for breast cancer mortality, among all women in the contiguous United States, years 2000 – 2015. (TIF 4710 KB)

Supplemental Figure 3

: Breast cancer mortality using spatial Empirical Bayes (EB) smoothed rates quintiles, among all women in the Contiguous United States, years 2000 – 2015. (TIF 5027 KB)

Supplemental Figure 4

: Getis-Ord (Gi*) for breast cancer mortality hot spots, among NH-Black women in the contiguous United States, years 2000 – 2015. (TIF 6918 KB)

Supplemental Figure 5

: Local indicators of spatial association (LISA) for breast cancer mortality, among NH-Black women in the contiguous United States, years 2000 – 2015. (TIF 6565 KB)

Supplemental Figure 6

: Breast cancer mortality using spatial Empirical Bayes (EB) smoothed rates quintiles, among NH-Black women in the Contiguous United States, years 2000 – 2015. (TIF 7139 KB)

Supplemental Figure 7

: Getis-Ord (Gi*) for breast cancer mortality hot spots, among Hispanic women in the contiguous United States, years 2000 – 2015. (TIF 5983 KB)

Supplemental Figure 8

: Local indicators of spatial association (LISA) for breast cancer mortality, among Hispanic women in the contiguous United States, years 2000 – 2015. (TIF 5618 KB)

Supplemental Figure 9

: Breast cancer mortality using spatial Empirical Bayes (EB) smoothed rates quintiles, among Hispanic women in the Contiguous United States, years 2000 – 2015. (TIF 6262 KB)

Supplemental Figure 10

: Getis-Ord (Gi*) for breast cancer mortality hot spots, among NH-White women in the contiguous United States, years 2000 – 2015. (TIF 5442 KB)

Supplemental Figure 11

: Local indicators of spatial association (LISA) for breast cancer mortality, among NH-White women in the contiguous United States, years 2000 – 2015. (TIF 5459 KB)

Supplemental Figure 12

: Breast cancer mortality using spatial Empirical Bayes (EB) smoothed rates quintiles, among NH-White women in the Contiguous United States, years 2000 – 2015. (TIF 5811 KB)

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Moore, J.X., Royston, K.J., Langston, M.E. et al. Mapping hot spots of breast cancer mortality in the United States: place matters for Blacks and Hispanics. Cancer Causes Control 29, 737–750 (2018). https://doi.org/10.1007/s10552-018-1051-y

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  • DOI: https://doi.org/10.1007/s10552-018-1051-y

Keywords

  • Breast cancer
  • Health disparities
  • Socioeconomic factors
  • Geospatial analysis