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Latent class model characterization of neighborhood socioeconomic status

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Abstract

Purpose

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

Methods

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

Results

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

Conclusions

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

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References

  1. Jemal A, Simard EP, Dorell C, Noone A-M, Markowitz LE et al (2013) Annual Report to the Nation on the Status of Cancer, 1975–2009, featuring the burden and trends in human papillomavirus (HPV)-associated cancers and HPV vaccination coverage levels. J Natl Cancer Inst 105:175–201. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3565628&tool=pmcentrez&rendertype=abstract. Accessed 1 Feb 2014

  2. Bauer KR, Brown M, Cress RD, Parise CA, Caggiano V (2007) Descriptive analysis of estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and HER2-negative invasive breast cancer, the so-called triple-negative phenotype: a population-based study from the California cancer Registry. Cancer 109:1721–1728. http://www.ncbi.nlm.nih.gov/pubmed/17387718. Accessed 8 Nov 2013

  3. Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D et al (2006) Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 295:2492–2502. http://www.ncbi.nlm.nih.gov/pubmed/16757721

  4. Hudis CA, Gianni L (2011) Triple-negative breast cancer: an unmet medical need. Oncologist 16:1–11. http://www.ncbi.nlm.nih.gov/pubmed/21278435. Accessed 28 Apr 2014

  5. Rakha EA, Reis-Filho JS, Ellis IO (2008) Basal-like breast cancer: a critical review. J Clin Oncol Off J Am Soc Clin Oncol 26:2568–2581. http://www.ncbi.nlm.nih.gov/pubmed/18487574. Accessed 8 Nov 2013

  6. Krieger N (2013) History, biology, and health inequities: emergent embodied phenotypes and the illustrative case of the breast cancer estrogen receptor. Am J Public Health 103:22–27. http://www.ncbi.nlm.nih.gov/pubmed/23153126. Accessed 8 Nov 2013

  7. Dent R, Trudeau M, Pritchard KI, Hanna WM, Kahn HK et al (2007) Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res 13:4429–4434. http://www.ncbi.nlm.nih.gov/pubmed/17671126. Accessed 30 Apr 2014

  8. Millikan RC, Newman B, Tse C-K, Moorman PG, Conway K et al (2008) Epidemiology of basal-like breast cancer. Breast Cancer Res Treat 109:123–139. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2443103&tool=pmcentrez&rendertype=abstract. Accessed 8 Nov 2013

  9. Diez Roux AV (2001) Investigating neighborhood and area effects on health. Am J Public Health 91:1783–1789. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1446876&tool=pmcentrez&rendertype=abstract

  10. Yen IH, Syme SL (1999) The social environment and health: a discussion of the epidemiologic literature. Annu Rev Public Health 20:287–308. http://www.ncbi.nlm.nih.gov/pubmed/10352860

  11. Stafford M, Marmot M (2003) Neighbourhood deprivation and health: does it affect us all equally? Int J Epidemiol 32:357–366. http://www.ije.oupjournals.org/cgi. doi:10.1093/ije/dyg084. Accessed 7 Nov 2013

  12. LeClere FB, Rogers RG, Peters KD (1997) Ethnicity and mortality in the United states: individual and community correlates. Soc Forces 76:169–198

    Article  Google Scholar 

  13. O’Neill MS, Jerrett M, Kawachi I, Levy JI, Cohen AJ et al (2003) Health, wealth, and air pollution: advancing theory and methods. Environ Health Perspect 111:1861–1870. http://www.ehponline.org/ambra-doi-resolver. doi:10.1289/ehp.6334. Accessed 17 May 2014

  14. Diez Roux AV, Mair C (2010) Neighborhoods and health. Ann N Y Acad Sci 1186:125–145. http://www.ncbi.nlm.nih.gov/pubmed/20201871. Accessed 1 May 2014

  15. Mohnen SM, Völker B, Flap H, Groenewegen PP (2012) Health-related behavior as a mechanism behind the relationship between neighborhood social capital and individual health—a multilevel analysis. BMC Public Health 12:116. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3347984&tool=pmcentrez&rendertype=abstract

  16. Emmons KM, Stoddard AM, Fletcher R, Gutheil C, Suarez EG et al (2005) Cancer prevention among working class, multiethnic adults: results of the healthy directions–health centers study. Am J Public Health 95:1200–1205. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1449340&tool=pmcentrez&rendertype=abstract. Accessed 16 May 2014

  17. Krieger N, Williams DR, Moss NE (1997) Measuring social class in US public health research: concepts, methodologies, and guidelines. Annu Rev Public Health 18:341–378. http://www.ncbi.nlm.nih.gov/pubmed/9143723

  18. Messer LC, Laraia BA, Kaufman JS, Eyster J, Holzman C et al (2006) The development of a standardized neighborhood deprivation index. J Urban Health Bull N Y Acad Med 83:1041–1062. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3261293&tool=pmcentrez&rendertype=abstract. Accessed 7 Nov 2013

  19. Sánchez BN, Budtz-Jørgensen E, Ryan LM, Hu H (2005) Structural equation models. J Am Stat Assoc 100:1443–1455. doi:10.1198/016214505000001005

    Article  Google Scholar 

  20. Morris GJ, Naidu S, Topham AK, Guiles F, Xu Y et al (2007) Differences in breast carcinoma characteristics in newly diagnosed African-American and Caucasian patients: a single-institution compilation compared with the national cancer institute’s surveillance, epidemiology, and end results database. Cancer 110:876–884. doi:10.1002/cncr.22836

    Article  PubMed  Google Scholar 

  21. Eibner C, Sturm R (2006) US-based indices of area-level deprivation: results from HealthCare for Communities. Soc Sci Med 62:348–359. doi:10.1016/j.socscimed.2005.06.017

    Article  PubMed  Google Scholar 

  22. Hayton JC, Allen DG, Scarpello V (2004) Factor retention decisions in exploratory factor analysis: a tutorial on parallel analysis. Organ Res Methods 7:191–205. http://orm.sagepub.com/cgi. doi:10.1177/1094428104263675

  23. Muthén LK, Muthén BO (2012) MPlus user’s guide, 7th edn. Muthén & Muthén, Los Angeles

    Google Scholar 

  24. Muthén BO (2001) Latent variable mixture modeling. In: Marcoulides GA, Schumacker RE (eds) new developments and techniques in structural equation modeling. Lawrence Erlbaum Associates, Inc., Mahwah, pp 1–34

    Google Scholar 

  25. Nylund KL, Asparouhov T, Muthén BO (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo Simulation study. Struct Equ Model 14:535–569

    Article  Google Scholar 

  26. Greene FL, Page DL, Fleming ID, Fritz AG, Balch CM, Haller DG, Morrow M (eds) (2002) AJCC cancer staging manual, 6th edn. Springer, New York

  27. Singletary SE, Connolly JL (2006) Breast cancer staging: working with the sixth edition of the AJCC cancer staging manual. CA Cancer J Clin 56:37–47. doi:10.3322/canjclin.56.1.37

    Article  PubMed  Google Scholar 

  28. Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R et al (2009) Circos: an information aesthetic for comparative genomics. Genome Res 19:1639–1645. doi:10.1101/gr.092759.109.19

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  29. Andaya AA, Enewold L, Horner M-J, Jatoi I, Shriver CD et al (2012) Socioeconomic disparities and breast cancer hormone receptor status. Cancer Causes Control 23:951–958. http://www.ncbi.nlm.nih.gov/pubmed/22527173. Accessed 8 Nov 2013

  30. Mair C, Diez-Roux AV, Galea S (2008) Are neighbourhood characteristics associated with depressive symptoms? A review of evidence. J Epidemiol Community Health 62:940–946, 8 p following 946. http://www.ncbi.nlm.nih.gov/pubmed/18775943. Accessed 30 Apr 2014

  31. Robert SA, Strombom I, Trentham-Dietz A, Hampton JM, McElroy JA et al (2004) Socioeconomic risk factors for breast cancer. Epidemiology 15:442–450. http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00001648-200407000-00011. Accessed 23 Apr 2014

  32. Webster TF, Hoffman K, Weinberg J, Vieira V, Aschengrau A (2008) Community- and individual-level socioeconomic status and breast cancer risk: multilevel modeling on Cape Cod, Massachusetts. Environ Health Perspect 116:1125–1129. doi:10.1289/ehp.l0818

    Article  PubMed Central  PubMed  Google Scholar 

  33. Palmer JR, Boggs DA, Wise LA, Adams-Campbell LL, Rosenberg L (2012) Individual and neighborhood socioeconomic status in relation to breast cancer incidence in African-American women. Am J Epidemiol 176:1141–1146. http://www.ncbi.nlm.nih.gov/pubmed/23171873. Accessed 8 Nov 2013

  34. McCutcheon AL (1987) Latent class analysis. Sage, Newbury Park

    Google Scholar 

  35. Gomez SL, Shariff-Marco S, DeRouen M, Keegan THM, Yen IH et al (2015) The impact of neighborhood social and built environment factors across the cancer continuum: current research, methodological considerations, and future directions. Cancer. doi:10.1002/cncr.29345

    Google Scholar 

  36. Muthén BO (1992) latent variable modeling in epidemiology. Alcohol Health Res World 16:286–292

    Google Scholar 

  37. Lynch SM, Rebbeck TR (2013) Bridging the gap between biologic, individual, and macroenvironmental factors in cancer: a multilevel approach. Cancer Epidemiol Biomark Prev 22:485–495. http://cebp.aacrjournals.org/cgi. doi:10.1158/1055-9965.EPI-13-0010

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Acknowledgments

This research was supported by Grants from Susan G. Komen for the Cure,© Investigator-Initiated Grant No. KG110710 (A.P., Y.M., T.H.) and Promise Grant No. KG091116 from Komen for the Cure (T.H).

Author information

Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, Drexel University, Nesbitt Hall, 3215 Market St, 5th Floor, Philadelphia, PA, 19104, USA

    Aimee Palumbo & Yvonne Michael

  2. Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA

    Terry Hyslop

  3. Duke Cancer Institute, Durham, NC, USA

    Terry Hyslop

Authors
  1. Aimee Palumbo
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  2. Yvonne Michael
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  3. Terry Hyslop
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Correspondence to Aimee Palumbo.

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Appendix

Appendix

See Table 3.

Table 3 Model fit parameters for latent class analysis
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Palumbo, A., Michael, Y. & Hyslop, T. Latent class model characterization of neighborhood socioeconomic status. Cancer Causes Control 27, 445–452 (2016). https://doi.org/10.1007/s10552-015-0711-4

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