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Cancer Causes & Control

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01-03-2016 | Brief report

Latent class model characterization of neighborhood socioeconomic status

Authors: Aimee Palumbo, Yvonne Michael, Terry Hyslop

Published in: Cancer Causes & Control | Issue 3/2016

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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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

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

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

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

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

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

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

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

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 76:169–198CrossRef

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 CrossRef

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 CrossRefPubMed

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 CrossRefPubMed

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

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

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 14:535–569CrossRef

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 CrossRefPubMed

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 PubMedCentralCrossRefPubMed

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 PubMedCentralCrossRefPubMed

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

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

36.

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

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

Title: Latent class model characterization of neighborhood socioeconomic status
Authors: Aimee Palumbo
Yvonne Michael
Terry Hyslop
Publication date: 01-03-2016
Publisher: Springer International Publishing
Published in: Cancer Causes & Control / Issue 3/2016
Print ISSN: 0957-5243
Electronic ISSN: 1573-7225
DOI: https://doi.org/10.1007/s10552-015-0711-4

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