Latent class model characterization of neighborhood socioeconomic status.

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Palumbo, A; Michael, Y; Hyslop, T

Published Date

  • March 2016

Published In

Volume / Issue

  • 27 / 3

Start / End Page

  • 445 - 452

PubMed ID

  • 26797452

Pubmed Central ID

  • PMC4763341

Electronic International Standard Serial Number (EISSN)

  • 1573-7225

Digital Object Identifier (DOI)

  • 10.1007/s10552-015-0711-4


  • eng

Conference Location

  • Netherlands