ArticleCancer causes & control : CCC2016
Latent class model characterization of neighborhood socioeconomic status.
Article in Cancer causes & control : CCC, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Comparing Neighborhood Indices of Socioeconomic Status, Segregation, and Healthcare Access for Predicting Late-Stage Breast Cancer.Journal of urban health : bulletin of the New York Academy of Medicine · 2026Article
- Applying a Novel Measure of Community-Level Healthcare Access to Assess Breast Cancer Care Timeliness.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Article
- Genomic Analysis Reveals Racial and Age-Related Differences in the Somatic Landscape of Breast Cancer and the Association with Socioeconomic Factors.Cancer research · 2025Article
- Spatial Clustering for Carolina Breast Cancer Study.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2025Article
- Disparities in OncotypeDx Testing and Subsequent Chemotherapy Receipt by Geography and Socioeconomic Status.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024Article
- A tale of many neighborhoods: Latent profile analysis to derive a national neighborhood typology for the US.Health & place · 2024Article
- Racial disparities in time to hematopoietic cell transplant among patients with hematologic malignancies at a large urban academic center.Bone marrow transplantation · 2022Article
- Socioeconomic status, access to care, risk factor patterns, and stage at diagnosis for head and neck cancer among black and white patients.Head & neck · 2022Article
- Socioeconomic Classes among Oldest-Old Women in South Korea: A Latent Class Analysis.International journal of environmental research and public health · 2021Article
- Neighborhood archetypes and breast cancer survival in California.Annals of epidemiology · 2021Article
- Spatiotemporal strategies to identify aggressive biology in precancerous breast biopsies.WIREs mechanisms of disease · 2021Review
- Breast cancer treatment delays by socioeconomic and health care access latent classes in Black and White women.Cancer · 2020Article
- Using Latent Class Modeling to Jointly Characterize Economic Stress and Multipollutant Exposure.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Integrating biology and access to care in addressing breast cancer disparities: 25 years' research experience in the Carolina Breast Cancer Study.Current breast cancer reports · 2020Article
- Associations between the Neighborhood Social Environment and Obesity Among Adolescents: Do Physical Activity, Screen Time, and Sleep Play a Role?Health & place · 2020Article
- Integrating access to care and tumor patterns by race and age in the Carolina Breast Cancer Study, 2008-2013.Cancer causes & control : CCC · 2020Article
- Neighborhood affluence is not associated with positive and negative valence processing in adults with mood and anxiety disorders: A Bayesian inference approach.NeuroImage. Clinical · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
purposeNeighborhood-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.
methodsBreast 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.
resultsComplete 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.
conclusionsLatent 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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