IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0106322.html
   My bibliography  Save this article

Individual- and Neighborhood-Level Predictors of Mortality in Florida Colorectal Cancer Patients

Author

Listed:
  • Stacey L Tannenbaum
  • Monique Hernandez
  • D Dandan Zheng
  • Daniel A Sussman
  • David J Lee

Abstract

Purpose: We examined individual-level and neighborhood-level predictors of mortality in CRC patients diagnosed in Florida to identify high-risk groups for targeted interventions. Methods: Demographic and clinical data from the Florida Cancer Data System registry (2007–2011) were linked with Agency for Health Care Administration and US Census data (n = 47,872). Cox hazard regression models were fitted with candidate predictors of CRC survival and stratified by age group (18–49, 50–64, 65+). Results: Stratified by age group, higher mortality risk per comorbidity was found among youngest (21%), followed by middle (19%), and then oldest (14%) age groups. The two younger age groups had higher mortality risk with proximal compared to those with distal cancer. Compared with private insurance, those in the middle age group were at higher death risk if not insured (HR = 1.35), or received healthcare through Medicare (HR = 1.44), Medicaid (HR = 1.53), or the Veteran’s Administration (HR = 1.26). Only Medicaid in the youngest (52% higher risk) and those not insured in the oldest group (24% lower risk) were significantly different from their privately insured counterparts. Among 18–49 and 50–64 age groups there was a higher mortality risk among the lowest SES (1.17- and 1.23-fold higher in the middle age and 1.12- and 1.17-fold higher in the older age group, respectively) compared to highest SES. Married patients were significantly better off than divorced/separated (HR = 1.22), single (HR = 1.29), or widowed (HR = 1.19) patients. Conclusion: Factors associated with increased risk for mortality among individuals with CRC included being older, uninsured, unmarried, more comorbidities, living in lower SES neighborhoods, and diagnosed at later disease stage. Higher risk among younger patients was attributed to proximal cancer site, Medicaid, and distant disease; however, lower SES and being unmarried were not risk factors in this age group. Targeted interventions to improve survivorship and greater social support while considering age classification may assist these high-risk groups.

Suggested Citation

  • Stacey L Tannenbaum & Monique Hernandez & D Dandan Zheng & Daniel A Sussman & David J Lee, 2014. "Individual- and Neighborhood-Level Predictors of Mortality in Florida Colorectal Cancer Patients," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
  • Handle: RePEc:plo:pone00:0106322
    DOI: 10.1371/journal.pone.0106322
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0106322
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0106322&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0106322?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Krieger, N., 1992. "Overcoming the absence of socioeconomic data in medical records: Validation and application of a census-based methodology," American Journal of Public Health, American Public Health Association, vol. 82(5), pages 703-710.
    2. Roetzheim, R.G. & Pal, N. & Gonzalez, E.C. & Ferrante, J.M. & Van Durme, D.J. & Krischer, J.P., 2000. "Effects of health insurance and race on colorectal cancer treatments and outcomes," American Journal of Public Health, American Public Health Association, vol. 90(11), pages 1746-1754.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shannon M Lynch & Elizabeth Handorf & Kristen A Sorice & Elizabeth Blackman & Lisa Bealin & Veda N Giri & Elias Obeid & Camille Ragin & Mary Daly, 2020. "The effect of neighborhood social environment on prostate cancer development in black and white men at high risk for prostate cancer," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-18, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nan Zhang & Heng Xu, 2024. "Fairness of Ratemaking for Catastrophe Insurance: Lessons from Machine Learning," Information Systems Research, INFORMS, vol. 35(2), pages 469-488, June.
    2. Cots, Francesc & Mercade, Lluc & Castells, Xavier & Salvador, Xavier, 2004. "Relationship between hospital structural level and length of stay outliers: Implications for hospital payment systems," Health Policy, Elsevier, vol. 68(2), pages 159-168, May.
    3. Martin Gaechter & Peter Schwazer & Engelbert Theurl, 2012. "Stronger Sex but Earlier Death: A Multi-level Socioeconomic Analysis of Gender Differences in Mortality in Austria," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 1, pages 1-23, March.
    4. Michelle Sholzberg & Tara Gomes & David N Juurlink & Zhan Yao & Muhammad M Mamdani & Andreas Laupacis, 2016. "The Influence of Socioeconomic Status on Selection of Anticoagulation for Atrial Fibrillation," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-12, February.
    5. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    6. Clarke, Christina A. & Miller, Tim & Chang, Ellen T. & Yin, Daixin & Cockburn, Myles & Gomez, Scarlett L., 2010. "Racial and social class gradients in life expectancy in contemporary California," Social Science & Medicine, Elsevier, vol. 70(9), pages 1373-1380, May.
    7. Floriane Calocer & Olivier Dejardin & Karine Droulon & Guy Launoy & Gilles Defer, 2018. "Socio-economic status influences access to second-line disease modifying treatment in Relapsing Remitting Multiple Sclerosis patients," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-12, February.
    8. Allison C. Morgan & Nicholas LaBerge & Daniel B. Larremore & Mirta Galesic & Jennie E. Brand & Aaron Clauset, 2022. "Socioeconomic roots of academic faculty," Nature Human Behaviour, Nature, vol. 6(12), pages 1625-1633, December.
    9. Keyes, Katherine M. & March, Dana & Link, Bruce G. & Chilcoat, Howard D. & Susser, Ezra, 2013. "Do socio-economic gradients in smoking emerge differently across time by gender? Implications for the tobacco epidemic from a pregnancy cohort in California, USA," Social Science & Medicine, Elsevier, vol. 76(C), pages 101-106.
    10. Jinani Jayasekera & Eberechukwu Onukwugha & Christopher Cadham & Donna Harrington & Sarah Tom & Francoise Pradel & Michael Naslund, 2019. "An ecological approach to monitor geographic disparities in cancer outcomes," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-14, June.
    11. Justin Stoler & John R Weeks & Richard Appiah Otoo, 2013. "Drinking Water in Transition: A Multilevel Cross-sectional Analysis of Sachet Water Consumption in Accra," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
    12. Michael Adjemian & Jeffrey Williams, 2009. "Using census aggregates to proxy for household characteristics: an application to vehicle ownership," Transportation, Springer, vol. 36(2), pages 223-241, March.
    13. Philibert, M.D. & Pampalon, R. & Hamel, D. & Thouez, J.-P. & Loiselle, C.G., 2007. "KW - Quebec: A local-scale evaluation system," Social Science & Medicine, Elsevier, vol. 64(8), pages 1651-1664, April.
    14. Masayoshi Oka, 2022. "Census-Tract-Level Median Household Income and Median Family Income Estimates: A Unidimensional Measure of Neighborhood Socioeconomic Status?," IJERPH, MDPI, vol. 20(1), pages 1-23, December.
    15. Grann, Victor & Troxel, Andrea B. & Zojwalla, Naseem & Hershman, Dawn & Glied, Sherry A. & Jacobson, Judith S., 2006. "Regional and racial disparities in breast cancer-specific mortality," Social Science & Medicine, Elsevier, vol. 62(2), pages 337-347, January.
    16. Stafford, Mai & Duke-Williams, Oliver & Shelton, Nicola, 2008. "Small area inequalities in health: Are we underestimating them?," Social Science & Medicine, Elsevier, vol. 67(6), pages 891-899, September.
    17. M. Manos & Chanda Ho & Rosemary Murphy & Valentina Shvachko, 2013. "Physical, Social, and Psychological Consequences of Treatment for Hepatitis C," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 6(1), pages 23-34, March.
    18. Andrea S Gershon & Deva Thiruchelvam & Shawn Aaron & Matthew Stanbrook & Nicholas Vozoris & Wan C Tan & Eunice Cho & Teresa To, 2019. "Socioeconomic status (SES) and 30-day hospital readmissions for chronic obstructive pulmonary (COPD) disease: A population-based cohort study," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-16, May.
    19. Rebecca M. Myerson & Reginald D. Tucker‐Seeley & Dana P. Goldman & Darius N. Lakdawalla, 2020. "Does Medicare Coverage Improve Cancer Detection and Mortality Outcomes?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(3), pages 577-604, June.
    20. Neugebauer Romain & Chandra Malini & Paredes Antonio & J. Graham David & McCloskey Carolyn & S. Go Alan, 2013. "A Marginal Structural Modeling Approach with Super Learning for a Study on Oral Bisphosphonate Therapy and Atrial Fibrillation," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 21-50, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0106322. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.