IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0022693.html
   My bibliography  Save this article

Identifying Unique Neighborhood Characteristics to Guide Health Planning for Stroke and Heart Attack: Fuzzy Cluster and Discriminant Analyses Approaches

Author

Listed:
  • Ashley Pedigo
  • William Seaver
  • Agricola Odoi

Abstract

Background: Socioeconomic, demographic, and geographic factors are known determinants of stroke and myocardial infarction (MI) risk. Clustering of these factors in neighborhoods needs to be taken into consideration during planning, prioritization and implementation of health programs intended to reduce disparities. Given the complex and multidimensional nature of these factors, multivariate methods are needed to identify neighborhood clusters of these determinants so as to better understand the unique neighborhood profiles. This information is critical for evidence-based health planning and service provision. Therefore, this study used a robust multivariate approach to classify neighborhoods and identify their socio-demographic characteristics so as to provide information for evidence-based neighborhood health planning for stroke and MI. Methods and Findings: The study was performed in East Tennessee Appalachia, an area with one of the highest stroke and MI risks in USA. Robust principal component analysis was performed on neighborhood (census tract) socioeconomic and demographic characteristics, obtained from the US Census, to reduce the dimensionality and influence of outliers in the data. Fuzzy cluster analysis was used to classify neighborhoods into Peer Neighborhoods (PNs) based on their socioeconomic and demographic characteristics. Nearest neighbor discriminant analysis and decision trees were used to validate PNs and determine the characteristics important for discrimination. Stroke and MI mortality risks were compared across PNs. Four distinct PNs were identified and their unique characteristics and potential health needs described. The highest risk of stroke and MI mortality tended to occur in less affluent PNs located in urban areas, while the suburban most affluent PNs had the lowest risk. Conclusions: Implementation of this multivariate strategy provides health planners useful information to better understand and effectively plan for the unique neighborhood health needs and is important in guiding resource allocation, service provision, and policy decisions to address neighborhood health disparities and improve population health.

Suggested Citation

  • Ashley Pedigo & William Seaver & Agricola Odoi, 2011. "Identifying Unique Neighborhood Characteristics to Guide Health Planning for Stroke and Heart Attack: Fuzzy Cluster and Discriminant Analyses Approaches," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-11, July.
    • Handle: RePEc:plo:pone00:0022693
    DOI: 10.1371/journal.pone.0022693
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0022693
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0022693&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0022693?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. Bill Seaver & Konstantinos Triantis & Barbara Hoopes, 2004. "Efficiency Performance and Dominance in Influential Subsets: An Evaluation using Fuzzy Clustering and Pair-wise Dominance," Journal of Productivity Analysis, Springer, vol. 21(2), pages 201-220, March.
    3. Diez-Roux, A.V., 1998. "Bringing context back into epidemiology: Variables and fallacies in multilevel analysis," American Journal of Public Health, American Public Health Association, vol. 88(2), pages 216-222.
    4. Picot, Garnett & Sceviour, Roger & Frenette, Marc, 2004. "How Long Do People Live in Low-income Neighbourhoods? Evidence for Toronto, Montreal and Vancouver," Analytical Studies Branch Research Paper Series 2004216e, Statistics Canada, Analytical Studies Branch.
    5. Hart, C.L. & Hole, D.J. & Smith, G.D., 2000. "The contribution of risk factors to stroke differentials, by socioeconomic position in adulthood: The Renfrew/Paisley study," American Journal of Public Health, American Public Health Association, vol. 90(11), pages 1788-1791.
    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. Amanda T. Charette & Mary B. Collins & Jaime E. Mirowsky, 2021. "Assessing residential socioeconomic factors associated with pollutant releases using EPA’s Toxic Release Inventory," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 11(2), pages 247-257, June.

    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. 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.
    2. Bolte, Gabriele, 2018. "Epidemiologische Methoden und Erkenntnisse als eine Grundlage für Stadtplanung und gesundheitsfördernde Stadtentwicklung," Forschungsberichte der ARL: Aufsätze, in: Baumgart, Sabine & Köckler, Heike & Ritzinger, Anne & Rüdiger, Andrea (ed.), Planung für gesundheitsfördernde Städte, volume 8, pages 118-134, ARL – Akademie für Raumentwicklung in der Leibniz-Gemeinschaft.
    3. Spielman, Seth E. & Yoo, Eun-hye, 2009. "The spatial dimensions of neighborhood effects," Social Science & Medicine, Elsevier, vol. 68(6), pages 1098-1105, March.
    4. 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.
    5. Dusan Paredes Araya & Tomothy M Komarek, 2013. "Spatial Income Inequality in Chile and the Rol of Spatial Labor Sorting," Documentos de Trabajo en Economia y Ciencia Regional 46, Universidad Catolica del Norte, Chile, Department of Economics, revised Apr 2013.
    6. Seth E Spielman & Eun-Hye Yoo & Crystal Linkletter, 2013. "Neighborhood Contexts, Health, and Behavior: Understanding the Role of Scale and Residential Sorting," Environment and Planning B, , vol. 40(3), pages 489-506, June.
    7. Zanetta Gant & Larry Gant & Ruiguang Song & Leigh Willis & Anna Satcher Johnson, 2014. "A Census Tract–Level Examination of Social Determinants of Health among Black/African American Men with Diagnosed HIV Infection, 2005–2009—17 US Areas," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-7, September.
    8. Miller, Charlotte E. & Vasan, Ramachandran S., 2021. "The southern rural health and mortality penalty: A review of regional health inequities in the United States," Social Science & Medicine, Elsevier, vol. 268(C).
    9. 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.
    10. Myers, Douglas J. & Kriebel, David & Karasek, Robert & Punnett, Laura & Wegman, David H., 2007. "The social distribution of risk at work: Acute injuries and physical assaults among healthcare workers working in a long-term care facility," Social Science & Medicine, Elsevier, vol. 64(4), pages 794-806, February.
    11. infocede, 2001. "Desnutrición infantil en Colombia: inequidades y determinantes," Documentos CEDE 20100, Universidad de los Andes, Facultad de Economía, CEDE.
    12. De Clercq, B. & Vyncke, V. & Hublet, A. & Elgar, F.J. & Ravens-Sieberer, U. & Currie, C. & Hooghe, M. & Ieven, A. & Maes, L., 2012. "Social capital and social inequality in adolescents’ health in 601 Flemish communities: A multilevel analysis," Social Science & Medicine, Elsevier, vol. 74(2), pages 202-210.
    13. 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.
    14. Kuang-Tsu Yang & Chun-Hao Yin & Yao-Min Hung & Shih-Ju Huang & Ching-Chih Lee & Tsu-Jen Kuo, 2020. "Continuity of Care Is Associated with Medical Costs and Inpatient Days in Children with Cerebral Palsy," IJERPH, MDPI, vol. 17(8), pages 1-15, April.
    15. Steffen Andreas Schüle & Gabriele Bolte, 2015. "Interactive and Independent Associations between the Socioeconomic and Objective Built Environment on the Neighbourhood Level and Individual Health: A Systematic Review of Multilevel Studies," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-31, April.
    16. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    17. Win Wah & Arul Earnest & Charumathi Sabanayagam & Ching-Yu Cheng & Marcus Eng Hock Ong & Tien Y Wong & Ecosse L Lamoureux, 2015. "Composite Measures of Individual and Area-Level Socio-Economic Status Are Associated with Visual Impairment in Singapore," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-12, November.
    18. Joanne Nicole Luke & Alister Thorpe & Carlina Black & Lisa Thorpe & David Thomas & Sandra Eades & Kevin Rowley, 2021. "Collaborative Social-Epidemiology: A Co-analysis of the Cultural and Structural Determinants of Health for Aboriginal Youth in Victorian Schools," IJERPH, MDPI, vol. 18(16), pages 1-22, August.
    19. repec:asg:wpaper:1020 is not listed on IDEAS
    20. 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.
    21. 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.

    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:pone00:0022693. 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.