IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0332486.html

Designing a Territorial Composite Vulnerability Index to guide public health action in Cali, Colombia

Author

Listed:
  • Carlos E Pinzón Flórez
  • Marcela Díaz
  • Luis Guillermo Echeverry
  • Germán Escobar Morales

Abstract

Background: Social determinants of health are central to explaining health inequalities. In fragmented urban contexts such as Cali, Colombia, territorially focused public health action requires analytical tools to identify priority areas for intervention. Objective: To design and apply a Territorial Composite Vulnerability Index for the city of Santiago de Cali to support the micro-planning of public health interventions. Methods: We conducted an ecological, citywide study with a geospatial, multivariate approach. Seven indicators representing social determinants were selected: multidimensional poverty, critical overcrowding, youth unemployment, adult illiteracy, limited access to basic services, food insecurity, and population officially registered as victims of violence and displacement. Indicators were standardized and combined using principal component analysis to derive a single composite score. Spatial patterns were depicted with choropleth maps, and local indicators of spatial association were used to identify statistically significant clusters of high vulnerability. Construct validity was assessed by examining correlations between the index and health outcomes, including infant mortality, adolescent pregnancy, and suicide attempts. Results: The composite index explained 74.3% of the joint variance of the underlying indicators. High-vulnerability areas concentrated in the eastern and hillside zones of the city, with significant high–high clusters in communes 13, 14, 15, 18, and 20. The index showed positive correlations with infant mortality, adolescent pregnancy, and suicide attempts, supporting its criterion validity. Conclusions: This Territorial Composite Vulnerability Index is a valid and operational tool for guiding territorial public health management. It enables targeting of interventions to areas at greater risk and supports intersectoral and community action. Incorporating the index into local planning may help reduce social gaps in health within fragmented urban settings.

Suggested Citation

  • Carlos E Pinzón Flórez & Marcela Díaz & Luis Guillermo Echeverry & Germán Escobar Morales, 2026. "Designing a Territorial Composite Vulnerability Index to guide public health action in Cali, Colombia," PLOS ONE, Public Library of Science, vol. 21(1), pages 1-16, January.
  • Handle: RePEc:plo:pone00:0332486
    DOI: 10.1371/journal.pone.0332486
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0332486
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0332486&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0332486?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. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    2. Diez Roux, A.V., 2001. "Investigating neighborhood and area effects on health," American Journal of Public Health, American Public Health Association, vol. 91(11), pages 1783-1789.
    Full references (including those not matched with items on IDEAS)

    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. Juan Carlos Chávez & Felipe J. Fonseca & Manuel Gómez-Zaldívar, 2017. "Resoluciones de disputas comerciales y desempeño económico regional en México. (Commercial Disputes Resolution and Regional Economic Performance in Mexico)," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 79-93, May.
    2. Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang K., 2014. "TVICA—Time varying independent component analysis and its application to financial data," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 95-109.
    3. Yan Yu Chen & Chun-Cheih Chao & Fu-Chen Liu & Po-Chen Hsu & Hsueh-Fen Chen & Shih-Chi Peng & Yung-Jen Chuang & Chung-Yu Lan & Wen-Ping Hsieh & David Shan Hill Wong, 2013. "Dynamic Transcript Profiling of Candida albicans Infection in Zebrafish: A Pathogen-Host Interaction Study," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-16, September.
    4. Plat, Richard, 2009. "Stochastic portfolio specific mortality and the quantification of mortality basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 123-132, August.
    5. Kondylis, Athanassios & Whittaker, Joe, 2008. "Spectral preconditioning of Krylov spaces: Combining PLS and PC regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2588-2603, January.
    6. M. J. Aziakpono & S. Kleimeier & H. Sander, 2012. "Banking market integration in the SADC countries: evidence from interest rate analyses," Applied Economics, Taylor & Francis Journals, vol. 44(29), pages 3857-3876, October.
    7. Bianca Maria Colosimo & Luca Pagani & Marco Grasso, 2024. "Modeling spatial point processes in video-imaging via Ripley’s K-function: an application to spatter analysis in additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 429-447, January.
    8. Subramanian, S.V. & Elwert, Felix & Christakis, Nicholas, 2008. "Widowhood and mortality among the elderly: The modifying role of neighborhood concentration of widowed individuals," Social Science & Medicine, Elsevier, vol. 66(4), pages 873-884, February.
    9. Ouyang, Yaofu & Li, Peng, 2018. "On the nexus of financial development, economic growth, and energy consumption in China: New perspective from a GMM panel VAR approach," Energy Economics, Elsevier, vol. 71(C), pages 238-252.
    10. Fan, Cheng & Sun, Yongjun & Zhao, Yang & Song, Mengjie & Wang, Jiayuan, 2019. "Deep learning-based feature engineering methods for improved building energy prediction," Applied Energy, Elsevier, vol. 240(C), pages 35-45.
    11. Ionela Munteanu & Adriana Grigorescu & Elena Condrea & Elena Pelinescu, 2020. "Convergent Insights for Sustainable Development and Ethical Cohesion: An Empirical Study on Corporate Governance in Romanian Public Entities," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    12. Daniel Boss & Annick Hoffmann & Benjamin Rappaz & Christian Depeursinge & Pierre J Magistretti & Dimitri Van de Ville & Pierre Marquet, 2012. "Spatially-Resolved Eigenmode Decomposition of Red Blood Cells Membrane Fluctuations Questions the Role of ATP in Flickering," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-10, August.
    13. Doukas, Haris & Papadopoulou, Alexandra & Savvakis, Nikolaos & Tsoutsos, Theocharis & Psarras, John, 2012. "Assessing energy sustainability of rural communities using Principal Component Analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 1949-1957.
    14. Paschalis Arvanitidis & Athina Economou & Christos Kollias, 2016. "Terrorism’s effects on social capital in European countries," Public Choice, Springer, vol. 169(3), pages 231-250, December.
    15. Rizvi, Syed Kumail Abbas & Rahat, Birjees & Naqvi, Bushra & Umar, Muhammad, 2024. "Revolutionizing finance: The synergy of fintech, digital adoption, and innovation," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    16. Teerachai Amnuaylojaroen & Pavinee Chanvichit, 2024. "Historical Analysis of the Effects of Drought on Rice and Maize Yields in Southeast Asia," Resources, MDPI, vol. 13(3), pages 1-18, March.
    17. Ixandra Achitouv, 2025. "Dynamical analysis of financial stocks network: Improving forecasting using network properties," PLOS ONE, Public Library of Science, vol. 20(5), pages 1-23, May.
    18. Xiaoqian Hou & Jingyu Hou & Guangyan Huang, 2022. "Bi-dimensional principal gene feature selection from big gene expression data," PLOS ONE, Public Library of Science, vol. 17(12), pages 1-15, December.
    19. Anahita Nodehi & Mousa Golalizadeh & Mehdi Maadooliat & Claudio Agostinelli, 2025. "Torus Probabilistic Principal Component Analysis," Journal of Classification, Springer;The Classification Society, vol. 42(2), pages 435-456, July.
    20. -, 2015. "The effects of climate change on the coasts of Latin America and the Caribbean: Climate variability, dynamics and trends," Documentos de Proyectos 39866, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).

    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:pone00:0332486. 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.