IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0208320.html
   My bibliography  Save this article

The Portuguese version of the European Deprivation Index: Development and association with all-cause mortality

Author

Listed:
  • Ana Isabel Ribeiro
  • Ludivine Launay
  • Elodie Guillaume
  • Guy Launoy
  • Henrique Barros

Abstract

Socioeconomic inequalities are major health determinants. To monitor and understand them at local level, ecological indexes of socioeconomic deprivation constitute essential tools. In this study, we describe the development of the updated version of the European Deprivation Index for Portuguese small-areas (EDI-PT), describe its spatial distribution and evaluate its association with a general health indicator–all-cause mortality in the period 2009–2012. Using data from the 2011 European Union–Statistics on Income and Living Conditions Survey (EU-SILC), we obtained an indicator of individual deprivation. After identifying variables that were common to both the EU-SILC and the census, we used the indicator of individual deprivation to test if these variables were associated with individual-level deprivation, and to compute weights. Accordingly, eight variables were included. The EDI-PT was produced for the smallest area unit possible (n = 18084 census block groups, mean/area = 584 inhabitants) and resulted from the weighted sum of the eight selected variables. It was then categorized into quintiles (Q1-least deprived to Q5-most deprived). To estimate the association with mortality we fitted Bayesian spatial models. The EDI-PT was unevenly distributed across Portugal–most deprived areas concentrated in the South and in the inner North and Centre of the country, and the least deprived in the coastal North and Centre. The EDI-PT was positively and significantly associated with overall mortality, and this relation followed a rather clear dose-response relation of increasing mortality as deprivation increases (Relative Risk Q2 = 1.012, 95% Credible Interval 0.991–1.033; Q3 = 1.026, 1.004–1.048; Q4 = 1.053, 1.029–1.077; Q5 = 1.068, 1.042–1.095). Summing up, we updated the index of socioeconomic deprivation for Portuguese small-areas, and we showed that the EDI-PT constitutes a sensitive measure to capture health inequalities, since it was consistently associated with a key measure of population health/development, all-cause mortality. We strongly believe this updated version will be widely employed by social and medical researchers and regional planners.

Suggested Citation

  • Ana Isabel Ribeiro & Ludivine Launay & Elodie Guillaume & Guy Launoy & Henrique Barros, 2018. "The Portuguese version of the European Deprivation Index: Development and association with all-cause mortality," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-13, December.
    • Handle: RePEc:plo:pone00:0208320
    DOI: 10.1371/journal.pone.0208320
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0208320
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0208320&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0208320?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. Carneiro, Anabela & Portugal, Pedro & Varejão, José, 2014. "Catastrophic job Destruction during the Portuguese Economic Crisis," Journal of Macroeconomics, Elsevier, vol. 39(PB), pages 444-457.
    2. C. B. Dean & M. D. Ugarte & A. F. Militino, 2001. "Detecting Interaction Between Random Region and Fixed Age Effects in Disease Mapping," Biometrics, The International Biometric Society, vol. 57(1), pages 197-202, March.
    3. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    4. 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.
    5. Niggebrugge, Aphrodite & Haynes, Robin & Jones, Andrew & Lovett, Andrew & Harvey, Ian, 2005. "The index of multiple deprivation 2000 access domain: a useful indicator for public health?," Social Science & Medicine, Elsevier, vol. 60(12), pages 2743-2753, June.
    6. Ana Isabel Ribeiro & Elias Teixeira Krainski & Marilia Sá Carvalho & Guy Launoy & Carole Pornet & Maria de Fátima Pina, 2018. "Does community deprivation determine longevity after the age of 75? A cross-national analysis," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(4), pages 469-479, May.
    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. Rocío Vela-Jiménez & Antonio Sianes, 2021. "Do Current Measures of Social Exclusion Depict the Multidimensional Challenges of Marginalized Urban Areas? Insights, Gaps and Future Research," IJERPH, MDPI, vol. 18(15), pages 1-16, July.
    2. Cláudia Costa & Paula Santana, 2021. "Gender and Age Differences in Socio‐economic Inequalities in Total and Avoidable Mortality in Portugal: A Trend Analysis," Fiscal Studies, John Wiley & Sons, vol. 42(1), pages 123-145, March.
    3. Claudia Costa & Angela Freitas & Ricardo Almendra & Paula Santana, 2020. "The Association between Material Deprivation and Avoidable Mortality in Lisbon, Portugal," IJERPH, MDPI, vol. 17(22), pages 1-16, November.

    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. Maria Dolores Ugarte, 2015. " Banerjee , S. Carlin , B. P. , and Gelfand , A. E. Hierarchical Modeling and Analysis for Spatial Data. Second Edition . CRC Press/Chapman & Hall . Monographs on Statistics and Applied Probability 13," Biometrics, The International Biometric Society, vol. 71(1), pages 274-277, March.
    2. Ocaña-Riola, Ricardo & Sánchez-Cantalejo, Carmen & Fernández-Ajuria, Alberto, 2006. "Rural habitat and risk of death in small areas of Southern Spain," Social Science & Medicine, Elsevier, vol. 63(5), pages 1352-1362, September.
    3. Ugarte, M.D. & Goicoa, T. & Militino, A.F., 2009. "Empirical Bayes and Fully Bayes procedures to detect high-risk areas in disease mapping," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2938-2949, June.
    4. Thomas C. McHale & Claudia M. Romero-Vivas & Claudio Fronterre & Pedro Arango-Padilla & Naomi R. Waterlow & Chad D. Nix & Andrew K. Falconar & Jorge Cano, 2019. "Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences during their 2014 to 2016 Epidemics in Barranquilla, Colombia," IJERPH, MDPI, vol. 16(10), pages 1-21, May.
    5. Naeimehossadat Asmarian & Seyyed Mohammad Taghi Ayatollahi & Zahra Sharafi & Najaf Zare, 2019. "Bayesian Spatial Joint Model for Disease Mapping of Zero-Inflated Data with R-INLA: A Simulation Study and an Application to Male Breast Cancer in Iran," IJERPH, MDPI, vol. 16(22), pages 1-13, November.
    6. Lee, Dae-Jin & Durbán, María, 2008. "Smooth-car mixed models for spatial count data," DES - Working Papers. Statistics and Econometrics. WS ws085820, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Nicoletta D’Angelo & Antonino Abbruzzo & Giada Adelfio, 2021. "Spatio-Temporal Spread Pattern of COVID-19 in Italy," Mathematics, MDPI, vol. 9(19), pages 1-14, October.
    8. Lee, Dae-Jin & Durbán, María, 2009. "Smooth-CAR mixed models for spatial count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2968-2979, June.
    9. G. Vicente & T. Goicoa & P. Fernandez‐Rasines & M. D. Ugarte, 2020. "Crime against women in India: unveiling spatial patterns and temporal trends of dowry deaths in the districts of Uttar Pradesh," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 655-679, February.
    10. Maria Dolores Ugarte, 2015. "Banerjee , S. Carlin , B. P. , and Gelfand , A. E. Hierarchical Modeling and Analysis for Spatial Data. Second Edition . CRC Press/Chapman & Hall . Monographs on Statistics and Applied Probability 135," Biometrics, The International Biometric Society, vol. 71(1), pages 274-277, March.
    11. Javier Barbero & Simone Salotti, 2021. "A general equilibrium analysis of the effects of the 2014-2020 European Cohesion policy in the Portuguese regions," JRC Working Papers on Territorial Modelling and Analysis 2021-02, Joint Research Centre.
    12. Katie Wilson & Jon Wakefield, 2022. "A probabilistic model for analyzing summary birth history data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(11), pages 291-344.
    13. Park, Seonyoung & Shin, Donggyun, 2017. "The extent and nature of downward nominal wage flexibility: An analysis of longitudinal worker/establishment data from Korea," Labour Economics, Elsevier, vol. 48(C), pages 67-86.
    14. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    15. João Ferreira do Amaral & João Carlos Lopes, 2015. "The Trade-off Unemployment Rate/External Deficit: Assessing the Economic Adjustment Program of the Troika (European Commission, ECB and IMF) for Portugal using an Input-Output Approach," Working Papers Department of Economics 2015/04, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    16. Portugal, Pedro & Rua, António, 2018. "Zooming the Ins and Outs of the U.S. Unemployment with a Wavelet Lens," IZA Discussion Papers 11559, Institute of Labor Economics (IZA).
    17. Shreosi Sanyal & Thierry Rochereau & Cara Nichole Maesano & Laure Com-Ruelle & Isabella Annesi-Maesano, 2018. "Long-Term Effect of Outdoor Air Pollution on Mortality and Morbidity: A 12-Year Follow-Up Study for Metropolitan France," IJERPH, MDPI, vol. 15(11), pages 1-8, November.
    18. Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
    19. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    20. Vanessa Santos-Sánchez & Juan Antonio Córdoba-Doña & Javier García-Pérez & Antonio Escolar-Pujolar & Lucia Pozzi & Rebeca Ramis, 2020. "Cancer Mortality and Deprivation in the Proximity of Polluting Industrial Facilities in an Industrial Region of Spain," IJERPH, MDPI, vol. 17(6), pages 1-15, March.

    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:pone00:0208320. 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.