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Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death

Author

Listed:
  • Miguel A. Martinez-Beneito

    (Departament d’Estadística e Investigaciò Opertiva, Universitat de València, 46100 Burjassot, Spain
    CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain)

  • Carlos Vergara-Hernández

    (FISABIO Foundation, 46020 Valencia, Spain)

  • Paloma Botella-Rocamora

    (Dirección General de Salut Pública i Adiccions, Conselleria de Sanitat Universal y Salut Pública, 46020 Valencia, Spain)

  • Francisca Corpas-Burgos

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    FISABIO Foundation, 46020 Valencia, Spain)

  • Jordi Pérez-Panadés

    (Dirección General de Salut Pública i Adiccions, Conselleria de Sanitat Universal y Salut Pública, 46020 Valencia, Spain)

  • Óscar Zurriaga

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    FISABIO Foundation, 46020 Valencia, Spain
    Dirección General de Salut Pública i Adiccions, Conselleria de Sanitat Universal y Salut Pública, 46020 Valencia, Spain
    Departament de Medicina Preventiva, Salut Pública, Ciències de l’Alimentación, Toxicología i Medicina Legal, Universitat de València, 46010 Valencia, Spain)

  • Elena Aldasoro

    (Dirección de Salud Pública y Adicciones, 48013 Bilbao, Spain)

  • Carme Borrell

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    Agència de Salut Pública de Barcelona, 08023 Barcelona, Spain
    Institut d’Investigació Biomèdica (IIB Sant Pau), 08025 Barcelona, Spain)

  • Elena Cabeza

    (Institut d’investigació sanitària de les Illes Balears, 07120 Palma de Mallorca, Spain)

  • Lluís Cirera

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    Department of Epidemiology, Regional Health Council-IMIB-Arrixaca, 30008 Murcia, Spain)

  • Josu Delfrade Osinaga

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    Instituto de Salud Pública y Laboral de Navarra, 31003 Pamplona, Spain)

  • Ana Fernández-Somoano

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    IUOPA-Medicine Department, Universidad de Oviedo, 33006 Oviedo, Spain
    Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), 33001 Oviedo, Spain)

  • Ana Gandarillas

    (Consejeria de Sanidad, 28035 Madrid, Spain)

  • Pedro L. Lorenzo Ruano

    (Servicio Canario de Salud, 35018 Las Palmas de Gran Canaria, Spain)

  • Marc Marí-Dell’Olmo

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    Agència de Salut Pública de Barcelona, 08023 Barcelona, Spain
    Institut d’Investigació Biomèdica (IIB Sant Pau), 08025 Barcelona, Spain)

  • Andreu Nolasco

    (Universidad de Alicante, 03690 San Vicente del Raspeig, Spain)

  • M. Dolores Prieto-Salceda

    (Fundación Marqués de Valdecilla-Observatorio de Salud Pública de Cantabria, 39008 Santander, Spain)

  • Rebeca Ramis

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    Instituto de Salud Carlos III, 28029 Madrid, Spain)

  • Maica Rodríguez-Sanz

    (CIBER de Epidemiología y Salud Pública, 28029 Madrid, Spain
    Agència de Salut Pública de Barcelona, 08023 Barcelona, Spain
    Institut d’Investigació Biomèdica (IIB Sant Pau), 08025 Barcelona, Spain)

  • Pablo Sánchez-Villegas

    (Escuela Andaluza de Salud Pública, 18011 Granada, Spain)

  • the MEDEA3 Project Group

    (Membership of the MEDEA3 Project Group is provided in the Acknowledgments.)

Abstract

The geographical distribution of mortality has frequently been studied. Nevertheless, those studies often consider isolated causes of death. In this work, we aim to study the geographical distribution of mortality in urban areas, in particular, in 26 Spanish cities. We perform an overall study of 16 causes of death, considering that their geographical patterns could be dependent and estimating the dependence between the causes of death. We study the deaths in these 26 cities during the period 1996–2015 at the census tract level. A multivariate disease mapping model is used in order to solve the potential small area estimation problems that these data could show. We find that most of the geographical patterns found show positive correlations. This suggests the existence of a transversal geographical pattern, common to most causes of deaths, which determines those patterns to a higher/lower extent depending on each disease. The causes of death that exhibit that underlying pattern in a more prominent manner are chronic obstructive pulmonary disease (COPD), lung cancer, and cirrhosis for men and cardiovascular diseases and dementias for women. Such findings are quite consistent for most of the cities in the study. The high positive correlation found between geographical patterns reflects the existence of both high and low-risk areas in urban settings, in general terms for nearly all the causes of death. Moreover, the high-risk areas found often coincide with neighborhoods known for their high deprivation. Our results suggest that dependence among causes of death is a key aspect to be taken into account when mapping mortality, at least in urban contexts.

Suggested Citation

  • Miguel A. Martinez-Beneito & Carlos Vergara-Hernández & Paloma Botella-Rocamora & Francisca Corpas-Burgos & Jordi Pérez-Panadés & Óscar Zurriaga & Elena Aldasoro & Carme Borrell & Elena Cabeza & Lluís, 2021. "Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death," IJERPH, MDPI, vol. 18(11), pages 1-15, May.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:11:p:5664-:d:562106
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    References listed on IDEAS

    as
    1. Darrell J. Gaskin & Eric T. Roberts & Kitty S. Chan & Rachael McCleary & Christine Buttorff & Benjo A. Delarmente, 2019. "No Man is an Island: The Impact of Neighborhood Disadvantage on Mortality," IJERPH, MDPI, vol. 16(7), pages 1-18, April.
    2. 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.
    3. F. Corpas-Burgos & P. Botella-Rocamora & M. A. Martinez-Beneito, 2019. "On the convenience of heteroscedasticity in highly multivariate disease mapping," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1229-1250, December.
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