IDEAS home Printed from https://ideas.repec.org/a/kap/jgeosy/v23y2021i2d10.1007_s10109-020-00335-1.html
   My bibliography  Save this article

Mortality by cause of death in Colombia: a local analysis using spatial econometrics

Author

Listed:
  • Jeroen Spijker

    (Universitat Autònoma de Barcelona)

  • Joaquín Recaño

    (Universitat Autònoma de Barcelona
    Universitat Autònoma de Barcelona)

  • Sandra Martínez

    (Universidad El Bosque)

  • Alessandra Carioli

    (University of Southampton)

Abstract

Colombia is undergoing major changes in mortality patterns. National- and department-level cause-specific analyses have previously been carried out, but very little is known about municipal-level trends, despite their epidemiological interest. We first analyze standardized mortality rates for seven cause-of-death groups to obtain high and low mortality clusters based on the spatial autocorrelation indicators Global Moran’s I and Local Moran’s I. The Mann–Whitney nonparametric test is then used to ascertain statistical associations between the high and low mortality clusters and known health determinants. We subsequently apply spatial lag and Durbin (when spatial autocorrelation was present) and OLS models (when not) to explain overall spatial patterns in cause-specific mortality. Age- and sex-specific cause-of-death mortality and population data were obtained from the National Administrative Department of Statistics (DANE). Deaths were corrected for each municipality due to under-registration. Results show that spatial autocorrelation declined over time for all cause-of-death categories, except male circulatory system diseases and perinatal mortality. It is highest in external causes, especially among men, with mortality hotspots moving from the central Andean area to Orinoquia and the Amazon rainforest. Male mortality is also more spatially clustered than female mortality and especially neoplasms, and external-cause mortality is also indirectly affected by the conditions of neighboring municipalities. Municipal surface area, ethnicity and public expenditure on health and education are the most frequent contextual variables explaining territorial differences in mortality. The identification of geographical mortality clusters in Colombia will allow decision makers to prioritize those regions with higher mortality.

Suggested Citation

  • Jeroen Spijker & Joaquín Recaño & Sandra Martínez & Alessandra Carioli, 2021. "Mortality by cause of death in Colombia: a local analysis using spatial econometrics," Journal of Geographical Systems, Springer, vol. 23(2), pages 161-207, April.
  • Handle: RePEc:kap:jgeosy:v:23:y:2021:i:2:d:10.1007_s10109-020-00335-1
    DOI: 10.1007/s10109-020-00335-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10109-020-00335-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10109-020-00335-1?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    2. M L Senior & H C W L Williams & G Higgs, 1998. "Spatial and Temporal Variation of Mortality and Deprivation 2: Statistical Modelling," Environment and Planning A, , vol. 30(10), pages 1815-1834, October.
    3. Lin, Chien-Yu & Hsu, Chia-Yueh & Gunnell, David & Chen, Ying-Yeh & Chang, Shu-Sen, 2019. "Spatial patterning, correlates, and inequality in suicide across 432 neighborhoods in Taipei City, Taiwan," Social Science & Medicine, Elsevier, vol. 222(C), pages 20-34.
    4. Peter Lloyd‐Sherlock & Nadia Minicuci & John Beard & Somnath Chatterji, 2012. "Social protection and preventing illness in developing countries: Establishing the health effects of pensions and health insurance," International Social Security Review, John Wiley & Sons, vol. 65(4), pages 51-68, October.
    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. Guohuan Su & Adam Mertel & Sébastien Brosse & Justin M. Calabrese, 2023. "Species invasiveness and community invasibility of North American freshwater fish fauna revealed via trait-based analysis," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Kuschnig, Nikolas, 2021. "Bayesian Spatial Econometrics and the Need for Software," Department of Economics Working Paper Series 318, WU Vienna University of Economics and Business.
    3. Chakir, Raja & Lungarska, Anna, 2015. "Agricultural land rents in land use models: a spatial econometric analysis," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212641, European Association of Agricultural Economists.
    4. Marcos-Martinez, Raymundo & Measham, Thomas G. & Fleming-Muñoz, David A., 2019. "Economic impacts of early unconventional gas mining: Lessons from the coal seam gas industry in New South Wales, Australia," Energy Policy, Elsevier, vol. 125(C), pages 338-346.
    5. Meilan An & Jeffrey Vitale & Kwideok Han & John N. Ng’ombe & Inbae Ji, 2021. "Effects of Spatial Characteristics on the Spread of the Highly Pathogenic Avian Influenza (HPAI) in Korea," IJERPH, MDPI, vol. 18(8), pages 1-13, April.
    6. Demidova, Olga, 2021. "Methods of spatial econometrics and evaluation of government programs effectiveness," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 64, pages 107-134.
    7. Biarnès, Anne & Bailly, Jean-Stéphane & Mekki, Insaf & Ferchichi, Intissar, 2021. "Land use mosaics in Mediterranean rainfed agricultural areas as an indicator of collective crop successions: Insights from a land use time series study conducted in Cap Bon, Tunisia," Agricultural Systems, Elsevier, vol. 194(C).
    8. Iacopo Odoardi & Donatella Furia & Piera Cascioli, 2021. "Can social support compensate for missing family support? An examination of dropout rates in Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 121-139, February.
    9. Ozgun, Burcu & Broekel, Tom, 2021. "The geography of innovation and technology news - An empirical study of the German news media," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    10. Pinto, Allan & Griffin, Terry W., 2022. "Detecting bubbles via single time-series variable: applying spatial specification tests to farmland values," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322534, Agricultural and Applied Economics Association.
    11. Jan Paul Baginski & Christoph Weber, "undated". "Coherent estimations for residential photovoltaic uptake in Germany including spatial spillover effects," EWL Working Papers 1902, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    12. Gianfranco Piras & Mauricio Sarrias, 2023. "Heterogeneous spatial models in R: spatial regimes models," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-32, December.
    13. Vinícius Diniz Mayrink & Flávio Bambirra Gonçalves, 2017. "A Bayesian hidden Markov mixture model to detect overexpressed chromosome regions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 387-412, February.
    14. Kandt, Jens & Leak, Alistair, 2019. "Examining inclusive mobility through smartcard data: What shall we make of senior citizens' declining bus patronage in the West Midlands?," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    15. Paola Cardamone, 2018. "Firm innovation and spillovers in Italy: Does geographical proximity matter?," Letters in Spatial and Resource Sciences, Springer, vol. 11(1), pages 1-16, March.
    16. Mauricio R. Bellon & Alicia Mastretta-Yanes & Alejandro Ponce-Mendoza & Daniel Ortiz-Santa María & Oswaldo Oliveros-Galindo & Hugo Perales & Francisca Acevedo & José Sarukhán, 2021. "Beyond subsistence: the aggregate contribution of campesinos to the supply and conservation of native maize across Mexico," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(1), pages 39-53, February.
    17. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    18. Paul Feichtinger & Klaus Salhofer, 2016. "The Fischler Reform of the Common Agricultural Policy and Agricultural Land Prices," Land Economics, University of Wisconsin Press, vol. 92(3), pages 411-432.
    19. Wu, Wenchao, 2017. "Agglomeration Economy and Input-output Linkage: Evidence from the Entry of the Agro-food Industry in China," Japanese Journal of Agricultural Economics (formerly Japanese Journal of Rural Economics), Agricultural Economics Society of Japan (AESJ), vol. 19.
    20. Anastasiya Penska, 2015. "Determinants of Corruption in Ukrainian Regions: Spatial Analysis," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 42.

    More about this item

    Keywords

    Spatial cluster analysis; Spatial Durbin model; Mortality; Causes of death; Epidemiology; Colombia;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • I10 - Health, Education, and Welfare - - Health - - - General
    • N36 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Latin America; Caribbean

    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:kap:jgeosy:v:23:y:2021:i:2:d:10.1007_s10109-020-00335-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.