IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v37y2017i41.html
   My bibliography  Save this article

Mortality selection among adults in Brazil: The survival advantage of Air Force officers

Author

Listed:
  • Vanessa di Lego

    (Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna))

  • Cássio M. Turra

    (Universidade Federal de Minas Gerais (UFMG))

  • Cibele Cesar

    (Universidade Federal de Minas Gerais (UFMG))

Abstract

Background: The impact of extreme conditions on survival has been the focus of mortality studies using military data. However, in countries at peace, the military live in favorable conditions, being positively selected with respect to health. In this type of context, military data may help to improve our understanding of mortality differentials, particularly in countries where defective vital systems are still cumbersome for mortality studies. Methods: We estimate death rates for Brazilian Air Force (BAF) officers through Poisson regression models, compute life expectancies, and compare them with those of average Brazilians and people in low-mortality countries. We also examine causes of death and mortality differentials through a competing risks framework and Fine and Gray regression models. Results: BAF life expectancy is higher than that of the average Brazilian and comparable to Sweden, France, and Japan in 2000. Younger pilots have a higher risk of dying on duty when compared with other officers but experience lower mortality rates from other causes at advanced ages. Conclusions: BAF officers are a population subgroup in Brazil with a life expectancy comparable to the one in advanced societies. There is no association between mortality and place of birth, which indicates that different childhood backgrounds did not affect BAF mortality differentials later in life. Contribution: This paper takes a novel approach focusing on a specific subgroup with lower mortality rates than the general population and good-quality longitudinal information available, a rarity in developing countries. We argue that this approach can be an interesting strategy to study mortality differentials in developing countries.

Suggested Citation

  • Vanessa di Lego & Cássio M. Turra & Cibele Cesar, 2017. "Mortality selection among adults in Brazil: The survival advantage of Air Force officers," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(41), pages 1339-1350.
    • Handle: RePEc:dem:demres:v:37:y:2017:i:41
    DOI: 10.4054/DemRes.2017.37.41
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol37/41/37-41.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/DemRes.2017.37.41?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. Luis Rosero-Bixby, 2008. "The exceptionally high life expectancy of Costa Rican nonagenarians," Demography, Springer;Population Association of America (PAA), vol. 45(3), pages 673-691, August.
    2. Dora Costa & Matthew Kahn, 2010. "Health, wartime stress, and unit cohesion: Evidence from Union Army veterans," Demography, Springer;Population Association of America (PAA), vol. 47(1), pages 45-66, February.
    3. Samuel Preston & Irma Elo & Ira Rosenwaike & Mark Hill, 1996. "African-american mortality at older ages: Results of a matching study," Demography, Springer;Population Association of America (PAA), vol. 33(2), pages 193-209, May.
    4. Emily Buzzell & Samuel H. Preston, 2007. "Mortality of American Troops in the Iraq War," Population and Development Review, The Population Council, Inc., vol. 33(3), pages 555-566, September.
    5. Ronald B. Geskus, 2011. "Cause-Specific Cumulative Incidence Estimation and the Fine and Gray Model Under Both Left Truncation and Right Censoring," Biometrics, The International Biometric Society, vol. 67(1), pages 39-49, March.
    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. Cássio M. Turra & Fernando Fernandes & Júlia Almeida Calazans & Marília R. Nepomuceno, 2023. "Age reporting for the oldest old in the Brazilian COVID-19 vaccination database: What can we learn from it?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(28), pages 829-848.
    2. Marília R. Nepomuceno & Cássio M. Turra, 2020. "Assessing the quality of education reporting in Brazilian censuses," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(15), pages 441-460.
    3. Marília R. Nepomuceno & Cássio M. Turra, 2020. "The Population of Centenarians in Brazil: Historical Estimates from 1900 to 2000," Population and Development Review, The Population Council, Inc., vol. 46(4), pages 813-833, December.
    4. Marilia R. Nepomuceno & Cássio M. Turra, 2019. "Assessing the quality of self-reported education in Brazil with intercensal survivorship ratios," MPIDR Working Papers WP-2019-022, Max Planck Institute for Demographic Research, Rostock, Germany.

    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. Dora L. Costa, 2015. "Health and the Economy in the United States from 1750 to the Present," Journal of Economic Literature, American Economic Association, vol. 53(3), pages 503-570, September.
    2. Bessudnov, Alexey, 2022. "Ethnic and regional inequalities in the Russian military fatalities in the 2022 war in Ukraine," SocArXiv s43yf, Center for Open Science.
    3. Hui Zheng, 2014. "Aging in the Context of Cohort Evolution and Mortality Selection," Demography, Springer;Population Association of America (PAA), vol. 51(4), pages 1295-1317, August.
    4. Ryan Masters & Robert Hummer & Daniel Powers & Audrey Beck & Shih-Fan Lin & Brian Finch, 2014. "Long-Term Trends in Adult Mortality for U.S. Blacks and Whites: An Examination of Period- and Cohort-Based Changes," Demography, Springer;Population Association of America (PAA), vol. 51(6), pages 2047-2073, December.
    5. Cook, Lisa D. & Logan, Trevon D. & Parman, John M., 2016. "The mortality consequences of distinctively black names," Explorations in Economic History, Elsevier, vol. 59(C), pages 114-125.
    6. Shiro Horiuchi & Nadine Ouellette & Siu Lan Karen Cheung & Jean-Marie Robine, 2013. "Modal age at death: lifespan indicator in the era of longevity extension," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 11(1), pages 37-69.
    7. Mayra Buvinic & Monica Das Gupta & Ursula Casabonne & Philip Verwimp, 2013. "Violent Conflict and Gender Inequality: An Overview," The World Bank Research Observer, World Bank, vol. 28(1), pages 110-138, February.
    8. Andrew Fenelon, 2013. "An examination of black/white differences in the rate of age-related mortality increase," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(17), pages 441-472.
    9. Brown, Dustin C & Lariscy, Joseph & Kalousova, Lucie, 2019. "Comparability of Mortality Estimates from Social Surveys and Vital Statistics Data in the United States," SocArXiv x9f5y_v1, Center for Open Science.
    10. Dan A. Black & Yu-Chieh Hsu & Seth G. Sanders & Lynne Steuerle Schofield & Lowell J. Taylor, 2017. "The Methuselah Effect: The Pernicious Impact of Unreported Deaths on Old-Age Mortality Estimates," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2001-2024, December.
    11. Luis Rosero-Bixby, 2023. "The vanishing advantage of longevity in Nicoya, Costa Rica: A cohort shift," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(27), pages 723-736.
    12. Dalkhat M. Ediev, 2018. "Constrained Mortality Extrapolation to Old Age: An Empirical Assessment," European Journal of Population, Springer;European Association for Population Studies, vol. 34(3), pages 441-457, August.
    13. Deresa, Negera Wakgari & Van Keilegom, Ingrid, 2020. "A multivariate normal regression model for survival data subject to different types of dependent censoring," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    14. Chau-kiu Cheung & Lih-rong Wang & Raymond Chan, 2013. "Differential Impacts of Stressors on Sense of Belonging," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 113(1), pages 277-297, August.
    15. Jackson P. Lautier & Vladimir Pozdnyakov & Jun Yan, 2022. "On the Convergence of Credit Risk in Current Consumer Automobile Loans," Papers 2211.09176, arXiv.org, revised Jan 2024.
    16. Dora L. Costa & Heather DeSomer & Eric Hanss & Christopher Roudiez & Sven E. Wilson & Noelle Yetter, 2017. "Union Army veterans, all grown up," Historical Methods: A Journal of Quantitative and Interdisciplinary History, Taylor & Francis Journals, vol. 50(2), pages 79-95, April.
    17. Ferrie, Joseph & Rolf, Karen, 2011. "Socioeconomic status in childhood and health after age 70: A new longitudinal analysis for the U.S., 1895–2005," Explorations in Economic History, Elsevier, vol. 48(4), pages 445-460.
    18. Brown, Dustin C, 2019. "Comparability of Mortality Estimates from Social Surveys and Vital Statistics Data in the United States," SocArXiv x9f5y, Center for Open Science.
    19. Dora Costa, 2012. "Scarring and Mortality Selection Among Civil War POWs: A Long-Term Mortality, Morbidity, and Socioeconomic Follow-Up," Demography, Springer;Population Association of America (PAA), vol. 49(4), pages 1185-1206, November.
    20. Patrick Heuveline, 2022. "Global and National Declines in Life Expectancy: An End‐of‐2021 Assessment," Population and Development Review, The Population Council, Inc., vol. 48(1), pages 31-50, March.

    More about this item

    Keywords

    adult mortality; early life conditions; mortality selection; Brazil; vanguard population;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

    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:dem:demres:v:37:y:2017:i:41. 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: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    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.