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Changes in the age-at-death distribution in four low mortality countries: A nonparametric approach

Author

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  • Nadine Ouellette

    (Université de Montréal)

  • Robert Bourbeau

    (Université de Montréal)

Abstract

Since the beginning of the twentieth century, important transformations have occurred in the age-at-death distribution within human populations. We propose a flexible nonparametric smoothing approach based on P-splines to refine the monitoring of these changes. Using data from the Human Mortality Database for four low mortality countries, namely Canada (1921-2007), France (1920-2009), Japan (1947-2009), and the USA (1945-2007), we find that the general scenario of compression of mortality no longer describes appropriately some of the recent adult mortality trends recorded. Indeed, reductions in the variability of age at death above the mode have stopped since the early 1990s in Japan and since the early 2000s for Canadian, US, and French women, while their respective modal age at death continued to increase. These findings provide additional support to the shifting mortality scenario, using an alternative method free from any assumption on the shape of the age-at-death distribution.

Suggested Citation

  • Nadine Ouellette & Robert Bourbeau, 2011. "Changes in the age-at-death distribution in four low mortality countries: A nonparametric approach," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(19), pages 595-628.
  • Handle: RePEc:dem:demres:v:25:y:2011:i:19
    DOI: 10.4054/DemRes.2011.25.19
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    Cited by:

    1. Lucia Zanotto & Vladimir Canudas-Romo & Stefano Mazzuco, 2021. "A Mixture-Function Mortality Model: Illustration of the Evolution of Premature Mortality," European Journal of Population, Springer;European Association for Population Studies, vol. 37(1), pages 1-27, March.
    2. Pinheiro, Pedro Cisalpino & Queiroz, Bernardo L, 2018. "Regional Disparities in Brazilian Adult Mortality: an analysis using Modal Age at Death (M) and Compression of Mortality (IQR)," OSF Preprints t2ey3, Center for Open Science.
    3. Alyson A. van Raalte & Hal Caswell, 2012. "Perturbation analysis of indices of lifespan variability," MPIDR Working Papers WP-2012-004, Max Planck Institute for Demographic Research, Rostock, Germany.
    4. 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.
    5. Viorela Diaconu & Nadine Ouellette & Robert Bourbeau, 2020. "Modal lifespan and disparity at older ages by leading causes of death: a Canada-U.S. comparison," Journal of Population Research, Springer, vol. 37(4), pages 323-344, December.
    6. Nico Keilman, 2019. "Mortality shifts and mortality compression in period and cohort life tables," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(40), pages 1147-1196.
    7. Suryakant Yadav, 2021. "Progress of Inequality in Age at Death in India: Role of Adult Mortality," European Journal of Population, Springer;European Association for Population Studies, vol. 37(3), pages 523-550, July.
    8. Ugofilippo Basellini & Vladimir Canudas-Romo & Adam Lenart, 2019. "Location–Scale Models in Demography: A Useful Re-parameterization of Mortality Models," European Journal of Population, Springer;European Association for Population Studies, vol. 35(4), pages 645-673, October.
    9. Viorela Diaconu & Nadine Ouellette & Carlo Giovanni Camarda & Robert Bourbeau, 2016. "Insight on 'typical' longevity: An analysis of the modal lifespan by leading causes of death in Canada," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(17), pages 471-504.
    10. Bergeron-Boucher, Marie-Pier & Vázquez-Castillo, Paola & Missov, Trifon, 2022. "A modal age at death approach to forecasting mortality," SocArXiv 5zr2k, Center for Open Science.
    11. Ugofilippo Basellini & Søren Kjærgaard & Carlo Giovanni Camarda, 2020. "An age-at-death distribution approach to forecast cohort mortality," Working Papers axafx5_3agsuwaphvlfk, French Institute for Demographic Studies.
    12. Marco Bonetti & Ugofilippo Basellini, 2021. "Epilocal: A real-time tool for local epidemic monitoring," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(12), pages 307-332.
    13. Dustin Brown & Mark Hayward & Jennifer Montez & Robert Hummer & Chi-Tsun Chiu & Mira Hidajat, 2012. "The Significance of Education for Mortality Compression in the United States," Demography, Springer;Population Association of America (PAA), vol. 49(3), pages 819-840, August.
    14. Alyson Raalte & Hal Caswell, 2013. "Perturbation Analysis of Indices of Lifespan Variability," Demography, Springer;Population Association of America (PAA), vol. 50(5), pages 1615-1640, October.
    15. Wen Su & Vladimir Canudas-Romo, 2024. "Cross-sectional Average Length of Life Entropy ( $${\mathcal{H}}_{\text{CAL}}$$ H CAL ): International Comparisons and Decompositions," European Journal of Population, Springer;European Association for Population Studies, vol. 40(1), pages 1-23, December.
    16. Alyson A. van Raalte & Pekka Martikainen & Mikko Myrskylä, 2012. "Lifespan variation by occupational class: compression or stagnation over time?," MPIDR Working Papers WP-2012-010, Max Planck Institute for Demographic Research, Rostock, Germany.
    17. Trifon Missov & Adam Lenart & Laszlo Nemeth & Vladimir Canudas-Romo & James W. Vaupel, 2015. "The Gompertz force of mortality in terms of the modal age at death," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(36), pages 1031-1048.
    18. Jorge M. Uribe & Helena Chuliá & Montserrat Guillen, 2018. "Trends in the Quantiles of the Life Table Survivorship Function," European Journal of Population, Springer;European Association for Population Studies, vol. 34(5), pages 793-817, December.
    19. Isaac Sasson, 2016. "Trends in Life Expectancy and Lifespan Variation by Educational Attainment: United States, 1990–2010," Demography, Springer;Population Association of America (PAA), vol. 53(2), pages 269-293, April.
    20. Paola Vazquez-Castillo & Marie-Pier Bergeron-Boucher & Trifon Missov, 2024. "Longevity à la mode: A discretized derivative tests method for accurate estimation of the adult modal age at death," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 50(11), pages 325-346.
    21. Marie-Pier Bergeron-Boucher & Marcus Ebeling & Vladimir Canudas-Romo, 2015. "Decomposing changes in life expectancy: Compression versus shifting mortality," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(14), pages 391-424.
    22. Basellini, Ugofilippo & Kjærgaard, Søren & Camarda, Carlo Giovanni, 2020. "An age-at-death distribution approach to forecast cohort mortality," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 129-143.
    23. Carlo Giovanni Camarda, 2019. "Smooth constrained mortality forecasting," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(38), pages 1091-1130.

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    More about this item

    Keywords

    shifting mortality; modal age of death; old-age mortality compression; P-spline smoothing;
    All these keywords.

    JEL classification:

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

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