Skip to content
DraconiticResearch
Search Sources API
194,161 studies31 sourcesUpdated 54 min ago
PreprintCC BY 4.0arXiv

Characterising mortality dynamics across countries and time using a multi-stage clustering approach

Abstract

Comparative analyses of mortality dynamics across countries have long shaped our understanding of mortality inequalities and patterns of divergence and convergence over time. However, most existing studies focus on either mortality differences across countries at a single point in time or on country trajectories, without considering both factors simultaneously. In this paper, we address this gap by introducing a multi-stage clustering framework, applied to 94 countries by sex over the period 1960-2019 using data from the World Population Prospects. Specifically, we model life-table probabilities of death using a time-dependent beta latent variable model and identify a small set of ``mortality states'' that characterise the mortality pattern of each country at any given point in time. We then cluster countries based on their sequences of mortality states. Our results reveal substantial heterogeneity in the timing and pace of transitions between mortality states, including a persistent East-West divide in Europe and distinctive Latin American patterns associated with elevated young-adult male mortality. Cross-country inequality increased for both sexes until the 1990s, before plateauing and subsequently declining. Our proposed multi-stage clustering framework provides an interpretable, time-explicit description of mortality dynamics that jointly captures within-country change and between-country differences, and can be applied to other settings where trajectories of categorical or discretised profiles are of interest.

Related

  1. Borrowing Space, Clustering Temporal Dynamics: Bayesian Regime Mapping and Spatial Prediction for European PM10
    Luca Aiello, Lucia Clarotto
    arXivPreprintCC BY-NC-ND 4.0Full textStatisticsarXiv
  2. Multivariate analysis of poverty and social exclusion across EU countries in the context of Sustainable Development Goal 1
    Silvia Megyesiova, Cecilia Olexova
    PLOS OnePeer-reviewedCC BY 4.0Full textStatisticsEpidemiology & public healthPLOS
  3. Characterising canonical lifts of ordinary Calabi-Yau varieties
    Samuel A. Moore
    arXivPreprintCC BY 4.0Full textAlgebra & number theoryarXiv
  4. State-space representation of early-life child mortality dynamics: linking event history analysis and orbit-based models
    Wendy Lefotlha, David Sherwell, Maria Vivien Visaya
    arXivPreprintCC BY 4.0Full textStatisticsarXiv
  5. Minimal Superior Penalties: Characterising and Calibrating Decision-Aware Proper Scoring Rules
    Rouhollah Ahmadian
    arXivPreprintarXiv licenceFull textStatisticsarXiv
BibTeX
@misc{araujo2026characterising,
  title = {{Characterising mortality dynamics across countries and time using a multi-stage clustering approach}},
  author = {Pedro Menezes de Araújo and Ugofilippo Basellini and Thomas Brendan Murphy and Isobel Claire Gormley},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.17268},
  eprint = {2609.17268},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.17268},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Characterising mortality dynamics across countries and time using a multi-stage clustering approach
AU  - Pedro Menezes de Araújo
AU  - Ugofilippo Basellini
AU  - Thomas Brendan Murphy
AU  - Isobel Claire Gormley
PY  - 2026
DA  - 2026/09/15
PB  - arXiv
DO  - 10.48550/arxiv.2609.17268
UR  - https://arxiv.org/abs/2609.17268
AB  - Comparative analyses of mortality dynamics across countries have long shaped our understanding of mortality inequalities and patterns of divergence and convergence over time. However, most existing studies focus on either mortality differences across countries at a single point in time or on country trajectories, without considering both factors simultaneously. In this paper, we address this gap by introducing a multi-stage clustering framework, applied to 94 countries by sex over the period 1960-2019 using data from the World Population Prospects. Specifically, we model life-table probabilities of death using a time-dependent beta latent variable model and identify a small set of ``mortality states'' that characterise the mortality pattern of each country at any given point in time. We then cluster countries based on their sequences of mortality states. Our results reveal substantial heterogeneity in the timing and pace of transitions between mortality states, including a persistent East-West divide in Europe and distinctive Latin American patterns associated with elevated young-adult male mortality. Cross-country inequality increased for both sexes until the 1990s, before plateauing and subsequently declining. Our proposed multi-stage clustering framework provides an interpretable, time-explicit description of mortality dynamics that jointly captures within-country change and between-country differences, and can be applied to other settings where trajectories of categorical or discretised profiles are of interest.
ER  -