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Thesis

The causes and the consequences of growing life expectancy shortfalls

Abstract:
Life expectancy stagnation—the lack of improvement in life expectancy over time—and life expectancy divergence—the widening of an existing life expectancy gap—are both warning signs that population health is not developing as well as it could. Most demographic research has used a stagnation perspective to understand recent life expectancy trends in high-income countries. This dissertation argues that a within-country approach risks overlooking critical mortality dynamics that are unique to the population experiencing life expectancy stagnation. It proposes to complement within-country analysis of life expectancy stagnation with between-country analysis of life expectancy divergence. In three empirical studies, this dissertation identifies the causes of recent life expectancy trends in the United States of America (USA) and the United Kingdom (UK) relative to other high-income countries before, during, and after the COVID-19 pandemic, and quantifies the consequences of this life expectancy divergence for population composition. Using demographic decomposition, Chapter 2 identifies the age groups and causes of death that contributed to the decreasing life expectancy advantage or increasing life expectancy disadvantage of England and Wales relative to other European countries in the period 2010–2019. Chapter 3 identifies the age groups and causes of death that contributed to life expectancy divergence between the USA and the UK and better-performing peer countries during the COVID-19 pandemic. Chapter 4 considers the consequences of the growing life expectancy shortfall of the USA. Using counterfactual methods, it estimates the number of children that were never born because the USA consistently experienced higher mortality than its peers. Across the three chapters, the proposed divergence approach points to critical population dynamics in the USA and the UK that had previously gone unnoticed with a stagnation approach. Thus, this dissertation argues that the joint application of the two approaches should become more common practice in demographic analysis.

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Institution:
University of Oxford
Division:
SSD
Department:
Sociology
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MSD
Department:
Nuffield Department of Population Health
Role:
Contributor
ORCID:
0000-0001-7622-9088
Role:
Contributor
Role:
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Funder identifier:
https://ror.org/012mzw131
Funding agency for:
Polizzi, AE
Dowd, J
Tilstra, A
Zhang, L
Aburto, J
Grant:
RC-2018-003
More from this funder
Funder identifier:
https://ror.org/0472cxd90
Funding agency for:
Polizzi, AE
Dowd, J
Tilstra, A
Grant:
ERC-2021-CoG-101002587
More from this funder
Funder identifier:
https://ror.org/001aqnf71
Funding agency for:
Tilstra, A
Grant:
EP/X027678/1
More from this funder
Funder identifier:
https://ror.org/05mmh0f86
Funding agency for:
Timonin, S
Grant:
DP210100401
More from this funder
Funding agency for:
Gupta, A
Aburto, J
Grant:
101027598
896821


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


Language:
English
Keywords:
Subjects:
Deposit date:
2026-05-07
ARK identifier:


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