Lifespan variation among people with a given disease or condition.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 07 03 2023
accepted: 18 08 2023
medline: 7 9 2023
pubmed: 1 9 2023
entrez: 1 9 2023
Statut: epublish

Résumé

In addition to fundamental mortality metrics such as mortality rates and mortality rate ratios, life expectancy is also commonly used to investigate excess mortality among a group of individuals diagnosed with specific diseases or conditions. However, as an average measure, life expectancy ignores the heterogeneity in lifespan. Interestingly, the variation in lifespan-a measure commonly used in the field of demography-has not been estimated for people with a specific condition. Based on recent advances in methodology in research within epidemiology and demography, we discuss two metrics, namely, the average life disparity and average lifetable entropy after diagnosis, which estimate the variation in lifespan for time-varying conditions in both absolute and relative aspects. These metrics are further decomposed into early and late components, separated by their threshold ages. We use mortality data for women with mental disorders from Danish registers to design a population-based study and measure such metrics. Compared with women from the general population, women with a mental disorder had a shorter average remaining life expectancy after diagnosis (37.6 years vs. 44.9 years). In addition, women with mental disorders also experienced a larger average lifespan variation, illustrated by larger average life disparity (9.5 years vs 9.1 years) and larger average lifetable entropy (0.33 vs 0.27). More specifically, we found that women with a mental disorder had a larger early average life disparity but a smaller late average life disparity. Unlike the average life disparity, both early and late average lifetable entropy were higher for women with mental disorders compared to the general population. In conclusion, the metric proposed in our study complements the current research focusing merely on life expectancy and further provides a new perspective into the assessment of people's health associated with time-varying conditions.

Identifiants

pubmed: 37656703
doi: 10.1371/journal.pone.0290962
pii: PONE-D-23-06555
pmc: PMC10473533
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0290962

Informations de copyright

Copyright: © 2023 Zheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Yan Zheng (Y)

Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.

Iñaki Permanyer (I)

Centre d'Estudis Demogràfics, Cerdanyola del Vallès, Barcelona, Spain.
ICREA, Passeig Lluís Companys 23, Barcelona, Spain.

Vladimir Canudas-Romo (V)

School of Demography, ANU College of Arts & Social Sciences, Australian National University, Canberra, Australia.

José Manuel Aburto (JM)

Department of Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Leverhulme Centre for Demographic Science, Department of Sociology and Nuffield College, University of Oxford, Oxford, United Kingdom.
Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Odense, Denmark.

Andrea Nigri (A)

Department of Economics, Management and Territory, University of Foggia, Foggia, Italy.

Oleguer Plana-Ripoll (O)

Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.

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Classifications MeSH