Birth cohort effects on diagnosed atrial fibrillation incidence: nationwide cohort study from 1980 to 2018.

Atrial Fibrillation Epidemiology

Journal

Heart (British Cardiac Society)
ISSN: 1468-201X
Titre abrégé: Heart
Pays: England
ID NLM: 9602087

Informations de publication

Date de publication:
12 Mar 2024
Historique:
received: 24 11 2023
accepted: 17 02 2024
medline: 13 3 2024
pubmed: 13 3 2024
entrez: 12 3 2024
Statut: aheadofprint

Résumé

The incidence of atrial fibrillation (AF) shows substantial temporal trends, but the contribution of birth cohort effects is unknown. These effects refer to the relationship between birth year and the likelihood of developing AF. We aimed to assess trends in cumulative incidence of diagnosed AF across birth cohorts and to disentangle the effects of age, birth cohort and calendar period by using age-period-cohort analyses. In a Danish nationwide population-based cohort study, 4.7 million individuals were selected at a given index age (45, 55, 65 and 75 years) free of AF and followed up for diagnosed AF. For each index age, we assessed trends in 10-year cumulative incidence of AF across six 5-year birth cohorts. An age-period-cohort model was estimated using Poisson regression with constrained spline functions collapsing data into 1-year intervals across ages and calendar years. Cumulative incidence of AF diagnosis increased across birth cohorts for all index ages (p Substantial birth cohort effects, independent of age and calendar period, influence trends in diagnosed AF incidence.

Sections du résumé

BACKGROUND BACKGROUND
The incidence of atrial fibrillation (AF) shows substantial temporal trends, but the contribution of birth cohort effects is unknown. These effects refer to the relationship between birth year and the likelihood of developing AF. We aimed to assess trends in cumulative incidence of diagnosed AF across birth cohorts and to disentangle the effects of age, birth cohort and calendar period by using age-period-cohort analyses.
METHODS METHODS
In a Danish nationwide population-based cohort study, 4.7 million individuals were selected at a given index age (45, 55, 65 and 75 years) free of AF and followed up for diagnosed AF. For each index age, we assessed trends in 10-year cumulative incidence of AF across six 5-year birth cohorts. An age-period-cohort model was estimated using Poisson regression with constrained spline functions collapsing data into 1-year intervals across ages and calendar years.
RESULTS RESULTS
Cumulative incidence of AF diagnosis increased across birth cohorts for all index ages (p
CONCLUSION CONCLUSIONS
Substantial birth cohort effects, independent of age and calendar period, influence trends in diagnosed AF incidence.

Identifiants

pubmed: 38471730
pii: heartjnl-2023-323737
doi: 10.1136/heartjnl-2023-323737
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: NV has served as an advisory board member and consultant for AstraZeneca, no fees were received personally. PC—none. SPJ—co-principal investigator of AFFIRMO, which has received funding from the European Union’s Horizon 2020 research and innovation programme (no 899871); institutional research grant from BMS/Pfizer (not related to the current study); personal consulting fees received from BMS and Pfizer. EJB—R01HL092577; R01AG066010; 1R01AG066914; American Heart Association AF AHA_18SFRN34110082. LF is supported by the Health Research Foundation of Central Denmark Region and has served as a consultant for BMS/Pfizer and AstraZeneca. LT was supported by a research grant from the American Heart Association (18SFRN34150007).

Auteurs

Nicklas Vinter (N)

Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark nicvin@rm.dk.
Diagnostic Centre, University Clinic for Development of Innovative Patient Pathways, Silkeborg Regional Hospital, Silkeborg, Denmark.
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.

Pia Cordsen (P)

Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.

Søren Paaske Johnsen (SP)

Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.

Emelia J Benjamin (EJ)

Department of Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts, USA.
Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA.

Lars Frost (L)

Diagnostic Centre, University Clinic for Development of Innovative Patient Pathways, Silkeborg Regional Hospital, Silkeborg, Denmark.
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.

Ludovic Trinquart (L)

Danish Center for Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
Tufts Clinical and Translational Science Institute, Tufts University, Boston, Massachusetts, USA.
Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, USA.
Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA.

Classifications MeSH