Kirstine Wodschow1, Kristine Bihrmann2, Mogens Lytken Larsen3, Gunnar Gislason2,4,5,6, Annette Kjær Ersbøll2. 1. National Institute of Public Health, University of Southern Denmark, Studiestræde 6, 1455, Copenhagen K, Denmark. ikwo@si-folkesundhed.dk. 2. National Institute of Public Health, University of Southern Denmark, Studiestræde 6, 1455, Copenhagen K, Denmark. 3. Department of Clinical Medicine, Aalborg University, Aalborg, Denmark. 4. Department of Cardiology, Herlev and Gentofte Hospital, Herlev, Denmark. 5. Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. 6. The Danish Heart Foundation, Copenhagen, Denmark.
Abstract
BACKGROUND: The prevalence and incidence rate of atrial fibrillation (AF) increase worldwide and AF is a risk factor for more adverse cardiovascular diseases including stroke. Approximately 44% of AF cases cannot be explained by common individual risk factors and risk might therefore also be related to the environment. By studying geographical variation and clustering in risk of incident AF adjusted for socioeconomic position at an individual level, potential neighbourhood risk factors could be revealed. METHODS: Initially, yearly AF incidence rates 1987-2015 were estimated overall and stratified by income in a register-based cohort study. To examine geographical variation and clustering in AF, we used both spatial scan statistics and a hierarchical Bayesian Poisson regression analysis of AF incidence rates with random effect of municipalities (n = 98) in Denmark in 2011-2015. RESULTS: The 1987-2015 cohort included 5,453,639 individuals whereof 369,800 were diagnosed with an incident AF. AF incidence rate increased from 174 to 576 per 100,000 person-years from 1987 to 2015. Inequality in AF incidence rate ratio between highest and lowest income groups increased from 23% in 1987 to 38% in 2015. We found clustering and geographical variation in AF incidence rates, with incidence rates at municipality level being up to 34% higher than the country mean after adjusting for socioeconomic position. CONCLUSIONS: Geographical variations and clustering in AF incidence rates exist. Compared to previous studies from Alberta, Canada and the United States, we show that geographical variations exist in a country with free access to healthcare and even when accounting for socioeconomic differences at an individual level. An increasing social inequality in AF was seen from 1987 to 2015. Therefore, when planning prevention strategies, attention to individuals with low income should be given. Further studies focusing on identification of neighbourhood risk factors for AF are needed.
BACKGROUND: The prevalence and incidence rate of atrial fibrillation (AF) increase worldwide and AF is a risk factor for more adverse cardiovascular diseases including stroke. Approximately 44% of AF cases cannot be explained by common individual risk factors and risk might therefore also be related to the environment. By studying geographical variation and clustering in risk of incident AF adjusted for socioeconomic position at an individual level, potential neighbourhood risk factors could be revealed. METHODS: Initially, yearly AF incidence rates 1987-2015 were estimated overall and stratified by income in a register-based cohort study. To examine geographical variation and clustering in AF, we used both spatial scan statistics and a hierarchical Bayesian Poisson regression analysis of AF incidence rates with random effect of municipalities (n = 98) in Denmark in 2011-2015. RESULTS: The 1987-2015 cohort included 5,453,639 individuals whereof 369,800 were diagnosed with an incident AF. AF incidence rate increased from 174 to 576 per 100,000 person-years from 1987 to 2015. Inequality in AF incidence rate ratio between highest and lowest income groups increased from 23% in 1987 to 38% in 2015. We found clustering and geographical variation in AF incidence rates, with incidence rates at municipality level being up to 34% higher than the country mean after adjusting for socioeconomic position. CONCLUSIONS: Geographical variations and clustering in AF incidence rates exist. Compared to previous studies from Alberta, Canada and the United States, we show that geographical variations exist in a country with free access to healthcare and even when accounting for socioeconomic differences at an individual level. An increasing social inequality in AF was seen from 1987 to 2015. Therefore, when planning prevention strategies, attention to individuals with low income should be given. Further studies focusing on identification of neighbourhood risk factors for AF are needed.
Entities:
Keywords:
Atrial fibrillation; Bayesian analysis.; Cluster analysis; Epidemiology; Health registers; Health status disparities
Authors: Thomas Andersen Rix; Sam Riahi; Kim Overvad; Søren Lundbye-Christensen; Erik Berg Schmidt; Albert Marni Joensen Journal: Scand Cardiovasc J Date: 2012-03-29 Impact factor: 1.589
Authors: Jared W Magnani; Michiel Rienstra; Honghuang Lin; Moritz F Sinner; Steven A Lubitz; David D McManus; Josée Dupuis; Patrick T Ellinor; Emelia J Benjamin Journal: Circulation Date: 2011-11-01 Impact factor: 29.690
Authors: Bouwe P Krijthe; Anton Kunst; Emelia J Benjamin; Gregory Y H Lip; Oscar H Franco; Albert Hofman; Jacqueline C M Witteman; Bruno H Stricker; Jan Heeringa Journal: Eur Heart J Date: 2013-07-30 Impact factor: 29.983
Authors: Rhonda J Rosychuk; Hensley H Mariathas; Michelle M Graham; Brian R Holroyd; Brian H Rowe Journal: Acad Emerg Med Date: 2015-07-23 Impact factor: 3.451
Authors: Husam Abdel-Qadir; Leo E Akioyamen; Jiming Fang; Andrea Pang; Andrew C T Ha; Cynthia A Jackevicius; David A Alter; Peter C Austin; Clare L Atzema; R Sacha Bhatia; Gillian L Booth; Sharon Johnston; Irfan Dhalla; Moira K Kapral; Harlan M Krumholz; Candace D McNaughton; Idan Roifman; Karen Tu; Jacob A Udell; Harindra C Wijeysundera; Dennis T Ko; Michael J Schull; Douglas S Lee Journal: Circulation Date: 2022-06-09 Impact factor: 39.918