Geographical inequalities in acute myocardial infarction beyond neighbourhood-level and individual-level sociodemographic characteristics

a Danish 10-year nationwide population-based cohort study

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

OBJECTIVE: This study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics. DESIGN: An open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005-2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education. SETTING: Residents in Denmark (2005-2014). PARTICIPANTS: The study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI. OUTCOME MEASURE: Incident AMI registered in the National Patient Register or the Register of Causes of Death. RESULTS: Including individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40% increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns. CONCLUSIONS: Differences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.

Original languageEnglish
Article numbere024207
JournalBMJ Open
Volume9
Issue number2
ISSN2044-6055
DOIs
Publication statusPublished - 2019

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Cohort Studies
Population
Denmark
Incidence
Population Density
Registries
Cause of Death
Education
Health

Keywords

  • epidemiology
  • myocardial infarction
  • social medicine

Cite this

@article{dd9cea08c2f54a3d9e3f41d284375d33,
title = "Geographical inequalities in acute myocardial infarction beyond neighbourhood-level and individual-level sociodemographic characteristics: a Danish 10-year nationwide population-based cohort study",
abstract = "OBJECTIVE: This study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics. DESIGN: An open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005-2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education. SETTING: Residents in Denmark (2005-2014). PARTICIPANTS: The study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI. OUTCOME MEASURE: Incident AMI registered in the National Patient Register or the Register of Causes of Death. RESULTS: Including individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40{\%} increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns. CONCLUSIONS: Differences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.",
keywords = "epidemiology, myocardial infarction, social medicine",
author = "Kj{\ae}rulff, {Thora Majlund} and Kristine Bihrmann and Ingelise Andersen and Gislason, {Gunnar Hilmar} and Larsen, {Mogens Lytken} and Ersb{\o}ll, {Annette Kj{\ae}r}",
year = "2019",
doi = "10.1136/bmjopen-2018-024207",
language = "English",
volume = "9",
journal = "B M J Open",
issn = "2044-6055",
publisher = "BMJ Group",
number = "2",

}

TY - JOUR

T1 - Geographical inequalities in acute myocardial infarction beyond neighbourhood-level and individual-level sociodemographic characteristics

T2 - a Danish 10-year nationwide population-based cohort study

AU - Kjærulff, Thora Majlund

AU - Bihrmann, Kristine

AU - Andersen, Ingelise

AU - Gislason, Gunnar Hilmar

AU - Larsen, Mogens Lytken

AU - Ersbøll, Annette Kjær

PY - 2019

Y1 - 2019

N2 - OBJECTIVE: This study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics. DESIGN: An open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005-2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education. SETTING: Residents in Denmark (2005-2014). PARTICIPANTS: The study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI. OUTCOME MEASURE: Incident AMI registered in the National Patient Register or the Register of Causes of Death. RESULTS: Including individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40% increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns. CONCLUSIONS: Differences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.

AB - OBJECTIVE: This study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics. DESIGN: An open cohort study design of AMI-free adults (age ≥30 years) with a residential location in Denmark in 2005-2014 was used based on nationwide administrative population and health register data linked by the unique personal identification number. Poisson regression of AMI incidence rates (IRs) with a geographical random effect component was performed using a Bayesian approach. The analysis included neighbourhood-level variables on income, ethnic composition, population density and population turnover and accounted for individual-level age, sex, calendar year, cohabitation status, income and education. SETTING: Residents in Denmark (2005-2014). PARTICIPANTS: The study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI. OUTCOME MEASURE: Incident AMI registered in the National Patient Register or the Register of Causes of Death. RESULTS: Including individual and neighbourhood sociodemographic characteristics in the model decreased the variation in IRs of AMI. However, living in certain areas was associated with up to 40% increased IRs of AMI in the adjusted model and accounting for sociodemographic characteristics only moderately changed the geographical disease patterns. CONCLUSIONS: Differences in sociodemographic characteristics of the neighbourhood and individuals explained part, but not all of the geographical inequalities in incident AMI. Prevention strategies should address the confirmed social inequalities in incident AMI, but also target the areas with a heavy disease burden to enable efficient allocation of prevention resources.

KW - epidemiology

KW - myocardial infarction

KW - social medicine

U2 - 10.1136/bmjopen-2018-024207

DO - 10.1136/bmjopen-2018-024207

M3 - Journal article

VL - 9

JO - B M J Open

JF - B M J Open

SN - 2044-6055

IS - 2

M1 - e024207

ER -