Abstract:Techniques based on geographic information systems (GIS) have been widely adopted and applied in the fields of infectious disease and environmental epidemiology; their use in chronic disease programs is relatively new. The Centers for Disease Control and Prevention’s Division for Heart Disease and Stroke Prevention is collaborating with the National Association of Chronic Disease Directors and the University of Michigan to provide health departments with capacity to integrate GIS into daily operations, which s… Show more
“…Geographical variation in ischaemic heart disease, including acute myocardial infarction (AMI), exists globally and within countries 1–3. Identifying and understanding geographical patterns in disease provide important information on potential drivers of disease inequalities and disease aetiology as well as where to implement prevention strategies that target the most vulnerable populations and areas 4 5…”
ObjectiveThis study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics.DesignAn 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.SettingResidents in Denmark (2005–2014).ParticipantsThe study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI.Outcome measureIncident AMI registered in the National Patient Register or the Register of Causes of Death.ResultsIncluding 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.ConclusionsDifferences 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.
“…Geographical variation in ischaemic heart disease, including acute myocardial infarction (AMI), exists globally and within countries 1–3. Identifying and understanding geographical patterns in disease provide important information on potential drivers of disease inequalities and disease aetiology as well as where to implement prevention strategies that target the most vulnerable populations and areas 4 5…”
ObjectiveThis study examined whether geographical patterns in incident acute myocardial infarction (AMI) were explained by neighbourhood-level and individual-level sociodemographic characteristics.DesignAn 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.SettingResidents in Denmark (2005–2014).ParticipantsThe study population included 4 128 079 persons (33 907 796 person-years at risk) out of whom 98 265 experienced an incident AMI.Outcome measureIncident AMI registered in the National Patient Register or the Register of Causes of Death.ResultsIncluding 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.ConclusionsDifferences 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.
“…While there are improvements that can still be made in GIS, they can still be extremely useful in the study of environmental epidemiology 10. Mapping through GIS can make substantial gains in the evaluation of environmental health risks 11.…”
backgroundThe purpose of this literature review is to understand geographical information systems (GISs) and how they can be applied to public health informatics, medical informatics and epidemiology.
“…Given the value of applied GIS, we invited staff members from 1 local and 3 state health departments to describe their use of GIS to address chronic disease priorities. These health departments previously participated in the Building GIS Capacity for Chronic Disease Surveillance training, which is provided through a collaboration of the Centers for Disease Control and Prevention (CDC), the National Association of Chronic Disease Directors, and the Children’s Environmental Health Initiative (CEHI) (currently at Rice University) (2). The prompts given to the health departments were:…”
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