The association of neighborhood characteristics with care outcomes among type 2 diabetes patients

Authors: Maija Toivakka*, University of Eastern Finland, Joensuu Finland, Markku Tykkyläinen, University of Eeastern Finland, Joensuu Finland, Tiina Laatikainen, University of Eastern Finland, Kuopio Finland; Joint municipal authority for North Karelia social and health services Joensuu, Finland; National Institute for Health and Welfare (THL), Helsinki, Finland
Topics: Medical and Health Geography, Geographic Information Science and Systems, Spatial Analysis & Modeling
Keywords: neighborhood characteristics, green space, residential greenness, type 2 diabetes, electronic health record, geographical information systems
Session Type: Paper
Day: 4/3/2019
Start / End Time: 4:30 PM / 6:10 PM
Room: Taylor, Marriott, Mezzanine Level
Presentation File: No File Uploaded


A growing interest in studying neighborhood greenness and how it affects human health exists. Our aim was to investigate the association between neighborhood characteristics, especially green space, and type 2 diabetes (T2D) prevalence and clinical care outcomes in North Karelia, eastern Finland. This region is rather green by nature as forests cover 89% of the land area. It has 166,441 inhabitants and the area is equal to the size of New Jersey.

The data consists of all diagnosed T2D patients (n=13,545) alive at the end of 2017. Electronic health records of T2D patients were retrieved from the regional electronic patient database. Patient information comprised age, gender, date of birth, the place of domicile (municipality, address), laboratory data, and clinical visit data. We assessed clinical care outcomes by different laboratory results and information recorded in clinical visits. Information on neighborhood characteristics were extracted from CORINE Land Cover 2012 dataset and topographic database of National Land Survey of Finland. In addition, Lipas, a national database of sport facilities, routes for outdoor activities and recreation areas was utilized. To study these associations between the neighborhood characteristics and care outcomes we applied Geographic Information System (GIS) techniques and statistical analysis.

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