PMID- 28208207
OWN - NLM
STAT- MEDLINE
DCOM- 20190610
LR  - 20190613
IS  - 1439-4421 (Electronic)
IS  - 0941-3790 (Linking)
VI  - 80
IP  - S 02
DP  - 2018 Mar
TI  - [Spatial Distribution of Type 2 Diabetes Mellitus in Berlin: Application of a 
      Geographically Weighted Regression Analysis to Identify Location-Specific Risk 
      Groups].
PG  - S64-S70
LID - 10.1055/s-0042-123845 [doi]
AB  - Understanding which population groups in which locations are at higher risk for 
      type 2 diabetes mellitus (T2DM) allows efficient and cost-effective interventions 
      targeting these risk-populations in great need in specific locations. The goal of 
      this study was to analyze the spatial distribution of T2DM and to identify the 
      location-specific, population-based risk factors using global and local spatial 
      regression models. To display the spatial heterogeneity of T2DM, bivariate kernel 
      density estimation was applied. An ordinary least squares regression model (OLS) 
      was applied to identify population-based risk factors of T2DM. A geographically 
      weighted regression model (GWR) was then constructed to analyze the spatially 
      varying association between the identified risk factors and T2DM. T2DM is 
      especially concentrated in the east and outskirts of Berlin. The OLS model 
      identified proportions of persons aged 80 and older, persons without migration 
      background, long-term unemployment, households with children and a negative 
      association with single-parenting households as socio-demographic risk groups. 
      The results of the GWR model point out important local variations of the strength 
      of association between the identified risk factors and T2DM. The risk factors for 
      T2DM depend largely on the socio-demographic composition of the neighborhoods in 
      Berlin and highlight that a one-size-fits-all approach is not appropriate for the 
      prevention of T2DM. Future prevention strategies should be tailored to target 
      location-specific risk-groups.
CI  - (c) Georg Thieme Verlag KG Stuttgart . New York.
FAU - Kauhl, Boris
AU  - Kauhl B
AD  - Arztliche Versorgung, AOK Nordost, Potsdam.
FAU - Pieper, Jonas
AU  - Pieper J
AD  - Fachbereich Bauingenieur- und Geoinformationswesen, Beuth Hochschule fur Technik 
      Berlin, Berlin.
FAU - Schweikart, Jurgen
AU  - Schweikart J
AD  - Fachbereich III, Beuth Hochschule fur Technik Berlin, Berlin.
FAU - Keste, Andrea
AU  - Keste A
AD  - Arztliche Versorgung, AOK Nordost, Potsdam.
FAU - Moskwyn, Marita
AU  - Moskwyn M
AD  - Arztliche Versorgung, AOK Nordost, Potsdam.
LA  - ger
PT  - Journal Article
TT  - Die raumliche Verbreitung des Typ 2 Diabetes Mellitus in Berlin - Die Anwendung 
      einer geografisch gewichteten Regressionsanalyse zur Identifikation 
      ortsspezifischer Risikogruppen.
DEP - 20170216
PL  - Germany
TA  - Gesundheitswesen
JT  - Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes 
      (Germany))
JID - 9204210
SB  - IM
MH  - Adult
MH  - Aged
MH  - Aged, 80 and over
MH  - Berlin
MH  - Child
MH  - *Diabetes Mellitus, Type 2/epidemiology
MH  - *Geographic Information Systems
MH  - Germany/epidemiology
MH  - Humans
MH  - Middle Aged
MH  - Regression Analysis
MH  - Risk Factors
MH  - Spatial Analysis
MH  - *Spatial Regression
COIS- Die Autoren geben an, dass kein Interessenkonflikt besteht.
EDAT- 2017/02/17 06:00
MHDA- 2019/06/14 06:00
CRDT- 2017/02/17 06:00
PHST- 2017/02/17 06:00 [pubmed]
PHST- 2019/06/14 06:00 [medline]
PHST- 2017/02/17 06:00 [entrez]
AID - 10.1055/s-0042-123845 [doi]
PST - ppublish
SO  - Gesundheitswesen. 2018 Mar;80(S 02):S64-S70. doi: 10.1055/s-0042-123845. Epub 
      2017 Feb 16.