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Geographic analysis of diabetes prevalence in an urban area

Author

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  • Green, Chris
  • Hoppa, Robert D.
  • Young, T. Kue
  • Blanchard, J. F.

Abstract

The objective of this research is to identify the sociodemographic, environmental, and lifestyle factors associated with the geographic variability of Diabetes Mellitus (DM) prevalence in the City of Winnipeg, Manitoba in Canada. An ecological regression study design was employed for this purpose. The study population included all prevalent cases of DM in 1998 for Winnipeg. Predictor and outcome data were aggregated for analysis using two methods. First, the spatial scan statistic was used to aggregate study data into highly probable diabetes prevalence clusters. Secondly, predictor and outcome data were aggregated to existing administrative health areas. Analysis of variance and spatial and non-spatial linear regression techniques were used to explore the relationship between predictor and outcome variables. The results of the two methods of data aggregation on regression results were compared. Mapping and statistical analysis revealed substantial clustering and small-area variations in the prevalence of DM in the City of Winnipeg. The observed variations were associated with variations in socioeconomic, environmental and lifestyle characteristics of the population. The two methods of data aggregation used in the study generated very similar results in terms of identifying the geographic location of DM clusters and of the population characteristics ecologically correlated to those clusters. High rates of DM prevalence are strongly correlated with indicators of low socioeconomic status, poor environmental quality and poor lifestyles. This analysis further illustrates what a useful tool the spatial scan statistic can be when used in conjunction with ecological regression to explore the etiology of chronic disease.

Suggested Citation

  • Green, Chris & Hoppa, Robert D. & Young, T. Kue & Blanchard, J. F., 2003. "Geographic analysis of diabetes prevalence in an urban area," Social Science & Medicine, Elsevier, vol. 57(3), pages 551-560, August.
    • Handle: RePEc:eee:socmed:v:57:y:2003:i:3:p:551-560
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    Citations

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    Cited by:

    1. Chaufan, Claudia, 2007. "How much can a large population study on genes, environments, their interactions and common diseases contribute to the health of the American people?," Social Science & Medicine, Elsevier, vol. 65(8), pages 1730-1741, October.
    2. Crighton, Eric J. & Elliott, Susan J. & Moineddin, Rahim & Kanaroglou, Pavlos & Upshur, Ross, 2007. "A spatial analysis of the determinants of pneumonia and influenza hospitalizations in Ontario (1992-2001)," Social Science & Medicine, Elsevier, vol. 64(8), pages 1636-1650, April.
    3. Vaneckova, Pavla & Beggs, Paul J. & Jacobson, Carol R., 2010. "Spatial analysis of heat-related mortality among the elderly between 1993 and 2004 in Sydney, Australia," Social Science & Medicine, Elsevier, vol. 70(2), pages 293-304, January.
    4. Bartlett, Judith G. & Iwasaki, Yoshitaka & Gottlieb, Benjamin & Hall, Darlene & Mannell, Roger, 2007. "Framework for Aboriginal-guided decolonizing research involving Métis and First Nations persons with diabetes," Social Science & Medicine, Elsevier, vol. 65(11), pages 2371-2382, December.
    5. Fee, Margery, 2006. "Racializing narratives: Obesity, diabetes and the "Aboriginal" thrifty genotype," Social Science & Medicine, Elsevier, vol. 62(12), pages 2988-2997, June.
    6. Ke-wei Wang & Zhan-kun Shu & Le Cai & Jun-Qing Wu & Wei Wei, 2013. "Assessment of the Magnitude of Contextual and Individual Demographic Effects on Diabetes Mellitus and Glucose Intolerance in Rural Southwest China: A Multilevel Analysis," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
    7. Aletta Dijkstra & Fanny Janssen & Marinus De Bakker & Jens Bos & René Lub & Leo J G Van Wissen & Eelko Hak, 2013. "Using Spatial Analysis to Predict Health Care Use at the Local Level: A Case Study of Type 2 Diabetes Medication Use and Its Association with Demographic Change and Socioeconomic Status," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-9, August.

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