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Environment and Urbanization, Vol. 13, No. 1, 235-255 (2001)
DOI: 10.1177/095624780101300117

Evaluating sanitary quality and classifying urban sectors according to environmental conditions

Craig A. Milroy

National Security Education Programme (NSEP), Instituto de Saude Coletiva, craig{at}ufba.br

Patricia C. Borja

borja{at}ufba.br

Fernando R. Barros

fernanbarros{at}bol.com.br

Mauricio L. Barreto

Instituo de Saude Coletiva (Federal University of Bahia), mauricio{at}ufba.br

This paper describes how principal components and cluster analyses were used to quantitatively score and rank sanitary conditions in 30 areas of Salvador (Northeast Brazil) and to identify groups of areas with similar environmental quality prior to a programme to improve sanitary infrastructure. In collecting data, street by street, a broad definition of sanitary quality was used, encompassing type and quality of housing, paving, water supply, sewage disposal, drainage and household waste disposal. All variables used in the principal components analysis were coded to reflect the absence of infrastructural elements that contribute to health and environmental quality. Summary variables generated by the analysis were used to score the sanitary quality of each of the areas, and cluster analysis identified four groups of areas, representing high, intermediate, poor and very poor sanitary quality. Higher rates of parasitic infection among children aged 7-14 years of age were found in areas with the worst sanitary conditions, with prevalences increasing progressively from the group with the best sanitary quality to the group with the worst sanitary quality. This kind of analysis provides a method both to appraise the needs of each community (including being able to prioritize areas most in need and identify areas with special sanitation needs) and to score baseline conditions that later allow the impacts of interventions to be assessed.

References

  • Selvin, S (1995), "Principal components analysis" in Practical Biostatistical Methods, Wadsworth Publishing Co., Belmont CA , pages 221-245.
  • Kleinbaum, D G, L L Kupper and K E Muller (1988), "Factor analysis" in Applied Regression Analysis and Other Multivariate Methods (2nd edition), Duxbury Press, North Scituate MA , pages 595-640.
  • Johnston, R J (1978), "Principal components analysis and factor analysis" in Multivariate Statistical Analysis in Geography: A Primer on the General Linear Model, Longman Group Ltd., London, UK , pages 127-183.

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[Abstract] [Full Text] [PDF]


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