Small-scale health-related indicator acquisition using secondary data spatial interpolation

BackgroundDue to the lack of small-scale neighbourhood-level health related indicators, the analysis of social and spatial determinants of health often encounter difficulties in assessing the interrelations of neighbourhood and health. Although secondary data sources are now becoming increasingly available, they usually cannot be directly utilized for analysis in other than the designed study due to sampling issues. This paper aims to develop data handling and spatial interpolation procedures to obtain small area level variables using the Canadian Community Health Surveys (CCHS) data so that meaningful small-scale neighbourhood level health-related indicators can be obtained for community health research and health geographical analysis.ResultsThrough the analysis of spatial autocorrelation, cross validation comparison, and modeled effect comparison with census data, kriging is identified as the most appropriate spatial interpolation method for obtaining predicted values of CCHS variables at unknown locations. Based on the spatial structures of CCHS data, kriging parameters are suggested and potential small-area-level health-related indicators are derived. An empirical study is conducted to demonstrate the effective use of derived neighbourhood variables in spatial statistical modeling. Suggestions are also given on the accuracy, reliability and usage of the obtained small area level indicators, as well as further improvements of the interpolation procedures.ConclusionsCCHS variables are moderately spatially autocorrelated, making kriging a valid method for predicting values at unsampled locations. The derived variables are reliable but somewhat smoother, with smaller variations than the real values. As potential neighbourhood exposures in spatial statistical modeling, these variables are more suitable to be used for exploring potential associations than for testing the significance of these associations, especially for associations that are barely significant. Given the spatial dependency of current health-related risks, the developed procedures are expected to be useful for other similar health surveys to obtain small area level indicators.

[1]  J. L. Simpson,et al.  Are physical activity and employment related to preterm birth and low birth weight? , 1993, American journal of obstetrics and gynecology.

[2]  G. Smith,et al.  Disease aetiology and materialist explanations of socioeconomic mortality differentials: a research note , 1997 .

[3]  R. Moineddin,et al.  Birth outcomes by neighbourhood income and recent immigration in Toronto. , 2007, Health reports.

[4]  W. Wilson,et al.  Book Review: When Work Disappears: The World of the New Urban Poor , 1997 .

[5]  D. Shepard.  A two-dimensional interpolation function for irregularly-spaced data , 1968, ACM National Conference.

[6]  B. Wellman,et al.  Networks, Neighborhoods, and Communities , 1979 .

[7]  R. Nichols,et al.  A method for distinguishing consanguinity and population substructure using multilocus genotype data. , 2001, Molecular biology and evolution.

[8]  D. Pfeffermann.  Small Area Estimation‐New Developments and Directions , 2002 .

[9]  David Lamb,et al.  PA—Precision Agriculture: Remote-Sensing and Mapping of Weeds in Crops , 2001 .

[10]  P. Moran.  Notes on continuous stochastic phenomena. , 1950, Biometrika.

[11]  J. Morenoff,et al.  Neighborhood Mechanisms and the Spatial Dynamics of Birth Weight1 , 2003, American Journal of Sociology.

[12]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[13]  M. Bartley.  Health inequality : an introduction to theories, concepts and methods , 2004 .

[14]  T. Liszka.  An interpolation method for an irregular net of nodes , 1984 .

[15]  S. Łukaszyk.  A new concept of probability metric and its applications in approximation of scattered data sets , 2004 .

[16]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[17]  Russell Wilkins,et al.  Effect of neighbourhood income and maternal education on birth outcomes: a population-based study , 2006, Canadian Medical Association Journal.

[18]  M. E. Calle,et al.  Risk factors for low birth weight: a review. , 2004, European journal of obstetrics, gynecology, and reproductive biology.

[19]  H. Cleak,et al.  Health Inequality: An Introduction to Theories, Concepts and Methods , 2005 .

[20]  G. Shaw,et al.  Ambient air pollution and risk of birth defects in Southern California. , 2002, American journal of epidemiology.

[21]  D. Shaw,et al.  Social determinants of health, 2nd edn , 2008 .