Skip to main content

Advertisement

SpringerLink
Log in

Spatial Sampling Design for a Demographic and Health Survey

  • Published:
Population Research and Policy Review Aims and scope Submit manuscript

Abstract

The recent advances in global position systems (GPS), geographic information systems (GIS), and remote sensing (RS) can be exploited for spatial sampling design for demographic and health surveys. These technologies are particularly useful when a sampling frame is unavailable and/or location (of household) is important for data collection (e.g., location of residence might greatly impact exposure to ambient air pollution among members of a population). Building on these technologies, this article presents a methodology of spatial sampling adopted for the respiratory health and demographic survey conducted in Delhi and its environs from January through April 2004. The overall goal of the survey was to select households that adequately represented exposure to ambient air pollution. The proposed methodology involved constructing a sampling frame of residential areas and the simulation of weighted random points within residential areas. The simulated locations were navigated with the aid of GPS to identify households at these locations and to acquire residents’ consent to participate in the survey; a total of 1,576 households at the 2,000 simulated locations were found suitable and participated in the survey. The average ambient air pollution at the sample sites was not significantly different from the average air pollution observed in the study area, which demonstrates the robustness of the proposed sampling method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Notes

  1. Overall PM10 concentration in the study area was substantially higher than the EPA standards in the US that are (a) a 24-h standard = 150 μg/m3, and (b) an annual 24-h standard = 50 μg/m3. (EPA 2005, retrieved from http://www.epa.gov/ttn/oarpg/naaqsfin/pmfact.html.)

References

  • Ackers, M., et al. (2005). Gender, age, and ethnicity in HIV vaccine-related research and clinical trials: Report from a WHO-UNAIDS consultation, 26–28 August 2004. Lausanne, Switzerland. Aids, 19(17), W7–W28.

    Google Scholar 

  • Amblard-Gross, G., Maul, A., Ferard, J. F., Carrot, F., & Ayrault, S. (2004). Spatial variability of sampling: Grid size impact on atmospheric metals and trace elements deposition mapping with mosses. Journal of Atmospheric Chemistry, 49(1–3), 39–52.

    Article  Google Scholar 

  • Angulo, J. M., Ruiz-Medina, M. D., Alonso, F. J., & Bueso, M. C. (2005). Generalized approaches to spatial sampling design. Environmetrics, 16(5), 523–534.

    Article  Google Scholar 

  • Arbia, G., & Lafratta, G. (2002). Anisotropic spatial sampling designs for urban pollution. Journal of the Royal Statistical Society, Series C-Applied Statistics, 51, 223–234.

    Article  Google Scholar 

  • Cerin, E., Saelens, B. E., Sallis, J. F., & Frank, L. D. (2006). Neighborhood environment walkability scale: validity and development of a short form. Medicine and Science in Sports and Exercise, 38(9), 1682–1691.

    Article  Google Scholar 

  • Cressie, N. (1990). The origins of kriging. Mathematical Geology, 2(3), 239–252.

    Article  Google Scholar 

  • Dessard, H., & Bar-Hen, A. (2005). Experimental design for spatial sampling applied to the study of tropical forest regeneration. Canadian Journal of Forest Research - Revue Canadienne De Recherche Forestiere, 35(5), 1149–1155.

    Article  Google Scholar 

  • Di Zio, S., Fontanella, L., & Ippoliti, L. (2004). Optimal spatial sampling schemes for environmental surveys. Environmental and Ecological Statistics, 11(4), 397–414.

    Article  Google Scholar 

  • Dumitrescu, A., Granados, A., Wallace, J., & Watson, S. (2006). Demand-driven evidence network in Europe. Bulletin of the World Health Organization, 84(1), 2–2.

    Google Scholar 

  • Eicher. (2001). Delhi: City map. New Delhi: Eicher Goodearth Ltd.

  • ESRI. (2005). ArcGIS, Version 9.1, Redlands. CA: Environmental Systems Research Institute.

  • Fleishman, E., McNally, R., & Murphy, D. D. (2005). Relationships among non-native plants, diversity of plants and butterflies, and adequacy of spatial sampling. Biological Journal of the Linnean Society, 85(2), 157–166.

    Article  Google Scholar 

  • Getis, A., Drummy, P., Gartin, J., Gorr, W., Harries, K., Rogerson, P., Stoe, D., & Wright, R. (2000). Geographic information science and crime analysis. URISA Journal, 12(2), 7–14.

    Google Scholar 

  • Goodchild M. F., & Janelle D. G. (eds.). (2004). Spatially integrated social science. Oxford, England: Oxford University Press.

    Google Scholar 

  • Gordon-Larsen, P., Nelson, M. C., Page, P., & Popkin, B. M. (2006). Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics, 117(2), 417–424.

    Article  Google Scholar 

  • Isaaks, E. H., & Srivastava, R. M. (1989). An introduction to applied geostatistics. New York: Oxford University Press.

    Google Scholar 

  • Kumar, N. (2006). Air quality regulation and spatial dimension of air pollution in Delhi and its surroundings. Economic and Political Weekly.

  • Lafratta, G. (2006). Efficiency evaluation of MEV spatial sampling strategies: A scenario analysis. Computational Statistics & Data Analysis, 50(3), 878–890.

    Article  Google Scholar 

  • Lee, C., Moudon, A. V., & Courbois, J. Y. P. (2006). Built environment and behavior: Spatial sampling using parcel data. Annals of Epidemiology, 16(5), 387–394.

    Article  Google Scholar 

  • Lewis, P. A.W., & Shedler, G. S. (1979). Simulating non-homogeneous Poisson processes by thinning. Naval Research Logistics Quarterly, 26, 403–413.

    Article  Google Scholar 

  • Liao, D. P., Peuquet, D., Duan, Y., Whitsel, E. A., Dou, J., Smith, R. L., Lin, H.-M., Chen, J.-C., & Heiss, G. (2006). GIS approaches for the estimation of residential-level ambient PM concentrations. Environmental Health Perspectives, 114(9), 1374–1380.

    Article  Google Scholar 

  • Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (1999). Geographical information systems. New York: John Wiley & Sons.

    Google Scholar 

  • McBratney, A. B., & Webster, R. (1981). Detection of ride and furrow pattern by spectral analysis of crop yield. International Statistics Review, 49, 45–52.

    Article  Google Scholar 

  • Met One, Inc. (2003). AEROCET 531: Operation manual. Grants Pass OR.

  • Müller, W. G. (1998). Collecting spatial data: Optimum design of experiments for random fields. New York: Physica-Verlag.

    Google Scholar 

  • Nychka, D., & Saltzman, N. (1998). Design of air-quality monitoring networks. In D. Nychka, W. Piegorsch, & L. Cox (Eds.), Case studies in environmental statistics. New York: Springer-Verlag.

    Google Scholar 

  • Ramachandran, G., Adgate, J. L., Pratt, G. C., & Sexton, K. (2003). Characterizing indoor and outdoor 15 minute average PM2.5 concentrations in urban neighborhoods. Aerosol Science and Technology, 37, 33–45.

    Article  Google Scholar 

  • Salehi, M. (2004). Optimal sampling design under a spatial correlation model. Journal of Statistical Planning and Inference, 118(1–2), 9–18.

    Article  Google Scholar 

  • Schabenberger, O., & Gotway, C. A. (2005). Statistical methods for spatial data analysis. Texts in Statistical Science. Boca Raton FL: Chapman & Hall/CRC.

    Google Scholar 

  • Schwartz, J. (1996). Air pollution and hospital admissions for respiratory disease. Epidemiology, 7(1), 20–28.

    Article  Google Scholar 

  • Stevens, D. L., Jr., & Olsen, A. R. (2004). Spatially balanced sampling of natural resources. Journal of the American Statistical Association, 99(465), 262–278.

    Article  Google Scholar 

  • Thomas, A., & Gebhart, J. (1994). Correlations between gravimetry and light-scattering photometry for atmospheric aerosols. Atmospheric Environment, 28(5), 935–938.

    Article  Google Scholar 

  • Thompson, S. K. (2002). Sampling: Wiley series in probability and statistics. London, England: John Wiley and Sons.

    Google Scholar 

  • Violante, F. S., Barbieri, A., Curti, S., Sanguinetti, G., Graziosi, F., & Mattioli, S. (2006). Urban atmospheric pollution: Personal exposure versus fixed monitoring station measurements. Chemosphere, 64(10), 1722–1729.

    Article  Google Scholar 

  • World Health Organization [WHO]. (2000). Guidelines for air quality. Geneva, Switzerland: World Health Organization.

    Google Scholar 

  • Zhu, Z. Y., & Stein, M. L. (2006). Spatial sampling design for prediction with estimated parameters. Journal of Agricultural Biological and Environmental Statistics, 11(1), 24–44.

    Article  Google Scholar 

  • Zhu, Z. Y., & Zhang, H. (2006). Spatial sampling design under the infill asymptotic framework. Environmetrics, 17(4), 323–337.

    Article  Google Scholar 

Download references

Acknowledgments

We greatly acknowledge the funding support provided by the Population Studies and Training Center, Brown University to collect air pollution data, and NICHD and NIH (grant # R21 HD046571-01A1) for the data analysis. We are thankful to Mr. Vineet Kumar, Dr. O.P. Malik, and Mr. Amit Kumar for air pollution data collection, identification of households around the simulated locations, and preparing the household list. We would also like to thank two anonymous referees for their valuable comments and suggestions.

Author information

Authors and Affiliations

  1. Department of Geography, University of Iowa, Iowa City, IA, 52242, USA

    Naresh Kumar

Authors
  1. Naresh Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Naresh Kumar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kumar, N. Spatial Sampling Design for a Demographic and Health Survey. Popul Res Policy Rev 26, 581–599 (2007). https://doi.org/10.1007/s11113-007-9044-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11113-007-9044-7

Keywords

Search

Navigation