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A Flexible Urban Health Index for Small Area Disparities

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Abstract

Available urban health metrics focus primarily on large area rankings. Less has been done to develop an index that provides information about level of health and health disparities for small geographic areas. Adopting a method used by the Human Development Index, we standardized indicators for small area units on a (0, 1) interval and combined them using their geometric mean to form an Urban Health Index (UHI). Disparities were assessed using the ratio of the highest to lowest decile and measurement of the slope of the eight middle deciles (middle; 80 %) of the data. We examined the sensitivity of the measure to weighting, to changes in the method, to correlation among indicators, and to substitution of indicators. Using seven health determinants and applying these methods to the 128 census tracts in the city of Atlanta, USA, we found a disparity ratio of 5.92 and a disparity slope of 0.54, suggesting substantial inequality and heterogeneity of risk. The component indicators were highly correlated; their systematic removal had a small effect on the results. Except in extreme cases, weighting had a little effect on the rankings. A map of Atlanta census tracts exposed a swath of high disparity. UHI rankings, ratio, and slope were resistant to alteration in composition and to non-extreme weighting schemes. This empirical evaluation was limited to a single realization, but suggests that a flexible tool, whose method rather than content is standardized, may be of use for local evaluation, for decision making, and for area comparison.

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References

  1. World Health Organization. World Health Statistics 2010. Indicator compendium. Web, 2010. http://www.who.int/whosis/indicators/WHS10_IndicatorCompendium_20100513.pdf. Accessed 21 Dec 2010.

  2. US Department of Health and Human Services. Community Health Status Indicators. Web, 2009. http://communityhealth.hhs.gov/homepage.aspx?j=1. Accessed 21 Dec 2010

  3. The World Bank. World Development Indicators. Web, 2010. http://data.worldbank.org/indicator. Accessed 21 Dec 2010.

  4. Office of Disease Prevention and Health Promotion, US Department of Health and Human Services. Health People 2010. Web, 2010. http://www.healthypeople.gov/default.htm. Accessed 21 Dec 2010.

  5. Boerma J, Mathers C, Abou-Zahr C. WHO and Global Health Monitoring: the Way Forward. PLoS Med. 2010; 7: 11.

    Article  Google Scholar 

  6. Byass P. The imperfect world of global health estimates. PLoS Med. 2010; 7: 11.

    Google Scholar 

  7. Graham WJ, Adjei S. A call for responsible estimation of global health. PLoS Med. 2010; 7(11).

  8. Murray CJL, Lopez AD. Production and analysis of health indicators: the role of academia. PLoS Med. 2010; 7: 11.

    Google Scholar 

  9. PLoS Medicine Editors. We count on global health estimates? PLoS Med. 2010; 7: (11).

    Google Scholar 

  10. Sankoh O. Global health estimates: tronger collaboration needed with low- and middle-income countries. PLoS Med. 2010; 7(11).

  11. Saltelli A, Nardo M, Saisana J, Tarantola S. Composite indicators: the controversy and the way forward. In Proceedings of the OECD Forum "Statistics, Knowledge and Policy: World Forum on Key Indicators" November 2004. Web, 2004. http://www.sourceoecd.org/general/economics/9264009000. Accessed 21 Dec 2010.

  12. European Commission Joint Research Centre. Composite Indicators. Web, 2009. http://composite-indicators.jrc.ec.europa.eu/. Accessed 30 Dec 2010.

  13. Saltelli A. Composite indicators: between analysis and advocacy. Soc Indic Res. 2007; 81: 65–77.

    Google Scholar 

  14. Saltelli A. Composite Indicators: ten Steps. Web, 2009. http://composite-indicators.jrc.ec.europa.eu/Seminar_Eurostat_2009/Saltelli-TenSteps.pdf. Accessed 30 Dec 2010.

  15. Tarantola S, Saltelli A. Composite indicators: the art of mixing apples and oranges. Web, 2007. http://kolloq.destatis.de/2007/tarantola.pdf. Accessed 30 Dec 2010.

  16. Gardner JW, Sanborn JS. Years of Potential Life Lost (YPLL)-What does it measure? Epidemiology. 2010; 1: 322–9.

    Article  Google Scholar 

  17. Nardo M, Saisana M, Saltelli A, Tarantola S, Hoffman A, Giovannini E. Handbook on constructing composite indicators: methodology and user guide. OECC Statistics Working Papers, 2005/3. Paris, France: OECD Publishing; 2005.

  18. Nardo M, Saisana J, Saltelli A, Tarantola S. Tools for composite indicators building. from European Commission: Joint Research Centre. Web, 2005. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.114.4806&rep=rep1&type=pdf. Accessed 28 Mar 2014.

  19. Rey G, Jougla E, Fouillet A, Hemon D. Ecological association between a deprivation index and mortality in France over the period 1997–2001: variations with spatial scale, degree of urbanicity, age, gender, and cause of death. BMC Public Health. 2009; 9: 33.

    Google Scholar 

  20. United National Development Programme. Human Development Indices: technical notes. Web, 2010. http://hdr.undp.org/en/media/HDR_2010_EN_TechNotes_reprint.pdf. Accessed 30 Dec 2010.

  21. United National Development Programme. Human Development Report 2010. Web, 2010. http://hdr.undp.org/en/statistics/indices/. Accessed 21 Dec 2010.

  22. Etches V, Frank J, DiRuggiero E, Manuel D. Measuring population health: a review of indicators. Annu Rev Public Health. 2006; 27: 29.

    Article  PubMed  Google Scholar 

  23. Handcock M, Morris M. Relative distribution methods. Sociol Methodol. 1998; 28: 53–97.

    Article  Google Scholar 

  24. Handcock M, Morris M. Relative distribution methods in the social sciences. In: Fienberg S, Lievesley D, Rolph J, eds. Statistics for Social Sciences and Public policy. New York, NY: Springer-Verlag, Inc; 1999.

  25. Houweling TAJ, Kunst AE, Mackenbach JP. World health report 2000: inequality index and socioeconomic inequalities in mortality. Lancet. 2001; 357: 1671–2.

    Article  PubMed  CAS  Google Scholar 

  26. Mackenbach JP, Kunst A. Measuring the magnitude of socio-economic inequalities in health: and overview of available measures illustrated with two examples from Europe. Soc Sci Med. 2010; 44(6): 757–71.

    Article  Google Scholar 

  27. Schneider MC, Castillo-Salgado C, Bacallao J, et al. Methods for measuring health inequalities (Part I). Epidemiol Bull. 2004; 25(2): 12–4.

    Google Scholar 

  28. Schneider MC, Castillo-Salgado C, Bacallao J, et al. Methods for measuring health inequalities (Part II). Epidemiol Bull. 2005; 26(1): 5–10.

    Google Scholar 

  29. Schneider MC, Castillo-Salgado C, Bacallao J, et al. Methods for measuring health inequalities (Part III). Epidemiol Bull. 2005; 26(2): 12–5.

    PubMed  Google Scholar 

  30. World Health Organization: centre for Health Development. Urban Health Equity Assessment and Response Tool (Urban HEART). Web, 2010. http://www.who.or.jp/urbanheart.html. Accessed 22 Dec 2010.

  31. United States Census Bureau. Pre-2010 Census Cartographic Boundary Files. US Census Bureau, 2012. http://www.census.gov/geo/www/cob/bdy_files.html. Accessed 20 Jan 2013.

  32. WHO Kobe Centre. Report of Consultation Meeting on Urban Health Metrics Research 23–25 February, 2011. 2012.

  33. Hardisty F, Robinson AC. The GeoViz Toolkit: using component-oriented coordination methods for geographic visualization and analysis. Int J Geogr Inf Sci. 2011; 25(2): 191–210.

    Article  PubMed  PubMed Central  Google Scholar 

  34. WHO Commission of Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of health. Geneva: world Health Organization, 2013. http://www.who.int/social_determinants/thecommission/finalreport/en/index.html. Accessed 21 Jan 2013.

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Acknowledgment

This study was supported by a grant from the WHO Center for Health Development (the WHO Kobe Center). Research support was also provided by the National Institute of Minority Health and Health Disparities of the National Institutes of Health under award number 1P20MD004806. The content is solely the responsibility of the authors and does not necessarily represent the official views of the World Health Organization or of the National Institutes of Health.

The authors would like to acknowledge the advice and encouragement of Dr. Michael Eriksen, Founding Dean of the School of Public Health, GSU; and Byungwoo Cho, Prasanth Kambhatla, and Kumiko Miyake, who provided technical assistance in translation, data management, and analysis.

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Correspondence to Richard Rothenberg.

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Rothenberg, R., Weaver, S.R., Dai, D. et al. A Flexible Urban Health Index for Small Area Disparities. J Urban Health 91, 823–835 (2014). https://doi.org/10.1007/s11524-014-9867-6

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  • DOI: https://doi.org/10.1007/s11524-014-9867-6

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