Skip to main content
SpringerLink
Log in

Do Area-Based Markers of Poverty Accurately Measure Personal Poverty?

  • Published:
Canadian Journal of Public Health Aims and scope Submit manuscript

Abstract

Area-based markers of deprivation (e.g., postal codes) are commonly used to identify groups of people with low socioeconomic status (SES); the validity of this approach, however, remains unknown. In this study, we determined the accuracy of using income quintile groups calculated on the basis of the median family income of each forward sortation area (1996 Canadian census) to identify those living in poverty (i.e., annual family income of < $12,620). The sensitivity and specificity of using the lowest income quintile to capture those in poverty were 26% and 83%, respectively (likelihood ratio (LR) of 1.49; 99% CI, 1.49 to 1.50). Among those in non-metropolitan and metropolitan areas, the LRs were 1.26 (99% CI, 1.26 to 1.27) and 2.01 (99% CI, 2.01 to 2.02), respectively. The use of postal codes as the only marker to identify people with low SES may result in substantial misclassification of personal poverty, particularly in nonmetropolitan areas.

Résumé

On utilise communément les indicateurs de dénuement fondés sur la zone (p. ex., le code postal) pour définir les groupes de gens dont le statut socio-économique (SSE) est faible, mais on ignore encore la validité d’une telle approche. Dans notre étude, nous avons déterminé le degré d’exactitude de l’emploi de quintiles de revenus calculés selon le revenu familial médian dans chaque région de tri d’acheminement (Recensement canadien de 1996) pour identifier les personnes vivant sous le seuil de pauvreté (revenu familial annuel <12 620 $). La sensibilité et la spécificité de l’emploi du quintile de revenus inférieur pour identifier ces personnes étaient de 26 % et de 83 %, respectivement (rapport des vraisemblances (RV) de 1,49; IC 99 %, 1,49 à 1,50). Pour la population à l’extérieur des régions urbaines et en zone métropolitaine, les RV étaient respectivement de 1,26 (IC 99 %, 1,26 à 1,27) et de 2,01 (IC 99 %, 2,01 à 2,02). L’emploi du code postal comme seul indicateur des gens à faible SSE pourrait donc entraîner d’importantes erreurs de classement de la pauvreté individuelle, surtout à l’extérieur des régions urbaines.

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

Similar content being viewed by others

References

  1. Pappas G, Queen S, Hadden W, Fisher G. The increasing disparity in mortality between socioe-conomic groups in the United States, 1960 and 1986. N Engl J Med 1993;329(2):103–9.

    Article  CAS  Google Scholar 

  2. Andrulis DP. Access to care is the centerpiece in the elimination of socioeconomic disparities in health. Ann Intern Med 1998;129(5):412–16.

    Article  CAS  Google Scholar 

  3. Ward P, Morton-Jones AJ, Pringle MA, et al. Generating social class data in primary care. Public Health 1994;108(4):279–87.

    Article  CAS  Google Scholar 

  4. Alter DA, Naylor CD, Austin P, et al. Effects of socioeconomic status on access to invasive cardiac procedures and on mortality after acute myocar-dial infarction. N Engl J Med 1999;341(18):1359–67.

    Article  CAS  Google Scholar 

  5. Krieger N. Overcoming the absence of socioeco-nomic data in medical records: Validation and application of a census-based methodology. Am J Public Health 1992;82(5):703–10.

    Article  CAS  Google Scholar 

  6. McLoone P, Ellaway A. Postcodes don’t indicate individuals’ social class. BMJ 1999;319(7215):1003–4.

    Article  CAS  Google Scholar 

  7. National Council of Welfare (Canada). Sounding the alarm: Poverty in Canada. Ottawa: Parliament. Senate, 1998; 48–96 (ISBN 0-662-26727-3).

    Google Scholar 

  8. Alberta Health and Wellness. AHIP; Premium and Rates. Available at www.health.gov.ab.ca/ahcip/premiums.htm.

  9. Statistics Canada. Census Metropolitan Area, Census Agglomeration and Census Tract (CMA/CA/CT) Reference Maps, 1996 Census. Ottawa: 92F0092XPB, 1997.

    Google Scholar 

  10. Salit SA, Kuhn EM, Hartz AJ, et al. Hospitalization costs associated with homeless-ness in New York City. N Engl J Med 1998;338(24):1734–40.

    Article  CAS  Google Scholar 

  11. Lynch JW, Kaplan GA, Pamuk ER, et al. Income inequality and mortality in metropolitan areas of the United States. Am J Public Health 1998;88(7):1074–80.

    Article  CAS  Google Scholar 

  12. Wilkinson RG. Unhealthy Societies: The Afflictions of Inequality. London: Routledge, 1996.

    Google Scholar 

  13. Demissie K, Hanley JA, Menzies D, et al. Agreement in measuring socio-economic status: Area-based versus individual measures. Chron Dis Can 2000;21(1):1–7.

    CAS  Google Scholar 

  14. Kaplan GA, Seeman TE, Cohen RD, et al. Mortality among the elderly in the Alameda County Study: Behavioral and demographic risk factors. Am J Public Health 1987;77(3):307–12.

    Article  CAS  Google Scholar 

  15. Marmot M, Bobak M, Smith GD. Explanations for social inequalities in health. In: Amick BC III, Levine S, Tarlov AR, Walsh DC (Eds.), Society and Health. New York: Oxford University Press, 1995;172–210.

    Google Scholar 

  16. Williamson DL, Fast JE. Poverty and medical treatment: When public policy compromises accessibility. Can J Public Health 1998;89(2):120–24.

    CAS  PubMed  Google Scholar 

  17. Taylor J. Access to health care for children in low-income families. Aust J Public Health 1994;18(1):111–13.

    Article  CAS  Google Scholar 

  18. Gravelle H. How much of the relation between population mortality and unequal distribution of income is a statistical artefact? BMJ 1998;316(7128):382–85.

    Article  CAS  Google Scholar 

  19. Danesh J, Gault S, Semmence J, et al. Postcodes as useful markers of social class: Population based study in 26,000 British households. BMJ 1999;318(7187):843–44.

    Article  CAS  Google Scholar 

  20. Carstairs V. Deprivation indices: Their interpretation and use in relation to health. J Epidemiol Community Health 1995;49(Suppl 2):S3–S8.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Pulmonary Medicine, Department of Medicine, University of Alberta, 2E4.29 Walter C. Mackenzie Centre, Edmonton, AB, T6G 2B7, Canada

    Don D. Sin MD, MPH & S. F. Paul Man MD

  2. Public Health Sciences, University of Alberta; and Health Surveillance Branch, Alberta Health and Wellness, Canada

    Larry W. Svenson BSc

Authors
  1. Don D. Sin MD, MPH
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Larry W. Svenson BSc
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. F. Paul Man MD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Don D. Sin MD, MPH.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sin, D.D., Svenson, L.W. & Man, S.F.P. Do Area-Based Markers of Poverty Accurately Measure Personal Poverty?. Can J Public Health 92, 184–187 (2001). https://doi.org/10.1007/BF03404301

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03404301

Search

Navigation