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Canadian Journal of Public Health

, Volume 109, Issue 3, pp 410–418 | Cite as

Comparing individual and area-based income measures: impact on analysis of inequality in smoking, obesity, and diabetes rates in Canadians 2003–2013

  • Erin Pichora
  • Jane Y. Polsky
  • Christina Catley
  • Nita Perumal
  • Jing Jin
  • Sara Allin
Quantitative Research

Abstract

Objectives

The aims of this study were to examine (1) the concordance between income measured at the individual and area-based level and (2) the impact of using each measure of income on inequality estimates for three health indicators—the prevalence, respectively, of diabetes, smoking, and obesity.

Methods

Data for the health indicators and individual income among adults came from six cycles of the Canadian Community Health Survey (cycles 2003 through 2013). Area-based income was obtained by linking respondents’ residential postal codes to neighbourhood income quintiles derived from the 2006 Canadian census. Relative and absolute inequality between the lowest and highest income quintiles for each measure was assessed using rate ratios and rate differences, respectively.

Results

Concordance between the two income measures was poor in the overall sample (weighted Kappa estimates ranged from 0.19 to 0.21 for all years), and for the subset of participants reporting diabetes, smoking, or obesity. Despite the poor concordance, both individual and area-based income measures identified generally comparable levels of relative and absolute inequality in the rates of diabetes, smoking, and obesity over the 10-year study period.

Conclusion

The results of this study show that individual and area-based income measures categorize Canadians differently according to income quintile, yet both measures reveal striking income-related inequalities in rates of diabetes and smoking, and obesity among women. This suggests that either individual or area-level measures can be used to monitor income-related health inequalities in Canada; however, whenever possible, it is informative to consider both measures since they likely represent distinct social constructs.

Keywords

Income* Health status disparities Socio-economic factors Diabetes mellitus Obesity Smoking 

Résumé

Objectifs

Examiner (1) la concordance entre le revenu personnel et régional et (2) l’incidence de l’utilisation de chaque indicateur du revenu sur les estimations des inégalités pour trois indicateurs de la santé, soit la prévalence, respectivement, du diabète, du tabagisme et de l’obésité.

Méthode

Les données des indicateurs de la santé et du revenu personnel chez les adultes proviennent de six cycles (2003 à 2013) de l’Enquête sur la santé dans les collectivités canadiennes. Le revenu régional a été obtenu en maillant les codes postaux de résidence des répondants aux quintiles de revenu selon le quartier dérivés du Recensement du Canada de 2006. Les inégalités relatives et absolues entre les quintiles de revenu inférieur et supérieur pour chaque indicateur ont été évaluées par les rapports de taux et les différences de taux, respectivement.

Résultats

La concordance entre les deux indicateurs du revenu est faible dans l’échantillon global (le coefficient kappa pondéré est de 0,19 à 0,21 pour toutes les années) et pour le sous-ensemble de participants ayant fait état de diabète, de tabagisme ou d’obésité. Malgré cette faible concordance, les indicateurs du revenu personnel et régional révèlent des niveaux généralement comparables d’inégalités relatives et absolues dans les taux de diabète, de tabagisme et d’obésité sur les 10 ans de l’étude.

Conclusion

Les résultats de l’étude montrent que les indicateurs du revenu personnel et régional classent les Canadiens différemment selon le quintile de revenu, mais que les deux indicateurs révèlent des inégalités marquantes liées au revenu dans les taux de diabète et de tabagisme, et chez les femmes, dans les taux d’obésité. L’indicateur personnel ou l’indicateur régional peuvent donc l’un et l’autre être utilisés pour surveiller les inégalités de santé liées au revenu au Canada; dans la mesure du possible, il est toutefois instructif de les utiliser tous les deux, car ils représentent probablement des constructions sociales distinctes.

Mots-clés

Revenu* Disparités de l’état de santé Facteurs socioéconomiques Diabète Obésité Tabagisme 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Agence de la Santé et des Services Sociaux de Montreal. 2011 report of the director of public health. Social inequalities in health in Montreal: Progress to date. Montreal, QC; 2011.Google Scholar
  2. Braveman, P. A., Cubbin, C., Egerter, S., et al. (2005). Socioeconomic status in health research: one size does not fit all. J Am Med Assoc, 294(22), 2879–2888.  https://doi.org/10.1001/jama.294.22.2879.CrossRefGoogle Scholar
  3. Braveman, P., Egerter, S., & Williams, D. R. (2011). The social determinants of health: coming of age. Annu Rev Public Health, 32, 381–398.  https://doi.org/10.1146/annurev-publhealth-031210-101218.CrossRefPubMedGoogle Scholar
  4. Canadian Institute for Health Information. (2015). Trends in income-related health inequalities in Canada. Ottawa, ON: CIHI.Google Scholar
  5. Canadian Institute for Health Information. (2016). Pan-Canadian dialogue to advance the measurement of equity in health care. Ottawa, ON: CIHI.Google Scholar
  6. Demissie, K., Hanley, J. A., Menzies, D., Joseph, L., & Ernst, P. (2000). Agreement in measuring socio-economic status: area-based versus individual measures. Chronic Dis Can, 21(1), 1–7.PubMedGoogle Scholar
  7. Diez Roux, A. V. (2001). Investigating neighborhood and area effects on health. Am J Public Health, 91(11), 1783–1789.CrossRefPubMedPubMedCentralGoogle Scholar
  8. Finkelstein, M. M. (2004). Ecologic proxies for household income: how well do they work for the analysis of health and health care utilization? Canadian Journal of Public Health, 95(2), 90–94.PubMedGoogle Scholar
  9. Geronimus, A. T., & Bound, J. (1998). Use of census-based aggregate variables to proxy for socioeconomic group: evidence from national samples. Am J Epidemiol, 148(5), 475–486.CrossRefPubMedGoogle Scholar
  10. Hanley, G. E., & Morgan, S. (2008). On the validity of area-based income measures to proxy household income. BMC Health Serv Res, 8.  https://doi.org/10.1186/1472-6963-8-79.
  11. Hosseinpoor, A. R., Bergen, N., Koller, T., et al. (2014). Equity-oriented monitoring in the context of universal health coverage. PLoS Med, 11(9).  https://doi.org/10.1371/journal.pmed.1001727.CrossRefPubMedPubMedCentralGoogle Scholar
  12. Humphries, K. H., & Van Doorslaer, E. (2000). Income-related health inequality in Canada. Soc Sci Med, 50(5), 663–671.  https://doi.org/10.1016/S0277-9536(99)00319-6.CrossRefPubMedGoogle Scholar
  13. Institute for Health Metrics and Evaluations. Global burden of disease study (GBD), country profiles: Canada. Available at: http://www.healthdata.org/canada. Updated 2015. Accessed November 30, 2016.
  14. Krieger, N. (1992). Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health, 82(5), 703–710.CrossRefPubMedPubMedCentralGoogle Scholar
  15. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.CrossRefGoogle Scholar
  16. Locker, D., & Ford, J. (1996). Using area-based measures of socioeconomic status in dental health services research. J Public Health Dent, 56(2), 69–75.CrossRefPubMedGoogle Scholar
  17. Marra, C. A., Lynd, L. D., Harvard, S. S., & Grubisic, M. (2011). Agreement between aggregate and individual-level measures of income and education: a comparison across three patient groups. BMC Health Serv Res, 11.  https://doi.org/10.1186/1472-6963-11-69.
  18. Martens, P. J., Brownell, M., Au, W., et al. (September 2010). Health inequalities in Manitoba: is the socioeconomic gap widening or narrowing over time? Winnipeg, MB: Manitoba Centre for Health Policy.Google Scholar
  19. Meijer, M., Röhl, J., Bloomfield, K., & Grittner, U. (2012). Do neighborhoods affect individual mortality? A systematic review and meta-analysis of multilevel studies. Soc Sci Med, 74(8), 1204–1212.  https://doi.org/10.1016/j.socscimed.2011.11.034.CrossRefPubMedGoogle Scholar
  20. Mustard, C. A., Derksen, S., Berthelot, J., & Wolfson, M. (1999). Assessing ecologic proxies for household income: a comparison of household and neighbourhood level income measures in the study of population health status. Health and Place., 5(2), 157–171.  https://doi.org/10.1016/S1353-8292(99)00008-8.CrossRefPubMedGoogle Scholar
  21. Narla, N. P., Pardo-Crespo, M. R., Beebe, T. J., et al. (2015). Concordance between individual vs. area-level socioeconomic measures in an urban setting. J Health Care Poor Underserved, 26(4), 1157–1172.CrossRefPubMedGoogle Scholar
  22. Pampalon, R., Hamel, D., & Gamache, P. (2009). A comparison of individual and area-based socio-economic data for monitoring social inequalities in health. Health Reports / Statistics Canada, 20(4), 85–94.Google Scholar
  23. Pampalon, R., Hamel, D., & Gamache, P. (2010). Health inequalities in urban and rural Canada: comparing inequalities in survival according to an individual and area-based deprivation index. Health and Place, 16(2), 416–420.  https://doi.org/10.1016/j.healthplace.2009.11.012.CrossRefPubMedGoogle Scholar
  24. Potter, B. K., Speechley, K. N., Gutmanis, I. A., Campbell, M. K., Koval, J. J., & Manuel, D. A. (2005). Comparison of measures of socioeconomic status for adolescents in a Canadian national health survey. Chronic Dis Can., 26(2–3), 80–89.PubMedGoogle Scholar
  25. Public Health Agency of Canada. The chief public health officer’s report on the state of public health in Canada: addressing health inequalities. PHAC: Ottawa, ON; 2008.Google Scholar
  26. Raphael, D., Anstice, S., Raine, K., McGannon, K. R., Rizvi, S. K., & Yu, V. (2008). The social determinants of the incidence and management of type 2 diabetes mellitus: are we prepared to rethink our questions and redirect our research activities? Giornale Italiano di Diabetologia e Metabolismo, 28(3), 154–161.Google Scholar
  27. Robinette, J. W., Charles, S. T., Almeida, D. M., & Gruenewald, T. L. (2016). Neighborhood features and physiological risk: an examination of allostatic load. Health and Place., 41, 110–118.  https://doi.org/10.1016/j.healthplace.2016.08.003.CrossRefPubMedGoogle Scholar
  28. Shavers, V. L. (2007). Measurement of socioeconomic status in health disparities research. J Natl Med Assoc, 99(9), 1013–1023.PubMedPubMedCentralGoogle Scholar
  29. Sin, D. D., Svenson, L. W., & Man, S. F. P. (2001). Do area-based markers of poverty accurately measure personal poverty? Canadian Journal of Public Health., 92(3), 184–187.PubMedGoogle Scholar
  30. Southern, D. A., McLaren, L., Hawe, P., Knudtson, M. L., & Ghali, W. A. (2005). Individual-level and neighborhood-level income measures: agreement and association with outcomes in a cardiac disease cohort. Med Care, 43(11), 1116–1122.  https://doi.org/10.1097/01.mlr.0000182517.57235.6d.CrossRefPubMedGoogle Scholar
  31. Statistica Canada (2006). Income and earnings reference guide, 2006 census. Catalogue no. 97–563-GWE2006003. Available at: http://www12.statcan.gc.ca/census-recensement/2006/ref/rp-guides/income-revenu-eng.cfm. Accessed May 6, 2017.
  32. Statistics Canada. 2006 Census Dictionary. Available at: www.statcan.gc.ca. Updated 2008. Accessed January 2, 2016.
  33. Statistics Canada. (2011). Annual component, 2009–2010 derived variable (DV) specification. Otattawa, ON: Statistics Canada.Google Scholar
  34. Statistics Canada. Canadian Community Health Survey—Annual Component (CCHS). Available at: http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=3226. Updated (2016). Accessed November 30, 2016.
  35. Toronto Public Health. (2015). The unequal city 2015: income and health inequalities in Toronto. Toronto, ON: Toronto Public Health.Google Scholar
  36. Walker, A. E., & Becker, N. G. (2005). Health inequalities across socio-economic groups: comparing geographic-area-based and individual-based indicators. Public Health, 119(12), 1097–1104.  https://doi.org/10.1016/j.puhe.2005.02.008.CrossRefPubMedGoogle Scholar
  37. Wilkins R. Neighbourhood income quintiles derived from Canadian postal codes are apt to be misclassified in rural but not urban areas (working paper). Statistics Canada. Available at: https://www.researchgate.net/publication/301488517_Neighbourhood_income_quintiles_derived_from_Canadian_postal_codes_are_apt_to_be_misclassified_in_rural_but_not_urban_areas. Updated (2004). Accessed November 30, 2016.
  38. Wilkins, R., & Khan, S. (2011). PCCF+ version 5J* user’s guide. Ottawa, ON: Statistics Canada.Google Scholar
  39. Yip, A. M., Kephart, G., & Veugelers, P. J. (2002). Individual and neighbourhood determinants of health care utilization: implications for health policy and resource allocation. Canadian Journal of Public Health., 93(4), 303–307.PubMedGoogle Scholar

Copyright information

© The Canadian Public Health Association 2018

Authors and Affiliations

  • Erin Pichora
    • 1
  • Jane Y. Polsky
    • 1
    • 2
  • Christina Catley
    • 1
  • Nita Perumal
    • 1
  • Jing Jin
    • 1
  • Sara Allin
    • 1
  1. 1.Canadian Institute for Health Information (CIHI)OttawaCanada
  2. 2.Dalla Lana School of Public HealthUniversity of TorontoTorontoCanada

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