Abstract
Background
The purposes of this study were to determine (i) the extent to which small-area estimates of self-rated health are dependent upon the choice of areal unit and measure of socio-economic (SES) status, and (ii) the extent to which place effects on self-rated health are dependent upon the choice of areal unit and measure of SES.
Methods
The data were obtained from a subset of respondents in the Canadian Community Health Survey 2.1 (2003) aged 18 to 74 residing in the Vancouver Census Metropolitan Area. General health status was estimated using an item assessing respondents’ self-rated health. Small-area data were obtained from the Statistics Canada 2001 Census at two spatial levels: larger Census Tract (CT) (average population 2,500-8,000) and smaller Dissemination Area (DA) (average population 400-700). SES quintiles were constructed using median family income and two indices. Hierarchical non-linear modelling was used to test for place effects.
Results
A gradient was found of increasing prevalence of “fair or poor” self-rated health by decreasing SES quintile at both the DA and CT level. With age category, sex, family income and education controlled for, hierarchical analysis showed that compared with living in a high SES CT or DA the odds of reporting fair or poor self-rated health increased for respondents living in the lowest quintile CT or DA.
Interpretation
Aggregation using DAs or CTs produces only small differences in estimates of fair or poor self-rated health by quintiles of SES. Gradients are somewhat stronger for DAs. Place effects are somewhat stronger for deprivation indices than the measure of median income.
MeSH terms: Factors, socioeconomic, small-area analysis, health, inequalities, urban spatial distribution
Résumé
Contexte
Cette étude visait à déterminer i) la mesure dans laquelle, à l’échelle d’un petit secteur, les estimations de l’état de santé dépendent du choix de l’unité spatiale et des variables du statut socioéconomique (SSE), et ii) la mesure dans laquelle l’influence du lieu sur l’état de santé dépend aussi de ces choix.
Méthode
Nos données proviennent d’un sous-ensemble de répondants de l’Enquête sur la santé dans les collectivités canadiennes 2.1 (2003) âgés de 18 à 74 ans et habitant la région métropolitaine de recensement de Vancouver. Nous avons estimé leur état de santé général à l’aide d’un élément de l’enquête relatif à l’autoévaluation de la santé. Les données par petit secteur sont tirées du Recensement 2001 de Statistique Canada à deux échelles spatiales: le secteur de recensement (SR) (2 500 à 8 000 habitants en moyenne) et l’aire de diffusion (AD) (400 à 700 habitants en moyenne). Les quintiles de SSE ont été élaborés d’après le revenu familial médian et deux indices de pauvreté. L’effet du lieu a été calculé par modélisation non linéaire hiérarchique.
Résultats
On observe un gradient de prévalence inverse entre l’état de santé évalué « moyen ou mauvais » et le quintile de SSE, tant à l’échelle des AD qu’à celle des SR. En rajustant les données selon l’âge, le sexe, le revenu familial et l’instruction, la modélisation hiérarchique a montré que la probabilité d’évaluer son état de santé comme étant mauvais ou moyen augmentait chez les répondants vivant dans un SR ou une AD du quintile inférieur, comparée aux réponses des répondants des SR ou des AD des quintiles de statut socioéconomique plus élevé.
Interprétation
Les regroupements par AD ou par SR ne produisent que de faibles écarts dans les estimations de l’état de santé selon le quintile de SSE. Le gradient est un peu plus prononcé pour les aires de diffusion. L’influence du lieu est un peu plus forte avec les indices de pauvreté qu’avec la mesure du revenu médian.
Footnotes
Acknowledgements: This project was supported by a grant from the Canadian Institute for Health Information’s Canadian Population Health Initiative. We would like to thank the staff at the British Columbia Inter-university Research Data Centre for their technical assistance and Urban Structures, Public Policy and Population Health project manager Darrin Grund.
This analysis was based on the Statistics Canada master file CCHS (Cycle 2.1), which contains anonymized data collected in 2003. All computations were prepared by the authors and conducted at the British Columbia Inter-university Research Data Centre, University of British Columbia, Vancouver, British Columbia, Canada. The responsibility for the use and interpretation of these data is solely that of the authors. The opinions expressed in this paper are those of the authors and do not represent the views of Statistics Canada.
References
- 1.Macintyre S, Ellaway A. Neighborhoods and health: an overview. In: Kawachi I, Berkman L, editors. Neighborhoods and Health. 2003. p. 26. [Google Scholar]
- 2.Wilkins R, Berthelot J-M, Ng E. Trends in mortality by neighbourhood income in urban Canada from 1971 to 1996. Health Rep. 2002;13(suppl):45–72. doi: 10.1503/cmaj.1031528. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Ross NA, Tremblay S, Graham K. Neighbourhood influences on health in Montreal, Canada. Soc Sci Med. 2004;59(7):1485–94. doi: 10.1016/j.socscimed.2004.01.016. [DOI] [PubMed] [Google Scholar]
- 4.Mamdani MM, Tu K, Austin PC, Alter DA. Influence of socioeconomic status on drug selection for the elderly in Canada. Ann Pharmacother. 2002;36(5):804–8. doi: 10.1345/aph.1A044. [DOI] [PubMed] [Google Scholar]
- 5.Soubhi H, Raina P, Kohen D. Neighborhood, family, and child predictors of childhood injury in Canada. Am J Health Behavior. 2004;28(5):397–409. doi: 10.5993/ajhb.28.5.2. [DOI] [PubMed] [Google Scholar]
- 6.Boyle MH, Lipman EL. Do places matter? Socioeconomic disadvantage and behavioral problems of children in Canada. J Consult Clin Psychol. 2002;70(2):378–89. doi: 10.1037//0022-006x.70.2.378. [DOI] [PubMed] [Google Scholar]
- 7.Oliver L, Hayes MV. Neighbourhood socio-economic status and the prevalence of overweight Canadian children and youth. Can J Public Health. 2005;96(6):415–20. doi: 10.1007/BF03405180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Roos LL, Magoon J, Gupta S, et al. Socioeconomic determinants of mortality in two Canadian provinces: multilevel modelling and neighborhood context. Soc Sci Med. 2004;59(7):1435–47. doi: 10.1016/j.socscimed.2004.01.024. [DOI] [PubMed] [Google Scholar]
- 9.Wakefield J, Elliot P. Issues in the statistical analysis of small area health data. Stat Med. 1999;18:2377–99. doi: 10.1002/(sici)1097-0258(19990915/30)18:17/18<2377::aid-sim263>3.0.co;2-g. [DOI] [PubMed] [Google Scholar]
- 10.Pickett KE, Pearl M. Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J Epidemiol Community Health. 2001;55(2):111–22. doi: 10.1136/jech.55.2.111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Macintyre S, Ellaway A, Cummins S. Place effects on health: How can we conceptualise, operationalise and measure them? Soc Sci Med. 2002;55(1):125–39. doi: 10.1016/s0277-9536(01)00214-3. [DOI] [PubMed] [Google Scholar]
- 12.Openshaw S. The Modifiable Areal Unit Problem. England: Geobooks; 1983. [Google Scholar]
- 13.Geddes A, Flowerdew R. The effect of the modifiable areal unit problem in modelling the distribution of limiting long-term illness in Northern England. In: Boyle P, Curtis S, Graham E, Moore E, editors. The Geography of Health Inequalities in the Developed World: Views from Britain and North America. Aldershot, England: Ashgate Publishing Limited; 2004. pp. 267–92. [Google Scholar]
- 14.Reijneveld SA, de Verheij RA, Bakker DH. The impact of area deprivation on differences in health: Does the choice of the geographical classification matter? J Epidemiol Community Health. 2000;54:306–13. doi: 10.1136/jech.54.4.306. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Boyle MH, Willms JD. Place effects for areas defined by administrative boundaries. Am J Epidemiol. 1999;149(6):577–85. doi: 10.1093/oxfordjournals.aje.a009855. [DOI] [PubMed] [Google Scholar]
- 16.Martikainen P, Kauppinen TM, Valkonen T. Effects of the characteristics of neighbourhoods and the characteristics of people on cause specific mortality: a register based follow up study of 252 000 men. J Epidemiol Community Health. 2003;57(3):210–17. doi: 10.1136/jech.57.3.210. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Gordon D. Area-based deprivation measures—a U.K. Perspective. In: Kawachi I, Berkman LF, editors. Neighbourhoods and Health. New York: Oxford University Press; 2003. [Google Scholar]
- 18.Chron Dis Can. 2000.
- 19.Krieger N, Williams D, Moss N. Measuring social class in US public health research: concepts, methodologies and guidelines. Annu Rev Public Health. 1997;18:341–78. doi: 10.1146/annurev.publhealth.18.1.341. [DOI] [PubMed] [Google Scholar]
- 20.Kohen DE, Brooks-Gunn J, Leventhal T, Hertzman C. Neighborhood income and physical and social disorder in Canada: associations with young children’s competencies. Child Dev. 2002;73(6):1844–60. doi: 10.1111/1467-8624.t01-1-00510. [DOI] [PubMed] [Google Scholar]
- 21.Ng E, Wilkins R, Fung MFK, Berthelot JM. Cervical cancer mortality by neighbourhood income in urban Canada from 1971 to 1996. CMAJ. 2004;170(5):1545–49. doi: 10.1503/cmaj.1031528. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Hou F, Myles J. Neighbourhood inequality, neighbourhood affluence and population health. Soc Sci Med. 2005;60(7):1557–69. doi: 10.1016/j.socscimed.2004.08.033. [DOI] [PubMed] [Google Scholar]
- 23.Jarman B. Identification of underprivileged areas. BMJ. 1983;286:1705–9. doi: 10.1136/bmj.286.6379.1705. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Carstairs V. Multiple deprivation and health state. Community Med. 1981;3:4–13. [PubMed] [Google Scholar]
- 25.Townsend P, Phillimore P, Beattie A. Health and Deprivation. London: Croom Helm; 1988. [DOI] [PubMed] [Google Scholar]
- 26.Salmond C, Crampton P, Sutton F. NZDep91: a New Zealand index of deprivation. Aust N Z J Public Health. 1998;22(7):835–37. doi: 10.1111/j.1467-842x.1998.tb01505.x. [DOI] [PubMed] [Google Scholar]
- 27.Krieger N, J T Chen, P D Waterman, et al. Choosing area based socioeconomic measures to monitor social inequalities in low birth weight and childhood lead poisoning: The Public Health Disparities Geocoding Project (US). J Epidemiol Community Health 2003;57:186–99. [DOI] [PMC free article] [PubMed]
- 28.Carstairs V. Deprivation indices—their interpretation and use in relation to health. J Epidemiol Community Health. 1995;49(Suppl2):s3–s8. doi: 10.1136/jech.49.suppl_2.s3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Frohlich KL, Mustard C. A regional comparison of socioeconomic and health indices in a Canadian province. Soc Sci Med. 1996;42(9):1273–81. doi: 10.1016/0277-9536(95)00220-0. [DOI] [PubMed] [Google Scholar]
- 30.Blakely TA, Kawachi I. What is the difference between controlling for mean versus median income in analyses of income inequality? J Epidemiol Community Health. 2001;55(5):352–53. doi: 10.1136/jech.55.5.352. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Morgan MZ, Treasure ET. Comparison of four composite deprivation indices and two census variables in predicting dental caries in 12-year-old children in Wales. Community Dent Health. 2001;18(2):87–93. [PubMed] [Google Scholar]
- 32.Frohlich N, Mustard C. Socio-Economic Characteristics. Manitoba: Manitoba Centre for Health Policy and Evaluation, Department of Community Health Services, Faculty of Medicine, University of Manitoba; 1994. [Google Scholar]
- 33.Statistics Canada. Canadian Community Health Survey 2.1 (2003) Public Use Microdata Documentation. Ottawa, ON: Health Statistics Division; 2005. [Google Scholar]
- 34.Statistics Canada. 2001 Census Dictionary. Ottawa: Ministry of Industry, 2003;382.
- 35.Raudenbush S, Bryk A. Hierarchical Linear Models: Applications and Data Analysis Methods. Thousand Oaks, CA: Sage Publications; 2002. [Google Scholar]
- 36.Snijders TAB, Bosker RJ. Multilevel Analysis: an Introduction to Basic and Advanced Multilevel Modeling. Thousand Oaks, CA: Sage; 1999. [Google Scholar]