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Social Indicators Research

, Volume 67, Issue 3, pp 315–332 | Cite as

Socio-economic Indexes in Surveys for Comparisons between Countries

  • J.M. Batista-Foguet
  • J. Fortiana
  • C. Currie
  • J.R. Villalbí
Article

Abstract

The study of socio-economic inequalities from across-national perspective has been hampered by the lack of adequate common indices of socio-economic status that can be used in a self-report survey instrument. This paper examines the construction and the properties of global social indexes in general, and of the Family Affluence Scale (henceforth FAS) in particular. The paper proposes a new strategy for making comparisons of the global index with stratified data, building a revised FAS based on Adapted Canonical Variate Analysis (henceforth ACVA). This alternative strategy for constructing a global index is available in standard software, and the new proposal for stratified data only requires a simple program, which is justified, explained and provided in the text. Data come from the 1998 Health Behaviour in School-Aged Children (HBSC), a WHO Cross-National Study using cluster sampling of schoolchildren from five countries: Denmark, Latvia, Portugal, Scotland and the USA. The results reveal that in every country we would have had a completely different evaluation of the three indicators of Family Affluence if we had used either linear or nonlinear approaches to compute the global indexes. Moreover, Family Affluence comparisons among countries shows that the relative contribution of the three indicators to the overall FAS, changes from country to country. We conclude that separate indicators of Family Affluence are not equally relevant in each country and, as a consequence, do not contribute equally to the global index. For cross-cultural studies, the strategy for constructing an index should be country specific. The methodological developments presented in the paper open up opportunities to study socio-economic patterning of health among young people in the developed world, since self completed surveys can now employ a common measure of family material wealth. The findings show that the RFAS (Revised FAS) is a useful index of socio-economic status for use in national and cross-national surveys of adolescent health and health behaviour. The new strategy for weighting observed indicators in the index gives it enhanced power to detect in equalities.

canonical variate analysis health-behaviour optimal scaling socio-economic indexes social inequalities summated rating scale 

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REFERENCES

  1. Batista-Foguet, J.M., G. Coenders and A. Artés: 2001, ‘Using structural equation models to evaluate the magnitude of measurement error in blood pressure’, Statistics in Medicine V20(15), pp. 2351–2368.Google Scholar
  2. Batista-Foguet, J.M., R. Mendoza, M. Pérez and R. Rius: 2000, ‘Life-styles of Spanish school-aged children: Their evolution over time. Use of Multiple Correspondence Analysis to determine overall trends over time in a sequential, cross-sectional’, in A. Ferligoj (ed.) Advances in Methodology, Data Analysis and Statistics, Metodološki zvezki (Ljubljana), pp. 173–210.Google Scholar
  3. Batista-Foguet, J.M., W.E. Saris and X. Tort-Martorell: 1990, ‘Design of experimental studies for measurement and evaluation of the determinants of job-satisfaction’, Social Indicators Research 22, pp. 49–67.CrossRefGoogle Scholar
  4. Bechger, T.M., G. van den Wittenboer, J.J. Hox and C. de Glopper: 1999, ‘The validity of comparative educational studies’, Educational Measurement: Issues and Practice 18, pp. 18–26.CrossRefGoogle Scholar
  5. Boelhouwer, J. and I. Stoop: 1998, ‘Measuring well-being in the Netherlands. The SCP index from 1974 to 1997’, Social Indicators Research 48, pp. 51–75.Google Scholar
  6. Boelhouwer, J.: 2002, ‘Quality of live and living conditions in the Netherlands’, Social Indicators Research 58, pp. 115–140.CrossRefGoogle Scholar
  7. Booysen, F.: 2002, ‘An overview and evaluation of composite indices of development’, Social Indicators Research 59(2), pp. 115–151.CrossRefGoogle Scholar
  8. Carstairs, V.: 1995, ‘Deprivation indices: their interpretation and use in relation to health’, Journal of Epidemiology and Community Health 49(suppl 2), pp. S3–8.Google Scholar
  9. Currie, C.: 2001, ‘Socio-economic circumstances among school-aged children in Europe and North America’, in K. Vleminckx and T.M. Smeeding (eds.), Child Well Being, Child Poverty and Child Policy in Modern Nations: What Do We Know? Bristol (The Policy Press), pp. 347–364.Google Scholar
  10. Currie, C., R.A. Elton, J. Todd and S. Platt: 1997, ‘Indicators of socio-economic status for adolescents: the WHO health behaviour in school-aged children survey’, Health Education Research 12(3), pp. 385–397.Google Scholar
  11. Currie, C., K. Hurrlemann, W. Settertobulte, R. Smith and J. Todd (eds.): 2000, ‘Health and health behaviour among young people: Health behaviour in school-aged children: A WHO Cross-National Study (HBSC) international report’. WHO Policy Series Health policy for children and adolescents Issue 1, WHO Copenhagen; available from http://www.HBSC.org., p. 132.Google Scholar
  12. Currie, C. and A. Klocke: 1998, ‘Rationale for social inequalities’, in C. Currie et al. (eds.), ‘Health behaviour in school-aged children: A WHO Cross-National Survey (HBSC): Research protocol for the 1997/98 survey. Edinburgh: Research unit in health and behavioural change, University of Edinburgh; available from http://www.HBSC.org., pp. 64–72.Google Scholar
  13. Flury, B.: 1988, Common Principal Components and Related Multivariate Methods. New York: J. Wiley & Sons.Google Scholar
  14. Fowlell, K.: 1995, ‘Single measures of deprivation’, Journal of Epidemiology and Community Health 49(Suppl 2), pp. 51–56.Google Scholar
  15. Gifi, A.: 1990, Nonlinear Multivariate Analysis. New York: J. Wiley & Sons.Google Scholar
  16. Greenacre, M.J.: 1993, Correspondence Analysis in Practice (Academic Press).Google Scholar
  17. Jolly, D.L., J.N. Moller and R.E. Volkmer: 1993, ‘The socio-economic context of child injury in Australia’, Journal of Paediatric Child Health 29, pp. 438–444.Google Scholar
  18. Krzanowski, W.J. and F.H.C. Marriott: 1994, Multivariate Analysis, Part I. Distributions, Ordination and Inference (Edward Arnold, London).Google Scholar
  19. Little, T.D., W.A. Cunningham and G. Shahar: 2002, ‘To parcel or not to parcel: Exploring the question, weighing the merits’, Structural Equation Modeling 9(2), pp. 151–173.CrossRefGoogle Scholar
  20. Morrison, M.A., G. Todd, G. Morrison, A. Pope and B.D. Zumbo: 1999, ‘An investigation of measures of modern and old-fashioned sexism’, Social Indicators Research 48, pp. 39–50.CrossRefGoogle Scholar
  21. Roos, E., E. Lahelma, M. Virtanen, R. Prattala and P. Pietinen: 1998, ‘Gender, socio-economic status and family status as determinants of food behaviour’, Social Science and Medicine 46(12), pp. 1519–1529.Google Scholar
  22. Samdal, O. (1998). The School Environment as a Risk or Resource for Students' Health-Related Behaviours and Subjective Well-being. PhD. Dissertation, RCHP, University of Bergen.Google Scholar
  23. Shen, S.M. and Y.L. Lai: 1998, ‘Optimally scaled quality-of-life indicators’, Social Indicators Research, pp. 225–254.Google Scholar
  24. Spector, P.E.: 1992, ‘Summated rating scale construction’, Quantitative applications to Social Sciences (Sage Pub), p. 70.Google Scholar
  25. Williams, J., C. Currie, P. Wright, R. Elton and T. Beattie: 1997, ‘Socio-economic status and adolescent injuries’, Social Science and Medicine 44, pp. 1881–1891.Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • J.M. Batista-Foguet
    • 1
  • J. Fortiana
    • 2
  • C. Currie
    • 3
  • J.R. Villalbí
    • 4
  1. 1.ESADE Business SchoolUniversitat Ramon LlullBarcelonaSpain
  2. 2.Department of Statistics, Facultat de MatemàtiquesUniversitat de BarcelonaSpain
  3. 3.Department of Community Health SciencesUniversity of EdinburghScotland
  4. 4.Institut Municipal de Salut Pública, Ajuntament de BarcelonaSpain

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