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Estimates of the Relative Risk of Mortality Based on the Ontario Longitudinal Study of Aging

Published online by Cambridge University Press:  29 November 2010

John P. Hirdes  and
William F. Forbes
John P. Hirdes
Affiliation:
University of Waterloo
William F. Forbes
Affiliation:
University of Waterloo
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Abstract

Data from the Ontario Longitudinal Study of Aging were analyzed to examine the associations of the independent variables income, income change, education, smoking and perceived health with the dependent variable mortality during a ten year follow-up beginning in 1969. The analyses investigate the associations of the independent variables with deaths, with other causes of attrition and with all causes of attrition. The results indicate that smoking is the strongest predictor of mortality, and income is the strongest socioeconomic predictor. The analyses also show that perceived health measured prior to the mortality follow-up masks the association between the independent variables and mortality. Since the exclusion of the perceived health variable did not appreciably reduce the fit of the models, it was omitted from further analyses. The distributions of mortality for the various independent variables differed appreciably between models using deaths and all causes, but the bivariate and multivariate associations between variables were relatively unaffected by the alternative methods of operationalizing the dependent variable.

Résumé

Des données extraites du Ontario Longitudinal Study of Aging sont analysées dans le but d'examiner les liens entre une série de variables indépendantes, dont le revenu, le changement du revenu, le niveau d'étude, la cigarette, la perception de la santé, et une variable dépendante, celle de la mortalité, ceci pendant dix ans, à partir de 1969. L'analyse cherche à établir le lien qui pourrait exister entre les variables indépendantes et la mortalité, d'autres causes attribuées à l'attrition et toutes les causes d'attrition. Selon les résultats, la cigarette est le meilleur déterminant lorsqu'il s'agit de prédire la mort, et le revenu en est le meilleur déterminant socio-économique. Les analyses indiquent également que la perception de la santé telle que mesurée avant le suivi sur la mortalité masque le lien entre les variables indépendantes et la mortalité. Puisque l'exclusion de cette variable ne changeait sensiblement pas la valeur relative des modèles, elle a désormais été exclue des analyses. Les distributions de la mortalité au niveau des diverses variables indépendantes varient considérablement selon les modèles lorsque la mort et toutes les causes entrent en ligne de compte, mais les liens bivariés et multivariés entre les variables demeurent relativement non affectés par les différentes méthodes visant à opérationnaliser la variable dépendante.

Keywords

MortalityRelative RiskLongitudinal StudiesAging
Type
Articles
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 8 , Issue 3 , Fall/automne 1989 , pp. 222 - 237
Copyright
Copyright © Canadian Association on Gerontology 1989

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References

REFERENCES

Billette, A. and Hill, G.B. (1978). “Risque Relatif de Mortalité Masculine et les Classes Sociales au Canada 1974”. L'Union Médicale du Canada 107 (6): 583–590.Google Scholar
Branch, L.G. and Jette, A.M. (1984). “Personal Health Practices and Mortality among the Elderly,” American Journal of Public Health 74 (10): 1126–1129.CrossRefGoogle ScholarPubMed
Canada (1981). The Health of Canadians: Report of the Canada Health Survey Ottawa: Ministry of National Health and Welfare.Google Scholar
Cleary, P.D. and Angel, R. (1984). “The Analysis of Relationships Involving Dichotomous Dependent Variables”. Journal of Health and Social Behavior 25 (3): 334–348.CrossRefGoogle ScholarPubMed
Forbes, W.F., McPherson, B.D. and Shadbolt-Forbes, M. (1989). “The Validation of Longitudinal Studies: The Case of the Ontario Longitudinal Study of Aging (LSA)”. Canadian Journal on Aging 8 (1): 51–67.CrossRefGoogle Scholar
Harell, F.E. (1983). “The Logist Procedure”, SUGI Supplemental Library User's Guide 1983 Edition Cary, NC: SAS Institute, 181–202.Google Scholar
Hirdes, J.P., Brown, K.S., Vigoda, D.S., Forbes, W.F. and Crawford, L. (1986). “The Association Between Self-Reported Income and Perceived Health Based on the Ontario Longitudinal Study of Aging”. Canadian Journal on Aging 5 (3): 189–204.CrossRefGoogle Scholar
Hirdes, J.P., Brown, K.S., Vigoda, D.S., Crawford, L. and Forbes, W.F. (1987). “Health Effects of Cigarette Smoking: Data from the Ontario Longitudinal Study on Aging”. Canadian Journal of Public Health 78 (1): 13–17.Google ScholarPubMed
Hirdes, J.P., and Forbes, W.F. (Forthcoming). “The Maintenance of Good Health on the Basis of Social and Lifestyle Variables in Longitudinal Models”. Journal of Gerontology.Google Scholar
Kaplan, G.A. and Camacho, T. (1983). “Perceived Health and Mortality: A Nine Year Follow-up of the Human Population Laboratory Cohort” American Journal of Epidemiology 117: 292–304.CrossRefGoogle ScholarPubMed
Kaplan, G.A., Seeman, T.E., Cohen, R.D., Knudsen, L.P. and Guralnik, J. (1987). “Mortality Among die Elderly in the Alameda County Study: Behavioural and Demographic Risk Factors”. American Journal of Public Health 77 (3): 307–312.CrossRefGoogle Scholar
Kitagawa, E.M., and Hauser, P.M. (1973). Differential Mortality in the United States: A Study in Socioeconomic Epidemiology. Cambridge: Harvard University Press.CrossRefGoogle Scholar
Kleinbaum, D.G., Kupper, L.L. and Morgenstein, H.C. (1982). “Modelling: Theoretical Considerations”, in Epidemiological Research, 421–428. Toronto: Wadsworth Inc.Google Scholar
Marshall, J.R. (1987). “The Reliability and Validity of Dietary Data as Used in Epidemiology”. Cancer Surveys 6 (4): 673–683.Google ScholarPubMed
Moser, K.A., Pugh, H.S. and Goldblatt, P.O. (1988). “Inequalities in Women's health. Looking at Mortality Differentials Using an Alternative Approach”. British Medical Journal 296(6631): 1221–1224.CrossRefGoogle ScholarPubMed
Mossey, J.M. and Shapiro, E. (1982). “Self-Rated Health: A Predictor of Mortality Among the Elderly”. American Journal of Public Health 72 (8): 800–808.CrossRefGoogle Scholar
Pocock, S.J., Shaper, A.G., Cook, D.G., Phillips, A.N. and Walker, M. (1987). “Social Class Differences in Ischaemic Heart Disease in British Men”. The Lancet, 8552: 197–201.CrossRefGoogle Scholar
Palmore, E.B. (1982). “Predictors of the Longevity Difference: A 25-Year Follow-up”. The Gerontologist 22 (6): 513–518.CrossRefGoogle ScholarPubMed
Seidell, J.C., Bakx, K.C., Deurenberg, P., Burema, J., Hautvast, J.G.A.J. and Huygen, F.J.A. (1986). “The Relation Between Overweight and Subjective Health According to Age, Social Class, Slimming Behavior and Smoking Habits in Dutch Adults”. American Journal of Public Health 76 (12): 1410–1415.CrossRefGoogle ScholarPubMed
Thompson, M.E. and Forbes, W.F. (In Press). “The Problem of Low Response Rates in Surveys of the Elderly”. The Mathematical Scientist.Google Scholar
Townsend, P. and Davidson, N. (eds.) (1980). Inequalities in Health: The Black Report. Suffolk: The Chaucer Press.Google Scholar
Ugnat, A. and Mark, E. (1987). “Life Expectancy by Sex, Age and Income Level”. Chronic Diseases in Canada S (I): 12–13.Google Scholar
U.S. Department of Health, Education and Welfare (1979). Smoking and Health. A Report of the Surgeon General.Google Scholar
Wigle, D.T. and Mao, Y. (1980). Mortality by Income Level in Urban Canada. Ottawa: Ministry of National Health and Welfare, Health Protection Branch.Google Scholar
Wilkins, R. and Adams, O.B. (1983). “Health Expectancy in Canada, late 1970's: Demographic, Regional, and Social Dimensions”. American Journal of Public Health 73 (9): 1073–1080.CrossRefGoogle Scholar
World Health Organization (1980). “The Inequality of Death: Assessing Socioeconomic Influences on Mortality”. WHO Chronicle 34 (1): 9–15.Google Scholar