Abstract
STUDY OBJECTIVE—Simple measures of inequalities in health are proposed to facilitate the work of health policy makers and to build on the understanding of health differences between populations. In addition, it is aimed to make these measures applicable for comparisons of small populations and subgroups. METHODS—Inequalities in health or health deficiencies were quantified as the difference between the life expectancy of the subgroup of interest and that of the national population. Health deficiencies were divided into disease specific components by partial application of cause eliminated life table methods. To manage small numbers and to depict time trends, locally weighted regression smoothing was applied. Confidence intervals were constructed through Monte Carlo simulations. APPLICATIONS AND COMPARISONS—The proposed approaches were applied to the health situation in Cape Breton County, Nova Scotia, Canada, and disclosed the significance of different diseases and distinct patterns between communities. The proposed measures were also compared with the traditionally used standardised mortality rates and ratios. Here, the proposed measures appeared beneficial in that they are easier to comprehend and that they provide time trends and more robust estimates. CONCLUSIONS—The above advantages make the proposed approaches beneficial to health policy makers and epidemiologists. The approaches may also be incorporated in economic evaluations as well as in more sophisticated public health models. Keywords: epidemiological methods; health status indicators; mortality; chronic diseases; cancer
Full Text
The Full Text of this article is available as a PDF (141.1 KB).
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- Gardner J. W., Sanborn J. S. Years of potential life lost (YPLL)--what does it measure? Epidemiology. 1990 Jul;1(4):322–329. doi: 10.1097/00001648-199007000-00012. [DOI] [PubMed] [Google Scholar]
- Gunning-Schepers L. J. Models: instruments for evidence based policy. J Epidemiol Community Health. 1999 May;53(5):263–263. doi: 10.1136/jech.53.5.263. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Lee W. C. Quantifying the future impact of disease on society: life table-based measures of potential life lost. Am J Public Health. 1997 Sep;87(9):1456–1460. doi: 10.2105/ajph.87.9.1456. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Linn S., Sheps S. Disability and the years of potential productivity lost: modifying the years of potential life lost and the investment-production-consumer model by disability level. Epidemiology. 1993 Sep;4(5):449–454. [PubMed] [Google Scholar]
- Mackenbach J. P., Kunst A. E., Lautenbach H., Oei Y. B., Bijlsma F. Gains in life expectancy after elimination of major causes of death: revised estimates taking into account the effect of competing causes. J Epidemiol Community Health. 1999 Jan;53(1):32–37. doi: 10.1136/jech.53.1.32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mao Y., Wilkins K., Fortier L., Semenciw R., Urrutia M., Davies J., Wigle D. A telephone survey to measure risk factor prevalence in communities across Canada. Can J Public Health. 1990 Jul-Aug;81(4):312–316. [PubMed] [Google Scholar]
- McMichael A. J. Prisoners of the proximate: loosening the constraints on epidemiology in an age of change. Am J Epidemiol. 1999 May 15;149(10):887–897. doi: 10.1093/oxfordjournals.aje.a009732. [DOI] [PubMed] [Google Scholar]
- Pearce N. Traditional epidemiology, modern epidemiology, and public health. Am J Public Health. 1996 May;86(5):678–683. doi: 10.2105/ajph.86.5.678. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sasieni P. D., Adams J. Standardized lifetime risk. Am J Epidemiol. 1999 May 1;149(9):869–875. doi: 10.1093/oxfordjournals.aje.a009903. [DOI] [PubMed] [Google Scholar]
- Susser M. Does risk factor epidemiology put epidemiology at risk? Peering into the future. J Epidemiol Community Health. 1998 Oct;52(10):608–611. doi: 10.1136/jech.52.10.608. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Veugelers P. J., Cornelisse P. G., Craib K. J., Marion S. A., Hogg R. S., Strathdee S. A., Montaner J. S., O'Shaughnessy M. V., Schechter M. T. Models of survival in HIV infection and their use in the quantification of treatment benefits. Am J Epidemiol. 1998 Sep 1;148(5):487–496. doi: 10.1093/oxfordjournals.aje.a009674. [DOI] [PubMed] [Google Scholar]
- Veugelers P. J., Guernsey J. R. Health deficiencies in Cape Breton County, Nova Scotia, Canada, 1950-1995. Epidemiology. 1999 Sep;10(5):495–499. [PubMed] [Google Scholar]
- Veugelers P. J., Guernsey J. R. Sensitivity analysis of selective migration in ecologic comparisons of health. Epidemiology. 1999 Nov;10(6):784–785. doi: 10.1097/00001648-199911000-00025. [DOI] [PubMed] [Google Scholar]
- Veugelers P. J., Strathdee S. A., Moss A. R., Page K. A., Tindall B., Schechter M. T., Coutinho R. A., van Griensven G. J. Is the human immunodeficiency virus-related Kaposi's sarcoma epidemic coming to an end? Insights from the Tricontinental Seroconverter Study. Epidemiology. 1995 Jul;6(4):382–386. doi: 10.1097/00001648-199507000-00009. [DOI] [PubMed] [Google Scholar]
- Wray N. R., Alexander F. E., Muirhead C. R., Pukkala E., Schmidtmann I., Stiller C. A comparison of some simple methods to identify geographical areas with excess incidence of a rare disease such as childhood leukaemia. Stat Med. 1999 Jun 30;18(12):1501–1516. doi: 10.1002/(sici)1097-0258(19990630)18:12<1501::aid-sim135>3.0.co;2-e. [DOI] [PubMed] [Google Scholar]
