Descriptive Epidemiological Measures

  • Denise M. Oleske
Chapter

Summary

This chapter has presented common descriptive measures, namely rates and ratios, useful in planning and evaluating health care services, policies, and programs. Rates are used to identify and prioritize health problems within a population,assess variability of the utilization of health care resources, evaluate progress toward achieving health goals, and propose hypotheses regarding the etiology and control of health problems. Rates also are used to assess health, disease, and exposure patterns and their variability in populations. Ratios aid in evaluating the degree of the relationship between exposure and outcome.Descriptive mea- sures, in general, are useful in identifying the components of the health care system that could be modified to improve the health status of populations. The specific type of epidemiological measure used depends on the objective of the assessment, the nature of the health problem being evaluated, and the type of data available.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, R. N., and Rosenberg, H. M., 1998, Age standardization of death rates: Implementation of the year 2000 standard, National Vital Statistics Reports, Vol. 47,No. 3, National Center for Health Statistics, Hyattsville, MD.Google Scholar
  2. Carriere, K. C., and Roos, L. L., 1994, Comparing standardized rates of events, Am. J. Epidemiol. 140:472–482.PubMedGoogle Scholar
  3. Cole, P., and MacMahon, B., 1971, Attributable risk percent in case-control studies, Br. J. Prevention and Soc. Med. 25:242–244.Google Scholar
  4. Dean, A. G., Arner, T. G., Sangam, S., Sunki, G. G., Friedman, R., Lantiga, M., Zubieta, J. C., Sullivan, K. M., and Smith, D. C., 2000, Epi Info™ 2000, a database and statistics program for public health professionals for use on Window 95, 98, NT, and 2000 computers, Centers for Disease Control and Prevention, Atlanta, GA.Google Scholar
  5. Derby, C. A., Lapane, K. L., Feldman, H. A., and Carleton, R. A., 2000, Sex-specific trends in validated coronary heart disease rates in southeastern New England, 1980–1991, Am. J. Epidemiol. 151:417–429.PubMedGoogle Scholar
  6. Fleiss, J. L., 1981, Statistical Methods for Rates and Proportions, 2nd ed., John Wiley & Sons, New York.Google Scholar
  7. Gorelick, P. B., 1994, Stroke prevention: An opportunity for efficient utilization of health care resources during the coming decade, Stroke 25:220–224.PubMedGoogle Scholar
  8. Kahn, H. A., and Sempos, C. T., 1989, Statistical Methods in Epidemiology, Oxford University Press, New York.Google Scholar
  9. Kramarow, E., Lentzner, H., Rooks, R., Weeks, J., and Saydah, S., 1999, Health and Aging Chartbook: Health United States, 1999, National Center for Health Statistics, Hyattsville, MD.Google Scholar
  10. Lauderdale, D. S., Furner, S. E., Miles, T. P., and Goldberg, J., 1993, Epidemiologic uses of Medicare data. Epidemiol. Rev. 15:319–327.PubMedGoogle Scholar
  11. Los Angeles County Department of Health Services and the UCLA Center for Health Policy Research, 2000, The Burden of Disease in Los Angeles County, County of Los Angeles, CA.Google Scholar
  12. Murray, C. J. L., and Lopez, A. D. (eds.), 1996, The Global Burden of Disease: A Comprehensive Assessment of Mortality and Disability from Diseases, Injuries, and Risk Factors in 1990 and Projected to 2020, Harvard University Press, Cambridge, MA.Google Scholar
  13. Myers, A. H., Robinson, E. G., Van Natta, M. L., Michelson, D., Collins, K., and Baker, S. P., 1991, Hip fractures among the elderly: Factors associated with in-hospital mortality, Am. J. Epidemiol. 134:1128–1137.PubMedGoogle Scholar
  14. National Center for Health Statistics, 1999, Health United States, 1999 with Health and Aging Chartbook, Hyattsville, MD.Google Scholar
  15. Oleske, D. M., Branca, M. L., Schmidt, J. B., Ferguson, R., and Linn, E. S., 1998, A comparison of capitated and fee-for-service Medicaid reimbursement methods on pregnancy outcomes, HSR: Health Services Res. 33:55–73.Google Scholar
  16. Ries, L. A. G., Kosary, C. L., Hankey, B. F., Miller, B. A., Cleff, L., and Edwards, B. K. (eds.), 1999, SEER Cancer Statistics Review 1973–1996, National Cancer Institute. Bethesda, MD.Google Scholar
  17. Sesso, H. D., Paffenbarger, R. S., and Lee, I., 2000, Comparison of national death index and world wide web death searches, Am. J. Epidemiol. 152:107–111PubMedCrossRefGoogle Scholar
  18. Sorlie, P. D., Thom, T. J., Manolio, T., Rosenberg, H. M., Anderson, R. N., and Burke, G. L., 1999, Age-adjusted death rates: Consequences of the year 2000 standard, Ann. Epidemiol. 9:93–100.PubMedGoogle Scholar
  19. Walter, S. D., 1978, Calculation of attributable risks from epidemiological data, Int. J. Epidemiol. 7:75–182.Google Scholar
  20. Wilson, P. W. F., and Evans, J. C., 1993, Coronary artery disease prediction, Am. J. Hypertens. 6:309S–312S.PubMedGoogle Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Denise M. Oleske
    • 1
  1. 1.Departments of Health Systems Management and Preventive MedicineRush UniversityChicago

Personalised recommendations