Advertisement

Concepts and Basic Measures of Mortality

  • Jacob S. Siegel
Chapter

Abstract

Death statistics are a basic element in measuring progress toward improved health and increased longevity of a population. They are needed both for demographic studies and for public health administration. Death statistics are used in the analysis of the past and present demographic status of a population as well as its prospective growth; in serving the administrative and research needs of public health agencies in connection with the development, operation, and evaluation of public health programs; and in basic research and analysis of the health, survival, and longevity of a population or some group within it. Death statistics are needed to conduct analyses of past population changes as well as past changes in the health and longevity of the population. These analyses are required to make projections of mortality, population size, and other demographic characteristics, and to prepare, interpret, and evaluate projections of the health status of the population.

Keywords

Infant Death Death Certificate Standardize Mortality Ratio Crude Death Rate Standard Population 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References and Suggested Readings

  1. .
    Beard, R. E. (1971). Some aspects of theories of mortality, cause of death analysis, forecasting and stochastic processes. In W. Brass (Ed.), Biological aspects of demography (pp. 57–68). New York: Barnes and Noble.Google Scholar
  2. .
    Bongaarts, J. (2005). Long-range trends in adult mortality: Models and projection methods. Demography, 42(1), 23–49.CrossRefGoogle Scholar
  3. .
    Carey, J. R. (2002). The importance of teaching biodemography in the demography curriculum. Genus, 58(3–4), 189–200.Google Scholar
  4. .
    Carnes, B. A., Olshansky, S. J., & Grahn, D. (1996). Continuing the search for a law of mortality. Population and Development Review, 22(2), 231–264.CrossRefGoogle Scholar
  5. .
    Carnes, B. A., Holden, L. R., Olshansky, S. J., Witten, T. M., & Siegel, J. S. (2006). Mortality partitions and their relevance to research on senescence. Biogerontology, 7, 183–198.CrossRefGoogle Scholar
  6. .
    Galley, C., & Woods, R. (1999). On the distribution of deaths during the first year of life. Population 5, 1998. Population: An English Selection, 11, 35–60. Paris: INED.Google Scholar
  7. .
    Gompertz, B. (1825). On the nature of the function expressive of the law of human mortality. Philosophical Transactions of the Royal Society of London, 115, 513–593.CrossRefGoogle Scholar
  8. .
    Heligman, L., & Pollard, J. H. (1980). The age pattern of mortality. Journal of the Institute of Actuaries, 10, 49–80.CrossRefGoogle Scholar
  9. .
    Horiuchi, S., & Wilmoth, J. R. (1998). Deceleration in the age pattern of mortality at older ages. Demography, 35(4), 391–412.CrossRefGoogle Scholar
  10. .
    Makeham, W. M. (1865). On the law of mortality and the construction of annuity tables. Journal of the Institute of Actuaries, 8, 301–310.Google Scholar
  11. .
    Mode, C. J., & Busby, R. C. (1982) An eight parameter model of human mortality – The single decrement case. Bulletin of Mathematical Biology, 44, 647–659.Google Scholar
  12. .
    Olshansky, S. J., Carnes, B. A., & Grahn, B. (1998). Confronting the boundaries of human longevity. American Scientist, 86(1), 52–61.Google Scholar
  13. .
    Rogers, A., & Little, J. S. (1994). Parameterizing age patterns of demographic rates with the multiexponential model schedules. Mathematical Population Studies, 4, 175–195.CrossRefGoogle Scholar
  14. .
    Siegel, J. S., & Swanson, D. A. (Eds.). (2004). Methods and materials of demography (2nd ed.). San Diego, CA: Elsevier/Academic.Google Scholar
  15. .
    Suchindran, C. M. (2004). Model life tables and stable population tables. In J. S. Siegel & D. A. Swanson (Eds.), Methods and materials of demography (2nd ed., pp. 653–676). San Diego, CA: Elsevier/Academic.Google Scholar
  16. .
    Thatcher, A. R. (1999). The long-term pattern of adult mortality and the highest attained age. Journal of the Royal Statistical Society, 162(Pt. 1), 5–43.Google Scholar
  17. .
    Thatcher, A. R., Kannisto, V., & Vaupel, J. W. (1998). The force of mortality at ages 80 to 120. Odense. Denmark: Odense University Press.Google Scholar
  18. .
    Thiele, P. N. (1872). On a mathematical formula to express the rate of mortality throughout the whole of life. Journal of the Institute of Actuaries, 16, 213–239.Google Scholar
  19. .
    U.S. National Center for Health Statistics. (2008). Deaths: Final data for 2005. By H. C. Kung, D. L. Hoyert, J. Xu, &S. L. Murphy. National Vital Statistics Reports, 56(10).Google Scholar
  20. .
    Vaupel, J. W., Carey, J. R., Christensen, K., Johnson, T. C., et al. (1998). Biodemographic trajectories of longevity. Science, 280, 855–860.CrossRefGoogle Scholar
  21. .
    Coale, A. J. (1990). Defects in data on old-age mortality in the United States: New procedures for calculating mortality schedules and life tables at the highest ages. Asian Pacific Population Forum, 4(1), 1–31.Google Scholar
  22. .
    Coale, A. J., & Kisker, E. E. (1986). Mortality crossovers: Reality or bad data? Population Studies, 40, 389–401.CrossRefGoogle Scholar
  23. .
    Kestenbaum, B. (1992). A description of the extreme aged population based on improved Medicare enrollment data. Demography, 29, 565–580.CrossRefGoogle Scholar
  24. .
    Keyfitz, N., & Litman, G. (1979). Mortality in a heterogeneous population. Population Studies, 33, 333–334.Google Scholar
  25. .
    Manton, K. G., & Stallard, E. (1984, July 7–10). Heterogeneity and its effect on mortality measurement. In Proceedings, seminar on methodology and data collection in mortality studies, International Union for the Scientific Study of Population, Dakar, Senegal.Google Scholar
  26. .
    Manton, K. G., Poss, S. S., & Wing, S. (1979). The black-white crossover: Investigation from the perspective of the components of aging. Gerontologist, 19, 291–300.CrossRefGoogle Scholar
  27. .
    Nam, C. (1995). Another look at mortality crossovers. Social Biology, 42(1–2):133–142.Google Scholar
  28. .
    Thornton, R. G., & Nam, C. B. (1968). The lower mortality rates of nonwhites at the older ages: An enigma in demographic analysis. Research Reports in Social Science, 811(1), 1–8.Google Scholar
  29. .
    U.S. National Center for Health Statistics. (1998). Vital statistics of the United States, 1993: Mortality (Vol. A). Hyattsville, MD: U.S. National Center for Health Statistics.Google Scholar
  30. .
    U.S. National Center for Health Statistics. (2002). Vital Statistics of the United States: Mortality (Vol. II, Parts A and B, 1993). Hyattsville, MD: U.S. National Center for Health Statistics.Google Scholar
  31. .
    Vaupel, J. W., Manton, K. G., & Stallard, E. (1979). The impact of heterogeneity in individual frailty on the dynamics of mortality. Demography, 16, 439–454.CrossRefGoogle Scholar
  32. .
    Lynch, S. M., & Brown, J. S. (2001). Reconsidering mortality compression and deceleration: An alternative model of mortality rates. Demography, 38(1), 79–96.CrossRefGoogle Scholar
  33. .
    Myers, G. C., & Manton, K. G. (1984). Compression of mortality: Myth or reality? The Gerontologist, 24, 346–353.CrossRefGoogle Scholar
  34. .
    Nusselder, W. J., & Mackenbach, J. P. (1996). Rectangularization of the survival curve in the Netherlands, 1950–1992. Gerontologist, 36(6), 773–782.CrossRefGoogle Scholar
  35. .
    Rothenberg, R., Lentzner, H. R., & Parker, R. A. (1991). Population aging patterns: The expansion of mortality. Journal of Gerontology: Social Sciences, 46 (2), S66–S80.Google Scholar
  36. .
    Wilmoth, J. R., & Horiuchi, S. (1999). Rectangularization revisited: Variability of age at death within populations. Demography, 36(4), 475–497.CrossRefGoogle Scholar
  37. .
    Carnes, B. A., & Olshansky, S. J. (1997). A biologically motivated partitioning of mortality. Experimental Gerontology, 32(6), 615–631.CrossRefGoogle Scholar
  38. .
    Israel, R. A., Rosenberg, H. M., & Curtin, L. R. (1986). Analytical potential for multiple cause-of-death data. American Journal of Epidemiology, 124(2), 161–179.Google Scholar
  39. .
    Manzini, V. P., Revignas, M. G., & Brollo, A. (1995). Diagnoses of malignant tumor: Comparison between clinical and autopsy diagnoses. Human Pathology, 26, 280–283.CrossRefGoogle Scholar
  40. .
    Mosley, W. H., & Chen, L. (1984). An analytical framework for the study of child survival in developing countries. Population and Development Review, (A supplement to volume 10), 25–45.Google Scholar
  41. .
    Sarode, V. R., Datta, B. N., Banerjee, A. K., et al. (1993). Autopsy findings and clinical diagnoses: a review of 1000 cases. Human Pathology, 24, 194–198.CrossRefGoogle Scholar
  42. .
    Stallard, E (2002, January 17–18). Underlying and multiple cause mortality at advanced ages: United States, 1980–1998. In CD of proceedings of the society of actuaries, international symposium: living to 100 and beyond: Mortality at advanced ages, Lake Buena Vista, FL.Google Scholar
  43. .
    U.S. National Center for Health Statistics. (1982). Annotated bibliography of cause-of-death validation studies, 1958–80. By A. Gittlesohn & P. N. Royston. Vital and Health Statistics, 2(89).Google Scholar
  44. .
    U.S. National Center for Health Statistics. (1986). TRANSAX, the NCHS system for producing multiple cause-of-death statistics, 1968–78. By R. F. Chamblee & M. C. Evans. Vital and Health Statistics, 1(20).Google Scholar
  45. .
    U.S. National Center for Health Statistics. (1995). Vital statistics of the United States: Mortality (Vol. II, Parts A and B). Hyattsville, MD: U.S. National Center for Health Statistics, 1991.Google Scholar
  46. .
    U.S. National Center for Health Statistics. (2001a). The autopsy, medicine, and mortality statistics. By D. L. Hoyert. Vital and Health Statistics, 3(32).Google Scholar
  47. .
    U.S. National Center for Health Statistics. (2001b). Comparability of cause of death between ICD-9 and ICD-10: Preliminary estimates. By R. A. Anderson, A. M. Miniño, D. Hoyert, & H. Rosenberg. National Vital Statistics Reports, 49(2).Google Scholar
  48. .
    U.S. National Center for Health Statistics. (2003). Public-use data set documentation. Mortality data set for ICD-10, 2000. Hyattsville, MD: National Center for Health Statistics.Google Scholar
  49. .
    U.S. National Center for Health Statistics. (2007). Deaths: Leading causes for 2004. By M. P. Heron. National Vital Statistics Reports, 56(5).Google Scholar
  50. .
    U.S. National Center for Health Statistics. (2007). Autopsy patterns in 2003. By D. L. Hoyert, H. C. Kung, & J. Xu. Vital and Health Statistics, 20(32).Google Scholar
  51. .
    Veress, B., & Alafuzoff, I. (1994). A retrospective analysis of clinical diagnoses and autopsy findings in 3,042 cases during two different time periods. Human Pathology, 25, 140–145.CrossRefGoogle Scholar
  52. .
    World Health Organization. (1977). Manual of the international statistical classification of diseases, injuries, and causes of death, based on the recommendations of the ninth revision conference, 1975. Geneva, Switzerland: World Health Organization.Google Scholar
  53. .
    Das Gupta, P. (1993). Standardization and decomposition of rates: A user’s manual. Current Population Reports, P23–186. Special Studies. Washington, DC: U.S. Bureau of the Census.Google Scholar
  54. .
    Horiuchi, H., Wilmoth, J., & Pletcher, S. D. (2008). A decomposition method based on a model of continuous change. Demography, 45(4), 785–802.CrossRefGoogle Scholar
  55. .
    Kitagawa, E. M. (1955). Components of a difference between two rates. Journal of the American Statistical Association, 50(272), 1168–1194.Google Scholar
  56. .
    Liao, T. F. (1989). A flexible approach for the decomposition of rate differences. Demography, 26(4), 717–726.CrossRefGoogle Scholar
  57. .
    Little, R. J. A., & Pullum, T. W. (1979). The general linear model and direct standardization: A comparison. Sociological Methods and Research, 7, 475–501.CrossRefGoogle Scholar
  58. .
    U.S. National Center for Health Statistics. (2008). Deaths: Final data for 2005. By H. C. Kung, D. L. Hoyert, J. Xu, & S. L. Murphy. National Vital Statistics Reports, 56(10).Google Scholar
  59. .
    Vaupel, J. W., & Canudas Romo, V. (2002). Decomposing demographic change into direct vs. compositional components. Demographic Research, 7, 2–14.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.J. Stuart Siegel Demographic ServicesNorth BethesdaUSA

Personalised recommendations