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Gauging Population Health: Measures Linking Mortality and Morbidity

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The Demography and Epidemiology of Human Health and Aging

Abstract

As countries progress through the more advanced stages of the epidemiologic transition, the traditional indicators of population health, based on mortality rates alone, are expected to change little. Therefore, the incidence, prevalence, duration, and disabling effects of morbid conditions are becoming increasingly important measures in the evaluation of population health. The most informative summary measures of population health, the type developed in this chapter, combine those for mortality and morbidity.

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Notes

  1. 1.

    For interpolation to derive single-year-of-age data, the following approximation is satisfactory: \({\mathrm{l}}_{\mathrm{x(hs)}} =.50{\mathrm{L}}_{\mathrm{x}-1(\mathrm{hs})} +.50{\mathrm{L}}_{\mathrm{x(hs)}}\). For grouped data, osculatory interpolation, such as was described in Chap. 4, can be used. Once single ages are derived by such interpolation, the formula shown here can be applied to convert Lx to lx.

  2. 2.

    Like tables of healthy life, tables of working life can also be constructed by the event-exposure method and by the multistate methods, to be discussed later. I do not consider here the calculation of the average remaining years in the labor force for those who are still in the labor force, only for the entire survivor population. This is another option for securing a measure of the effect of disability on average years in the labor force.

  3. 3.

    Another rough procedure for adjusting the stationary labor force in the life table involves augmenting the change in the stationary labor force from age to age by the estimated loss from withdrawals due to disability: (1) Obtain the differences between the stationary labor force at successive ages; (2) next, estimate the deaths at each age in the labor-force population by applying the observed death rates to the stationary labor force, (3) take the difference between the net changes from age to age in the stationary labor force in (1) and the deaths in (2); and (4) combine the results in (3) with the original labor-force stationary population.

  4. 4.

    One way of making an adjustment using this type of data is to secure from the most recent census or Current Population Survey, for each age-sex group, (1) the sum of persons not in the labor force with a work disability and (b) the labor force; (2) divide the result in (1) by the labor force; and (3) multiply the factor in (2) by the labor force participation ratio in the first of the two labor force life tables being prepared; and (4) use the adjusted ratios in (3) to construct the second labor force life table.

  5. 5.

    The adjustment in the total number of deaths and in the total number of new cases of breast cancer is the same and can be made in either function.

    If mortality rates can be determined separately for women who are free of breast cancer and those who are not free of it from two successive panel surveys, the adjustment for double jeopardy can be avoided. In such a case the functions obtained would be the deaths for women who have not incurred breast cancer, the number of new breast-cancer cases excluding any deaths, and the deaths of the new breast-cancer cases. The two main functions, adjusted deaths and new breast cancer cases, will then represent nonoverlapping numbers of persons to be used for reducing the function, female survivors free of breast cancer.

  6. 6.

    We may choose to take an indirect route to derive this measure by using the prevalence-ratio method of constructing the life table. We would apply the percentages of persons at each age who are not residents of nursing homes from a survey or census to the stationary population in a standard life table (Lx), to derive the person-years of non-residence in nursing homes at each age. The rest of the life table, including the function for the chances of ever entering a nursing home, can be derived by working backward to derive the prior functions for the number of deaths and the number of net admissions at each age. The net admissions to nursing homes and the deaths in the population excluding admitted persons are bound together in the age-to-age changes in the stationary population of nonresidents of nursing homes. The analyst has the task of unbinding these age-to age changes in the stationary population to extract the components. This is difficult because of the lack of information on the relative mortality of nursing-home residents and community-dwellers. Another problem is that this procedure yields data on all (net) entries into nursing homes, not only first entries.

  7. 7.

    An alternative route for carrying out the calculations of multistate tables may be employed. Transition probabilities can be derived directly from the survey data. To do this, first, an n by n + 1 contingency table giving health status at the earlier date and health status and deaths at the later date is set up. Age-specific transition probabilities (P x ) can be calculated directly from this table. For example, the probability of transferring from the healthy survivor population at year y to an unhealthy survivor population at year y + 1 between age x and age x + 1 is calculated as the proportion of such transfers out the total number of healthy survivors in year y. These transition probabilities can be converted into central age-specific transfer rates (M x ) by appropriate formulas. (See The Methods and Materials of Demography, 2004, p. 333). The age-specific transfer rates can be multiplied against the stationary populations to derive the transfers of each kind, including death, i.e., Dx = Mx  ∗ Lx.

  8. 8.

    The Global Burden of Diseaseand Injury Series (Murray and Lopez, editors, 1996) is a landmark publication on the world‘s health condition, produced by researchers from the Harvard School of Public Health and the World Health Organization and several dozen collaborators from around the world. It is a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 for the regions and countries of the world, with projections to 2020. The study provides an internally consistent and comparable set of estimates of current patterns of mortality and disability, with detailed information on the epidemiology of 240 conditions. The result of the research is the 10-volume, TheGlobal Burden of Disease and Injury Series published in 1996 with the support of the World Bank.

  9. 9.

    In essence, the weight is set in terms of the number of people with a given condition whose claim on a fixed healthcare budget is equal, in the judgment of a member of the advisory board, to that of 1,000 healthy people. For example, if the member judges that 1,000 healthy people have an equal claim on the fixed resources as 8,000 people with some severe disability, the weight assigned to that particular disability is equal to [1 − (1, 000 ÷ 8, 000)], or 0.875.

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Siegel, J.S. (2012). Gauging Population Health: Measures Linking Mortality and Morbidity. In: The Demography and Epidemiology of Human Health and Aging. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1315-4_8

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