Including the Smoking Epidemic in Internationally Coherent Mortality Projections

Abstract

We present a new mortality projection methodology that distinguishes smoking- and non-smoking-related mortality and takes into account mortality trends of the opposite sex and in other countries. We evaluate to what extent future projections of life expectancy at birth (e 0) for the Netherlands up to 2040 are affected by the application of these components. All-cause mortality and non-smoking-related mortality for the years 1970–2006 are projected by the Lee-Carter and Li-Lee methodologies. Smoking-related mortality is projected according to assumptions on future smoking-attributable mortality. Projecting all-cause mortality in the Netherlands, using the Lee-Carter model, leads to high gains in e 0 (4.1 for males; 4.4 for females) and divergence between the sexes. Coherent projections, which include the mortality experience of the other 21 sex- and country-specific populations, result in much higher gains for males (6.4) and females (5.7), and convergence. The separate projection of smoking and non-smoking-related mortality produces a steady increase in e 0 for males (4.8) and a nonlinear trend for females, with lower gains in e 0 in the short run, resulting in temporary sex convergence. The latter effect is also found in coherent projections. Our methodology provides more robust projections, especially thanks to the distinction between smoking- and non-smoking-related mortality.

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Acknowledgments

We would like to thank Anouschka van der Meulen and Trudy Lisci from Statistics Netherlands for the provision of detailed data on all-cause mortality and population size.

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Correspondence to Fanny Janssen.

Appendix: Projection of Smoking-Related Mortality

Appendix: Projection of Smoking-Related Mortality

Future levels of the age- and sex-specific etiological fraction (EF) (i.e., the proportion of all deaths attributable to smoking) for the Netherlands (Fig. 3) were estimated by applying the general ideas from the descriptive model of the smoking epidemic (Lopez et al. 1994), by examining historical trends in etiological fractions by age and sex, and by studying recent trends in smoking prevalence.

The descriptive model of the smoking epidemic shows the common pattern of an increase and thereafter a decrease in smoking prevalence, followed by similar patterns in smoking-attributable mortality three to four decades later. For females, the increase in both smoking prevalence and smoking-attributable mortality started later than for males and is more modest. All countries follow more or less the same patterns, but with a different timing of onset, saturation, and so on (Lopez et al. 1994).

Females in Denmark and in England and Wales are among the few who already experienced a peak in smoking-attributable mortality. In these two countries, the smoking-attributable mortality trends by age for males show a clear cohort pattern up to the peak, followed by a period pattern after the peak. For females, the cohort pattern is much less evident. An important observation is that for each age group the time span between the maximum EF for males and the maximum EF for females is almost the same and approximately equals the number of years between males and females in reaching the maximum EF for all ages combined.

In the Netherlands, the maximum level of EF for all ages combined was reached for males in 1983, whereas the maximum has not yet been reached by females in any of the age groups. For females, we therefore need to estimate the year and level of the maximum EF, as well as the trend up to and after this maximum. For males, it is necessary to estimate only the future decline.

To estimate the year in which EF will reach its maximum among Dutch females, we applied an age-period-cohort Poisson regression model to lung cancer mortality data from 1950 to 2004 by five-year age groups and five-year periods. As an offset term, we used the log of the average population. By adding the average age of dying from lung cancer (68) to the cohort with the highest lung cancer mortality (1953), we obtained the year in which EF reaches its maximum for females: 2021. This year resembles adding a lag time of 35–41 years to the years 1980–1986, in which smoking prevalence reached its maximum level among Dutch females. The years in which EF will reach its maximum for females for the separate age groups were subsequently estimated by applying the difference in timing between males and females of the maximum EF for all ages combined (38) to the years in which the maximum EF was reached for males in the separate age groups. These years in which the EF reached its maximum for males were assessed by means of the smoothed trends, obtained by fitting fourth-degree polynomials.

For females, the trend in the age-specific EF up to the maximum was based on the age-specific growth rate observed over the past 10 years. A deceleration of the growth rate to 1 was applied.

The age-specific long-term decline after the maximum for both males and females was set equal to the trend in EF for all ages combined after the maximum for males (–1.5 %), which reflects the current trend in smoking prevalence for all ages combined (–1.7 % for males, and –1.3 % for females), as well as the similarity in the current decline in smoking prevalence in the Netherlands between both sexes and the different age groups.

Fig. 3
figure3

Smoking-attributable mortality fractions (EF) by age and sex, observed (smoothed) and projected, 1950–2040. The restriction that the proportion of the population exposed to smoking should be smaller or equal to 1 is responsible for the plateau for males aged 45–49 in 1954–1985

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Janssen, F., van Wissen, L.J.G. & Kunst, A.E. Including the Smoking Epidemic in Internationally Coherent Mortality Projections. Demography 50, 1341–1362 (2013). https://doi.org/10.1007/s13524-012-0185-x

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Keywords

  • Life expectancy
  • Projection
  • Smoking
  • Europe
  • Li-Lee methodology