International Differences in Mortality at Older Ages Dimensions and Sources (2010) / Chapter Skim
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4 Contribution of Smoking to International Differences in Life Expectancy--Samuel H. Preston, Dana A. Glei, and John R. Wilmoth
4 Contribution of Smoking to International Differences in Life Expectancy--Samuel H. Preston, Dana A. Glei, and John R. Wilmoth
Pages 105-131
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From page 105... ...
. The most persuasive data identifying the mortality risks associated with smoking have been drawn from prospective cohort studies that compare the death rates of current smokers and former smokers with the death rates of those who never smoked regularly.
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From page 106... ...
Rather than applying them to the distribution of the population by smoking status, they instead used observed death rates from lung cancer as an indicator of the population's cumulative smoking exposure, which may be a more reliable index of the cumulative damage from smoking than directly measured smoking behavior based on self-report. Having selected lung cancer death rates as the indicator of the cumulative damage from smoking, Peto et al.
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From page 107... ...
We then estimate the impact of removing these deaths from a population's mortality profile on life expectancy at age 50 and on international variation therein. METHODS Modeling Strategy2 The model that we use for estimating the impact of smoking on mortality is based on the assumption that lung cancer mortality is a good proxy 2The model was introduced by Preston, Glei, and Wilmoth (2010)
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From page 108... ...
. The assumption that smoking is the overwhelming factor accounting for variation in lung cancer mortality is further justified by estimates that, among men ages 30 and older in industrialized countries in 2000, 91-92 percent of lung cancer deaths are attributable to smoking; for women, the corresponding percentages are 70-72 percent (Ezzati and Lopez, 2003)
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From page 109... ...
represents ML interacted with the age dummies. Estimating the Attributable Fraction To estimate the fraction of deaths attributable to smoking, we assume that in the absence of smoking, lung cancer rates (by sex and 5-year age group)
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are less than half the nonsmoker rates observed in the CPS-II. To the extent that we overestimate lung cancer death rates for nonsmokers, we will underestimate the fraction of deaths attributable to smoking and vice versa.
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, we investigated the validity of this approach by applying it to specific causes of death in addition to the combination category, "all causes other than lung cancer." We observe the expected relationships for both men and women: lung cancer mortality is powerfully related to mortality from respiratory diseases across populations, strongly related to smoking-related cancers, positively but more weakly related to other cancers, and unrelated (or even slightly negatively related) to mortality from external causes.
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Estimating the Effects of Smoking on e50 To estimate the impact of removing smoking-attributable deaths on life expectancy at age 50 (e50) , we used period life table estimates from the Human Mortality Database (Human Mortality Database, 2009)
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From page 113... ...
RESULTS Table 4-1 presents the estimated age- and sex-specific regression coefficients depicting the relationship between lung cancer death rates and mortality from other causes for 2003. As noted earlier, we estimate the coefficient for ages 85+ as the mean of coefficients for ages 70-74, 75-79, and 80-84.
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From page 114... ...
France, Portugal, and Spain are exceptions where the imprint of smoking remains small for women; thus, more than a "Mediterranean diet" may be involved in the favorable mortality conditions among women in Spain and France TABLE 4-2 Estimated Smoking-Attributable Fraction Among Deaths at Ages 50 and Older in 1955, 1980, 2003, by Sex and Country Men Women Country 1955 1980 2003 1955 1980 2003 Australia 0.07 0.22 0.17 0.00 0.04 0.10 Austria 0.15 0.21 0.17 0.01 0.02 0.05 0.27a 0.05a Belgium 0.09 0.30 0.00 0.01 Canada 0.07 0.22 0.24 0.01 0.06 0.19 Denmark 0.07 0.22 0.20 0.01 0.06 0.16 Finland 0.18 0.28 0.17 0.01 0.02 0.04 France 0.05 0.17 0.19 0.00 0.00 0.02 Hungary 0.07 0.22 0.30 0.01 0.05 0.13 Iceland 0.03 0.06 0.16 0.00 0.11 0.18 Ireland 0.04 0.17 0.19 0.02 0.07 0.14 Italy 0.04 0.20 0.23 0.00 0.01 0.04 Japan 0.01 0.11 0.20 0.00 0.03 0.09 Netherlands 0.10 0.32 0.26 0.00 0.01 0.09 New Zealand 0.08 0.21 0.17 0.00 0.06 0.12 Norway 0.02 0.09 0.16 0.00 0.01 0.07 Portugal 0.02 0.07 0.12 0.00 0.00 0.01 Spain 0.04 0.14 0.22 0.00 0.00 0.00 Sweden 0.03 0.10 0.09 0.00 0.02 0.06 Switzerland 0.09 0.19 0.16 0.00 0.01 0.04 United Kingdom 0.16 0.30 0.20 0.02 0.09 0.15 United States 0.08 0.23 0.22 0.01 0.08 0.20 aEstimates based on data from 2004 for Belgium. SOURCES: Calculations by authors based on data in the Human Mortality Database (accessed November 2009)
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From page 115... ...
Our high estimate for Japanese women is primarily attributable to very high lung cancer mortality above age 80, a phenomenon that seems likely to have an epidemiological source other than smoking (although passive smoke from coresidence with men and with a younger generation is a conceivable factor) .5 Table 4-3 presents a comparison of the smoking-attributable fraction estimated by our model with the Peto-Lopez estimates for 2000, the latest year for which the Peto-Lopez method has been widely applied to data from developed countries (Peto et al., 2006)
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cEstimates for Belgium are based on data for 1999. SOURCES: Model estimates are based on calculations by authors using data in the Human Mortality Database (accessed November 6, 2009)
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SOURCES: Calculations by authors based on data in the Human Mortality Database (accessed November 2009) and the World Health Organization Mortality Database (accessed December 2009)
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, it is noteworthy TABLE 4-5 Effect of Removal of Smoking-Attributable Deaths on Ranking of e50 in 2003 Men Women Rank Before Rank After Rank Before Rank After Country Removal Removal Removal Removal Australia 2 4 3 3 Austria 14 16 14 16 Belgiuma 13 8 10 13 Canada 6 3 7 2 Denmark 19 18 20 15 Finland 18 19 13 17 France 11 10 2 6 Hungary 21 21 21 21 Iceland 1 2 9 4 Ireland 17 17 19 19 Italy 8 5 6 8 Japan 3 1 1 1 Netherlands 16 13 15 18 New Zealand 7 7 12 7 Norway 9 11 11 12 Portugal 20 20 16 20 Spain 10 9 5 10 Sweden 5 14 8 11 Switzerland 4 6 4 5 United Kingdom 12 15 18 14 United States 15 12 17 9 aEstimates for Belgium based on 2004 data. SOURCES: Calculations by authors based on data in the Human Mortality Database (accessed November 2009)
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From page 119... ...
to their histories of light smoking: when smoking deaths are excluded for all countries, they drop below the median in terms of e50. It is sometimes remarked that Japan is an anomaly because people in Japan smoke heavily yet the country enjoys an excellent ranking in life expectancy comparisons (Stellman et al., 2001)
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SOURCES: Calculations by authors based on data in the Human Mortality Database (accessed November 2009) and the World Health Organization Mortality Database (accessed December 2009)
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The earlier impact of smoking on male mortality and the catch-up phase for women has produced a striking pattern of sex mortality differentials. Figure 4-2 shows the observed trend in the difference between female and male life expectancy at age 50.
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SOURCE: Calculations by authors based on data in the Human Mortality Database (accessed November 2009) and the World Health Organization Mortality Fig4-1.eps Database (accessed December 2009)
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and the World Health Organization Mortality Database (accessed December 2009)
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Human Mortality Database.
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. The international comparability of cancer mortality data.
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. Methods Protocol for the Human Mortality Database.
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Thus, any departure of lung cancer mortality in the population from that of nonsmokers is assumed to be attributable to smoking. θ is used as a measure of the mortality damage caused by the N prevalence, duration, and intensity of smoking.
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From page 128... ...
Thus, within the framework of generalized linear models (McCullagh and Nelder, 1989) , we assume a negative binomial probability distribution of observed death counts in order to estimate the following model of ln MO (or, technically, the log of its expected value)
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We estimate what MO would N have been in the absence of smoking by substituting λL , the assumed lung cancer death rate among nonsmokers, in place of ML. We then divide the difference between these two expressions by the model's prediction of MO.
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and the World Health Organization Mortality Database (accessed December 2009)
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From page 131... ...
CONTRIBUTION OF SMOKING TO INTERNATIONAL DIFFERENCES Women Lung Cancer Other Causes All Causes % of All % of All % of All N Deaths N Deaths N Deaths 1,742 2.9 4,524 7.6 6,266 10.5 590 1.5 1,549 3.9 2,138 5.3 5,702 5.5 13,974 13.4 19,676 18.9 1,186 4.4 3,155 11.6 4,341 16.0 291 1.2 791 3.3 1,082 4.5 2,047 0.8 3,305 1.3 5,352 2.1 1,671 2.7 6,383 10.3 8,054 13.0 49 5.5 106 12.1 155 17.6 459 3.4 1,477 11.1 1,936 14.5 3,314 1.2 9,580 3.3 12,894 4.5 8,705 2.0 31,475 7.1 40,180 9.0 1,856 2.7 4,318 6.2 6,173 8.9 456 3.5 1,118 8.6 1,574 12.2 499 2.4 1,015 4.8 1,514 7.2 108 0.2 200 0.4 308 0.6 298 0.2 415 0.2 713 0.4 888 1.9 2,075 4.5 2,963 6.4 459 1.5 886 2.8 1,345 4.3 10,817 3.5 37,062 12.0 47,879 15.5 55,331 4.8 169,840 14.8 225,171 19.7
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