The future of smoking-attributable mortality: the case of England & Wales, Denmark and the Netherlands

Projections of Lung Cancer Incidence by 2035 in 40 Countries Worldwide: Population-Based Study

BACKGROUND

The global burden of lung cancer (LC) is increasing. Quantitative projections of the future LC burden in different world regions could help optimize the allocation of resources and provide a benchmark for evaluating LC prevention and control interventions.

OBJECTIVE

We aimed to predict the future incidence of LC in 40 countries by 2035, with an emphasis on country- and sex-specific disparities.

METHODS

Data on LC incidence from 1978 to 2012 were extracted from 126 cancer registries of 40 countries in Cancer Incidence in Five Continents Volumes V-XI and used for the projection. Age-standardized incidence rates (ASRs) per 100,000 person-years and the number of incident cases were predicted through 2035, using the NORDPRED age-period-cohort model.

RESULTS

Global ASRs of the 40 studied countries were predicted to decrease by 23% (8.2/35.8) among males, from 35.8 per 100,000 person-years in 2010 to 27.6 in 2035, and increase by 2% (0.3/16.8) among females, from 16.8 in 2010 to 17.1 in 2035. The ASRs of LC among females are projected to continue increasing dramatically in most countries by 2035, with peaks after the 2020s in most European, Eastern Asian, and Oceanian countries, whereas the ASRs among males will continue to decline in almost all countries. The ASRs among females are predicted to almost reach those among males in Ireland, Norway, the United Kingdom, the Netherlands, Canada, the United States, and New Zealand in 2025 and in Slovenia in 2035 and even surpass those among males in Denmark in 2020 and in Brazil and Colombia in 2025. In 2035, the highest ASRs are projected to occur among males in Belarus (49.3) and among females in Denmark (36.8). The number of new cases in 40 countries is predicted to increase by 65.32% (858,000/1,314,000), from 1.31 million in 2010 to 2.17 million in 2035. China will have the largest number of new cases.

CONCLUSIONS

LC incidence is expected to continue to increase through 2035 in most countries, making LC a major public health challenge worldwide. The ongoing transition in the epidemiology of LC highlights the need for resource redistribution and improved LC control measures to reduce future LC burden worldwide.

Trends in smoking-attributable mortality in Spain: 1990-2018

BACKGROUND

This study sought to analyse the trend in smoking-attributable mortality (SAM) in Spain among the population aged ≥35 years across the period 1990-2018.

METHODS

SAM was estimated by applying a prevalence-independent method, which uses lung cancer (LC) mortality as a proxy of tobacco consumption. We sourced observed mortality from the National Institute of Statistics (Spain), LC mortality rates in smokers and never smokers from the Cancer Prevention Study I-II, and relative risks from 5 US cohorts. Estimates of annual SAM by cause of death, sex and age are shown, along with crude and annual standardised SAM rates. The trend in standardised all-cause and LC rates was analysed using a joinpoint regression model.

RESULTS

Tobacco caused 1 717 150 deaths in Spain in the period 1990-2018. Among men, cancers replaced cardiovascular diseases-diabetes mellitus (CVD-DM) as the leading group of tobacco-related cause of death in 1994. Among women, CVD-DM remained the leading cause of death throughout the period. Trend analysis of standardised SAM rates due to all causes and LC showed a decrease in men and an increase in women.

CONCLUSIONS

The tobacco epidemic in Spain across the period 1990-2018 has had an important impact on mortality and has evolved differently in both genders. SAM is expected to increase dramatically in women in the coming years. SAM data highlight the importance of including a gender perspective in SAM analyses, in designing more effective and comprehensive public health interventions and in developing gender-specific tobacco control policies to curb tobacco consumption.

The combined impact of smoking, obesity and alcohol on life-expectancy trends in Europe

BACKGROUND

Smoking, obesity and alcohol abuse greatly affect mortality and exhibit a distinct time dynamic, with their prevalence and associated mortality rates increasing and (eventually) declining over time. Their combined impact on secular trends in life expectancy is unknown but is relevant for understanding these trends. We therefore estimate the combined impact of smoking, obesity and alcohol on life-expectancy trends in Europe.

METHODS

We used estimated national age-specific smoking-, obesity- and alcohol-attributable mortality fractions for 30 European countries by sex, 1990-2014, which we aggregated multiplicatively to obtain lifestyle-attributable mortality. We estimated potential gains in life expectancy by eliminating lifestyle-attributable mortality and compared past trends in life expectancy at birth (e0) with and without lifestyle-attributable mortality. We examined all countries combined, by region and individually.

RESULTS

Among men, the combined impact of smoking, obesity and alcohol on e0 declined from 6.6 years in 1990 to 5.8 years in 2014, mainly due to declining smoking-attributable mortality. Among women, the combined impact increased from 1.9 to 2.3 years due to mortality increases in all three lifestyle-related factors. The observed increase in e0 over the 1990-2014 period was 5.0 years for men and 4.0 years for women. After excluding lifestyle-attributable mortality, this increase would have been 4.2-4.3 years for both men and women.

CONCLUSION

Without the combined impact of smoking, obesity and alcohol, the increase over time in life expectancy at birth would have been smaller among men but larger among women, resulting in a stable increase in e0, parallel for men and women.

Future Alcohol-Attributable Mortality in France Using a Novel Generalizable Age-Period-Cohort Projection Methodology

AIM

To forecast age- and sex-specific alcohol-attributable mortality in France for the period 2015-2050 using a novel generalizable methodology that includes different scenarios regarding period and cohort change.

METHODS

For the French national population aged 25-90 years (1979-2014), we estimated alcohol-attributable mortality by mortality from the main causes of death wholly attributable to alcohol, plus liver cirrhosis mortality. We modelled sex-specific alcohol-attributable mortality by adjusting for age, period and birth cohort. We forecasted the model parameters to obtain future age- and sex-specific alcohol-attributable mortality up until 2050 using a conventional baseline, scenario I (favourable period change) and scenario II (unfavourable cohort change).

RESULTS

Alcohol-attributable mortality is clearly declining in France, with the decline decelerating from 1992 onwards. In 2014, the age-standardized alcohol-attributable mortality rates, in deaths per 100,000, were 34.7 among men and 9.9 among women. In 2050, the estimated rates are between 10.5 (prediction interval: 7.6-14.4; scenario I) and 17.6 (13.1-23.7; scenario II) among men, and between 1.1 (0.7-1.7; scenario I) and 1.8 (1.2-2.9; scenario II) among women; which implies declines of 58% for men and 84% for women (baseline).

CONCLUSION

Alcohol-attributable mortality in France is expected to further decline in the coming decades, accompanied by age pattern changes. However, France's levels are not expected to reach the current lower levels in Italy and Spain for 15 years or more. Our results point to the value of implementing preventive policy measures that discourage alcohol consumption among people of all ages, but especially among adolescents.

Accounting for Smoking in Forecasting Mortality and Life Expectancy

Smoking is one of the main risk factors that has affected human mortality and life expectancy over the past century. Smoking accounts for a large part of the nonlinearities in the growth of life expectancy and of the geographic and sex differences in mortality. As Bongaarts (2006) and Janssen (2018) suggested, accounting for smoking could improve the quality of mortality forecasts due to the predictable nature of the smoking epidemic. We propose a new Bayesian hierarchical model to forecast life expectancy at birth for both sexes and for 69 countries with good data on smoking-related mortality. The main idea is to convert the forecast of the non-smoking life expectancy at birth (i.e., life expectancy at birth removing the smoking effect) into life expectancy forecast through the use of the age-specific smoking attributable fraction (ASSAF). We introduce a new age-cohort model for the ASSAF and a Bayesian hierarchical model for non-smoking life expectancy at birth. The forecast performance of the proposed method is evaluated by out-of-sample validation compared with four other commonly used methods for life expectancy forecasting. Improvements in forecast accuracy and model calibration based on the new method are observed.

The Role of Smoking in Country Differences in Life Expectancy Across Europe, 1985-2014

INTRODUCTION

Smoking contributes substantially to mortality levels and trends. Its role in country differences in mortality has, however, hardly been quantified. The current study formally assesses the-so far unknown-changing contribution of smoking to country differences in life expectancy at birth (e0) across Europe.

METHODS

Using all-cause mortality data and indirectly estimated smoking-attributable mortality rates by age and sex for 30 European countries from 1985 to 2014, the differences in e0 between each individual European country and the weighted average were decomposed into a smoking- and a nonsmoking-related part.

RESULTS

In 2014, e0 ranged from 70.8 years in Russia to 83.1 years in Switzerland. Men exhibited larger country differences than women (variance of 21.9 and 7.0 years, respectively). Country differences in e0 increased up to 2005 and declined thereafter. Among men, the average contribution of smoking to the country differences in e0 was highest around 1990 (47%) and declined to 35% in 2014. Among women, the average relative contribution of smoking declined from 1991 to 2011, and smoking resulted in smaller differences with the average e0 level in the majority of European countries. For both sexes combined, the contribution of smoking to country differences in e0 was higher than 20% throughout the period.

CONCLUSIONS

Smoking contributed substantially to the country differences in e0 in Europe, their increases up to 1991, and their decreases since 2005, especially among men. Policies that discourage smoking can help to reduce inequalities in mortality levels across Europe in the long run.

IMPLICATIONS

Smoking contributes substantially to country differences in life expectancy at birth (e0) in Europe, particularly among men, for whom the contribution was highest around 1990 (47%) and declined to 35% in 2014. In line with the anticipated progression of the smoking epidemic, the differences between European countries in e0 due to smoking are expected to further decline among men, but to increase among women. The role of smoking in mortality convergence since 2005 illustrates that smoking policies can help to reduce inequalities in life expectancy levels across Europe, particularly when they target smoking in countries with low e0.

Smoking epidemic in Europe in the 21st century

OBJECTIVE

To estimate smoking-attributable mortality in the long-term future in 29 European countries using a novel data-driven forecasting approach that integrates the wave pattern of the smoking epidemic and the cohort dimension.

METHODS

We estimated and forecasted age-specific and age-standardised smoking-attributable mortality fractions (SAMF) and 95% projection intervals for 29 European countries by sex, 1950-2100, using age-period-cohort modelling with a generalised logit link function. We projected the (decelerating) period increases (women) by a quadratic curve to obtain future declines, and extrapolated the past period decline (men). In addition, we extrapolated the recent cohort trend.

RESULTS

SAMF among men are projected to decline from, on average, 25% in 2014 (11% (Sweden)-41% (Hungary)) to 11% in 2040 (range: 6.3%-15.4%), 7% in 2065 (range: 5.9%-9.4%) and 6% in 2100. SAMF among women in 21 non-Eastern European countries, currently at an average of 16%, are projected to reach peak levels in 2013 (Northern Europe), 2019 (Western Europe), 2027 (Greece, Italy) and 2022 (Central Europe), with maximum levels of, on average, 17% (8% (Greece)-28% (Denmark)), and to decline to 10% in 2040 (range: 4%-20%), 5% in 2065 (range: 3.5%-7.6%) and 4% in 2100. For women, a short-term shift in the peak of the inverse U-shaped age pattern to higher ages is projected, and crossovers between the age-specific trends.

CONCLUSION

Our novel forecasting method enabled realistic estimates of the mortality imprint of the smoking epidemic in Europe up to 2100. The high peak values in smoking-attributable mortality projected for women warrant attention.

Similarities and Differences Between Sexes and Countries in the Mortality Imprint of the Smoking Epidemic in 34 Low-Mortality Countries, 1950-2014

INTRODUCTION

The smoking epidemic greatly affected mortality levels and trends, especially among men in low-mortality countries. The objective of this article was to examine similarities and differences between sexes and low-mortality countries in the mortality imprint of the smoking epidemic. This will provide important additions to the smoking epidemic model, but also improve our understanding of the differential impact of the smoking epidemic, and provide insights into its future impact.

METHODS

Using lung-cancer mortality data for 30 European and four North American or Australasian countries, smoking-attributable mortality fractions (SAMF) by sex, age (35-99), and year (1950-2014) were indirectly estimated. The timing and level of the peak in SAMF35-99, estimated using weighting and smoothing, were compared.

RESULTS

Among men in all countries except Bulgaria, a clear wave pattern was observed, with SAMF35-99 peaking, on average, at 33.4% in 1986. Eastern European men experienced the highest (40%) and Swedish men the lowest (16%) peak. Among women, SAMF35-99 peaked, on average, at 18.1% in 2007 in the North American/Australasian countries and five Northwestern European countries, and increased, on average, to 7.5% in 2014 in the remaining countries (4% in Southern and Eastern Europe). The average sex difference in the peak is at least 25.6 years in its timing and at most 22.9 percentage points in its level.

CONCLUSIONS

Although the progression of smoking-attributable mortality in low-mortality countries was similar, there are important unexpected sex and country differences in the maximum mortality impact of the smoking epidemic driven by cross-country differences in economic, political, and emancipatory progress.

IMPLICATIONS

The formal, systematic, and comprehensive analysis of similarities and differences between sexes and 34 low-mortality countries in long-term time trends (1950-2014) in smoking-attributable mortality provided important additions to the Global Burden of Disease study and the descriptive smoking epidemic model (Lopez et al.). Despite a general increase followed by a decline, the timing of the maximum mortality impact differs more between sexes than previously anticipated, but less between regions. The maximum mortality impact among men differs considerably between countries. The observed substantial diversity warrants country-specific tobacco control interventions and increased attention to the current or expected higher smoking-attributable mortality shares among women compared to men.

ESTIMATING AND FORECASTING THE SMOKING-ATTRIBUTABLE MORTALITY FRACTION FOR BOTH GENDERS JOINTLY IN OVER 60 COUNTRIES

Smoking is one of the leading preventable threats to human health and a major risk factor for lung cancer, upper aero-digestive cancer, and chronic obstructive pulmonary disease. Estimating and forecasting the smoking attributable fraction (SAF) of mortality can yield insights into smoking epidemics and also provide a basis for more accurate mortality and life expectancy projection. Peto et al. (1992) proposed a method to estimate the SAF using the lung cancer mortality rate as an indicator of exposure to smoking in the population of interest. Here we use the same method to estimate the all-age SAF (ASAF) for both genders for over 60 countries. We document a strong and cross-nationally consistent pattern of the evolution of the SAF over time. We use this as the basis for a new Bayesian hierarchical model to project future male and female ASAF from over 60 countries simultaneously. This gives forecasts as well as predictive distributions that can be used to find uncertainty intervals for any quantity of interest. We assess the model using out-of-sample predictive validation, and find that it provides good forecasts and well calibrated forecast intervals, comparing favorably with other methods.

Progression of the smoking epidemic in high-income regions and its effects on male-female survival differences: a cohort-by-age analysis of 17 countries

BACKGROUND

Of all lifestyle behaviours, smoking caused the most deaths in the last century. Because of the time lag between the act of smoking and dying from smoking, and because males generally take up smoking before females do, male and female smoking epidemiology often follows a typical double wave pattern dubbed the 'smoking epidemic'. How are male and female deaths from this epidemic differentially progressing in high-income regions on a cohort-by-age basis? How have they affected male-female survival differences?

METHODS

We used data for the period 1950-2015 from the WHO Mortality Database and the Human Mortality Database on three geographic regions that have progressed most into the smoking epidemic: high-income North America, high-income Europe and high-income Oceania. We examined changes in smoking-attributable mortality fractions as estimated by the Preston-Glei-Wilmoth method by age (ages 50-85) across birth cohorts 1870-1965. We used these to trace sex differences with and without smoking-attributable mortality in period life expectancy between ages 50 and 85.

RESULTS

In all three high-income regions, smoking explained up to 50% of sex differences in period life expectancy between ages 50 and 85 over the study period. These sex differences have declined since at least 1980, driven by smoking-attributable mortality, which tended to decline in males and increase in females overall. Thus, there was a convergence between sexes across recent cohorts. While smoking-attributable mortality was still increasing for older female cohorts, it was declining for females in the more recent cohorts in the US and Europe, as well as for males in all three regions.

CONCLUSIONS

The smoking epidemic contributed substantially to the male-female survival gap and to the recent narrowing of that gap in high-income North America, high-income Europe and high-income Oceania. The precipitous decline in smoking-attributable mortality in recent cohorts bodes somewhat hopeful. Yet, smoking-attributable mortality remains high, and therefore cause for concern.

Statistical projection methods for lung cancer incidence and mortality: a systematic review

OBJECTIVES

To identify and summarise all studies using statistical methods to project lung cancer incidence or mortality rates more than 5 years into the future.

STUDY TYPE

Systematic review.

METHODS

We performed a systematic literature search in multiple electronic databases to identify studies published from 1 January 1988 to 14 August 2018, which used statistical methods to project lung cancer incidence and/or mortality rates. Reference lists of relevant articles were checked for additional potentially relevant articles. We developed an organisational framework to classify methods into groups according to the type of data and the statistical models used. Included studies were critically appraised using prespecified criteria.

RESULTS

One hundred and one studies met the inclusion criteria; six studies used more than one statistical method. The number of studies reporting statistical projections for lung cancer increased substantially over time. Eighty-eight studies used projection methods, which did not incorporate data on smoking in the population, and 16 studies used a method which did incorporate data on smoking. Age-period-cohort models (44 studies) were the most commonly used methods, followed by other generalised linear models (35 studies). The majority of models were developed using observed rates for more than 10 years and used data that were considered to be good quality. A quarter of studies provided comparisons of fitted and observed rates. While validation by withholding the most recent observed data from the model and then comparing the projected and observed rates for the most recent period provides important information on the model's performance, only 12 studies reported doing this.

CONCLUSION

This systematic review provides an up-to-date summary of the statistical methods used in published lung cancer incidence or mortality projections. The assessment of the strengths of existing methods will help researchers to better apply and develop statistical methods for projecting lung cancer rates. Some of the common methods described in this review can be applied to the projection of rates for other cancer types or other non-infectious diseases.

Lung cancer mortality in Australia: Projected outcomes to 2040

OBJECTIVES

The aim was to develop and validate a statistical model which uses past trends for lung cancer mortality and historical and current data on tobacco consumption to project lung cancer mortality rates into the future for Australia.

METHODS

We used generalized linear models (GLMs) with Poisson distribution including either age, birth cohort or period, and/or various measures of population tobacco exposure (considering cross-sectional smoking prevalence, cigarettes smoked and tar exposure per capita). Sex-specific models were fitted to data for 1956-2015 and age-standardized lung cancer mortality rates were projected forward to 2040. Possible lags of 20-30 years between tobacco exposure and lung cancer mortality were examined. The best model was selected using analysis of deviance. To validate the selected model, we temporarily re-fitted it to data for 1956-1990 and compared the projected rates to 2015 with the observed rates for 1991-2015.

RESULTS

The best fitting model used information on age, birth cohort and tar exposure per capita; close concordance with the observed data was achieved in the validation. The forward projections for lung cancer mortality using this model indicate that male and female age-standardized rates will decline over the period 2011-2015 to 2036-2040 from 27.2 to 15.1 per 100,000, and 15.8 to 11.8 per 100,000, respectively. However, due to population growth and ageing the number of deaths will increase by 7.9% for males and 57.9% for females; from 41,040 (24,831 males, 16,209 females) in 2011-2015 to 52,403 (26,805 males, 25,598 females) in 2036-2040.

CONCLUSION

In the context of the mature tobacco epidemic with past peaks in tobacco consumption for both males and females, lung cancer mortality rates are expected to continually decline over the next 25 years. However, the number of lung cancer deaths will continue to be substantial, and to increase, in Australia's ageing population.

Probabilistic mortality forecasting with varying age-specific survival improvements

Many mortality forecasting approaches extrapolate past trends. Their predictions of the future development can be quite precise as long as turning points and/or age-shifts of mortality decline are not present. To account even for such mortality dynamics, we propose a model that combines recently developed ideas in a single framework. It (1) uses rates of mortality improvement to model the aging of mortality decline, and it (2) optionally combines the mortality trends of multiple countries to catch anticipated turning points. We use simulation-based Bayesian inference to estimate and run this model that also provides prediction intervals to quantify forecast uncertainty. Validating mortality forecasts for British and Danish women from 1991 to 2011 suggest that our model can forecast regular and irregular mortality developments and that it can perform at least as well as other widely accepted approaches like, for instance, the Lee-Carter model or the UN Bayesian approach. Moreover, prospective mortality forecasts from 2012 to 2050 suggest gradual increases for British and Danish life expectancy at birth.

The Adoption of Smoking and Its Effect on the Mortality Gender Gap in Netherlands: A Historical Perspective

We examine in depth the effect of differences in the smoking adoption patterns of men and women on the mortality gender gap in Netherlands, employing a historical perspective. Using an indirect estimation technique based on observed lung cancer mortality from 1931 to 2012, we estimated lifetime smoking prevalence and smoking-attributable mortality. We decomposed the sex difference in life expectancy at birth into smoking-related and nonsmoking-related overall and cause-specific mortality. The smoking epidemic in Netherlands, which started among men born around 1850 and among women from birth cohort 1900 onwards, contributed substantially to the increasing sex difference in life expectancy at birth from 1931 (1.3 years) to 1982 (6.7 years), the subsequent decline to 3.7 years in 2012, and the high excess mortality among Dutch men born between 1895 and 1910. Smoking-related cancer mortality contributed most to the increase in the sex difference, whereas smoking-related cardiovascular disease mortality was mainly responsible for the decline from 1983 onwards. Examining nonsmoking-related (cause-specific) mortality shed new light on the mortality gender gap and revealed the important role of smoking-related cancers, the continuation of excess mortality among women aged 40-50, and a smaller role of biological factors in the sex difference than was previously estimated.