Role of smoking in regional variation in mortality in <scp>P</scp>oland

Muszyńska, Magdalena; Fihel, Agnieszka; Janssen, Fanny

doi:10.1111/add.12672

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…Janssen et al (2013) used this version to calculate age-specific SAF to partition mortality into smoking and non-smoking attributable parts, and projected them separately. Muszyńska et al (2014) and Stoeldraijer et al (2015) used the same method to cal-29 culate an age-standardized SAF, whose purposes are to compare the role of smoking in different regions of Poland, and to estimate and compare smoking attributable fraction of mortality among England & Wales, Denmark and the Netherlands, respectively. While agestandardization is used mainly to compare SAF among different populations, ASAF provides the all-cause SAF with all age-groups aggregated and is the main quantity reported in the iterature, e.g., Peto et al (1992Peto et al ( , 1994Peto et al ( , 2006; Preston et al (2009).…”

Section: Comparison Between Saf Estimation Methodsmentioning

confidence: 99%

Estimating and forecasting the smoking-attributable mortality fraction for both genders jointly in over 60 countries

Raftery

2020

Ann. Appl. Stat.

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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.

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Section: Comparison Between Saf Estimation Methodsmentioning

confidence: 99%

Estimating and forecasting the smoking-attributable mortality fraction for both genders jointly in over 60 countries

Raftery

2020

Ann. Appl. Stat.

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“…Smoking is among the leading determinants of international differences in mortality,1–3 the gender gap in mortality4–6 and mortality differences between socioeconomic groups 7 8. However, only a few high-quality studies explore the impact of smoking on regional differences in mortality,9–11 partly because of the limited availability of regional long-term series of mortality by cause of death. This kind of data, specifically mortality from lung cancer, is widely used to estimate smoking-attributable mortality at the national level 2 12…”

Section: Introductionmentioning

confidence: 99%

Quantifying the contribution of smoking to regional mortality disparities in Germany: a cross-sectional study

2022

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ObjectivesSubstantial regional variation in smoking behaviour in Germany has been well documented. However, little is known about how these regional differences in smoking affect regional mortality disparities. We aim to assess the contribution of smoking to regional mortality differentials in Germany over the last four decades.DesignA cross-sectional study using official cause-specific mortality data by German Federal State aggregated into five macro-regions: East, North, South, West-I and West-II.ParticipantsThe entire population of Germany stratified by sex, age and region during 1980–2019.Main outcome measuresSmoking-attributable fraction estimated using the Preston-Glei-Wilmoth method; life expectancy at birth before and after the elimination of smoking-attributable deaths.ResultsIn all macro-regions, the burden of past smoking has been declining among men but growing rapidly among women. The hypothetical removal of smoking-attributable deaths would eliminate roughly half of the contemporary advantage in life expectancy of the vanguard region South over the other macro-regions, apart from the East. In the latter, smoking only explains around a quarter (0.5 years) of the 2-year difference in male life expectancy compared with the South observed in 2019. Among women, eliminating smoking-attributable deaths would put the East in a more disadvantageous position compared with the South as well as the other macro-regions.ConclusionWhile regional differences in smoking histories explain large parts of the regional disparities in male mortality, they are playing an increasingly important role for female mortality trends and differentials. Health policies aiming at reducing regional inequalities should account for regional differences in past smoking behaviour.

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Changes in regional variation in mortality over five decades – The contribution of age and socioeconomic population composition

Suulamo

Tarkiainen

Remes

et al. 2021

SSM - Population Health

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Role of smoking in regional variation in mortality in Poland

Abstract: Differences in past smoking behaviour may largely explain the regional differences in all-cause mortality existing in 2008-10 in Poland, and its trends since 1991-1993.

Cited by 4 publications

References 24 publications

Estimating and forecasting the smoking-attributable mortality fraction for both genders jointly in over 60 countries

Estimating and forecasting the smoking-attributable mortality fraction for both genders jointly in over 60 countries

Quantifying the contribution of smoking to regional mortality disparities in Germany: a cross-sectional study

Changes in regional variation in mortality over five decades – The contribution of age and socioeconomic population composition

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