190 research outputs found

    Risk factors and public health in Denmark:Summary report

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    Contribution of smoking and alcohol consumption to income differences in life expectancy : evidence using Danish, Finnish, Norwegian and Swedish register data

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    Background Despite being comparatively egalitarian welfare states, the Nordic countries have not been successful in reducing health inequalities. Previous studies have suggested that smoking and alcohol contribute to this pattern. Few studies have focused on variations in alcohol-related and smoking-related mortality within the Nordic countries. We assess the contribution of smoking and alcohol to differences in life expectancy between countries and between income quintiles within countries. Methods We collected data from registers in Denmark, Finland, Norway and Sweden comprising men and women aged 25–79 years during 1995–2007. Estimations of alcohol-related mortality were based on underlying and contributory causes of death on individual death certificates, and smoking-related mortality was based on an indirect method that used lung cancer mortality as an indicator for the population-level impact of smoking on mortality. Results About 40%–70% of the between-country differences in life expectancy in the Nordic countries can be attributed to smoking and alcohol. Alcohol-related and smoking-related mortality also made substantial contributions to income differences in life expectancy within countries. The magnitude of the contributions were about 30% in Norway, Sweden and among Finnish women to around 50% among Finnish men and in Denmark. Conclusions Smoking and alcohol consumption make substantial contributions to both between-country differences in mortality among the Nordic countries and within-country differences in mortality by income. The size of these contributions vary by country and sex.Peer reviewe

    Population Dynamics and Air Pollution: The Impact of Demographics on Health Impact Assessment of Air Pollution

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    Objective. To explore how three different assumptions on demographics affect the health impact of Danish emitted air pollution in Denmark from 2005 to 2030, with health impact modeled from 2005 to 2050. Methods. Modeled air pollution from Danish sources was used as exposure in a newly developed health impact assessment model, which models four major diseases and mortality causes in addition to all-cause mortality. The modeling was at the municipal level, which divides the approximately 5.5 M residents in Denmark into 99 municipalities. Three sets of demographic assumptions were used: (1) a static year 2005 population, (2) morbidity and mortality fixed at the year 2005 level, or (3) an expected development. Results. The health impact of air pollution was estimated at 672,000, 290,000, and 280,000 lost life years depending on demographic assumptions and the corresponding social costs at 430.4 M€, 317.5 M€, and 261.6 M€ through the modeled years 2005–2050. Conclusion. The modeled health impact of air pollution differed widely with the demographic assumptions, and thus demographics and assumptions on demographics played a key role in making health impact assessments on air pollution

    Income security in Nordic welfare states for men and women who died when aged 55–69 years old

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    Income security when health impairment or other social risks occur is a major objective of welfare states. This comparative study uses register data from four Nordic welfare states for examining equivalized disposable income during the last 12 years alive among men and women who died when aged 55–69 years old. The analysed outcome indicates the aggregate result of a varied set of income maintenance mechanisms. Median income increased in the Finnish, Norwegian and Swedish samples, but decreased somewhat in Denmark, probably due to relatively frequent transitions to retirement and larger income drops after retirement than in the other Nordic countries. Analyses of comparison samples weighted by propensity scores indicated a better income development among those who lived beyond the observation period than among those who died. The higher educated had a more favourable income development during the years prior to death than those with low education.Peer reviewe
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