Widening educational inequalities in mortality in more recent birth cohorts: a study of 14 European countries.

BACKGROUND: Studies of period changes in educational inequalities in mortality have shown important changes over time. It is unknown whether a birth cohort perspective paints the same picture. We compared changes in inequalities in mortality between a period and cohort perspective and explored mortality trends among low-educated and high-educated birth cohorts. DATA AND METHODS: In 14 European countries, we collected and harmonised all-cause and cause-specific mortality data by education for adults aged 30-79 years in the period 1971-2015. Data reordered by birth cohort cover persons born between 1902 and 1976. Using direct standardisation, we calculated comparative mortality figures and resulting absolute and relative inequalities in mortality between low educated and high educated by birth cohort, sex and period. RESULTS: Using a period perspective, absolute educational inequalities in mortality were generally stable or declining, and relative inequalities were mostly increasing. Using a cohort perspective, both absolute and relative inequalities increased in recent birth cohorts in several countries, especially among women. Mortality generally decreased across successive birth cohorts among the high educated, driven by mortality decreases from all causes, with the strongest reductions for cardiovascular disease mortality. Among the low educated, mortality stabilised or increased in cohorts born since the 1930s in particular for mortality from cardiovascular diseases, lung cancer, chronic obstructive pulmonary disease and alcohol-related causes. CONCLUSIONS: Trends in mortality inequalities by birth cohort are less favourable than by calendar period. In many European countries, trends among more recently born generations are worrying. If current trends among younger birth cohorts persist, educational inequalities in mortality may further widen.

Socioeconomic inequalities in cancer mortality between and within countries in Europe: a population-based study.

Background: Reducing socioeconomic inequalities in cancer is a priority for the public health agenda. A systematic assessment and benchmarking of socioeconomic inequalities in cancer across many countries and over time in Europe is not yet available. Methods: Census-linked, whole-of-population cancer-specific mortality data by socioeconomic position, as measured by education level, and sex were collected, harmonized, analysed, and compared across 18 countries during 1990-2015, in adults aged 40-79. We computed absolute and relative educational inequalities; temporal trends using estimated-annual-percentage-changes; the share of cancer mortality linked to educational inequalities. Findings: Everywhere in Europe, lower-educated individuals have higher mortality rates for nearly all cancer-types relative to their more highly-educated counterparts, particularly for tobacco/infection-related cancers [relative risk of lung cancer mortality for lower- versus higher-educated = 2.4 (95% confidence intervals: 2.1-2.8) among men; = 1.8 (95% confidence intervals: 1.5-2.1) among women]. However, the magnitude of inequalities varies greatly by country and over time, predominantly due to differences in cancer mortality among lower-educated groups, as for many cancer-types higher-educated have more similar (and lower) rates, irrespective of the country. Inequalities were generally greater in Baltic/Central/East-Europe and smaller in South-Europe, although among women large and rising inequalities were found in North-Europe (relative risk of all cancer mortality for lower- versus higher-educated ≥1.4 in Denmark, Norway, Sweden, Finland and the England/Wales). Among men, rate differences (per 100,000 person-years) in total-cancer mortality for lower-vs-higher-educated groups ranged from 110 (Sweden) to 559 (Czech Republic); among women from approximately null (Slovenia, Italy, Spain) to 176 (Denmark). Lung cancer was the largest contributor to inequalities in total-cancer mortality (between-country range: men, 29-61%; women, 10-56%). 32% of cancer deaths in men and 16% in women (but up to 46% and 24%, respectively in Baltic/Central/East-Europe) were associated with educational inequalities. Interpretation: Cancer mortality in Europe is largely driven by levels and trends of cancer mortality rates in lower-education groups. Even Nordic-countries, with a long-established tradition of equitable welfare and social justice policies, witness increases in cancer inequalities among women. These results call for a systematic measurement, monitoring and action upon the remarkable socioeconomic inequalities in cancer existing in Europe. Funding: This study was done as part of the LIFEPATH project, which has received financial support from the European Commission (Horizon 2020 grant number 633666), and the DEMETRIQ project, which received support from the European Commission (grant numbers FP7-CP-FP and 278511). SV and WN were supported by the French Institut National du Cancer (INCa) (Grant number 2018-116). PM was supported by the Academy of Finland (#308247, # 345219) and the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No 101019329). The work by Mall Leinsalu was supported by the Estonian Research Council (grant PRG722).

Joint effects of educational attainment, type 2 diabetes and coexisting morbidity on disability pension: results from a longitudinal, nationwide, register-based study.

AIMS/HYPOTHESIS: High prevalence of coexisting morbidity in people with type 2 diabetes highlights the need to include interactions with education and comorbidity in the assessments of societal consequences of type 2 diabetes. The purpose of this study was to estimate the joint effects of education, type 2 diabetes and six frequent comorbidities. METHODS: Nationwide administrative register data on type 2 diabetes diagnosis, hospital admissions, education and disability pension were grouped at the individual level by means of a unique personal identification number. Included were all people (N = 2,281,599) in the age span of 40-59 years living in Denmark in the period 2005 to 2017, covering a total of 17,754,788 person-years. We used both Cox proportional hazards and Aalen additive hazards models to estimate relative and absolute joint effects of type 2 diabetes, educational attainment and six common comorbidities (CVD, cancer and cerebrovascular, respiratory, musculoskeletal and psychiatric diseases). We decomposed the joint effects of educational level, type 2 diabetes and comorbidities into main effects and the interaction effect, measured as extra cases of disability pension. RESULTS: Lower level of educational attainment, type 2 diabetes and comorbidities independently contributed to additional granted disability pensions. The joint number of cases of disability pension exceeded the sum of the three exposures, which is explained by a synergistic effect of lower educational level, type 2 diabetes and comorbidity. CONCLUSIONS/INTERPRETATION: In this population study, the joint effects of type 2 diabetes, lower education and comorbidity were associated with larger than additive rates of disability pension. An integrated approach that takes into account socioeconomic barriers to type 2 diabetes rehabilitation may slow down disease progression and increase the working ability of socially disadvantaged people.

Determinants of educational inequalities in disability-free life expectancy between ages 35 and 80 in Europe.

Socioeconomic inequalities in disability-free life expectancy (DFLE) exist across all European countries, yet the driving determinants of these differences are not completely known. We calculated the impact on educational inequalities in DFLE of equalizing the distribution of eight risk factors for mortality and disability using register-based mortality data and survey data from 15 European countries for individuals between 35 and 80 years old. From the selected risk factors, the ones that contribute the most to the educational inequalities in DFLE are low income, high body-weight, smoking (for men), and manual occupation of the father. Potentially large reductions in inequalities can be achieved in Eastern European countries, where educational inequalities in DFLE are also the largest.

Smoking and inequalities in mortality in 11 European countries: a birth cohort analysis.

PURPOSE: To study the trends of smoking-attributable mortality among the low and high educated in consecutive birth cohorts in 11 European countries. METHODS: Register-based mortality data were collected among adults aged 30 to 79 years in 11 European countries between 1971 and 2012. Smoking-attributable deaths were estimated indirectly from lung cancer mortality rates using the Preston-Glei-Wilmoth method. Rate ratios and rate differences among the low and high-educated were estimated and used to estimate the contribution of inequality in smoking-attributable mortality to inequality in total mortality. RESULTS: In most countries, smoking-attributable mortality decreased in consecutive birth cohorts born between 1906 and 1961 among low- and high-educated men and high-educated women, but not among low-educated women among whom it increased. Relative educational inequalities in smoking-attributable mortality increased among both men and women with no signs of turning points. Absolute inequalities were stable among men but slightly increased among women. The contribution of inequality in smoking-attributable mortality to inequality in total mortality decreased in consecutive generations among men but increased among women. CONCLUSIONS: Smoking might become less important as a driver of inequalities in total mortality among men in the future. However, among women, smoking threatens to further widen inequalities in total mortality.

Determinants of inequalities in years with disability: an international-comparative study.

BACKGROUND: Persons with a lower socioeconomic position spend more years with disability, despite their shorter life expectancy, but it is unknown what the important determinants are. This study aimed to quantify the contribution to educational inequalities in years with disability of eight risk factors: father's manual occupation, low income, few social contacts, smoking, high alcohol consumption, high body-weight, low physical exercise and low fruit and vegetable consumption. METHODS: We collected register-based mortality and survey-based disability and risk factor data from 15 European countries covering the period 2010-14 for most countries. We calculated years with disability between the ages of 35 and 80 by education and gender using the Sullivan method, and determined the hypothetical effect of changing the prevalence of each risk factor to the prevalence observed among high educated ('upward levelling scenario'), using Population Attributable Fractions. RESULTS: Years with disability among low educated were higher than among high educated, with a difference of 4.9 years among men and 5.5 years among women for all countries combined. Most risk factors were more prevalent among low educated. We found the largest contributions to inequalities in years with disability for low income (men: 1.0 year; women: 1.4 year), high body-weight (men: 0.6 year; women: 1.2 year) and father's manual occupation (men: 0.7 year; women: 0.9 year), but contributions differed by country. The contribution of smoking was relatively small. CONCLUSIONS: Disadvantages in material circumstances (low income), circumstances during childhood (father's manual occupation) and high body-weight contribute to inequalities in years with disability.

Progress against inequalities in mortality: register-based study of 15 European countries between 1990 and 2015.

Socioeconomic inequalities in mortality are a challenge for public health around the world, but appear to be resistant to policy-making. We aimed to identify European countries which have been more successful than others in narrowing inequalities in mortality, and the factors associated with narrowing inequalities. We collected and harmonised mortality data by educational level in 15 European countries over the last 25 years, and quantified changes in inequalities in mortality using a range of measures capturing different perspectives on inequality (e.g., 'relative' and 'absolute' inequalities, inequalities in 'attainment' and 'shortfall'). We determined which causes of death contributed to narrowing of inequalities, and conducted country- and period-fixed effects analyses to assess which country-level factors were associated with narrowing of inequalities in mortality. Mortality among the low educated has declined rapidly in all European countries, and a narrowing of absolute, but not relative inequalities was seen in many countries. Best performers were Austria, Italy (Turin) and Switzerland among men, and Spain (Barcelona), England and Wales, and Austria among women. Ischemic heart disease, smoking-related causes (men) and amenable causes often contributed to narrowing inequalities. Trends in income inequality, level of democracy and smoking were associated with widening inequalities, but rising health care expenditure was associated with narrowing inequalities. Trends in inequalities in mortality have not been as unfavourable as often claimed. Our results suggest that health care expansion has counteracted the inequalities widening effect of other influences.

Determinants of inequalities in life expectancy: an international comparative study of eight risk factors.

BACKGROUND: Socioeconomic inequalities in longevity have been found in all European countries. We aimed to assess which determinants make the largest contribution to these inequalities. METHODS: We did an international comparative study of inequalities in risk factors for shorter life expectancy in Europe. We collected register-based mortality data and survey-based risk factor data from 15 European countries. We calculated partial life expectancies between the ages of 35 years and 80 years by education and gender and determined the effect on mortality of changing the prevalence of eight risk factors-father with a manual occupation, low income, few social contacts, smoking, high alcohol consumption, high bodyweight, low physical exercise, and low fruit and vegetable consumption-among people with a low level of education to that among people with a high level of education (upward levelling scenario), using population attributable fractions. FINDINGS: In all countries, a substantial gap existed in partial life expectancy between people with low and high levels of education, of 2·3-8·2 years among men and 0·6-4·5 years among women. The risk factors contributing most to the gap in life expectancy were smoking (19·8% among men and 18·9% among women), low income (9·7% and 13·4%), and high bodyweight (7·7% and 11·7%), but large differences existed between countries in the contribution of risk factors. Sensitivity analyses using the prevalence of risk factors in the most favourable country (best practice scenario) showed that the potential for reducing the gap might be considerably smaller. The results were also sensitive to varying assumptions about the mortality risks associated with each risk factor. INTERPRETATION: Smoking, low income, and high bodyweight are quantitatively important entry points for policies to reduce educational inequalities in life expectancy in most European countries, but priorities differ between countries. A substantial reduction of inequalities in life expectancy requires policy actions on a broad range of health determinants. FUNDING: European Commission and Network for Studies on Pensions, Aging, and Retirement.

Mortality inequalities by occupational class among men in Japan, South Korea and eight European countries: a national register-based study, 1990-2015.

BACKGROUND: We compared mortality inequalities by occupational class in Japan and South Korea with those in European countries, in order to determine whether patterns are similar. METHODS: National register-based data from Japan, South Korea and eight European countries (Finland, Denmark, England/Wales, France, Switzerland, Italy (Turin), Estonia, Lithuania) covering the period between 1990 and 2015 were collected and harmonised. We calculated age-standardised all-cause and cause-specific mortality among men aged 35-64 by occupational class and measured the magnitude of inequality with rate differences, rate ratios and the average inter-group difference. RESULTS: Clear gradients in mortality were found in all European countries throughout the study period: manual workers had 1.6-2.5 times higher mortality than upper non-manual workers. However, in the most recent time-period, upper non-manual workers had higher mortality than manual workers in Japan and South Korea. This pattern emerged as a result of a rise in mortality among the upper non-manual group in Japan during the late 1990s, and in South Korea during the late 2000s, due to rising mortality from cancer and external causes (including suicide), in addition to strong mortality declines among lower non-manual and manual workers. CONCLUSION: Patterns of mortality by occupational class are remarkably different between European countries and Japan and South Korea. The recently observed patterns in the latter two countries may be related to a larger impact on the higher occupational classes of the economic crisis of the late 1990s and the late 2000s, respectively, and show that a high socioeconomic position does not guarantee better health.

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

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.

The effect of smoking on the healthy life expectancy of Palestinian men in the West Bank: a cross-sectional study.

BACKGROUND: The high prevalence of smoking (40%) in men living in the West Bank of the occupied Palestinian territory is a major challenge for the Palestinian health authorities. The aim of this study was to estimate life expectancy and the average lifetime with and without chronic disease in men living in the West Bank who had never smoked, were ex-smokers, or were smokers. METHODS: We used a life table for the male population in the West Bank and Danish relative risk estimates for death for smokers and ex-smokers versus never smokers and data from the 2010 Palestinian Family Survey. We estimated expected life time with and without chronic disease, and the contributions from the mortality and morbidity effects to smoking-related differences in average lifetime with and without chronic disease were assessed by decomposition. FINDINGS: The life expectancy of a Palestinian man aged 15 years who would never start smoking was 59·5 years, of which 41·1 years (95% CI 40·3-41·9) were expected to be without chronic disease. Ex-smokers could expect 57·9 years of remaining life time, 37·7 years (35·9-39·4) of which would be without chronic disease. For life-long heavy smokers, the expected lifetime was 52·6 years, of which 38·5 years (37·3-39·7) would be without chronic disease. Of the total loss of 6·9 years of life expectancy in heavy smokers, the mortality effect accounted for 2·5 years without disease and 4·4 years with disease, whereas the morbidity effect was negligible. The morbidity component of the decomposition accounted for 1·7 years with disease for moderate smokers and 2·9 years without disease for ex-smokers. INTERPRETATION: The high prevalence of smoking causes a considerable loss of life-years and life time without chronic disease. We recommend that the Palestinian health authorities enforce an anti-smoking law. FUNDING: None.

The impact of smoking on expected lifetime with and without chronic disease among Palestinian men in the West Bank.

Background: The purpose of the study was to estimate life expectancy and the average lifetime with and without chronic disease among male never smokers, ex-smokers and smokers living in the West Bank of the occupied Palestinian territory. Methods: The study used a life table for the West Bank male population and Danish relative risk estimates for death for smokers and ex-smokers vs. never smokers and utilized data from the Palestinian Family Survey 2010. Expected lifetime with and without chronic disease was estimated and the contributions from the mortality and the morbidity effect to smoking related difference in average lifetime with and without chronic disease were assessed by decomposition. Results: In the West bank 40% of the male population are smokers. Life expectancy of 15-year-old Palestinian men who would never start smoking was 59.5 years, 41.1 of which were expected to be without chronic disease. Ex-smokers could expect 57.9 years of remaining lifetime, 37.7 years of which without disease. For lifelong heavy smokers (> 20 cigarettes per day), the expected lifetime was reduced to 52.6 years, of which 38.5 years were without chronic disease. Of the total loss of 6.9 years of life expectancy among heavy smokers, the mortality effect accounted for 2.5 years without and 4.4 years with disease, whereas the morbidity effect was negligible. Conclusions: The high prevalence of smoking causes a considerable loss of life years and lifetime without chronic disease. We recommend the Palestinian health authorities to enforce the anti-smoking law.

Midlife Cognitive Ability, Education, and Tooth Loss in Older Danes.

OBJECTIVE: To examine the possible influence of cognitive ability and education at age 50 or 60 on number of teeth at age 70. SETTING: Community-dwelling population in Copenhagen, Denmark. PARTICIPANTS: Men and women born in 1914 (N = 302). MEASUREMENTS: Cognitive ability was assessed using the Wechsler Adult Intelligence Scale at age 50 or 60. A global cognitive ability measure was used as a continuous measure and according to tertile. Information on education was gathered using a questionnaire at age 50 or 60. A clinical oral examination took place at age 70, and oral health was measured according to number of teeth (<6 vs ≥6). Baseline covariates were smoking, alcohol, sex, and income. RESULTS: Logistic regression analyses revealed that greater cognitive ability and educational attainment had a protective effect against risk of tooth loss. The associations were significant and persisted after adjusting for confounders and a two-way interaction between cognitive ability and education. CONCLUSION: Higher education level and cognitive ability measured at age 50 or 60 were associated with having more teeth at age 70. Whether these findings are due to the interaction of these factors with oral health, related socioeconomic factors, or other factors remains to be studied.

Increasing illness among people out of labor market - A Danish register-based study.

In spite of decades of very active labor market policies, 25% of Denmark's population in the working ages are still out-of-work. The aim of this study was to investigate whether that is due to consistent or even increasing prevalence of ill health. For the period of 2002-2011, we investigated if i) the prevalence of four chronic diseases (cardiovascular disease, diabetes, cancer and mental disorders) among those out-of-work had changed, ii) the occurrence of new cases of those diseases were higher among those who were already out-of-work, or iii) if non-health-related benefits were disproportionately given to individuals recently diagnosed with a disease compared to those without disease. The study was register-based and comprised all Danish residents aged 20-60. During the study period, the prevalence of cardiovascular diseases and mental disorders increased among both employed and non-employed people. The increased prevalence for mental disorder was particularly high among people receiving means-tested benefits. Disease incidence was higher among people outside rather than inside the labor market, especially for mental disorders. Employed people with incident diseases had an unsurprisingly increased risk of leaving the labor market. However, a high proportion of people with incident mental disorders received low level means-tested benefits in the three years following this diagnosis, which is concerning. Men treated for mental disorders in 2006 had high excess probability of receiving a cash-benefit, OR = 4.83 (4.53-5.14) for the period 2007-2010. The estimates were similar for women.

Gender-specific modifying effect on the educational disparities in the impact of smoking on health expectancy.

BACKGROUND: Smoking reduces life years in good health but it is unclear how education modifies the impact of smoking. We hypothesize that the vulnerability of the effect of smoking on health expectancy decreases with educational level in both genders and examine the contributions of mortality and health effects. METHODS: Life tables by educational level and smoking category were constructed from registers and survey data. For each educational level, difference in expected lifetime in self-rated good and poor health between 30-year-old never smokers and smokers were estimated and decomposed into contributions from mortality and health status. RESULTS: Difference in expected lifetime in good health between never smokers and smokers decreased with educational level for women but increased for men. Thus, the differences between never smokers and heavy smokers among 30-year-old women with a low, medium and high educational level were 12.9, 8.9 and 4.1 years, respectively. In contrast, the differences between male never smokers and heavy smokers with a low, medium and high educational level were 10.3, 11.4 and 14.3 years, respectively. Regardless of educational level, the mortality effect increased by exposure to smoking but the effect of health status increased by educational level for men and decreased for women. CONCLUSION: The social differential vulnerability to the effect of smoking differed between genders. Thus, whereas smoking had a substantial effect on health among women with a low educational level the pattern for men was opposite because the health gain for never smokers was greatest for men with a high education.

Assessment of health impacts of decreased smoking prevalence in Copenhagen: Application of the DYNAMO-HIA model.

AIMS: Tobacco smoking is among the leading risk factors for chronic disease and early death in developed countries, including Denmark, where smoking causes 14% of the disease burden. In Denmark, many public health interventions, including smoking prevention, are undertaken by the municipalities, but models to estimate potential health effects of local interventions are lacking. The aim of the current study was to model the effects of decreased smoking prevalence in Copenhagen, Denmark. METHODS: The DYNAMO-HIA model was applied to the population of Copenhagen, by using health survey data and data from Danish population registers. We modelled the effects of four intervention scenarios aimed at different target groups, compared to a reference scenario. The potential effects of each scenario were modelled until 2040. RESULTS: A combined scenario affecting both initiation rates among youth, and cessation and re-initiation rates among adults, which reduced the smoking prevalence to 4% by 2025, would have large beneficial effects on incidence and prevalence of smoking-related diseases and mortality. Health benefits could also be obtained through interventions targeting only cessation or re-initiation rates, whereas an intervention targeting only initiation among youth had marginal effects on morbidity and mortality within the modelled time frame. CONCLUSIONS: By modifying the DYNAMO-HIA model, we were able to estimate the potential health effects of four interventions to reduce smoking prevalence in the population of Copenhagen. The effect of the interventions on future public health depended on population subgroup(s) targeted, duration of implementation and intervention reach.

Population dynamics and air pollution: the impact of demographics on health impact assessment of air pollution.

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.

A method to assess the potential effects of air pollution mitigation on healthcare costs.

OBJECTIVE: The aim of this study was to develop a method to assess the potential effects of air pollution mitigation on healthcare costs and to apply this method to assess the potential savings related to a reduction in fine particle matter in Denmark. METHODS: The effects of air pollution on health were used to identify "exposed" individuals (i.e., cases). Coronary heart disease, stroke, chronic obstructive pulmonary disease, and lung cancer were considered to be associated with air pollution. We used propensity score matching, two-part estimation, and Lin's method to estimate healthcare costs. Subsequently, we multiplied the number of saved cases due to mitigation with the healthcare costs to arrive to an expression for healthcare cost savings. RESULTS: The potential cost saving in the healthcare system arising from a modelled reduction in air pollution was estimated at €0.1-2.6 million per 100,000 inhabitants for the four diseases. CONCLUSION: We have illustrated an application of a method to assess the potential changes in healthcare costs due to a reduction in air pollution. The method relies on a large volume of administrative data and combines a number of established methods for epidemiological analysis.

Particulate emissions: health effects and labour market consequences.

The objective of this study was to analyse the productivity cost savings associated with mitigation of particulate emissions, as an input to a cost-benefit analysis. Reduced emissions of particulate matter (PM(2.5)) may reduce the incidence of diseases related to air pollution and potentially increase productivity as a result of better health. Based on data from epidemiological studies, we modelled the impact of air pollution on four different diseases: coronary heart disease, stroke, lung cancer, and chronic obstructive pulmonary disease. We identified individuals with these diseases and modelled changes in disease incidence as an expression of exposure. The labour market affiliation and development in wages over time for exposed individuals was compared to that of a reference group of individuals matched on a number of sociodemographic variables, comorbidity, and predicted smoking status. We identified a productivity cost of about 1.8 million EURO per 100,000 population aged 50-70 in the first year, following an increase in PM(2.5) emissions. We have illustrated how the potential impact of air pollution may influence social production by application of a matched study design that renders a study population similar to that of a trial. The result suggests that there may be a productivity gain associated with mitigation efforts.

Smoking and increased risk of multiple sclerosis: parallel trends in the sex ratio reinforce the evidence.

PURPOSE: Smoking behavior in industrialized nations has changed markedly over the second half of the 20th century, with diverging patterns in male and female smoking rates. We examined whether the female/male incidence of multiple sclerosis (MS) changed concomitantly with smoking, as would be expected if smoking truly increased MS risk. METHODS: We identified relevant studies reporting male and female age-specific incidence of MS throughout the world using within-country birth cohorts as units of observation. We then correlated the male/female ratio of MS incidence in each birth cohort with the corresponding male/female ratios in smoking behavior obtained from national statistics. We also examined in depth the within-country trends of smoking and MS in Canada and Denmark, two populations in which statistics on MS are readily available. RESULTS: We show that, on the natural log scale, the gender ratio of MS is correlated with the gender ratio of smoking (r = 0.16; 95% confidence interval [CI]: 0.06, 0.26; p = 0.002). Additionally, we estimated an overall incidence rate ratio of 1.50 (95% CI: 1.17, 2.01) of MS for ever-smokers as compared with never-smokers. The trend in the gender ratio of smoking, however, is driven by a decline in smoking among men, rather than by an increase in women as observed for MS incidence. CONCLUSIONS: Our results are consistent with the hypothesis that smoking increases the risk of MS and explains in part the divergence in MS incidence rates in men and women. Some other factor, however, must account for the increasing MS incidence among women.