Margarete C. Kulik

How can inequalities in mortality be reduced? A quantitative analysis of 6 risk factors in 21 european populations

Background Socioeconomic inequalities in mortality are one of the greatest challenges for health policy in all European countries, but the potential for reducing these inequalities is unclear. We therefore quantified the impact of equalizing the distribution of six risk factors for mortality: smoking, overweight, lack of physical exercise, lack of social participation, low income, and economic inactivity. Methods We collected and harmonized data on mortality and risk factors by educational level for 21 European populations in the early 2000s. The impact of the risk factors on mortality in each educational group was determined using Population Attributable Fractions. We estimated the impact on inequalities in mortality of two scenarios: a theoretical upward levelling scenario in which inequalities in the risk factor were completely eliminated, and a more realistic best practice scenario, in which inequalities in the risk factor were reduced to those seen in the country with the smallest inequalities for that risk factor. Findings In general, upward levelling of inequalities in smoking, low income and economic inactivity hold the greatest potential for reducing inequalities in mortality. While the importance of low income is similar across Europe, smoking is more important in the North and East, and overweight in the South. On the basis of best practice scenarios the potential for reducing inequalities in mortality is often smaller, but still substantial in many countries for smoking and physical inactivity. Interpretation Theoretically, there is a great potential for reducing inequalities in mortality in most European countries, for example by equity-oriented tobacco control policies, income redistribution and employment policies. Although it is necessary to achieve substantial degrees of upward levelling to make a notable difference for inequalities in mortality, the existence of best practice countries with more favourable distributions for some of these risk factors suggests that this is feasible.

Health impacts of increasing alcohol prices in the European Union : a dynamic projection

OBJECTIVE Western Europe has high levels of alcohol consumption, with corresponding adverse health effects. Currently, a major revision of the EU excise tax regime is under discussion. We quantify the health impact of alcohol price increases across the EU. DATA AND METHOD We use alcohol consumption data for 11 member states, covering 80% of the EU-27 population, and corresponding country-specific disease data (incidence, prevalence, and case-fatality rate of alcohol related diseases) taken from the 2010 published Dynamic Modelling for Health Impact Assessment (DYNAMO-HIA) database to dynamically project the changes in population health that might arise from changes in alcohol price. RESULTS Increasing alcohol prices towards those of Finland (the highest in the EU) would postpone approximately 54,000 male and approximately 26,100 female deaths over 10 years. Moreover, the prevalence of a number of chronic diseases would be reduced: in men by approximately 97,800 individuals with diabetes, 65,800 with stroke and 62,200 with selected cancers, and in women by about 19,100, 23,500, and 27,100, respectively. CONCLUSION Curbing excessive drinking throughout the EU completely would lead to substantial gains in population health. Harmonisiation of prices to the Finnish level would, for selected diseases, achieve more than 40% of those gains.

DYNAMO-HIA-A Dynamic Modeling Tool for Generic Health Impact Assessments

Background Currently, no standard tool is publicly available that allows researchers or policy-makers to quantify the impact of policies using epidemiological evidence within the causal framework of Health Impact Assessment (HIA). A standard tool should comply with three technical criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) to be useful in the applied setting of HIA. With DYNAMO-HIA (Dynamic Modeling for Health Impact Assessment), we introduce such a generic software tool specifically designed to facilitate quantification in the assessment of the health impacts of policies. Methods and Results DYNAMO-HIA quantifies the impact of user-specified risk-factor changes on multiple diseases and in turn on overall population health, comparing one reference scenario with one or more intervention scenarios. The Markov-based modeling approach allows for explicit risk-factor states and simulation of a real-life population. A built-in parameter estimation module ensures that only standard population-level epidemiological evidence is required, i.e. data on incidence, prevalence, relative risks, and mortality. DYNAMO-HIA provides a rich output of summary measures – e.g. life expectancy and disease-free life expectancy – and detailed data – e.g. prevalences and mortality/survival rates – by age, sex, and risk-factor status over time. DYNAMO-HIA is controlled via a graphical user interface and is publicly available from the internet, ensuring general accessibility. We illustrate the use of DYNAMO-HIA with two example applications: a policy causing an overall increase in alcohol consumption and quantifying the disease-burden of smoking. Conclusion By combining modest data needs with general accessibility and user friendliness within the causal framework of HIA, DYNAMO-HIA is a potential standard tool for health impact assessment based on epidemiologic evidence.

Educational Inequalities in Three Smoking-Related Causes of Death in 18 European Populations

INTRODUCTION Smoking is an important determinant of socioeconomic inequalities in mortality in many countries. As the smoking epidemic progresses, updates on the development of mortality inequalities attributable to smoking are needed. We provide estimates of relative and absolute educational inequalities in mortality from lung cancer, aerodigestive cancers, and chronic obstructive pulmonary disease (COPD)/asthma in Europe and assess the contribution of these smoking-related diseases to inequalities in all-cause mortality. METHODS We use data from 18 European populations covering the time period 1998-2007. We present age-adjusted mortality rates, relative indices of inequality, and slope indices of inequality. We also calculate the contribution of inequalities in smoking-related mortality to inequalities in overall mortality. RESULTS Among men, relative inequalities in mortality from the 3 smoking-related causes of death combined are largest in the Czech Republic and Hungary and smallest in Spain, Sweden, and Denmark. Among women, these inequalities are largest in Scotland and Norway and smallest in Italy and Spain. They are often larger among men and tend to be larger for COPD/asthma than for lung and aerodigestive cancers. Relative inequalities in mortality from these conditions are often larger in younger age groups, particularly among women, suggesting a possible further widening of inequalities in mortality in the coming decades. The combined contribution of these diseases to inequality in all-cause mortality varies between 13% and 32% among men and between -5% and 30% among women. CONCLUSION Our results underline the continuing need for tobacco control policies, which take into account socioeconomic position.

Concerted Efforts to Control or Eliminate Neglected Tropical Diseases: How Much Health Will Be Gained?

Background The London Declaration (2012) was formulated to support and focus the control and elimination of ten neglected tropical diseases (NTDs), with targets for 2020 as formulated by the WHO Roadmap. Five NTDs (lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths and trachoma) are to be controlled by preventive chemotherapy (PCT), and four (Chagas’ disease, human African trypanosomiasis, leprosy and visceral leishmaniasis) by innovative and intensified disease management (IDM). Guinea worm, virtually eradicated, is not considered here. We aim to estimate the global health impact of meeting these targets in terms of averted morbidity, mortality, and disability adjusted life years (DALYs). Methods The Global Burden of Disease (GBD) 2010 study provides prevalence and burden estimates for all nine NTDs in 1990 and 2010, by country, age and sex, which were taken as the basis for our calculations. Estimates for other years were obtained by interpolating between 1990 (or the start-year of large-scale control efforts) and 2010, and further extrapolating until 2030, such that the 2020 targets were met. The NTD disease manifestations considered in the GBD study were analyzed as either reversible or irreversible. Health impacts were assessed by comparing the results of achieving the targets with the counterfactual, construed as the health burden had the 1990 (or 2010 if higher) situation continued unabated. Principle Findings/Conclusions Our calculations show that meeting the targets will lead to about 600 million averted DALYs in the period 2011–2030, nearly equally distributed between PCT and IDM-NTDs, with the health gain amongst PCT-NTDs mostly (96%) due to averted disability and amongst IDM-NTDs largely (95%) from averted mortality. These health gains include about 150 million averted irreversible disease manifestations (e.g. blindness) and 5 million averted deaths. Control of soil-transmitted helminths accounts for one third of all averted DALYs. We conclude that the projected health impact of the London Declaration justifies the required efforts.

Socioeconomic Inequalities in Neglected Tropical Diseases: A Systematic Review

Background Neglected tropical diseases (NTDs) are generally assumed to be concentrated in poor populations, but evidence on this remains scattered. We describe within-country socioeconomic inequalities in nine NTDs listed in the London Declaration for intensified control and/or elimination: lymphatic filariasis (LF), onchocerciasis, schistosomiasis, soil-transmitted helminthiasis (STH), trachoma, Chagas’ disease, human African trypanosomiasis (HAT), leprosy, and visceral leishmaniasis (VL). Methodology We conducted a systematic literature review, including publications between 2004–2013 found in Embase, Medline (OvidSP), Cochrane Central, Web of Science, Popline, Lilacs, and Scielo. We included publications in international peer-reviewed journals on studies concerning the top 20 countries in terms of the burden of the NTD under study. Principal findings We identified 5,516 publications, of which 93 met the inclusion criteria. Of these, 59 papers reported substantial and statistically significant socioeconomic inequalities in NTD distribution, with higher odds of infection or disease among poor and less-educated people compared with better-off groups. The findings were mixed in 23 studies, and 11 studies showed no substantial or statistically significant inequality. Most information was available for STH, VL, schistosomiasis, and, to a lesser extent, for trachoma. For the other NTDs, evidence on their socioeconomic distribution was scarce. The magnitude of inequality varied, but often, the odds of infection or disease were twice as high among socioeconomically disadvantaged groups compared with better-off strata. Inequalities often took the form of a gradient, with higher odds of infection or disease each step down the socioeconomic hierarchy. Notwithstanding these inequalities, the prevalence of some NTDs was sometimes also high among better-off groups in some highly endemic areas. Conclusions While recent evidence on socioeconomic inequalities is scarce for most individual NTDs, for some, there is considerable evidence of substantially higher odds of infection or disease among socioeconomically disadvantaged groups. NTD control activities as proposed in the London Declaration, when set up in a way that they reach the most in need, will benefit the poorest populations in poor countries.

Occupational class inequalities in all-cause and cause-specific mortality among middle-aged men in 14 European populations during the early 2000s

This study analyses occupational class inequalities in all-cause mortality and four specific causes of death among men, in Europe in the early 2000s, and is the most extensive comparative analysis of occupational class inequalities in mortality in Europe so far. Longitudinal data, obtained from population censuses and mortality registries in 14 European populations, from around the period 2000–2005, were used. Analyses concerned men aged 30–59 years and included all-cause mortality and mortality from all cancers, all cardiovascular diseases (CVD), all external, and all other causes. Occupational class was analysed according to five categories: upper and lower non-manual workers, skilled and unskilled manual workers, and farmers and self-employed combined. Inequalities were quantified with mortality rate ratios, rate differences, and population attributable fractions (PAF). Relative and absolute inequalities in all-cause mortality were more pronounced in Finland, Denmark, France, and Lithuania than in other populations, and the same countries (except France) also had the highest PAF values for all-cause mortality. The main contributing causes to these larger inequalities differed strongly between countries (e.g., cancer in France, all other causes in Denmark). Relative and absolute inequalities in CVD mortality were markedly lower in Southern European populations. We conclude that relative and absolute occupational class differences in all-cause and cause specific mortality have persisted into the early 2000s, although the magnitude differs strongly between populations. Comparisons with previous studies suggest that the relative gap in mortality between occupational classes has further widened in some Northern and Western European populations.

Comparison of Tobacco Control Scenarios: Quantifying Estimates of Long-Term Health Impact Using the DYNAMO-HIA Modeling Tool

Background There are several types of tobacco control interventions/policies which can change future smoking exposure. The most basic intervention types are 1) smoking cessation interventions 2) preventing smoking initiation and 3) implementation of a nationwide policy affecting quitters and starters simultaneously. The possibility for dynamic quantification of such different interventions is key for comparing the timing and size of their effects. Methods and Results We developed a software tool, DYNAMO-HIA, which allows for a quantitative comparison of the health impact of different policy scenarios. We illustrate the outcomes of the tool for the three typical types of tobacco control interventions if these were applied in the Netherlands. The tool was used to model the effects of different types of smoking interventions on future smoking prevalence and on health outcomes, comparing these three scenarios with the business-as-usual scenario. The necessary data input was obtained from the DYNAMO-HIA database which was assembled as part of this project. All smoking interventions will be effective in the long run. The population-wide strategy will be most effective in both the short and long term. The smoking cessation scenario will be second-most effective in the short run, though in the long run the smoking initiation scenario will become almost as effective. Interventions aimed at preventing the initiation of smoking need a long time horizon to become manifest in terms of health effects. The outcomes strongly depend on the groups targeted by the intervention. Conclusion We calculated how much more effective the population-wide strategy is, in both the short and long term, compared to quit smoking interventions and measures aimed at preventing the initiation of smoking. By allowing a great variety of user-specified choices, the DYNAMO-HIA tool is a powerful instrument by which the consequences of different tobacco control policies and interventions can be assessed.

Between-Country Inequalities in the Neglected Tropical Disease Burden in 1990 and 2010, with Projections for 2020

Background The World Health Organization (WHO) has set ambitious time-bound targets for the control and elimination of neglected tropical diseases (NTDs). Investing in NTDs is not only seen as good value for money, but is also advocated as a pro-poor policy since it would improve population health in the poorest populations. We studied the extent to which the disease burden from nine NTDs (lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths, trachoma, Chagas disease, human African trypanosomiasis, leprosy, visceral leishmaniasis) was concentrated in the poorest countries in 1990 and 2010, and how this would change by 2020 in case the WHO targets are met. Principal Findings Our analysis was based on 1990 and 2010 data from the Global Burden of Disease (GBD) 2010 study and on projections of the 2020 burden. Low and lower-middle income countries together accounted for 69% and 81% of the global burden in 1990 and 2010 respectively. Only the soil-transmitted helminths and Chagas disease caused a considerable burden in upper-middle income countries. The global burden from these NTDs declined by 27% between 1990 and 2010, but reduction largely came to the benefit of upper-middle income countries. Achieving the WHO targets would lead to a further 55% reduction in the global burden between 2010 and 2020 in each country income group, and 81% of the global reduction would occur in low and lower-middle income countries. Conclusions The GBD 2010 data show the burden of the nine selected NTDs in DALYs is strongly concentrated in low and lower-middle income countries, which implies that the beneficial impact of NTD control eventually also largely comes to the benefit of these same countries. While the nine NTDs became increasingly concentrated in developing countries in the 1990–2010 period, this trend would be rectified if the WHO targets were met, supporting the pro-poor designation.

The smoking population in the USA and EU is softening not hardening

Background It has been argued that as smoking prevalence declines in countries, the smokers that remain include higher proportions of those who are unwilling or unable to quit (a process known as ‘hardening’). Smokeless tobacco and e-cigarettes have been promoted as a strategy to deal with such smokers. If hardening is occurring, there would be a positive association between smoking prevalence and quitting, with less quitting at lower prevalence. There would also be a neutral or negative association between prevalence and the number of cigarettes smoked. Methods We examined US state-level associations using the Tobacco Use Supplement (1992/1993–2010/2011) and Eurobarometer surveys for 31 European countries (2006–2009–2012) using regressions of quit attempts, quit ratios, and number of cigarettes smoked on smoking prevalence over time. Results For each 1% drop in smoking prevalence, quit attempts increase by 0.55%±.07 (p<0.001) in the USA and remain stable in Europe (p=0.53), US quit ratios increase by 1.13%±0.06 (p<0.001), and consumption drops by 0.32 cig/day±0.02 (p<0.001) in the USA and 0.22 cig/day±0.05 (p<0.001) in Europe. These associations remain stable over time (p>0.24), with significantly lower consumption at any given prevalence level as time passed in the USA (−0.15 (cig/day)/year±0.06, p<0.05). Conclusions Consistent with prior research using different data and methods, these population-level results reject the hypothesis of hardening as smoking prevalence drops, instead supporting softening of the smoking population as prevalence declines.