Enabling the examination of long-term mortality trends by educational level for England and Wales in a time-consistent and internationally comparable manner.

BACKGROUND: Studying long-term trends in educational inequalities in health is important for monitoring and policy evaluation. Data issues regarding the allocation of people to educational groups hamper the study and international comparison of educational inequalities in mortality. For the UK, this has been acknowledged, but no satisfactory solution has been proposed. OBJECTIVE: To enable the examination of long-term mortality trends by educational level for England and Wales (E&W) in a time-consistent and internationally comparable manner, we propose and implement an approach to deal with the data issues regarding mortality data by educational level. METHODS: We employed 10-year follow-ups of individuals aged 20+ from the Office for National Statistics Longitudinal Study (ONS-LS), which include education information from each decennial census (1971-2011) linked to individual death records, for a 1% representative sample of the E&W population. We assigned the individual cohort data to single ages and calendar years, and subsequently obtained aggregate all-cause mortality data by education, sex, age (30+), and year (1972-2017). Our data adjustment approach optimised the available education information at the individual level, and adjusts-at the aggregate level-for trend discontinuities related to the identified data issues, and for differences with country-level mortality data for the total population. RESULTS: The approach resulted in (1) a time-consistent and internationally comparable categorisation of educational attainment into the low, middle, and high educated; (2) the adjustment of identified data-quality related discontinuities in the trends over time in the share of personyears and deaths by educational level, and in the crude and the age-standardised death rate by and across educational levels; (3) complete mortality data by education for ONS-LS members aged 30+ in 1972-2017 which aligns with country-level mortality data for the total population; and (4) the estimation of inequality measures using established methods. For those aged 30+ , both absolute and relative educational inequalities in mortality first increased and subsequently decreased. CONCLUSION: We obtained additional insights into long-term trends in educational inequalities in mortality in E&W, and illustrated the potential effects of different data issues. We recommend the use of (part of) the proposed approach in other contexts.

Reversals in past long-term trends in educational inequalities in life expectancy for selected European countries.

BACKGROUND: Across Europe, socioeconomic inequalities in mortality are large and persistent. To better understand the drivers of past trends in socioeconomic mortality inequalities, we identified phases and potential reversals in long-term trends in educational inequalities in remaining life expectancy at age 30 (e30), and assessed the contributions of mortality changes among the low-educated and the high-educated at different ages. METHODS: We used individually linked annual mortality data by educational level (low, middle and high), sex and single age (30+) from 1971/1972 onwards for England and Wales, Finland and Italy (Turin). We applied segmented regression to trends in educational inequalities in e30 (e30 high-educated minus e30 low-educated) and employed a novel demographic decomposition technique. RESULTS: We identified several phases and breakpoints in the trends in educational inequalities in e30. The long-term increases (Finnish men, 1982-2008; Finnish women, 1985-2017; and Italian men, 1976-1999) were driven by faster mortality declines among the high-educated aged 65-84, and by mortality increases among the low-educated aged 30-59. The long-term decreases (British men, 1976-2008, and Italian women, 1972-2003) were driven by faster mortality improvements among the low-educated than among the high-educated at age 65+. The recent stagnation of increasing inequality (Italian men, 1999) and reversals from increasing to decreasing inequality (Finnish men, 2008) and from decreasing to increasing inequality (British men, 2008) were driven by mortality trend changes among the low-educated aged 30-54. CONCLUSION: Educational inequalities are plastic. Mortality improvements among the low-educated at young ages are imperative for achieving long-term decreases in educational inequalities in e30.

Long-Term Trends in Obesity Prevalence by Socio-Economic Group in Five European Countries and the USA: The Relevance of the Diffusion of Innovations Theory.

INTRODUCTION: Cross-national comparison suggests that the timing of the obesity epidemic differs across socio-economic groups (SEGs). Similar to the smoking epidemic, these differences might be described by the diffusion of innovations theory, which states that health behaviours diffuse from higher to lower SEGs. However, the applicability of the diffusion of innovations theory to long-term time trends in obesity by SEG is unknown. We studied long-term trends in the obesity prevalence by SEG in England, France, Finland, Italy, Norway, and the USA and examined whether trends are described by the diffusion of innovations theory. METHODS: Obesity prevalence from 1978 to 2019 by educational level, sex, and age group (25+ years) from health surveys was harmonized, age-standardized, Loess-smoothed, and visualized. Prevalence rate differences were calculated, and segmented regression was performed to obtain annual percentage changes, which were compared over time and across SEGs. RESULTS: Obesity prevalence among lower educated groups has exceeded that of higher educated groups, except among American men, in all countries throughout the study period. A comparable increase across educational levels was observed until approximately 2000. Recently, obesity prevalence stagnated among higher educated groups in Finland, France, Italy, and Norway and lower educated groups in England and the USA. DISCUSSION: Recent trends in obesity prevalence by SEG are mostly in line with the diffusion of innovations theory; however, no diffusion from higher to lower SEGs at the start of the epidemic was found. The stagnation among higher SEGs but not lower SEGs suggests that the latter will likely experience the greatest future burden.

Early-life exposure to economic stress and metabolic risks in young adulthood: the children of the reunification in East Germany.

BACKGROUND: Research on the long-term health consequences of early-life exposure to economic crises is scarce. We examine for the first time the long-term effects of early-life exposure to an economic crisis on metabolic health risks. We study objective health measures, and exploit the quasi-experimental situation of the postreunification economic crisis in East Germany. METHODS: Data were drawn from two waves of the longitudinal German Health Interview and Examination Survey for Children and Adolescents (2003-2006, 2014-2017). We compared 392 East Germans who were exposed to the economic crisis in utero and at ages 0-5 with 1123 of their West German counterparts using propensity score matching on individual and family characteristics. We assessed blood pressure, cholesterol, blood fat and body mass index (BMI); both combined as above-average metabolic health risks and individually at ages 19-30. RESULTS: Early-life exposure to the economic crisis significantly increased the number of above-average metabolic health risks in young adulthood by 0.1482 (95% CI 0.0169 to 0.2796), which was 5.8% higher compared with no exposure. Among individuals exposed in utero, only females showed significant effects. Early-life exposure to the economic crisis was associated with increased systolic (0.9969, 95% CI -0.2806 to 2.2743) and diastolic blood pressure (0.6786, 95% CI -0.0802 to 1.4373), and with increased BMI (0.0245, 95% CI -0.6516 to 0.7001). CONCLUSION: The increased metabolic health risks found for women exposed to the postreunification economic crisis in-utero are likely attributable to increased economic stress. While the observed differences are small, they may foreshadow the emergence of greater health disparities in older age.

Alcohol and educational inequalities: Hazardous drinking prevalence and all-cause mortality by hazardous drinking group in people aged 50 and older in Europe.

BACKGROUND: We examined educational inequalities in hazardous drinking prevalence among individuals aged 50 or more in 14 European countries, and explored educational inequalities in mortality in hazardous drinkers in European regions.Methods: We analyzed data from waves 4, 5 and 6 of the Survey of Health Ageing and Retirement in Europe (SHARE). We estimated age-standardized hazardous drinking prevalence, and prevalence ratios (PR) of hazardous drinking by country and educational level using Poisson regression models with robust variance. We estimated the relative index of inequality (RII) for all-cause mortality among hazardous drinkers and non-hazardous drinkers using Cox proportional hazards regression models and for each region (North, South, East and West).Results: In men, educational inequalities in hazardous drinking were not observed (PRmedium = 1.09 [95%CI: 0.98-1.21] and PRhigh = 0.99 [95%CI: 0.88-1.10], ref. low), while in they were observed in women, having the highest hazardous drinking prevalence in the highest educational levels (PRmedium = 1.28 [95%CI: 1.15-1.42] and PRhigh = 1.53 [95%CI: 1.36-1.72]). Overall, the Relative Index of Inequality (RII) in all-cause mortality among hazardous drinkers was 1.12 [95%CI: 1.03-1.22] among men and 1.10 [95%CI: 0.97-1.25] among women. Educational inequalities among hazardous drinkers were observed in Eastern Europe for both men (RIIhazardous = 1.21 [95%CI: 1.01-1.45]) and women (RIIhazardous = 1.46 [95%CI: 1.13-1.87]). Educational inequalities in mortality among non-hazardous drinkers were observed in Southern, Western and Eastern Europe among men, and in Eastern Europe among women.Conclusions: Higher educational attainment is positively associated with hazardous drinking prevalence among women, but not among men in most of the analyzed European countries. Clear educational inequalities in mortality among hazardous drinkers were only observed in Eastern Europe. Further research on the associations between alcohol use and inequalities in all-cause mortality in different regions is needed.

Future life expectancy in Europe taking into account the impact of smoking, obesity, and alcohol.

Introduction: In Europe, women can expect to live on average 82 years and men 75 years. Forecasting how life expectancy will develop in the future is essential for society. Most forecasts rely on a mechanical extrapolation of past mortality trends, which leads to unreliable outcomes because of temporal fluctuations in the past trends due to lifestyle 'epidemics'. Methods: We project life expectancy for 18 European countries by taking into account the impact of smoking, obesity, and alcohol on mortality, and the mortality experiences of forerunner populations. Results: We project that life expectancy in these 18 countries will increase from, on average, 83.4 years for women and 78.3 years for men in 2014 to 92.8 years for women and 90.5 years for men in 2065. Compared to others (Lee-Carter, Eurostat, United Nations), we project higher future life expectancy values and more realistic differences between countries and sexes. Conclusions: Our results imply longer individual lifespans, and more elderly in society. Funding: Netherlands Organisation for Scientific Research (NWO) (grant no. 452-13-001).

On average, in Europe, men can currently expect to live till the age of 75 and women until they are 82. But what will their lifespans be in the next decades? Reliable answers to this question are essential to help governments plan for future health care and social security costs. While medical improvements are likely to further extend lifespans, lifestyle factors can result in temporal distortions of this trend. Yet, most estimates of future life expectancy fail to consider changing lifestyles, as they only use past mortality trends in their calculations. This can make these projections unreliable: for example, increases in smoking rates among Northern and Western European men led to stagnating male life expectancies in the 1950s and 1960s, but these picked up again after smoking declined. The same pattern is showing for women, except it is lagging as they took up smoking later than men. Based simply on the extrapolation of past mortality trends, current projection models fail to consider the past and predicted modifications of life expectancy trends prompted by changing rates of health behaviours ­ such as increases followed by (anticipated) declines in alcohol consumption and obesity rates, similar to what was observed with smoking. To produce a more reliable forecast, Janssen et al. incorporated trends in smoking, obesity, and alcohol use into life expectancy projections for 18 European countries. The predictions suggest that life expectancy for women in these countries will increase from 83.4 years in 2014 to 92.8 years in 2065. For men, it will also go up, from 78.3 to 90.5 years. In the future, this integrative approach may help to track the effects of health-behaviour related prevention policies on life expectancy, and allow scientists to account for changes caused by the COVID-19 pandemic. In the meantime, these estimates are higher than those obtained using more traditional methods; they suggest that communities should start to adjust to the possibility of longer individual lifespans, and of larger numbers of elderly people in society.

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.

Past and Future Alcohol-Attributable Mortality in Europe.

Although alcohol consumption is an important public health issue in Europe, estimates of future alcohol-attributable mortality for European countries are rare, and only apply to the short-term future. We project (age-specific) alcohol-attributable mortality up to 2060 in 26 European countries, after a careful assessment of past trends. For this purpose we used population-level country-, sex-, age- (20-84) and year-specific (1990-2016) alcohol-attributable mortality fractions (AAMF) from the Global Burden of Disease (GBD) study, which we adjusted at older ages. To these data we apply an advanced age-period-cohort projection methodology, that avoids unrealistic future differences and crossovers between sexes and countries. We project that in the future, AAMF levels will decline in all countries, and will converge across countries and sexes. For 2060, projected AAMF are, on average, 5.1% among men and 1.4% among women, whereas in 2016 these levels were 10.1% and 3.3%, respectively. For men, AAMF is projected to be higher in Eastern and South-western Europe than in North-western Europe. All in all, the share of mortality due to alcohol is projected to eventually decline in all 26 European countries. Achieving these projected declines will, however, require strong ongoing public health action, particularly for selected Eastern and North-western European countries.

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.

Effects of changes in living environment on physical health: a prospective German cohort study of non-movers.

BACKGROUND: Longitudinal studies on associations between changes in living environment and health are few and focus on movers. Next to causal effects, differences in health can, however, result due to residential mobility. The present study explored changes in living environment related to (changes in) physical health among non-movers. Causality was reinforced by a novel study design. METHODS: We obtained longitudinal data on both living environment and physical health covering 4601 non-movers aged 18+ with 16 076 health observations from the German Socio-Economic Panel between 1999 and 2014. Changing and stable perceived living environment from three domains (infrastructure, environmental pollution, housing conditions) were included at household level. We performed linear regressions with robust standard errors and generalized estimating equations to predict the physical component summary (PCS) at baseline and changes in PCS over time. RESULTS: Stable moderate and worst as well as worsened environmental pollution and infrastructure were associated with worse PCS at baseline, as were stable poor and worsened housing conditions. Stable worst infrastructure was associated with negative changes in PCS for both sexes. Men's changes in PCS were more affected by worsened environmental pollution than women's. CONCLUSION: A suboptimal living environment has short- and long-term negative effects on physical health. Because even short-term changes in the living environment have an immediate influence on an individual's health status and health trajectories, public attention to living environment is essential to fight existing health inequalities.

Differences in the health transition patterns of migrants and non-migrants aged 50 and older in southern and western Europe (2004-2015).

BACKGROUND: Most previous research on migrant health in Europe has taken a cross-sectional perspective, without a specific focus on the older population. Having knowledge about inequalities in health transitions over the life course between migrants and non-migrants, including at older ages, is crucial for the tailoring of policies to the demands of an ageing and culturally diverse society. We analyse differences in health transitions between migrants and non-migrants, specifically focusing on the older population in Europe. METHODS: We used longitudinal data on migrants and non-migrants aged 50 and older in 10 southern and western European countries from the Survey of Health, Ageing and Retirement in Europe (2004-2015). We applied multinomial logistic regression models of experiencing health deterioration among individuals in good health at baseline, and of experiencing health improvement among individuals in poor health at baseline, separately by sex, in which migrant status (non-migrant, western migrant, non-western migrant) was the main explanatory variable. We considered three dimensions of health, namely self-rated health, depression and diabetes. RESULTS: At older ages, migrants in Europe were at higher risk than non-migrants of experiencing a deterioration in health relative to remaining in a given state of self-rated health. Western migrants had a higher risk than non-migrants of becoming depressed, while non-western migrants had a higher risk of acquiring diabetes. Among females only, migrants also tended to be at lower risk than non-migrants of experiencing an improvement in both overall and mental health. Differences in the health transition patterns of older migrants and non-migrants remained robust to the inclusion of several covariates, including education, job status and health-related behaviours. CONCLUSIONS: Our findings indicate that, in addition to having a health disadvantage at baseline, older migrants in Europe were more likely than older non-migrants to have experienced a deterioration in health over the study period. These results raise concerns about whether migrants in Europe are as likely as non-migrants to age in good health. We recommend that policies aiming to promote healthy ageing specifically address the health needs of the migrant population, thereby distinguishing migrants from different backgrounds.

Relative contribution of various chronic diseases and multi-morbidity to potential disability among Dutch elderly.

BACKGROUND: The amount of time spent living with disease greatly influences elderly people's wellbeing, disability and healthcare costs, but differs by disease, age and sex. METHODS: We assessed how various single and combined diseases differentially affect life years spent living with disease in Dutch elderly men and women (65+) over their remaining life course. Multistate life table calculations were applied to age and sex-specific disease prevalence, incidence and death rates for the Netherlands in 2007. We distinguished congestive heart failure, coronary heart disease (CHD), breast and prostate cancer, colon cancer, lung cancer, diabetes, COPD, stroke, dementia and osteoarthritis. RESULTS: Across ages 65, 70, 75, 80 and 85, CHD caused the most time spent living with disease for Dutch men (from 7.6 years at age 65 to 3.7 years at age 85) and osteoarthritis for Dutch women (from 11.7 years at age 65 to 4.8 years at age 85). Of the various co-occurrences of disease, the combination of diabetes and osteoarthritis led to the most time spent living with disease, for both men (from 11.2 years at age 65 to 4.9 -years at age 85) and women (from 14.2 years at age 65 to 6.0 years at age 85). CONCLUSIONS: Specific single and multi-morbid diseases affect men and women differently at different phases in the life course in terms of the time spent living with disease, and consequently, their potential disability. Timely sex and age-specific interventions targeting prevention of the single and combined diseases identified could reduce healthcare costs and increase wellbeing in elderly people.

An Assessment and Extension of the Mechanism-Based Approach to the Identification of Age-Period-Cohort Models.

Many methods have been proposed to solve the age-period-cohort (APC) linear identification problem, but most are not theoretically informed and may lead to biased estimators of APC effects. One exception is the mechanism-based approach recently proposed and based on Pearl's front-door criterion; this approach ensures consistent APC effect estimators in the presence of a complete set of intermediate variables between one of age, period, cohort, and the outcome of interest, as long as the assumed parametric models for all the relevant causal pathways are correct. Through a simulation study mimicking APC data on cardiovascular mortality, we demonstrate possible pitfalls that users of the mechanism-based approach may encounter under realistic conditions: namely, when (1) the set of available intermediate variables is incomplete, (2) intermediate variables are affected by two or more of the APC variables (while this feature is not acknowledged in the analysis), and (3) unaccounted confounding is present between intermediate variables and the outcome. Furthermore, we show how the mechanism-based approach can be extended beyond the originally proposed linear and probit regression models to incorporate all generalized linear models, as well as nonlinearities in the predictors, using Monte Carlo simulation. Based on the observed biases resulting from departures from underlying assumptions, we formulate guidelines for the application of the mechanism-based approach (extended or not).

Differences in healthy life expectancy between older migrants and non-migrants in three European countries over time.

OBJECTIVES: We analysed differences in healthy life expectancy at age 50 (HLE50) between migrants and non-migrants in Belgium , the Netherlands, and England and Wales, and their trends over time between 2001 and 2011 in the latter two countries. METHODS: Population, mortality and health data were derived from registers, census or surveys. HLE50 and the share of remaining healthy life years were calculated for non-migrants, western and non-western migrants by sex. We applied decomposition techniques to answer whether differences in HLE50 between origin groups and changes in HLE50 over time were attributable to either differences in mortality or health. RESULTS: In all three countries, older (non-western) migrants could expect to live less years in good health than older non-migrants. Differences in HLE50 between migrants and non-migrants diminished over time in the Netherlands, but they increased in England and Wales. General health, rather than mortality, mainly explained (trends in) inequalities in healthy life expectancy between migrants and non-migrants. CONCLUSIONS: Interventions aimed at reducing the health and mortality inequalities between older migrants and non-migrants should focus on prevention, and target especially non-western migrants.

Differences in mortality between groups of older migrants and older non-migrants in Belgium, 2001-09.

BACKGROUND: European societies are rapidly ageing and becoming multicultural. We studied differences in overall and cause-specific mortality between migrants and non-migrants in Belgium specifically focusing on the older population. METHODS: We performed a mortality follow-up until 2009 of the population aged 50 and over living in Flanders and the Brussels-Capital Region by linking the 2001 census data with the population and mortality registers. Overall mortality differences were analysed via directly age-standardized mortality rates. Cause-specific mortality differences between non-migrants and various western and non-western migrant groups were analysed using Poisson regression models, controlling for age (model 1) and additionally controlling for socio-economic status and urban typology (model 2). RESULTS: At older ages, most migrants had an overall mortality advantage relative to non-migrants, regardless of a lower socio-economic status. Specific migrant groups (e.g. Turkish migrants, French and eastern European male migrants and German female migrants) had an overall mortality disadvantage, which was, at least partially, attributable to a lower socio-economic status. Despite the general overall mortality advantage, migrants experienced higher mortality from infectious diseases, diabetes-related causes, respiratory diseases (western migrants), cardiovascular diseases (non-western female migrants) and lung cancer (western female migrants). CONCLUSION: Mortality differences between older migrants and non-migrants depend on cause of death, age, sex, migrant origin and socio-economic status. These differences can be related to lifestyle, social networks and health care use. Policies aimed at reducing mortality inequalities between older migrants and non-migrants should address the specific health needs of the various migrant groups, as well as socio-economic disparities.

Can selective migration explain why health is worse in regions with population decline?: A study on migration and self-rated health in the Netherlands.

BACKGROUND: Health disparities between population declining and non-declining areas have received little attention, even though population decline is an established phenomenon in Europe. Selective migration, in which healthier people move out of deprived areas, can possibly explain worse health in declining regions. We assessed whether selective migration can explain the observed worse average health in declining regions as compared with non-declining regions in the Netherlands. METHODS: Combining data from the Dutch Housing and Living Survey held in 2002 and 2006 with Dutch registry data, we studied the relation between health status and migration in a 5-year period at the individual level by applying logistic regression. In our sample of 130,600 participants, we compared health status, demographic and socioeconomic factors of movers and stayers from declining and non-declining regions. RESULTS: People in the Netherlands who migrated are healthier than those staying behind [odds ratio (OR): 1.80]. This effect is larger for persons moving out of declining regions (OR: 1.76) than those moving into declining regions (OR: 1.47). When controlled for demographic and socioeconomic characteristics, these effects are not significant. Moreover, only a small part of the population migrates out of (0.29%) or into (0.25%) declining regions in the course of 5 years. CONCLUSION: Despite the relation between health and migration, the effect of selective migration on health differences between declining and non-declining regions in the Netherlands is small. Both health and migration are complexly linked with socioeconomic and demographic factors.

Role of smoking in regional variation in mortality in Poland.

AIMS: We assess the effect of smoking on regional disparities in mortality in Poland and its contribution to the change in regional disparities during the last two decades. DESIGN, SETTING AND PARTICIPANTS: We used population-level mortality data from the population registry for 379 Nomenclature of Territorial Units for Statistics (NUTS)-4 Polish regions for 1991-93 and 2008-10. MEASUREMENTS: The importance of smoking was assessed by smoking-attributable mortality (SAM) derived using a simplified indirect Peto-Lopez method. Regional differences in age-standardized all-cause, smoking- and non-smoking-attributable mortality (NSAM) rates at ages 35 years and over were mapped, and spatial clustering (Moran's I) and coefficients of variation (CV) were estimated. The contribution of SAM to variation in all-cause mortality was assessed by variance decomposition and compared over time. FINDINGS: In 2008-10, all-cause and SAM rates were characterized by a similar pattern of spatial clustering (Moran's I > 0.44, P < 0.0001). For NSAM, a more random pattern with less regional clustering showed (Moran's I = 0.34, P < 0.0001). The contribution of smoking to regional variation was substantial [54%, 95% confidence interval (CI) = 44.9, 62.5 among men; 24.9%, 95% CI = 20.9, 29.1 among women], and compared with 1991-93, 27.5 percentage points lower for men and 6.3 percentage points higher for women. Smoking contributed to the divergence between the regions in all-cause mortality between 1991-93 and 2008-10 for men [increase in CV of SAM by 2% (0, 4%)], but not for women [decrease in CV of SAM by 15% (22, 10%)]. CONCLUSIONS: 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.

Using spatial analysis to predict health care use at the local level: a case study of type 2 diabetes medication use and its association with demographic change and socioeconomic status.

Local health status and health care use may be negatively influenced by low local socio-economic profile, population decline and population ageing. To support the need for targeted local health care, we explored spatial patterns of type 2 diabetes mellitus (T2DM) drug use at local level and determined its association with local demographic, socio-economic and access to care variables. We assessed spatial variability in these associations. We estimated the five-year prevalence of T2DM drug use (2005-2009) in persons aged 45 years and older at four-digit postal code level using the University of Groningen pharmacy database IADB.nl. Statistics Netherlands supplied data on potential predictor variables. We assessed spatial clustering, correlations and estimated a multiple linear regression model and a geographically weighted regression (GWR) model. Prevalence of T2DM medicine use ranged from 2.0% to 25.4%. The regression model included the extent of population ageing, proportion of social welfare/benefits, proportion of low incomes and proportion of pensioners, all significant positive predictors of local T2DM drug use. The GWR model demonstrated considerable spatial variability in the association between T2DM drug use and above predictors and was more accurate. The findings demonstrate the added value of spatial analysis in predicting health care use at local level.

Association between gross domestic product throughout the life course and old-age mortality across birth cohorts: parallel analyses of seven European countries, 1950-1999.

Mortality levels of national populations have often been studied in relation to levels of gross domestic product (GDP) at time of death. Following the life course perspective, we assessed whether old-age mortality levels for subsequent cohorts are differentially associated with GDP levels prevailing at different ages of the cohorts. We used all-cause and cause-specific mortality data by sex, age at death (65-99), year at death (1950-1999), and year of birth (1865-1924) for Denmark, England and Wales, Finland, France, the Netherlands, Norway, and Sweden. Trends in national GDP per capita between 1865 and 1999 were reconstructed from historical national accounts data. Through Poisson regression analyses, we determined for each country both univariate and multivariate associations across five-year birth cohorts between mortality and GDP levels prevailing at time of death, and at earlier ages of the cohorts (i.e. 0-5, 6-19, 20-49, and 50-64). For the subsequent cohorts, levels of GDP at time of death were strongly inversely associated with all-cause mortality, especially among women, and among men in England and Wales, Finland, and France. In most countries, stronger associations were observed with GDP levels prevailing at earlier ages of the cohorts. After control for GDP at time of death, these associations remained. An independent association of GDP at earlier ages of the cohort was also observed for cause-specific mortality. The associations were negative for ischaemic heart diseases, cerebrovascular diseases, and stomach cancer. They were positive for prostate cancer, breast cancer, COPD (women), and lung cancer (women). GDP prevailing at ages 20-49 (men) and ages 50-64 (women) had the largest associations with old-age mortality. These findings suggest an independent, mostly negative effect of GDP prevailing at earlier ages of subsequent cohorts on old-age mortality. Socio-economic circumstances during adulthood and middle age seem more important in determining old-age mortality trends than those during infancy or childhood.