Educational inequalities in major depressive disorder prevalence, timing and duration among adults over the life course: a microsimulation analysis based on the Lifelines Cohort Study.

BACKGROUND: Educational inequalities in major depressive disorder (MDD) pose a major challenge. Tackling this issue requires evidence on the long-term impact of intervening on modifiable factors, for example lifestyle and psychosocial factors. For this reason, we aimed to simulate the development of educational inequalities in MDD across the life course, and to estimate the potential impact of intervening on modifiable factors. METHODS: We used data from the prospective Dutch Lifelines Cohort Study to estimate the required input for a continuous-time microsimulation. The microsimulation allowed us to project the development of educational inequalities in MDD between ages 18 and 65, and to assess the potential benefit of intervening on quality of social contacts, health literacy and smoking. RESULTS: On average, an additional 19.1% of individuals with low education will ever experience MDD between ages 18 and 65 compared with those with high education. Additionally, individuals with low education generally will develop MDD 0.9 years earlier and spend 1.2 years more with MDD, than individuals with high education. Improving the quality of social contacts in individuals with low education produced the largest effect; it would reduce the inequalities in the prevalence, onset and duration of MDD by an average of 18.4%, 18.3% and 28.6%, respectively. CONCLUSIONS: Intervening on modifiable factors, particularly quality of social contacts, in individuals with low education could help reduce the estimated educational inequalities in MDD over the life course.

Educational inequalities in metabolic syndrome prevalence, timing, and duration amongst adults over the life course: a microsimulation analysis based on the lifelines cohort study.

BACKGROUND: Educational inequalities in metabolic syndrome (MetS) are a growing public health concern. Intervening on modifiable factors may help reduce these inequalities, but there is a need for evidence on the long-term impact of intervening on these factors. Thus, we simulate the development of educational inequalities in MetS across the life course and assess the impact of intervening on the modifiable factors that contribute to these inequalities. METHODS: We used data from the prospective multigenerational Dutch Lifelines Cohort Study to estimate the required input for a continuous-time microsimulation. The microsimulation projects the development of educational inequalities in MetS between ages 18 and 65, and assesses the potential benefit of intervening on smoking, alcohol use, diet quality, and health literacy. FINDINGS: The likelihood of ever experiencing MetS between ages 18 and 65 varies from 32.5% among high educated women to 71.5% among low educated men. On average, 27.6% more individuals with low education will ever experience MetS between ages 18 and 65 compared to those with high education. Additionally, individuals with low education generally will develop MetS 2.3 years earlier, and will spend an extra 2.6 years with MetS, compared to individuals with high education. Changes to smoking behaviours in individuals with low education produced the largest effect; it would reduce inequalities in prevalence, timing and duration by an average of 7.5%, 9.5%, and 6.9%, respectively. CONCLUSIONS: Interventions targeting the modifiable factors included in this study, especially smoking, could help reduce the estimated educational inequalities in MetS over the life course.

Microsimulation of Household and Marital Transitions Leading to Childlessness Among Dutch Women Born Between 1971 and 2000.

After reaching historically low levels among the women born in the early 1940s, childlessness has been increasing in most Western countries among women born in the 1950s and 1960s. This increase took place as patterns of transition to adulthood have become increasingly late, protracted, and complex. Yet, it is precisely those women who enter a first relationship late, spend more time as single, and experience union instability who more often remain childless. This suggests that levels of childlessness will continue to increase as younger cohorts complete their childbearing histories. In this study, we use microsimulation to project the household and union formation histories of cohorts of Dutch women born between 1971 and 2000. Results suggest that childlessness will actually decrease among cohorts born between 1971 and 1983 and then increase among those born between 1984 and 2000. The decrease occurs as pathways of household and union formation become later, more protracted, and more complex, but also as cohabiting women start to exhibit a higher propensity to become mothers. The increase, on the other hand, occurs as pathways become somewhat less protracted and complex, but also as the propensity of cohabiting women to become mothers returns to previous levels and as age at leaving the parental home strongly rises. Childlessness levels appear to increasingly depend on the childbearing decisions of cohabiting couples and on age at leaving the parental home.

Unequally ageing regions of Europe: Exploring the role of urbanization.

Since young adults tend to move from rural to urban regions, whereas older adults move from urban to rural regions, we may expect to see increasing differences in population ageing across urban and rural regions. This paper examines whether trends in population ageing across urban and rural NUTS-2 regions of the EU-27 have diverged over the period 2003-13. We use the methodological approach of convergence analysis, quite recently brought to demography from the field of economic research. Unlike classical beta and sigma approaches to convergence, we focus not on any single summary statistic of convergence, but rather analyse the whole cumulative distribution of regions. Such an approach helps to identify which specific group of regions is responsible for the major changes. Our results suggest that, despite expectations, there was no divergence in age structures between urban and rural regions; rather, divergence happened within each of the groups of regions.

A new parametric model to assess delay and compression of mortality.

BACKGROUND: A decrease in mortality across all ages causes a shift of the age pattern of mortality, or mortality delay, while differences in the rate of decrease across ages cause a change in the shape of the age-at-death distribution, mortality compression or expansion. Evidence exists for both compression and delay of mortality. Existing parametric models to describe the full age pattern of mortality are not able to capture mortality delay versus mortality compression. More recent models that assess delay versus compression mostly focused on the adult or old ages alone and did not distinguish mortality compression below and above the modal age at death, although they represent different mechanisms. METHODS: This paper presents a new parametric model that describes the full age pattern of mortality and assesses compression - at different stages of life - and delay of mortality: the CoDe model. The model includes 10 parameters, of which five are constant over time. The five time-varying parameters reflect delay of mortality and compression of mortality in infancy, adolescence, young adulthood, late adulthood, and old age. The model describes infant and background mortality by two simple functions, uses a mixed logistic model with different slopes in adult, middle, and old age, and includes the modal age at death as a parameter to account for the delay in mortality. RESULTS: Applying the CoDe model to age-specific probabilities of death for Japanese, French, American, and Danish men and women between 1950 and 2010 showed a very good fit of the full age pattern of mortality. Delay of mortality explained about two-thirds of the increase in life expectancy at birth, whereas compression of mortality due to mortality declines in young age explained about one-third. No strong compression of mortality in late adulthood age was observed. Mortality compression in old age has had a small negative impact on life expectancy. CONCLUSIONS: The CoDe model proved a valid instrument for describing the full age pattern of mortality and for disentangling the effects of mortality delay and compression - at different stages of life - on the increase in life expectancy.

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.

Mortality in 272 European regions, 2002-2004. An update.

This paper presents a comprehensive update of life expectancy and mortality in 2002-2004 in the modern European Union (EU-27) and EFTA countries. We focus on causes of death at younger ages (0-64 year). EUROSTAT delivered updated population numbers and mortality data by sex, age and cause of death for 272 NUTS-2 regions. We compared mortality by life tables, cause decomposition life tables and age standardized rates. Gini coefficients estimated inequity of death rates over the regions. Life expectancy at birth in the EU-27 was 75.1 years (men) and 81.3 years (women). The difference between the 10th and 90th percentile of 272 regions was 8.0 (men) and 5.6 years (women). Men lived 6.1 years shorter in the new member states (NMS, new members since 2004) than in the EU-15 (members before 2004), women 3.9 years. 60% (men) and 33% (women) of the differences in life expectancy between EU 15 and NMS were explained by mortality under age 65. The main causes explaining differences in life expectancy were ischemic and other heart disease, stroke, alcohol related mortality, lung cancer and injuries. The fraction of ill defined causes of death was large and very variable between countries. Mortality differences in the EU-27 are dominated by smoking, alcohol, diseases related to diet and a sedentary lifestyle, unsafe roads and differences in health care performance. Closing the health gap is feasible and ought to be a major target of the European Union, but monitoring will need better registration of causes of death.

Comparison of Population Aging in Europe and Asia Using a Time-Consistent and Comparative Aging Measure.

Objective: We compare population aging in Europe and Asia using a measure that is both consistent over time and appropriate for cross-country comparison. Method: Sanderson and Scherbov proposed to estimate the old-age threshold by the age at which the remaining life expectancy (RLE) equals 15 years. We propose an adjustment of this measure, taking into account cross-national differences in the exceptionality of reaching that age. Results: Our old-age threshold was lower than 65 years in 2012 in Central Asia, Southern Asia, Southeastern Asia, and many Eastern European countries. These populations also experienced a higher share of elderly compared with the RLE15 method. Our method revealed more geographical diversity in the shares of elderly. Both methods exhibited similar time trends for the old-age thresholds and the shares of elderly. Discussion: Our prospective and comparative measure reveals higher population aging estimates in most Asian and Eastern European countries and more diversity in aging.

Work Ability Trajectories and Retirement Pathways: A Longitudinal Analysis of Older American Workers.

OBJECTIVE: To determine whether older workers who follow different work ability (WA) trajectories tend to follow different retirement pathways. METHODS: Nationally representative data on Americans born between 1943 and 1948. Latent class growth modeling to estimate trajectories of work ability between ages 53-54 and 65-66. Multinomial log-linear models to assess the association between WA trajectories and retirement pathways. RESULTS: Three WA trajectories were identified: high (74%), declining (17%), and low (9%). Low WA leads more often to an early-gradual retirement. Declining WA leads to both early-gradual and early-crisp retirements. CONCLUSIONS: Workers with low and declining WA are more at risk of unemployment, disability, and inactivity prior to retirement; workers with declining WA are also likely to make a direct transition to early retirement. Future changes to social security should consider inter-individual variation over time in WA.

Decomposition of regional convergence in population aging across Europe.

In the face of rapidly aging population, decreasing regional inequalities in population composition is one of the regional cohesion goals of the European Union. To our knowledge, no explicit quantification of the changes in regional population aging differentiation exist. We investigate how regional differences in population aging developed over the last decade and how they are likely to evolve in the coming three decades, and we examine how demographic components of population growth contribute to the process. We use the beta-convergence approach to test whether regions are moving towards a common level of population aging. The change in population composition is decomposed into the separate effects of changes in the size of the non-working-age population and of the working-age population. The latter changes are further decomposed into the effects of cohort turnover, migration at working ages, and mortality at working ages. European Nomenclature of Territorial Units for Statistics (NUTS)-2 regions experienced notable convergence in population aging during the period 2003-2012 and are expected to experience further convergence in the coming three decades. Convergence in aging mainly depends on changes in the population structure of East-European regions. Cohort turnover plays the major role in promoting convergence. Differences in mortality at working ages, though quite moderate themselves, have a significant cumulative effect. The projections show that when it is assumed that net migration flows at working ages are converging across European regions, this will not contribute to convergence of population aging. The beta-convergence approach proves useful to examine regional variations in population aging across Europe.

Disentangling rectangularization and life span extension with the moving rectangle method.

PURPOSE: The moving rectangle method is used to disentangle the contributions of rectangularization and life span extension to the increase in life expectancy. It requires the choice of an endpoint of the survival curve that approaches the maximum age at death. We examined the effect of choosing different end points on the outcomes of this method. METHODS: For five developed countries, survival curves from age 50 years were constructed per calendar year from 1922 onward. Survival values of 0.1, 0.01, and 0.001 were chosen as end points of the survival curve, and the contributions of rectangularization and life span extension to the increase in life expectancy were calculated using the moving rectangle method. RESULTS: The choice of different survival values as end points profoundly influenced the estimated contributions of rectangularization and life span extension to the increase in life expectancy. When choosing 0.001, rectangularization contributed most years, whereas when choosing 0.1, life span extension contributed most years. CONCLUSIONS: When the moving rectangle method is used to estimate the contributions of rectangularization and life span extension to the increase in life expectancy, its outcomes depend on the choice of the endpoint of the survival curve.

European Regional Populations: Current Trends, Future Pathways, and Policy Options.

Europe is currently experiencing an ageing population and slowing population growth of both the total and working-age populations. These trends are likely to continue. Even though population ageing will affect all European regions, different regions will be affected in different ways. Even under favorable conditions, 35-40 % of all NUTS2 regions will face a labor force decline. If economic conditions are poor, some regions may continue to grow, but 55-70 % of the regions will see a labor force decline by 10 % or more. In most regions of Eastern Europe, the labor force may decrease by more than 30 %. To keep regions prosperous (maintaining competitiveness) and to avoid worse inequality (maintaining cohesion), policy-makers must find ways to cope with these challenges through new fiscal and social policies, though policies directly affecting demographic and migratory trends may also be needed.

Overcoming the Problems of Inconsistent International Migration data: A New Method Applied to Flows in Europe.

Due to differences in definitions and measurement methods, cross-country comparisons of international migration patterns are difficult and confusing. Emigration numbers reported by sending countries tend to differ from the corresponding immigration numbers reported by receiving countries. In this paper, a methodology is presented to achieve harmonised estimates of migration flows benchmarked to a specific definition of duration. This methodology accounts for both differences in definitions and the effects of measurement error due to, for example, under reporting and sampling fluctuations. More specifically, the differences between the two sets of reported data are overcome by estimating a set of adjustment factors for each country's immigration and emigration data. The adjusted data take into account any special cases where the origin-destination patterns do not match the overall patterns. The new method for harmonising migration flows that we present is based on earlier efforts by Poulain (European Journal of Population, 9(4): 353-381 1993, Working Paper 12, joint ECE-Eurostat Work Session on Migration Statistics, Geneva, Switzerland 1999) and is illustrated for movements between 19 European countries from 2002 to 2007. The results represent a reliable and consistent set of international migration flows that can be used for understanding recent changes in migration patterns, as inputs into population projections and for developing evidence-based migration policies.