Can changes in education alter future population ageing in Asia and Europe?

While population ageing is rising, the educational composition of the elderly remains rather heterogeneous. This study assesses the educational differences in future population ageing in Asia and Europe, and how future population ageing in Asia and Europe would change if the educational composition of its populations changed. A comparative population ageing measure (the Comparative Prospective Old-Age Threshold [CPOAT]) was used, which recalculates old-age thresholds after accounting for differences in life expectancy, and the likelihood of adults surviving to higher ages. Combined data from projected age- and sex-specific life-tables (from the United Nations) and projected age- and sex-specific survival ratios by different levels of education (from the Wittgenstein Centre for Demography and Global Human Capital) were used to construct projected life-tables (2015-2020, …, 2045-2050) by educational level and sex for different regions of Asia and Europe. Based on these life-tables, future comparative prospective old-age thresholds by educational level and sex were calculated. It was found that in both Asia and Europe, and among both men and women, the projected old-age thresholds are higher for higher educated people than for less-educated people. While Europe has a larger projected share of elderly in the population than Asia, Europe's older population is better educated. In alternative future scenarios in which populations hypothetically have higher levels of education, the projected shares of elderly in the population decrease across all regions of Asia and Europe, but more so in Asia. The results highlight the effectiveness of investing in education as a policy response to the challenges associated with population ageing in Asia and Europe. Such investments are more effective in the Asian regions, where the educational infrastructure is less developed.

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.

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.

Comparing strategies for matching mortality forecasts to the most recently observed data: exploring the trade-off between accuracy and robustness.

BACKGROUND: Given the increased link between retirement age and payments to the development in life expectancy, a precise and regular forecast of life expectancy is of utmost importance. The choice of the jump-off rates, i.e. the rates in the last year of the fitting period, is essential for matching mortality forecasts to the most recently observed data. A general approach to the choice of the jump-off rates is currently lacking. OBJECTIVE: We evaluate six different options for the jump-off rates and examine their effects on the robustness and accuracy of the mortality forecast. DATA AND METHODS: Death and exposure numbers by age for eight European countries over the years 1960-2014 were obtained from the Human Mortality Database. We examined the use of model values as jump-off rates versus observed values in the last year or averaged over the last couple of years. The future life expectancy at age 65 is calculated for different fitting periods and jump-off rates using the Lee-Carter model and examined on accuracy (mean absolute forecast error) and robustness (standard deviation of the change in projected e65). RESULTS: The choice for the jump-off rates clearly influences the accuracy and robustness of the mortality forecast, albeit in different ways. For most countries using the last observed values as jump-off rates resulted in the most accurate method, which relates to the relatively high estimation error of the model in recent years. The most robust method is obtained by using an average of observed years as jump-off rates. The more years that are averaged, the better the robustness, but accuracy decreases with more years averaged. CONCLUSION: Carefully considering the best choice for the jump-off rates is essential when forecasting mortality. The best strategy for matching mortality forecasts to the most recently observed data depends on the goal of the forecast, the country-specific past mortality trends observed, and the model fit.

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.

The future of smoking-attributable mortality: the case of England & Wales, Denmark and the Netherlands.

AIMS: We formally estimate future smoking-attributable mortality up to 2050 for the total national populations of England & Wales, Denmark and the Netherlands, providing an update and extension of the descriptive smoking-epidemic model. METHODS: We used smoking prevalence and population-level lung cancer mortality data for England & Wales, Denmark and the Netherlands, covering the period 1950-2009. To estimate the future smoking-attributable mortality fraction (SAF) we: (i) project lung cancer mortality by extrapolating age-period-cohort trends, using the observed convergence of smoking prevalence and similarities in past lung cancer mortality between men and women as input; and (ii) add other causes of death attributable to smoking by applying a simplified version of the indirect Peto-Lopez method to the projected lung cancer mortality. FINDINGS: The SAF for men in 2009 was 19% (44 872 deaths) in England & Wales, 22% (5861 deaths) in Denmark and 25% (16 385 deaths) in the Netherlands. In our projections, these fractions decline to 6, 12 and 14%, respectively, in 2050. The SAF for women peaked at 14% (38 883 deaths) in 2008 in England & Wales, and is expected to peak in 2028 in Denmark (22%) and in 2033 in the Netherlands (23%). By 2050, a decline to 9, 17 and 19%, respectively, is foreseen. Different indirect estimation methods of the SAF in 2050 yield a range of 1-8% (England & Wales), 8-13% (Denmark) and 11-16% (the Netherlands) for men, and 7-16, 12-26 and 13-31% for women. CONCLUSIONS: From northern European data we project that smoking-attributable mortality will remain important for the future, especially for women. Whereas substantial differences between countries remain, the age-specific evolution of smoking-attributable mortality remains similar across countries and between sexes.

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.

Including the smoking epidemic in internationally coherent mortality projections.

We present a new mortality projection methodology that distinguishes smoking- and non-smoking-related mortality and takes into account mortality trends of the opposite sex and in other countries. We evaluate to what extent future projections of life expectancy at birth (e 0) for the Netherlands up to 2040 are affected by the application of these components. All-cause mortality and non-smoking-related mortality for the years 1970-2006 are projected by the Lee-Carter and Li-Lee methodologies. Smoking-related mortality is projected according to assumptions on future smoking-attributable mortality. Projecting all-cause mortality in the Netherlands, using the Lee-Carter model, leads to high gains in e 0 (4.1 for males; 4.4 for females) and divergence between the sexes. Coherent projections, which include the mortality experience of the other 21 sex- and country-specific populations, result in much higher gains for males (6.4) and females (5.7), and convergence. The separate projection of smoking and non-smoking-related mortality produces a steady increase in e 0 for males (4.8) and a nonlinear trend for females, with lower gains in e 0 in the short run, resulting in temporary sex convergence. The latter effect is also found in coherent projections. Our methodology provides more robust projections, especially thanks to the distinction between smoking- and non-smoking-related mortality.

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.

Effects of the fertility transition on birth seasonality in the Netherlands.

Synchronous with the decline in fertility that took place in the post-war period in the Netherlands, patterns of birth seasonality changed as well. In this paper seasonal fluctuations in fertility in the Netherlands are examined using population register data for the period 1952 to 2005. The peak in births has changed from spring to summer and subsequently to August/September, thereby shifting from the European to the American pattern. The seasonal shift can be attributed to parity-specific changes. Before the transition, birth seasonality did not differ much between the different parities. In the transition period from higher to low fertility, differences between parities increased which persist up to today. At present, the overall seasonality pattern is determined by first births. Moreover, birth seasonality varies by maternal age. The findings stimulate the discussion on the role of planning as a cause of birth seasonality.