Population ageing in Central and Eastern Europe and its demographic and social context

Abstract

The article focuses on several demographic and socio-economic idiosyncrasies in Central and Eastern Europe, which impact the process of population ageing and intergenerational relations. These include the adverse mortality trends and especially the excess male mortality in certain countries, which exacerbated sex differences in life expectancy beyond anything ever recorded in peace-time population history, the combination of natural population decrease and net emigration, the disordered cohort flows and the shorter generational length. The rapid demographic change in these countries coincided with political, economic and social transformations. The shock of the fall of communism affected differently younger people, who could relatively easily reorganize their life cycles so as to adapt to the changed circumstances, and older persons for whom such reorganization was more difficult, or even impossible. This created the possibility for the opening of an intergenerational rift, as older generations felt being the losers of the transition. The article explores the implications of these idiosyncrasies and social context for living arrangements, kin networks, individual wellbeing and inter-generational relations, and identifies areas where particular challenges are likely to be faced when it comes to policies and programs aimed at older persons.

Introduction

Central and Eastern Europe is becoming increasingly diverse, not just socially and economically, but also demographically, as the countries in the region follow different development paths and vary in terms of the speed of the social, economic and political transformation that they are undergoing. Several groupings of countries/sub-regions are becoming clearly distinguishable geo-politically and distinct demographically. These include the new member states of the European Union (with a further distinction between the 8 countries that joined in 2004 on one hand, and Bulgaria and Romania on the other), the countries in South-Eastern Europe, many of which experienced ethnic strife following the fall of communism, and the European parts of the Commonwealth of Independent States (CIS).1

On the other hand, shared recent past continues to put an imprint on the demographic trends and patterns in these countries. Part of this imprint is a result of the inherent inertia of demographic processes. Another part is linked to the pronounced inter-cohort differences that emerged between the generations impacted by the communist rule and those raised after the fall of the Berlin wall. This article focuses on several features, which are shared by many of the countries in the region and influence directly or indirectly the process of population ageing and its social and economic implications. I argue that there are at least five such features with few if any parallels in world population history (including the adverse mortality trends and especially excess male mortality in certain countries, the combination of natural population decrease and net emigration, the disordered cohort flows, the ‘interference’ between demographic change and economic and political transition, and short generational length), which have wide-ranging implications for inter-generational relations, kin availability, living arrangements and individual wellbeing, and which merit the special attention of both researchers and policy makers.

Ageing without living longer

The adverse morbidity and mortality trends that the former Soviet Union and some of the other countries in Central and Eastern Europe started to experience as of the mid 1960s are one of the better-known idiosyncrasies of the demographic situation in the region (see, e.g. Murphy 2011; Meslé and Vallin 2002). Increases in mortality amongst working age men were first reported in Hungary (e.g. Carlson 1989), but then it quickly became clear that this was a more general trend shared by many countries in the former Soviet bloc. This was probably the first case in world population history of a sustained and substantial increase in mortality not associated with a major epidemic or a war. In the countries of Central Europe this trend was reversed with the fall of communism (e.g. Meslé 2004; Rychtaříková 2004). However, life expectancy there continues to be significantly below that in Western Europe. As Table 1 demonstrates, life expectancy at birth for men in 2010 in Central and Eastern Europe was generally below 75 years (Russia sets the lower boundary with under 63 years, which is still a significant improvement compared to 58.9 years in 2005), whilst in Western Europe it was by and large over 77 years (Switzerland being the leader with about 80 years). Amongst women the situation was less clear cut, but still in most CEE countries life expectancy was below 80 years, whilst in Western Europe it was generally above 82 years. It is worth noting, though, that on this indicator Slovenia surpasses countries like Denmark and Germany. In many of the successor states to the former Soviet Union the adverse mortality and morbidity trends persisted and even deepened after the fall of communism. These countries ‘hit the bottom’ in 2003–2005, after which a reversal also took place. For example, according to official estimates life expectancy at birth for men in Russia increased by 1 year or more in both 2006 and 2007—from 58.9 in 2005 to 60.4 in 2006 and 61.4 in 2007 (RosStat 2010, p. 101).

Table 1.

Life expectancy at birth by sex in selected countries (sorted in ascending order by the life expectancy for men in 2005)

Countries	1990		2005		2010
	Men	Women	Men	Women	Men	Women
Russiaa,b RU	63.79	74.42	58.9	72.4	62.8	74.7
Ukraineb UA	65.67	74.98	61.5	73.4	65.2	75.3
Belarusb,e BY	66.26	75.84	62.9	75.1	64.6	76.5
Moldovab MD	65.05	72.02	63.8	71.7	64.9	73.5
Lithuania LT	66.43	76.27	65.3	77.3	68.0	78.9
Latviac LV	64.18	74.63	65.4	76.5	68.6	78.4
Estonia EE	64.67	74.91	67.3	78.1	70.6	80.8
Hungary HU	65.15	73.79	68.7	77.2	70.7	78.6
Romaniaa RO	66.70	73.14	68.7	75.7	69.8	77.4
Bulgaria BG	67.97	74.71	69.0	76.2	70.3	77.4
Slovakia SK	66.72	75.70	70.2	78.1	71.7	79.3
Serbia RS	–	–	70.2	75.6	71.8	77.0
Poland PL	66.26	75.33	70.8	79.3	72.1	80.7
Montenegroc ME	74.25	80.66	71.4	76.9	76.4	76.2
FYR Macedoniac,d MK	69.88	74.53	71.6	75.9	72.9	77.2
Croatiac HR	68.7	76.38	71.9	78.92	73.5	79.9
Czech Republic CZ	67.57	75.48	72.9	79.2	74.5	80.9
Slovenia SI	69.82	77.83	73.9	80.9	76.4	83.1
Portugal PT	70.61	77.53	74.9	81.3	76.7	82.8
USAf US	71.86	78.87	75.1	80.2	–	–
Finland FI	70.96	79.00	75.6	82.5	76.9	83.5
Denmark DK	72.01	77.82	76.0	80.5	77.2	81.4
Belgiuma BE	72.73	79.54	76.2	81.9	77.3	82.8
Austria AT	72.28	78.99	76.6	82.2	77.9	83.5
Germany DE	71.99	78.53	76.7	82.0	78.0	83.0
Francea FR	72.83	81.19	76.8	83.9	78.0	85.0
Greece GR	74.66	79.48	76.8	81.6	78.7	83.1
Spain ES	73.39	80.59	77.0	83.7	79.1	85.3
UKa,c GB	72.98	78.73	77.1	81.3	78.3	82.5
Ireland IE	72.09	77.67	77.2	81.6	78.7	83.2
Netherlands NL	73.83	80.25	77.2	81.7	78.9	83.0
Norway NO	73.45	79.92	77.8	82.7	79.0	83.3
Sweden SE	74.84	80.55	78.5	82.9	79.6	83.6
Switzerlanda CH	73.99	80.93	78.7	84.0	79.9	84.6
Australiaf AU	73.84	80.06	78.9	83.7	–	–
Iceland IS	75.49	80.71	79.6	83.5	79.8	84.1

Source EuroStat online database (epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database) last accessed on 21 Jan 2012; WHO European Health for All database (data.euro.who.int/hfadb) last accessed on 3 Nov 2011; Human Mortality Database (www.mortality.org) last accessed on 21 Nov 2011; Statistical Yearbook of the Republic of Belarus, 2011, p. 94

Note This table does not include data for Albania (AL) and Bosnia and Herzegovina (BA) which have weaker statistical systems and comparable data are not always available. The two-letter country codes (ISO 3166-1 alpha-2) are provided, as they are used further in the figures. The geographic groupings that are used further are: Baltics—EE, LV and LT; CEE members of the European Union—BG, CZ, HU, PL, RO, SK and SI; European countries of CIS—BY, MD, RU and UA; South-East Europe—AL, BA, HR, MK, ME and RS; Nordic countries—IS, NO, SE, DK and FI; Southern Europe—CY, GR, IT, MT, PT and ES; Western Europe—AT, BE, FR, DE, IE, GB, LU and NL

^aData in italics refer to 2009

^bData for 1990 and 2005 are from WHO European Health for All database

^cData for 1990 are from WHO European Health for All database

^dData in italics refer to 1991

^eData for 2010 are from Statistical Yearbook of the Republic of Belarus, 2011

^fData from Human Mortality Database (presented for comparative purposes)

The significance of the adverse trends in mortality and life expectancy in the countries of Central and Eastern Europe is manifold. Three aspects, however, are worth noting here. First, these trends stand in sharp contrast to the continuous gains in life expectancy in the western parts of Europe and North America and in virtually all countries of the world, with the exception of the AIDS afflicted African countries like Botswana, Zambia, or Zimbabwe. They underline probably the ultimate East–West inequality. Whilst men in France added 9.3 years to their life expectancy at birth between 1965 and 2005, their brethren in Russia lost 5.5 years, and in Ukraine 6.3 years (see Fig. 1). This underscores the need for rapid improvement of the health-care systems in the affected countries and for the promotion of healthier life styles.

Fig. 1.

Changes in life expectancy at birth in selected countries, 1965–2005. Source Human Mortality Database (accessed 9 Nov 2011)

Second, as the adverse trends in mortality have affected mostly men (see Fig. 1), the gender differences in life expectancy in CEE, and particularly in CIS, were exacerbated beyond anything recorded so far in peace-time world population history. In 2005, at the peak of the adverse mortality trends, this difference was 13.5 years in Russia, over 12 years in Belarus, and around 11 years in Ukraine and the three Baltic countries (Estonia, Latvia and Lithuania)—see Table 1. As a result, the prevalence of widowhood amongst older women is very high (see Table 2). For the cohorts of women who faced the post-World War II marriage squeeze in these countries (i.e. those born in the 1920s and earlier), the situation was further complicated by the fact that the huge war losses had already created a ‘male deficit’. The data in Table 2 demonstrate that over three quarters of the women of these cohorts were widows according to the 1989 Soviet census. As the affected cohorts ‘leave’, the proportion widowed amongst older women will decline. Still, the provision of care for older women who do not have an immediate family on which to rely for support in old age will be a serious challenge not only in the CIS countries, but also in many CEE countries as their infrastructures for institutional care are inadequate (see Botev 1999 for more on the gender aspects of ageing in CEE).

Table 2.

Percent widowed amongst the women aged 70 and over (according to the 1990 and 2000 round of censuses)

	Census round
	1990	2000
Russian Federation	75.2	65.8
Belarus	75.2	65.4
Ukraine	75.1	66.4
Republic of Moldova	73.7	–
Slovakia	71.1	67.1
Czech Republic	70.9	64.8
Latvia	69.5	47.4
Hungary	69.3	66.3
Poland	68.5	65.2
Croatia	68.0	64.7
Lithuania	67.7	61.5
Romania	67.1	64.4
Serbia and Montenegro	62.5	59.6
Slovenia	62.2	49.5
Bulgaria	59.7	61.8
Estonia	–	59.5
Austria	63.8	56.1
Belgium	61.0	54.8
Greece	59.5	52.5
France	59.1	53.4
Italy	59.1	56.8
Finland	57.1	52.8
UK	57.1	55.6
The Netherlands	56.1	53.8
Ireland	55.4	54.9
Turkeya	54.6	59.3
Cyprus	54.4	53.2
Spain	54.2	52.0
Portugal	54.2	50.5
Norway	53.1	54.7
Switzerland	51.9	49.5
Sweden	50.9	48.9

Source EuroStat online database (epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database), accessed on 3 Nov 2011; UN Demographic Yearbook, Special Census Topics, vol 1—basic population characteristics (unstats.un.org/unsd/demographic/products/dyb/dybcens.htm), accessed on 20 Sept 2009

^aData from the 1990 census are for women aged 65 and over

Third, even if rapid and dramatic progress is achieved in lowering mortality and increasing life expectancy (e.g. something similar to the progress recorded in Russia in 2006 and 2007), the adverse mortality trends of the past decades will continue to ‘haunt’ the populations in CEE through the aforementioned impact on sex ratios amongst older persons and through the inter-generational differences in survivorship, as the survival probabilities of the younger generations will be significantly higher than these of the parental generations. As a result, for several decades the proportion of widows amongst older women will continue to be higher compared to other parts of Europe, and younger people in CEE countries will have lower probability compared to their peers in Western Europe, ceteris paribus, to have a surviving male grandparent in good health (see “Shorter generational length” for factors that are likely to counter-balance that trend). This will create a form of ‘vertical deprivation’ (Hagestad 2008) and is likely to affect both inter-generational relations and the socialization of younger generations.

The adverse trends in mortality and the low life expectancy are partly behind the fact that the countries in Central and Eastern Europe and particularly those in CIS have lower values on the indicators of population ageing compared to Western Europe (see Fig. 2), even though the rapid decline in fertility since the end of the 1980s has resulted in a rapid shrinkage of the younger generations. This means that the populations in most parts of CEE are still ageing mostly from the bottom. In a perverse way this could be interpreted as good news for the social security systems in these countries, as it mitigates the fiscal implications of population ageing. Clearly though, this is sad news for individuals. It also puts a note of irony in the international discourse on ageing in the European region, which has been driven mostly by the concerns of countries in the western parts of Europe and North America, and focuses on concepts like extending working life, or ‘long(er)-life societies’ (see Botev 2008b for further details).

Fig. 2.

Median age and percent of the population age 65 and over in European countries, 2005. Source United Nations (2011)

Ageing in the context of natural population decrease and emigration

Another feature of the demographic situation in Central and Eastern Europe, which has so far no parallels in world population history, is the combination of natural population decrease and significant emigration that some of the countries in the region are experiencing, or at least have experienced at some point following the fall of the Berlin wall. This situation has precipitated the population shrinkage and has given rise to concerns about the ‘demographic security’ in some of these countries and has offered ample material for nationalistic rhetoric and attempts to put in place pro-natalist policies. Figure 3 shows the cleavage between CEE on one hand and Western and Northern Europe on the other. The countries of latter region are concentrated in the upper right quadrant of the graph (denoted as B), indicating that in the period 2000–2005 most of them had low positive natural increase and net migration growth. In contrast, the CEE countries are dispersed in the other three quadrants. Most of the countries in South East Europe (incl. Albania, the Former Yugoslav Republic of Macedonia, and Serbia) had positive natural increase in 2000–2005, which, however, was lost to emigration, hence these countries occupy the upper left quadrant of the graph (quadrant A). Eight countries (mostly those in Eastern Europe and the Baltics) are in the lower left quadrant (quadrant D), which means that they were losing population both due the excess of deaths over births and through migration. Finally, in several countries the natural decrease is partially offset by net immigration, hence they find themselves in the lower right quadrant of the graph (denoted as C).

Fig. 3.

Countries by contribution of natural increase and net migration to population growth, 2000–2005. Source United Nations (2011)

Migration influences significantly population structures both in sending and receiving countries, and impacts socio-economic development and the living conditions of different generations through the ‘brain drain/brain gain’, the flow of remittances, etc. Whilst this article does not aim to address this subject in detail, several points related to Central and Eastern Europe need to be emphasized. First, the combination of low fertility and emigration exacerbates the effects of ageing, as it is young people who are more likely to migrate. This creates a double ‘whammy’ in terms of population ageing, as young people are also the potential parents, so their leaving further reduces the size of the new generations. Second, emigration could also result in the redistribution of care responsibilities across generations in the countries of origin, as many grandparents (often in need of care themselves) end up caring for grandchildren whose parents are abroad (see, e.g. HelpAge International 2008). In the case of four co-surviving generations, the ‘young’ old could find themselves ‘sandwiched’ between care responsibilities vis-á-vis their parents and their grandchildren, in the absence of their emigrant children—or example, consider the case of a Moldovan woman in her sixties who has to care for both her mother who is in her eighties and for her grand children, whilst her daughter is working in Italy. Last but not least, emigration sifts away part of the ‘demographic dividend’2 in CEE countries, which could have provided an opportunity for a more rapid economic recovery and would have helped them better face the challenges of population ageing.

The last point is particularly important. Recent research suggests that conditions similar to what most CEE countries were experiencing in the 1990s and early 2000s, and some will continue to experience in the near future, where the working age segment grows faster than the total population, are particularly propitious to faster economic growth and development, and might have been major factors in East Asia’s “economic miracles” (see, e.g. Bloom et al. 2003). Whether or not the potential created by these changes in the age structure is realized depends on the broad policy and institutional environment in a given country, including the openness of its economy and the macroeconomic management, the quality of governmental institutions, the labour legislation and the flexibility of the labour market, the educational and skill structure of the labour force, etc. Hence, the highest priority for those countries for which the ‘demographic window of opportunity’ is still opened is to create the necessary policy and institutional environment so that they can benefit from the ‘demographic dividend’, and accelerate their economic growth and social development. This will later allow them to better face the challenges and opportunities of the further changes in the age structures of their populations.

Disordered cohort flows

A third feature shared by many countries in the region (particularly those in the European parts of CIS, but also elsewhere) is the disordered cohort flows, stemming from a ‘stormy’ demographic past. Wave-like sequences of large and small cohorts were generated by the rapid fertility transitions in these countries, by the human losses and birth-dearth during the two world wars and the famines in the former Soviet Union, as well as by the fluctuations in fertility levels and growth rates as a result of the pro-natalist policy measures adopted at various times by the former Communist regimes (Fig. 4). Such ‘demographic waves’ could pose challenges at both macro- and microlevels. At the macrolevel, these challenges arise from the lags in infrastructural adjustment as the passage of excessively large cohorts through different stages of the life cycle requires investments in specialized infrastructure to meet the increased demand for services. At the microlevel the ‘demographic waves’ are usually associated with disruptions in individual life cycles, partly because members of excessively large generations need to cope with more competitive environments in terms of access to education, to the labour market, to various social services and even in terms of facing a tighter marriage market, which in turn has implications for union formation and living arrangements. (For more on demographic waves see Easterlin (1987) according to whom demographic and social behaviours change cyclically as a result of fluctuations in cohort size, as members of large cohorts face reduced economic opportunities and income relative to smaller parental generations, and vice versa; before Easterlin, Kuznets (1930) linked demographic waves created by immigration and the ensuing infrastructural adjustments with economic cycles, which came to be known as ‘Kuznets swings’).

Fig. 4.

Age pyramids for Romania and the Russian Federation (as of 1 Jan 2010). Source EuroStat online database

The effect of disordered cohort flows in CEE will be magnified by two factors discussed earlier: (1) the high emigration rates amongst younger persons, which means that many people from the parental generations will be left without immediate family on which to rely for support, (2) the excessive gender differences in mortality and life expectancy, and the ensuing high rates of widowhood amongst older women. This will further aggravate the challenges faced by the inadequate care provision infrastructure. The older persons in many CEE countries risk ending up being a lost generation, which could potentially open an intergenerational rift. Another factor that could contribute to the opening or widening of this rift is the interplay between the disordered cohort flows and the implications of the fact that demographic changes in the region are occurring alongside major political and economic transitions, as a result of which the inter-cohort differences are probably more pronounced in CEE than elsewhere in Europe. I will address this issue next.

From red to gray

The fourth feature that affects virtually all countries in CEE is the fact that the dramatic demographic changes there coincided with equally dramatic political and economic transitions, creating a sort of an ‘interference’ effect. This fact is captured well in the World Bank report ‘From Red to Gray’ (World Bank 2007). Some have even argued that “population ageing in CEE is an unintended side effect of the socio-economic transition from ‘communist’ to ‘capitalist’ societies” (Hoff 2008, p. 22; see also Hoff 2011). Whilst such an assertion is questionable as population ageing is a global process corollary to the demographic transition, it is clear that the implications of the ‘interference’ between demographic change and social, economic and political transitions in CEE are multi-faced. Of particular importance for this analysis is that it opened a potential intergenerational rift, as the shock of the fall of communism affected differently younger people, who could relatively easily reorganize their life cycles so as to adapt to the changed economic, social and political conditions, and the older persons for whom such reorganization was more difficult, or even impossible. This potential rift needs to be taken into account by researchers and policy makers as the policy formulation process needs to account for the higher probability of intergenerational conflict in CEE (see also Vanhuysse 2008).

One particular manifestation of the potential rift is the inter-generational differences in well-being, both objective and subjective. Old-age income maintenance schemes were eroded as a result of the economic difficulties and the need for fiscal austerity during the transition to a market economy. Consequently, the poverty rates amongst older persons increased significantly. Subjective perceptions also indicate that older persons see themselves as the losers of the transition process (Ravallion and Lokshin 2002; Deaton 2008; Lelkes 2008). At the same time, poverty levels amongst children in these countries are also high (see, e.g. UNICEF 2006). This is visible in Fig. 5, which presents data on the child and old-age poverty rates in the current EU member states. In the upper part of the figure, which presents data for 2001 based on the European Community Household Panel survey (ECHP), the ‘old’ member states (EU-15) are approximately equally distributed around the isoline (the sloped line in the graph representing points of equal poverty rates amongst children and older persons), with a slight shift to the right (i.e. in general the poverty rates amongst persons aged 65 and over are slightly higher than those amongst children). The new member states (NMS) with the exception of Slovenia, on the other hand, are above that line, i.e. the poverty rate of the children under age 15 is higher than that of persons over 65 (see also European Commission 2007).

Fig. 5.

Child versus old-age poverty in the EU member States, 2001 and 2009. Source EuroStat, on-line database (data accessed 29 April 2011)

The higher child poverty rates in CEE countries, which ECHP data appear to suggest, are sometimes attributed to the ‘relatively high level of retirement pensions relative to wages’ in these countries (European Commission 2009, p. 49) and it is assumed that pensioners may feel poorer than the objective welfare indicator suggest because of the falling income trajectory that they face, or stated in other words, because older persons expect to move down the income distribution (Ravallion and Lokshin 2002). There are, however, at least two ‘structural’ factors that could also be behind the ‘East–West’ differences. First, ECHP uses relatively small general purpose samples, which in the case of the Eastern European countries with their lower life expectancy and probability of survival to older ages, cover relatively small numbers of the oldest old who are the most vulnerable and at the greatest risk of poverty. Instead, the data for these countries are driven mostly by the ‘younger’ old who in many cases are employed in the informal sector, in addition to being eligible for and receiving a pension. This, I have argued, misrepresents the vulnerabilities and might lead to ill-informed policy decisions (see Botev 2008b). The data for 2009 in the lower part of Fig. 5, which are based on the new EU Survey of Income and Living Conditions (EU-SILC) with its larger samples presents a more balanced picture—half of the 10 NMS in Central and Eastern Europe are above the isoline and the other half below it. Moreover, the SILC data indicate that Estonia, Bulgaria and Latvia, along with Cyprus are the countries with the highest poverty rates amongst older persons in the European Union.

The second factor that needs to be kept in mind when interpreting the data in Fig. 5, is the differences in the timing of births between the new and the old member states (see Fig. 6). Earlier childbearing means that parents have lower income and assets, and thus contributes to higher poverty rates amongst children. Hence, ‘demographic’ effects related to the earlier childbearing in CEE countries might play a role in the high child poverty rates there. Several studies have looked at the relative importance of demographic effects on one hand and income redistribution on the other as determinants of child poverty in the context of Western countries (Weinshenker and Heuveline 2006; Rainwater and Smeeding 2003). The general finding is that the importance of demographic effects is relatively small. It needs to be noted, however, that in those cases demographic effects were usually limited to living arrangement differences that result in children living in family structures with different poverty risks (e.g. single mother headed households versus two parent families). It is important to replicate these studies for CEE and elucidate the effects of earlier fertility on child poverty, particularly in view of the fact that many experts and policy makers in Central and Eastern Europe advocate measures to increase fertility that might operate through the calendar of births. By pushing fertility towards younger ages, such measures could undermine the efforts to address the issue of child poverty in these countries (Botev 2008a).

Fig. 6.

Mean age at childbearing in the European countries, 1990–2010. Source EuroStat online database; demoscope database

Shorter generational length

A fifth feature is also related to the earlier childbearing in CEE countries, and concerns the potential impact it could have on intergenerational relations. Figure 6 registers the fact that by the time the Berlin wall fell, the East and the West parts of Europe were two different worlds in terms of timing of fertility. In Western and Northern Europe a trend towards postponement of fertility had emerged in the late 1970s and 1980s (usually associated with the so-called ‘second demographic transition’). In the former socialist countries, on the other hand, a number of factors including the pro-natalist policies of the 1970s and 1980s, the idiosyncrasies of the housing situation, etc., kept fertility relatively early. As a result, by 1990 the mean age at first birth in many of these countries was below 23 years (it was lowest in Bulgaria, with 22.2 years). In Russia, for example, where the mean age at first birth in 1990 was 22.6 years, about a quarter of the women born in the early 1970s had their first child by age 20 (see Zakharov and Ivanova 1996). The two Germanys were a good example of the east–west ‘divide’ in fertility timing—whilst in West Germany the mean age at childbearing in 1990 was 28.3 years, in East Germany it was over 3 years younger, at 25.1 years. The mean ages at first birth were, respectively, 27.0 and 24.6 years.

After the fall of the Berlin wall, the countries of CEE started to ‘catch up’ as a trend of delayed childbearing emerged in most of them. The ‘catch up’ was fastest in the countries of Central Europe, where by 2005 the mean age of mothers at first birth was over 25.5 (the case of the Czech Republic, where this indicator increased from 22.4 years in 1990 to 26.6 years in 2005 is quite telling). In the European parts of CIS early fertility persisted until the mid-1990s, mostly due to the accelerated timing of low parity births (i.e. the age of mothers at the birth of particularly the first child kept decreasing, whilst for higher order births it started to increase). This is why the Russian Federation, Belarus, Moldova and Ukraine (along with Bulgaria and Romania) occupy the bottom slots for 2010 in Fig. 6. Irrespective of the catch up in the Central European countries, the ‘East’ and the ‘West’ continue to be easily distinguishable in terms of the timing of births (see Fig. 6)—thus, in 2010 the mean age at childbearing in the CEE countries was under 29.5 years (Slovenia being an exception with 30.1, which probably explains partly why it is an outlier amongst the other new member states in Fig. 5), whilst in the ‘Western’ countries it was above that age (UK is an exception with 29.4 years; Italy, Ireland, Spain and Switzerland have the highest values on this indicator with around 31.2 years).

Even if fertility patterns converge, the past differences in the timing of childbearing will continue to have an imprint, particularly on inter-generational relations. Earlier fertility means shorter generational length. The question is whether one would relate differently (in terms of emotional attachment, compatibility of interests, etc.) to her/his parents in later life if the age difference with them is 20 years instead of say 35 years. If shorter generational length fosters better relations across generations, it could conceivably counter-balance the effect of the ‘rift’ to which we referred above (see “From red to grey”). A related issue is the availability to provide care—a smaller age difference would imply that the children’s generation would be more likely to be retired by the time their parents are in their 80s and most in need of care. In that sense the shorter age gap between generations could potentially help avoid the ‘sandwiched generations’ effect, as it increases the probability for the co-survival of four generations. The higher probability of co-survival as a result of shorter generational length also counterbalances the effect on generational ‘overlap’ of the adverse mortality trends and patterns in CEE (see “Ageing without living longer”).

Throughout many of the former socialist countries, earlier fertility, the high labour force participation amongst women, and the inadequate child care infrastructure resulted in a redistribution of child care responsibilities between generations, as grandparents took over part of that care from the parents. This situation was further facilitated by the low retirement age amongst women (in the majority of these countries the statutory retirement age for women was 55 years), which made them available to provide child care, as well as by the chronic housing deficits in the former socialist countries, which often resulted in forced co-residence of three or more generations. In a sense, there was a situation where children were bearing children and grandparents were rearing them. The fact that grandparents (and particularly grandmothers) in Eastern Europe were very involved in raising their grandchildren has been often quoted in the literature on care arrangements, family and gender studies (see Siemienska 1994; Gheaus 2008), however, virtually no attention has been paid to the implications of this fact on the socialization of the younger generations, and on intergenerational relations. It could be assumed that the fact that grandparents were a major provider of child care could affect intergenerational relations through at least two mechanisms. First, by increasing the interdependence across generations, as the involvement of grandparents in raising children probably fosters the expectation that in older age they will also be recipients of care. Second, by fostering relationships with grandparents in later life and thus influencing positively the image of older persons in a society. Both mechanisms could be expected to counteract the intergenerational rift described earlier.

Demography is not destiny, but still…

This article attempted to demonstrate that the countries of Central and Eastern Europe will be facing a number of issues when it comes to harnessing the opportunities of ageing and addressing the challenges that arise from it. This is partly because of several idiosyncrasies in their demographic development, a situation that is complicated by the fact that the rapid demographic change in these countries coincided with political, economic and social transformations, which affected differently younger and older generations. Given the diversity of the region, it could be expected that the magnitude of the challenges will differ from country to country, as will the preparedness of the state and the other social actors to address them.

As emphasized already, the policy formulation process needs to take into account these demographic idiosyncrasies and the impact that they could have on intergenerational relations, living arrangements, care needs, etc. This is increasingly recognized by the social actors in the region—in a growing number of countries the issues related to ageing are being given higher priority on the social policy agenda, and are being addressed in various sectoral programmes and policies, and particularly in national population strategies, policies and programmes. This is a positive sign and a good example of mainstreaming ageing. On the negative side, population policies in CEE are associated primarily with measures to increase fertility, and population ageing is often used as a justification for the overt pronatalism of these policies. The complexity of the demographic situation in the region necessitates a holistic and coherent approach to policy formulation, which needs to account for the changes in population age structures and their social and economic implications. This means that the objectives, means and instruments of ageing-related and population policies need to be consistent and coherent both with each other and with the objectives, means and instruments of the other social policy domains. Last but not least, this calls for a change in thinking/paradigm—the current premise that population trends have to be moulded to existing social institutions needs to be combined with a concern on how to adapt the social institutions to the new demographic realities (Botev 2008a).

The article also attempted to demonstrate the need for solid evidence on which to base policy interventions and programmes aimed at older persons. Political expediency often results in actions being taken on the basis of incomplete information, or with no regard to existing evidence. Without adequate understanding of the trends and patterns underlying social phenomena and processes, and of their historical background, there is a risk of misidentifying vulnerabilities (as is the case with the issue of child versus old-age poverty rates discussed earlier) and as a result interventions could end up being misdirected, with all the ensuing social, financial and political implications.

Finally, it needs to be pointed out that many of the conjectures in this article, particularly those related to the influence of demographic trends and patterns on intergenerational relations, are largely speculative, and need to be verified by specialized research. Irrespective of the clear research significance and policy relevance of these issues, surprisingly little attention has been paid to them so far. Fortunately, there is already a recognition in the research community that “Eastern and Central Europe constitute compelling ‘laboratories’ for studying the complex interplay of culture, demographic structures and social policy in shaping intergenerational transfer regimes on macro- and microlevels of social reality” (Hagestad and Herlofson 2007, p. 353).