Poster session on Population ageing and intergenerational relations (1)

The ageing of population is often associated with strain of health system due to increasing healthcare utilization among elderly. The extent to which demographic mingles with non-demographic factors, however, was rarely addressed. This study aims at investigating the effects of demographic and non-demographic changes to the future healthcare utilization. Using individual and household level data from various national-level surveys, discrete choice models are used to estimate the propensity of use of healthcare for each population group specified by demographic and non-demographic characteristics, which is then projected to the future population. The study shows that the effects of demographic change are quite substantial in term of size and pattern of utilization. However, these effects can be either compounded or undermined by non-demographic factors, such as health insurance subscription and chronic diseases. The share of health care utilization among elderly is not as high as commonly been perceived. This study offers an insight that the effects of demographic change to healthcare utilization is not straightforward if we are to acknowledge that ageing progresses along with the non-demographic factors as the case in many developing countries.

Warren C. Sanderson and Sergei Scherbov
Conventional studies of population ageing include changes in age structures but not changes in the relevant age-specific characteristics of people and, as a result, produce misleading results. Changes in the characteristics of people, such as in their remaining life expectancies, survival rates, disability rates, and cognitive abilities, for example, are all pertinent to a full understanding of population ageing. In this paper we formally develop a systematic approach to the study of population ageing that incorporates changes in the age-specific characteristics of people. We do this by generalizing the concept of age and linking these characteristic-based age indicators to new measures of population ageing. One of these indicators divides the life course into two stages, where the ratio of the durations of the two is kept constant. For example, one of these stages could be considered to be “old age”. This indicator is useful in discussions of the demographic indexation of pension ages. When changing age-specific characteristics are taken into account, we obtain a more comprehensive picture of population ageing.

China’s internal population movement is dominated by rural labour migrants moving without their families, leaving older parents and young children at rural hometowns. The deficiency of support for the rural older left-behind population has recently begun to draw the attention of the central government and researchers in various disciplines. However, the majority of previous research related to the left-behind population was based on migrant workers’ perspective. It is not sufficient to reveal the well-being of left-behind in rural area by using secondary data from migrant-oriented surveys. The term ‘left-behind’ is a flexible term with endogenous heterogeneity in different contexts, and this research will focus on the older people left-behind and their well-being in rural China, adopting a mixed-method approach to collect small-scale primary data in three rural villages from older persons and from their social networks, in order to examine the process of ‘becoming left-behind’ and its impact on meeting older people’s social care needs. The results of this research have the potential to inform the social care needs and socio-economic circumstances of older people left-behind in rural China, providing research evidence for policy that can contribute to the improvement of wellbeing for older people in rural China.

I analyze in this article differences by age and time of the components of the life-cycle deficit; namely, labor income and consumption. I use the specific case of Mexico, where no panel data is available for longitudinal analysis, but repeated cross-sectional survey data is used to construct age profiles of these variables by age for a period from 1992 to 2010. The age profiles where constructed following the National Transfer Accounts (NTA) methodology. Given this information, I try to answer the following questions. How bigger are the differences in the age pattern of consumption and labor income over time? Which part of those differences can be explained by policy issues, quality of data, period, and cohort effects? I apply an age-period-cohort (APC) analysis, using a random effects hierarchical APC model specification to explore in more detail possible answers to these questions.

The role of the national health systems is to provide health for their citizens but each country achieves it up to a different degree. The health systems are heterogeneous not only in their efficiency but in their funding, organization and management too. As it is difficult to measure their efficiency in absolute terms, the countries can be compared with each other. The relative efficiency of health systems can be measured by the life expectancy that they provide by taking education level and their funding structure into account. Based on data coming from the HMD, GGS, OECD and WHO, data envelopment analysis is used to explore the relative efficiencies of the countries.

Introduction: WHO defines health as a state of mental, physical and social wellbeing. However, there have been limited detailed evidences that systematically assessed the chronological relationships between these three health aspects and long-term care (LTC) needs.
Method: Among the urban dwelling elderly aged 65 years and over, data were collected through self-reported questionnaire in 2001 and 2004 in Tokyo. Ultimately, 8,126 respondents were included in the analysis. Exploratory factor analysis and Structural Equation Model (SEM) method was adopted in the analysis.
Results: By using exploratory factor analysis, 3 factors, named ’mental health’,’ physical health’, ‘social health’ , were defined as latent variables, respectively. The SEM analysis indicated significant direct but negative correlations between ‘physical health 2001’ and ‘LTC needs 2004’. In contrast, ‘mental health 2001’ and ‘social health 2001’ had little direct effects on ‘LTC needs 2004’. Meanwhile, we also observed an indirect effect of ‘mental health 2001’ on ‘LTC needs 2004’ through ‘physical health 2001’.
Conclusions: This study illustrates that the LTC needs is mainly confirmed by physical health, followed by mental and social health. It suggests that maintenance of good physical health may be entirely crucial to decrease the LTC needs.

A state-funded non-contributory pension plays an important role in poor and AIDS-affected rural South African households. Earlier cross-sectional analyses of 2006 and 2010 WHO-INDEPTH Study of Global Aging and Adult Health (WHO-SAGE) survey from the MRC/University of the Witwatersrand Rural Public Health and Health Transitions Unit (Agincourt) show strong sex differences in reports of health and wellbeing in persons over the age of 50, as well as gendered but temporary positive impact of pension receipt on older persons’ health and wellbeing. This paper builds on the earlier work through longitudinal analyses within individuals interviewed in both 2006 and 2010 to assess whether individual results mirror the cross-sectional results. Specifically, we hypothesize that for individuals, reported health and wellbeing will improve in the five years following pension receipt, and decrease in the years following; and, that the “pension bump” will be more prominent for women than for men.

Background. We investigate individual-level variations across Europe in grandparental childcare and whether key family cultures and labour market structures are important for shaping the role grandparents play in family life.
Methods and Data. We use data from two comparable European surveys (SHARE, the Survey of Health, Ageing and Retirement in Europe; and ELSA, the English Longitudinal Study of Ageing) and macro-level indicators (such as proportion of mothers not in paid work) to investigate personal, familial and institutional characteristics associated with grandparental care across 11 European countries. Multilevel analysis was used to examine to what extent a country’s cultural-contextual environment and individual-level characteristics help to explain variations in intensive grandparent childcare.
Results. Our preliminary findings show that grandparents in poor health, who are older than 70 and who are in paid work are less likely to provide childcare. However, socio-economic and demographic characteristics do not fully explain the dramatic differences observed across Europe in the prevalence of intensive grandparental childcare. Our analyses support the hypothesis that cultures and structures (which in turn influence policies) shape the extent to which grandparents provide intensive childcare across Europe.

Although many efforts have been developed for better accessibility in France since the 90’s, people who feel difficulty while travelling have increased. To what extent has the population structure influenced this rise? In the paper, we address the factors of this increase by means of a demographic approach to study the links between disability and mobility. Hence this paper firstly aims to better understand the socio-demographic situation of people disabled while travelling. Secondly, the medical factors and health conditions of people with a disability are studied.
Three surveys are used: the two latest French National Travel Surveys (1993 and 2007) which report 8% of the population have difficulty while travelling in 1993 against 9% in 2007 and the National Survey on Disability, Impairment and Dependence realized in 1999. They permit firstly to compare the difficulty while travelling over time, secondly to give medical reasons of difficulty while travelling in order to encompass individual and environmental characteristics of disability.
Difficulty while travelling is highly determined by age which is the main reason for this rise from 1993 to 2007. Yet, age is linked with the appearance of deficiencies that cause inabilities and limit mobility.

This study is one of the first attempts to quantify and decompose health inequalities among the older population in India. At the same time, the study aims to examine whether these inequalities vary for the older population below 70 years and 70 years and above. The initial investigation begins with a bivariate assessment of the socioeconomic differentials in terms of poor health status of the older population. Subsequently, concentration index is used as a measure of health inequality, which is further decomposed into determining factors to find out the relative contribution of the different socioeconomic predictors. Decomposition estimates suggest that poor economic condition stand to be the dominant contributor to health inequalities among older population followed by illiteracy and rural place of residence. Comparative assessment suggests that socioeconomic inequality is critical for health inequality for the population below 70 years and 70 years and above as well.