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Le Touquet – Paris-Plage, France

Gaymu J.,Institute National dEtudes Demographiques
Ageing and Society | Year: 2010

This study focuses on the influence of objective living conditions on the life satisfaction of older Europeans living alone from a gender and cross-national perspective. The data were drawn from the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE), which includes a single-item question for life satisfaction and a large set of health, family and socio-economic indicators. From a descriptive point of view, a lower proportion of women living alone declared themselves to be satisfied with life compared to men. When inequalities in living conditions were controlled for, the difference disappeared, but some determinants of life satisfaction differed for men and women and varied among countries. No limitations in daily activities, a high level of education, participation in leisure activities and an older age increased life satisfaction for both men and women living alone, but the existence of a child influenced only the life satisfaction of men, while income level (or home ownership) had an impact only for women. Moreover, a North-South gradient was clearly observable only for women living alone: all other things being equal, women had a higher probability of declaring themselves satisfied with life in northern European countries than in the South, and their determinants of life satisfaction were strongly linked to the socio-cultural context. Copyright © Cambridge University Press 2010.

Agency: Cordis | Branch: FP7 | Program: CP-FP | Phase: SSH-2009-2.1.1. | Award Amount: 3.88M | Year: 2010

Increasing concerns about sustainable development and the growth of urban areas have brought forth in recent years a renewed enthusiasm and need for the use of quantitative models in the field of transportation and spatial planning. This project proposes to improve urban simulation models and their interaction with transport models. Unified operational models that favour a microscopic approach, such as UrbanSim and ILUTE (Integrated Land Use, Transportation, and Environment Modelling System) have recently gained a lot of interest both in the land use and transport communities. Nevertheless, in their current forms these models still require further development to support a comprehensive analysis of the main environmental and socio-economic questions of the sustainability of urban growth and the relevant public policies. The goal of this project is to address the modelling and computational issues of integrating modern mobility simulations with the latest micro-simulation land use models. The project intends to advance the state-of-the-art in the field of the micro-simulation of prospective integrated models of Land-Use and Transport (LUTI). On the modelling side, the main challenges are to integrate a demographic evolution module, to add an environmental module, to improve the overall consistency and, last but not least, to deal with the multi-scale aspects of the problem: several time horizons and spatial resolutions are involved.

Habbema J.D.F.,Erasmus Medical Center | Eijkemans M.J.C.,University Utrecht | Leridon H.,Institute National dEtudes Demographiques | Te Velde E.R.,Erasmus Medical Center
Human Reproduction | Year: 2015

STUDY QUESTION Until what age can couples wait to start a family without compromising their chances of realizing the desired number of children? SUMMARY ANSWER The latest female age at which a couple should start trying to become pregnant strongly depends on the importance attached to achieving a desired family size and on whether or not IVF is an acceptable option in case no natural pregnancy occurs. WHAT IS KNOWN ALREADY It is well established that the treatment-independent and treatment-dependent chances of pregnancy decline with female age. However, research on the effect of age has focused on the chance of a first pregnancy and not on realizing more than one child. STUDY DESIGN, SIZE, DURATION An established computer simulation model of fertility, updated with recent IVF success rates, was used to simulate a cohort of 10 000 couples in order to assess the chances of realizing a one-, two- or three-child family, for different female ages at which the couple starts trying to conceive. PARTICIPANTS/MATERIALS, SETTING, METHODS The model uses treatment-independent pregnancy chances and pregnancy chances after IVF/ICSI. In order to focus the discussion, we single out three levels of importance that couples could attach to realizing a desired family size: (i) Very important (equated with aiming for at least a 90% success chance). (ii) Important but not at all costs (equated with a 75% success chance) (iii) Good to have children, but a life without children is also fine (equated with a 50% success chance). MAIN RESULTS AND THE ROLE OF CHANCE In order to have a chance of at least 90% to realize a one-child family, couples should start trying to conceive when the female partner is 35 years of age or younger, in case IVF is an acceptable option. For two children, the latest starting age is 31 years, and for three children 28 years. Without IVF, couples should start no later than age 32 years for a one-child family, at 27 years for a two-child family, and at 23 years for three children. When couples accept 75% or lower chances of family completion, they can start 4-11 years later. The results appeared to be robust for plausible changes in model assumptions. LIMITATIONS, REASONS FOR CAUTION Our conclusions would have been more persuasive if derived directly from large-scale prospective studies. An evidence-based simulation study (as we did) is the next best option. We recommend that the simulations should be updated every 5-10 years with new evidence because, owing to improvements in IVF technology, the assumptions on IVF success chances in particular run the risk of becoming outdated. WIDER IMPLICATIONS OF THE FINDINGS Information on the chance of family completion at different starting ages is important for prospective parents in planning their family, for preconception counselling, for inclusion in educational courses in human biology, and for increasing public awareness on human reproductive possibilities and limitations. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.

Bonneuil N.,Institute National dEtudes Demographiques
Journal of Theoretical Biology | Year: 2012

The question of protected polymorphism is addressed in terms of dynamic maintenance within a set of constraints defining polymorphism. Stricto sensu, the maintenance of polymorphism is identified with the set of states, called the C-viability kernel, from which there exists at least one trajectory remaining in the set of constraints. Protected polymorphism under time-dependent selection and migration is re-formulated as a C-viability problem. The C-viability kernel is computed under conditions of time-dependent unpredictable migration and selection, from the case of two demes and two alleles up to that of three demes and three alleles. It delineates the trade-off between isolation and openness to migration combined with relative fitness values. The problem of protected polymorphism in time-varying conditions is then answered in its full dimensionality. © 2011 Elsevier Ltd.

J-AGEII, the Coordination Action for implementation and alignment activities of the Joint Programming Initiative (JPI) More Years Better Lives the Challenges and Opportunities of Demographic Change, will support and foster the overall management of the JPI, update the Strategic Research Agenda and support implementation through joint activities between Member States. Furthermore, the work plan will include dissemination and information exchange with scientific and societal stakeholders, policy makers and research funders as well as an evaluation and monitoring exercise. Ultimately, the project and the JPI seek to stimulate the alignment of relevant national programmes and EU initiatives, strengthen the base of multi-disciplinary and holistic ageing research in Europe and to provide scientific evidence for policy responses to demographic change.

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