324 research outputs found

    Monitoring Health Inequalities in France: A Short Tool for Routine Health SUrvey to Account for LifeLong Adverse Experiences

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    Conventional health surveys focus on current health and social context but rarely address past experiences of hardship or exclusion. However, recent research shows how such experiences contribute to health status and social inequalities. In order to analyse in routine statistics the impact of lifelong adverse experiences (LAE) on various health indicators, a new set of questions on financial difficulties, housing difficulties due to financial hardship and isolation was introduced in the 2004 French National health, health care and insurance survey (ESPS 2004). Logistic regressions were used to analyze associations between LAE, current socioeconomic status (SES) (education, occupation, income) and health (self-perceived health, activity limitation, chronic morbidity), on a sample of 4308 men and women aged 35 years and older. In our population, LAE were reported by 1 person out of 5. Although more frequent in low SES groups, they concerned above 10% of the highest incomes. For both sexes, LAE are significantly linked to poor self-perceived health, diseases and activity limitations, even controlling for SES (OR>2) and even in the highest income group. This pattern remains significant for LAE experienced only during childhood. The questions successfully identified in a conventional survey people exposed to health problems in relation to past experiences. LAE contribute to the social health gradient and explain variability within social groups. These questions will be useful to monitor health inequalities, for instance by further analyzing LAE related health determinants such as risk factors, exposition and care use.Health inequalities; Lifelong adverse experiences; Health surveys

    Health after union dissolution(s): Cumulative and temporal dynamics

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    The number of individuals experiencing one or multiple union dissolutions in their lifetime is increasing. The literature has shown significant interactions with health disorders, in response to the crisis situation that affects the spouses. However, processes are still unclear, in particular regarding the timing of the affection. This study explored whether different health disorders are observed shortly after dissolution or are delayed, and whether they are short- or long-lasting. We used data from the two waves (2006 and 2010) of the French Health and Professional Lives Survey (SIP) among 8349 individuals aged 25–64 years. Based on three health disorders, we studied 1) their levels in relation to the retrospective histories of union dissolutions; 2) health changes associated with a dissolution occurring between the two waves. We found that individuals who experienced one or multiple union dissolutions had worse self-rated health, more depressive symptoms and sleep disorders. The two latter were more related with a recent dissolution than with distant ones, suggesting an immediate association, yet long-lasting. Self-rated health was related with distant dissolutions only, suggesting a lagged, however also long-lasting association. Experiencing union dissolution between the two waves was linked to a higher probability of the onset of sleep disorders and depressive mood, and of deterioration of self-rated health if it was not the first dissolution. Our study shows that union dissolutions are highly correlated with different poor health measures, in the short and the long run, depending on the health disorder, with cumulative and durable effects

    Occupational and educational differentials in mortality in French elderly people

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    DiffĂ©rences d’espĂ©rance de vie sans incapacitĂ© dans les dĂ©partements français

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      Les espĂ©rances de vie sans incapacitĂ© ainsi que leurs dĂ©terminants individuels ont fait l'objet de nombreux travaux, en France comme dans l'ensemble des pays Ă  faible mortalitĂ©. En revanche, Ă  l’échelle infra-nationale les Ă©tudes sont trĂšs rares, faute d’enquĂȘte mesurant les niveaux d’incapacitĂ© reprĂ©sentative Ă  cet Ă©chelon. Pourtant, Ă  l'instar des Ă©carts infra-nationaux de mortalitĂ© dĂ©jĂ  dĂ©montrĂ©s, il y a tout lieu de penser que l'indicateur national d'espĂ©rance de vie sans incapacitĂ© recouvre d'importantes inĂ©galitĂ©s territoriales. En 2014, l’enquĂȘte Vie Quotidienne et SantĂ© (VQS) offre la possibilitĂ© de calculer, pour la premiĂšre fois, les niveaux d’incapacitĂ© des 60 ans et plus Ă  partir d’un Ă©chantillon reprĂ©sentatif Ă  l’échelle dĂ©partementale. Nous mobilisons les donnĂ©es de cette enquĂȘte pour, dans un premier temps, calculer l’espĂ©rance de vie sans incapacitĂ© dans chacun des 100 dĂ©partements français, puis, dans un second temps, mettre en lien cet indicateur avec les limitations fonctionnelles rencontrĂ©es par la population des 60 ans et plus. Les premiers rĂ©sultats mettent en Ă©vidence de forts Ă©carts dĂ©partementaux concernant l’incapacitĂ©, selon une gĂ©ographie proche de celle des Ă©carts de mortalitĂ©. Les dĂ©partements dans lesquels l’espĂ©rance de vie sans incapacitĂ© est faible se caractĂ©risent par une forte prĂ©valence des limitations fonctionnelles touchant les fonctions physiques.   &nbsp

    The use of the global activity limitation Indicator and healthy life years by member states and the European Commission

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    Background: In 2005, the European Union (EU) started to use a disability-free life expectancy, known as Healthy Life Years (HLY), to monitor progress in the strategic European policies such as the 2000 Lisbon strategy. HLY are based on the underlying measure: the Global Activity Limitation Indicator (GALI). Twelve years after its implementation, this study aims to assess its current use in EU Member States and the European Commission. Methods: In March 2017, a questionnaire was sent to 28 Member states and the European Commission. The questionnaire inquired how the GALI and HLY are used to set policy targets, in which surveys the GALI has been introduced since 2005, how the GALI and HLY are presented, and what the capacity in each country is to investigate the GALI and HLY. Results: The survey was answered by 22 Member States and by the Commission. HLY are often used to set targets and develop strategies in health such as national health plans. Analysis of HLY has even led to policy change. In some countries, HLY have become the main indicator for health, gaining more importance than life expectancy. More recently, the GALI and HLY have also been used for policy targets outside the health sector such as in the area of pension and retirement age or in the context of sustainable development. Regarding surveys, the GALI is mostly obtained from the EU-SILC, SHARE and EHIS, but is also increasingly introduced in national surveys. National health reporting systems usually present HLY on their national statistics websites. Most countries have up to three specialists working on the GALI and HLY, which has been consistent through time. Others have increased their capacity over various institutions. Conclusion: HLY is an indicator that is systematically used to monitor health developments in most EU countries. The SHARE, EU-SILC and EHIS are commonly used to assess HLY through the GALI. The results are then described in reports and presented on national statistics websites and used in different policy settings. Expertise to analyse the GALI and HLY is available in most countries

    L’allongement de l’espĂ©rance de vie en Europe

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    Depuis une trentaine d’annĂ©es, face Ă  l’allongement de l’espĂ©rance de vie, chercheurs et acteurs de santĂ© publique s’interrogent sur les rĂ©percussions attendues sur la santé : gagne-t-on des annĂ©es de bonne santĂ© ou vit-on plus longtemps avec des maladies ? Ces interrogations dĂ©coulent d’une augmentation de la survie aux grands Ăąges, plus exposĂ©s aux problĂšmes de santĂ©, mais aussi de la plus grande survie avec certaines maladies et incapacitĂ©s dont la lĂ©talitĂ© diminue. En rĂ©ponse Ă  ces questions, les indicateurs d’espĂ©rance de vie en santĂ© ont apportĂ© la dimension qualitative au dĂ©compte des annĂ©es de vie. Et les « annĂ©es de vie en bonne santé », basĂ©es sur une mesure de la santĂ© fonctionnelle, ont Ă©tĂ© ajoutĂ©es Ă  la liste des indicateurs structurels de l’Union europĂ©enne. CalculĂ©es annuellement depuis 2008, elles permettent de suivre l’évolution concomitante de l’espĂ©rance de vie et des annĂ©es vĂ©cues avec et sans limitation d’activitĂ© dans les pays europĂ©ens et d’éclairer les disparitĂ©s entre pays.Over the last thirty years, researchers and public health actors have been investigating the potential health impact of increasing life expectancy : are we gaining healthy years or do we live longer with diseases ? These questions arise as a consequence of increased survival to older ages at which health problems are common, and increased survival with diseases and disabilities whose lethality has decreased. In response to these questions, health expectancy indicators now provide a measure of both the quantitative and the qualitative dimensions of the years lived. And “healthy life years”, based on a functional health measurement, have been added to the European Union’s list of structural indicators. Calculated annually since 2008, they track the concomitant changes in life expectancy and years lived with and without activity limitations in European countries and shed light on the disparities between countries

    Assessing the validity of the Global Activity Limitation Indicator in fourteen European countries.

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    BACKGROUND: The Global Activity Limitation Indicator (GALI), the measure underlying the European indicator Healthy Life Years (HLY), is widely used to compare population health across countries. However, the comparability of the item has been questioned. This study aims to further validate the GALI in the adult European population. METHODS: Data from the European Health Interview Survey (EHIS), covering 14 European countries and 152,787 individuals, were used to explore how the GALI was associated with other measures of disability and whether the GALI was consistent or reflected different disability situations in different countries. RESULTS: When considering each country separately or all combined, we found that the GALI was significantly associated with measures of activities of daily living, instrumental activity of daily living, and functional limitations (P < 0.001 in all cases). Associations were largest for activity of daily living and lowest though still high for functional limitations. For each measure, the magnitude of the association was similar across most countries. Overall, however, the GALI differed significantly between countries in terms of how it reflected each of the three disability measures (P < 0.001 in all cases). We suspect cross-country differences in the results may be due to variations in: the implementation of the EHIS, the perception of functioning and limitations, and the understanding of the GALI question. CONCLUSION: The study both confirms the relevance of this indicator to measure general activity limitations in the European population and the need for caution when comparing the level of the GALI from one country to another

    Gender Differences in Social Mortality Differentials in Switzerland (1990-2005)

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    Using data from the 1990 and 2000 Swiss Federal Censuses linked to the death records of the years 1990-1995 and 2000-2005, this paper investigates gender differences in mortality differentials by level of educational achievement and by marital status. In both periods, the differential by level of education is clearly more pronounced among men, but the difference in the educational gradient between men and women decreases between the two periods of observation. Health behavior might contribute to the gender difference in the educational mortality gradient, but it is probably not the main reason for this finding. The mortality differential by marital status is also stronger in men, but the difference between men and women narrows over time. Our analysis also shows that gender differences in the mortality differential by marital status almost disappear when gender differences in population composition by level of education, nationality, employment status, and housing situation are taken into account
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