Intérêt de l’analyse des causes multiples dans l’étude de la mortalité aux grands âges : l’exemple français

En France, la plus grande part des décès se produit aux âges élevés et même très élevés. Le décès est alors souvent l’aboutissement d’un processus complexe qui met en jeu plusieurs affections. Or, la plupart des études traitant des profils ou des tendances de la mortalité par cause reposent uniquement sur la cause initiale du décès. L’objectif de cet article est d’étudier l’impact de la prise en compte des causes multiples (cause initiale, cause directe et causes associées) sur la caractérisation de la mortalité en France à 60 ans ou plus. Les trois causes de décès les plus fréquentes à ces âges (maladies cardio-vasculaires, tumeurs et maladies de l’appareil respiratoire) sont inchangées mais la méthode fait ressortir le poids d’autres pathologies, en particulier le diabète et les troubles mentaux. L’interprétation des associations constatées entre différentes causes est complexe car la multiplicité des combinaisons théoriquement possibles nous oblige à effectuer des regroupements. L’article propose une analyse approfondie pour les deux groupes de causes de décès les plus fréquentes : les maladies de l’appareil circulatoire et les tumeurs.In France, most deaths occur among the elderly and very elderly. Death is often the end result of a complex process involving a number of ailments. However, most studies dealing with cause-specific mortality profiles or trends are only based on the underlying cause of death. The aim of this article is to study the impact of considering multiple causes (the underlying cause, direct cause and contributing causes) on the characterization of mortality in France at age 60 and over. The three most frequent causes of death at these ages (cardiovascular illness, tumours and respiratory illness) remain unchanged, but the method brings out the importance of other disorders, particularly diabetes and mental illness. Interpretation of the associations observed between various causes is a complex process since we need to set up groupings in view of the multiple theoretically possible combinations. The article offers an in-depth analysis of two groups of the most frequent causes of death: circulatory system illness and tumours

Les causes de décès aux grands âges en France, évolution récente

Dans les pays les plus avancés, la mort survient de plus en plus aux grands âges. En France, par exemple, en 2016, 73 % des décès féminins se sont produits après 85 ans, alors que ce n’était le cas que de 41 % en 1975 et même seulement 25 % en 1950. Alors que le sujet paraissait jadis anecdotique, des chercheurs s’interrogent de plus en plus sur ce que peuvent être les causes de décès aux grands âges. Beaucoup, cependant, estiment que la question est relativement vaine car plus l’âge avance, plus les causes sont multiples ce qui rend d’autant plus difficile la détermination d’une cause principale tandis que de leur côté les médecins déclarants posent souvent des diagnostics flous. Il est vrai que le nombre de décès dont la cause est mal définie, voire non déclarée, augmente avec l’âge, mais il nous semble néanmoins que les certificats médicaux de cause de décès portent de plus en plus d’informations exploitables jusqu’à des âges très avancés dans beaucoup de pays, dont la France. Dans le même temps, la précision des âges au décès recueillis par la statistique de l’état civil, longtemps assez défaillante aux grands âges, s’est beaucoup améliorée au cours des dernières décennies. Nous tentons donc ici de suivre l’évolution de la mortalité française par cause et par âge au-delà de 90 ans, depuis la fin des années 1970, tant pour les hommes que pour les femmes. Non seulement, l’étude confirme que la mortalité diminue à tous les âges, y compris les plus élevés, et quel que soit le sexe. Elle nous permet aussi d’évaluer le poids de chacun des grands groupes de causes (cancers, maladies du cœur, autres maladies de l’appareil circulatoire, maladies infectieuses et respiratoires, diabète, démences et maladies neuro-dégénératives, autres maladies, accidents et sénilité), dans ce recul de la mortalité aux âges élevés et donc dans la montée des espérances de vie à 90 ans, ainsi que le rôle qu’ils jouent dans la différence d’espérance de vie entre les sexes dont l’évolution, même aux grands âges s’est récemment retournée

Mortality in the Caucasus

With the collapse of the Soviet Union, Caucasian countries experienced remarkable migration flows, political conflicts, and deterioration of civil registration systems. The reassessment of Armenian and Georgian population after censuses carried out in the early 2000s enables to re-estimate recent mortality levels in both countries. Vital statistics since the 1980s are presented and discussed. Infant mortality is corrected according to sample surveys, and mortality above age 60 estimated through model life tables. On the basis of these estimates, trends in life expectancy were similar in the two countries, unfavourable during the 1990s, especially for males for whom the health progress, notably in Georgia, is still low.administrative data, Armenia, estimation, Georgia, life expectancy, mortality, reliability, survey data

Modelling the global spread of diseases: A review of current practice and capability

Mathematical models can aid in the understanding of the risks associated with the global spread of infectious diseases. To assess the current state of mathematical models for the global spread of infectious diseases, we reviewed the literature highlighting common approaches and good practice, and identifying research gaps. We followed a scoping study method and extracted information from 78 records on: modelling approaches; input data (epidemiological, population, and travel) for model parameterization; model validation data. We found that most epidemiological data come from published journal articles, population data come from a wide range of sources, and travel data mainly come from statistics or surveys, or commercial datasets. The use of commercial datasets may benefit the modeller, however makes critical appraisal of their model by other researchers more difficult. We found a minority of records (26) validated their model. We posit that this may be a result of pandemics, or far-reaching epidemics, being relatively rare events compared with other modelled physical phenomena (e.g. climate change). The sparsity of such events, and changes in outbreak recording, may make identifying suitable validation data difficult. We appreciate the challenge of modelling emerging infections given the lack of data for both model parameterisation and validation, and inherent complexity of the approaches used. However, we believe that open access datasets should be used wherever possible to aid model reproducibility and transparency. Further, modellers should validate their models where possible, or explicitly state why validation was not possible

Revisiting the mortality of France and Italy with the multiple-cause-of-death approach

In this paper, we use the multiple cause-of-death approach to compare the mortality profiles of France and Italy in 2003. Our analysis leads to a substantial re-evaluation of the role played by certain conditions in the process leading to death. Regarding the associations of causes, we distinguish three patterns that are common to both countries. The numerous similarities that emerge from the comparison of the two countries are a clear indication that, contrary to what is generally thought, misreporting by the certifying physicians generally do not distort the observation.cause of death, France, international comparisons, Italy, mortality, multiple causes of death

L' evolution de la mortalite par cause: les differentes facettes de la transition epidemiologique

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Revisiting the mortality of France and Italy with the multiple-cause-of-death approach

International audience; In this paper we revisit the mortality profiles of France and Italy in 2003 using the multiple-cause-of-death approach. The method leads to a substantial upward reassessment of the role played by certain conditions - e.g. diseases of the blood and diseases of the skin - in overall mortality. Regarding the associations of causes, we distinguish three patterns of pairwise joint occurrence of causes that are common to both countries. The numerous similarities that emerge from the comparison of the two countries are a positive signal of the reliability of the multiple-cause-of-death data

Mortality in Belarus, Lithuania, and Russia: divergence in recent trends and possible explanations

Before the collapse of the Soviet Union, Belarus, Lithuania, and Russia were quite comparable in terms of their socioeconomic development. Despite some differences in overall mortality levels, the three former Soviet republics were also very close to each other in terms of directions of mortality trends and age- and cause-specific mortality patterns. After 1991, all the three countries experienced substantial political and social transformations, and the challenges associated with the transition from a socialist to a market economy system. The sudden changes brought numerous problems, such as rapid growth in unemployment, falling standards of living, and growing social and income inequalities. These factors contributed to the significant deterioration of the health situation in all the countries, but the size and the nature of the mortality crisis was different in Belarus than it was in Lithuania and Russia. The marked similarities in socioeconomic and mortality trends in the countries up to 1991 contrast with their notable divergence during the subsequent years. The nature and success of market reforms seems to be the most plausible explanation for these differences. Russia and Lithuania have chosen more radical forms of economic and political transformations, which have led to massive privatization campaigns. The reforms were more sustainable and systematic in Lithuania than in Russia. By contrast, Belarus has chosen a gradual and slow transition path. Recent mortality trends in Belarus are explored in detail here, and are contrasted with those observed in Lithuania and Russia. Including a cause-of-death analysis sheds more light on the plausible determinants of the variations in mortality levels between the countries.Avant la chute de l’Union Soviétique, la Biélorussie, la Lituanie et la Russie étaient tout à fait comparables en termes de développement socio-économique. En dépit de quelques différences de taux de mortalité générale, les ex-Républiques Soviétiques étaient également très proches en termes de tendances et de variations de la mortalité par cause et par âge. Après 1991, les 3 pays ont connu des bouleversements politiques et sociaux, et ont dû faire face aux défis associés au passage d’une économie socialiste à l’économie de marché. Ces changements soudains ont provoqué de nombreux problèmes, tels qu’une montée rapide du chômage, la baisse du niveau de vie et le développement d’inégalités sociales et de revenu. L’ensemble de ces facteurs a contribué à une détérioration significative de la situation sanitaire dans tous les pays, mais la crise de mortalité en Biélorussie était différente de celles de la Lituanie et de la Russie, à la fois en termes d’étendue et de nature. Les grandes similitudes des tendances socio-économiques et de mortalité dans ces pays jusqu’en 1991 contrastent avec leur divergence notable au cours des années qui ont suivi. La nature et le succès des réformes liées au passage à l’économie de marché est l’explication la plus plausible de ces différences. La Russie et la Lituanie ont choisi des formes plus radicales de transformation économique et politique, qui ont mené à des campagnes de privatisation massives. Les réformes étaient plus durables et systématiques en Lituanie qu’en Russie. La Biélorussie, en revanche, a choisi la voie d’une transformation graduelle et lente. Les tendances récentes de la mortalité en Biélorussie sont examinées en détail dans cette étude, et comparées à celles observées en Lituanie et en Russie. Une analyse des causes de décès éclaire sur les déterminants plausibles des variations de niveau de mortalité entre ces pays

Is East-West Life Expectancy Gap Narrowing in the Enlarged European Union?

The fall of the Berlin Wall in 1990 and EU enlargement in 2004 are two major political events in the recent history of the Central and Eastern European region. By systematically comparing the changes and differences in life expectancy at birth between the seven new member countries from Central and Eastern Europe and more advanced countries of the EU-15, this article attempts to identify the vanguards and laggards in the health convergence process before and after the 2004 EU enlargement. The results of decomposition analysis highlight the changing patterns of age- and cause-specific contributions to the differences in life expectancy. Finally, we focus on the variations in the progress in reducing the burden of cardiovascular diseases and external causes of death, which were known to be responsible for the long-term mortality crisis during the period of communist rule. Our findings suggest that the collapse of the communist regimes led to immediate positive changes in the Central European countries. At the same time, health disadvantages persisted and even worsened in the Baltic countries. Later on, joining the EU in 2004 was not accompanied by immediate systematic convergence of life expectancy. However, very rapid progress in the initially worst performing Baltic countries after 2007 and especially during the 2010s, may suggest a delayed positive impact of EU enlargement leading to decreasing longevity disadvantage. The convergence process after 2004 was generally slower in the initially better-performing four Central European countries. Despite these country-specific variations, Czechia, Poland, and, especially, Estonia remain clear health vanguards in the region. Further progress requires much more systematic efforts to combat cardiovascular diseases and the persisting burden of excess male mortality at adult working ages. * This article belongs to a special issue on “Demographic Developments in Eastern and Western Europe Before and After the Transformation of Socialist Countries”