Guillaume Wunsch

Sex Differentials in Mortality - Trends, Determinants and Consequences - Lopez,Ad, Ruzicka,Lt

This book contains a selection of papers presented at a conference on sex differentials in mortality jointly organized by the Australian National University the United Nations and the World Health Organization and held in Canberra Australia December 1-7 1981. The papers are grouped under the following general topics: patterns and trends determinants social and demographic implications economic consequences public health aspects methodological issues and conclusions and prospects. The geographical focus is worldwide. (ANNOTATION)

Differential Mortality: Methodological Issues and Biosocial Factors

There are strongly pronounced differentials between survival chances for different social classes in less developed countries. This book gives insight into the variety of factors-biological, social, economic and cultural-associated with these inequalities in mortality rates. Certain of the papers deal with new conceptual approaches and methodological issues, while others cover particular countries in Asia and Latin America, providing overall an important and provoking study of inequality in death.

Do we necessarily need longitudinal data to infer causal relations

A-t-on nécessairement besoin de données longitudinales pour inférer des relations causales ? Il est généralement admis que les causes précèdent leurs effets dans le temps. Cela justifie usuellement la préférence pour les études longitudinales par rapport aux études transversales, parce que les premières permettent la modèlisation du processus dynamique engendrant le résultat, tandis que les secondes ne le peuvent pas. Les partisans de l’approche longitudinale proposent deux justifications interdépendantes : (i) l’inférence causale nécessite le suivi des mêmes personnes au fil du temps, et (ii) aucune inférence causale ne peut être tirée de données transversales. Dans cet article, nous remettons en question ce point de vue et proposons des objections à ces deux arguments. Nous soutenons également que la possibilité d’établir des relations de cause à effet ne dépend pas tant de l’utilisation de données longitudinales ou transversales, mais plutôt de savoir si la stratégie de modélisation est d’ordre structurel ou non. It is generally admitted that causes precede their effects in time. This usually justifies the preference for longitudinal studies over cross-sectional ones, because the former allow the modelling of the dynamic process generating the outcome, while the latter cannot. Supporters of the longitudinal view make two interrelated claims: (i) causal inference requires following the same individuals over time, and (ii) no causal inference can be drawn from cross-sectional data. In this paper, we challenge this view and offer counter-arguments to both claims. We also argue that the possibility of establishing causal relations does not so much depend upon whether we use longitudinal or cross-sectional data, but rather on whether or not the modelling strategy is structural.

Structural Modelling, Exogeneity, and Causality

This paper deals with causal analysis in the social sciences. We first present a conceptual framework according to which causal analysis is based on a rationale of variation and invariance, and not only on regularity. We then develop a formal framework for causal analysis by means of structural modelling. Within this framework we approach causality in terms of exogeneity in a structural conditional model based which is based on (i) congruence with background knowledge, (ii) invariance under a large variety of environmental changes, and (iii) model fit. We also tackle the issue of confounding and show how latent confounders can play havoc with exogeneity. This framework avoids making untestable metaphysical claims about causal relations and yet remains useful for cognitive and action-oriented goals.

Inferring causality through counterfactuals in observational studies - Some epistemological issues

L’inférence causale par contrefactuels dans les études observationnelles — Quelques épistémologiques : Cet article contribue au débat sur les vertus et les vices de contrefactuels comme base pour l’inférence causale. L’objectif est de mettre l’approche contrefactuelle dans une perspective épistémologique. Nous discutons d’un certain nombre de questions, allant de sa base non observable au parallélisme établi entre cette approche en statistique et en philosophie. Nous soutenons que la question n’est pas de rejeter ou d’approuver l’approche contrefactuelle par principe, mais de décider quel cadre de modélisation est préférable en fonction du contexte de la recherche. This paper contributes to the debate on the virtues and vices of counterfactuals as a basis for causal inference. The goal is to put the counterfactual approach in an epistemological perspective. We discuss a number of issues, ranging from its non-observable basis to the parallelisms drawn between the counterfactual approach in statistics and in philosophy. We argue that the question is not to oppose or to endorse the counterfactual approach as a matter of principle, but to decide what modelling framework is best to adopt depending on the research context.

Parents’ age at birth of their offspring and child survival

Abstract This study presents some new results on parental age as a risk factor for child survival. The study is based on individual registration forms for live births and infant deaths collected in Hungary from 1984 to 1988. Logistic regression models have been fitted for early neonatal and neonatal mortality on the one hand, and post‐neonatal mortality on the other hand. Children of older males and females have significantly higher early neonatal and neonatal mortality rates compared to those of younger males and females. The impact of age of both parents remains, however, slighter than that of other biological characteristics such as previous number of fetal deaths, induced abortions, or live births. The authors discuss possible biological explanations.

Paternal Age and Child Death: The Stillbirth Case

Previous research has shown an association between paternal age and neonatal mortality controlling for age of mother and other confounding factors. As this association is possibly of a biological nature, one would also expect to find a significant relationship between paternal age and fœtal mortality,stillbirth in particular. The present research is based on a Czech individual data set for the period 1986–1990. The risk of stillbirth is examined using logistic regression, taking account of both parental ages, sex of the fœtus, birth order, prematurity, and education of parents. It is shown that, in this data set, there is a significant relation between age of father and risk of stillbirth.

Les mesures de la fréquence du divorce. Une analyse comparative

Las medidas de la frecuencia del divorcio. Un analisis comparative. Josianne Duchene y Guillaume WUNSCH La frecuencia del divorcio es medida, a menudo, en un ano dado, es decir en un corte transversal, debido a que no se dispone de datos que permitan un analisis рог cohorte de matrimonios о рог que se desea expresamente un indice de momento. Aqui se proponen seis medidas diferentes (desde la formula (a) ha sta la formula (f)) a partir del numero de divorcios observados D(a, t) que ocur- rieron a una duracion a del matrimonio y en el ano t (o su total D(t)), del numero de matrimonios M(t) realizados en el ano E, del numero N(a. , t) de matrimonios no disueltos todavia en elano Xy realizados aanos antes (о su total N(t)). En ciertas formulas intervienen tambien : e^, duracion media de la vida de un matrimonio, AD duracion media del matrimonio en el momento del divorcio, o Am duracion media de los matrimonios restantes. Se constituyo un modelo de simulacion para verificar el comportamiento de estos diversos indices en condiciones no estacionarias. Se supuso que el numero de matrimonios M(t) crece de ano en ano, y que un cambio interviene en la duracion de los matrimonios al momento del divorcio (pasa de 12 a 9 anos), sin que sea afectada la frecuencia final. Se ajusta una funcion gama a la distribucion de los divorcios segun duracion del matrimonio : elgrafico la representa el ajuste menos apropiado (Dinamarca) y elgrafico lb el mejor (Alemania). En este modelo se supuso que no intervenian la mortalidad, ni las migraciones durante los primeros 35 anos de matrimonio. En la tabla 1 se presentan los diversos indices transversales, cuando el verdadero valor de la frecuencia por cohorte se hace igual a 100. En las columnas se encuentra : 2) la evaluacion que se obtiene mediante la construccionde una tabla de momento ; 3) la evaluacion por la formula (c) 4) la evaluacion por la formula (d) con un calendario tipo (ol-J, frances de la decada de 1950. 5) el mismo metodo, utilizando el calendario tipo de Alemania Federal ; 6) la evaluacion por la formula (a), (la mas simple) ; 7) la evaluacion por la formula (b) ; 8) la evaluacion por la formula (e) ; 9) la evaluacion por la formula (f). Se efectuaron, ademas, otřas simulaciones : aumento del numero de matrimonios y de su duracion, reduccion del numero de matrimonios y aumento de su duracion, reduccion de los matrimonios y de su duracion. La tabla 2 proporciona la suma de las diferencias absolutas de la estimacion, en relacion al verdadero valor de la intensidad en los diversos casos presentados. Los mejores metodos son, por orden descendente : el 9 que requiere datos muy elaborados, el 6 relacion del total de divorcios con respecto al numero inicial de promociones de matrimonios, y los 4 y 5, que son metodos de dis- tribuciones cronologicas tipicas.

Relations Generales Entre Mouvement et Structure Demographiques

An overview is provided of recent theoretical developments that generalize stable population theory to open population with variable fertility and mortality rates. Applications in mortality and fertility estimation useful for developing countries are then deduced from the generalized stable equations, sometimes called r-variable methods. The general relations extend Lotkas original stable population formulations, but their practical advantages are not always evident. Most of the relations are essentially tautological and do not necessarily provide better results than direct calculation. Most independence between risks. For example, a variable representing the probability of survival excludes the risk of migration, but the assumption of independence is not always realistic. The general relations have permitted introduction of new techniques of evaluation and estimation of demographic characteristics requiring fewer assumptions than the classic methods based on the theories of stability or quasi-stability. But the techniques require intercensal estimation of growth rates by age, which in developing countries are often biased due to defective data. As with all indirect techniques, these methods offer an uncertain alternative to correct and complete collection of data.

Un exemple de distorsion en analyse transversale: L’âge moyen au mariage par la méthode de Hajnal

Cette note est consacree a l’examen empirique des biais de distorsion en analyse transversale provenant d’une modification par cohorte du calendrier ou de l’intensite du phenomene etudie. Ces biais, lies a l’utilisation de l’artifice de la cohorte fictive, ont ete bien decrits par N.B. Ryder notamment sous le nom de « distributional distortion ». L’intensite d’un phenomene (nombre moyen d’evenements par tete), mesure dans l’optique transversale d’analyse, ne depend pas seulement de l’intensite du phenomene par cohorte mais egalement des variations du calendrier de ce phenomene d’une cohorte a l’autre; de meme, la duree moyenne d’eventualite mesuree en analyse transversale ne depend pas seulement du calendrier reel du phenomene par cohorte mais subit egalement l’influence d’une modification de l’intensite du phenomene d’une cohorte a l’autre. C’est ce dernier probleme que nous analyserons ici en recourant a l’exemple de l’âge moyen au premier mariage calcule par la methode elaboree par John Hajnal.