Facteurs de risque de chutes chez les aînés vivant dans la communauté et ayant recours aux services de soutien à domicile : covariables dépendantes du temps et événements récurrents

Les chutes chez les personnes âgées représentent un problème majeur. Il n’est donc pas étonnant que l’identification des facteurs qui en accroissent le risque ait mobilisé autant d’attention. Les aînés plus fragiles ayant besoin de soutien pour vivre dans la communauté sont néanmoins demeurés le parent pauvre de la recherche, bien que, plus récemment, les autorités québécoises en aient fait une cible d’intervention prioritaire. Les études d’observation prospectives sont particulièrement indiquées pour étudier les facteurs de risque de chutes chez les personnes âgées. Leur identification optimale est cependant compliquée par le fait que l’exposition aux facteurs de risque peut varier au cours du suivi et qu’un même individu peut subir plus d’un événement. Il y a 20 ans, des chercheurs ont tenté de sensibiliser leurs homologues à cet égard, mais leurs efforts sont demeurés vains. On continue aujourd’hui à faire peu de cas de ces considérations, se concentrant sur la proportion des personnes ayant fait une chute ou sur le temps écoulé jusqu’à la première chute. On écarte du coup une quantité importante d’information pertinente. Dans cette thèse, nous examinons les méthodes en usage et nous proposons une extension du modèle de risques de Cox. Nous illustrons cette méthode par une étude des facteurs de risque susceptibles d’être associés à des chutes parmi un groupe de 959 personnes âgées ayant eu recours aux services publics de soutien à domicile. Nous comparons les résultats obtenus avec la méthode de Wei, Lin et Weissfeld à ceux obtenus avec d’autres méthodes, dont la régression logistique conventionnelle, la régression logistique groupée, la régression binomiale négative et la régression d’Andersen et Gill. L’investigation est caractérisée par des prises de mesures répétées des facteurs de risque au domicile des participants et par des relances téléphoniques mensuelles visant à documenter la survenue des chutes. Les facteurs d’exposition étudiés, qu’ils soient fixes ou variables dans le temps, comprennent les caractéristiques sociodémographiques, l’indice de masse corporelle, le risque nutritionnel, la consommation d’alcool, les dangers de l’environnement domiciliaire, la démarche et l’équilibre, et la consommation de médicaments. La quasi-totalité (99,6 %) des usagers présentaient au moins un facteur à haut risque. L’exposition à des risques multiples était répandue, avec une moyenne de 2,7 facteurs à haut risque distincts par participant. Les facteurs statistiquement associés au risque de chutes incluent le sexe masculin, les tranches d’âge inférieures, l’histoire de chutes antérieures, un bas score à l’échelle d’équilibre de Berg, un faible indice de masse corporelle, la consommation de médicaments de type benzodiazépine, le nombre de dangers présents au domicile et le fait de vivre dans une résidence privée pour personnes âgées. Nos résultats révèlent cependant que les méthodes courantes d’analyse des facteurs de risque de chutes – et, dans certains cas, de chutes nécessitant un recours médical – créent des biais appréciables. Les biais pour les mesures d’association considérées proviennent de la manière dont l’exposition et le résultat sont mesurés et définis de même que de la manière dont les méthodes statistiques d’analyse en tiennent compte. Une dernière partie, tout aussi innovante que distincte de par la nature des outils statistiques utilisés, complète l’ouvrage. Nous y identifions des profils d’aînés à risque de devenir des chuteurs récurrents, soit ceux chez qui au moins deux chutes sont survenues dans les six mois suivant leur évaluation initiale. Une analyse par arbre de régression et de classification couplée à une analyse de survie a révélé l’existence de cinq profils distinctifs, dont le risque relatif varie de 0,7 à 5,1. Vivre dans une résidence pour aînés, avoir des antécédents de chutes multiples ou des troubles de l’équilibre et consommer de l’alcool sont les principaux facteurs associés à une probabilité accrue de chuter précocement et de devenir un chuteur récurrent. Qu’il s’agisse d’activité de dépistage des facteurs de risque de chutes ou de la population ciblée, cette thèse s’inscrit dans une perspective de gain de connaissances sur un thème hautement d’actualité en santé publique. Nous encourageons les chercheurs intéressés par l’identification des facteurs de risque de chutes chez les personnes âgées à recourir à la méthode statistique de Wei, Lin et Weissfeld car elle tient compte des expositions variables dans le temps et des événements récurrents. Davantage de recherches seront par ailleurs nécessaires pour déterminer le choix du meilleur test de dépistage pour un facteur de risque donné chez cette clientèle.

La régression de Poisson multiniveau généralisée au sein d’un devis longitudinal : un exemple de modélisation du nombre d’arrestations de membres de gangs de rue à Montréal entre 2005 et 2007

Les données comptées (count data) possèdent des distributions ayant des caractéristiques particulières comme la non-normalité, l’hétérogénéité des variances ainsi qu’un nombre important de zéros. Il est donc nécessaire d’utiliser les modèles appropriés afin d’obtenir des résultats non biaisés. Ce mémoire compare quatre modèles d’analyse pouvant être utilisés pour les données comptées : le modèle de Poisson, le modèle binomial négatif, le modèle de Poisson avec inflation du zéro et le modèle binomial négatif avec inflation du zéro. À des fins de comparaisons, la prédiction de la proportion du zéro, la confirmation ou l’infirmation des différentes hypothèses ainsi que la prédiction des moyennes furent utilisées afin de déterminer l’adéquation des différents modèles. Pour ce faire, le nombre d’arrestations des membres de gangs de rue sur le territoire de Montréal fut utilisé pour la période de 2005 à 2007. L’échantillon est composé de 470 hommes, âgés de 18 à 59 ans. Au terme des analyses, le modèle le plus adéquat est le modèle binomial négatif puisque celui-ci produit des résultats significatifs, s’adapte bien aux données observées et produit une proportion de zéro très similaire à celle observée.

The potential utility of age, triage score, and disposition data contained in emergency department electronic records for influenza-like illness surveillance in Montreal

La surveillance de l’influenza s’appuie sur un large spectre de données, dont les données de surveillance syndromique provenant des salles d’urgences. De plus en plus de variables sont enregistrées dans les dossiers électroniques des urgences et mises à la disposition des équipes de surveillance. L’objectif principal de ce mémoire est d’évaluer l’utilité potentielle de l’âge, de la catégorie de triage et de l’orientation au départ de l’urgence pour améliorer la surveillance de la morbidité liée aux cas sévères d’influenza. Les données d’un sous-ensemble des hôpitaux de Montréal ont été utilisées, d’avril 2006 à janvier 2011. Les hospitalisations avec diagnostic de pneumonie ou influenza ont été utilisées comme mesure de la morbidité liée aux cas sévères d’influenza, et ont été modélisées par régression binomiale négative, en tenant compte des tendances séculaires et saisonnières. En comparaison avec les visites avec syndrome d’allure grippale (SAG) totales, les visites avec SAG stratifiées par âge, par catégorie de triage et par orientation de départ ont amélioré le modèle prédictif des hospitalisations avec pneumonie ou influenza. Avant d’intégrer ces variables dans le système de surveillance de Montréal, des étapes additionnelles sont suggérées, incluant l’optimisation de la définition du syndrome d’allure grippale à utiliser, la confirmation de la valeur de ces prédicteurs avec de nouvelles données et l’évaluation de leur utilité pratique.

Distribution patterns of infection with multiple types of human papillomaviruses and their association with risk factors

Background: Infection with multiple types of human papillomavirus (HPV) is one of the main risk factors associated with the development of cervical lesions. In this study, cervical samples collected from 1,810 women with diverse sociocultural backgrounds, who attended to their cervical screening program in different geographical regions of Colombia, were examined for the presence of cervical lesions and HPV by Papanicolau testing and DNA PCR detection, respectively. Principal Findings: The negative binomial distribution model used in this study showed differences between the observed and expected values within some risk factor categories analyzed. Particularly in the case of single infection and coinfection with more than 4 HPV types, observed frequencies were smaller than expected, while the number of women infected with 2 to 4 viral types were higher than expected. Data analysis according to a negative binomial regression showed an increase in the risk of acquiring more HPV types in women who were of indigenous ethnicity (+37.8%), while this risk decreased in women who had given birth more than 4 times (-31.1%), or were of mestizo (-24.6%) or black (-40.9%) ethnicity. Conclusions: According to a theoretical probability distribution, the observed number of women having either a single infection or more than 4 viral types was smaller than expected, while for those infected with 2-4 HPV types it was larger than expected. Taking into account that this study showed a higher HPV coinfection rate in the indigenous ethnicity, the role of underlying factors should be assessed in detail in future studies.

Media bias and central bank response. Evidence from the nominal exchange rate behavior in Colombia

Since 1991 Colombia has had a market-determined Peso - US Dollar Nominal Exchange Rate (NER), after more than 20 years of controlled and multiple exchange rates. The behavior (revaluation / devaluation) of the NER is constantly reported in news, editorials and op-eds of major newspapers of the nation with particular attention to revaluation. The uneven reporting of revaluation episodes can be explained by the existence of an interest group particulary affected by revaluation, looking to increase awareness and sympathy for help from public institutions. Using the number of news and op-eds from a major Colombian newspaper, it is shown that there is an over-reporting of revaluation episodes in contrast to devaluation ones. Secondly, using text analysis upon the content of the news, it is also shown that the words devaluation and revaluation are far apart in the distribution of words within the news; and revaluation is highly correlated with words related to: public institutions, exporters and the need of assistance. Finally it is also shown that the probability of the central bank buying US dollars to lessen revaluation effects increases with the number of news; even though the central bank allegedly intervenes in the exchange rate market only to tame volatility or accumulate international reserves.

Determinants of demand for antenatal care in Colombia

Even though antenatal care is universally regarded as important, determinants of demand for antenatal care have not been widely studied. Evidence concerning which and how socioeconomic conditions influence whether a pregnant woman attends or not at least one antenatal consultation or how these factors affect the absences to antenatal consultations is very limited. In order to generate this evidence, a two-stage analysis was performed with data from the Demographic and Health Survey carried out by Profamilia in Colombia during 2005. The first stage was run as a logit model showing the marginal effects on the probability of attending the first visit and an ordinary least squares model was performed for the second stage. It was found that mothers living in the pacific region as well as young mothers seem to have a lower probability of attending the first visit but these factors are not related to the number of absences to antenatal consultation once the first visit has been achieved. The effect of health insurance was surprising because of the differing effects that the health insurers showed. Some familiar and personal conditions such as willingness to have the last children and number of previous children, demonstrated to be important in the determination of demand. The effect of mother’s educational attainment was proved as important whereas the father’s educational achievement was not. This paper provides some elements for policy making in order to increase the demand inducement of antenatal care, as well as stimulating research on demand for specific issues on health.

Asymptotic normality in mixtures of power series distributions

The problem of estimating the individual probabilities of a discrete distribution is considered. The true distribution of the independent observations is a mixture of a family of power series distributions. First, we ensure identifiability of the mixing distribution assuming mild conditions. Next, the mixing distribution is estimated by non-parametric maximum likelihood and an estimator for individual probabilities is obtained from the corresponding marginal mixture density. We establish asymptotic normality for the estimator of individual probabilities by showing that, under certain conditions, the difference between this estimator and the empirical proportions is asymptotically negligible. Our framework includes Poisson, negative binomial and logarithmic series as well as binomial mixture models. Simulations highlight the benefit in achieving normality when using the proposed marginal mixture density approach instead of the empirical one, especially for small sample sizes and/or when interest is in the tail areas. A real data example is given to illustrate the use of the methodology.

On the clustering of winter storm loss events over Germany

During the last decades, several windstorm series hit Europe leading to large aggregated losses. Such storm series are examples of serial clustering of extreme cyclones, presenting a considerable risk for the insurance industry. Clustering of events and return periods of storm series for Germany are quantified based on potential losses using empirical models. Two reanalysis data sets and observations from German weather stations are considered for 30 winters. Histograms of events exceeding selected return levels (1-, 2- and 5-year) are derived. Return periods of historical storm series are estimated based on the Poisson and the negative binomial distributions. Over 4000 years of general circulation model (GCM) simulations forced with current climate conditions are analysed to provide a better assessment of historical return periods. Estimations differ between distributions, for example 40 to 65 years for the 1990 series. For such less frequent series, estimates obtained with the Poisson distribution clearly deviate from empirical data. The negative binomial distribution provides better estimates, even though a sensitivity to return level and data set is identified. The consideration of GCM data permits a strong reduction of uncertainties. The present results support the importance of considering explicitly clustering of losses for an adequate risk assessment for economical applications.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

Physical disability, recent illnesses and health self-assessment in a population-based study in Sao Paulo, Brazil

Objectives. To investigate health self-assessment and to estimate the prevalence of chronic diseases and recent illnesses in people with and without physical disabilities (PD) in the state of Sao Paulo, southeastern Brazil. Study design. A Cross-sectional study comprising two population-based health surveys conducted in 2002 and 2003. Methods. A total of 8317 persons (165 with PD) were interviewed in the two studies. Variables concerning to health self-assessment; chronic disease and recent illness were compared in the people with and without PD. Negative binomial regression was used in the analysis. Results. Subjects with PD more often assessed their health as poor/very poor compared to non-disabled ones. They reported more illnesses in the 15 days prior to interview as well as more chronic diseases (skin conditions, anaemia, chronic kidney disease, stroke, depression/anxiety, migraine/headache, pulmonary diseases, hypertension, diabetes, arthritis/arthrosis/rheumatic conditions and heart disease). This higher disease prevalence can be either attributed to disability itself or be associated to gender, age and schooling. Conclusions. Subjects with PD had more recent illnesses and chronic diseases and poorer health self-assessment than non-disabled ones. Age, gender, schooling and disability have individual roles in disease development among disabled people.

A flexible model for survival data with a cure rate: a Bayesian approach

In this paper we deal with a Bayesian analysis for right-censored survival data suitable for populations with a cure rate. We consider a cure rate model based on the negative binomial distribution, encompassing as a special case the promotion time cure model. Bayesian analysis is based on Markov chain Monte Carlo (MCMC) methods. We also present some discussion on model selection and an illustration with a real dataset.

A hands-on approach for fitting long-term survival models under the GAMLSS framework

In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. in this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

A Bayesian Long-term Survival Model Parametrized in the Cured Fraction

The main goal of this paper is to investigate a cure rate model that comprehends some well-known proposals found in the literature. In our work the number of competing causes of the event of interest follows the negative binomial distribution. The model is conveniently reparametrized through the cured fraction, which is then linked to covariates by means of the logistic link. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis in the proposed model. The procedure is illustrated with a numerical example.

Power series generalized nonlinear models

We introduce in this paper a new class of discrete generalized nonlinear models to extend the binomial, Poisson and negative binomial models to cope with count data. This class of models includes some important models such as log-nonlinear models, logit, probit and negative binomial nonlinear models, generalized Poisson and generalized negative binomial regression models, among other models, which enables the fitting of a wide range of models to count data. We derive an iterative process for fitting these models by maximum likelihood and discuss inference on the parameters. The usefulness of the new class of models is illustrated with an application to a real data set. (C) 2008 Elsevier B.V. All rights reserved.

Earthquake fatalities : the interaction of nature and political economy

To say that the level of fatalities resulting from an earthquake is inversely related to a country's per capita level of income is hardly novel. What makes our approach novel is that we relate fatalities to both per capita income and the level of inequality that exists within a country through their joint impact on the likelihood of collective action being taken to mitigate the destructive potential of quakes. We first develop a theoretical model which offers an explanation as to why, in some environments, different segments of society prove incapable of arriving at what all parties perceive to be an agreeable distribution of the burden of the necessary collective action, causing the relatively wealthy simply to self-insure against the disaster while leaving the relatively poor to its mercy. Following this, we test our theoretical model by evaluating 269 large earthquakes occurring worldwide, between 1960 and 2002, taking into account other factors that influence a quake's destructiveness such as its magnitude, depth and proximity to population centers. Using a Negative Binomial estimation strategy with both random and fixed estimators, we find strong evidence of the theoretical model's predictions. That is, while earthquakes themselves are natural phenomena beyond the reach of humankind, our collective inaction with respect to items like the creation and enforcement of building codes, failure to retrofit structures and to enact quake-sensitive zoning clearly plays a part in determining the actual toll that a given quake takes. And, it is through these and other examples of collective inaction that limited per capita income and inequality couple together with a given quake's natural destructive power in determining the actual fatalities resulting from a quake.