Quality of life of caregivers for patients of cerebrovascular accidents: association of (socio-demographic) characteristics and burden

OBJECTIVE Investigating the association between quality of life with socio-demographic characteristics and the burden of caregivers for individuals with cerebrovascular accident sequelae. METHOD A descriptive, cross-sectional study with a sample composed of 136 caregivers. For data collection, a semi-structured questionnaire, the Barthel, Burden Interview and Short-Form-36 scales were used. Correlation analysis, t-Student test and F-test were used for the analysis in order to compare averages. RESULTS Significant averages in quality of life were demonstrated in association with female caregivers and those over 60 years in the field 'functional capacity,' and in the domains of 'mental health' and 'vitality' for those with higher income. Regarding burden association, the highlighted areas were 'functional capacity,' 'physical aspects,' 'emotional aspects' and 'pain.' CONCLUSION The creation of public policies and social support to effectively reduce the burden on caregivers is a necessity.

Predictability of drug expenditures: An application using morbidity data

The growth of pharmaceutical expenditure and its prediction is a major concern for policy makers and health care managers. This paper explores different predictive models to estimate future drug expenses, using demographic and morbidity individual information from an integrated healthcare delivery organization in Catalonia for years 2002 and 2003. The morbidity information consists of codified health encounters grouped through the Clinical Risk Groups (CRGs). We estimate pharmaceutical costs using several model specifications, and CRGs as risk adjusters, providing an alternative way of obtaining high predictive power comparable to other estimations of drug expenditures in the literature. These results have clear implications for the use of risk adjustment and CRGs in setting the premiums for pharmaceutical benefits.

Demographic and behavioral factors associated with adolescent pregnancy in Switzerland.

Switzerland has the lowest adolescent fertility rate in Western Europe. According to data collected in 1993 as part of the Swiss Multicentre Adolescent Survey on Health, 5% of 1,726 sexually active adolescents in a group of 3,993 15-20-year-old women enrolled in academic or vocational classes had ever been pregnant; most of these women (80%) had terminated their pregnancy. Adolescents who had ever been pregnant did not differ significantly from those who had not by demographic characteristics. Multiple logistic regression analysis identified seven factors associated with pregnancy: having had four or more sexual partners; not having used contraceptives at first intercourse; ever use of less-effective contraceptive methods; having used illicit drugs during the last 30 days; living apart from one's parents; recently experiencing stress; and perceiving a lack of future prospects.

Nonagenarians and centenarians in Switzerland, 1860-2001: a demographic analysis.

STUDY OBJECTIVE: To explore the rapid rise of the extremely old population, showing the magnitude of the increase and identifying demographic mechanisms underlying this increase. DESIGN: Demographic analysis using census data, yearly population estimates, and mortality statistics. SETTING: Switzerland 1860-2001. MAIN RESULTS: Indicators suggest a strong increase in the number of nonagenarians and centenarians in Switzerland as compared with other countries. The increase is mostly attributable to the decline in mortality after age 80. This decline started in the 1950s. CONCLUSION: Nonagenarians and centenarians constitute a new population, which became sizeable after 1950 in Switzerland. There is a need to monitor this population with appropriate demographic and epidemiological indicators.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.

Socio-demographic and behavioural determinants of weight gain in the Swiss population.

BackgroundIn Switzerland, socio-demographic and behavioural factors are associated with obesity, but no study ever assessed their impact on weight gain using prospective data.MethodsData from 4,469 participants (53.0% women), aged 35 to 75 years at baseline and followed for 5.5 years. Weight gain was considered as a rate (kg/year) or as gaining ¿5 kg during the study period.ResultsRate of weight gain was lower among participants who were older (mean¿±¿standard deviation: 0.46¿±¿0.92, 0.33¿±¿0.88, 0.21¿±¿0.86 and 0.06¿±¿0.74 kg/year in participants aged [35-45[, [45-55[, [55¿65[and [65+ years, respectively, P<0.001); physically active (0.27¿±¿0.82 vs. 0.35¿±¿0.95 kg/year for sedentary, P¿<¿0.005) or living in a couple (0.29¿±¿0.84 vs. 0.35¿±¿0.96 kg/year for living single, P¿<¿0.05), and higher among current smokers (0.41¿±¿0.97, 0.26¿±¿0.84 and 0.29±0.85 kg/year for current, former and never smokers, respectively, p<0.001). These findings were further confirmed by multivariable analysis. Multivariable logistic regression showed that receiving social help, being a current smoker or obese increased the likelihood of gaining ¿5Kg: Odds ratio (OR) and 95% confidence interval (CI) 1.43 (1.16-1.77); 1.63 (1.35-1.95) and 1.95 (1.57-2.43), respectively, while living in couple or being physically active decreased the risk: 0.73 (0.62-0.86) and 0.72 (0.62-0.83), respectively. No association was found between weight gain and gender, being born in Switzerland or education.ConclusionsIn Switzerland, financial difficulties (indicated by receiving social help) and current smoking were associated with increases in body weight over a 5 years follow-up. Living in couple, being older or physically active were protective against weight gain.

Antiretroviral therapy during pregnancy and premature birth: analysis of Swiss data.

BACKGROUND: There is an ongoing debate as to whether combined antiretroviral treatment (cART) during pregnancy is an independent risk factor for prematurity in HIV-1-infected women. OBJECTIVE: The aim of the study was to examine (1) crude effects of different ART regimens on prematurity, (2) the association between duration of cART and duration of pregnancy, and (3) the role of possibly confounding risk factors for prematurity. METHOD: We analysed data from 1180 pregnancies prospectively collected by the Swiss Mother and Child HIV Cohort Study (MoCHiV) and the Swiss HIV Cohort Study (SHCS). RESULTS: Odds ratios for prematurity in women receiving mono/dual therapy and cART were 1.8 [95% confidence interval (CI) 0.85-3.6] and 2.5 (95% CI 1.4-4.3) compared with women not receiving ART during pregnancy (P=0.004). In a subgroup of 365 pregnancies with comprehensive information on maternal clinical, demographic and lifestyle characteristics, there was no indication that maternal viral load, age, ethnicity or history of injecting drug use affected prematurity rates associated with the use of cART. Duration of cART before delivery was also not associated with duration of pregnancy. CONCLUSION: Our study indicates that confounding by maternal risk factors or duration of cART exposure is not a likely explanation for the effects of ART on prematurity in HIV-1-infected women.

Demographic and clinical predictors of leptomeningeal collaterals in stroke patients.

BACKGROUND: Leptomeningeal collaterals improve outcome after stroke, including reduction of hemorrhagic complications after thrombolytic or endovascular therapy, smaller infarct size, and reduction in symptoms at follow-up evaluation. The purpose of this study was to determine the demographic and clinical variables that are associated with a greater degree of cerebral collaterals. METHODS: Clinical data of patients presenting with M1 occlusions of the middle cerebral artery (MCA) and associated computed tomography angiography studies after admission from 3 separate institutions were retrospectively compiled (n = 82). Occluded hemispheres were evaluated against the intact hemisphere for degree of collateralization in the MCA territory. Regression analysis of variance was conducted between clinical variables and collateral score to determine which variables associate with greater collateral development. RESULTS: Smaller infarct size corresponded to greater collateral scores, whereas older age and statin use corresponded to lower collateral scores (P < .001). CONCLUSIONS: Cerebral collateralization is influenced by age and statin use and influences infarct size.

Inferring the mode of origin of polyploid species from next-generation sequence data.

Many eukaryote organisms are polyploid. However, despite their importance, evolutionary inference of polyploid origins and modes of inheritance has been limited by a need for analyses of allele segregation at multiple loci using crosses. The increasing availability of sequence data for nonmodel species now allows the application of established approaches for the analysis of genomic data in polyploids. Here, we ask whether approximate Bayesian computation (ABC), applied to realistic traditional and next-generation sequence data, allows correct inference of the evolutionary and demographic history of polyploids. Using simulations, we evaluate the robustness of evolutionary inference by ABC for tetraploid species as a function of the number of individuals and loci sampled, and the presence or absence of an outgroup. We find that ABC adequately retrieves the recent evolutionary history of polyploid species on the basis of both old and new sequencing technologies. The application of ABC to sequence data from diploid and polyploid species of the plant genus Capsella confirms its utility. Our analysis strongly supports an allopolyploid origin of C. bursa-pastoris about 80 000 years ago. This conclusion runs contrary to previous findings based on the same data set but using an alternative approach and is in agreement with recent findings based on whole-genome sequencing. Our results indicate that ABC is a promising and powerful method for revealing the evolution of polyploid species, without the need to attribute alleles to a homeologous chromosome pair. The approach can readily be extended to more complex scenarios involving higher ploidy levels.

Reconstructing native American migrations from whole-genome and whole-exome data.

There is great scientific and popular interest in understanding the genetic history of populations in the Americas. We wish to understand when different regions of the continent were inhabited, where settlers came from, and how current inhabitants relate genetically to earlier populations. Recent studies unraveled parts of the genetic history of the continent using genotyping arrays and uniparental markers. The 1000 Genomes Project provides a unique opportunity for improving our understanding of population genetic history by providing over a hundred sequenced low coverage genomes and exomes from Colombian (CLM), Mexican-American (MXL), and Puerto Rican (PUR) populations. Here, we explore the genomic contributions of African, European, and especially Native American ancestry to these populations. Estimated Native American ancestry is 48% in MXL, 25% in CLM, and 13% in PUR. Native American ancestry in PUR is most closely related to populations surrounding the Orinoco River basin, confirming the Southern American ancestry of the Taíno people of the Caribbean. We present new methods to estimate the allele frequencies in the Native American fraction of the populations, and model their distribution using a demographic model for three ancestral Native American populations. These ancestral populations likely split in close succession: the most likely scenario, based on a peopling of the Americas 16 thousand years ago (kya), supports that the MXL Ancestors split 12.2kya, with a subsequent split of the ancestors to CLM and PUR 11.7kya. The model also features effective populations of 62,000 in Mexico, 8,700 in Colombia, and 1,900 in Puerto Rico. Modeling Identity-by-descent (IBD) and ancestry tract length, we show that post-contact populations also differ markedly in their effective sizes and migration patterns, with Puerto Rico showing the smallest effective size and the earlier migration from Europe. Finally, we compare IBD and ancestry assignments to find evidence for relatedness among European founders to the three populations.

The regional distribution of unemployment. What do micro-data tell us?

Regional disparities in unemployment rates are large and persistent. The literature provides evidence of their magnitude and evolution, as well as evidence of the role of certain economic, demographic and environmental factors in explaining the gap between regions of low and high unemployment. Most of these studies, however, adopt an aggregate approach and so do not account for the individual characteristics of the unemployed and employed in each region. This paper, by drawing on micro-data from the Spanish wave of the Labour Force Survey, seeks to remedy this shortcoming by analysing regional differentials in unemployment rates. An appropriate decomposition of the regional gap in the average probability of being unemployed enables us to distinguish between the contribution of differences in the regional distribution of individual characteristics from that attributable to a different impact of these characteristics on the probability of unemployment. Our results suggest that the well-documented disparities in regional unemployment are not just the result of regional heterogeneity in the distribution of individual characteristics. Non-negligible differences in the probability of unemployment remain after controlling for this type of heterogeneity, as a result of differences across regions in the impact of the observed characteristics. Among the factors considered in our analysis, regional differences in the endowment and impact of an individual’s education are shown to play a major role.

Classification models for neurocognitive impairment in HIV infection based on demographic and clinical variables

Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to btain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.

Data mining and mall users profile

Marketing scholars have suggested a need for more empirical research on consumer response to malls, in order to have a better understanding of the variables that explain the behavior of the consumers. The segmentation methodology CHAID (Chi-square automatic interaction detection) was used in order to identify the profiles of consumers with regard to their activities at malls, on the basis of socio-demographic variables and behavioral variables (how and with whom they go to the malls). A sample of 790 subjects answered an online questionnaire. The CHAID analysis of the results was used to identify the profiles of consumers with regard to their activities at malls. In the set of variables analyzed the transport used in order to go shopping and the frequency of visits to centers are the main predictors of behavior in malls. The results provide guidelines for the development of effective strategies to attract consumers to malls and retain them there.

Demographic Modelling of Human Population Growth

This work presents models and methods that have been used in producing forecasts of population growth. The work is intended to emphasize the reliability bounds of the model forecasts. Leslie model and various versions of logistic population models are presented. References to literature and several studies are given. A lot of relevant methodology has been developed in biological sciences. The Leslie modelling approach involves the use of current trends in mortality,fertility, migration and emigration. The model treats population divided in age groups and the model is given as a recursive system. Other group of models is based on straightforward extrapolation of census data. Trajectories of simple exponential growth function and logistic models are used to produce the forecast. The work presents the basics of Leslie type modelling and the logistic models, including multi- parameter logistic functions. The latter model is also analysed from model reliability point of view. Bayesian approach and MCMC method are used to create error bounds of the model predictions.

Normative data for the Brazilian population in the Boston Diagnostic Aphasia Examination: influence of schooling

In Neurolinguistics, the use of diagnostic tests developed in other countries can create difficulties in the interpretation of results due to cultural, demographic and linguistic differences. In a country such as Brazil, with great social contrasts, schooling exerts a powerful influence on the abilities of normal individuals. The objective of the present study was to identify the influence of schooling on the performance of normal Brazilian individuals in the Boston Diagnostic Aphasia Examination (BDAE), in order to obtain reference values for the Brazilian population. We studied 107 normal subjects ranging in age from 15 to 84 years (mean ± SD = 47.2 ± 17.6 years), with educational level ranging from 1 to 24 years (9.9 ± 4.8 years). Subjects were compared for scores obtained in the 28 subtests of the BDAE after being divided into groups according to age (15 to 30, N = 24, 31 to 50, N = 33 and 51 years or more, N = 50) and education (1 to 4, N = 26, 5 to 8, N = 17 and 9 years or more, N = 61). Subjects with 4 years or less of education performed poorer in Word Discrimination, Visual Confrontation Naming, Reading of Sentences and Paragraphs, and Primer-Level Dictation (P < 0.05). When breakdown by schooling was 8 years or less, subjects performed poorer in all subtests (P < 0.05), except Responsive Naming, Word Recognition and Word-Picture Matching. The elderly performed poorer (P < 0.05) in Complex Ideational Material, Visual Confrontation Naming, Comprehension of Oral Spelling, Written Confrontation Naming, and Sentences to Dictation. We present the reference values for the cut-off scores according to educational level.