952 resultados para Linear models (Statistics)


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PURPOSE: Bioaerosols and their constituents, such as endotoxins, are capable of causing an inflammatory reaction at the level of the lung-blood barrier, which becomes more permeable. Thus, it was hypothesized that occupational exposure to bioaerosols can increase leakage of surfactant protein-D (SP-D), a lung-specific protein, into the bloodstream. METHODS: SP-D was determined by ELISA in 316 wastewater workers, 67 garbage collectors, and 395 control subjects. Exposure was assessed with four interview-based indicators and by preliminary endotoxin measurements using the Limulus amoebocyte lysate assay. Influence of exposure on serum SP-D was assessed by multiple linear regression considering smoking, glomerular function, lung diseases, obesity, and other confounders. RESULTS: Overall, mean exposure levels to endotoxins were below 100 EU/m(3). However, special tasks of wastewater workers caused higher endotoxin exposure. SP-D concentration was slightly increased in this occupational group and associated with the occurrence of splashes and contact to raw sewage. No effect was found in garbage collectors. Smoking increased serum SP-D. No clinically relevant correlation between spirometry results and SP-D concentrations appeared. CONCLUSIONS: These results support the hypothesis that inhalation of bioaerosols, even at low concentrations, has a subclinical effect on the lung-blood barrier, the permeability of which increases without associated spirometric changes.

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OBJECTIVES: Age- and height-adjusted spirometric lung function of South Asian children is lower than those of white children. It is unclear whether this is purely genetic, or partly explained by the environment. In this study, we assessed whether cultural factors, socioeconomic status, intrauterine growth, environmental exposures, or a family and personal history of wheeze contribute to explaining the ethnic differences in spirometric lung function. METHODS: We studied children aged 9 to 14 years from a population-based cohort, including 1088 white children and 275 UK-born South Asians. Log-transformed spirometric data were analyzed using multiple linear regressions, adjusting for anthropometric factors. Five different additional models adjusted for (1) cultural factors, (2) indicators of socioeconomic status, (3) perinatal data reflecting intrauterine growth, (4) environmental exposures, and (5) personal and family history of wheeze. RESULTS: Height- and gender-adjusted forced vital capacity (FVC) and forced expired volume in 1 second (FEV1) were lower in South Asian than white children (relative difference -11% and -9% respectively, P < .001), but PEF and FEF50 were similar (P ≥ .5). FEV1/FVC was higher in South Asians (1.8%, P < .001). These differences remained largely unchanged in all 5 alternative models. CONCLUSIONS: Our study confirmed important differences in lung volumes between South Asian and white children. These were not attenuated after adjustment for cultural and socioeconomic factors and intrauterine growth, neither were they explained by differences in environmental exposures nor a personal or family history of wheeze. This suggests that differences in lung function may be mainly genetic in origin. The implication is that ethnicity-specific predicted values remain important specifically for South Asian children.

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Western European landscapes have drastically changed since the 1950s, with agricultural intensifications and the spread of urban settlements considered the most important drivers of this land-use/land-cover change. Losses of habitat for fauna and flora have been a direct consequence of this development. In the present study, we relate butterfly occurrence to land-use/land-cover changes over five decades between 1951 and 2000. The study area covers the entire Swiss territory. The 10 explanatory variables originate from agricultural statistics and censuses. Both state as well as rate was used as explanatory variables. Species distribution data were obtained from natural history collections. We selected eight butterfly species: four species occur on wetlands and four occur on dry grasslands. We used cluster analysis to track land-use/land-cover changes and to group communes based on similar trajectories of change. Generalized linear models were applied to identify factors that were significantly correlated with the persistence or disappearance of butterfly species. Results showed that decreasing agricultural areas and densities of farms with more than 10 ha of cultivated land are significantly related with wetland species decline, and increasing densities of livestock seem to have favored disappearance of dry grassland species. Moreover, we show that species declines are not only dependent on land-use/land-cover states but also on the rates of change; that is, the higher the transformation rate from small to large farms, the higher the loss of dry grassland species. We suggest that more attention should be paid to the rates of landscape change as feasible drivers of species change and derive some management suggestions.

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Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

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OBJECTIVE: Renal cytochrome P450 3A5 (CYP3A5) activity has been associated with blood pressure and salt sensitivity in humans. We determined whether CYP3A5 polymorphisms are associated with ambulatory blood pressure (ABP) and with glomerular filtration rate (GFR) in African families. METHODS: Using a cross-sectional design, 375 individuals from 72 families, each with at least two hypertensive siblings, were recruited through a hypertension register in the Seychelles (Indian Ocean). We analyzed the association between the CYP3A5 alleles (*1, *3, *6 and *7) and ABP, GFR and renal sodium handling (fractional excretion of lithium), from pedigree data, allowing for other covariates and familial correlations. RESULTS: CYP3A5*1 carriers increased their daytime systolic and diastolic ABP with age (0.55 and 0.23 mmHg/year) more than non-carriers (0.21 and 0.04 mmHg/year). CYP3A5*1 had a significant main effect on daytime systolic/diastolic ABP [regression coefficient (SE): -29.6 (10.0)/-8.2 (4.1) mmHg, P = 0.003/0.045, respectively] and this effect was modified by age (CYP3A5*1 x age interactions, P = 0.017/0.018). For night-time ABP, the effect of CYP3A5*1 was modified by urinary sodium excretion, not by age. For renal function, CYP3A5*1 carriers had a 7.6(3.8) ml/min lower GFR (P = 0.045) than non-carriers. Proximal sodium reabsorption decreased with age in non-carriers, but not in CYP3A5*1 carriers (P for interaction = 0.02). CONCLUSIONS: These data demonstrate that CYP3A5 polymorphisms are associated with ambulatory BP, CYP3A5*1 carriers showing a higher age- and sodium- related increase in ABP than non-carriers. The age effect may be due, in part, to the action of CYP3A5 on renal sodium handling.

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Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.

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PURPOSE: Not in Education, Employment, or Training (NEET) youth are youth disengaged from major social institutions and constitute a worrying concern. However, little is known about this subgroup of vulnerable youth. This study aimed to examine if NEET youth differ from other contemporaries in terms of personality, mental health, and substance use and to provide longitudinal examination of NEET status, testing its stability and prospective pathways with mental health and substance use. METHODS: As part of the Cohort Study on Substance Use Risk Factors, 4,758 young Swiss men in their early 20s answered questions concerning their current professional and educational status, personality, substance use, and symptomatology related to mental health. Descriptive statistics, generalized linear models for cross-sectional comparisons, and cross-lagged panel models for longitudinal associations were computed. RESULTS: NEET youth were 6.1% at baseline and 7.4% at follow-up with 1.4% being NEET at both time points. Comparisons between NEET and non-NEET youth showed significant differences in substance use and depressive symptoms only. Longitudinal associations showed that previous mental health, cannabis use, and daily smoking increased the likelihood of being NEET. Reverse causal paths were nonsignificant. CONCLUSIONS: NEET status seemed to be unlikely and transient among young Swiss men, associated with differences in mental health and substance use but not in personality. Causal paths presented NEET status as a consequence of mental health and substance use rather than a cause. Additionally, this study confirmed that cannabis use and daily smoking are public health problems. Prevention programs need to focus on these vulnerable youth to avoid them being disengaged.

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Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

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BACKGROUND. Autoimmunity appears to be associated with the pathophysiology of Meniere's disease (MD), an inner ear disorder characterized by episodes of vertigo associated with hearing loss and tinnitus. However, the prevalence of autoimmune diseases (AD) in patients with MD has not been studied in individuals with uni or bilateral sensorineural hearing loss (SNHL). METHODS AND FINDINGS. We estimated the prevalence of AD in 690 outpatients with MD with uni or bilateral SNHL from otoneurology clinics at six tertiary referral hospitals by using clinica criteria and an immune panel (lymphocyte populations, antinuclear antibodies, C3, C4 and proinflammatory cytokines TNFα, INFγ). The observed prevalence of rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and ankylosing spondylitis (AS) was higher than expected for the general population (1.39 for RA, 0.87 for SLE and 0.70 for AS, respectively). Systemic AD were more frequently observed in patients with MD and diagnostic criteria for migraine than cases with MD and tension-type headache (p = 0.007). There were clinical differences between patients with uni or bilateral SNHL, but no differences were found in the immune profile. Multiple linear regression showed that changes in lymphocytes subpopulations were associated with hearing loss and persistence of vertigo, suggesting a role for the immune response in MD. CONCLUSIONS. Despite some limitations, MD displays an elevated prevalence of systemic AD such as RA, SLE and AS. This finding, which suggests an autoimmune background in a subset of patients with MD, has important implications for the treatment of MD.

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Ambulatory blood pressure (BP) monitoring has become useful in the diagnosis and management of hypertensive individuals. In addition to 24-hour values, the circadian variation of BP adds prognostic significance in predicting cardiovascular outcome. However, the magnitude of circadian BP patterns in large studies has hardly been noticed. Our aims were to determine the prevalence of circadian BP patterns and to assess clinical conditions associated with the nondipping status in groups of both treated and untreated hypertensive subjects, studied separately. Clinical data and 24-hour ambulatory BP monitoring were obtained from 42,947 hypertensive patients included in the Spanish Society of Hypertension Ambulatory Blood Pressure Monitoring Registry. They were 8384 previously untreated and 34,563 treated hypertensives. Twenty-four-hour ambulatory BP monitoring was performed with an oscillometric device (SpaceLabs 90207). A nondipping pattern was defined when nocturnal systolic BP dip was <10% of daytime systolic BP. The prevalence of nondipping was 41% in the untreated group and 53% in treated patients. In both groups, advanced age, obesity, diabetes mellitus, and overt cardiovascular or renal disease were associated with a blunted nocturnal BP decline (P<0.001). In treated patients, nondipping was associated with the use of a higher number of antihypertensive drugs but not with the time of the day at which antihypertensive drugs were administered. In conclusion, a blunted nocturnal BP dip (the nondipping pattern) is common in hypertensive patients. A clinical pattern of high cardiovascular risk is associated with nondipping, suggesting that the blunted nocturnal BP dip may be merely a marker of high cardiovascular risk.

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BACKGROUND The effect of the macronutrient composition of the usual diet on long term weight maintenance remains controversial. METHODS 373,803 subjects aged 25-70 years were recruited in 10 European countries (1992-2000) in the PANACEA project of the EPIC cohort. Diet was assessed at baseline using country-specific validated questionnaires and weight and height were measured at baseline and self-reported at follow-up in most centers. The association between weight change after 5 years of follow-up and the iso-energetic replacement of 5% of energy from one macronutrient by 5% of energy from another macronutrient was assessed using multivariate linear mixed-models. The risk of becoming overweight or obese after 5 years was investigated using multivariate Poisson regressions stratified according to initial Body Mass Index. RESULTS A higher proportion of energy from fat at the expense of carbohydrates was not significantly associated with weight change after 5 years. However, a higher proportion of energy from protein at the expense of fat was positively associated with weight gain. A higher proportion of energy from protein at the expense of carbohydrates was also positively associated with weight gain, especially when carbohydrates were rich in fibre. The association between percentage of energy from protein and weight change was slightly stronger in overweight participants, former smokers, participants ≥60 years old, participants underreporting their energy intake and participants with a prudent dietary pattern. Compared to diets with no more than 14% of energy from protein, diets with more than 22% of energy from protein were associated with a 23-24% higher risk of becoming overweight or obese in normal weight and overweight subjects at baseline. CONCLUSION Our results show that participants consuming an amount of protein above the protein intake recommended by the American Diabetes Association may experience a higher risk of becoming overweight or obese during adult life.

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OBJECTIVE We investigated the association between the proportion of long-chain n-3 polyunsaturated fatty acids (PUFA) in plasma phospholipids from blood samples drawn at enrollment and subsequent change in body weight. Sex, age, and BMI were considered as potential effect modifiers. METHOD A total of 1,998 women and men participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) were followed for a median of 4.9 years. The associations between the proportion of plasma phospholipid long-chain n-3 PUFA and change in weight were investigated using mixed-effect linear regression. RESULTS The proportion of long-chain n-3 PUFA was not associated with change in weight. Among all participants, the 1-year weight change was -0.7 g per 1% point higher long-chain n-3 PUFA level (95% confidence interval: -20.7 to 19.3). The results when stratified by sex, age, or BMI groups were not systematically different. CONCLUSION The results of this study suggest that the proportion of long-chain n-3 PUFA in plasma phospholipids is not associated with subsequent change in body weight within the range of exposure in the general population.

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OBJECTIVE: To investigate the association between fear of falling and gait performance in well-functioning older persons. DESIGN: Survey. SETTING: Community. PARTICIPANTS: Subjects (N=860, aged 65-70y) were a subsample of participants enrolled in a cohort study who underwent gait measurements. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Fear of falling and its severity were assessed by 2 questions about fear and related activity restriction. Gait performance, including gait variability, was measured using body-fixed sensors. RESULTS: Overall, 29.6% (210/860) of the participants reported fear of falling, with 5.2% (45/860) reporting activity restriction. Fear of falling was associated with reduced gait performance, including increased gait variability. A gradient in gait performance was observed from participants without fear to those reporting fear without activity restriction and those reporting both fear and activity restriction. For instance, stride velocity decreased from 1.15+/-.15 to 1.11+/-.17 to 1.00+/-.19 m/s (P<.001) in participants without fear, with fear but no activity restriction and with fear and activity restriction, respectively. In multivariate analysis, fear of falling with activity restriction remained associated with reduced gait performance, independent of sex, comorbidity, functional status, falls history, and depressive symptoms. CONCLUSIONS: In these well-functioning older people, those reporting fear of falling with activity restriction had reduced gait performance and increased gait variability, independent of health and functional status. These relationships suggest that early interventions targeting fear of falling might potentially help to prevent its adverse consequences on mobility and function in similar populations.

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The mathematical representation of Brunswik s lens model has been usedextensively to study human judgment and provides a unique opportunity to conduct ameta-analysis of studies that covers roughly five decades. Specifically, we analyzestatistics of the lens model equation (Tucker, 1964) associated with 259 different taskenvironments obtained from 78 papers. In short, we find on average fairly high levelsof judgmental achievement and note that people can achieve similar levels of cognitiveperformance in both noisy and predictable environments. Although overall performancevaries little between laboratory and field studies, both differ in terms of components ofperformance and types of environments (numbers of cues and redundancy). An analysisof learning studies reveals that the most effective form of feedback is information aboutthe task. We also analyze empirically when bootstrapping is more likely to occur. Weconclude by indicating shortcomings of the kinds of studies conducted to date, limitationsin the lens model methodology, and possibilities for future research.

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Este trabalho baseia-se na análise de dados do desemprego em Cabo Verde nos anos de 2006 e 2008, usando informação da base de dados do INE e IEFP. Partindo da análise dos dados em estudo vai-se procurar descrever e perspectivar metodologias que contemplam as variáveis qualitativas e quantitativas com significado social positivo para a sociedade deste país. Após a introdução no capítulo 1, fez-se, no capítulo 2, a análise exploratória dos dados do desemprego em Cabo Verde referente aos anos 2006 e 2008. No capítulo 3 estudam-se associações entre variáveis, usando a metodologia de tabelas contingência, através da realização de testes de independência e testes de homogeneidade, e análise de medidas de associação. As variáveis usadas, vão ser essencialmente, o escalão etário, o género e o ano. O capítulo 4 é dedicado ao estudo de modelos Log - lineares em tabela de contingência, finalizando-se o trabalho com a apresentação das principais conclusões.