Dietary omega-3 fatty acid and omega-3: omega-6 fatty acid ratio predict improvement in glucose disturbances in Japanese Brazilians

Objective: We investigated whether lifestyle-induced changes in dietary fat quality are related to Improvements on glucose metabolism disturbances in Japanese Brazilians at high risk of type 2 diabetes Methods: One hundred forty-eight first- and second-generation subjects with impaired glucose tolerance or impaired fasting glycemia who attended a lifestyle intervention program for 12 mo were studied in the city of Bauru. State of Sao Paulo, Brazil Dietary fatty acid intakes at baseline and after 12 mo were estimated using three 24-h recalls. The effect of dietary fat intake on glucose metabolism was investigated by multiple logistic regression models Results: At baseline, mean standard deviation age and body mass index were 60 II y and 25 5 4.2 kg/m2, respectively After 12 mo. 92 subjects had normal plasma glucose levels and 56 remained in prediabetic conditions. Using logistic regression models adjusted for age, gender, generation, basal intake of explanatory nutrient, energy intake, physical activity, and waist circumference, the odds ratios (95% confidence intervals) for reversion to normoglycemia were 3 14 (1 22-8 10) in the second wrote of total w-3 fatty acid, 4 26 (1.34-13 57) in the second tunic of eicosapentaenoic acid, and 280 (1 10-7.10) in the second tertile of linolenic acid. Similarly. subjects in the highest wrote of w-3.w-6 fatty acid ratio showed a higher chance of improving glucose disturbances (2 51, 1.01-6.37) Conclusions: Our findings support the evidence of an independent protective effect of omega-3 fatty acid and of a higher omega-3:omega-6 fatty acid ratio on the glucose metabolism of high-risk individuals (C) 2010 Elsevier Inc All rights reserved.

Comparing time-varying autoregressive structures of locally stationary processes

In this paper, a novel statistical test is introduced to compare two locally stationary time series. The proposed approach is a Wald test considering time-varying autoregressive modeling and function projections in adequate spaces. The covariance structure of the innovations may be also time- varying. In order to obtain function estimators for the time- varying autoregressive parameters, we consider function expansions in splines and wavelet bases. Simulation studies provide evidence that the proposed test has a good performance. We also assess its usefulness when applied to a financial time series.

Influence diagnostics for linear models with first-order autoregressive elliptical errors

We introduce in this paper the class of linear models with first-order autoregressive elliptical errors. The score functions and the Fisher information matrices are derived for the parameters of interest and an iterative process is proposed for the parameter estimation. Some robustness aspects of the maximum likelihood estimates are discussed. The normal curvatures of local influence are also derived for some usual perturbation schemes whereas diagnostic graphics to assess the sensitivity of the maximum likelihood estimates are proposed. The methodology is applied to analyse the daily log excess return on the Microsoft whose empirical distributions appear to have AR(1) and heavy-tailed errors. (C) 2008 Elsevier B.V. All rights reserved.

Testing common nonlinear features in vector nonlinear autoregressive models

This paper studies a special class of vector smooth-transition autoregressive (VSTAR) models that contains common nonlinear features (CNFs), for which we proposed a triangular representation and developed a procedure of testing CNFs in a VSTAR model. We first test a unit root against a stable STAR process for each individual time series and then examine whether CNFs exist in the system by Lagrange Multiplier (LM) test if unit root is rejected in the first step. The LM test has standard Chi-squared asymptotic distribution. The critical values of our unit root tests and small-sample properties of the F form of our LM test are studied by Monte Carlo simulations. We illustrate how to test and model CNFs using the monthly growth of consumption and income data of United States (1985:1 to 2011:11).

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE transactions data, with special attention to IBM price durations. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE price duration data on the IBM stock. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems

This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.

A (semi-)parametric functional coefficient autoregressive conditional duration model

In this paper, we propose a class of ACD-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and sign and size asymmetries in financial durations. In particular, our functional coefficient autoregressive conditional duration (FC-ACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing that the sufficient conditions for strict stationarity do not exclude explosive regimes, we address model identifiability as well as the existence, consistency, and asymptotic normality of the quasi-maximum likelihood (QML) estimator for the FC-ACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate using a sieve approach a semiparametric variant of the FC-ACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations.

Assessing global economic activity linkages: an empirical exercise based on global autoregressive regression

Economic performance increasingly relies on global economic environment due to the growing importance of trade and nancial links among countries. Literature on growth spillovers shows various gains obtained by this interaction. This work aims at analyzing the possible e ects of a potential economic growth downturn in China, Germany and United States on the growth of other economies. We use global autoregressive regression approach to assess interdependence among countries. Two types of phenomena are simulated. The rst one is a one time shock that hit these economies. Our simulations use a large shock of -2.5 standard deviations, a gure very similar to what we saw back in the 2008 crises. The second experiment simulate the e ect of a hypothetical downturn of the aforementioned economies. Our results suggest that the United States play the role of a global economy a ecting countries across the globe whereas Germany and China play a regional role.

Double sampling (x)over-bar control chart for a first-order autoregressive moving average process model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Performance, incidence of metabolic disturbances and endocrine variables of food-restricted male broiler chickens

1. This experiment was carried out to evaluate the productive and physiological consequences of a slight but long term food restriction of male broiler chickens from 2 commercial strains.2. Cobb-500 and Ross chickens were submitted to a 20% food restriction from 8 to 21 d of age. Strain, food programme and their interactive effects were analysed in terms of consequences upon performance, mortality, incidence of sudden death syndrome (SDS) and ascites syndrome (AS), index of right cardiac hypertrophy and plasma concentrations of hormones related to metabolism and growth (T-3, T-4, T-3:T-4 ratio, IGF-I and GH).3. Although some catch-up growth was observed by refeeding previously restricted birds after 22 d of rearing, food restriction decreased (P less than or equal to 0.05) body weight at market age (42 d) irrespective of the strain, but improved (P less than or equal to 0.05) food conversion.4. The incidence of mortality was not high in non-restricted birds but SDS and AS caused more than 50% of deaths. Hypertrophic cardiac index was observed in chickens of both strains after 4 weeks of age and was higher in ad libitum fed birds.5. During the period of food restriction, plasma T-3 and IGF-I concentrations decreased whereas plasma T-4 and GH concentrations increased compared to those of the age-matched ad libitum fed counterparts. During the subsequent ad libitum feeding period, few differences in circulating hormone concentrations were observed, except for the higher mean CH litres in previously food-restricted chickens at 35 d of age.6. These results indicate that even a non-severe food restriction negatively affects body weight of 42-d-old male broilers but these are benefits with improved food efficiency and diminished mortality from metabolic disturbances. The hormone results suggest that the degree of food restriction applied was not severe because there was a very fast adaptive response with small and transient alterations in T-3, T-4 and GH plasma concentrations during the period of compensatory growth.

Physical activity attenuates neuropsychiatric disturbances and caregiver burden in patients with dementia

INTRODUCTION: A significant benefit from physical activity has recently been described in some patients who suffer from neurodegenerative diseases. OBJECTIVE: To assess the effects of physical activity on neuropsychiatric disturbances in demented patients and on the mental burden of their caregivers. METHODS: Assisted by a public geriatric psychiatry clinical unit, we studied 59 patients with dementia. Patients were divided into three groups according to their diagnosis and level of physical activity. Data were assessed through a semi-structured interview. Patients were evaluated with the Neuropsychiatric Inventory, the Mini-Sleep Questionnaire and the Baecke Questionnaire. The data were statistically analyzed using the Mann-Whitney U test and linear regression, with the level of significance set at 5%. RESULTS: Patients with Alzheimer's or vascular dementia who engaged in physical activity had fewer neuropsychiatric symptoms than those who did not. When compared to the control group, the caregivers of patients with vascular dementia who engaged in physical activity had a reduced burden. CONCLUSION: The regular practice of physical activity seems to contribute to a reduction in neuropsychiatric symptoms in dementia patients and to attenuate the burden of the caregivers of those patients.