Underreporting of Energy Intake in Brazilian Women Varies According to Dietary Assessment: A Cross-Sectional Study Using Doubly Labeled Water

Objective Underreporting of energy intake is prevalent in food surveys, but there is controversy about which dietary assessment method provides greater underreporting rates. Our objective is to compare validity of self-reported energy intake obtained by three dietary assessment methods with total energy expenditure (TEE) obtained by doubly labeled water (DLW) among Brazilian women. Design We used a cross-sectional study. Subjects/setting Sixty-five females aged 18 to 57 years (28 normal-weight, 10 over-weight, and 27 obese) were recruited from two universities to participate. Main outcome measures TEE determined by DLW, energy intake estimated by three 24-hour recalls, 3-day food record, and a food frequency questionnaire (FFQ). Statistical analyses performed Regression and analysis of variance with repeated measures compared TEE and energy intake values, and energy intake-to-TEE ratios and energy intake-TEE values between dietary assessment methods. Bland and Altman plots were provided for each method. chi(2) test compared proportion of underreporters between the methods. Results Mean TEE was 2,622 kcal (standard deviation [SD] =490 kcal), while mean energy intake was 2,078 kcal (SD=430 kcal) for the diet recalls; 2,044 kcal (SD=479 kcal) for the food record and 1,984 kcal (SD=832 kcal) for the FFQ (all energy intake values significantly differed from TEE; P<0.0001). Bland and Altman plots indicated great dispersion, negative mean differences between measurements, and wide limits of agreement. Obese subjects underreported more than normal-weight subjects in the diet recalls and in the food records, but not in the FFQ. Years of education, income and ethnicity were associated with reporting accuracy. Conclusions The FFQ produced greater under- and overestimation of energy intake. Underreporting of energy intake is a serious and prevalent error in dietary self-reports provided by Brazilian women, as has been described in studies conducted in developed countries.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

The numbers of sample design for evaluation of the soil fertility

The determination of the amount of sample units that will compose the sample express the optimization of the workforce, and reduce errors inherent in the report of recommendation and evaluation of soil fertility. This study aimed to determine in three systems use and soil management, the numbers of units samples design, needed to form the composed sample, for evaluation of soil fertility. It was concluded that the number of sample units needed to compose the composed sample to determination the attributes of organic matter, pH, P, K, Ca, Mg, Al and H+Al and base saturation of soil vary by use and soil management and error acceptable to the mean estimate. For the same depth of collected, increasing the number of sample units, reduced the percentage error in estimating the average, allowing the recommendation of 14, 14 and 11 sample in management with native vegetation, pasture cultivation and corn, respectively, for a error 20% on the mean estimate.

An improved finite element space for discontinuous pressures

We consider incompressible Stokes flow with an internal interface at which the pressure is discontinuous, as happens for example in problems involving surface tension. We assume that the mesh does not follow the interface, which makes classical interpolation spaces to yield suboptimal convergence rates (typically, the interpolation error in the L(2)(Omega)-norm is of order h(1/2)). We propose a modification of the P(1)-conforming space that accommodates discontinuities at the interface without introducing additional degrees of freedom or modifying the sparsity pattern of the linear system. The unknowns are the pressure values at the vertices of the mesh and the basis functions are computed locally at each element, so that the implementation of the proposed space into existing codes is straightforward. With this modification, numerical tests show that the interpolation order improves to O(h(3/2)). The new pressure space is implemented for the stable P(1)(+)/P(1) mini-element discretization, and for the stabilized equal-order P(1)/P(1) discretization. Assessment is carried out for Poiseuille flow with a forcing surface and for a static bubble. In all cases the proposed pressure space leads to improved convergence orders and to more accurate results than the standard P(1) space. In addition, two Navier-Stokes simulations with moving interfaces (Rayleigh-Taylor instability and merging bubbles) are reported to show that the proposed space is robust enough to carry out realistic simulations. (c) 2009 Elsevier B.V. All rights reserved.