Statistical Innovations Improve Prevalence Estimates of Nutrient Risk Populations: Applications in Sao Paulo, Brazil

The objective of this study was to estimate the prevalence of inadequate micronutrient intake and excess sodium intake among adults age 19 years and older in the city of Sao Paulo, Brazil. Twenty-four hour dietary recall and sociodemographic data were collected from each participant (n=1,663) in a cross-sectional study, Inquiry of Health of Sao Paulo, of a representative sample of the adult population of the city of Sao Paulo in 2003 (ISA-2003). The variability in intake was measured through two replications of the 24-hour recall in a subsample of this population in 2007 (ISA-2007). Usual intake was estimated by the PC-SIDE program (version 1.0, 2003, Department of Statistics, Iowa State University), which uses an approach developed by Iowa State University. The prevalence of nutrient inadequacy was calculated using the Estimated Average Requirement cut-point method for vitamins A and C, thiamin, riboflavin, niacin, copper, phosphorus, and selenium. For vitamin D, pantothenic acid, manganese, and sodium, the proportion of individuals with usual intake equal to or more than the Adequate Intake value was calculated. The percentage of individuals with intake equal to more than the Tolerable Upper Intake Level was calculated for sodium. The highest prevalence of inadequacy for males and females, respectively, occurred for vitamin A (67% and 58%), vitamin C (52% and 62%), thiamin (41% and 50%), and riboflavin (29% and 19%). The adjustment for the within-person variation presented lower prevalence of inadequacy due to removal of within-person variability. All adult residents of Sao Paulo had excess sodium intake, and the rates of nutrient inadequacy were high for certain key micronutrients. J Acad Nutr Diet. 2012;112:1614-1618.

STATISTICAL TEST FOR GENOTYPE AND ENVIRONMENT CONTRIBUTION IN THE GENOTYPES x ENVIRONMENTS INTERACTION MATRIX

The objective of the present work was to propose a method for testing the contribution of each level of the factors in a genotypes x environments (GxE) interaction using multi-environment trials analyses by means of an F test. The study evaluated a data set, with twenty genotypes and thirty-four environments, in a block design with four replications. The sum of squares within rows (genotypes) and columns (environments) of the GxE matrix was simulated, generating 10000 experiments to verify the empirical distribution. Results indicate a noncentral chi-square distribution for rows and columns of the GxE interaction matrix, which was also verified by the Kolmogorov-Smirnov test and Q-Q plot. Application of the F test identified the genotypes and environments that contributed the most to the GxE interaction. In this way, geneticists can select good genotypes in their studies.

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

Probing the statistical properties of unknown texts: application to the Voynich manuscript

While the use of statistical physics methods to analyze large corpora has been useful to unveil many patterns in texts, no comprehensive investigation has been performed on the interdependence between syntactic and semantic factors. In this study we propose a framework for determining whether a text (e.g., written in an unknown alphabet) is compatible with a natural language and to which language it could belong. The approach is based on three types of statistical measurements, i.e. obtained from first-order statistics of word properties in a text, from the topology of complex networks representing texts, and from intermittency concepts where text is treated as a time series. Comparative experiments were performed with the New Testament in 15 different languages and with distinct books in English and Portuguese in order to quantify the dependency of the different measurements on the language and on the story being told in the book. The metrics found to be informative in distinguishing real texts from their shuffled versions include assortativity, degree and selectivity of words. As an illustration, we analyze an undeciphered medieval manuscript known as the Voynich Manuscript. We show that it is mostly compatible with natural languages and incompatible with random texts. We also obtain candidates for keywords of the Voynich Manuscript which could be helpful in the effort of deciphering it. Because we were able to identify statistical measurements that are more dependent on the syntax than on the semantics, the framework may also serve for text analysis in language-dependent applications.