Proposal of a short-form version of the Brazilian Food Insecurity Scale

OBJECTIVE To propose a short version of the Brazilian Food Insecurity Scale. METHODS Two samples were used to test the results obtained in the analyses in two distinct scenarios. One of the studies was composed of 230 low income families from Pelotas, RS, Southern Brazil, and the other was composed of 15,575 women, whose data were obtained from the 2006 National Survey on Demography and Health. Two models were tested, the first containing seven questions, and the second, the five questions that were considered the most relevant ones in the concordance analysis. The models were compared to the Brazilian Food Insecurity Scale, and the sensitivity, specificity and accuracy parameters were calculated, as well as the kappa agreement test. RESULTS Comparing the prevalence of food insecurity between the Brazilian Food Insecurity Scale and the two models, the differences were around 2 percentage points. In the sensitivity analysis, the short version of seven questions obtained 97.8% and 99.5% in the Pelotas sample and in the National Survey on Demography and Health sample, respectively, while specificity was 100% in both studies. The five-question model showed similar results (sensitivity of 95.7% and 99.5% in the Pelotas sample and in the National Survey on Demography and Health sample, respectively). In the Pelotas sample, the kappa test of the seven-question version totaled 97.0% and that of the five-question version, 95.0%. In the National Survey on Demography and Health sample, the two models presented a 99.0% kappa. CONCLUSIONS We suggest that the model with five questions should be used as the short version of the Brazilian Food Insecurity Scale, as its results were similar to the original scale with a lower number of questions. This version needs to be administered to other populations in Brazil in order to allow for the adequate assessment of the validity parameters.

Handling random errors and biases in methods used for short-term dietary assessment

Epidemiological studies have shown the effect of diet on the incidence of chronic diseases; however, proper planning, designing, and statistical modeling are necessary to obtain precise and accurate food consumption data. Evaluation methods used for short-term assessment of food consumption of a population, such as tracking of food intake over 24h or food diaries, can be affected by random errors or biases inherent to the method. Statistical modeling is used to handle random errors, whereas proper designing and sampling are essential for controlling biases. The present study aimed to analyze potential biases and random errors and determine how they affect the results. We also aimed to identify ways to prevent them and/or to use statistical approaches in epidemiological studies involving dietary assessments.

Wind-CSP short-term coordination by Milp approach

This paper is on the maximization of total profit in a day-ahead market for a price-taker producer needing a short-term scheduling for wind power plants coordination with concentrated solar power plants, having thermal energy storage systems. The optimization approach proposed for the maximization of profit is a mixed-integer linear programming problem. The approach considers not only transmission grid constraints, but also technical operating constraints on both wind and concentrated solar power plants. Then, an improved short-term scheduling coordination is provided due to the more accurate modelling presented in this paper. Computer simulation results based on data for the Iberian wind and concentrated solar power plants illustrate the coordination benefits and show the effectiveness of the approach.