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Rossato, Sinara

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Rossato

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Sinara

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Rossato, Sinara
Author's Publications: search.filters.isAuthorOfPublication.3878e936-d282-4d07-889c-963457f22dbc

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    Handling random errors and biases in methods used for short-term dietary assessment
    (Faculdade de Saúde Pública da Universidade de São Paulo, 2014) Rossato, Sinara; Fuchs, Sandra C
    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.
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    Seasonal variation in food intake and the interaction effects of sex and age among adults in southern Brazil
    (Springer Nature, 2015) Rossato, Sinara; Olinto, M T A; Henn, R L; Moreira, L B; Camey, S A; Anjos, L A; Wahrlich, V; Waissmann, W; Fuchs, F D; Fuchs, S C
    Background/Objective: Because studies have evidenced variations 1 in nutrient intake, further investigation of the interaction between demographic characteristics and the seasons is necessary. We aimed to test the differences in food intake throughout the seasons and the interaction between the seasons and sex and age. Methods: This study included 273 individuals. Food intake was evaluated with 24-hour dietary recalls, and the reported food items were sorted into food groups. We performed the test on the differences in intake of food groups throughout the seasons with repeated measures and on the interaction by using the Generalized Estimate Equation (GEE). Results: Intake of fruits and natural fruit juices and sweetened beverages was lower, while that of grains and derivatives was higher in the winter. The intake of leafy vegetables and fish and seafood was lower in the autumn. The consumption of coffee and eggs was higher in the spring. Ingestion of chocolate powder and sugar, salt, and lean poultry was higher in the winter. The variation in consumption of grains and derivatives, eggs, fatty poultry, and processed meat over the seasons was more likely to be modified by sex. Age interacted with the seasons for leafy vegetables, beans and lentils, lean beef, lean poultry, low fat milk and light yogurt, vegetable oil and unsalted margarine, chocolate powder and sugar, and processed meat. Conclusion: This study shows that food intake may change seasonally and that seasonal variation depends on sex and age, which might aggregate a specific co-variation component.