Eating disorders and body image satisfaction among brazilian undergraduate nutrition students and dietitians

The objective of this study was to evaluate the prevalence of risk behaviors related to eating disorders and body image satisfaction among Brazilian dietitians and undergraduate Nutrition students. The national representative sample was composed of 427 undergraduate students of Nutrition and 318 dietitians. Data were collected via an online questionnaire. Body image satisfaction was assessed by the Body Shape Questionnaire, and attitudes suggestive of an eating disorder (called positive EAT) were assessed by the Eating Attitudes Test. Adjusted Prevalence Ratios were performed by Poisson’s regression. More than 50.0% of women were dissatisfied with their body image, but severe dissatisfaction was more prevalent among students (26.7% versus 16.0%). There was no difference in the prevalence of positive EAT test between both groups. Students with positive EAT had more chance of body dissatisfaction (PRadj 1.31; 95%CI 1.03-1.66). Dietitians with positive EAT had 35% more chance of being dissatisfied with their body image (PRadj 1.35; 95%IC 1.01-1.80). Undergraduate Nutrition students and dietitians are likely to develop attitudes suggestive of an eating disorder and being dissatisfied with their body image. The susceptibility of developing an eating disorder might have a relation with their professional field(AU)

O objetivo deste estudo foi avaliar a prevalência de comportamentos de risco relacionados com distúrbios alimentares e satisfação com a imagem corporal entre mulheres nutricionistas e estudantes de Nutrição brasileiras. Adotou-se uma amostra representativa nacional, composta por 427 estudantes de Nutrição e 318 nutricionistas. Os dados foram coletados por meio de um questionário on-line. A satisfação com a imagem corporal foi avaliada pelo Body Shape Questionnaire, e as atitudes sugestivas de transtorno alimentar (denominadas EAT positivo) foram avaliadas por meio do Eating Attitudes Test. Razões de Prevalências Ajustadas foram calculadas usando Regressão de Poisson. Mais de 50,0% das mulheres estavam insatisfeitas com sua imagem corporal, mas a insatisfação severa foi mais prevalente entre as estudantes (26,7% versus 16,0%). Não houve diferença na prevalência de EAT positivo entre os grupos. Estudantes com EAT positivo tinham mais chances de ter insatisfação corporal (PRadj 1,31; 95%CI 1,03-1,66). Nutricionistas com EAT positivo tinham 35% mais chances de estarem insatisfeitas com sua imagem corporal (PRadj 1,35; 95%IC 1,01-1,80). Estudantes de Nutrição e nutricionistas tendem a desenvolver atitudes sugestivas de transtornos alimentares e estarem insatisfeitas com sua imagem corporal. Sua susceptibilidade a transtornos alimentares pode ter uma relação com sua área de atuação profissional(AU)

Use of a predictive model for food insecurity estimates in Brazil / Uso de un modelo estadístico predictivo para inseguridad alimentaria grave en Brasil

In 2004 the National Household Survey (Pesquisa Nacional por Amostras de Domicílios - PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p=0.561) and ROC curve (area=0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.

La Investigación Nacional por Muestreo de Domicilios de 2004 (PNAD), generó estimativas de la prevalencia de inseguridad alimentaria y nutricional en Brasil. Todavía las informaciones de PNAD no pueden ser desagregadas para las municipalidades. El objetivo de este estudio fue construir un modelo estadístico predictivo para inseguridad alimentaria grave en las municipalidades empleando la base de datos PNAD. Los criterios de exclusión fueran: hogares con datos incompletos (19.30%), informantes menores de 18 anos (0.07%), hogares colectivos (0.05%) y hogar con jefe indígena (0.19%). El modelaje fue realizado en 3 etapas, la primera fue la selección de las variables relacionadas con inseguridad alimentar grave mediante regresión logística única. Fueron escogidas variables presentes en PNAD y en el Censo Demográfico de 2000. Por último se realizó regresión logística múltiple, siendo retiradas las variables no significativas según el Odds Ratio ajustado. Fue usado el test de Wald para evaluar la significancia estadística de los coeficientes en la ecuación logística. El modelo final incluye las variables: renta domiciliar per cápita, años de escolaridad, raza y sexo del jefe de familia, localización urbana o rural del domicilio, disponibilidad de red de agua potable, presencia de niños, total de miembros en la familia y provincia de residencia. Se verificó la adecuación del modelo usando el test de Hosmer-Lemeshow (p=0,56) y la Curva de ROC (área=0,823). Los testes indican que el modelo tiene gran poder predictivo para estimar la inseguridad alimentaria grave en municipalidades brasileñas, sugiriendo que modelos predictivos similares puedan ser herramientas útiles en otros países Latinoamericanos.