Revista de terapia de pérdida de peso y obesidad

Abstracto

Dietary Intake among Nurses Working Rotating Hospital Shifts by BMI Category

Mona Boaz, Vered Kaufman-Shriqui, Ludmila Fradkin and Olga Raz

Background: Shift work has been associated with increased body mass index (BMI), metabolic disruption and increased chronic disease risk. Typically, these reports compare individuals who work the day shift to those who work the night shift. Because shift assignment is not random, differences may reflect other, unmeasured characteristics that account for outcome differences. In this study, we compare individuals who work rotating shifts by BMI category (BMI<25 kg/m² vs. BMI ≥ 25 kg/m²).
Objective: To compare dietary intake on days the participant worked the night shift to days she worked the day shift; and to compare these difference by BMI category in a population of female nurses who work rotating shifts at a hospital.
Methods: This cross-sectional study recruited 132 female registered nurses who work rotating shifts in surgical or internal medicine departments. Dietary intake was ascertained using food diaries and analyzed on Tzameret Nutrition Analysis Software (Israel Ministry of Health). Demographic and anthropometric variables were also recorded.
Results: Compared to dietary intake on a day the nurse worked the day shift, intake of the following nutrients increased significantly on the day she worked the night shift: energy: protein; carbohydrates; total fat; saturated fat; and calcium. However, this difference was driven by nurses with BMI<25 kg/m²; nurses with BMI ≥ 25 kg/m² did not alter their dietary intake by shift.
Discussion and conclusion: A significant increase in calorie, macronutrient and calcium intake on days nurses worked the night shift compared to days they worked the day shift was demonstrated; but driven by differences among nurses with BMI<25 kg/m2. The mechanism for this is not clear but may represent voluntary inhibition among overweight nurses. Prospective follow-up can reveal whether this pattern predicts weight gain over time.