Physical Activity, Energy Expenditure, Nutritional Habits, Quality of Sleep and Stress Levels in Shift-Working Health Care Personnel.

BACKGROUND: Among health care personnel working regular hours or rotating shifts can affect parameters of general health and nutrition. We have investigated physical activity, sleep quality, metabolic activity and stress levels in health care workers from both groups. METHODS: We prospectively recruited 46 volunteer participants from the workforce of a University Medical Department of which 23 worked in rotating shifts (all nursing) and 21 non-shift regular hours (10 nursing, 13 clerical staff). All were investigated over 7 days by multisensory accelerometer (SenseWear Bodymedia® armband) and kept a detailed food diary. Physical activity and resting energy expenditure (REE) were measured in metabolic equivalents of task (METs). Quality of sleep was assessed as Pittsburgh Sleeping Quality Index and stress load using the Trier Inventory for Chronic Stress questionnaire (TICS). RESULTS: No significant differences were found for overall physical activity, steps per minute, time of exceeding the 3 METs level or sleep quality. A significant difference for physical activity during working hours was found between shift-workers vs. non-shift-workers (p<0.01) and for shift-working nurses (median = 2.1 METs SE = 0.1) vs. non-shift-working clerical personnel (median = 1.5 METs SE = 0.07, p<0.05). Non-shift-working nurses had a significantly lower REE than the other groups (p<0.05). The proportion of fat in the diet was significantly higher (p<0.05) in the office worker group (median = 42% SE = 1.2) whereas shift-working nurses consumed significantly more carbohydrates (median = 46% SE = 1.4) than clerical staff (median = 41% SE = 1.7). Stress assessment by TICS confirmed a significantly higher level of social overload in the shift working group (p<0.05). CONCLUSION: In this prospective cohort study shift-working had no influence on overall physical activity. Lower physical activity during working hours appears to be compensated for during off-hours. Differences in nutritional habits and stress load warrant larger scale trials to determine the effect on implicit health-associated conditions.

Evaluation of a non-invasive multisensor accelerometer for calculating energy expenditure in ventilated intensive care patients compared to indirect calorimetry and predictive equations.

Continuous measurement of resting energy expenditure (REE) in critically ill patients remains challenging but is required to prevent malnutrition. SenseWear Pro 3 Armband (SWA) is a research grade accelerometer for assessment of REE with the advantage of easy handling. In a prospective study we compared SWA with indirect calorimetry (IC) and predictive equations in critically ill, ventilated patients. REE was measured by SWA, IC and calculated by predictive formulas. Potential confounding factors that influence REE were also recorded. Results of SenseWear Armband and indirect calorimetry were compared using the Bland-Altman method. 34 ICU patients were investigated. SWA underestimated resting energy expenditure compared to IC with a mean bias of ΔREE = -253.6 ± 333.2 kcal, equivalent to -11.7 % (p = 0.025). This underestimation was seen in both, medical (-14.9 %) and surgical (-12.9 %) patients and the bias was greater in patients with fever (-19.0 %), tachycardia (-18.7 %) or tachypnea (-26.2 %). Differences were also noted when SWA was compared to predictive formulas. At present, SWA cannot be regarded as an alternative to indirect calorimetry. Individual measurements are often inaccurate and should be used with caution until improved algorithms, based on the results of this study, have been implemented.