The need to accurately measure energy intake and expenditure in patients with systemic sclerosis.

Background: Malnutrition is common in systemic sclerosis and patients are frequently underweight. However, the balance between assessed dietary energy intake versus expenditure has been neglected to date. This study aimed to assess energy (dietary) intakes and expenditures and to compare discrepancies in systemic sclerosis. Methods: Thirty-six outpatients with systemic sclerosis completed the study. Demographics and clinical data were recorded. Functional questionnaires were completed. Predicted energy requirements were calculated. Over a consecutive 3-day period, patients completed an estimated food diary and wore a specialist energy expenditure monitor (SenseWear® Armband). Assessments of intake and expenditure were compared for individual patients, and the impact according to patient demographics, clinical manifestations and disease severity evaluated. Results: Energy intake did not correlate with predicted (s = 0.117; p = 0.511) or measured (s = -0.039; p = 0.825) expenditures. Predicted and measured energy expenditures correlated, but actual values differed for individuals (intraclass correlation = 0.62; 95% limits of agreement = -459 to 751 kcal). Respiratory involvement was negatively correlated with number of steps (s = -0.350; p = 0.04) and time spent lying (s = 0.333; p = 0.05). There was a significant correlation between body mass index and predicted versus measured energy discrepancy (s = 0.41; p = 0.02), and this discrepancy was greater with higher body mass indices. Conclusion: There was no correlation between intake and either predicted or measured energy expenditure. Predicted and measured energy expenditures were strongly correlated yet differed for the individual patient. In patients with systemic sclerosis, where energy expenditure must be accurately assessed, it should be directly measured.

Influence of chemotherapy on total energy expenditure in patients with gastrointestinal cancer: A pilot study.

OBJECTIVE: Resting energy expenditure (REE) and physical activity (PA) undergo variations during chemotherapy. The aim of this study was to use a metabolic Holter (SenseWear Armband [SWA]) to assess REE, total energy expenditure (TEE), and PA changes in patients undergoing chemotherapy to ensure the appropriate calorie intake. To our knowledge, this is the first study to do so. METHODS: Eight patients with gastrointestinal tumors and a Karnofsky performance status of >50 underwent evaluation of the body mass index; REE, TEE, metabolic equivalent, and sleep efficiency were evaluated by SWA. Fat-free mass and fat mass were measured by bioelectrical impedance analysis, muscle strength by handgrip, and dietary intake by food diary. All evaluations were performed before chemotherapy (T0), at mid-treatment (T1), and at the end of treatment (T2). A calorie-equivalent diet to the TEE was recommended to all patients. RESULTS: At T0, a body weight loss of 15.1 ± 7.2% in the previous 6 mo was observed in all patients. Two patients did not complete treatment. During chemotherapy, thanks to the nutritional counseling, the remaining patients increased their calorie intake (P = 0.006) and no significant change was observed in other parameters. The REE calculation measured by SWA was correlated to the Harris-Benedict formula (P ≤ 0.002). CONCLUSION: The present data excluded significant variations of REE and PA in the course of chemotherapy in patients who do not experience weight loss and who have a Karnofsky performance status of >50. Nutritional counseling based on SWA measurements is useful to support nutritional status in patients undergoing chemotherapy.

Evaluation of a smartphone food diary application using objectively measured energy expenditure.

BACKGROUND: Dietary assessment methods are limited in their ability to adequately measure food and beverage consumption. Smartphone applications may provide a novel method of dietary assessment to capture real-time food intake and the contextual factors surrounding eating occasions. The aim of this study is to evaluate the capability of a Smartphone meal diary app ("FoodNow") to measure food intake using a validated objective method for assessing energy expenditure among young adults. METHODS: Participants (18-30 years) used FoodNow over four non-consecutive days recording all eating occasions through a combination of written text, and/or optional images and voice recordings. A series of contextual questions were also completed. Participants wore the validated SenseWear Armband (BodyMedia Inc, USA) during the same period to measure free-living energy expenditure. Intra-class correlation coefficients (ICC) estimated the reliability of FoodNow to measure estimated energy intake compared to measured energy expenditure. RESULTS: Ninety participants (71 female, 19 male; mean age = 24.9 ± 4.1 years) were recruited to use the FoodNow app to record their eating occasions. Thirteen were excluded as they did not meet minimum requirements for number of reporting days (n = 3) or SenseWear Armband wear time (5 days of 11 h), while 21 participants were excluded after being identified as mis-reporters (Huang method). Among the remaining sample (n = 56), reliability between estimated energy intake and measured energy expenditure was high (ICC, 95% CI: 0.75, 0.61-0.84). CONCLUSIONS: FoodNow is a suitable method for capturing estimated energy intake data from young adults. Despite wide levels of agreement at the individual level (-3709 kJ to 2056 kJ), at the group level, FoodNow appears to have potential as a dietary assessment tool. This new dietary assessment method will offer an alternative and novel method of dietary assessment which is capable of collecting both estimated energy intake and contextual factors surrounding eating occasions. Information collected may be used to inform future public health messages or research interventions.

Multi-instrument assessment of physical activity in female office workers.

OBJECTIVES: The aim of this study was to examine the multi-instrument assessment of physical activity in female office workers. MATERIAL AND METHODS: Fifty healthy women (age (mean ± standard deviation): 34.8±5.9 years, body height: 158±0.4 cm, body weight: 61.8±7.5 kg, body mass index: 24.6±2.7 kg/m2) workers from the same workplace volunteered to participate in the study. Physical activity was measured with the 7-day Physical Activity Assessment Questionnaire (7-d PAAQ), an objective multi-sensor armband tool, and also a waist-mounted pedometer, which were both worn for 7 days. RESULTS: A significant correlation between step numbers measured by armband and pedometer was observed (r = 0.735), but the step numbers measured by these 2 methods were significantly different (10 941±2236 steps/ day and 9170±2377 steps/day, respectively; p < 0.001). There was a weak correlation between the value of 7-d PAAQ total energy expenditure and the value of armband total energy expenditure (r = 0.394, p = 0.005). However, total energy expenditure values measured by armband and 7-d PAAQ were not significantly different (2081±370 kcal/ day and 2084±197 kcal/day, respectively; p = 0.96). In addition, physical activity levels (average daily metabolic equivalents (MET)) measured by armband and 7-d PAAQ were not significantly different (1.45±0.12 MET/day and 1.47±0.24 MET/day, respectively; p = 0.44). CONCLUSIONS: The results of this study showed that the correlation between pedometer and armband measurements was higher than that between armband measurements and 7-d PAAQ selfreports. Our results suggest that none of the assessment methods examined here, 7-d PAAQ, pedometer, or armband, is sufficient when used as a single tool for physical activity level determination. Therefore, multi-instrument assessment methods are preferable. Int J Occup Med Environ Health 2016;29(6):937-945.

School Day Energy Expenditure in Elementary School Children.

BACKGROUND: The purpose was to characterize energy expenditure (EE) during academic subjects and activities during an elementary school day. METHODS: Children in 2nd to 4th grades (N = 33) wore the SenseWear Armband (SWA) for 5 school days to measure EE. Teachers' logs were compared with SWA data to extract information about EE throughout the day. Energy expenditure was also compared among grades. RESULTS: After controlling for body mass, grade level was not a significant predictor of average daily caloric expenditure, F (2, 17.58) = .29, P = .75, ω(2) = .05. When comparing activities throughout the day, relative rates of EE differed significantly, Wilks' F (7, 23) = 52.2, P = .00, ηp(2) = .94, with PE and recess having higher EE. When academic subjects were compared (math, science, language arts), relative rate of EE was also significantly different, Wilks' F (2, 30) = 4.31, P = .02, ηp(2) = .22. For the full sample, relative rate EE was higher in science than in language arts. CONCLUSIONS: The school day provides opportunity for EE for children. These data support the potential benefit of active instruction in language arts as a method to increase school day EE.

A Mobile Phone App for Dietary Intake Assessment in Adolescents: An Evaluation Study.

BACKGROUND: There is a great need for dietary assessment methods that suit the adolescent lifestyle and give valid intake data. OBJECTIVE: To develop a mobile phone app and evaluate its ability to assess energy intake (EI) and total energy expenditure (TEE) compared with objectively measured TEE. Furthermore, to investigate the impact of factors on reporting accuracy of EI, and to compare dietary intake with a Web-based method. METHODS: Participants 14 to 16 years of age were recruited from year nine in schools in Gothenburg, Sweden. In total, 81 adolescents used the mobile phone app over 1 to 6 days. TEE was measured with the SenseWear Armband (SWA) during the same or proximate days. Individual factors were assessed with a questionnaire. A total of 15 participants also recorded dietary intake using a Web-based method. RESULTS: The mobile phone app underestimated EI by 29% on a group level (P<.001) compared to TEE measured with the SWA, and there was no significant correlation between EI and TEE. Accuracy of EI relative to TEE increased with a weekend day in the record (P=.007) and lower BMI z-score (P=.001). TEE assessed with the mobile phone app was 1.19 times the value of TEE measured by the SWA on a group level (P<.001), and the correlation between the methods was .75 (P<.001). Analysis of physical activity levels (PAL) from the mobile phone app stratified by gender showed that accuracy of the mobile phone app was higher among boys. EI, nutrients, and food groups assessed with the mobile phone app and Web-based method among 15 participants were not significantly different and several were significantly correlated, but strong conclusions cannot be drawn due to the low number of participants. CONCLUSIONS: By using a mobile phone dietary assessment app, on average 71% of adolescents' EI was captured. The accuracy of reported dietary intake was higher with lower BMI z-score and if a weekend day was included in the record. The daily question in the mobile phone app about physical activity could accurately rank the participants' TEE.

Validity and reliability of Nike + Fuelband for estimating physical activity energy expenditure.

BACKGROUND: The Nike + Fuelband is a commercially available, wrist-worn accelerometer used to track physical activity energy expenditure (PAEE) during exercise. However, validation studies assessing the accuracy of this device for estimating PAEE are lacking. Therefore, this study examined the validity and reliability of the Nike + Fuelband for estimating PAEE during physical activity in young adults. Secondarily, we compared PAEE estimation of the Nike + Fuelband with the previously validated SenseWear Armband (SWA). METHODS: Twenty-four participants (n = 24) completed two, 60-min semi-structured routines consisting of sedentary/light-intensity, moderate-intensity, and vigorous-intensity physical activity. Participants wore a Nike + Fuelband and SWA, while oxygen uptake was measured continuously with an Oxycon Mobile (OM) metabolic measurement system (criterion). RESULTS: The Nike + Fuelband (ICC = 0.77) and SWA (ICC = 0.61) both demonstrated moderate to good validity. PAEE estimates provided by the Nike + Fuelband (246 ± 67 kcal) and SWA (238 ± 57 kcal) were not statistically different than OM (243 ± 67 kcal). Both devices also displayed similar mean absolute percent errors for PAEE estimates (Nike + Fuelband = 16 ± 13 %; SWA = 18 ± 18 %). Test-retest reliability for PAEE indicated good stability for Nike + Fuelband (ICC = 0.96) and SWA (ICC = 0.90). CONCLUSION: The Nike + Fuelband provided valid and reliable estimates of PAEE, that are similar to the previously validated SWA, during a routine that included approximately equal amounts of sedentary/light-, moderate- and vigorous-intensity physical activity.

Physical activity and energy expenditure during depressive episodes of major depression.

BACKGROUND: Recent data suggest a substantial association between physical activity and depressive symptoms, but there is a lack of research evaluating the physical activity levels in patients suffering from unipolar depression across different stages of disease in an objective way. The aim of the present pilot study was to objectively examine physical activity levels of this patient group compared to healthy controls. METHODS: Physical activity performance of 19 patients with major depressive episode and 19 healthy controls was assessed at three different time points using a multisensory armband device (SenseWear® Pro3 Armband) and was reported as total energy expenditure (TEE), active energy expenditure (EE), metabolic equivalents (METs), physical activity (PA) and time of lying down (LD), in each case over 24h. RESULTS: Over all measurements, depressive patients presented a significantly lower mean TEE and EE over 24h. Moreover, the patient group showed significantly shorter duration of PA and lower average MET over 24h. When depressive symptoms abated, physical activity parameters significantly increased in the patient group. Correlation analyses demonstrated a significant relation between depressive status/anhedonia and parameters of physical activity, especially in healthy subjects. LIMITATIONS: Results represented valid data for inpatients only. CONCLUSION: Acute unipolar depression was associated with a significantly lower level of physical activity and showed a significant increase in parallel to clinical improvement. Electronic monitoring of physical activity may be an additional tool for evaluating and controlling therapeutic effects.

Validation of SenseWear Armband and ActiHeart monitors for assessments of daily energy expenditure in free-living women with chronic obstructive pulmonary disease.

To provide individually adapted nutritional support to patients with chronic obstructive pulmonary disease (COPD), objective and reliable methods must be used to assess patient energy requirements. The aim of this study was to validate the use of SenseWear Armband (SWA) and ActiHeart (AH) monitors for assessing total daily energy expenditure (TEE) and activity energy expenditure (AEE) and compare these techniques with the doubly labeled water (DLW) method in free-living women with COPD. TEE and AEE were measured in 19 women with COPD for 14 days using SWAs with software version 5.1 (TEESWA5, AEESWA5) or 6.1 (TEESWA6, AEESWA6) and AH monitors (TEEAH, AEEAH), using DLW (TEEDLW) as the criterion method. The three methods were compared using intraclass correlation coefficient (ICC) and Bland-Altman analyses. The mean TEE did not significantly differ between the DLW and SWA5.1 methods (-21 ± 726 kJ/day; P = 0.9), but it did significantly differ between the DLW and SWA6.1 (709 ± 667 kJ/day) (P < 0.001) and the DLW and AH methods (709 ± 786 kJ/day) (P < 0.001). Strong agreement was observed between the DLW and TEESWA5 methods (ICC = 0.76; 95% CI 0.47-0.90), with moderate agreements between the DLW and TEESWA6 (ICC = 0.66; 95% CI 0.02-0.88) and the DLW and TEEAH methods (ICC = 0.61; 95% CI 0.05-0.85). Compared with the DLW method, the SWA5.1 underestimated AEE by 12% (P = 0.03), whereas the SWA6.1 and AH monitors underestimated AEE by 35% (P < 0.001). Bland-Altman plots revealed no systematic bias for TEE or AEE. The SWA5.1 can reliably assess TEE in women with COPD. However, the SWA6.1 and AH monitors underestimate TEE. The SWA and AH monitors underestimate AEE.