Energy Expenditure in Institutionalized Older Adults

Martien, Sofie; Seghers, Jan; Boen, Filip; Delecluse, Christophe

doi:10.1249/mss.0000000000000529

Cited by 8 publications

(5 citation statements)

References 35 publications

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“…Four studies could not be synthesised by meta-analysis as mean difference between activity monitors and criterion measurements were not provided12 31–33; thus, 60 studies were included in the meta-analysis (figure 1). 10 13 34–88 A total of 1946 participants were included, with a mean age of 35 years (range 20–86 years). The mean body mass index (BMI) was 24.9 kg/m 2 (range 21.8–31.6 kg/m 2 ).…”

Section: Resultsmentioning

confidence: 99%

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies

et al. 2018

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Section: Resultsmentioning

confidence: 99%

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies

et al. 2018

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“…They reported that the absolute error rate was 28% compared with DLW measures, whereas we found a lower absolute error rate at about 20%. Martien, Seghers, Boen, and Delecluse (2015) also found SWMA underestimated EE in older adults during resting and three activity tasks using a portable gas analyzer as the criterion measure, with an overall absolute percent error of 14.1%. The current study is the first one to report the validity of SWMA in estimating EE in adolescents.…”

Section: Discussionmentioning

confidence: 78%

Energy expenditure of type-specific sedentary behaviors estimated using sensewear mini armband

Jin

Zhuang

Zhu

et al. 2018

Kinesiology (Zagreb, Online)

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SenseWear Mini Armband, an accelerometer with multiple physiological sensors, could be a practical means to estimate energy expenditure (EE) of children and adolescents, but its validity reported for these age groups has not been consistent within the literature. EE of twenty-six healthy Chinese 12-year-old adolescents was measured simultaneously using both SenseWear Mini Armband (SWMA) and metabolic chamber (MC) during a 16-hour stay in a MC. SWMA systematically underestimated the adolescents’ EE during sedentary behaviors, resting metabolic rate (RMR), basal metabolic rate (BMR), and total EE, with the absolute error rate ranging from 14.85% to 28.65%. The SWMA significantly underestimated EE compared with MC in Chinese adolescents. However, the amount of error can be reduced by applying correction equation proposed in this study.

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“…In some recent studies, TEE was evaluated by accelerometers in elderly residents (18,19). However, the validity of using an accelerometer for estimating TEE has not yet been described, and it is unclear whether TEE can be accurately measured by that method in inactive populations.…”

Section: Discussionmentioning

confidence: 99%

“…Percentage of fat mass (FM) was calculated as (body weight2FFM) divided by body weight. The CO2 production rate (rCO2) was calculated according to the following equation: rCO25 0.45543TBW3(1.0073 18 O elimination rate2 1.0413 2 H elimination rate) TEEDLW was calculated according to the following equation:…”

Section: Subjectsmentioning

confidence: 99%

Validity of One-Day Physical Activity Recall for Estimating Total Energy Expenditure in Elderly Residents at Long-Term Care Facilities: CLinical EValuation of Energy Requirements Study (CLEVER Study)

Nishida

Nakae

Yamada

et al. 2019

J Nutr Sci Vitaminol

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Malnutrition is a severe problem among elderly residents living in long-term care facilities. A simple and accurate estimation for total daily energy expenditure (TEE) is required in order to provide them with an adequate amount of food. The purpose of this study was to validate a physical activity assessment tool for estimating TEE among elderly residents. The data of 58 subjects aged 69-99 y were analyzed in this study. The one-day physical activity recall was filled out by facility staff for a typical day. TEE was measured by the doubly labeled water (DLW) method (TEEDLW), and predicted by one-day physical activity recall using the basal metabolic rate (pTEEBMR) and body weight (pTEEBW). The TEEDLW, pTEEBMR and pTEEBW were 1,1296196 kcal/d, 1,1866251 kcal/d and 1,3266236 kcal/d, respectively. In a regression model, body weight, movement means and sex explained 39.0% of the variance in the difference between pTEEBMR and TEEDLW (p,0.05). Percentage of fat mass, body weight, and Barthel Index except mobility explained 47.3% of the variance in the difference between pTEEBW and TEEDLW (p,0.05). The current results suggested that pTEEBW is not recommended to estimate TEE because the error depends on body size, and pTEEBMR was significantly correlated with TEEDLW but also included systematic errors in elderly residents. In order to improve the accuracy of the present assessment to estimate TEE, it is necessary to establish a new equation of basal metabolic rate for elderly residents and consider sex and movement means to estimate TEE.

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Energy Expenditure in Institutionalized Older Adults

Cited by 8 publications

References 35 publications

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies

Energy expenditure of type-specific sedentary behaviors estimated using sensewear mini armband

Validity of One-Day Physical Activity Recall for Estimating Total Energy Expenditure in Elderly Residents at Long-Term Care Facilities: CLinical EValuation of Energy Requirements Study (CLEVER Study)

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