Measurements of daily energy intake and total energy expenditure in people with dementia in care homes: The use of wearable technology

Authors: Murphy, J., Holmes, J. and Brooks,, C.

http://eprints.bournemouth.ac.uk/24359/

Journal: Journal of Nutrition, Health and Aging.

Publisher: Springer Verlag (Germany)

Authors: Murphy, J., Holmes, J. and Brooks, C.

http://eprints.bournemouth.ac.uk/24359/

Journal: Journal of Nutrition, Health and Aging

Publisher: Springer Verlag (Germany)

ISSN: 1279-7707

This data was imported from PubMed:

Authors: Murphy, J., Holmes, J. and Brooks, C.

http://eprints.bournemouth.ac.uk/24359/

Journal: J Nutr Health Aging

Volume: 21

Issue: 8

Pages: 927-932

eISSN: 1760-4788

DOI: 10.1007/s12603-017-0870-y

OBJECTIVE: To estimate daily total energy expenditure (TEE) using a physical activity monitor, combined with dietary assessment of energy intake to assess the relationship between daily energy expenditure and patterns of activity with energy intake in people with dementia living in care homes. DESIGN AND SETTING: A cross-sectional study in care homes in the UK. PARTICIPANTS: Twenty residents with confirmed dementia diagnosis were recruited from two care homes that specialised in dementia care. MEASUREMENTS: A physical activity monitor (SensewearTM Armband, Body Media, Pittsburgh, PA) was employed to objectively determine total energy expenditure, sleep duration and physical activity. The armband was placed around the left upper triceps for up to 7 days. Energy intake was determined by weighing all food and drink items over 4 days (3 weekdays and 1 weekend day) including measurements of food wastage. RESULTS: The mean age was 78.7 (SD ± 11.8) years, Body Mass Index (BMI) 23.0 (SD ± 4.2) kg/m2; 50% were women. Energy intake (mean 7.4; SD ± 2.6) MJ/d) was correlated with TEE (mean 7.6; SD ± 1.8 MJ/d; r=0.49, p<0.05). Duration of sleeping ranged from 0.4-12.5 (mean 6.1) hrs/d and time spent lying down was 1.3-16.0 (8.3) hrs/d. On average residents spent 17.9 (6.3-23.4) hrs/d undertaking sedentary activity. TEE was correlated with BMI (r=0.52, p<0.05) and body weight (r=0.81, p<0.001) but inversely related to sleep duration (r=-0.59, p<0.01) and time lying down (r=-0.62, p<0.01). Multiple linear regression analysis revealed that after taking BMI, sleep duration and time spent lying down into account, TEE was no longer correlated with energy intake. CONCLUSIONS: The results show the extent to which body mass, variable activity and sleep patterns may be contributing to TEE and together with reduced energy intake, energy requirements were not satisfied. Thus wearable technology has the potential to offer real-time monitoring to provide appropriate nutrition management that is more person-centred to prevent weight loss in dementia.

This data was imported from Scopus:

Authors: Murphy, J., Holmes, J. and Brooks, C.

http://eprints.bournemouth.ac.uk/24359/

Journal: Journal of Nutrition, Health and Aging

Volume: 21

Issue: 8

Pages: 927-932

eISSN: 1760-4788

ISSN: 1279-7707

DOI: 10.1007/s12603-017-0870-y

© 2017, The Author(s). Objective: To estimate daily total energy expenditure (TEE) using a physical activity monitor, combined with dietary assessment of energy intake to assess the relationship between daily energy expenditure and patterns of activity with energy intake in people with dementia living in care homes. Design and setting: A cross-sectional study in care homes in the UK. Participants: Twenty residents with confirmed dementia diagnosis were recruited from two care homes that specialised in dementia care. Measurements: A physical activity monitor (Sensewear™ Armband, Body Media, Pittsburgh, PA) was employed to objectively determine total energy expenditure, sleep duration and physical activity. The armband was placed around the left upper triceps for up to 7 days. Energy intake was determined by weighing all food and drink items over 4 days (3 weekdays and 1 weekend day) including measurements of food wastage. Results: The mean age was 78.7 (SD ± 11.8) years, Body Mass Index (BMI) 23.0 (SD ± 4.2) kg/m2; 50% were women. Energy intake (mean 7.4; SD ± 2.6) MJ/d) was correlated with TEE (mean 7.6; SD ± 1.8 MJ/d; r=0.49, p<0.05). Duration of sleeping ranged from 0.4-12.5 (mean 6.1) hrs/d and time spent lying down was 1.3-16.0 (8.3) hrs/d. On average residents spent 17.9 (6.3-23.4) hrs/d undertaking sedentary activity. TEE was correlated with BMI (r=0.52, p<0.05) and body weight (r=0.81, p<0.001) but inversely related to sleep duration (r=-0.59, p<0.01) and time lying down (r=-0.62, p<0.01). Multiple linear regression analysis revealed that after taking BMI, sleep duration and time spent lying down into account, TEE was no longer correlated with energy intake. Conclusions: The results show the extent to which body mass, variable activity and sleep patterns may be contributing to TEE and together with reduced energy intake, energy requirements were not satisfied. Thus wearable technology has the potential to offer realtime monitoring to provide appropriate nutrition management that is more person-centred to prevent weight loss in dementia.

This data was imported from Web of Science (Lite):

Authors: Murphy, J., Holmes, J. and Brooks, C.

http://eprints.bournemouth.ac.uk/24359/

Journal: JOURNAL OF NUTRITION HEALTH & AGING

Volume: 21

Issue: 8

Pages: 927-932

eISSN: 1760-4788

ISSN: 1279-7707

DOI: 10.1007/s12603-017-0870-y

The data on this page was last updated at 04:52 on April 20, 2019.