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

Measurements of daily energy intake and total energy expenditure in people with dementia in care homes: the use of wearable technology
Measurements of daily energy intake and total energy expenditure in people with dementia in care homes: the use of wearable technology
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 realtime monitoring to provide appropriate nutrition management that is more person-centred to prevent weight loss in dementia.
dementia, energy expenditure, energy intake, technology, diet, care home, activit
1279-7707
Murphy, Jane L.
6b35ebb2-8f6c-4fe6-9d38-032859ec4e86
Holmes, Joanne
7b4addf3-9e72-4587-9af7-b1e0feb9f53e
Brooks, Cindy
8a2fcddf-44b1-4f74-a14f-d877dddf58bd
Murphy, Jane L.
6b35ebb2-8f6c-4fe6-9d38-032859ec4e86
Holmes, Joanne
7b4addf3-9e72-4587-9af7-b1e0feb9f53e
Brooks, Cindy
8a2fcddf-44b1-4f74-a14f-d877dddf58bd

Murphy, Jane L., Holmes, Joanne and Brooks, Cindy (2017) Measurements of daily energy intake and total energy expenditure in people with dementia in care homes: the use of wearable technology. The Journal of Nutrition, Health & Aging. (doi:10.1007/s12603-017-0870-y).

Record type: Article

Abstract

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 realtime monitoring to provide appropriate nutrition management that is more person-centred to prevent weight loss in dementia.

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Accepted/In Press date: 21 June 2016
e-pub ahead of print date: 17 January 2017
Keywords: dementia, energy expenditure, energy intake, technology, diet, care home, activit
Organisations: University of Southampton, Centre for Innovation & Leadership

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Local EPrints ID: 407272
URI: http://eprints.soton.ac.uk/id/eprint/407272
ISSN: 1279-7707
PURE UUID: d258fa23-2dad-4e70-8e98-5fa4e90b9db4

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Date deposited: 01 Apr 2017 01:10
Last modified: 06 Oct 2020 17:26

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Author: Jane L. Murphy
Author: Joanne Holmes
Author: Cindy Brooks

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