ArticleThe journal of nutrition, health & aging2017
Measurements of Daily Energy Intake and Total Energy Expenditure in People with Dementia in Care Homes: The Use of Wearable Technology.
Article in The journal of nutrition, health & aging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 5 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 5 syntheses or guidelines pooled it, 32 citations in OpenAlex.
- Aesthetic Experience in the Acceptance of Wearable Technology for People With Dementia: Critical Interpretive Synthesis.JMIR aging · 2025Pooled it
- Wearable GPS and Accelerometer Technologies for Monitoring Mobility and Physical Activity in Neurodegenerative Disorders: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Review of Technology-Supported Multimodal Solutions for People with Dementia.Sensors (Basel, Switzerland) · 2021Pooled it
- Evaluation of Wearable Technology in Dementia: A Systematic Review and Meta-Analysis.Frontiers in medicine · 2020Pooled it
- Use of statins and the risk of dementia and mild cognitive impairment: A systematic review and meta-analysis.Scientific reports · 2018Pooled it
- The Effect of Food Odor Exposure on Appetite and Nutritional Intake of Older Adults with Dementia.The journal of nutrition, health & aging · 2022Trial
- Navigating next-gen nutrition care using artificial intelligence-assisted dietary assessment tools-a scoping review of potential applications.Frontiers in nutrition · 2025Review
- Corrigendum: Evaluation of Wearable Technology in Dementia: A Systematic Review and Meta-Analysis.Frontiers in medicine · 2021Article
- Mapping Movement: Applying Motion Measurement Technologies to the Psychiatric Care of Older Adults.Current psychiatry reports · 2018Review
- Editorial: Defining Undernutrition (Malnutrition) in Older Persons.The journal of nutrition, health & aging · 2018Article
- Home Behavior Monitoring Module in OpenEMR: Use of home sensors as Patient-Generated Data (PGD) for elderly care.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo 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
settingA cross-sectional study in care homes in the UK.
participantsTwenty 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.
resultsThe 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.
conclusionsThe 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.
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