A photographic method to measure food item intake. Validation in geriatric institutions

Exploring Whether Weight-Related Cues Affect Food Intake in Older Adults with Dementia

Purpose

Past research has shown that exposure to the image of a slim person reduces food consumption among young adults. However, it remains unknown whether this paradigm could be adapted and applied to increase food intake among older adults with dementia by exposing them to the image of a higher-weight person to mitigate weight loss and malnutrition. The present study explored whether weight-related visual cues affect the amount of food consumed by older adults with dementia.

Participants and Methods

In the experiment, twenty-one elderly people with dementia living in a nursing home were visually exposed to one of four conditions (a cartoon image of a normal-weight chef, a higher-weight chef, a flower or no image) during real-life daily lunch situations over the course of four weeks, during which each condition was presented for one week.

Results

Results demonstrate that participants finished their meals more frequently when they were exposed to the image of the higher-weight chef than when they were not exposed to any images.

Conclusion

These results suggest that exposure to a cartoon chef character representing a stereotyped social group related to body weight activates the stereotype and increases stereotype-consistent behavior in older adults with dementia. The present findings will contribute to understanding the effect of visual information on eating behavior and to designing eating environments which facilitate sufficient nutrition intake among older adults with dementia.

Assessment of Food Intake Assisted by Photography in Older People Living in a Nursing Home: Maintenance over Time and Performance for Diagnosis of Malnutrition

Malnutrition is related to poor outcomes. Food intake semi-quantitative assessment is helpful for malnutrition screening. Aims: to assess maintenance over one month of one-day semi-quantitative assessment of food intake (primary aim) and its performance in diagnosing malnutrition (secondary aim) in older people living in a nursing home. Food portions consumed at lunch and dinner were measured during 20 days by the Simple Evaluation of Food Intake (SEFI)^® assisted by photography (SEFI^®-AP) in 70 residents. Nutritional status was assessed in each patient during the first week of food intake monitoring according to Global Leadership Initiative on Malnutrition criteria. Food intake was decreased, i.e., SEFI^®-AP < 7, in 39% (n = 27/73) of patients. According to the methods, 36 to 48% (n = 25 to 33/73) of patients had malnutrition, and 6 to 37% (n = 4 to 25/73) sarcopenia. According to a generalized linear model on ranks with repeated measures, the SEFI^®-AP medians of lunch (p = 0.11) and means of lunch and dinner (p = 0.15) did not vary over time. Day 3 SEFI^®-AP anticipated decreased food intake from days 4 to 20, with a sensitivity of 78% (95% confidence interval (CI), 62-94), a specificity of 30% [95%CI, 17-44] and positive and negative predictive values of 41% [95%CI, 28-55] and 68% [95%CI, 48-89]. The performance of SEFI^®-AP for diagnosis of malnutrition using calf circumference <31 cm as a phenotypic criterion was correct: area under the curve = 0.71 [95%CI, 0.59-0.83]. SEFI^®-AP sensitivity was better if ≤9.5 than <7, and inversely for specificity. The food intake of older people living in nursing homes is stable over one month. One-day SEFI^®-AP correctly anticipates food intake during the following month and predicts diagnosis of malnutrition. Any decrease in food intake should lead to suspect malnutrition.

A Cross-Sectional Reproducibility Study of a Standard Camera Sensor Using Artificial Intelligence to Assess Food Items: The FoodIntech Project

Having a system to measure food consumption is important to establish whether individual nutritional needs are being met in order to act quickly and to minimize the risk of undernutrition. Here, we tested a smartphone-based food consumption assessment system named FoodIntech. FoodIntech, which is based on AI using deep neural networks (DNN), automatically recognizes food items and dishes and calculates food leftovers using an image-based approach, i.e., it does not require human intervention to assess food consumption. This method uses one-input and one-output images by means of the detection and synchronization of a QRcode located on the meal tray. The DNN are then used to process the images and implement food detection, segmentation and recognition. Overall, 22,544 situations analyzed from 149 dishes were used to test the reliability of this method. The reliability of the AI results, based on the central intra-class correlation coefficient values, appeared to be excellent for 39% of the dishes (n = 58 dishes) and good for 19% (n = 28). The implementation of this method is an effective way to improve the recognition of dishes and it is possible, with a sufficient number of photos, to extend the capabilities of the tool to new dishes and foods.

Validation of an electronic food intake tool and its usability and efficacy in the healthcare setting

BACKGROUND

Accurate dietary intake data are critical to nutrition care planning. Commonly used food record charts (FRC) are paper-based, time consuming, require nutrient analysis estimations, and may provide limited accuracy. The present study aimed to validate Mobile Intake® (MI) (an electronic food intake tool incorporating the five-point visual scale and providing automatic nutrient analysis) for usability and efficacy in quantifying dietary intake in the healthcare setting.

METHODS

Two research stages within two tertiary hospitals included: (1) examining criterion validity and efficiency of dietary intake quantification using FRC and MI compared to the gold standard weighed food record (WFR) in a controlled environment and (2) comparing efficiency and effectiveness of FRC and MI in usual care conditions.

RESULTS

In Stage 1, dietary intake was calculated (n = 90) with a significant difference across all methods (FRC, MI and WFR) for energy (p = 0.04), but not between MI and WFR (p = 1.00). The time taken for MI (40 s) was significantly less than FRC (174 s) and WFR (371 s) (p < 001). In Stage 2, dietary intake was determined (n = 210) using FRC and MI. Sufficient data to complete dietary analysis were available for 35% of meals from FRC compared to 98% from MI. Calculated mean daily energy intake (4764 ± 1432 kJ vs. 6636 ± 2519 kJ, p = 0.002) and mean daily protein intake (62.9 ± 12.7 g vs. 78.5 ± 22.2 g, p = 0.007) were significantly lower with FRC compared to MI. Average time to complete MI was 14.4 seconds.

CONCLUSIONS

MI demonstrates efficacy as an accurate measure of dietary intake compared to WFR, as well as usability, providing faster, more accurate and comprehensive real-time intake data in practice than FRC.

Personalized nutrition and healthy aging

The human lifespan and quality of life depend on complex interactions among genetic, environmental, and lifestyle factors. Aging research has been remarkably advanced by the development of high-throughput "omics" technologies. Differences between chronological and biological ages, and identification of factors (eg, nutrition) that modulate the rate of aging can now be assessed at the individual level on the basis of telomere length, the epigenome, and the metabolome. Nevertheless, the understanding of the different responses of people to dietary factors, which is the focus of precision nutrition research, remains incomplete. The lack of reliable dietary assessment methods constitutes a significant challenge in nutrition research, especially in elderly populations. For practical and successful personalized diet advice, big data techniques are needed to analyze and integrate the relevant omics (ie, genomic, epigenomic, metabolomics) with an objective and longitudinal capture of individual nutritional and environmental information. Application of such techniques will provide the scientific evidence and knowledge needed to offer actionable, personalized health recommendations to transform the promise of personalized nutrition into reality.

Is Weight Loss More Severe in Older People with Dementia?

Weight loss, a hallmark feature of dementia, is associated with higher mortality in older people. However, there is a lack of consensus in the literature as to whether the weight loss commonly observed in older people with dementia results from reduced energy intake and/or increased energy expenditure. Understanding the cause of energy imbalance in older people with dementia would allow more targeted interventions to avoid detrimental health effects in this vulnerable group. In this paper, we review studies that have considered weight change, energy intake, and energy expenditure in older people with and without dementia. We critically assess the studies' methodology and outline the various factors which may decrease and increase energy intake and expenditure respectively in older people with and without dementia. Current available literature does not support the view that there is a lower energy intake and/or a higher energy expenditure in older people with dementia when compared to those without dementia. The need for more high-quality studies is also highlighted in order to shed more light towards this issue which continues to elude researchers and clinicians alike.

Measuring Food Waste and Consumption by Children Using Photography

A photography method was used to measure waste on food trays in school lunch in France, using the 5-point quarter-waste scale. While food waste has been studied extensively in US school lunches, the structure of the French lunch meal is quite different, with multiple courses, and vegetables (raw and cooked) in more than one course. Vegetables were the most wasted food category as usually seen in school lunch research, especially cooked vegetables, which were wasted at rates of 66%-83%. Raw vegetables were still wasted more than main dishes, starchy products, dairy, fruit, and desserts. Vegetables were also the most disliked food category, with the classes of vegetables falling in the same order as for waste. Waste and liking were highly correlated. Sensory characteristics of the food were cited as a main reason for liking/disliking. There is a strong connection between food liking and food consumption, and this connection should be the basis for future attempts to modify school lunch to improve consumption. The photographic method of measuring food waste at an individual level performed well.

Validation of a novel image-weighed technique for monitoring food intake and estimation of portion size in hospital settings: a pilot study

OBJECTIVE

Optimal nutrition for hospital patients is crucial and routine monitoring of patients' nutrient intake is imperative. However, personalised monitoring and customised intervention using traditional methods is challenging and labour-intensive, consequently it is often neglected in hospital settings. The present pilot study aimed to examine the reliability and validity of the Dietary Intake Monitoring System (DIMS) against the weighed food method (WFM).

DESIGN

The DIMS 2.0 is composed of an integrated digital camera, weighing scale, radio-frequency identification sensor and WIFI connection for real-time image and weight dietary data acquisition and analysis. The DIMS equipment was used to collect data for a paired set of meals both before and after meal consumption at lunchtime.

SETTING

Odense University Hospital, Denmark.

SUBJECTS

Photos and weights of seventeen patient meals were captured.

RESULTS

The results showed a significant correlation between DIMS and WFM for energy (r=0·99, P&lt;0·01) and protein intake (r=0·98, P&lt;0·01). Intraclass correlation coefficients (ICC) revealed a high degree of agreement among the four non-trained assessors for estimates of portion size of each food item before (0·88, P&lt;0·01) and after consumption (0·99, P&lt;0·01). The ICC for energy and protein intake were 0·99 (P&lt;0·01) and 0·99 (P&lt;0·01), respectively. Bland-Altman plots revealed no systematic bias.

CONCLUSIONS

Considering the huge benefits associated with routine monitoring, technological advances have made it possible to develop a novel, easy-to-use DIMS that, according to the findings, is a valid alternative for use in hospital settings.

Measuring lunchtime consumption in school cafeterias: a validation study of the use of digital photography

OBJECTIVE

The present study tested the validity of a digital image-capture measure of food consumption suitable for use in busy school cafeterias.

DESIGN

Lunches were photographed pre- and post-consumption, and food items were weighed pre- and post-consumption for comparison.

SETTING

A small research team recorded children's lunchtime consumption in one primary and one secondary school over seven working days.ParticipantsA primary-school sample of 121 children from North Wales and a secondary-school sample of 124 children from the West Midlands, UK, were utilised. Nineteen children were excluded because of incomplete data, leaving a final sample of 239 participants.

RESULTS

Results indicated that (i) consumption estimates based on images were accurate, yielding only small differences between the weight- and image-based judgements (median bias=0·15-1·64 g, equating to 0·45-3·42 % of consumed weight) and (ii) good levels of inter-rater agreement were achieved, ranging from moderate to near perfect (Cohen's κ=0·535-0·819). This confirmed that consumption estimates derived from digital images were accurate and could be used in lieu of objective weighed measures.

CONCLUSIONS

Our protocol minimised disruption to daily lunchtime routine, kept the attrition low, and enabled better agreement between measures and raters than was the case in the existing literature. Accurate measurements are a necessary tool for all those engaged in nutrition research, intervention evaluation, prevention and public health work. We conclude that our simple and practical method of assessment could be used with children across a range of settings, ages and lunch types.

Energy and Nutrient Content of Food Served and Consumed by Nursing Home Residents

OBJECTIVE

The aim of this study was to compare energy and protein content of the served food with the actual intake from the food consumed by nursing home residents. This study also aimed to compare food intake and dietary allowances.

DESIGN

This is a cross sectional study.

SETTING

This study was performed in nursing homes.

PARTICIPANTS

Residents of these 2 nursing homes were eligible for the study if they agreed to participate and if they meet the selection criteria (to be older than 65 years and have a regular texture diet).

MEASUREMENT

Nutrient content of the served food and real food consumption was calculated for all meals during a 5-day period by precise weighting method. Difference between consumed and served dietary content was evaluated by the Chi² test.

RESULTS

Seventy-four Belgian nursing home residents (75% of women, 85.8 ± 7.04 years on average) were included in this study. These subjects had a mean body mass index of 24.9 ± 4.83 kg/m². The mean energy content of the served food was 1783.3 ± 125.7 kcal per day. However, residents did not eat the whole of the meals and the actual energy content of the consumed food was significantly less (1552.4 ± 342.1 kcal per day; p<.001). The average protein content of the food served was equal to 0.96 ± 0.20 g/kg/day and the average consumption of protein by the residents was 0.88 ± 0.25 g/kg/day. The difference between protein served and consumed was also significant (p=.04). Moreover, people considered as well nourished, eating significantly more energy than the others (p=.04).

CONCLUSION

Meals served in nursing homes are not entirely consumed by their residents. As expected, the energy consumed are lower in subjects considered as malnourished or at risk of malnutrition.