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1.
J Nutr Health Aging ; 22(2): 230-236, 2018.
Article in English | MEDLINE | ID: mdl-29380850

ABSTRACT

OBJECTIVES: To investigate the ability of older adults, younger adults and nutritionists to assess portion size using traditional methods versus a computer-based method. This was to inform the development of a novel dietary assessment method for older adults "The NANA system". DESIGN: Older and younger adults assessed the portion size of self-served portions of foods from a buffet style set up using traditional and computerised portion size assessment aids. Nutritionists assessed the portion size of foods from digital photographs using computerised portion size aids. These estimates were compared to known weights of foods using univariate analyses of covariance (ANCOVA). SETTING: The University of Sheffield, United Kingdom. SUBJECTS: Forty older adults (aged 65 years and over), 41 younger adults (aged between 18 and 40 years) and 25 nutritionists. RESULTS: There was little difference in the abilities of older and younger adults to assess portion size using both assessment aids with the exception of small pieces morphology. Even though the methods were not directly comparable among the test groups, there was less variability in portion size estimates made by the nutritionists. CONCLUSION: Older adults and younger adults are similar in their ability to assess food portion size and demonstrate wide variability of estimation compared to the ability of nutritionists to estimate portion size from photographs. The results suggest that the use of photographs of meals consumed for portion size assessment by a nutritionist may improve the accuracy of dietary assessment. Improved portion size assessment aids are required for all age groups.


Subject(s)
Diet Surveys/methods , Diet/methods , Nutritionists/standards , Portion Size/standards , Adolescent , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Young Adult
2.
J Affect Disord ; 213: 187-190, 2017 Apr 15.
Article in English | MEDLINE | ID: mdl-28259086

ABSTRACT

BACKGROUND: Depression is currently underdiagnosed among older adults. As part of the Novel Assessment of Nutrition and Aging (NANA) validation study, 40 older adults self-reported their mood using a touchscreen computer over three, one-week periods. Here, we demonstrate the potential of these data to predict future depression status. METHODS: We analysed data from the NANA validation study using a machine learning approach. We applied the least absolute shrinkage and selection operator with a logistic model to averages of six measures of mood, with depression status according to the Geriatric Depression Scale 10 weeks later as the outcome variable. We tested multiple values of the selection parameter in order to produce a model with low deviance. We used a cross-validation framework to avoid overspecialisation, and receiver operating characteristic (ROC) curve analysis to determine the quality of the fitted model. RESULTS: The model we report contained coefficients for two variables: sadness and tiredness, as well as a constant. The cross-validated area under the ROC curve for this model was 0.88 (CI: 0.69-0.97). LIMITATIONS: While results are based on a small sample, the methodology for the selection of variables appears suitable for the problem at hand, suggesting promise for a wider study and ultimate deployment with older adults at increased risk of depression. CONCLUSIONS: We have identified self-reported scales of sadness and tiredness as sensitive measures which have the potential to predict future depression status in older adults, partially addressing the problem of underdiagnosis.


Subject(s)
Depressive Disorder/diagnosis , Geriatric Assessment/methods , Psychiatric Status Rating Scales , Psychometrics/instrumentation , Aged , Aged, 80 and over , Female , Humans , Lethargy/diagnosis , Logistic Models , Male , Predictive Value of Tests , Psychiatric Status Rating Scales/standards , ROC Curve , Retrospective Studies
3.
Exp Gerontol ; 60: 100-7, 2014 Dec.
Article in English | MEDLINE | ID: mdl-25456843

ABSTRACT

Prospective measurement of nutrition, cognition, and physical activity in later life would facilitate early detection of detrimental change and early intervention but is hard to achieve in community settings. Technology can simplify the task and facilitate daily data collection. The Novel Assessment of Nutrition and Ageing (NANA) toolkit was developed to provide a holistic picture of an individual's function including diet, cognition and activity levels. This study aimed to validate the NANA toolkit for data collection in the community. Forty participants aged 65 years and over trialled the NANA toolkit in their homes for three 7-day periods at four-week intervals. Data collected using the NANA toolkit were compared with standard measures of diet (four-day food diary), cognitive ability (processing speed) and physical activity (self-report). Bland-Altman analysis of dietary intake (energy, carbohydrates, protein fat) found a good relationship with the food diary and cognitive processing speed and physical activity (hours) were significantly correlated with their standard counterparts. The NANA toolkit enables daily reporting of data that would otherwise be collected sporadically while reducing demands on participants; older adults can complete the daily reporting at home without a researcher being present; and it enables prospective investigation of several domains at once.


Subject(s)
Aging , Nutrition Assessment , Software , Aged , Aged, 80 and over , Aging/physiology , Aging/psychology , Cognition , Data Collection/methods , Data Collection/statistics & numerical data , Diet Records , Female , Humans , Male , Motor Activity , Prospective Studies , Self Report , United Kingdom , User-Computer Interface
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