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The Journal of Nutrition, Health & Aging logoLink to The Journal of Nutrition, Health & Aging
. 2016 Oct 10;21(6):614–621. doi: 10.1007/s12603-016-0814-y

Validation of the photography method for nutritional intake assessment in hospitalized elderly subjects

Fiammetta Monacelli 1, M Sartini 2, V Bassoli 3, D Becchetti 1, AL Biagini 2, A Nencioni 1, M Cea 4, R Borghi 1, F Torre 5, P Odetti 1
PMCID: PMC12879804  PMID: 28537324

Abstract

Objective

The aim of the present study was to validate the photographic indirect method as an accurate and specific tool to assess nutritional intake in a cohort of elderly hospitalized patients.

Design

this is a prospective observational study.

Setting

hospital (geriatric acute ward and transitional care of IRCCSS AUO San Martino Hospital, Genoa, Italy).

Participants

255 consecutive elderly hospitalized patients. Measurements: assessment of malnutrition by: Mini nutritional assessment (MNA) and abbreviated Comprehensive geriatric assessment (CIRS; Barthel index, SPMSE). The direct method (Gold standard): food dish weight (before lunch) and residual (after lunch) food dish weight and estimation of the percentage of eaten food and of residual food for each dish. The percentages of food intake and residual food were calculated according to the following formula: intake %= initial weight of the dishes- residual food weight)/ initial weight dish x100. The unit of variable was the percentage. The indirect photographic method with extrapolation of the lunch food intake by photographic method confronting initial meal and residual meal (25% quartile food dish estimation).

Results

The results showed a significant correlation between the direct method (weighing residual food) and the indirect photographic method(n=255; r=0.9735; p<0.001) as well as a significant positive correlation between the indirect photographic method and the food caloric estimation calculated by the direct method (n=255; r= 0.6489, p<0.001). Intraclass coefficient (ICC), showed a highly significant degree of agreement between the gold standard and the indirect photographic method (ICC: 0.69; p<0.0001). Additionally, the results showed a good inter rater agreement of the indirect photographic method (kappa-statistic measure of interrater agreement: (Z=13.04; p<0.001); agreement 70.29% e Kappa=0.5965) and a good specificity of the indirect method as it was independent on the single food item.

Conclusions

The study originally provided the validation of the indirect photographic method for the assessment of nutritional intake in a vast cohort of hospitalized elderly subjects. The present results moved a step forward in the appropriate assessment of nutrition intake in frail elderly, providing an easy to use tool that may be incorporate in routine clinical practice for early and targeted therapeutic interventions.

Key words: Hospitalized elderly, nutritional intake, photographic method assessment

Introduction

Malnutrition in the elderly represents a matter of clinical concern. The prevalent rate progressively rises according to age and to the clinical setting (1, 2). Accumulating evidence indicates a 40% of community dwelling undernourished elderly people, up to 55% of hospitalized elderly people affected by malnutrition (3, 4, 5).

Malnutrition is a recognized intrinsic factor for developing frailty, a multidimensional state characterized by loss of physiologic and cognitive reserve predicts unfavourable clinical outcomes (6). Both Fried criteria and the Rockwood cumulative index for assessing frailty, include malnutrition as a key relevant determinant in accelerating the degenerative trajectory towards elderly failure to thrive or pre death status (7, 8, 9, 10, 11).

Malnutrition critically infers the prognosis of elderly inpatients, worsening the outcome of the hospitalization (12). Malnourished hospitalized elderly people have longer periods of illness with higher infection rate, longer hospitalization (13, 14), increased comorbidity, exceeding disability and overall mortality (15, 16, 17, 18). Additionally, dramatic unintentional weight loss is an independent factor for 1-year mortality and /or life threatening morbidity, even when the severity of illness is under control (19, 20, 21, 22, 23, 24).

The risk for nutritional deterioration, in hospitalized patients, is even greater than the prevalence of reported malnourishment at admission (25, 26). Multimorbidity, clinical instability, presence of dementia, pre existing disability, oral problems (edentulia, or unrecognized dysphagia) represent the most relevant geriatric clinical conditions, which may contribute to malnutrition (12, 27, 28, 29).

On the other hand, the higher malnutrition risk in the hospital setting is mainly attributable to the poor recognition and monitoring of the nutritional intake; the patients' inadequate energetic expenditure and caloric estimation, inaccurate medical record documentation and the poor quality of feeding assistance are the most relevant under recognized clinical issues (20, 30, 31, 32).

While nutritional risk or slight malnutrition, if early identified, are amenable to effective interventions which may reverse the course, severe malnutrition is more likely to become irreversible and leads to death. Despite the epidemiological prevalence of malnutrition in geriatrics, there is no gold standard for malnutrition assessment (30). The mini nutritional assessment (MNA) showed better clinometric properties to estimate the nutritional status and to address appropriate and targeted interventions (33, 34). A plethora of nutritional screening tools has also been developed to improve the accuracy of assessment in geriatrics but further research is needed to accomplish the goal of routinely screening for patient's nutritional status in order to implement standardized clinical protocols for nutritional care in the hospital setting (35).

Literature offered few examples of alternative instruments to assess nutritional status in the elderly, in the long term care setting. In particular, the paper of Simmons (36) has compared three different monitoring methods for nutritional assessment (staff reported daily food record, direct meal observation and meal photograph before and after food consumption) in a nursing home setting. The results have reported, strikingly, that the staff daily food record was highly erratic in estimating the average food intake with higher underestimation rates, especially in older malnourished people at major risk of failure.

Moreover, a recent paper has validated the photographic method as a specific and accurate tool for the identification of malnutrition in elderly residents in Dutch nursing homes (37).

Using this data as a starting point and due to the lack of comparable data in the in hospital setting, the aim of the present study was to validate the photographic method for measuring the patients' nutritional intake and early identifying malnutrition in a cohort of hospitalized elderly people.

Materials and methods

The meal was provided to the hospital by a catering service (Ristorazione Serenissima: CF/IVA 01617950249; Rossi catering, Vicenza, Italy). The average meal was composed of 5 dishes: main course (pasta or soup); second course (red or white meat or fish); side dish (seasonal vegetables); bread or bread sticks (50 gr); fruit (sweet or seasonal fruit or yogurt); parmigiano cheese 5gr and olive oil 10 gr to add to the dishes. The mean caloric content of the meal was of 938 ± 35 Kcal die. The mean bromatological composition of the meal was the following: protein 18%; lipids 37%; carbohydrates 45% (Figure 1). The plates served to the patients were prepared 5–30 minutes before each meal. To maintain an adequate temperature, the prepared plates were placed in a steam cabinet at 75 °C before being served. The quantity of each food item (meat, sauce and side dish) served to each patient were chosen according to the national nutritional guidelines.

Figure 1.

Figure 1

An average in hospital served meal, composed of 5 dishes (first course; second course with side dish; bread or bread sticks; fruit and parmigiano dressing)

For each patient, the meal food intake was evaluated according to two distinct assessment procedures: - the direct method (Gold standard): food dish weight (before lunch) and residual (after lunch) food dish weight and estimation of the percentage of eaten food and of residual food for each dish. The percentages of food intake and residual food were calculated according to the following formula: intake %= initial weight of the dishes- residual food weight)/ initial weigh dish x100. The unit of variable was the percentage.

- the indirect method (Photographic method): extrapolation of the lunch food intake by photographic method comparing the initial meal and the residual meal. Furthermore, a visual estimation of food was performed estimating in quartiles the residuals of any single dish in order to obtain a quartile (25%) estimation of the meal food intake (Figure 2). The unit of variable was the division in fourths (four parts, one part corresponds to 25% of the photograph taken).

Figure 2.

Figure 2

Visual quartile (25%) estimation between the initial meal and the residual meal food intake, by indirect photographic method. The unit of variable was the division in fourths

The food weighing was performed by Laika Lc711 balance and the photographic analysis by digital Nikon S250 reflex camera (8-megapixel resolution) with a fixed distance from the plate and a consistent viewing angle.

In parallel, a nurse and a health care professional, respectively, were asked to perform a direct observation of the meal to collect data (visual quartiles:25% estimation of each dish) on the patients' lunch food intake. Moreover, the physician in charge of the ward (a geriatrician and/or an internal medicine physician) was interviewed through a semi structured interview in order to gather information on each enrolled patients' nutritional intake, as illustrated in Table 1.

Table 1.

Semi-structured physician’s interview

Physician’s interview
A. General assessment of patients’ nutritional intake?
 1. nothing
 2. ew food items
 3. sufficient food
 4. enough
 5. all the food provided
B. Estimate from 0 to ten, the average food item intake:
 1 and 2 = 0% 3 and 4 = 25% 5 and 6 = 50% 7 and 8 = 75% 9 and 10 = 100%
 First course ____ Second course ____ Side dish ____ Bread and sticks ____ Fruit ____
C. Is it the nutritional intake adequate to patients’ caloric expenditure and need?
 1. Less than 50%
 2. More than 50%
 3. 100%
D. Has the patient a parallel partial parenteral nutrition?
 1. Glucose
 2. Parenteral nutrition 610 Kcal (N4 1000ml)
 3. Parenteral nutrition between 3. 610 Kcal/die and 1000 Kcal/die
E. Do you directly assess patients’ nutritional intake?
 1. I read it from the nurse clinical record
 2. I ask to the nurse staff
 3. No, it is referred by the nurse staff
 4. No, it is referred by the caregiver
 5. Yes, at mealtimes
F. Is it patients’ arousal and vigilance adequate for oral nutrition and feeding?
 1. No
 2. Yes
G. Did you performed the three times water bolus test to assess dysphagia?
 1. No
 2. Yes
H. MNA administration
 1. No
2. Yes

Statistics

Data are expressed as mean ± SD. The analysis of sample normality was evaluated by D'Agostino & Pearson omnibus normality test and the relationship between variables was estimated by Spearman correlation test. Kappa-statistic measure of interrater agreement was used to assess the inter agreement between data collectors in estimating the same variable.

Intraclass coefficient (ICC) was used to estimate the degree of agreement between the indirect photographic method compared to the gold standard.

Analyses were carried out by using Graph Pad Prism 4.0 (Graph Pad Software, San Diego, CA) and STATA/SE14tm software (StataCorp LP, College Station, TX, USA). A P value <0.05 was considered statistically significant.

Results

Two hundred and fifty-five elderly patients (mean age 83±7.1 years, ranging from 65 to 99 years), male: 36.00% with a mean age of 83±8.0 (ranging from 65 to 97 years); female: 64.00% with a mean age of 84±6.0 years (ranging from 65 to 99 years), out of 875 patients admitted from January 2015 to June 2016 in two medical wards (geriatric acute ward and transitional care ward of the IRCCS University Hospital of S. Martino Genoa, Italy) were consecutively enrolled in the study after oral informed consent was obtained.

The inclusion criteria were: both gender; age ≥ 65 years.

The exclusion criteria were: age <65 years; clinical instability and/or end stage terminal patients; patients from intensive care and/or surgery; patients carrying PEG for different clinical conditions, including severe dysphagia; patients on total parenteral nutrition, and/or oral nutritional supplementation; patients submitted to special diets (hypoglucidic or hypoproteic or hypo caloric diets, fibers free diets or any diet which differs from the common daily diet provided by the hospital).

According to the exclusion criteria, 620 out of 875 admitted patients resulted non eligible for the study.

The patients' clinical characteristics were collected through the abbreviated comprehensive geriatric assessment, composed of MNA (38), SPMSQ (39), Barthel index (40), CIRS (41), as illustrated in Table 2.

Table 2.

Patients’ clinical characteristics, assessed by abbreviated comprehensive geriatric assessment

CIRS (comorbidity status): 4.25±1.99 score
Barthel index (functional status): 35.9±30.05 score
SPMSQ (presence of dementia): 3.70±2.77 score
MNA (malnutrition assessment): 15.39±4.95 score
Chewing status:
12.10% with edentulia;
57.88 % with partial edentulia;
32.36% with edentulia and appropriate denture;
9.66% with invalid denture
Presence of dysphagia and/or foniatric specialist advice:
78.71 % non dysphagia;
12.45% dysphagia for liquids;
6.02% dysphagia for both liquids and solid
Presence of formal or informal care giver: 25.60%

The results of the study, showed a mean patients' caloric food intake of 566.99±5.1 Kcal die (range 0- 1312; 559.36 IQR 358-778.52), assessed by the gold standard direct method (weighing of residual food intake).

Interestingly, with regards to the patients' nutritional intake, the results showed a significant correlation between the direct method (weighing residual food) and the indirect method (photographic analysis of the lunch meal) (n=255; r=0.9735; p<0.001) (Figure 3).

Figure 3.

Figure 3

Significant correlation between the indirect photographic method and patients' nutritional intake assessed with the direct method (n=255; r=0.9735; p<0.001). The unit of variable of the indirect photographic method was the division in fourths (four parts, one part corresponds to 25% of the photograph taken). The unit of variable for the direct method (gold standard) was the percentages of food intake and residual food (calculated according to the following formula: intake %= initial weight of the dishes-residual food weight)/ initial weigh dish x100)

Furthermore, concerning the food caloric intake, the results showed a significant positive correlation between the direct method (weighing the lunch food) and the indirect method (photographic analysis of the meal) (n=255; r= 0.6489, p<0.001) (Figure 4).

Figure 4.

Figure 4

Significant correlation between the indirect photographic method and patients' caloric Intake assessed with the direct method (n=255, r= 0.6489, p<0.001). The unit of variable of the indirect photographic method was the division in fourths (four parts, one part corresponds to 25% of the photograph taken). The unit of variable for the direct method (gold standard) was the percentages of food intake and residual food (calculated according to the following formula: intake %= initial weight of the dishes-residual food weight)/ initial weigh dish x100)

Additionally, Intraclass coefficient (ICC), used to assess the accuracy of the indirect photographic method, in estimating the patients' caloric and nutritional intake, compared to gold standard, showed a highly significant degree of agreement (ICC: 0.69; p<0.0001).

The present results showed a good correlation between the indirect method and MNA (n=255; r= 0.3257, p<0.001); in particular, MNA assessment showed a good correlation with the patients' caloric intake assessed by the indirect photographic method (n=255; r= 0.3649, p<0.001) as well as a less but still significant correlation with the patients' nutritional intake (n=255; r= 0.3182, p<0.001).

The measurement of the extent to which data collectors assign the same score to the same variable was tested by interrater agreement. The agreement of scores given by two non-trained raters, using the photographic method was evaluated for each food item and for total food intake (same items served within the same meal but evaluated by two distinct raters). The results showed a good inter reliability of the indirect photographic method (kappa-statistic measure of interrater agreement: (Z=13.04; p<0.001); agreement 70.29% and Kappa=0.5965). The inter rater agreement indicated a good repeatability of the indirect method in assessing nutritional and caloric patient's intake.

Moreover, the results showed a good correlation of the indirect method with single food items: the first course good correlation with the nutritional intake by the photographic method (r=0.9511; p<0.001) as did soup (r=0.9802, p<0.001). The second course also displayed a good correlation with the nutritional intake by the photographic method (r=0.9514; p<0.001); in particular, meat showed a good correlation with the nutritional intake by the photographic method (r=0.9641 p<0.001) and cheese or ham showed a good correlation with the nutritional intake by the photographic method (r=0.9511; p<0.001); (r=0.9412; p<0.001) (Figure 5). The indirect photographic method was not dependent on the type of served food, indicating a tool specificity for food intake measuring in hospitalized elderly patients.

Figure 5.

Figure 5

Indirect photographic method specificity independent on the type of food The unit of variable of the indirect photographic method was the division in fourths (four parts, one part corresponds to 25% of the photograph taken). The unit of variable for the direct method food intake (gold standard) was the percentages of food intake and residual food (calculated according to the following formula: intake %= initial weight of the dishes- residual food weight)/ initial weigh dish x100)

Interestingly, the results showed a significant positive correlation between the patients' functional status (Barthel index) and mean patients' caloric intake by the indirect photographic method (n=255; r= 0.3355, p<0.001) as well as a significant negative correlation between the patients' comorbidity (CIRS) and mean patients' caloric intake by indirect photographic method (n=255r=- 0.1788, p<0.05).

The comparison of different health care professionals in appropriately assessing the patients' nutritional intake showed the following significant differences.

A positive correlation between the nurse (direct visual lunch observation) and the photographic method was shown for all the meal dishes; first course: (n=255; r=0.2913 p<0.001); second course (n=255; r=0.3180 p<0.001); bread or bread sticks (n=255; r=0.2918 p<0.05); fruit and dessert (n=255; r=0.1916 p<0.05). A non significant correlation was shown when comparing the two method accuracy for the side dish (n=255; r=0.1192, p<0.05).

A positive correlation between the health care professional (direct visual lunch observation) and the photographic method for all the food intake (n=255; r=0.1266, p<0.05).

Interestingly, a non significant correlation was found between the physician's food caloric intake estimation (semistructured interview) and the photographic method for all the meal dishes (first course: n=255; r= -0.1487, p>0.05); second course (n=255; r= -0.0282, p>0.05); bread or bread sticks (n=255; r= -0.0168, p>0.05); fruit or dessert (n=255; r=-0.0189 p>0.05).

Discussion

In most health care setting and organizations, there is still great unawareness for identifying and treating malnourished patients, especially if elderly and frail. A bulk of evidence has reported, so far, the poor availability of effective screening methods and quality indicators (malnutrition protocols/ guidelines, nutritional education, training and weighing policy on a regular basis) for malnutrition, across different heath care setting (32, 42). Thus, targeting malnutrition in elderly people is still a problematic issue as well as the development of easy to use and effective screening tools for informing appropriate interventions.

Moreover, poor food intake, common in hospitals, may be also be due to several barriers that contribute to worsen the nutritional status during hospitalization; being interrupted at meals, not being given food when food was missed, loss of appetite, feeling too sick or tired, self reported low amount of served food or of scarce quality and taste were among the most experienced barriers in older patients (43).

Measuring food intake in elderly people is a real challenge: subjective recording may be inappropriate in the elderly as subjected to biases dependent on age and/or cognitive deficit (44). Direct health care professionals visual record of the patients' food intake represents an alternative, also subjected to high inaccuracy with large degree of food overestimation (36).

The weighed food method is the gold standard to measure real food consumption (45). However, weighing food is complex, time demanding, of specialist expertise with potential discrepancies between food distribution and food collection, and, at present, it just can't be incorporated into current clinical practice.

The indirect photographic method has shown to be a reliable technique if compared to the weighed food method in an experimental restaurant (46) and cafeteria (47, 48), enabling also the digital storage of raw data with delayed analysis of food items. To date, few studies have validated this method in geriatric institutions, uniquely in long term care setting (36).

Some reports (49) have demonstrated the reliability of this photographic method, using puréed food, compared to the direct visual estimation. Interestingly, the present study showed the validation of the frailty trajectories. The examined cohort of hospitalized elderly patients showed a frail clinical phenotype with high multimorbidity (CIRS 4.25±1.99 score), disability (Barthel index 35.9±30.05 score) and malnutrition (MNA 15.39±4.95 score).

The examined indirect photographic method in a vast cohort of hospitalized frail elderly patients with good accuracy, high reliability and specificity (regardless of the examined dish), in estimating the patients' food and caloric intake.

Whereas the nutritional intake is calculated from total food intake, the photographic method showed no significant overor under-estimation in measuring total food intake by adding together the single food item estimates.

The adequate inter rater reliability of the indirect photographic method also confirmed the observations of Parent (49), who demonstrated that non-trained assessors performed as well as trained assessors in estimating food intake.

Additionally, the indirect method can also distinguish single food item intake, investigating qualitative differences between dishes. This added qualitative analysis turns into a higher precision of the method in evaluating food consumption, that was currently beyond the scope of the research.

To our best knowledge, the data is original, as literature uniquely reported the effectiveness of the photographic method in a long-term care setting (36, 37) and adds knowledge to the pioneering research on the photographic application in the field of nutrition (49).

This clinical investigation was conducted in a hospital geriatric setting where malnutrition is a strong determinant of poorer prognosis and a potent driver of oldest old cohort of patients confirmed the prevalence of malnutrition and, specifically, the inverse correlation between the indirect method and CIRS and Barthel scale, respectively, showed that the indirect method is effective in measuring nutritional intake and identifying malnutrition in frail elderly people (50, 51, 52, 53).

Both the nurse and health care professional direct visual observation showed a fair but significant assessment of the patients' meal consumption, with a tendency to overestimate the overall food consumption.

Strikingly, the physician's estimation of the patients' meal consumption, even if applied by a geriatrician and/or an internal medicine with skills in geriatrics, was greatly inappropriate in assessing the nutritional and caloric intake. The physician deeply underestimated the patients' food intake and failed to estimate the patients' nutritional status by MNA administration. Furthermore, the physician's attitude was also poor in assessing the patients' dysphagia or swallowing impairments. All these clinical misconducts resulted in an inappropriate early setting of malnutrition targeted interventions. This elusive behaviour may also result in precipitating a catastrophic failure to thrive, being malnutrition, an independent determinant of mortality in frail individuals (54). This last original result strengthens the fact that malnutrition continues being considered a marginal clinical issue, also in geriatrics, and that there is still a great inadequacy in assessing malnutrition from a diagnostic and therapeutic framework, especially in the acute inpatient's setting.

Thus, in line with the results, the photographic food intake monitoring could be considered a valid method for the assessment of nutritional intake in elderly people and it might be included as a specific tool in the comprehensive geriatric assessment. Additionally, the photographic food intake method includes a series of clinical advantages; it is easy to manage, it is low cost and requires a low grade of staff training. The indirect method provides a quantitative and qualitative analysis of the patient's food intake, allowing permanent registration and monitoring. Further, this method can be easily incorporated into clinical practice permitting nurses to save time. Additionally, the indirect method can be part of a specialist section on malnutrition in clinical computerized records; thus, the interdisciplinary management of malnutrition in elderly hospitalized patients is expected to improve.

In conclusion, the photographic food intake monitoring method represents a step forward in the early assessment of the in hospital elderly patients' nutritional intake, to be routinely performed in the hospital setting at the time of patient admission and throughout his in hospital stay. This indirect method might help overcome the in hospital barriers for tailored nutritional interventions in frail elderly patients, by the sharing of common knowledge between different health care professionals.

Disclosure statement: Each author has no disclosure to declare.

Conflict of interest: Each author has no conflict of interest to declare.

Ethical Standards: The study on human subjects was conducted in accordance with the Helsinki Declaration.

References

  • 1.Wilson MM, Vaswani S, Liu D, Morley JE, Miller DK. Prevalence and causes of undernutrition in medical outpatients. The American journal of medicine. 1998;104(1):56–63. doi: 10.1016/s0002-9343(97)00279-9. 10.1016/S0002-9343(97)00279-9 PubMed PMID: 9528720. [DOI] [PubMed] [Google Scholar]
  • 2.de Groot CP, van Staveren W S i E o N t E aCA. Undernutrition in the European SENECA studies. Clinics in geriatric medicine. 2002;18(4):699–708. doi: 10.1016/s0749-0690(02)00043-5. 10.1016/S0749-0690(02)00043-5 PubMed PMID: 12608498. [DOI] [PubMed] [Google Scholar]
  • 3.Agarwal E, Miller M, Yaxley A, Isenring E. Malnutrition in the elderly: a narrative review. Maturitas. 2013;76(4):296–302. doi: 10.1016/j.maturitas.2013.07.013. 10.1016/j.maturitas.2013.07.013 PubMed PMID: 23958435. [DOI] [PubMed] [Google Scholar]
  • 4.Kaiser MJ, Bauer JM, Ramsch C, Uter W, Guigoz Y, Cederholm T, Thomas DR, Anthony PS, Charlton KE, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. Journal of the American Geriatrics Society. 2010;58(9):1734–1738. doi: 10.1111/j.1532-5415.2010.03016.x. 10.1111/j.1532-5415.2010.03016.x PubMed PMID: 20863332. [DOI] [PubMed] [Google Scholar]
  • 5.Arvanitakis M, Coppens P, Doughan L, van Gossum A. Nutrition in care homes and home care: recommendations -a summary based on the report approved by the Council of Europe. Clinical nutrition. 2009;28(5):492–496. doi: 10.1016/j.clnu.2009.07.011. 10.1016/j.clnu.2009.07.011 PubMed PMID: 19699562. [DOI] [PubMed] [Google Scholar]
  • 6.Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9868):752–762. doi: 10.1016/S0140-6736(12)62167-9. 10.1016/S0140-6736(12)62167-9 PubMed PMID: 23395245. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, et al. Frailty in older adults: evidence for a phenotype. The journals of gerontology Series A, Biological sciences and medical sciences. 2001;56(3):M146–M156. doi: 10.1093/gerona/56.3.m146. 10.1093/gerona/56.3.M146 PubMed PMID: 11253156. [DOI] [PubMed] [Google Scholar]
  • 8.Rockwood K, Mitnitski A, Song X, Steen B, Skoog I. Long-term risks of death and institutionalization of elderly people in relation to deficit accumulation at age 70. Journal of the American Geriatrics Society. 2006;54(6):975–979. doi: 10.1111/j.1532-5415.2006.00738.x. 10.1111/j.1532-5415.2006.00738.x PubMed PMID: 16776795. [DOI] [PubMed] [Google Scholar]
  • 9.Evans SJ, Sayers M, Mitnitski A, Rockwood K. The risk of adverse outcomes in hospitalized older patients in relation to a frailty index based on a comprehensive geriatric assessment. Age and ageing. 2014;43(1):127–132. doi: 10.1093/ageing/aft156. 10.1093/ageing/aft156 PubMed PMID: 24171946. [DOI] [PubMed] [Google Scholar]
  • 10.Naseer M, Forssell H, Fagerstrom C. Malnutrition, functional ability and mortality among older people aged 60 years: a 7-year longitudinal study. European journal of clinical nutrition. 2016;70(3):399–404. doi: 10.1038/ejcn.2015.196. 10.1038/ejcn.2015.196 PubMed PMID: 26603879. [DOI] [PubMed] [Google Scholar]
  • 11.de Boissieu P, Mahmoudi R, Hentzien M, Toquet S, Novella JL, Blanchard F, Jolly D, Drame M. Predictors of Long-Term Mortality in Oldest Old Patients (90+) Hospitalized to Medical Wards via the Emergency Department: The SAFES Cohort. The journal of nutrition, health & aging. 2015;19(6):702–707. doi: 10.1007/s12603-015-0515-y. 10.1007/s12603-015-0515-y [DOI] [PubMed] [Google Scholar]
  • 12.Keshavarzi S, Ahmadi SM, Lankarani KB. The impact of depression and malnutrition on health-related quality of life among the elderly Iranians. Global journal of health science. 2015;7(3):161–170. doi: 10.5539/gjhs.v7n3p161. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Kubrak C, Jensen L. Malnutrition in acute care patients: a narrative review. International journal of nursing studies. 2007;44(6):1036–1054. doi: 10.1016/j.ijnurstu.2006.07.015. 10.1016/j.ijnurstu.2006.07.015 PubMed PMID: 16996065. [DOI] [PubMed] [Google Scholar]
  • 14.Kagansky N, Berner Y, Koren-Morag N, Perelman L, Knobler H, Levy S. Poor nutritional habits are predictors of poor outcome in very old hospitalized patients. The American journal of clinical nutrition. 2005;82(4):784–791. doi: 10.1093/ajcn/82.4.784. PubMed PMID: 16210707. [DOI] [PubMed] [Google Scholar]
  • 15.Rasheed S, Woods RT. Malnutrition and associated clinical outcomes in hospitalized patients aged 60 and older: an observational study in rural Wales. Journal of nutrition in gerontology and geriatrics. 2013;32(1):71–80. doi: 10.1080/21551197.2012.753772. 10.1080/21551197.2012.753772 PubMed PMID: 23451847. [DOI] [PubMed] [Google Scholar]
  • 16.Naithani S, Whelan K, Thomas JE, Gulliford MC. Multiple morbidity is associated with increased problems of food access in hospital: a cross-sectional survey utilising the Cumulative Illness Rating Scale. Journal of human nutrition and dietetics: the official journal of the British Dietetic Association. 2010;23(6):575–582. doi: 10.1111/j.1365-277X.2010.01119.x. 10.1111/j.1365-277X.2010.01119.x [DOI] [PubMed] [Google Scholar]
  • 17.Poulsen I R, Hallberg I, Schroll M. Nutritional status and associated factors on geriatric admission. The journal of nutrition, health & aging. 2006;10(2):84–90. [PubMed] [Google Scholar]
  • 18.Giner M, Laviano A, Meguid MM, Gleason JR. In 1995 a correlation between malnutrition and poor outcome in critically ill patients still exists. Nutrition. 1996;12(1):23–29. doi: 10.1016/0899-9007(95)00015-1. 10.1016/0899-9007(95)00015-1 PubMed PMID: 8838832. [DOI] [PubMed] [Google Scholar]
  • 19.Gariballa S, Forster S. Malnutrition is an independent predictor of 1-year mortality following acute illness. The British journal of nutrition. 2007;98(2):332–336. doi: 10.1017/S0007114507701708. 10.1017/S0007114507701708 PubMed PMID: 17391564. [DOI] [PubMed] [Google Scholar]
  • 20.Volkert D, Saeglitz C, Gueldenzoph H, Sieber CC, Stehle P. Undiagnosed malnutrition and nutrition-related problems in geriatric patients. The journal of nutrition, health & aging. 2010;14(5):387–392. doi: 10.1007/s12603-010-0085-y. 10.1007/s12603-010-0085-y [DOI] [PubMed] [Google Scholar]
  • 21.Neyens J, Halfens R, Spreeuwenberg M, Meijers J, Luiking Y, Verlaan G, Schols J. Malnutrition is associated with an increased risk of falls and impaired activity in elderly patients in Dutch residential long-term care (LTC): a cross-sectional study. Archives of gerontology and geriatrics. 2013;56(1):265–269. doi: 10.1016/j.archger.2012.08.005. 10.1016/j.archger.2012.08.005 PubMed PMID: 22939947. [DOI] [PubMed] [Google Scholar]
  • 22.Chen LY, Liu LK, Hwang AC, Lin MH, Peng LN, Chen LK, Lan CF, Chang PL. Impact of Malnutrition on Physical, Cognitive Function and Mortality among Older Men Living in Veteran Homes by Minimum Data Set: A Prospective Cohort Study in Taiwan. The journal of nutrition, health & aging. 2016;20(1):41–47. doi: 10.1007/s12603-016-0674-5. 10.1007/s12603-016-0674-5 [DOI] [PubMed] [Google Scholar]
  • 23.Rentero Redondo L, Iniesta Navalon C, Gascon Canovas JJ, Tomas Jimenez C, Sanchez Alvarez C. [Malnutrition in the Elderly Patient to Hospital Admission, an Old Problem Unsolved] Nutricion hospitalaria. 2015;32(5):2169–2177. doi: 10.3305/nh.2015.32.5.9712. PubMed PMID: 26545674. [DOI] [PubMed] [Google Scholar]
  • 24.Bien B, Bien-Barkowska K, Wojskowicz A, Kasiukiewicz A, Wojszel ZB. Prognostic factors of long-term survival in geriatric inpatients. Should we change the recommendations for the oldest people? The journal of nutrition, health & aging. 2015;19(4):481–488. doi: 10.1007/s12603-014-0570-9. [DOI] [PubMed] [Google Scholar]
  • 25.Zhang J, Zhao X, Wang A, Zhou Y, Yang B, Wei N, Yu D, Lu J, Chen S, et al. Emerging malnutrition during hospitalisation independently predicts poor 3-month outcomes after acute stroke: data from a Chinese cohort. Asia Pacific journal of clinical nutrition. 2015;24(3):379–386. doi: 10.6133/apjcn.2015.24.3.13. PubMed PMID: 26420177. [DOI] [PubMed] [Google Scholar]
  • 26.Feldblum I, German L, Castel H, Harman-Boehm I, Bilenko N, Eisinger M, Fraser D, Shahar DR. Characteristics of undernourished older medical patients and the identification of predictors for undernutrition status. Nutrition journal. 2007;6:37. doi: 10.1186/1475-2891-6-37. 10.1186/1475-2891-6-37 PubMed PMID: 17980023; PMCID 2204029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Carrion S, Cabre M, Monteis R, Roca M, Palomera E, Serra-Prat M, Rofes L, Clave P. Oropharyngeal dysphagia is a prevalent risk factor for malnutrition in a cohort of older patients admitted with an acute disease to a general hospital. Clinical nutrition. 2015;34(3):436–442. doi: 10.1016/j.clnu.2014.04.014. 10.1016/j.clnu.2014.04.014 PubMed PMID: 24882372. [DOI] [PubMed] [Google Scholar]
  • 28.Felton DA. Complete Edentulism and Comorbid Diseases: An Update. Journal of prosthodontics: official journal of the American College of Prosthodontists. 2016;25(1):5–20. doi: 10.1111/jopr.12350. 10.1111/jopr.12350 [DOI] [PubMed] [Google Scholar]
  • 29.Yildiz D B, Pekel N, Kilic AK, Tolgay EN, Tufan F. Malnutrition is associated with dementia severity and geriatric syndromes in patients with Alzheimer disease. Turkish journal of medical sciences. 2015;45(5):1078–1081. doi: 10.3906/sag-1406-76. 10.3906/sag-1406-76 PubMed PMID: 26738350. [DOI] [PubMed] [Google Scholar]
  • 30.Omidvari AH, Vali Y, Murray SM, Wonderling D, Rashidian A. Nutritional screening for improving professional practice for patient outcomes in hospital and primary care settings. The Cochrane database of systematic reviews. 2013;6:CD005539. doi: 10.1002/14651858.CD005539.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Eide HD, Halvorsen K, Almendingen K. Barriers to nutritional care for the undernourished hospitalised elderly: perspectives of nurses. Journal of clinical nursing. 2015;24(5-6):696–706. doi: 10.1111/jocn.12562. 10.1111/jocn.12562 PubMed PMID: 24646060. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Meijers JM, Halfens RJ, van Bokhorst-de van der Schueren MA, Dassen T, Schols JM. Malnutrition in Dutch health care: prevalence, prevention, treatment, and quality indicators. Nutrition. 2009;25(5):512–519. doi: 10.1016/j.nut.2008.11.004. 10.1016/j.nut.2008.11.004 PubMed PMID: 19135863. [DOI] [PubMed] [Google Scholar]
  • 33.Vellas B, Guigoz Y, Garry PJ, Nourhashemi F, Bennahum D, Lauque S, Albarede JL. The Mini Nutritional Assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition. 1999;15(2):116–122. doi: 10.1016/s0899-9007(98)00171-3. 10.1016/S0899-9007(98)00171-3 PubMed PMID: 9990575. [DOI] [PubMed] [Google Scholar]
  • 34.Guigoz Y, Lauque S, Vellas BJ. Identifying the elderly at risk for malnutrition. The Mini Nutritional Assessment. Clinics in geriatric medicine. 2002;18(4):737–757. doi: 10.1016/s0749-0690(02)00059-9. 10.1016/S0749-0690(02)00059-9 PubMed PMID: 12608501. [DOI] [PubMed] [Google Scholar]
  • 35.Baek MH, Heo YR. Evaluation of the efficacy of nutritional screening tools to predict malnutrition in the elderly at a geriatric care hospital. Nutrition research and practice. 2015;9(6):637–643. doi: 10.4162/nrp.2015.9.6.637. 10.4162/nrp.2015.9.6.637 PubMed PMID: 26634053; PMCID 4667205. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Simmons SF, Reuben D. Nutritional intake monitoring for nursing home residents: a comparison of staff documentation, direct observation, and photography methods. Journal of the American Geriatrics Society. 2000;48(2):209–213. doi: 10.1111/j.1532-5415.2000.tb03914.x. 10.1111/j.1532-5415.2000.tb03914.x PubMed PMID: 10682952. [DOI] [PubMed] [Google Scholar]
  • 37.Pouyet V, Cuvelier G, Benattar L, Giboreau A. A photographic method to measure food item intake. Validation in geriatric institutions. Appetite. 2015;84:11–19. doi: 10.1016/j.appet.2014.09.012. PubMed PMID: 25261733. [DOI] [PubMed] [Google Scholar]
  • 38.Guigoz Y, Vellas B. The mini nutritional assessment (MNA) for grading the nutritional state of elderly patients: presentation of the MNA, history and validation. Nestle Nutr Workshop Ser Clin Perform Programme. 1999;1:3–11. doi: 10.1159/000062967. 10.1159/000062967 PubMed PMID: 11490593. [DOI] [PubMed] [Google Scholar]
  • 39.Pfeiffer E. A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc. 1975;23:433–441. doi: 10.1111/j.1532-5415.1975.tb00927.x. 10.1111/j.1532-5415.1975.tb00927.x PubMed PMID: 1159263. [DOI] [PubMed] [Google Scholar]
  • 40.Mahoney FI, Barthel DW. Functional evaluation: The Barthel index. Md State Med J. 1965;14:61–65. PubMed PMID: 14258950. [PubMed] [Google Scholar]
  • 41.Salvi MD, Miller A, Grilli R, Giorgi AL, Towers V Morichi. A manual of guidelines to score the modified cumulative illness rating scale and its validation in acute hospitalized elderly patients. Am Geriatr Soc. 2008;56(10):1926–1931. doi: 10.1111/j.1532-5415.2008.01935.x. 10.1111/j.1532-5415.2008.01935.x [DOI] [PubMed] [Google Scholar]
  • 42.Morley JE. Assessment of malnutrition in older persons: a focus on the Mini Nutritional Assessment. The journal of nutrition, health & aging. 2011;15(2):87–90. doi: 10.1007/s12603-011-0018-4. 10.1007/s12603-011-0018-4 [DOI] [PubMed] [Google Scholar]
  • 43.Keller H, Allard J, Vesnaver E, Laporte M, Gramlich L, Bernier P, Davidson B, Duerksen D, Jeejeebhoy K, Payette H. Barriers to food intake in acute care hospitals: a report of the Canadian Malnutrition Task Force. Journal of human nutrition and dietetics: the official journal of the British Dietetic Association. 2015;28(6):546–557. doi: 10.1111/jhn.12314. 10.1111/jhn.12314 [DOI] [PubMed] [Google Scholar]
  • 44.van Staveren WA, de Groot LC, Blauw YH, van der Wielen RP. Assessing diets of elderly people: problems and approaches. The American journal of clinical nutrition. 1994;59:221S–223S. doi: 10.1093/ajcn/59.1.221S. PubMed PMID: 8279429. [DOI] [PubMed] [Google Scholar]
  • 45.Nelson M, Atkinson M, Darbyshire S. Food photography II: use of food photographs for estimating portion size and the nutrient content of meals. The British journal of nutrition. 1996;76(1):31–49. doi: 10.1079/bjn19960007. 10.1079/BJN19960007 PubMed PMID: 8774215. [DOI] [PubMed] [Google Scholar]
  • 46.Hinton EC, Brunstrom JM, Fay SH, Wilkinson LL, Ferriday D, Rogers PJ, de Wijk R. Using photography in ‘The Restaurant of the Future'. A useful way to assess portion selection and plate cleaning? Appetite. 2013;63:31–35. doi: 10.1016/j.appet.2012.12.008. PubMed PMID: 23262297. [DOI] [PubMed] [Google Scholar]
  • 47.Swanson M. Digital photography as a tool to measure school cafeteria consumption. The Journal of school health. 2008;78(8):432–437. doi: 10.1111/j.1746-1561.2008.00326.x. 10.1111/j.1746-1561.2008.00326.x PubMed PMID: 18651930. [DOI] [PubMed] [Google Scholar]
  • 48.Williamson DA, Allen HR, Martin PD, Alfonso AJ, Gerald B, Hunt A. Comparison of digital photography to weighed and visual estimation of portion sizes. Journal of the American Dietetic Association. 2003;103(9):1139–1145. doi: 10.1016/s0002-8223(03)00974-x. 10.1016/S0002-8223(03)00974-X PubMed PMID: 12963941. [DOI] [PubMed] [Google Scholar]
  • 49.Parent M, Niezgoda H, Keller HH, Chambers LW, Daly S. Comparison of visual estimation methods for regular and modified textures: real-time vs digital imaging. Journal of the Academy of Nutrition and Dietetics. 2012;112(10):1636–1641. doi: 10.1016/j.jand.2012.06.367. 10.1016/j.jand.2012.06.367 PubMed PMID: 23017574. [DOI] [PubMed] [Google Scholar]
  • 50.Kaiser M, Bandinelli S, Lunenfeld B. Frailty and the role of nutrition in older people. A review of the current literature. Acta bio-medica: Atenei Parmensis. 2010;81:37–45. [PubMed] [Google Scholar]
  • 51.Avila-Funes JA, Medina-Campos RH, Tamez-Rivera O, Navarrete-Reyesb AP, Amieva H, Aguilar-Navarro S. Frailty is associated with disability and recent hospitalization in community-dwelling elderly: the coyocan cohort. J Frailty Aging. 2014;3(4):206–210. doi: 10.14283/jfa.2014.25. PubMed PMID: 27048858. [DOI] [PubMed] [Google Scholar]
  • 52.Pohlhausen S, Uhlig K, Kiesswetter E, Diekmann R, Heseker H, Volkert D, Stehle P, Lesser S. Energy and Protein Intake, Anthropometrics, and Disease Burden in Elderly Home-care Receivers-A Cross-sectional Study in Germany (ErnSIPP Study) J Nutr Health Aging. 2016;20(3):361–368. doi: 10.1007/s12603-015-0586-9. 10.1007/s12603-015-0586-9 PubMed PMID: 26892587. [DOI] [PubMed] [Google Scholar]
  • 53.Zuniga K, McAuley E. Considerations in selection of diet assessment methods for examining the effect of nutrition on cognition. J Nutr Health Aging. 2015;19(3):333–340. doi: 10.1007/s12603-014-0566-5. 10.1007/s12603-014-0566-5 PubMed PMID: 25732219. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Bonnefoy M, Berrut G, Lesourd B, Ferry M, Gilbert T, Guerin O, Hanon O, Jeandel C, Paillaud E, et al. Frailty and nutrition: searching for evidence. The journal of nutrition, health & aging. 2015;19(3):250–257. doi: 10.1007/s12603-014-0568-3. 10.1007/s12603-014-0568-3 [DOI] [PubMed] [Google Scholar]

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