Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Validity of the portuguese version of the mini nutritional assessment in brazilian elderly

  • Renata Santos Pereira Machado1Email author,
  • Maria Auxiliadora Santa Cruz Coelho1 and
  • Renato Peixoto Veras2
BMC Geriatrics201515:132

https://doi.org/10.1186/s12877-015-0129-6

Received: 18 November 2014

Accepted: 12 October 2015

Published: 22 October 2015

Abstract

Background

Malnutrition is common and affects negatively the health of the older adult. The Mini Nutritional Assessment (MNA), a nutritional assessment tool allows to identify elders malnourished and at risk of malnutrition. The aim of this study is to validate the Portuguese version of the MNA.

Methods

Cross-sectional study with 344 Brazilian elderly. The full version of the MNA was performed, also calf circumference (CC), mid arm circumference (MAC) and body fat (BF). Psychometric evaluation was carried out and correlation, diagnostic accuracy and ROC curves were generated.

Results

Construct validity was supported, all four questionnaire dimensions were evidenced in the Principal Component Analysis and also significant Spearman correlation (P < 0.001) were demonstrated. Criterion validity was also evidenced with relevant sensitivity (MAC = 82.8; CI95% = 64.2-94.2) and specificity (CC = 80.0; CI95% = 74.0-85.1). In the ROC curve AUC was excellent (MAC = 0.832; CI95% =0.785-0.873).

Conclusions

The full MNA demonstrated significant results and sufficient exploratory psychometric properties that supported its validity. It seems to be valid tool to access nutritional status of Brazilian elderly.

Keywords

Elderly Malnutrition Mini nutritional assessment Validation Accuracy

Background

Malnutrition is common and affects negatively the health of the older adult. It can lead to various health concerns, including a weak immune system, poor wound healing, muscle weakness and also disinterest in eating or lack of appetite. Malnutrition is often caused by a combination of physical, social and psychological issues. It is more common and increasing in the older population; currently 16 % of those >65 years and 2 % of those >85 years are classed as malnourished. Almost two-thirds of general and acute hospital beds are used by people aged >65 years [13]. As the research statistics indicate, not only is malnutrition prevalent in the elderly, it is also frequently misdiagnosed or unrecognized. Many health care professionals are not properly screening or assessing malnutrition in the elderly [2, 4].

The Mini Nutritional Assessment (MNA), a nutritional assessment tool widely used around the world, allows to identify elders malnourished and at risk of malnutrition. It has been translated in over 20 languages with more than 600 PUBMED references [5, 6]. The MNA consists of 18 items including anthropometric, global, dietetic and subjective assessment dimensions. Currently the MNA is used in clinical practice and clinical research [710] to assess community-dwelling older adults [11, 12], hospitalized patients [13] or nursing home residents [8, 14, 15].

Studies about malnutrition in the elderly using the MNA in Brazil are insufficient and no validation study has been developed there yet. It very is important to do nutritional assessment in the elderly, making use of valid tools.

The purpose of this article is to validate the Portuguese version of the Mini Nutritional Assessment in Brazilian elderly.

Method

Participants

This was a cross-sectional study, conducted with institutionalized elderly residents in public long term geriatric units in Rio de Janeiro, Brazil as part of a larger observational study of nutritional assessment.

Elderly aged 60 year or older were eligible, as recommended by the World Health Organization (WHO) for developing countries such as Brazil [16]. It was also an inclusion criteria have being able to communicate and the strength to carry out an interview and give written informed consent. The exclusion criteria were to suffer from cognitive impairment and not to accept to take part in the survey. The survey consisted of 344 elderly that were residents in one of the 12 municipal shelters in Rio de Janeiro, aged 60–117 years old, 41 % of men and 59 % women and the data were collected in 2001. All included participants provided informed consent.

Nutritional assessment

The full-form MNA was administered by trained nutritionists, despite the score in the first part of the test. The score range from 0 to 30, and it was calculated as the sum of the values from the 18 items. An MNA score of 24 or higher identifies the patient with a good nutritional status, scores between 17 and 23.5 indicates patients at risk for malnutrition and score less than 17 identifies patients with protein-caloric malnutrition [17].

The anthropometric assessment that were carried out included body weight and height [18], arm span [19], calf circumference (CC) [20], mid arm circumference (MAC) [21] and bioimpedance electric (BIO).

Weight was measured to the nearest 0.1 kg, with the subject in light clothes and no shoes, using a digital scale Kratos with a maximum capacity of 150 kg. Height was measured to the nearest 0.1 cm using a vertical stadiometer Leicester, with the subject’s bare feet close together, back and heels against the wall, standing erect and looking straight ahead. To measure MAC the mid-point between the tip of the acromion and the olecranon process was marked while the subject held the forearm in horizontal position. The measurement was performed on the subject’s arm hanging freely along the trunk with a flexible inextensible tape. CC was measured at the maximal circumference between the ankle and the knee with a flexible tape measure, manipulated to maintain close contact with the skin without compression of underlying tissues. These measures were performed on the non-dominant arm and leg.

In order to classify under nutrition, to BMI it was used the cut-off proposed by the World Health Organization for the elderly [16]. The BMI [weight (kg)/height (m2)] was classified by using the WHO cut-off points, considering women and <23 cm for men, were used to predict under-nutrition [22] and to CC < 31 [16]. To percentage of body fat values the cut-off points were < 24 % for women and < 13 % for man [23].

MAC and CC are parameters used for measurement of muscle mass and subcutaneous adipose tissue [24] and a low MAC among the elderly has been shown to increase risk of mortality and indicates loss of peripheral muscle mass [25, 26]. As for CC, a value of less than 31 cm will indicate muscle loss especially in the lower limb [16]. Body composition was assessed by bioelectric bioimpedance. Fat-free mass, total body fat and per cent body fat were determined.

Statistical analyses

Descriptive results are presented as means and standard deviations, frequencies and 95 % confidence intervals (CI 95 %). The analysis of data involved descriptive statistics such as mean, standard deviation (SD) and simple frequency. It was used analysis of variance (ANOVA) to compare means between the continuous variables.

To validity it was assessed construct validity and criterion validity, according to Streiner & Norman (2008) [27]. Spearman’s rank correlation coefficients between total MNA score obtained and the criteria of BMI, MAC, CC and BF were calculated. Also measures of accuracy of the tests, sensitivity, specificity, and areas under ROC curves (AUC) were calculated (CI95%). Classification of AUC (range 0–1): acceptable 0.70-0.80, excellent 0.80-0.90, outstanding >0.90 [28].

Exploratory factor analysis with principal components extraction was performed, using PROMAX Rotation with Kaiser Normalization applied to the component matrix.

Significance statistics was considered with p < 0.05. Statistical analyses were performed with IBM SPSS Statistics 19 (SPSS Inc. Chicago IL, USA). Graphics for ROC analyses were created with MedCalc version 12.7.

Ethics

The local ethics committee of the Federal University of Rio de Janeiro – UFRJ, approved the study protocol. All participants gave written informed consent.

Results

A total of 344 subjects were evaluated. The full MNA classified 36.1 % of participants in the total data set well nourished, 55.6 % as at risk, and 8.3 % as malnourished. Total MNA scores averaged 22.3 (SD 3.6) and ranged from a minimum of 10.0 to a maximum of 29.0. The age range of the subjects was between 60 and 117 years old with a mean age of 75.4 (SD 9.4) years old.

The socio-demographic profile indicated similarity in the marital status and income of men and women. In relation to age, women have higher prevalence in the older age group and also higher prevalence in the range of education with fewer years of study (Table 1). Nutritional assessment according to MNA is shown in Table 2, with statistical significance for weight, BF, MAC, CC and BMI.
Table 1

Socio-demographic and anthropometrics characteristics of subjects according to sex

  

Men

Women

Total

p-value

  

N (%)

N (%)

N (%)

 

Age

 

<70

53 (37.9)

53 (26.0)

106 (30.8)

0.013*

 

> = 70

87 (62.1)

151 (79.0)

238 (69.2)

 

Marital status

 

Married

14 (10.0)

11 (5.4)

25 (7.3)

0.081

 

Not married

126 (90.0)

193 (94.6)

319 (92.7)

 

Years of Education

 

<=4

70 (50.0)

138 (67.6)

208 (60.5)

0.001*

 

>4

70 (50.0)

66 (32.4)

136 (39.5)

 

Income

 

<2 minimum wage

98 (90.7)

136 (88.9)

234 (89.7)

0.384

 

2+ minimum wage

10 (9.3)

17 (11.1)

27 (10.3)

 

MNA

 

Malnutrition

8 (6.6)

17 (9.4)

25 (8.3)

0.242

 

At risk of malnutrition

72 (59.0)

96 (53.3)

168 (55.6)

0.246

 

Well nourished

42 (34.4)

67 (37.2)

109 (36.1)

 

BMI

 

Underweigth

54 (38.6)

54 (26.5)

108 (31.4)

0.012*

 

Normal

86 (61.4)

150 (73.5)

236 (98.6)

 

MAC

 

Underweigth

8 (5.7)

24 (11.8)

32 (9.3)

0.041*

 

Normal

132 (94.3)

180 (88.2)

312 (90.7)

 

CC

 

Underweigth

22 (17.9)

56 (29.8)

78 (25.1)

0.012*

 

Normal

101 (82.1)

132 (70.2)

233 (74.9)

 

PBF

 

Underweigth

29 (24.4)

50 (27.3)

79 (26.2)

0.333

 

Normal

90 (75.6)

133 (72.7)

233 (73.8)

 

MNA mini nutritional assessment, BMI body mass index, MAC mid-arm circumference, CC calf circumference, PBF percentage of body fat

* p < 0.05, significance level difference between sex (ANOVA)

Table 2

Characteristics of nutritional assessment according to the Portuguese version of the MNA

 

MNA

 

Malnutrition

At risk of malnutrition

Well nourished

p-value

 

N

Mean (DP)

N

Mean (DP)

N

Mean (DP)

 

Age (y)

25

76,68 (10,49)

168

76,1 (9,15)

109

73,61 (9,52)

0,072

Height (cm)

24

151,70 (8,77)

157

155,40 (10,71)

108

155,62 (10,36)

0,233

Weight (Kg)

24

50,70 (12,37)

157

55,82 (11,80)

108

65,99 (14,79)

0,000*

Body fat (Kg)

22

22,27 (10,96)

149

22,53 (10,17)

104

28,24 (10,12)

0,000*

MAC (cm)

23

25,05 (4,26)

157

26,94 (4,27)

105

29,65 (4,93)

0,000*

CC (cm)

24

30,46 (3,23)

156

32,80 (4,26)

104

35,52 (4,93)

0,000*

BMI (m/Kg2)

24

22,01 (4,89)

157

23,17 (4,79)

108

27,29 (5,75)

0,000*

MNA mini nutritional assessment, BMI body mass index, MAC mid-arm circumference, CC calf circumference,

* p < 0.05, significance level difference between MNA (ANOVA)

The Kayser-Meyer-Olkin (KMO) measure was 0.64. When above 0.5 it shows an adequation of the method. The Bartletts Test of Sphericity was 623.706, df = 153 and p = 0.000, indicating that the sample was adequate for conducting Factor Analysis.

In the Principal Component Analysis of the MNA, the results show a dispersion of the items for 6 components. It explains 52.6 % of the total variance in the explanatory psychometric evaluation. All four dimensions of the MNA are evidenced in the component analysis. The items are arranged according to the dimensions proposed in the original questionnaire, defining the constructs. The anthropometric assessment dimension corresponds to component 1; the global assessment dimension to component 4; the dietetic dimension to component 5; and the subjective dimension to component 2 (Table 3).
Table 3

Structure matrix of principal component analysis of the mini nutritional assessment questionnaire variables

Area

Item content

Component

1

2

3

4

5

6

Anthropometric assessment

Body mass index

0,853

0,140

0,090

−0,015

−0,006

0,066

 

Mid-arm circumference

0,805

0,070

0,107

0,023

0,078

0,016

 

Calf circumference

0,775

0,121

0,189

0,054

0,033

−0,032

 

Weight loss

−0,036

0,720

−0,045

0,079

0,050

−0,095

Global assessment

Independence at home

0,066

−0,070

0,028

0,127

−0,077

0,702

 

Number of medication per day

−0,169

−0,044

0,008

0,575

−0,268

−0,063

 

Psycological stress

0,051

0,203

−0,034

0,523

0,181

0,154

 

Mobility

0,085

0,032

0,698

0,132

−0,055

−0,120

 

Neuropsychological problems

−0,075

0,346

0,491

0,125

−0,032

−0,458

 

Pressure skin ulcer

0,129

0,153

0,025

0,648

0,114

−0,059

Dietetic assessment

Number of meals per day

−0,127

0,038

0,071

−0,250

0,374

0,357

 

Serves of high-protein foods

0,009

0,165

0,076

0,051

0,735

−0,111

 

Fruit and vegetables intake

0,037

0,087

−0,010

0,069

0,697

−0,009

 

Fluid intake

0,047

0,067

0,319

0,458

0,272

−0,464

 

Mode of feeding

0,202

0,013

0,663

−0,200

0,167

0,166

 

Appetite

0,174

0,711

−0,095

0,240

0,259

−0,055

Subjective assessment

Self-rated nutritional status

0,181

0,697

0,350

0,163

0,097

−0,093

 

Self-rated health

0,146

0,475

0,356

−0,083

0,059

−0,360

Rotation Method: Promax with Kaiser Normalization

Table 4 shows significant score correlations of the dimensional items of the MNA questionnaire, except for independence at home and number of meals per day.
Table 4

Item-total score correlations (Spearman, r) for the Portuguese version of the Mini Nutritional Assessment

Area

Item content

r

P - value

Anthropometric assessment

Body mass index

0,468

0,000

 

Mid-arm circumference

0,380

0,000

 

Calf circumference

0,430

0,000

 

Weight loss

0,512

0,000

Global assessment

Independence at home

−0,190

0,746

 

Number of medications per day

0,115

0,046

 

Psychological stress

0,339

0,000

 

Mobility

0,289

0,000

 

Neuropsychological problems

0,316

0,000

 

Pressure skin ulcers

0,314

0,000

Dietetic assessment

Number of meals per day

0,033

0,563

 

Serves of high-protein foods

0,183

0,001

 

Fruit and vegetables intake

0,242

0,000

 

Fluid Intake

0,326

0,000

 

Mode of feeding

0,218

0,000

 

Appetite

0,489

0,000

Subjective assessment

Self-rated nutritional status

0,528

0,000

 

Self-rated health

0,416

0,000

All nutritional variables had correlation with the full MNA (Fig. 1). There is strong and significant correlation between BF, CC, MAC, BMI and the MNA in this study population.
Fig. 1

Scatter plot and Spearman Correlation Coefficient of anthropometric measures according to Mini Nutritional Assessment (MNA) score. BMI, body mass index; MAC, mid-arm circumference; CC, calf circumference; BF, body fat; r, Spearman rank correlation coefficients

The ROC curve is presented in Fig. 2, as well as the corresponding AUC values. In this study, MAC provided excellent discrimination and the other anthropometric measures acceptable discrimination values (Table 5). All indicators showed good sensibility and specificity. MAC was more sensitive (82.8; CI95% 64.2-94.2) and CC more specific (80.0; CI95% 74.0-85.1).
Fig. 2

ROC curves of the Portuguese Mini Nutritional Assessment according to anthropometric measures. BMI, body mass index; MAC, mid-arm circumference; CC, calf circumference; BF, body fat; AUC, area under roc curve

Table 5

Accuracy the Portuguese version of the mini nutritional assessment tool according to BMI, MAC, CC and BF

Measure

Sensitivity (95 % CI)

Specificity (95 % CI)

AUC (95 % CI)

AUC discrimination

BMI

73.7 (63.9 – 82.1)

62.6 (55.5 – 69.2)

0.728 (0.674 – 0.777)

acceptable

MAC

82.8 (64.2 – 94.2)

76.9 (71.5 – 81.8)

0.832 (0.785 – 0.873)

excellent

CC

66.7 (54.3 – 77.6)

80.0 (74.0 – 85.1)

0.776 (0.723 – 0.823)

acceptable

BF

58.7 (46.7 – 64.9)

74 (67.3 – 79.9)

0.717 (0.660 – 0.769)

acceptable

BMI body mass index, MAC mid-arm circumference, CC calf circumference, BF body fat, CI confidence interval, AUC area under roc curve, r spearman rank correlation coefficients

Discussion

MNA is used widely around the world to evaluate nutrition status of the elderly. Other studies show that the MNA is an accurate assessment tool for nutritional problems, however it was not validated yet for Brazilian or other Latin American population [17, 29].

In the present study we used anthropometric measures including BMI, MAC, CC and BF. Even though there are not currently, generally accepted criteria for the diagnosis of malnutrition, these parameters have been widely used to evaluate nutritional status [30].

According to these testing results, the MNA full version was shown to have sufficient evidence of validity, including sensitivity and specificity in a sample of older home dwelling people, for identifying elderly hospital at nutritional risk and malnutrition. Anthropometric measures were used as standard to assess concurrent validity and to estimate sensitivity and specificity values.

Validity was supported when testing construct validity, when there is objective criterion that can be used. The Principal Component analysis was robust, with all dimensions represented and with significant correlations. Almost all item-to-total correlations were statically significant. However, not for two of the correlation coefficients: independence at home and number of meals per day. It can be explained by the fact that most of the people in this study gave the same answer, that is, they had the same meals and were not independent at home.

Criterion validity was also supported. It answers the question of how well the scores on a test agree with performance on a task it was meant to predict. The test had significant values of AUC, sensibility and specificity when the criteria BMI, MAC and CC were used. These criteria are common anthropometric measurements and often used in nutritional assessments [31].

According to the American Journal of Nursing, nine studies report sensitivity of the MNA to be 70 % or higher, compared with other nutritional parameters [3240], similar to this study results. In the original study of MNA as an indicator of protein-calorie under nutrition was found to have a sensitivity of 96 % and specificity of 98 % [17]; however we found lower sensitivity and specificity among Brazilian elderly, but still solid results. Based on the observation of the ROC curve, we also showed that the MNA is accurate.

Some limitations of this study deserve mentioning. First, due to the cross-sectional nature of this study we were unable to estimate a relative risk. Second, in order to increase the possibility of generalization, this association should be studied also in a free living sample. Nevertheless, this study is an important step in supporting scientific using of a popular instrument that measures risk and malnutrition in the elderly.

Conclusion

In conclusion, various studies support the use of MNA through the world among the elderly population. Malnutrition leads to a decline in health and possibly death; it is often unrecognized and under-treated by healthcare professionals. The full Portuguese version of the MNA demonstrated significant results that supported its validity. MNA has also shown robust exploratory psychometric properties for performing a nutritional screening. It seems to be valid tool to access nutritional status of Brazilian elderly.

Abbreviations

MNA: 

Mini Nutritional Assessment

CC: 

Calf circumference

MAC: 

Mid arm circumference

BF: 

Body fat

BIO: 

Bioimpedance electric

BMI: 

Body mass index

r: 

Spearman correlation coefficient

ANOVA: 

Variance analysis

SD: 

Standard deviation

AUC: 

Area under ROC curve

Declarations

Acknowledgements

We appreciate the reviewers for comments that have improved the manuscript. This work was supported by FAPERJ – Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Instituto de Nutrição Josué de Castro – INJC, Universidade Federal do Rio de Janeiro – UFRJ
(2)
Universidade Aberta da Terceira Idade – UnATI, Universidade Estadual do Rio de Janeiro – UERJ

References

  1. Ahmed T, Haboubi N. Assessment and management of nutrition in older people and its importance to health. Clinical Interventions in Aging. 2010;5:207–16.PubMedPubMed CentralGoogle Scholar
  2. Caplan GA. Geriatric Medicine: an Introduction. Melbourne: 1st, IP Communications; 2014.Google Scholar
  3. Tsutsumi R, Tsutsumi YM, Horikawa YT, Takehisa Y, Hosaka T, Harada N, et al. Decline in anthropometric evaluation predicts a poor prognosis in geriatric patients. Asia Pac J Clin Nutr. 2012;21(1):44–51.PubMedGoogle Scholar
  4. Adams NE, Bowie AJ, Simmance N, Murrary M, Crowe T. Recognition by Medical and nursing professionals of malnutrition and risk of malnutrition in elderly Hospitalised patients. Nutrition and Dietetics. 2008;65:144–50.View ArticleGoogle Scholar
  5. Abellan Van Kan G, Vellas B. Is the Mini Nutritional Assessment an appropriate tool to assess frailty in older adults? J Nutr Health Aging. 2011;15(3):159–61.View ArticlePubMedGoogle Scholar
  6. Vellas B, Villars H, Abellan G, Soto ME, Rolland Y, Guigoz Y, et al. Overview of the MNA-Its history and challenges. J Nutr Health Aging. 2006;10(6):456–63.PubMedGoogle Scholar
  7. Abellan Van Kan G, Rolland Y, Bergman H, Morley JE, Kritchevsky SB, Vellas B. The I.A.N.A Task Force on frailty assessment of older people in clinical practice. J Nutr Health Aging. 2008;12(1):29–37.View ArticlePubMedGoogle Scholar
  8. Salva A, Coll-Planas L, Bruce S, De Groot L, Andrieu S, Abellan G, et al. Nutritional assessment of residents in long-term care facilities (LTCFs): recommendations of the task force on nutrition and ageing of the IAGG European region and the IANA. J Nutr Health Aging. 2009;13(6):475–83.View ArticlePubMedGoogle Scholar
  9. Lei Z, Qingyi D, Feng G, Chen W, Hock RS, Changli W. Clinical study of mininutritional assessment for older Chinese inpatients. J Nutr Health Aging. 2009;13(10):871–5.View ArticlePubMedGoogle Scholar
  10. Tsai AC, Ku PY, Tsai JD. Population-specific anthropometric cutoff standards improve the functionality of the Mini Nutritional Assessment without BMI in institutionalized elderly in Taiwan. J Nutr Health Aging. 2008;12(10):696–700.PubMedGoogle Scholar
  11. Johansson L, Sidenvall B, Malmberg B, Christensson L. Who will become malnourished? A prospective study of factors associated with malnutrition in older persons living at home. J Nutr Health Aging. 2009;13(10):855–61.View ArticlePubMedGoogle Scholar
  12. Johansson Y, Bachrach-Lindström M, Carstensen J, Ek AC. Malnutrition in a homeliving older population: prevalence, incidence and risk factors. A prospective study. J ClinNurs. 2009;18(9):1354–64.Google Scholar
  13. Cansado P, Ravasco P, Camilo M. A longitudinal study of hospital undernutrition in the elderly: comparison of four validated methods. J Nutr Health Aging. 2009;13(2):159–64.View ArticlePubMedGoogle Scholar
  14. Kaiser R, Winning K, Uter W, Lesser S, Stehle P, Sieber CC, et al. Comparison of two different approaches for the application of the mini nutritional assessment in nursing homes: resident interviews versus assessment by nursing staff. J Nutr Health Aging. 2009;13(10):863–9.View ArticlePubMedGoogle Scholar
  15. Pereira Machado RS, Santa Cruz Coelho MA. Risk of malnutrition among Brazilian institutionalized elderly: a study with the Mini Nutritional Assessment (MNA) questionnaire. J Nutr Health Aging. 2011;15(7):532–5.View ArticlePubMedGoogle Scholar
  16. WHO: Expert Committee on Physical Status: the Use and Interpretation of Anthropometry Physical status: the use and interpretation of anthropometry: report of a WHO expert committee. WHO technical report series, 1995; 854.Google Scholar
  17. Guigoz Y, Vellas B, Garry PJ. Mini Nutritional Assessment: a practical tool for grading the nutritional state of the elderly patients. Facts Res Gerontol. 1994;suppl 2:15–60.Google Scholar
  18. Fidanza F, Keller W. Nutritional Status Assessment. London: Chapman and Hall; 1991.View ArticleGoogle Scholar
  19. Kwok T, Whitelaw MN. The use of armspan in nutritional assessment of the elderly. J Am Geriatr Soc. 1991;39(5):492–6.View ArticlePubMedGoogle Scholar
  20. Chumlea WC, Guo SS, Vellas B, Guigoz Y. Techniques of assessing muscle mass and function (sarcopenia) for epidemiological studies of the elderly. J Gerontol A BiolSci Med Sci. 1995;50(special issue):45–51.Google Scholar
  21. Ferro-Luzzi A, Sette S, Franklin M, James WPT. A simplified approach to assessing adult chronic energy deficiency. European Journal of Clinical Nutrition. 1992;46:173–86.PubMedGoogle Scholar
  22. Burr B, Phillips K. Anthropometric Norms in the Elderly. Br. J. of Nutr.51: 165. Forbes, G.B. (1976). The Adult Decline in Lean Body Mass. Hum Biol. 1984;48:161–6.Google Scholar
  23. Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J ClinNutr. 2000;72(3):694–701.Google Scholar
  24. Woods A, Moshang J: Lowering the risks of diabetes, hypertension, and heart disease. Nursing 2005, Feb;Suppl:4–8; quiz 8–9. Review.Google Scholar
  25. Tajima O, Nagura E, Ishikawa-Takata K, Ohta T. Two new potent and convenient predictors of mortality in older nursing home residents in Japan. Geriatr Gerontol Int. 2004;4:77–83.View ArticleGoogle Scholar
  26. Vandewoude MFJ, Alish CJ, Sauer AC, Hegazi RA. Malnutrition-sarcopenia syndrome: is this the future of nutrition screening and assessment for older adults? J Aging Res. 2012;651570:8.Google Scholar
  27. Streiner DL, Norman GR. Health Measurement Scales: A Practical Guide to their Development and Use. 4th ed. Oxford: Oxford University Press; 2008.View ArticleGoogle Scholar
  28. Hosmer DW, Lemeshow S. Applied Logistic Regression. 2nd ed. New York: John Wiley and Sons; 2000.View ArticleGoogle Scholar
  29. Guigoz Y, Vellas B. The Mini Nutritional Assessment (MNA) for grading de nutritional state of the elderly patients: Presentation of the MNA, History and Validation. Nestlé Nutr Workshop Ser Clin Perform Program. 1999;1:3–12.View ArticleGoogle Scholar
  30. Omran ML, Morley JE. Assessment of protein energy malnutrition in older persons, Part II: laboratory evaluation. Nutrition. 2000;16:131.View ArticlePubMedGoogle Scholar
  31. Kuzuya M, Kanda S, Koike T, Suzuki Y, Satake S, Iguchi A. Evaluation of Mini-Nutritional Assessment for Japanese frail elderly. Nutrition. 2005;21(4):498–503.View ArticlePubMedGoogle Scholar
  32. Christensson L, Unosson M, Ek AC. Evaluation of nutritional assessment techniques in elderly people newly admitted to municipal care. Eur J ClinNutr. 2002;56(9):810–8.View ArticleGoogle Scholar
  33. Delacorte RR, Moriguti JC, Matos FD, Pfrimer K, Marchinil JS, Ferriolli E. Mini-Nutritional Assessment score and the risk for undernutrition in free-living older persons. J Nutr Health Aging. 2004;8(6):531–4.PubMedGoogle Scholar
  34. Donini LM, de Felice MR, Tassi L, de Bernardini L, Pinto A, Giusti AM, et al. A “proportional and objective score” for the Mini Nutritional Assessment in long-term geriatric care. J Nutr Health Aging. 2002;6(2):141–6.PubMedGoogle Scholar
  35. Murphy MC, Brooks CN, New SA, Lumbers ML. The use of the Mini-Nutritional Assessment (MNA) tool in elderly orthopaedic patients. Eur J Clin Nutr. 2000;54(7):555–62.View ArticlePubMedGoogle Scholar
  36. Read JA, Crockett N, Volker DH, MacLennan P, Choy ST, Beale P, et al. Nutritional assessment in cancer: comparing the Mini-Nutritional Assessment (MNA) with the scored Patient-Generated Subjective Global Assessment (PGSGA). Nutr Cancer. 2005;53(1):51–6.View ArticlePubMedGoogle Scholar
  37. Thomas DR, Zdrowski CD, Wilson MM, Conright KC, Lewis C, Tariq S, et al. Malnutrition in subacute care. Am J ClinNutr. 2002;75(2):308–13.Google Scholar
  38. Thorsdottir I, Jonsson PV, Asgeirsdottir AE, Hjaltadottir I, Bjornsson S, Ramel A. Fast and simple screening for nutritional status in hospitalized, elderly people. J Hum Nutr Diet. 2005;18(1):53–60.View ArticlePubMedGoogle Scholar
  39. Visvanathan R, Penhall R, Chapman I. Nutritional screening of older people in a sub-acute care facility in Australia and its relation to discharge outcomes. Age Ageing. 2004;33(3):260–5.View ArticlePubMedGoogle Scholar
  40. Wikby K, Ek AC, Christensson L. Nutritional status in elderly people admitted to community residential homes: comparisons between two cohorts. J Nutr Health Aging. 2006;10(3):232–8.PubMedGoogle Scholar

Copyright

© Machado et al. 2015

Advertisement