Skip to main content
The Journal of Nutrition, Health & Aging logoLink to The Journal of Nutrition, Health & Aging
. 2013 Oct 21;18(4):372–377. doi: 10.1007/s12603-013-0400-5

Factors associated with deterioration of mini nutritional assessment-short form status of nursing home residents during a 2-year period

Sachiko Izawa 1,3,5,a, H Enoki 2,3, J Hasegawa 3, T Hirose 4, M Kuzuya 3
PMCID: PMC12880513  PMID: 24676317

Abstract

Objective

A number of other studies have been conducted to verify the Mini Nutritional Assessment (MNA) or the MNA short form (MNA-SF) as a nutritional assessment/screening tool in various clinical settings or communities. However, there are few longitudinal studies using these tools to analyze which factors affect the incidence of deteriorating nutritional status. We tried to identify the factors associated with deterioration of MNA-SF status of nursing home residents during a 2-year period.

Methods

Participants were 392 people with a mean age of 84.3 in 12 nursing homes in Japan. The factors associated with deterioration in MNA-SF categories during the study period compared to stable/improved MNA-SF categories were identified.

Results

At baseline, 19.9% of the participants were malnourished and 60.2% were at risk of malnutrition, according to the MNA-SF classification. After 2 years, 66.3% participants maintained and 6.1% participants improved their nutritional status according to the MNA-SF classification, while 27.6% showed deterioration in MNA-SF status. Stepwise logistic-regression procedure indicated that basic ADL impairment and hospitalization during the follow-up period were associated with declining MNA-SF status.

Conclusions

Poor basic ADL status and hospitalization during the follow-up period were associated with malnutrition and risk of malnutrition as assessed by MNA-SF of nursing homes residents during a 2-year period.

Key words: The factors associated with deterioration of Mini Nutritional Assessment-Short Form stage, frail elderly, nursing home

Introduction

Japan has the most rapidly aging population in the world and soon will have the largest percentages of elderly and very elderly in its population. In 2011, the rate of the population over age sixty-five was 23.3%. Elderly persons 100 years or older numbered 47,756 and 87.1% of these were women. The numbers of frail elderly people living in the community or institutions for the aged are increasing, along with their hospital admissions.

The nutritional status of older people is an important determinant of quality of life, morbidity and mortality 1, 2, 3. The relationship between poor nutritional status and impaired immune functions, the development of pressure sores, and impaired muscle function is well established (4, 5, 6). Therefore, it is quite important for the elderly to maintain good nutritional status.

The Mini-Nutritional Assessment (MNA) is a simple clinical scale for the evaluation of the nutritional status of frail elderly subjects 4, 7, 8. We evaluated the MNA test as a screening tool for malnutrition in the Japanese elderly population and concluded that the MNA full test is a useful screening tool for identifying Japanese elderly with malnutrition or a risk of malnutrition (9). A number of other studies have been conducted to verify the MNA or the MNA short form (MNA-SF) as a nutritional assessment/screening tool in various clinical settings or communities. However, there are few longitudinal studies using these tools to analyze which factors affect the incidence of deteriorating nutritional status.

In the present prospective study we tried to identify the factors associated with deterioration of MNA-SF status of residents of nursing homes during a 2-year period.

Methods

Subjects

The study population consisted of 649 residents of 12 nursing homes located in Nagoya City (116 men and 533 women, age 65 years or older). Twelve nursing homes belonged to a single social welfare corporation and staffs of nursing homes received the same education training. The dietitians carry out the nutritional assessment of the nursing home residents according to the Long-Term Care Insurance (LTCI) program. These participants, who were enrolled between May 1 and June 30, 2009, were scheduled to undergo comprehensive assessments by trained nursing home staff at baseline, and at 12 and 24 months. At 3-month intervals, data were collected about any important events in the lives of the participants, including admission to the hospital, and mortality. Written informed consent for participation, according to procedures approved by the institutional review board of Nagoya University Graduate School of Medicine, was obtained from the residents or, for those with substantial cognitive impairment, from a surrogate (usually the closest relative or legal guardian).

Data collection

The data were collected at the nursing homes using structured interviews with residents and nursing home staff, and from nursing home records taken by trained nurses. The data included clients’ demographic characteristics and a rating for ten basic Activities of Daily Living (ADL: getting out of bed, transferring, walking, bathing, grooming, dressing, putting on and taking off pants, feeding, bowel and bladder management). For each ADL task, nurses rated residents as independent (a score of 10, able to perform the activity without help), partially dependent (a score of 5, requiring some assistance), or completely dependent (a score of 0, needing help for the entire activity). The sum of these scores theoretically range from 0 (total disability) to 100 (no disability). Nurse ratings were based on direct observation, interviews with residents, and information from staff. Information obtained from nursing homes records included data on the following physician-diagnosed chronic conditions: ischemic heart disease, congestive heart failure, cerebrovascular disease, diabetes mellitus, dementia, cancer, neurodegenerative disorders including Parkinson's disease, and other diseases comprising the Charlson Comorbidity Index (10), which represents the sum of weighted indexes taking into account the number and seriousness of preexisting comorbid conditions. Chewing ability was categorized into three groups: difficulty chewing even soft food items such as boiled rice, tuna sashimi, and grilled eel (poor), difficulty chewing harder foods such as hard rice crackers, peanuts, and yellow pickled radish (fair), and no difficulty chewing harder foods (good). Dietitian ratings were based on direct observation and information from other staff.

Anthropometry

Height and weight data were generally measured at the nursing homes and collected by trained staff. Weight was measured in light clothing without shoes using a portable weight scale at the nursing homes. Height was generally measured in an upright position using a tape measure attached to the wall. However, when participants could not maintain an upright position, height measurements were obtained in a prone position.

Nutritional Assessment

The MNA-SF is composed of a combination of six questions taken from the full MNA about appetite loss, weight loss, mobility, stress/acute disease, dementia/depression, and body mass index (BMI). The score of the MNA-SF was used to classify subjects’ nutritional status as well-nourished (a score of 12-14), at-risk for malnutrition (a score of 8-11), or malnourished (a score of 0-7). The MNA-SF was administered by dietitians, except for the mental state questionnaire which was obtained from nursing staff members or medical records at baseline, at 1 year later and at 2 years later.

Study participants

Among 450 survivors, the participants who stayed in the nursing home and were re-assessed at both baseline and at 2 years later were 392. The 60 participants who were assessed as malnourished according to the MNA-SF at both baseline and at 2 years later were excluded from our analysis to identify the factors associated with becoming malnourished or at risk of malnutrition.

Statistical analysis

The Student's t-test and Chi-squared test were used to compare differences between participants with the MNA-SF stage decline and those without decline (improved or stable MNA-SF stage). The 392 study participants were divided into tertiles according to the basic ADL score at baseline (first, 55-100; second, 20-50; third, 0-15). The significance level was set at P< 0.05 and quoted are two-sided.

Univariate and multivariate logistic regression models were used to identify independent predictors of declining MNA-SF status. The following baseline data were used in univariate analysis: gender, age, basic ADL, ability of chewing, and hospitalization during the 2-year period. The covariates included in the multivariate analysis were those variables associated with dependent variables at a level of P< 0.05 in univariate analysis. Stepwise logistic-regression procedure was conducted. The risk of a variable was expressed as an odds ratio (OR) with a corresponding 95% confidence interval (CI).

All analyses were performed using the Statistical Package for the Social Sciences (SPSS) Version 20.0. A probability value of 0.05 or less was considered significant.

Results

Among the 649 participants, 199 subjects died during the 2-year study period. It should be noted that mean MNA-SF score of 199 at the base line was significantly lower than that of 450 survivors (8.2 (SD 2.0) vs 9.3 (SD 2.4), P<0.001).

Table 1 shows the characteristics of the 392 participants at baseline. The mean age was 84.3 (SD 7.21) years, with 49.7% of the subjects 85 years or older and 82.9% of them women. The mean BMI, MNA-SF score and basic ADL score were 20.3 (SD 3.7) kg/m2, 9.3 (SD 2.3) points, and 37.3 (SD 29.7) points, respectively. The participants had a high prevalence of dementia (56.9%), cerebrovascular disease (49.9%) and hypertension (46.4%). Among the 392 participants, 20.1% participants had poor chewing ability.

Table 1.

Baseline characteristics of the 392 frail elderly

total (n 392)
n % of total mean SD
Age (years) 392 84,3 7,2
Body Mass Index (kg/m2) 392 20,3 3,7
MNA-SF score (max. 14 points) 392 9,3 2,3
MNA-SF classification
malnourished 78 19,9
at risk of malnutrition 236 60,2
well-nourished 78 19,9
Charlson comorbidity index (range, 0-19) 392 2,3 1,6
Chronic diseases
dementia 223 56,9
cerebrovascular disease 195 49,9
hypertension 182 46,4
heart failure 61 15,6
ischemic heart disease 62 15,8
diabetes mellitus 60 15,3
Parkinson's disease 24 6,1
Basic ADL (range, 0-100) 392 37,3 29,7
Chewing ability
good 129 33,2
fair 181 46,6
poor
78
20,1


At baseline, 19.9% of the participants were malnourished and 60.2% were at risk of malnutrition, according to the MNA-SF classification (Table 1). As shown in table 2, after 2 years, 37.2% of the participants were classified as malnourished and 49.2% were at risk of malnutrition, according to the MNA-SF classification. Among the 392 participants, 260 (66. 3%) participants maintained and 24 (6.1%) participants improved their nutritional status according to the MNA-SF classification (18 moved from “malnutrition” to “at risk of malnutrition”; 6 from “at risk” to “normal nutrition”), while 108 (27.6%) showed deterioration of MNA-SF categories during the study period (9 from normal nutrition to malnutrition, 22 from normal nutrition to at-risk status, and 77 from at-risk to malnutrition). Sixty (15.3%) participants were assessed as malnourished at both baseline and at 2 years later (Table 2). Therefore, the number of participants with improved/stable and deteriorating status according to MNA-SF classification, after excluding participants with malnutrition at both baseline and follow-up, were 224 and 108, respectively.

Table 2.

Mini Nutritional Assessment Short Form status at baseline and at 2-year follow-up

Baseline MNA-SF Malnourished MNA-SF status at 2-yr follow-up At risk of malnutriton Well-nourished Total
Malnourished
number of participants 60 18 0 78
% of baseline 76,9% 23,1% 0,0% 100,0%
% of at 2-year 41,1% 9,3% 0,0% 19,9%
At risk of malnutrition
number of participants 77 153 6 236
% of baseline 32,6% 64,8% 2,5% 100,0%
% of at 2-year 52,7% 79,3% 11,3% 60,2%
Well-nourished
number of participants 9 22 47 78
% of baseline 11,5% 28,2% 60,3% 100,0%
% of at 2-year 6,2% 11,4% 88,7% 19,9%
Total
number of participants 146 193 53 392
% of baseline 37,2% 49,2% 13,5% 100,0%
% of at 2-year
100,0%
100,0%
100,0%
100,0%

Table 3 compares the baseline characteristics of participants whose MNA-SF status deteriorated and remained stable/improved during the 2-year period. No differences were observed in age, Charlson Comorbidity Index score, BMI, or the MNA-SF score at baseline between participants in the two groups. The basic ADL score (range, 0-100) at baseline of the stable/improved MNA-SF group (44.3, SD 30.0) was significantly higher than that of the deteriorating MNA-SF group (35.0, SD 29.1) (P = 0.007). The prevalence rates of hospitalization during the 2-year period were significantly higher for those with decline in MNA-SF status (39.8%) than for those with improved/stable MNA-SF status (26.8%) (P = 0.022). There was also a significant difference in the chewing ability between two groups (P = 0.026).

Table 3.

Baseline and 2-yr follow-up characteristics of participants with improved/stable or deteriorating MNA-SF status

MNA-SF change during 2-year period
improved/stable status (n 224) deteriorating status (n 108)
n % of total mean SD n % of total mean SD P value
Men/Women 50/174 22.3/77.7 11/97 10.2/89.8 0.007f
Age (years) 224 83,9 7,3 108 85,0 7,3 0.183*
Body Mass Index (kg/m2) 224 21,1 3,8 108 20,5 3,7 0.120*
Charlson Comorbidity Index 224 2,3 1,6 108 2,2 1,6 0.589*
Basic ADL (range, 0-100 points) first tertile (55-100points) second tertile (20-50points) third tertile (0-15 points) 224 44,3 30,0 108 35,0 29,1 0.007*
98 43,8 27 25,0 0.003f
65 29,0 46 42,6
61 27,2 35 32,4
Chewing ability
good 91 41,0 32 29,9 0.026f
fair 107 48,2 53 49,5
poor 24 10,8 22 20,6
MNA-SF score (max. 14 points) 224 10,0 2,0 108 9,8 1,9 0.523*
Hospitalization during the 2-year period
60
26,8


43
39,8


0.022f
*

Student's t-test was used to compare differences between participants with the MNA-SF stage decline and those without decline; f Chi-square test was used to compare differences between participants with the MNA-SF stage decline and those without decline

To identify the factors associated with categorical decline of MNA-SF during the study compared to stable/improved MNA-SF status, stepwise logistic-regression procedure was conducted. As shown in Table 4, women, lowest basic ADL status, poor chewing ability, and hospitalization during the 2-year period were independent predictors of a decline in MNA-SF status in univariate analysis.

Table 4.

Stepwise logistic-regression procedure to identify independent predictors of deteriorating MNA-SF status

OR* crude 95% CI p OR* model 1 95% CI multivariate p OR* model 2 95% CI p
Women (vs men) 2,53 1,26 -5,10 0,009 2,54 1,25-5,17 0,010 2,41 1,18 -4,92 0,016
Age (continuous variable) 1,02 0,99 -1,06 0,183
The score of basic ADL (range:0-100 first tertile (55-100points) second tertile (20-50points) third tertile (0-15 points) 1,00
  • 2,57

  • 2,08

1,45 -4,54
  • 1,15 -3,78

0,001
  • 0,016

1,00
  • 2,60

  • 2,01

1,46-4,63
  • 1,10 -3,68

0,001
  • 0,024

1,00
  • 2,62

  • 2,02

1,47 - 4,69
  • 1,10 -3,72

0,001
  • 0,024

Chewing ability
good
  • fair

  • poor

1,00
  • 1,41

  • 2,61

0,84 -2,37
  • 1,29 -5,28

0,197
  • 0,008

Hospitalization during the 2-year period
no
  • yes


1,00
  • 1,81


1,11 -2,94
0,017



1,00
  • 1,80


1,09 -2,97
0,023

OR* Odds Ratio; P values; logistic regression variables; model 1 using stepwise selection; adjusted includes gender, age,the score of ADL at baseline, and chewing ability at baseline; model 2 using stepwise selection; adjusted includes gender, age, the score of ADL at baseline, chewing ability at baseline, and hospitalization during the 2-year period

We used two different models to conduct multivariate analysis, in which the variables with P < 0.05 in univariate analysis were further examined. In model 1 the covariates included were gender, age, basic ADL status, and chewing ability. In model 2, hospitalization during the 2-year period was added in the analysis. Stepwise logistic- regression procedure indicated a lower and lowest basic ADL status in model 1, and a lower and lowest basic ADL status and hospitalization during the follow-up period in model 2 were associated with deteriorating MNA-SF status (OR 2.60, 95%CI 1.46, 4.63, OR 2.01, 95%CI 1.10, 3.68, OR 2.62, 95% CI 1.47, 4.69, OR 2.02, 95% CI 1.10, 3.72, OR 1.80, 95% CI 1.09, 2.97, respectively).

Discussion

The aim of the present study was to identify the factors associated with deterioration of MNA-SF status of nursing home residents during a 2-year period. We showed that 27.6% of subjects had deteriorating MNA-SF status during the 2-year period and that basic ADL impairment and hospitalization experience during the study period were associated with this decline. Severity of comorbidity was not related with deteriorating MNA-SF status in this study.

At the baseline of this study, 19.9% and 60.2% of the participants were categorized by MNA-SF as malnourished and at risk of malnutrition, respectively. One review article has summarized the 13 studies in which MNA has been used for nutritional assessment in nursing homes, and reported that malnutrition was observed in 2 to 38% and a risk of malnutrition in 37 to 62% of nursing home residents (11). The combined database providing information on 1586 nursing home residents from 7 countries demonstrated that 32.9%, 53.4%, and 13.8% of residents were well-nourished, at risk of malnutrition, and malnourished, respectively (12). Recent study in which MNA has been used for nutritional assessment in 286 nursing home residents reported, malnourished (18.2%)and at risk of malnutrition (42.0%) (13). There have been only few studies to assess nutritional status of nursing home residents using MNA-SF. One study reported that 39.9% nursing home residents were assessed as well-nourished, 41.9% at risk of malnutrition, and 18.1% malnourished (14). In another study reported 66% of the screened by MNA-SF individuals were at risk of malnutrition and the prevalence of malnutrition is higher in women, in nursing homes and in older age groups (15). From these observations the prevalence rates of malnutrition classified through MNA/MNA-SF vary among various nursing homes. Compared with previous observations from nursing homes, fewer malnourished residents and more at risk of malnutrition were observed in the present cohort.

Most of the prospective studies using MNA/MNA-SF have demonstrated the predictive values of these nutritional screening tools for mortality or functional decline in various geriatric settings (16, 17, 18). However, there was no prospective studies to identify the risk of deterioration of MNA/MNA-SF status during a follow-up period. In the present study, we demonstrated that 3 variables at baseline—female gender, basic ADL impairment, and hospitalization—were associated with deterioration in MNA-SF status during a 2-year period. We do not know why women were associated with nutritional decline compared with men. Although women in nursing homes are on average older than men, the association persisted even if when age was incorporated in the analysis. It is possible that unmeasured factors might mediate this gender difference.

The odds ratio of dereriorating MNA-SF scores for participants in the third tertile (worst function) was lower than those in the second tertile. In the present study, the participants of the third tertile contained lower levels of mobility including bed ridden situation. It was possible there were the lower total energy expenditure among participants with advanced dysfunction compared with those with mid dysfunction.

There have been a number of cross-sectional studies demonstrating an association between physical function impairment/ADL dependence and poor nutritional status as assessed by MNA/MNA-SF (19, 20, 21). Although these studies suggest that there is an interrelationship between the nutritional status of the elderly in various settings and reduced functional capacity (22, 23, 24), the exact causal relationships remain controversial. The prior studies demonstrated that weight loss predicts the development of disability in older people (22, 23, 24). However, it remains unknown whether physical function/ADL status may influence the development of malnutrition or risk of malnutrition (25). The present study clearly indicated that the lowest basic ADL status was associated with a decline in MNA-SF status. This association persisted after adjusting for gender, age, and hospitalization during study periods.

There have been several cross-sectional studies showing that chewing problems are associated with malnutrition (26, 27, 28). Again, these results did not reveal the causal relationships between chewing ability and poorer nutritional status in the older people. The present study showed that poor chewing ability at baseline was associated with declining MNA-SF status during the study period in the crude model, although the ability was not selected by stepwise regression procedure, indicating that more attention should be paid to the impact of oral health, which imposes dietary restrictions on older people with consequences for their nutritional status.

The present study showed that hospitalization during the 2-year period was associated with a decline in MNA-SF status. In consisted with the previous studies demonstrated an association between hospitalization and malnutrition 3, 29. It should be noted that there is one item asking about the presence or absence of psychological stress or acute disease in the past 3 months in MNA-SF. This may influence the association.

The present study has several limitations. The subjects of the present study were dependent elderly people who had chronic diseases and needed help in everyday life at the nursing home. The results of the present study cannot be transferred to community-dwelling independent elderly individuals. These findings may not be generalizable to other populations given that they may have been influenced by health practices and a variety of social and economic factors.

In conclusion, this study showed that poor basic ADL status and hospitalization of nursing home residents during a 2-year follow-up period were associated with malnutrition and risk of malnutrition as assessed by MNA-SF.

Acknowledgments

Acknowledgments: This work was supported by JSPS KAKENHI Grant Number 23617030 (Izawa S) and from a Grant-in Aid for the Comprehensive Research on Aging and Health from the Ministry of Health, Labor, and Welfare of Japan (H21-chojyu-ippan-003) (Kuzuya M).

Conflict of Interest: All authors state that they have no conflicts of interest.

References

  • 1.Topinkova E. Aging, disability and frailty. Ann Nutr Metab. 2008;52(Suppl.1):6–11. doi: 10.1159/000115340. PubMed PMID: 18382070. [DOI] [PubMed] [Google Scholar]
  • 2.Akner G, Cederholm T. Treatment of protein-energy malnutrition in chronic nonmalignant disorders. Am J Clin Nutri. 2001;74:6–24. doi: 10.1093/ajcn/74.1.6. [DOI] [PubMed] [Google Scholar]
  • 3.Margetts BM, Thomoson RL, Elia M, Jackson AA. Prevalence of risk of undernutrition is associated with poor health status in older people in the UK. Eur J Clin Nutr. 2003;57:69–74. doi: 10.1038/sj.ejcn.1601499. 10.1038/sj.ejcn.1601499 PubMed PMID: 12548299. [DOI] [PubMed] [Google Scholar]
  • 4.Guigoz Y. The Mini Nutritional Assessment (MNA) review of the literature-What does it tell us? J Nutr Health Aging. 2006;10:466–485. PubMed PMID: 17183419. [PubMed] [Google Scholar]
  • 5.Izawa S, Kuzuya M, Okada K, Enoki H, Koike T, Kanda S, Iguchi A. The nutritional status of frail elderly with care needs according to the mini-nutritional assessment. Clin Nutr. 2006;25:962–967. doi: 10.1016/j.clnu.2006.05.006. 10.1016/j.clnu.2006.05.006 PubMed PMID: 16859814. [DOI] [PubMed] [Google Scholar]
  • 6.Saletti A, Lindgren EY, Johansson L, Cederholm T. Nutritional status according to mini nutritional assessment in an institutionalized elderly population in Sweden. Gerontology. 2000;46:139–145. doi: 10.1159/000022149. 10.1159/000022149 PubMed PMID: 10754371. [DOI] [PubMed] [Google Scholar]
  • 7.Bauer JM, Kaiser MJ, Anthony P, Guigoz Y, Sieber CC. The Mini Nutritional Assessment-its history, today's practice, and future perspectives. Nutr Clin Pract. 2008;23:388–396. doi: 10.1177/0884533608321132. 10.1177/0884533608321132 PubMed PMID: 18682590. [DOI] [PubMed] [Google Scholar]
  • 8.Kaiser MJ, Bauer JM, Ramsch C, et al. Validation of the Mini Nutritional Assessment short-form (MNA-SF): a practical tool for identification of nutritional status. J Nutr Health Aging. 2009;13:782–788. doi: 10.1007/s12603-009-0214-7. 10.1007/s12603-009-0214-7 PubMed PMID: 19812868. [DOI] [PubMed] [Google Scholar]
  • 9.Kuzuya M, Kanda S, Koike T, Suzuki Y, Satake S, Iguchi A. Evaluation of Mini-Nutritional Assessment for Japanese frail elderly. Nutrition. 2005;21:498–503. doi: 10.1016/j.nut.2004.08.023. 10.1016/j.nut.2004.08.023 PubMed PMID: 15811771. [DOI] [PubMed] [Google Scholar]
  • 10.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–383. doi: 10.1016/0021-9681(87)90171-8. 10.1016/0021-9681(87)90171-8 PubMed PMID: 3558716. [DOI] [PubMed] [Google Scholar]
  • 11.Pauly L, Stehle P, Volkert D. Nutritional situation of elderly nursing home residents. Z Gerontol Geriatr. 2007;40:3–12. doi: 10.1007/s00391-007-0430-x. 10.1007/s00391-007-0430-x PubMed PMID: 17318726. [DOI] [PubMed] [Google Scholar]
  • 12.Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58:1734–1738. doi: 10.1111/j.1532-5415.2010.03016.x. 10.1111/j.1532-5415.2010.03016.x PubMed PMID: 20863332. [DOI] [PubMed] [Google Scholar]
  • 13.Stange I, Poeschl K, Stehle P, et al. Screening for malnutrition in nursing home residents: comparison of different risk markers and their association to functional impairment. J Nutr Health Aging. 2013;17:357–363. doi: 10.1007/s12603-013-0021-z. 10.1007/s12603-013-0021-z PubMed PMID: 23538659. [DOI] [PubMed] [Google Scholar]
  • 14.Kaiser MJ, Bauer JM, Uter W, et al. Prospective validation of the modified mini nutritional assessment short-forms in the community, nursing home, and rehabilitation setting. J Am Geriatr Soc. 2011;59:2124–2128. doi: 10.1111/j.1532-5415.2011.03659.x. 10.1111/j.1532-5415.2011.03659.x PubMed PMID: 22092071. [DOI] [PubMed] [Google Scholar]
  • 15.Vandewoude M, Van Gossum A. Nutritional screening strategy in nonagenarians: the value of the MNA-SF (mini nutritional assessment short form) in NutriAction. J Nutr Health Aging. 2013;17:310–314. doi: 10.1007/s12603-013-0033-8. 10.1007/s12603-013-0033-8 PubMed PMID: 23538651. [DOI] [PubMed] [Google Scholar]
  • 16.Formiga F, Chivite D, Solé A, Manito N, Ramon JM, Pujol R. Functional outcomes of elderly patients after the first hospital admission for decompensated heart failure (HF) A prospective study. Arch Gerontol Geriatr. 2006;43:175–185. doi: 10.1016/j.archger.2005.10.010. 10.1016/j.archger.2005.10.010 [DOI] [PubMed] [Google Scholar]
  • 17.Sancarlo D, D'Onofrio G, Franceschi M, et al. Validation of a Modified-Multidimensional Prognostic Index (m-MPI) including the Mini Nutritional Assessment Short-Form (MNA-SF) for the prediction of one-year mortality in hospitalized elderly patients. J Nutr Health Aging. 2011;15:169–173. doi: 10.1007/s12603-010-0293-5. 10.1007/s12603-010-0293-5 PubMed PMID: 21369662. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Dent E, Visvanathan R, Piantadosi C, Chapman I. Nutritional screening tools as predictors of mortality, functional decline, and move to higher level care in older people: a systematic review. J Nutr Gerontol Geriatr. 2012;31:97–145. doi: 10.1080/21551197.2012.678214. 10.1080/21551197.2012.678214 PubMed PMID: 22607102. [DOI] [PubMed] [Google Scholar]
  • 19.Suominen M, Muurinen S, Routasalo P, et al. Malnutrition and associated factors among aged residents in all nursing homes in Helsinki. Eur J Clin Nutr. 2005;59:578–583. doi: 10.1038/sj.ejcn.1602111. 10.1038/sj.ejcn.1602111 PubMed PMID: 15744328. [DOI] [PubMed] [Google Scholar]
  • 20.Saka B, Kaya O, Ozturk GB, Erten N, Karan MA. Malnutrition in the elderly and its relationship with other geriatric syndromes. Clin Nutr. 2010;29:745–748. doi: 10.1016/j.clnu.2010.04.006. 10.1016/j.clnu.2010.04.006 PubMed PMID: 20627486. [DOI] [PubMed] [Google Scholar]
  • 21.Oliveira MR, Fogaça KC, Leandro-Merhi VA. Nutritional status and functional capacity of hospitalized elderly. Nutr J. 2009;17:54. doi: 10.1186/1475-2891-8-54. 10.1186/1475-2891-8-54 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Tully CL, Snowdon DA. Weight change and physical function in older women: findings from the Nun Study. J Am Geriatr Soc. 1995;43:1394–1397. doi: 10.1111/j.1532-5415.1995.tb06620.x. PubMed PMID: 7490392. [DOI] [PubMed] [Google Scholar]
  • 23.Al Snih S, Raji MA, Markides KS, Ottenbacher KJ, Goodwin JS. Weight change and lower body disability in older Mexican Americans. J Am Geriatr Soc. 2005;53:1730–1737. doi: 10.1111/j.1532-5415.2005.53522.x. 10.1111/j.1532-5415.2005.53522.x PubMed PMCID 1941701; PMID 16181172. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Ritchie CS, Locher JL, Roth DL, McVie T, Sawyer P, Allman R. Unintentional weight loss predicts decline in activities of daily living function and life-space mobility over 4 years among communitydwelling older adults. J Gerontol A Biol Sci Med Sci. 2008;63:67–75. doi: 10.1093/gerona/63.1.67. 10.1093/gerona/63.1.67 PubMed PMID: 18245763. [DOI] [PubMed] [Google Scholar]
  • 25.Izawa S, Enoki H, Hirakawa Y, Iwata M, Hasegawa J, Iguchi A, Kuzuya M. The longitudinal change in anthropometric measurements and the association with physical function decline in Japanese community-dwelling frail elderly. Br J Nutr. 2010;103:289–294. doi: 10.1017/S0007114509991723. 10.1017/S0007114509991723 PubMed PMID: 19747412. [DOI] [PubMed] [Google Scholar]
  • 26.Feldblum I, German L, Castel H, et al. Characteristics of undernourished older medical patients and the identification of predictors for undernutrition status. Nutr J. 2007;2:37. doi: 10.1186/1475-2891-6-37. 10.1186/1475-2891-6-37 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Nykänen I, Lönnroos E, Kautiainen H, Sulkava R, Hartikainen S. Nutritional screening in a population-based cohort of community-dwelling older people. Eur J Public Health. 2013;23:405–409. doi: 10.1093/eurpub/cks026. 10.1093/eurpub/cks026 PubMed PMID: 22539629. [DOI] [PubMed] [Google Scholar]
  • 28.Okada K, Enoki H, Izawa S, Iguchi A, Kuzuya M. Association between masticatory performance and anthropometric measurements and nutritional status in the elderly. Geriatr Gerontol Int. 2010;10:56–63. doi: 10.1111/j.1447-0594.2009.00560.x. 10.1111/j.1447-0594.2009.00560.x PubMed PMID: 20102383. [DOI] [PubMed] [Google Scholar]
  • 29.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;13:855–861. doi: 10.1007/s12603-009-0242-3. 10.1007/s12603-009-0242-3 PubMed PMID: 19924344. [DOI] [PubMed] [Google Scholar]

Articles from The Journal of Nutrition, Health & Aging are provided here courtesy of Elsevier

RESOURCES