Perspective Using the Mini Nutritional Assessment
Matthias J. Kaiser, MD,
Ju¨rgen M. Bauer, MD,
Christiane Ra¨msch, Dipl.-Biomath. (FH),
wWolfgang Uter, MD,
wYves Guigoz, PhD,
zTommy Cederholm, MD, PhD,
§David R. Thomas, MD,
kPatricia S. Anthony, MS, RD,
zKaren E. Charlton, PhD,
#Marcello Maggio, MD, PhD,
Alan C. Tsai, PhD,
wwBruno Vellas, MD, PhD,
z zand Cornel C. Sieber, MD,
for the Mini Nutritional Assessment International Group
OBJECTIVES: To provide pooled data on the prevalence of malnutrition in elderly people as evaluated using the Mini Nutritional Assessment (MNA).
DESIGN: Retrospective pooled analysis of previously pub- lished datasets.
SETTING: Hospital, rehabilitation, nursing home, community.
PARTICIPANTS: Four thousand five hundred seven peo- ple (75.2% female) with a mean age of 82.3.
MEASUREMENTS: The prevalence of malnutrition in the combined database and in the four settings was examined.
RESULTS: Twenty-four data sets with information on full MNA classification from researchers from 12 countries were submitted. In the combined database, the prevalence of malnutrition was 22.8%, with considerable differences between the settings (rehabilitation, 50.5%; hospital, 38.7%; nursing home, 13.8%; community, 5.8%). In the combined database, the ‘‘at risk’’ group had a prevalence of 46.2%. Consequently, approximately two-thirds of study participants were at nutritional risk or malnourished.
CONCLUSION: The MNA has gained worldwide accep- tance and shows a high prevalence of malnutrition in differ- ent settings, except for the community. Because of its
specific geriatric focus, the MNA should be recommended as the basis for nutritional evaluation in older people. J Am Geriatr Soc 58:1734–1738, 2010.
Key words: malnutrition; undernutrition; Mini Nutri- tional Assessment; elderly; nutritional screening
M
alnutrition is one of the most relevant conditions that negatively affects the health of older people.1 The prevalence of malnutrition is generally high in older adults, but it is strongly dependent on the population studied. Pre- vious publications reported a prevalence of malnutrition ranging from nonexistent in healthy, community-living‘‘young old’’ persons2to as high as 57% in residents of long- term care institutions.3In the community, poor nutritional status is present before disease appears, as is risk of mal- nutrition.4,5Therefore, a systematic and structured nutri- tional screening is recommended for early detection of malnutrition to counteract the decline of health status caused by deficiencies in macro- and micronutrients. The criterion standard for the diagnosis of malnutrition has not been established, although for older adults, efforts have been made to create a screening tool that includes factors associated with physical, social, and cognitive domains of older individuals. Since the Mini Nutritional Assessment (MNA) was first published in 1994,6,7the MNA has been established as one of the most valid and most frequently used nutritional screening tools in older persons.8,9 The MNA is a recommended part of the comprehensive geriatric assessment and is an important research tool in geriatric medicine, with more than 400 scientific papers published about it.10In addition, the MNA may be useful for teaching purposes in the context of nutritional care in older per- sons.11Unlike many of the existing nutrition screening tools
Address correspondence to Matthias J. Kaiser, Institute for Biomedicine of Aging, Friedrich-Alexander University Erlangen-Nu¨rnberg, Heimerichstrasse 58, 90419 Nuremberg, Germany. E-mail: dr-kaiser@web.de
DOI: 10.1111/j.1532-5415.2010.03016.x
From theInstitute for Biomedicine of Aging andwDepartment of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander University Erlangen-Nu¨rnberg, Erlangen, Germany;zNestle´ Nutrition/HealthCare Nu- trition, Gland, Switzerland;§Clinical Nutrition and Metabolism, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden;
kDivision of Geriatric Medicine, Saint Louis University Health Sciences Center, St. Louis, Missouri;#School of Health Sciences, Faculty of Health and Behavioral Sciences, University of Wollongong, Wollongong, Australia;
Department of Internal Medicine and Biomedical Sciences, Section of Geriatrics, University Hospital of Parma, Parma, Italy;wwGraduate Institute of Long-Term Care, Department of Healthcare Administration, Asia Uni- versity, Taiwan, ROC; andzzCHU Toulouse, Inserm U558, Department of Geriatric Medicine, Toulouse, France.
JAGS 58:1734–1738, 2010 r2010, Copyright the Authors
Journal compilation r 2010, The American Geriatrics Society 0002-8614/10/$15.00
available, the MNA was specifically designed and validated for use in older persons. It has been shown to perform well in diverse settings and across populations.12The aim of the present study was to pool existing international data on the MNA from high-quality trials (published in peer-reviewed journals) in one large database and to provide information on the prevalence of malnutrition in older persons on a larger scale. All settings relevant for the care of older per- sons were included: community, nursing homes, acute care hospitals, and rehabilitation units.
METHODS
Data Collection and Database Setup
The present study is a retrospective pooled analysis. To identify eligible studies, a literature search was performed on PubMed. Because of ongoing changes in population de- mographics, studies published before 2000 were not in- cluded. Studies were selected if the MNA (preferably full form) was used and a clear definition of the setting was provided. Authors were contacted in writing and asked to submit their original data sets. All data sets were transmit- ted electronically in a structured format. Occasionally, data sets had to be revised before transmission to increase com- prehensibility (e.g., translation into English) and to meet advisory board or ethics committee regulations on data transfer (e.g., deletion of patient names). Two members of the study group (RC and KMJ) reviewed each data set and appended it to the database. Setting allocation was made on the basis of setting description provided by the respective publications. In some cases, authors were contacted and asked to describe their patient collective to enable an ad- equate allocation. Only data from study participants aged 65 and older were entered into the database.
Ethics Approval and Statistical Analysis
The ethics committee of the University of Erlangen- Nuremberg approved the conceptual design. Statistical analysis was based on the combined database and on sub- sets of data, stratified for settings. Statistical analysis was performed using SAS (version 9.2, SAS Institute, Cary, NC).
RESULTS
Database Content
Investigators from all five continents agreed to participate and submitted 27 datasets including information on more than 6,000 study participants aged 65 and older. Because of the unavailability of the full MNA classification in several data- sets, the effective sample size used in the following analyses was 4,507 (24 study files from 12 countries). This also in- cluded data from two theses (otherwise unpublished) and one previously unpublished study file that were acquired through personal contacts. Geographically, the data received cover study participants from all five continents, with a stronger focus on European populations (80.6% of study data).
The combined database provided information on 1,384 hospitalized patients from Belgium,13 Switzerland,14 Ger- many,15 Italy (unpublished data, 16), and Sweden.17 Study files from 1,586 nursing home residents came from Switzer- land,18Germany,19–22Spain,23France,24the Netherlands,25 the United States,26and South Africa.27Information on 964
community-dwelling study participants was available from Switzerland,28 France,29 Japan,30 Sweden,31 and South Africa.27Data on 345 patients from geriatric rehabilitation was available from Australia,32 Italy,33 and the United States.34 Two hundred twenty-eight cases from Japan re- mained unclassified with regard to setting but were included in the prevalence analysis of the combined sample.35 Demographic Characteristics and Prevalence of Malnutrition
The basic characteristics of the study population stratified for setting and sex are given in Table 1; 75.2% of study participants were female. The mean age of the study pop- ulation was 82.3 7.5. Women were older than men (82.7 vs 81.3). More than 60% of the study population was aged 80 and older. Age distribution differed between the settings.
Nursing home residents were oldest, particularly women.
The youngest population was the community-dwelling group. The differences in age distribution between acute care and geriatric rehabilitation were minor. The setting- specific distribution of MNA categories (well nourished, at risk, malnourished) in the combined database and the four examined settings is given in Figure 1. In the combined da- tabase, more than two-thirds of the study participants were classified as at risk of malnutrition (46.2%) or overtly mal- nourished (22.8%). The proportion of well-nourished older adults was particularly low in convalescent older persons in geriatric rehabilitation (8.5%) and in hospitalized elderly patients (14.0%). In those two settings, approximately 90%
of study participants were malnourished or at risk of devel- oping malnutrition. In the nursing home setting, only 32.9%
of residents were well nourished. Although the level of mal- nutrition was low in the community setting, 31.9% of com- munity-living elderly persons were at risk of malnutrition.
DISCUSSION
The database used for the present analysis was compiled from 24 data sets provided by researchers from all five continents. This is the largest database of information on nutrition screening in older adults from a range of residen- tial settings. The information provides insight into the prevalence of malnutrition using the well-validated MNA tool8,9,12 in older populations with various degrees of de- pendence, from older persons living autonomously in the community to patients in geriatric hospitals and residents of long-term care institutions.
Overt malnutrition according to the MNA affected nearly one-quarter of the examined population, with the lowest prevalence reported in community-dwelling older adults and the highest prevalence in rehabilitation units. In the total sample, as well as in two out of four settings (hos- pital and nursing home), the largest proportion of older adults was classified as being at nutritional risk. Nutritional status deteriorates as dependency and care needs grow, fol- lowing a sequence from community living to nursing home and hospital. Similar differences in the prevalence of malnu- trition across settings have been described previously.9,12,36 Nevertheless, percentages given in original research papers sometimes differ substantially from one another.8,12 Here, pooled analyses help to smooth results to gain a clearer pic- ture on a greater scale. The MNA may be regarded as a
particularly suitable tool for diagnosis of malnutrition be- cause it offers a multidimensional approach to elderly people by selection of items that correspond well with relevant fea- tures of the target population (e.g., dementia, mobility, mode of feeding, pressure sores). Although tools such as the Mal- nutrition Universal Screening Tool (MUST)37and the Nu- tritional Risk Screening 2002 (NRS)38are also often used to assess nutritional status in elderly persons, it is the specific focus of the MNA that has enhanced acceptance and appli- cation of this tool in geriatric medicine.10,39 The MUST seems limited to use as a brief screening tool, without proper representation of change in older people’s body shape. The body mass index (BMI) cutoff in the MUST is a low 18.5 kg/
m2, which many experts regard as too low. In the MNA, alternatively, subjects begin to lose points for BMI values below 23.0 kg/m2. The NRS was developed and validated on adults, but not specifically older adults, in the acute care setting. The NRS indicates the greater risk of elderly persons of being malnourished by adding 1 point to the risk score if subjects are aged 70 and older, but by strongly focusing on acute disease, the NRS seems to be less appropriate for com- munity-dwelling older people and nursing home residents because their health is often much stabler than that of their counterparts in acute care.
There are a number of limitations to the present study.
Despite the large sample size, results may not be generalized because of the heterogenous and convenience nature of the database. The four settingsFhospital, nursing home, reha- bilitation, communityFare not evenly represented in the combined database, which is dominated by patients in acute care and nursing home residents. Particularly the sample size from the rehabilitation is smaller than those from the other settings. Ethnic heterogeneity also warrants consid- eration. Although the present study was designed to include a large number of data sets from around the world, its main focus was on European populations, whereas populations from Australia, Asia, Africa, and the United States consti- tuted only a minority of the total sample size. Therefore, although it indicates the general magnitude of the problem (malnutrition in older people), the results from the analyses are not to be regarded as representative with regard to a certain country or continent or the world.
In the process of allocation of collected data to one of the aforementioned settings, the authors applied great care, but in some cases, the inclusion of the respective data was possible only after consultation with the respective authors to clarify characteristics of the study population with regard to disease status, therapeutic measures, and duration of stay. Nevertheless, the characteristics of rehabilitation, long-term care, and acute care setting may vary between countries and continents. Therefore, misinterpretations leading to wrong setting allocation cannot be completely excluded.
CONCLUSION
The MNA has been established as a nutritional screening tool for use in various care settings for older persons and as such has been used globally as a component of comprehen- sive geriatric assessment. According to MNA classification, the proportion of older people who are overtly malnour- ished or at risk of becoming malnourished is high in all Table1.BasicCharacteristicsoftheStudyPopulation(N54,507) Characteristic
HospitalNursingHomeCommunityRehabilitationCombinedDatabase Men n5385Women n5943Men n5397Women n51,189Men n5116Women n5848Men n599Women n5246Men n51,063Women n53,388 Age,meanSD81.27.182.96.981.38.385.17.479.37.279.36.680.27.682.37.581.37.782.77.4 MiniNutritionalAssessmentscore,median(IQR)17.5(8.5)18.5(8.0)22.0(6.0)22.0(5.5)22.8(5.3)25.5(5.0)17.5(7.5)16.0(8.0)20.5(7.5)21.5(7.5) Malnourished,%45.236.014.413.59.55.340.453.328.020.8 Atrisk,%41.049.952.453.752.629.052.539.448.945.6 Wellnourished,%13.814.133.332.737.965.77.17.323.133.6 Bodymassindex,kg/m2,meanSDn53,34823.84.324.45.625.15.126.35.723.14.025.66.424.25.724.66.224.14.825.45.9 Albumin,g/L,meanSD,n51,55036.16.436.46.438.79.842.38.739.03.638.33.432.95.033.65.136.57.237.87.1 C-reactiveprotein,mg/dL,median(IQR),n51,4252.1(5.4)1.6(4.5)0.8(1.3)0.4(1.0)FFFF1.9(5.2)1.4(4.0) Tricepsskinfold,mm,meanSD,n51,91311.06.114.47.914.96.218.88.020.511.428.59.88.34.711.25.313.07.217.48.9 228caseswereunclassifiableregardingsetting;56caseswereunclassifiableregardingsex. SD5standarddeviation;IQR5interquartilerange.
examined settings except for the community. Even though no tool, neither the MNA nor any other tool in use, can be regarded as the criterion standard for nutritional screening of older persons, MNA items specifically address relevant features of the aging population that allow for early detec- tion of malnutrition risk and enable assessors to take im- mediate action. Therefore, performing the MNA as a screening test is strongly recommended as the basis for nu- tritional evaluation.
ACKNOWLEDGMENTS
The authors wish to acknowledge all colleagues from the MNA International Group who submitted original data and participated in discussions on the project’s progress.
The authors are indebted to Marcello Maggio, who pro- vided a previously unpublished dataset. Part of this work was presented as a poster and oral communication at the 2009 International Association of Gerontology and Geri- atrics Congress, Paris, France, and the 2009 European So- ciety for Clinical Nutrition and Metabolism Congress, Vienna, Austria.
Conflict of Interest: All authors are members of the MNA International Group and attended a workshop in Lausanne, Switzerland, in October 2008 that was fully funded by Nestle´. Kaiser has been supported by a research grant from Nestle´ Nutrition, Vevey, Switzerland. Bauer is a consultant to Nutricia and has received research grants from Nestle´ and Nutricia. He has received honoraria for giving talks in collaboration with Nestle´, Abbott, and Fresenius. Sieber and Vellas are consultants to Nestle´ and have received honoraria for giving talks in collaboration with Nestle´. Anthony is an employee of Nestec Ltd. Guigoz is an external advisor to Nestec Ltd.
The study has been supported through a research grant by Nestle´ Nutrition (Vevey, Switzerland) to Matthias J.
Kaiser.
Author Contributions: Matthias J. Kaiser: conception, data collection, analysis, and interpretation; preparation of manuscript. Ju¨rgen M. Bauer and Cornel C. Sieber: con- ception, data collection and interpretation, preparation of
manuscript. Christiane Ra¨msch and Wolfgang Uter: data analysis and interpretation, preparation of manuscript.
Yves Guigoz: conception, data analysis and interpretation, preparation of manuscript. Tommy Cederholm and David R. Thomas: conception, data interpretation, preparation of manuscript. Patricia S. Anthony: conception, data collec- tion and interpretation. Karen E. Charlton: data interpre- tation, preparation of manuscript. Marcello Maggio:
conception, data interpretation. Alan C. Tsai: data inter- pretation. Bruno Vellas: conception, data interpretation.
Sponsor’s Role: None.
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