at SciVerse ScienceDirect

Clinical Nutrition 32 (2013) 438e443

Contents lists available

Clinical Nutrition

journal homepage: http: / /www.elsevier .com/locate/clnu

Original article

Malnutrition and associated factors in nursing home residents: A cross-sectional,multi-centre study

Mathieu Verbrugghe a,*, Dimitri Beeckman a,b,c, Ann Van Hecke a,d, Katrien Vanderwee a,Koen Van Herck e, Els Clays e, Ilse Bocquaert a, Hanne Derycke a, Bart Geurden f, Sofie Verhaeghe a

aNursing Science, Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, UZ Blok A, De Pintelaan 185, 9000 Ghent, Belgiumb Florence Nightingale School of Nursing & Midwifery, King’s College London, London, UKcDepartment of Bachelor in Nursing, Artevelde University College Ghent, Ghent, Belgiumd Staff member Nursing Science, University Hospital Ghent, Ghent, Belgiume Epidemiology and Preventive Medicine, Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, Ghent, BelgiumfNursing and Midwifery, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium

a r t i c l e i n f o

Article history:Received 3 February 2012Accepted 19 September 2012

Keywords:MalnutritionElderlyNursing homeAssociated factorsPrevalence

* Corresponding author. Tel.: þ32 9 3320588.E-mail addresses: Mathieu.Verbrugghe@uge

Dimitri.Beeckman@ugent.be (D. Beeckman), Ann.VHecke), Koen.VanHerck@ugent.be (K. Van Herck), EIlse.Bocquaert@uzgent.be (I. Bocquaert), Hanne.Derybart.geurden@ua.ac.be (B. Geurden), Sofie.Verhaeghe@

0261-5614/$ e see front matter � 2012 Elsevier Ltd ahttp://dx.doi.org/10.1016/j.clnu.2012.09.008

s u m m a r y

Background & aims: Malnutrition is a common problem in the elderly living in nursing homes. A clearunderstanding of associated factors is missing. The aim of this study was to evaluate prevalence ofmalnutrition and to determine factors independently associated with malnutrition in this setting.Methods: A cross-sectional, multi-centre study was conducted in 23 nursing homes in Flanders, Belgium.The nutritional status was assessed using the Mini Nutritional Assessment (MNA). Data on possibleassociated factors were collected using validated scales.Results: The study included 1188 elderly residents; 38.7% were at risk for malnutrition and 19.4% weremalnourished. The presence of a wound/pressure ulcer, a recent hospitalization (<3 months ago), beinginvolved in a tailored nutritional intervention, and suffering from a lower cognitive state were signifi-cantly associated with malnutrition. Receiving additional meals provided by family members wasnegatively associated with malnutrition.Conclusion: Malnutrition is a prevalent problem in nursing homes in Flanders. Systematic screening andwell-defined tailored interventions should be further developed and evaluated in this population at risk.

� 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

1. Introduction

Malnutrition is a prevalent problem in the elderly.1 Malnutritioncan be a complication resulting from a disease or it can be anindependent disease.

Multiple definitions are used to definemalnutrition.2,3 All include(1) insufficient dietary intake of essential nutritional elements and(2) protein-energymalnutrition (PEM), which can be both a primary(resulting from an insufficient food intake) or a secondary problem(resulting from a disease).4 However, a universally accepted defini-tion for malnutrition does not exist.3,5 Elia in Stratton et al. definesundernutrition as “a state of nutrition inwhich adeficiencyof energy,protein and other nutrients causes adverse effects on tissue or body

nt.be (M. Verbrugghe),anHecke@ugent.be (A. Vanls.Clays@ugent.be (E. Clays),cke@ugent.be (H. Derycke),ugent.be (S. Verhaeghe).

nd European Society for Clinical N

form (body shape, size and composition), function or clinicaloutcomes”.3 This current study will focus on undernutrition;however, the terms ‘malnutrition’ and ‘undernutrition’ will be usedinterchangeably analogous to the literature.

The Malnutrition Universal Screening Tool (MUST), the Nutri-tional Risk Screening (NRS-2002), and the Mini-NutritionalAssessment (MNA) are the most commonly used screening toolsfor malnutrition. In the 2002 guidelines for nutritional screening bythe European Society for Clinical Nutrition and Metabolism(ESPEN), the MNA is recommended to screen patients for malnu-trition in elderly in home-care programs, nursing homes andhospitals.6 The MNA includes physical and mental aspects affectingthe nutritional status. According to the ESPEN guidelines, the MNAis more likely to identify risk for malnutrition at an early stage.6 TheMNA contains anthropometric measurements, type of accommo-dation, medication, the presence of a wound/pressure ulcer,number of meals, food and fluid intake, autonomy of feeding, andself-perception of health and nutrition. A brief version of the MNAwas developed by Rubenstein and colleagues in 2001 (Mini Nutri-tional Assessment e Short Form (MNA-SF)).7 The MNA-SF includes

utrition and Metabolism. All rights reserved.

M. Verbrugghe et al. / Clinical Nutrition 32 (2013) 438e443 439

6 items: appetite, weight loss, mobility, psychological stress oracute disease, neuropsychological diseases, and Body Mass Index(BMI). If the MNA-SF considers a person at risk for malnutrition, thefull MNA needs to be completed.

Malnutrition has a negative impact on functional status,psychosocial well-being, and the quality of life of the elderly2,8 andis reported as a risk factor for mortality.2,9,10 Malnutrition may leadto an extended hospital stay and increased costs for patients,healthcare facilities and broader society.11,12

Prevalence figures of malnutrition in elderly are ambiguous andvary between 0 and 78%.12e17 This variety is mainly due to theinclusion of different settings, age categories, underlying disease,screening instruments, and, even more important, the definition ofmalnutrition. A review by Guigoz reported that 23% [1e74] of thehospitalized elderly and 21% [5e71] of the institutionalized elderlysuffer from malnutrition when the MNA is used.13

In 2010, a cross-sectional study in 2329 patients in 90 elderlycare wards in Belgian hospitals was conducted to (1) gain insightinto the prevalence of malnutrition and (2) to identify factorsassociatedwithmalnutrition.18 TheMNAwas used to assess the riskfor malnutrition in the included patients. The authors concludedthat 43% of the included patients were at risk for malnutrition, and33% of the patients were malnourished.

In 2009, a cross-sectional study was used to report on theprevalence of malnutrition in Belgian nursing homes.19 This studyincluded 5334 nursing home residents. The MNA-SF was used andpossible associated factors were not studied. The authors reportedthat 58.7% of the elderly were considered at risk for malnutrition.The results were confirmed by other international studies in thispopulation.20e22

Several factors are thought to be associated with malnutrition.These factors include immobility, dementia, depression, difficultiesin eating and swallowing, and the presence of a wound/pressureulcer.21,23e25Malnutrition in elderly is also associatedwith the loss ofLean Body Mass and with a range of other factors which reduce theintake of food and fluids.26,27 Furthermore, vulnerability for malnu-trition increaseswith age andweakening of functional capabilities.25

In a study by Vanderwee and colleagues, swallowing difficultiesand a reduced ability to taste were found to be associated withmalnutrition in elderly admitted to a hospital.18 Furthermore, theauthors concluded that patients admitted from a nursing homewere significantly more likely to be malnourished than residentsadmitted from a service flat.

In nursing home residents, malnutrition was found to be asso-ciated with impaired functioning, swallowing difficulties,dementia, eating dependency, the presence of a wound/pressureulcer, gender, and poor oral intake.21,28 Thus far, little research isavailable on elderly in nursing homes. To our knowledge, extensivestudies identifying factors associated with malnutrition in Belgiannursing homes are missing.

2. Aim

The aims of this study were to report on (1) the prevalence ofmalnutrition and on (2) associated factors for malnutrition inelderly living in Belgian nursing homes.

3. Methods

3.1. Design

A cross-sectional, multi-centre study was performed. Theoutcome measures were the prevalence of malnutrition and theindependent associated factors for malnutrition.

3.2. Setting and sample

This study was conducted in nursing homes in Flanders(Belgium) and included elderly residents. A stratified randomsample was taken from a total of 694 nursing homes in Flanders.The sample was selected based on geographical region, number ofbeds, and funding characteristics (government or privately funded).In total, 55 nursing homes were invited to participate; 23 institu-tions agreed to participate. Reasons for non-participation werea recent change in- or absence of managing board, high workload,relocation, the absence of a financial compensation and a lack ofstaff.

In each participating nursing home, a random sample of resi-dents was selected to participate. The random sample includedpatients born on a day with an odd number. Inclusion criteria wereset as having completed the entire questionnaire and being �55years of age. In total, 1188 residents were included in this study.

3.3. Instruments

A set of validated instruments was used to collect data ondemographic characteristics, nutritional state, problems related tofood intake, swallowing mechanism, energy and appetite, cognitivestate, and functional state.

3.3.1. Demographic characteristicsA questionnaire to collect demographic data was developed

using a double type Delphi procedure involving researchers witha high level of expertise in the area of elderly care and/or nutrition.Data on (1) demographic characteristics (age, sex, weight, length ofstay, recent hospitalization), (2) physiological characteristics(medication, comorbidity), (3) nutritional status (diet, nutritionalintervention) and (4) eating habits (nature and frequency ofassistance during meals, use of supplements, meals brought byfamily) were collected.

3.3.2. Nutritional stateThe two-step Mini Nutritional Assessment tool (MNA-SF & MNA)

wasused toevaluate thenutritional state of the elderly. TheMNA is anextensively validated instrument to identify the elderly who have orare at risk formalnutrition.6,13,29e31 The instrument is recommendedin both national and international guidelines and by organizationssuch as National Food and Health Plan Belgium and ESPEN.6,32

Research showed that the MNA-SF is highly correlated with theMNA.7,33 Themaximum score of theMNA-SF is 14. Participants witha score�12 were considered to bewell-nourished. A score<12 wasconsidered indicative for the risk for undernutrition, in this case,the full MNA had to be completed.

Participants with a total score <17 on the full MNA, wereconsidered to be malnourished. Residents having a score between17 and 23.5 were defined as being at risk for malnutrition. Partic-ipants with a score�24were considered as beingwell-nourished.34

3.3.3. Problems related to food intake, swallowing, energy andappetite

The Minimal Eating Observation Form e Version II (MEOF-II)was used to determine problems related to food intake, swallowing,energy, and appetite.27 The MEOF-II includes three elements: (1)ingestion, (2) deglutition, and (3) energy. Ingestion includes (1) themanipulation of food on the plate, (2) the transport of food to themouth, and (3) the sitting posture. Deglutition includes (1) theability to chew, (2) the manipulation of food in the mouth, and (3)swallowing. Energy includes (1) alertness, (2) appetite, and (3)eating <3/4 of the food being served.27 The instrument has beenextensively validated.27

M. Verbrugghe et al. / Clinical Nutrition 32 (2013) 438e443440

3.3.4. Cognitive statusThe Mini Mental Status Examination (MMSE) was used to assess

the cognitive status of the elderly. The MMSE focuses on theorientation in time and space, direct memory (uptake), attention,calculation skills, recall, and language. The MMSE is widely usedand studied in terms of validity and reliability.35,36 The maximumMMSE score is 30; a score <24 indicates a cognitive disorder.

3.3.5. Functional statusThe Katz scale was used to assess functional status of the resi-

dents. The scale focuses on functional dependency for washing,dressing, the ability to go to the toilet, transfer/relocation, conti-nence, eating and orientation in time and space. This scale is rec-ommended by the Belgian National Institute for Health andDisability. Each item was scored on a 4-point Likert scale, with 1(fully independent) to 4 (fully dependent). The maximum scorewas 32.37

3.4. Data collection procedure

Data were collected by the nursing staff on the wards betweenMay 15th and July 31st, 2010. Nurses were educated by theresearchers prior to the study to standardize the data collection. Atleast one delegate from each nursing homes attended a trainingsession. During this session, information about the aims andprocedure and the instruments for data collection was provided.Patient cases were used to support the training and to increase thereliability of the data collection. The delegates received an educa-tional material to allow them to share the information with allmembers of the nursing staff.

3.5. Ethical consideration

The study procedure was approved by the ethics committee ofthe Université Catholique de Louvain (B40320108632). All partici-pants gave informed consent to participate in this study. All datawere encoded and kept confidentially.

3.6. Statistical analyses

Descriptive data were presented as means and standard devia-tions. The dependent variable nutritional status (MNA) wasdichotomized (malnourished versus at risk for malnutrition/well-nourished) to determine independent associations betweenmalnutrition and other factors. Odds ratios and related 95% confi-dence interval were calculated for each variable using a univariatelogistic regression analysis. Continuous variables were normallydistributed.

Table 1Characteristics of the elderly according to their nutritional status (MNA).

Well-nourished (n ¼ 413) At risk for malnutriti

Mean (SD) Mean (SD)

Age (years) 83.3 (7.49) 84.8 (7.92)BMI (kg/m2) 27.5 (4.71) 23.7 (5.05)Length of stay (years) 3.3 (3.03) 3.6 (3.59)MNA-SF scores 12.8 (0.92) 9.4 (1.33)MNA-scores e 20.0 (1.79)MMSE-scores 21.2 (6.65) 16.4 (7.51)Katz-scores 16.4 (5.66) 21.2 (5.57)Gender % (n) % (n)Male 27.6 (113) 21.2 (79)Female 72.4 (296) 78.8 (293)

Recently hospitalized 4.4 (18) 12.8 (48)

Variables with a value p <0.20 were simultaneously entered ina multivariate logistic regression analysis to evaluate the inde-pendency of the observed associations. A correlation analysis wasperformed to test for multicollinearity between the independentvariables. Spearmans’ r was set at <0.60 to be included in themodel. Multicollinearity was observed between (1) functionalrestriction and dependency (Katz), (2) eating (Katz) and ingestion(MEOF-II), (3) orientation in place (Katz) and ingestion (MEOF-II),and (4) the MMSE-score and orientation in time and place (Katz).Results were considered significant if the two-tailed p-value was<0.05. Statistical analyses were performed using SPSS 18.0 (SPSSInc., Chicago, IL, USA).

Additionally, analyses were made without dichotomizing theMNA categories. Well-nourished patients (without patients at riskfor malnutrition) versus malnourished patients were analysed witha multivariate logistic analysis.

4. Results

4.1. Demographic data

The sample included 1188 residents; 75.9% (n ¼ 886) beingfemale. The mean agewas 84.3 years (SD¼ 7.70) and the mean BMIwas 24.4 kg/m2 (SD ¼ 5.29). The mean length of stay was 3.6 years(SD ¼ 3.43) and 11.1% of the sample had recently been admitted toa hospital (<3 months ago). The most frequently reported under-lying diseases were: cardio-vascular diseases (19.9%), diabetes(19.7%), swallowing problems (11.8%), cancer (9.9%), cerebrovas-cular accidents (9.1%), chronic obstructive pulmonary disease(8.8%), and the presence of a wound/pressure ulcer (4.5%).

Approximately half of the residents were found to be fullydependent for washing (51.5%) and dressing (57.4%). The meanMMSE score was 16.6 (SD ¼ 8.32); 75.6% of the residents hada cognitive problem (MMSE score < 24).

4.2. Prevalence of malnutrition

In total, one in five (19.4%) of the residents were found to bemalnourished, 38.7% were at risk for malnutrition and 41.9% werewell-nourished. An overview of general characteristics and thenutritional status of the residents according to the MNA is pre-sented in Table 1.

4.3. Independently associated factors

The univariate analysis (see Table 2) showed that a reducedcognitive state, a recent hospitalization, having an oncologicalproblem, swallowing problems, the presence of a wound/pressureulcer, receiving a nutritional intervention such as precut food, were

on (n ¼ 381) Malnourished (n ¼ 191) P-value Test

Mean (SD)

84.6 (7.65) <0.05 ANOVA20.2 (3.58) <0.01 ANOVA3.8 (4.00) 0.30 ANOVA5.9 (1.88) <0.01 ANOVA13.3 (2.42) <0.01 ANOVA11.7 (8.08) <0.01 ANOVA26.3 (4.82) <0.01 ANOVA% (n) 0.07 Chi-square21.4 (40)78.6 (147)20.2 (38) <0.01 Chi-square

Table 2Univariate logistic binary regression with malnutrition (MNA < 17) as dependentvariable and potential predictors of malnutrition.

Variable OR [95% CI] P-value

Gendera 1.20 [0.82e1.76] 0.36Recently hospitalized (<3 months ago)b 2.75 [1.77e4.25] <0.05MMSE 0.90 [0.88e0.92] <0.01Diabetes mellitusb 0.58 [0.37e0.91] <0.05COPDb 1.45 [02.87e2.42] 0.15Oncological problemb 1.62 [1.00e2.62] <0.05Swallowing problemsb 3.43 [2.26e5.22] <0.05Cerebrovascular accidentb 1.36 [0.82e2.26] 0.24Cardio-vascular diseaseb 0.84 [0.56e1.25] 0.39Presence of a wound/Pressure ulcerb 4.74 [2.48e9.08] <0.05Medication intake/dayc

1e5 0.90 [0.18e4.55] 0.906e10 0.65 [0.13e3.28] 0.65>10 0.49 [0.09e2.61] 0.41

Receiving a nutritional interventionb,d 8.30 [4.73e14.57] <0.05Dietb,e 0.46 [0.30e0.71] <0.05Additional meals provided by familyb 0.67 [0.45e1.00] <0.05MEOF-IIIngestionf

1 problem 4.47 [2.44e8.20] <0.052 problems 8.05 [5.01e12.93] <0.053 problems 30.97 [18.70e51.31] <0.05

Deglutitionf

1 problem 3.27 [2.07e5.18] <0.052 problems 6.11 [3.68e10.14] <0.053 problems 28.57 [14.97e54.51] <0.05

Energyf

1 problem 3.10 [1.88e5.09] <0.052 problems 10.96 [6.84e17.56] <0.053 problems 20.68 [12.06e35.46] <0.05

OR ¼ odds ratio; CI ¼ confidence interval; COPD ¼ chronic obstructive pulmonarydisease; SD ¼ standard deviation; age (years).

a Reference category is male.b Reference category is No.c Reference category is 0 medicines/day.d Nutritional intervention ¼ nutritional supplement(s), adjusted consistency,

flavour enhancers, concentrated food, tube feeding, other.e Diet ¼ diabetic diet, salt diet, dialyses diet, cholesterol diet, gastro-intestinal

sparing diet, liver sparing diet, other.f Reference category is no problems.

Table 3Multivariate binary logistic regression with malnutrition (MNA < 17) as dependentvariable and potential predictors of malnutrition as independent variables.

Variable B (SE) WaldChi-square(c2)

OR [95% CI] P-value

Age 0.02 (0.02) 1.75 1.02 [0.99e1.06] 0.19Gendera 0.38 (0.33) 1.36 1.46 [0.77e2.77] 0.24Recently hospitalizedb 1.14 (0.37) 9.74 3.12 [1.53e6.37] <0.01MMSE �0.054 (0.02) 10.41 0.95 [0.92e0.98] <0.01Diabetes mellitusb �0.28 (0.45) 0.40 1.33 [0.55e3.20] 0.53COPDb 0.052 (0.43) 0.02 0.95 [0.41e2.20] 0.90Oncological problemb 0.05 (0.42) 0.01 1.05 [0.46e2.39] 0.91Swallowing problemsb 0.32 (0.43) 0.56 0.73 [0.31e1.69] 0.46Presence of a wound/

pressure ulcerb1.61 (0.56) 8.44 5.02 [1.69e14.92] <0.01

Receiving nutritionalinterventionb

1.11 (0.46) 5.96 3.04 [1.25e7.43] <0.05

Dietb �0.46 (0.44) 1.12 0.63 [0.27e1.48] 0.29Additional meals

provided by familyb�0.78 (0.35) 4.92 0.46 [0.23e0.91] <0.05

MEOF-IIIngestion <0.01No problemsc 23.54 11 problem 1.00 (0.43) 5.49 2.71 [1.18e6.25] <0.052 problems 1.23 (0.35) 12.73 3.43 [1.74e6.76] <0.013 problems 1.93 (0.42) 20.62 6.85 [2.99e15.73] <0.01

Deglutition 0.09No problemsc 6.61 11 problem 0.24 (0.36) 0.45 1.27 [0.63e2.56] 0.502 problems 0.21 (0.45) 0.22 1.23 [0.51e2.99] 0.643 problems 1.38 (0.54) 6.47 3.98 [1.37e11.53] <0.05

Energy <0.01No problemsc 41.48 11 problem 0.50 (0.36) 1.91 1.65 [0.81e3.38] 0.172 problems 1.77 (0.34) 26.39 5.85 [2.98e11.47] <0.013 problems 2.17 (0.42) 26.97 8.77 [3.86e19.90] <0.01

B ¼ regression coefficient; SE ¼ standard error; OR ¼ odds ratio; CI ¼ confidenceinterval; COPD ¼ chronic obstructive pulmonary disease.

a Reference category is male.b Reference category is No.c Reference category.

M. Verbrugghe et al. / Clinical Nutrition 32 (2013) 438e443 441

independently associated with a significantly higher prevalence ofmalnutrition. Malnutrition was positively associated with thenumber of problems related to ingestion, deglutition and energy(MEOF-II). Diabetic patients on a diet or residents receiving addi-tional meals provided by their family, were negatively associatedwith malnutrition.

The multivariate model (see Table 3) showed that residents whowere recently hospitalized, had a wound/pressure ulcer, or receiveda nutritional interventionwere associatedwith a significantly higherprevalence of malnutrition. A higher prevalence of malnutritionwaspositively associated with the number of problems related to inges-tion and energy (MEOF-II). A lower cognitive status was associatedwith malnutrition. Residents receiving additional meals provided bytheir family, were negatively associated with malnutrition.

Considering well-nourished patients (without patients at riskfor malnutrition) versus malnourished patients, the multivariatemodel showed similar results. Only one variable, followinga specific diet (diabetic diet, salt diet, dialyses diet, cholesterol diet,gastro-intestinal sparing diet, liver sparing diet, and other) wasadditionally found to be significantly associated with malnutrition(p < 0.05).

5. Discussion

The study revealed that approximately one in five residents(19.4%) was malnourished and two in five (38.7%) were at risk for

malnutrition. Several factors were found to be independentlyassociated with malnutrition in nursing home residents.

The current results support previous figures, indicating thatmalnutrition is a substantial problem in nursing home resi-dents.20,33 Furthermore, Guigoz concluded in a review that insti-tutionalized elderly were particularly vulnerable to becomemalnourished; with 21% suffering malnutrition and 51% being atrisk for malnutrition.13 Van Gossum & Vandewoude found that58.7% of the nursing home residents in Belgium were at risk formalnutrition.19 A few differences between the current study andthe Van Gossum & Vandewoude study need to be addressed: in thelatter participants <70 years of age were excluded while in thisstudy participants <55 were excluded. In the Van Gossum & Van-dewoude study, the aim was measuring the risk for malnutritionusing the MNA-SF. In this study the full MNA was used to assessmalnutrition.

In our study, four major factors were found to be independentlyassociated with malnutrition in nursing homes: being recentlyhospitalized (<3 months ago), the presence of a wound/pressureulcer, receiving a specific nutritional intervention, and a lowercognitive status of the resident.

The association between malnutrition and recent hospitaliza-tion was also found in several other studies.15,18 Being malnour-ished and/or being at risk for malnutritionmight have been alreadypresent at the time of hospitalization. The design of this study didnot allow to focus on this. Elderly admitted to hospital froma nursing home are generally highly dependent in their

M. Verbrugghe et al. / Clinical Nutrition 32 (2013) 438e443442

functioning. Previous studies indicated that vulnerability formalnutrition increases with weakening of functional capabil-ities.21,25 This association was also supported in the present study;risk for malnutrition was associated with the number of problemswith ingestion, deglutition and energy (MEOF-II). It is reasonable toaccept that hospitalization and the indications for hospitalizationsuch as the kind of disease, may also accelerate the process ofmalnutrition. This association needs further attention in futurestudies and in practice. More attention should be paid to residentsrecently hospitalized.

There was a significant association between the presence ofa wound/pressure ulcer and being malnourished. Several otherstudies support the existence of a correlation.21,38e40 Factors suchas low nutritional intake, low BMI (<18.5) and poor oral food intakewere found to be associated with the presence of pressureulcers.41,42 Malnutrition has a detrimental effect on the healing ofpressure ulcers due to reduced nutrient availability for tissuemaintenance and repair.3,43 Pressure ulcers are known to be one ofthe most expensive and physically debilitating complications.44

Therefore, nutritional interventions should be included in eachpressure ulcer prevention- and treatment plan. The National Pres-sure Ulcer Advisory Panel and the European Pressure Ulcer Advi-sory Panel (NPUAP & EPUAP), emphasize the importance ofnutritional status screening in individuals at risk for pressure ulcersand to provide specialized individual nutritional support andfollow-up for elderly at risk.45

There was a significant association between malnutrition andreceiving a tailored nutritional intervention. This association seemsrational as a tailored nutritional intervention is often due toa nutritional problem or can be an sign of increased awareness ofhealthcare providers for this problem. This was supported by theresults in this study, given that almost all residents consideredbeing malnourished, received a nutritional intervention (93%).Despite this awareness, malnutrition still remains a seriousproblem. Evidence-based strategies are needed and should beimplemented in a sound way. Education of staff is most likely to beone of the most important components of such an implementationprocess. However, while determining the aim of an intervention,the caregiver should also take the nutritional history of the residentinto account. The goal of the caregiver might be maintainingnutritional status or increasing nutritional intake. However, theperspective and the former nutritional habits of the resident mightbe different. This possible discrepancy raises ethical questions.

A lower cognitive status of the residents was also associatedwith malnutrition. Several other studies confirmed this associa-tion.46,47 The relationship between cognitive impairment andnutritional risk is a complex and reciprocal problem.46 Severalfactors found to have an impact onmalnutrition are associated witha lower cognitive state, such as oral health problems.48,49

The present study revealed that the association with malnutri-tion was over two times lower when family supplied meals ornutritional supplements. Approximately 24% of the residentsreceived meals provided by their family members. Depending onthe nutritional status according to the MNA, between 22% and 39%of the residents received meals provided by the family members.This study does not provide data about the frequency, amount andcontent of the meals. This finding raises the question if the positiveeffect is due to the food itself, the fact that family members havemore time than nursing staff or the social support by the family.Several studies support the fact that the eating environment is animportant factor affecting appetite in elderly.50,51 A study by Nijset al. showed that the family style of the meal (table dressing, foodservice, staff protocol, residents’ protocol, and mealtime protocol)caused a significant decrease of malnutrition in Dutch nursinghome residents.52 Further research is needed to clarify the exact

relation between family supplied meals and decreased risk ofmalnutrition in nursing home residents.

5.1. Limitations

A first limitation is the use of a cross-sectional design. Thisdesign did not allow to report on a causal relationship betweenmalnutrition and causative factors or on the effect of nutritionalsupport in case of risk for malnutrition. A longitudinal design isrecommended to address this limitation. A second limitation is thevoluntary participation in this study. Increased awareness formalnutrition might have been present in the participating nursinghomes. Actual figures of malnutrition might be higher. The thirdlimitation is the absence of data on non-response as this mightaffect prevalence rates and the internal and external validity.53

6. Conclusion

Malnutrition is a prevalent problem in nursing homes in Flan-ders. Several factors independently associated with malnutritionwere found in this study: the presence of a wound/pressure ulcer,a recent hospitalization (<3 months ago), being involved ina tailored nutritional intervention, and suffering from a lowercognitive state. Receiving additional meals provided by familymembers was negatively associated with malnutrition. Systematicscreening andwell-defined tailored interventions should be furtherdeveloped and evaluated in this population at risk.

Funding

This study was supported by a grant of the Belgian FederalPublic Service, Health, Food chain safety and Environment.

Statement of authorship

All authors have made substantial contributions and approvedthe conceptions, drafting, and final version of the manuscript.

Design of the study: SV, IB, BG, KV.Collection of data : SV, IB, HD, BG, KV.Statistical analyses: MV, EC, HD, KVH.Drafting and revising themanuscript: MV, DB, AVH, KV, KVH, EC,

IB, HD, BG, SV.

Conflict of interest

There is no conflict of interest.

Acknowledgements

SV, IB, BG, KV participated in the design of the study. SV, IB, HD,BG, KV carried out the study. MV, EC, HD, KVH performed thestatistical analyses. MV, KV, DB helped to draft the manuscript. MV,DB, AVH, KV, KVH, EC, IB, HD, BG, SV read and approved the finalmanuscript.

References

1. Margetts BM, Thompson RL, Elia M, Jackson AA. Prevalence of risk of under-nutrition is associated with poor health status in older people in the UK. Eur JClin Nutr 2003;57:69e74.

2. Chen CC, Schilling LS, Lyder CH. A concept analysis of malnutrition in theelderly. J Adv Nurs 2001;36(1):131e42.

3. Stratton J, Green CJ, Elia M. Consequences of disease-related malnutrition. In:Stratton RJ, Green CJ, Elia M, editors. Disease-related malnutrition: an evidence-based approach to treatment. Wallingford, Oxon, UK: CABI Publishing; 2003. p.113e55.

M. Verbrugghe et al. / Clinical Nutrition 32 (2013) 438e443 443

4. Suominen M. Nutrition and nutritional care of elderly people in Finnish nursinghomes and hospitals. Faculty of Agriculture and Forestry of the University ofHelsinki; 2007.

5. Meijers JMM, van Bokhorst-de van der Schueren MAE, Schols JMGA, Soeters PB,Halfens RJG. Defining malnutrition: mission or mission impossible? Nutrition2010;26:432e40.

6. Kondrup J, Allison SP, Elia M, Vellas B, Plauth M. ESPEN guidelines for nutritionscreening 2002. Clin Nutr 2003;22(4):415e21.

7. Rubenstein LA, Harker JO, Salva A, Guigoz Y, Vellas B. Screening for undernu-trition in geriatric practice: developing the short-form mini-nutritionalassessment (MNA-SF). J Gerontol A Biol Sci Med Sci 2001;56(6):366e72.

8. Crogan NL, Pasvogel A. The influence of protein-calorie malnutrition on qualityof life in nursing homes. J Gerontol A Biol Sci Med Sci 2003;58:159e64.

9. Dey DK, Rothenberg E, Sundh V, Bosaeus I, Steen B. Body mass index, weightchange and mortality in the elderly. A 15y longitudinal population study of 70yolds. Eur J Clin Nutr 2001;55:482e92.

10. Takala JK, Mattila KJ, Ryynanen OP. Overweight, underweight and mortalityamong the aged. Scand J Prim Health Care 1994;12:244e8.

11. Amaral TF, Matos LC, Tavares MM, Subtil A, Martins R, Nazare M, et al. Theeconomic impact of disease-related malnutrition at hospital admission. ClinNutr 2007;26(6):778e84.

12. Kubrak C, Jensen L. Malnutrition in acute care patients: a narrative review. IntNurs Stud 2007;44(6):1036e54.

13. Guigoz Y. Themini nutritional assessment (MNA) reviewof the literatureewhatdoes it tell us? J Nutr Health Aging 2006;10(6):466e85 [discussion 485-487].

14. Sullivan DH, Sun S, Walls RC. Protein-energy undernutrition among elderlyhospitalized patients: a prospective study. J Am Med Assoc 1999;281:2013e9.

15. Van Nes MC, Herrmann Fr, Gold G, Michel JP, Rizzoli R. Does the mini nutri-tional assessment predict hospitalization outcomes in older people? Age Ageing2001;30:221e6.

16. Meijers JMM, Schols JMGA, van Bokhorst-de van der Schueren MAE, Dassen T,Janssen MAP, Halfens RJG. Malnutrition prevalence in The Netherlands: resultsof the annual Dutch national prevalence measurement of care problems. Br JNutr 2009;101:417e23.

17. Van Nie-Visser NC, Meijers JMM, Schols JMGA, Lohrmann C, Bartholomeyczik S,Halfens RJG. Comparing quality of nutritional care in Dutch and Germannursing homes. J Clin Nurs 2011;20:2501e8.

18. Vanderwee K, Clays E, Bocquaert I, Gobert M, Folens B, Defloor T. Malnutritionand associated factors in elderly hospital patients: a Belgian cross-sectional,multi-centre study. Clin Nutr 2010;29:469e76.

19. Van Gossum A, Vandewoude M. Données épidémiologiques concernant ladénutrition chez des patients âgés de plus de 70 ans en Belgique (Nutriaction-Belgique). Nutrition clinique et métabolisme 2009;23:S51e2.

20. Pauly L, Stehle P, Volkert D. Nutritional situation of elderly nursing homeresidents. Z Gerontol Geriatr 2007;40:2e12.

21. Suominen M, Muurinen S, Routasalo P, Soini H, Suur-Uski I, Peiponen A, et al.Malnutrition and associated factors among aged residents in all nursing homesin Helsinki. Eur J Clin Nutr 2005;59:578e83.

22. Wojszel ZB. Determinants of nutritional status of older people in long-termcare settings on the example of the nursing home in Bialystok. Adv Med Sci2006;51:168e73.

23. Compan B, di Castri A, Plaze JM, Arnaud-Battandier F. Epidemiological study ofmalnutrition in elderly patients in acute, sub-acute and long-term care usingMNA. J Nutr Health Aging 1999;3:146e51.

24. Milne A, Avenell A, Potter J. Meta-analysis: protein and energy supplementa-tion in older people. Ann Intern Med 2006;144:37e8.

25. Schmid A, Weiss M, Heseker H. Recording the nutrient intake of nursing homeresidents by food weighing method and measuring the physical activity. J NutrHealth Aging 2003;7:294e5.

26. Pichard C, Kyle UG, Morabia A, Perrier A, Vermeulen B, Unger P. Nutritionalassessment: lean body mass depletion at hospital admission is associated withan increased length of stay. Am J Clin Nutr 2004;79:613e8.

27. Westergren A, Lindholm C, Mattsson A, Ulander K. Minimal eating Observationform: reliability and validity. J Nutr Health Aging 2009;13(1):6e12.

28. Blaum CS, Fries BE, Fiatarone MA. Factors associated with low body mass indexand weight loss in nursing home residents. J Gerontol A Biol Sci Med Sci1995;50(3):162e8.

29. Green SM, Watson R. Nutritional screening and assessment tools for olderadults: literature review. J Adv Nurs 2006;54(4):477e90.

30. Guigoz Y, Lauque S, Vellas BJ. Identifying the elderly at risk for malnutrition.The mini nutritional assessment. Clin Geriatr Med 2002;18(4):737e57.

31. Vellas B, Guigoz Y, Garry PJ, Nourhashemi F, Bennahum D, Lauque S, et al. Themini nutritional assessment (MNA) and its use in grading the nutritional stateof elderly patients. Nutrition 1999;15(2):116e22.

32. National Food and Health Plan for Belgium. Nationaal Voedings- en Gezond-heidsplan, http://https//portal.health.fgov.be/pls/portal/docs/PAGE/INTERNET_PG/HOMEPAGE_MENU/MIJNGEZONDHEID1_MENU/PRODUITSDECONSOMMATION1_MENU/ALIMENTATION1_MENU/ALIMENTATION1_DOCS/WETENSCHAPPELIJKE%20TEKST%20NVGP.PDF; 2005 [accessed 03.08.11].

33. Wikby K, Ek AC, Christenssons L. The two-step mini nutritional assess-ment procedure in community resident homes. J Clin Nurs 2008;17(9):1211e8.

34. Söderhamn U, Flateland S, Jessen L, Söderhamn O. Perceived health and risk ofundernutrition: a comparison of different nutritional screening results in olderpatients. J Clin Nurs 2011;20(15e16):2162e71.

35. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical methodfor grading the cognitive state of patients for the clinician. J Psychiatr Res1975;12:189e98.

36. Fountoulakis KN, Tsolaki M, Chantzi H, Kazis A. Mini mental state examination(MMSE): a validation study in Greece. Am J Alzheimers Dis Other Dement2000;15:342e5.

37. Katz S, Akpom CA. A measure of primary sociobiological functions. Int J HealthServ 1976;6:493e507.

38. Breslow RA, Bergstrom N. Nutritional prediction of pressure ulcers. J Am DietAssoc 1994;94:1301e6.

39. Larsson J, Unosson M, Ek A-C, Nilsson L, Thorskind S, Bjurulf P. Effect of dietarysupplement on nutritional status and clinical outcome in 501 geriatric patientse a randomized study. Clin Nutr 1990;9:179e84.

40. Pinchkofsky-Devin GD, Kaminski Jr MV. Correlation of pressure sores andnutritional status. J Am Geriatr Soc 1986;34(6):435e40.

41. Guenter P, Malyszek R, Bliss DZ, Steffe T, O’Hara D, LaVan F. Survey of nutri-tional status in newly hospitalized patients with stage III or stage IV pressureulcers. Adv Skin Wound Care 2000;13:164e8.

42. Mathus-Vliegen EMH. Nutritional status, nutrition and pressure ulcers. NutrClin Pract 2001;16:286e91.

43. Harris CL, Fraser C. Malnutrition in the institutionalized elderly: the effects onwound healing. Ostomy Wound Manage 2004;50(10):54e63.

44. Burdette-Taylor SR, Kass J. Heel ulcers in critical care unit: a major pressureproblem. Crit Care Nurse 2003;25:41e53.

45. National Pressure Ulcer Advisory Panel and European Pressure Ulcer AdvisoryPanel. Prevention and treatment of pressure ulcers: clinical practice guideline.Washington DC: National Pressure Ulcer Advisory Panel; 2009. 57e60.

46. Lee KS, Cheong HK, Kim EA, Kom KR, Oh BH, Hong CH. Nutritional riskand cognitive impairment in the elderly. Arch Gerontol Geriatr 2009;48:95e9.

47. Saka B, Kaya O, Gulistan BO, Erten N, Karan MA. Malnutrition in the elderlyand its relationship with other geriatric syndromes. Clin Nutr 2010;29(6):745e8.

48. Avlund K, Holm-Pedersen P, Morse DE, Viitanen M, Winblad B. Tooth loss andcaries prevalence in very old Swedish people the relationship to cognitivefunction and functional ability. Gerontology 2004;21:17e26.

49. Griep MI, Mets TF, Collys K, Ponjaert-Kristoffersen I, Massart DL. Risk ofmalnutrition in retirement homes elderly persons measured by the “mini-nutritional assessment”. J Gerontol 2000;55A(2):57e63.

50. de Castro JM, Brewer EM. The amount eaten in meals by humans is a powerfunction of the number of people present. Physiol Behav 1992;51:121e5.

51. Wikby K, Fägerskiöld A. The willingness to eat. Scand J Caring Sci 2004;18:120e7.

52. Nijs K, de Graaf C, Siebelink E, Blauw Y, Vanneste V, Kok F, et al. Effect of family-style meals on energy intake and risk of malnutrition in Dutch nursing homeresidents: a randomized controlled trial. J Gerontol A Biol Sci Med Sci2006;61(9):935e42.

53. Lahmann N, Halfens RJG, Dassen T. Effect of non-response bias in pressure ulcerprevalence studies. J Adv Nurs 2006:230e6.