Background and aim A body of evidence is supporting the association between (the risk of) malnutrition in relation to physi- cal performance, muscle strength, risk for depression and cognitive status in geriatric outpatients. Associations between being malnourished according to the newly proposed ESPEN definition for malnutrition and clinically relevant outcome measures of the aforementioned variables have not been confirmed yet. Therefore, the aim of this study was to examine the association between being malnourished according to the ESPEN definition and clinically relevant outcome measures in geriatric outpatients. Methods Associations between malnutrition and handgrip strength (HGS, kg), short physical performance battery (SPPB- score, points), timed up and go test (TUG, seconds), and hospital anxiety and depression scale (HADS depression score, points), were analysed using linear regression. History of falls (falls, yes/no) and a low score on the Mini Mental-State Exami- nation (MMSE-score ≤ 24 points) were analysed using logistic regression. All analyses were adjusted for age and gender. Results A total of 185 geriatric outpatients (60% women) were included. The mean age was 82 (± 7.3) years. Being mal- nourished (8.2%) according to the ESPEN definition was significantly associated with a lower HGS (− 3.38 kg, p = 0.031), lower SPPB score (− 1.8 point, p = 0.025), higher TUG time (1.35 times higher time, p = 0.020) and higher HADS depression score (2.03 times higher score, p = 0.007). Being malnourished tended towards an association with falls (OR 3.84, p = 0.087). No significant association was found with low MMSE score (OR 2.61, p = 0.110). Conclusion This study is the first to confirm the association between being malnourished, defined by the ESPEN definition and clinically relevant outcome measures in geriatric outpatients. Keywords Malnutrition · Nutrition · Physical performance · Muscle strength · Depression · Aged * M. A. E. de van der Schueren Department of Medicine and Aged Care, Royal Melbourne firstname.lastname@example.org Hospital, University of Melbourne, Melbourne, Australia Department of Rehabilitation Medicine, VU University Department of Internal Medicine, Section of Nutrition Medical Center, Amsterdam, The Netherlands and Dietetics, VU University Medical Center, De Boelelaan 1118, Room ZH4A15, 1081 HV Amsterdam, Department of Human Movement Sciences, MOVE Research The Netherlands Institute Amsterdam, Vrije Universiteit, Amsterdam, The Netherlands Department of Internal Medicine, Section of Gerontology and Geriatrics, VU University Medical Center, Amsterdam, Department of Nutrition, Sports and Health, Faculty The Netherlands of Health and Social Sciences, HAN University of Applied Sciences, Nijmegen, The Netherlands Department of Internal Medicine, Amstelland Hospital, Amstelveen, The Netherlands Vol.:(0123456789) 1 3 390 European Geriatric Medicine (2018) 9:389–394 analysis (DSM-BIA; In-Body 720; Biospace Co., Ltd, Introduction Seoul, Korea). Due to a protocol amendment BIA meas- urements were added at a later stage and performed in 135 The European Society for Clinical Nutrition and Metabo- out of 185 outpatients. lism (ESPEN) proposed a new consensus definition for malnutrition in 2015. In this definition, fat-free mass index (FFMI) was introduced as an additional parameter to ESPEN definition for malnutrition determine malnutrition, as FFMI provides important infor- mation on functional reserves and metabolic processes . After initial screening by a valid screening tool, the ESPEN This new ESPEN definition seems to identify less definition comprises of two options to diagnose malnutri- malnourished patients compared to other tools [2, 3]. In tion . The first option comprises a BMI below 18.5 kg/ geriatric (out)patients, malnutrition has previously been m . The second option comprises unintentional weight loss associated with poorer clinical outcomes, such as impaired (> 10% indefinite of time, or > 5% over the last 3 months), muscle strength, worse physical performance, depression combined with either a low BMI (< 20 kg/m if < 70 years or worse cognitive status [4–7]. Therefore, the aim of the old or < 22 kg/m if ≥ 70 years old) or a low FFMI 2 2 present study is to study whether the new ESPEN defini- (female: < 15 kg/m , male: < 17 kg/m ) . Outpatients were tion confirms this previously described associations, now diagnosed as malnourished (yes/no) if they fulfilled at least that FFMI has been added as additional parameter to the one of these options. definition. Outcome measures Muscle strength, physical performance, risk for depression, Materials and methods falls and cognitive status were considered as clinically rel- evant outcome measures. Handgrip strength (HGS in kg) Study design  was used to measure muscle strength. The short physi- cal performance battery (SPPB, 0–12 points)  and timed In this cross-sectional cohort study, 185 geriatric outpa- up and go (TUG, in seconds)  were used to measure tients who were included who referred to the geriatric physical performance. The Hospital Anxiety and Depression outpatient clinic of the Bronovo Hospital (The Hague, Scale (HADS depression score, 0–21 points, higher score the Netherlands) between March 2011 and January 2012. indicating higher risk) , was used to measure the risk for All patients underwent a comprehensive geriatric assess- depression. Falls in the past 12 months (y/n) indicated the ment. No exclusion criteria were applied. This study was presence of falls. The Mini Mental-State Examination Score reviewed and approved by the institutional review board of (MMSE-score, 0–30, low score defined as < 24)  was the Leiden University Medical Centre (Leiden, the Neth- used to measure cognitive status. All measurements were erlands). Data were obtained during routine care and the performed according to standard operating procedures. need for individual informed consent was waived by the ethical review board. Statistical analysis Continuous variables that were normally distributed are pre- Geriatric outpatient characteristics sented as mean and standard deviation. Skewed distributions are presented as median and interquartile range. The associa- Medical records were used to collect data on sex, age, tions between being malnourished according to the ESPEN polypharmacy (the use of five or more medicines) and definition (independent variable) and HGS, SPPB-score, multimorbidity (two or more of the following chronic dis- TUG and HADS depression score (dependent variables) eases: hypertension, myocardial infarct, chronic obstruc- were analysed using linear regression analysis. TUG and tive pulmonary disease (COPD), Parkinson’s disease, HADS were not normally distributed and were, therefore, diabetes mellitus, cancer, rheumatoid arthritis, and osteo- log-transformed. After back transformation to normal, the arthritis. Unintentional weight loss (< 3 kg weight loss interpretation should be interpreted as ‘times higher/lower vs. ≥ 3 kg weight loss), current alcohol use (yes/no) and compared to normal’ (proportional change). falls (yes/no) in the past 12 months were self-reported. Low MMSE score and falls (dependent variables) were Body mass index (BMI, kg/m ), fat-free mass (FFM, kg) analysed using logistic regression analysis. Age and sex and fat-free mass index (FFM/height ) were derived from were found to be confounders for the associations and thus direct segmental multi-frequency bioelectrical impedance included in the adjusted model. 1 3 European Geriatric Medicine (2018) 9:389–394 391 Sensitivity analyses were performed excluding the 50 Table 1 Geriatric outpatient characteristics patients without a measurement of FFMI. N All Data were analysed using the Statistical Package for the Age, years 185 82.0 (7.3) Social Sciences 22.0 (SPSS Inc., Chicago, Illinois, USA). Female, n (%) 185 111 (60.0) p-values below 0.05 were considered statistically significant. Widowed, n (%) 183 78 (42.6) p-values below 0.10 were considered as tending towards an Living independent, n (%) 145 59 (40.7) association. Anthropometry Height, (cm) 177 167.1 (9.9) Weight (kg) 173 71.9 (15.6) Results BMI (kg/m ) 171 25.7 (4.4) FFMI (kg/m ) 135 17.3 (2.8) Geriatric‑outpatient characteristics Male 55 18.7 (2.8) Female 80 16.4 (2.4) Table 1 shows the characteristics of the geriatric outpatients. Parameters of health Eight percent (n = 14) of patients were diagnosed malnour- Unintentional weight loss, n (%) 185 24 (13) ished: two (1.1%) had a BMI below 18.5 kg/m , 11 (5.9%) Polypharmacy, n (%) 180 110 (61.1) had experienced unintentional weight loss in combination Multimorbidity, n (%) 177 67 (37.9) with a low BMI, and nine (4.9%) had experienced uninten- Current alcohol use, n (%) 185 74 (40) tional weight loss in combination with a low FFMI. Seven ESPEN definition for malnutrition out of fourteen outpatients were malnourished according to Malnourished, n (%) 171 14 (8.2) more than one option of the ESPEN definition. BMI < 18.5 (kg/m ) 2 (1.1) Unintentional weight loss + low BMI 11 (5.9) Associations between the ESPEN definition Unintentional weight loss + low FFMI 9 (4.9) for malnutrition and outcome measures Clinically relevant outcome measures Handgrip strength, (kg) 181 26.1 (8.4) Table 2 shows the results of the linear regression analyses Male 73 33.9 (6.1) for the association between being malnourished and HGS, Female 108 20.8 (5.0) SPPB score, TUG and HADS depression score. SPPB score 179 7.0 (3.4) Being malnourished was significantly associated with TUG, seconds, median [IQR] 160 15.8 [11.8–21.8] lower HGS, lower SPPB score, a higher TUG time and a HADS depression score, median [IQR] 115 5.0 [3–9] higher score on the HADS depression score, after adjust- Falls in the past 12 months, n (%) 185 118 (63.8) ments for age and sex. Malnourished outpatients had a Low MMSE score, n (%) 183 40 (21.9) 3.38 kg lower HGS (p = 0.031), 1.8 points lower SPPB score (p = 0.025), a 1.35 times higher TUG time (p = 0.020), All numbers are presented as mean (SD) unless indicated otherwise and a 2.03 times higher score on the HADS depression BMI body mass index, FFMI fat-free mass index, ESPEN European score (p = 0.007) compared to outpatients who were not Society for Clinical Nutrition and Metabolism, SPPB short physical performance battery, TUG timed up and go test, IQR interquartile malnourished. range, HADS Hospital and Anxiety Scale, MMSE mini-mental state Table 3 shows the results of the logistic regression analy- examination ses for the association between malnutrition, falls and low Polypharmacy was defined as the use of five or more medicines MMSE score. Malnutrition tended to be associated with Multimorbidity was defined as two or more of following chronic dis- falls; the odds on a fall was 3.84 higher (p = 0.087) com- eases: hypertension, myocardial infarct, COPD, cancer, diabetes mel- pared to not being malnourished, adjusted for age and sex. litus, rheumatoid arthritis, osteoarthritis, Parkinson’s disease No significant association between being malnourished and c Low MMSE-score is defined as a MMSE-score < 24 MMSE score was found. In outpatients with available FFMI (n = 135), the associa- SPPB score (p = 0.074) in the outpatients with FFMI avail- tions between the ESPEN definition for malnutrition and clinically relevant outcome were almost identical to the able. The association with low MMSE score changed from a 2.614 higher odds (p = 0.110) on a low MMSE score in results in the total population. The association with SPPB score slightly attenuated from a 1.814 lower SPPB score the total population into a 3.934 higher odds (p = 0.033) on a low MMSE score in outpatients with FFMI available. (p = 0.025) in the total population to a 1.523 point lower 1 3 392 European Geriatric Medicine (2018) 9:389–394 Discussion This cross-sectional study is the first to describe the asso- ciation between being malnourished based on the new ESPEN definition and clinically relevant outcome meas- ures in geriatric outpatients. Being malnourished was associated with lower HGS, lower SPPB score, higher TUG time and higher HADS depression score. A trend was found between being malnourished and falls. No association was found between being malnourished and low MMSE score. The study confirms the low impact of having a low BMI alone on diagnosing malnutrition, and pleads for the combination of parameters of energy deple- tion (weight loss) and protein depletion (loss of fat free mass) as suggested in the ESPEN definition. Geriatric outpatient population The prevalence of malnutrition according to the ESPEN definition in this study (8.2%) is in line with a recently pub- lished meta-analysis by Cereda et al. using the full Mini Nutritional Assessment (MNA) in geriatric outpatients (6.4%) . Our study also confirms the previously reported associations between (the risk of) malnutrition (mostly defined by MNA) and HGS, SPPB score, TUG and HADS depression score [4–6, 13]. In the present study, a trend was observed for the associa- tion between being malnourished and falls. This is in dis- crepancy with a study of van Bokhorst de van der Schueren et al.  where falls were recalled differently as ever versus never and the present study reported a fall (yes/no) in the past 12 months. In the present study, no association was found between being malnourished and a low MMSE score which is in line with previous studies [6, 14] in a population of geriatric patients. In previous studies, the terms “malnutrition” and “risk of malnutrition” were often used interchangeably, leading to higher prevalence rates of malnutrition. The variety of set- tings in which studies were performed may also explain the different prevalence rates and different associations between malnutrition and outcome measures. Strengths and limitations This study is the first to describe the association between the new ESPEN criteria for malnutrition and clinically rel- evant outcome measures. In addition, the clinically relevant outcome measures that were used were measured objec- tively, except for falls and HADS, which were obtained by questionnaires. 1 3 Table 2 Associations between being malnourished according to the ESPEN definition and HGS, SPPB score, TUG and HADS depression score a, b a,b HGS (kg) SPPB score TUG HADS depression score N = 168 N = 165 N = 152 N = 115 β 95% CI p B 95% CI p B 95% CI P β 95% CI p Malnourished Crude model − 4.035 − 8.896; 0.826 0.103 − 1.682 − 3.467; − 0.103 0.065 1.320 1.017; 1.714 0.037 1.948 1.158; 3.277 0.012 Model 1 (age and − 3.378 − 6.439; − 0.317 0.031 − 1.814 − 3.398; − 0.230 0.025 1.353 1.049; 1.745 0.020 2.026 1.124; 3.380 0.007 sex adjusted) Interpretation: malnourished outpatients had a 3.38 kg lower (p = 0.031) handgrip strength compared to outpatients who were not malnourished p-values below 0.05 are considered statistically significant. p-values below 0.10 are considered as tending towards an association CI confidence interval, HGS handgrip strength, SPPB short physical performance battery, TUG timed up and go test, HADS Hospital Anxiety and Depression Scale Values were log transformed before analysis. After analysing, the log-transformed values were transformed back to normal Interpretation: malnourished outpatients had a 1.35 times higher timed up and go time compared to outpatients who were not malnourished European Geriatric Medicine (2018) 9:389–394 393 Table 3 Associations between Falls Low MMSE score being malnourished according to the ESPEN definition and N = 171 N = 169 falls and low MMSE score OR 95% CI p OR 95% CI p Malnourished Crude model 3.916 0.847; 18.098 0.081 2.520 0.784; 8.097 0.121 Model 1 (age and 3.841 0.822; 17.958 0.087 2.614 0.806; 8.482 0.110 sex adjusted) Interpretation: malnourished outpatients have a 3.84 higher odds (p = 0.087) on a fall in the past 12 months compared to outpatients who were not malnourished (not significant) Low MMSE score is defined as a MMSE-score < 24 CI confidence interval, OR odds ratio, MMSE mini-mental state examination A limitation of this study is the small sample of mal- Compliance with ethical standards nourished outpatients. The low prevalence might be a defi - Conflict of interest The authors declare that they have no conflict of nition problem: if the definition is too strict, the prevalence interest. will always be low. Another problem might be that geriat- ric outpatients are often at risk for malnutrition instead of Ethical approval The study was reviewed and approved by the insti- being diagnosed as malnourished; until now the ESPEN tutional review board (IRB) of the Leiden University Medical Center (Leiden, the Netherlands). Ethical guidelines were followed in accord- definition does not have a category for at-risk patients. ance with the Declaration of Helsinki. Furthermore, the complexity of diagnosing malnutrition is a limitation; for example cognitive impairment, depression Informed consent This research is based on regular care, the need for or falls may be risk factors as well as outcome factors. A individual informed consent was waived by the aforementioned IRB. final limitation is that a small inter-observer variability could have occurred, although standard operating proce- Open Access This article is distributed under the terms of the Crea- dures were applied. tive Commons Attribution 4.0 International License (http://creat iveco mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- tion, 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. Conclusion This study is the first to confirm the association between References being malnourished, defined by the new ESPEN definition, and clinically relevant outcome measures in a population of 1. Cederholm T, Bosaeus I, Barazzoni R, Bauer J, Van Gossum A, Klek S, Muscaritoli M, Nyulasi I, Ockenga J (2015) Diagnostic geriatric outpatients. Future research should focus on deter- criteria for malnutrition—An ESPEN consensus statement. Clin mining the predictive value of the ESPEN definition and Nutr 34(3):335–340. https://doi.or g/10.1016/j.clnu.2015.03.001 thereby taking the different cut off points used into account. 2. Cereda E, Pedrolli C, Klersy C, Bonardi C, Quarleri L, Cap- pello S, Turri A, Rondanelli M, Caccialanza R (2016) Nutri- Acknowledgements The authors thank M. Stijntjes and J.H. Pasma tional status in older persons according to healthcare setting: a for their contribution to the study. NMvR, AGMR, EMR, MCT, ABM, systematic review and meta-analysis of prevalence data using CGMM and MAEdvdS designed the study. NMvR performed the data MNA(R). Clin Nutr 35(6):1282–1290. https://doi.or g/10.1016/j. analysis and drafted the manuscript. All authors contributed to the clnu.2016.03.008 writing of the manuscript. All authors approved the final version of 3. Schilp J, Kruizenga HM, Wijnhoven HA, Leistra E, Evers AM, the manuscript. van Binsbergen JJ, Deeg DJ, Visser M (2012) High prevalence of undernutrition in Dutch community-dwelling older individu- als. Nutrition 28(11–12):1151–1156. https ://doi.org/10.1016/j. Funding This study was supported by the seventh framework program nut.2012.02.016 MYOAGE (HEALTH-2007-2.4.5–10), by the Dutch Technology Foun- 4. Singh DK, Manaf ZA, Yusoff NA, Muhammad NA, Phan MF, dation STW, which is part of the Netherlands Organization for Scien- Shahar S (2014) Correlation between nutritional status and com- tific Research, and by the European Union’s Horizon 2020 research and prehensive physical performance measures among older adults innovation programme (Nos. 689238 and 675003). with undernourishment in residential institutions. Clin Interv Aging 9:1415–1423. https ://doi.org/10.2147/CIA.S6499 7 5. Yoshimura K, Yamada M, Kajiwara Y, Nishiguchi S, Aoyama T (2013) Relationship between depression and risk of mal- nutrition among community-dwelling young-old and old-old 1 3 394 European Geriatric Medicine (2018) 9:389–394 elderly people. Aging Mental Health 17(4):456–460. https ://doi. performance battery assessing lower extremity function: associa- org/10.1080/13607 863.2012.74396 1 tion with self-reported disability and prediction of mortality and 6. van Bokhorst-de van der Schueren MA, Lonterman-Monasch S, de nursing home admission. J Gerontol 49(2):M85–M94 Vries OJ, Danner SA, Kramer MH, Muller M (2013) Prevalence 10. Podsiadlo D, Richardson S (1991) The timed “Up & Go”: a test and determinants for malnutrition in geriatric outpatients. Clin of basic functional mobility for frail elderly persons. J Am Geriatr Nutr 32(6):1007–1011. https://doi.or g/10.1016/j.clnu.2013.05.007 Soc 39(2):142–148 7. Aartolahti E, Hartikainen S, Lonnroos E, Hakkinen A (2014) 11. Zigmond AS, Snaith RP (1983) The hospital anxiety and depres- Health and physical function predicting strength and balance sion scale. Acta Psychiatr Scand 67(6):361–370 training adoption: a community-based study among individuals 12. Folstein MF, Folstein SE, McHugh PR (1975) “Mini-mental aged 75 and older. J Aging Phys Act 22(4):543–549. https ://doi. state”: a practical method for grading the cognitive state of org/10.1123/japa.2013-0113 patients for the clinician. J Psychiatr Res 12(3):189–198 8. Reijnierse EM, Trappenburg MC, Leter MJ, Blauw GJ, de van der 13. Norman K, Stobaus N, Gonzalez MC, Schulzke JD, Pirlich M Schueren MA, Meskers CG, Maier AB (2015) The association (2011) Hand grip strength: outcome predictor and marker of nutri- between parameters of malnutrition and diagnostic measures of tional status. Clin Nutr 30(2):135–142. https ://doi.org/10.1016/j. sarcopenia in geriatric outpatients. PLoS ONE 10(8):e0135933. clnu.2010.09.010 https ://doi.org/10.1371/journ al.pone.01359 33 14. Isenring E, Baker J, Kerr G (2013) Malnutrition and falls risk in 9. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman community-dwelling older adults. J Nutr Health Aging 17(3):277– LF, Blazer DG, Scherr PA, Wallace RB (1994) A short physical 279. https ://doi.org/10.1007/s1260 3-012-0408-2 1 3
European Geriatric Medicine – Springer Journals
Published: May 3, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera