Prevalence of malnutrition on admission to four hospitals in England

Clinical Nutrition (2000) 19(3): 191–195 © 2000 Harcourt Publishers Ltd doi:10.1054/clnu.1999.0121, available online at http://www.idealibrary.com on

ORIGINAL ARTICLE

Prevalence of malnutrition on admission to four hospitals in England THE MALNUTRITION PREVALENCE GROUP WHICH COMPRISES: J. EDINGTON*, J. BOORMAN*, E. R. DURRANT*, A. PERKINS†, C. V. GIFFIN‡, R. JAMES‡, J. M. THOMSON‡, J. C. OLDROYD∏, J. C. SMITH∏, A. D. TORRANCE∏, V. BLACKSHAW¶, S. GREEN¶, C. J HILL¶, C BERRY**, C MCKENZIE**, N. VICCA**, J. E. WARD** AND S. J. COLES* *Abbott Laboratories, Maidenhead, Berkshire UK; †Medians, Wargave, Berkshire, UK; ‡Oxford Radcliffe Hospital, Oxford, UK; ∏Royal Victoria Infirmary, Newcastle-upon-Tyne, UK; ¶North Staffordshire Hospital, Stoke-on-Trent, UK; **Rotherham General Hospital, Rotherham, UK. (Correspondence to: JE, Medical Division, Abbott Laboratories, Abbott House, Norden Road, Maidenhead, Berkshire SL6 4XE, UK)

Abstract—Aims: The primary objective was to estimate prevalence of malnutrition on admission to four hospitals. Secondary objectives included assessing the relationship between nutritional status and length of hospital stay, numbers of new prescriptions, new infections and disease severity. Methods: We entered eligible patients according to predefined quotas for elective and emergency admissions to 23 specialities. We measured height, weight, Body Mass Index and anthropometrics, and recorded history of unintentional weight loss. Patients who had lost ≥10% of their body weight, had a Body Mass Index <20, or had a Body Mass Index <20 with one anthropometric measurement <15th centile were considered malnourished. Results: Of 1611 eligible patients, 761 did not participate; 269 were too ill; 256 could not be weighed; and 236 refused consent. Eight hundred and fifty were subsequently evaluated. Prevalence of malnutrition on admission was 20%. Length of stay, new prescriptions and infections and disease severity were significantly higher in the malnourished. Conclusions: One patient in every five admitted to hospital is malnourished. Although this figure is unacceptably high, it may underestimate true prevalence. Malnutrition was associated with increased length of stay, new prescriptions and infections. Malnutrition may also have contributed to disease severity. © 2000 Harcourt Publishers Ltd

prevalence of malnutrition in patients admitted to two district general hospitals and two teaching hospitals in four geographic areas of England rather than in a single hospital. Secondary objectives were to assess the relationship between nutritional status on admission, and severity of disease, length of stay, new prescriptions and new infections in hospital.

Key words: malnutrition; admission; hospital; length of stay Introduction Since 1974, when Butterworth wrote his controversial paper, ‘The skeleton in the hospital closet’ (1), it has been known that the problem of malnutrition existed in patients in hospital, not only in the USA, but also in the UK, where it was almost entirely unrecognized (2). Twenty-five years later, despite immense advances in medical science and diagnostic techniques, little has changed. In 1994, McWhirter and Pennington found that 40% of patients admitted to five different specialities at Ninewells Hospital in Dundee were malnourished (3). Furthermore, 78% of those who were malnourished on admission deteriorated during their hospital stay (3). But that study was carried out in a single teaching hospital. The results may not have been truly representative of patients admitted to other hospitals or of patients admitted to hospitals other than teaching hospitals. The primary objective of this study was to estimate the

Patients and methods This study was approved by the Local Research Ethics Committee of each of the hospitals participating in the study. Two general acute teaching hospitals (The Newcastle-uponTyne Hospitals NHS Trust and Oxford Radcliffe NHS Trust) and two district general hospitals (North Staffordshire Hospitals NHS Trust and Rotherham General Hospital NHS Trust) participated in this study. Prior to beginning recruitment, each hospital identified the number of elective and emergency patients admitted during the previous year to each of the specialities shown in Table 1. For each hospital, the statistician (AP) prepared a list of the numbers of elective and emergency patients in 191

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Table 1

Number of patients in each speciality

Speciality General surgery Urology Trauma and orthopaedics Ear, nose and throat Ophthalmology Neurosurgey Plastic surgery Cardiothoracic surgery Accident and emergency General medicine Geriatric medicine Gastroenterology Haematology Cardiology Thoracic medicine Infectious diseases Nephrology Medical oncology Neurology Rheumatology Other Care shared between specialities * Total Patients Entered

Oxford 31 13 7 0 0 0 0 7 0 20 0 5 3 9 14 8 14 6 0 0 0 77 214

Newcastle 37 15 19 14 9 13 16 10 0 57 10 0 3 17 6 1 5 8 3 1 4 1 249

Rotherham 29 4 31 5 0 0 0 0 12 71 30 8 5 0 0 0 0 0 0 2 0 1 198

North Staffs 45 12 7 13 0 0 5 0 0 78 0 6 0 10 1 6 0 1 0 0 5 0 189

Total 142 44 64 32 9 13 21 17 12 226 40 19 11 36 21 15 19 15 3 3 9 79 850

*Some patients were admitted to more than one speciality, e.g. Accident and emergency and General medicine, but have only been counted once in the total number entered.

each speciality who were to be entered into the study. The numbers of patients entered were intended to be proportional to admissions to each speciality in each hospital during the previous year. The target number of patients to be surveyed in each hospital was between 200 and 250. Investigators screened patients admitted to the first speciality on the list and invited eligible patients to participate until the predefined number of elective and emergency patients for that speciality had been entered into the study. The same process was then repeated with patients admitted to each speciality on the list until the specified numbers of patients from each speciality had been entered into the study. Patients were considered eligible for entry if they were over the age of 18, required emergency or routine admission to any of the specialities listed above and were willing and able to give written informed consent. Patients admitted to day case units, bedridden patients and those admitted to intensive care units were excluded. Those who had not been assessed before they had been hospitalized for longer than 48 h, or who had undergone a clinical intervention, e.g. surgery, before being assessed, were not included. Seven dietitians in four hospital trusts took anthropometric measurements to determine each patient’s nutritional status. Height was measured without shoes to the nearest 0.5 cm with a Holtain stadiometer. If the patient was unable to stand, height was estimated using a validated method which involves measuring arm span (4, 5). Weight was measured using Seca chair scales which were calibrated monthly. Body Mass Index (BMI) was calculated from weight and height from the formula: BMI = weight (kg)/height2 (metres2). Mid-arm circumference (MAC) was measured with a tape measure. Triceps skinfold thickness (TST) was measured with Holtain skinfold calipers. Mid-arm muscle

circumference (MAMC) was calculated from the formula: MAMC (cm) = MAC (cm) – 3.14 3 TST (cm). Values were compared with centiles of normal values for TST and MAMC standardized for age and sex, for adults aged 16–64 (6) and aged 65 and older (7). During an interview with the patient any history of involuntary weight loss during the 6 months immediately preceeding admission was also recorded. We defined malnutrition as: 1. Mild–BMI <20 with either TST or MAMC below the fifteenth centile (3); 2. Moderate – BMI <18 with either TST or MAMC below the fifth centile (3); 3. Severe – BMI <16 with either TST or MAMC below the fifth centile (3); 4. BMI <20 and unintentional weight loss >10% of body weight during the 6 months immediately preceeding hospital admission (8); 5. BMI ≥20 and unintentional weight loss >10% body weight during the 6 months immediately preceeding hospital admission (8); and 6. BMI <20 and ≤10% weight loss during the 6 months immediately preceeding hospital admission (9). Each category was mutually exclusive. BMI was not adjusted for age and sex, as this is not generally recognized to be necessary. Additional information that was collected was the severity of the patient’s medical/surgical condition. The dietitian used common sense and the advice of hospital staff to assess each patient and grade severity of condition subjectively as mild (disease or condition is easily tolerated by the patient), moderate (disease or condition causes the patient discomfort and interrupts the patient’s usual activities), or severe (disease or condition causes considerable interference with the patient’s usual activities and may be incapacitating or life threatening). After discharge from hospital, or 12 weeks after admission whichever was sooner, we retrospectively reviewed each patient’s medical record pertaining to that admission to

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determine length of hospital stay (LOS) and medical events which occurred while they were in hospital. These included numbers of new prescriptions and infections and whether or not the patient was referred to a dietitian. The power calculation was based on a prevalence of malnutrition of 40%. Using a two-sided significance level of 0.05 and a statistical power of 95%, it would be possible to detect a difference of 16% between any two NHS trusts with a sample size of 250 patients in each NHS Trust. Statistical tests were carried out to compare the cohort of malnourished patients with the cohort who were not malnourished. For categorical data, the two groups were compared using Pearson x2 tests. The mean values for length of stay and numbers of new prescriptions were compared for the two groups using Mann–Whitney U-tests. The numbers of infective episodes were compared for the two groups using a Mantel-Haenszel test for linear association which was weighted for the number of episodes.

malnourished patients in teaching and district general hospitals were compared, the prevalence was higher in the teaching hospitals (22.4%) compared with the district general hospitals (16.5%) and these differences were just statistically significant (P = 0.031). Although 168 patients were found to be malnourished, only 41 were referred to a dietitian for dietary advice or treatment. Table 3 compares nutritional status with severity of condition, as assessed subjectively by the investigator using a common sense approach. Twenty-five percent of patients who were assessed as being severely ill were also malnourished, whereas 12% of patients who had a mild condition were malnourished. There was no significant difference between the conditions of patients admitted to teaching and non-teaching hospitals. Table 3 Comparison of severity of condition and nutritional status Severity of condition Nutritional status

Severe number (%)

Moderate number (%)

Mild number (%)

Malnourished Not malnourished Total

40 (25.2) 119 (74.8) 159 (100)

96 (22.3) 335 (77.7) 431 (100)

32 (12.3) 228 (87.7) 260 (100)

Results Of 1611 patients who were eligible to take part in the study, 761 did not participate for the following reasons: 236 refused consent, 269 were too ill and refused consent, or were deemed too ill by hospital staff and 256 were bedridden and could not be weighed. Eight hundred and fifty patients entered the study, 476 men and 374 women, mean age 58.5 years (SD 18.3, range 18–103 years). Numbers of patients who participated in each hospital were: Oxford, 214 (131 men, 83 women, mean age 58.2, SD 18.4, range 18 to 103 years): Newcastle, 249 (149 men, 100 women, mean age 59.2, SD 17.1, range 18–92 years): Rotherham, 198 (111 men, 87 women, mean age 57.8, SD 18.3, range 18–88 years); North Staffordshire, 189 (85 men, 104 women, mean age 58.5, SD 19.9, range 18–97 years). Table 1 shows the numbers of patients from each speciality who participated in each hospital. Numbers surveyed at each hospital were proportional to those admitted during the previous year. Table 2 shows the number of patients, by centre, who were malnourished. Overall, the prevalence of malnutrition was 19.8%. The difference in prevalence between centres was not statistically significant. However, when numbers of

P = 0.001, x2 = 13.74 with 2 d.f.

Table 4 Relationship between nutritional status and length of stay, number of new prescriptions and number of new infective episodes Nutritional status

Malnourished Not malnourished Total

Length of stay1

Number of new prescriptions2

Number of new infective episodes3

Mean (SD) number (n)

Mean (SD) number (n)

Mean (SD) number (n)

8.86 (9.67) n = 167 5.72(7.71) n = 675 6.34 (8.22) n = 842

5.28 (4.47) n = 166 4.49 (4.02) n = 672 4.65 (4.12) n = 838

0.38 (0.62) n = 167 0.23 (0.48) n = 674 0.26 (0.52) n = 841

1

P <0.001 when applying Mann–Whitney U-test. P = 0.024 when applying Mann–Whitney U-test. 3 P = 0.001 when applying Mantel–Haenszel test for linear association to compare cohort of malnourished patients with cohort of those who were not malnourished. The number of infective episodes ranged from 0 to a maximum of 3. 2

Table 2 Number of malnourished patients at each centre Study centre Degree of malnutrition

Oxford n = 214 number (%)

Newcastle n = 249 number (%)

Rotherham n = 198 number (%)

North Staffs n = 189 number (%)

Total n = 850 number (%)

Severely malnourished Moderately malnourished Mildly malnourished + BMI <20, >10% weight loss in 6 months + BMI ≥20, weight loss >10% + BMI <20, <10% weight loss Not malnourished Total malnourished

1 (0.5) 3 (1.4) 11 (5.1) 3 (1.4) 21 (9.8) 7 (3.3) 168 (78.5) 46 (21.5)

1 (0.4) 4 (1.6) 16 (6.4) 6 (2.4) 24 (9.6) 7 (2.8) 191 (76.7) 58 (23.3)

0 (0.0) 1 (0.5) 10 (5.1) 4 (2.0) 15 (7.6) 4 (2.0) 164 (82.8) 34 (17.2)

3 (1.6) 2 (1.1) 6 (3.2) 2 (1.1) 14 (7.4) 3 (1.6) 159 (84.1) 30 (15.9)

5 (0.6) 10 (1.2) 43 (5.1) 15 (1.8) 74 (8.7) 21 (2.5) 682 (80.2) 168 (19.8)

+ These patients are not included in any other group P = 0.172, x2 = 5.00 with 3 d.f. when all four centres are compared. P = 0.031, x2 = 4.67 with 1 d.f. when figures for teaching hospitals are combined and compared with those for the district general hospitals.

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Table 4 shows the relationship between nutritional status and length of stay, numbers of new prescriptions and numbers of new infections. It was found that malnourished patients stayed in hospital for a mean of 8.9 days which is significantly longer than patients who were not malnourished who stayed for a mean of 5.7 days (P < 0.001). In addition, the severely malnourished, and those who had a BMI <20 and weight loss of >10% stayed in hospital for 18.3 and 17.5 days respectively. Even those who had modest levels of malnutrition stayed in hospital for longer than those who were not malnourished. We found that those with BMI <20 and ≤10% weight loss had a LOS of 7.6 days. Malnourished patients required significantly more new prescriptions while in hospital than the patients who were not malnourished (5.3 compared with 4.5, P < 0.05). In addition, the malnourished patients experienced 0.4 new infections in hospital compared with those patients who were not malnourished who had 0.2 new infections in hospital (P = 0.001). Discussion The results of our study indicate that one patient in every five admitted to hospital is malnourished, a figure which is unacceptably high. Previous work in the community has shown that between 8 and 11% of patients are malnourished when applying McWhirter and Pennington’s criteria (10, 11). The prevalence we found agrees with the data of Strain et al. (12) who determined that 24% of patients were malnourished on admission to their hospital. But our prevalence results contrast sharply with those of McWhirter and Pennington who found that 40% of patients were malnourished on admission (3) and Bruun et al. who found 39% of patients were mildly/borderline to severely malnourished after 7 days in hospital (9). We did not find a difference in the prevalence of malnutrition between teaching and nonteaching hospitals. But, when numbers of malnourished patients in teaching and district general hospitals were compared, the prevalence was higher in the teaching hospitals (22.4%) compared with the district general hospitals (16.5%, P = 0.031). This may have resulted from differences in the underlying conditions of patients admitted to the two types of hospital. We also found, however, that there was a significant association between severity of condition and malnutrition, with the more severely malnourished patients staying in hospital for significantly longer than those who were not malnourished. Nineteen malnourished patients stayed for between 17 and 18 days, whereas those who were not malnourished stayed for an average of 6 days. Inevitably, longer lengths of stay were associated with significantly higher requirements for prescription drugs and infective episodes while in hospital. To determine prevalence of malnutrition we applied several different criteria, including those of McWhirter and Pennington (3). Using their criteria, the prevalence in our study sample was 7% – lower than that found in the general population (13), Clearly, in patients admitted to hospital, this would seem to be unlikely. But other investigators have used additional indicators of undernutrition (8, 9). These

include involuntary weight loss of greater than 10% in the 6 months preceeding hospital admission (8), and a BMI below 20 (9). Twenty percent of patients in our sample were undernourished when applying all criteria. The reasons for our findings being so different from those of other authors may have resulted from bias in our patient sample, or from differences in our respective patient samples. Overall, 850 patients participated, but there were a further 525 eligible patients whom we could not assess because they were either too ill (269 patients) or were bedbound and could not be weighed (256 patients). In addition, there were 236 patients, the majority of whom were elderly, who refused to participate. McWhirter and Pennington assessed 100 consecutive admissions from each of five disciplines, one of which was the care of the elderly. Bruun et al. assessed consecutive admissions from two disciplines after they had been in hospital for 7 days (9). We found it impractical to collect data on consecutive admissions and many eligible patients did not participate for the reasons described above. Because our data collection was incomplete, this may have biased our results. Clearly the patients we could not assess – the very ill and the very old – were those most likely to be at risk of malnutrition. Their inclusion may have changed our results so it is possible that we underestimated true prevalence. Strain and his colleagues had similar difficulties in assessing patients in their hospital (12). They were unable to assess 28% of their patient sample and concluded that they could not determine true prevalence, but that it may be lower than previously estimated. Despite the difficulties of assessing prevalence, it is very clear from our findings that malnourished patients stay in hospital for longer, require more prescription drugs and suffer more infections while in hospital than those who are not malnourished. It is unclear whether these events result from malnutrition or from disease severity, since it is impossible to isolate one from the other (14), but it seems logical that each contributes to the other. Of 159 patients whose condition was judged to be severe, we determined that 25% were also malnourished. This contrasts with 260 patients whose condition was judged to be mild, only 12% of whom were malnourished. It is possible that treating malnutrition early could reduce disease severity with a resulting reduction in other health events. Yet of 168 malnourished patients in our study, only 41 were referred to a dietitian. Our findings suggest that it is extremely difficult to obtain an accurate assessment of the prevalence of malnutrition in patients admitted to hospital but we know that it is at least 20%. Whatever the prevalence, it is clear that malnourished patients have poorer clinical outcomes and the resulting cost to the National Health Service cannot be ignored. There are two areas of further research which need to be addressed. Firstly, it has long been known that there is no established and accepted definition of malnutrition (14, 15). A practical definition of malnutrition is urgently needed. Health care professionals in hospitals and in the community can then be educated to recognize malnutrition and identify those patients who require treatment. Only then will malnutrition be treated appropriately. Secondly, prospective randomized

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controlled trials need to be conducted to determine whether improving the nutritional status of malnourished patients is cost effective and if it also improves clinical outcome and quality of life. References 1. Butterworth C E. The skeleton in the hospital closet. Nutrition Today 1974; 94–98 2. Hill G L, Pickford I, Young G A et al. Malnutrition in surgical patients. An unrecognised problem. Lancet 1977; 1: 689–692 3. McWhirter J P, Pennington C R. Incidence and recognition of malnutrition in hospital. BMJ 1994; 308: 945–958 4. Jelliffe D. The Assessment of the Nutritional Status of the Community. Serial No 53 ed. Geneva: World Health Organisation; 1966 5. Todorovic V E, Micklewright A. Parenteral and Enteral Nutrition Group of the British Dietetic Association. A Pocket Guide to Clinical Nutrition. Second. Birmingham: The British Dietetic Association 1997; 2: 10 6. Bishop C W, Bowen P E, Ritchley P I. Norms for nutritional assessment of American adults by upper arm anthropometry. Am J Clin Nutr 1981; 34: 2530–2539 Submission date: 24 November 1999 Accepted: 10 March 2000

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