Nutrition screening and assessment of patients attending a multidisciplinary falls clinic. (Original Research).
Objective: To describe the nutritional health and current nutritional management of a representative sample of patients attending an Australian falls clinic.
Design: Descriptive study.
Subjects: Ninety adults (65 years old and over) attending the Falls Clinic.
Setting: Fall and Injury Risk Assessment Clinic, Repatriation General Hospital, Daw Park, South Australia.
Main outcome measures: The Australian Nutrition Screening Initiative (ANSI) tool was administered. Measurements of height, weight, mid-upper arm circumference (MAC) and triceps skinfold thickness (TSF) were taken by a trained investigator on one occasion. Body mass index (BMI) was calculated for each participant. A BMI of less than 22 kg per [m.sup.2] and greater than 30 kg per [m.sup.2] were classified as underweight and overweight respectively. A BMI of less than 22 kg per [m.sup.2] and MAC or TSF less than the fifteenth percentile were considered undernourished. Case notes were audited to determine the number of referrals to the dietetics department.
Statistical analysis: Descriptive statistics were used to summarise the data. To identify significant differences between variables and genders, independent sample t-tests were used for continuous data and chi-square tests of significance for categorical data. A significance level of P < 0.05 was applied to all statistical tests.
Results: According to the ANSI checklist 41 of 90 participants were assessed as high nutritional risk'. The most common ANSI risk factors were 'taking three or more different medications daily' (n = 65), 'eating alone most of the time' (n = 41), having a 'history of unintentional weight change' (n = 28), and having an 'illness or condition that affects dietary intake' (n = 26). Seventeen participants were considered overweight with a BMI > 30 kg/[m.sup.2] and 11 were classified as undernourished with a BMI < 22 kg/[m.sup.2] and a MAC or TSF less than the fifteenth percentile. One referral was made to the dietetics department at the Repatriation General Hospital.
Conclusion or application: The results of this study have shown that a substantial number of older adults susceptible to falling are at risk of poor nutritional health and that there is limited nutritional management of this population. While weight and height are routinely collected in this falls clinic and the possibility to monitor weight is available, there is an opportunity to raise awareness of the nutritional health of these patients. (Nutr Diet 2002;569:234-9)
Key words: elderly, nutrition assessment, falls, nutrition screening, body mass index
The number of persons aged 65 years and over currently comprises 12% of the total Australian population and this is projected to increase to 24 to 27% in 2051 (1). Age-related changes including increased body sway, altered gait pattern, impaired balance and visual impairment make older adults vulnerable to falls (2). It has been estimated that of people aged 65 years and over who live in the community, approximately 30% fall each year (3,4) and for those aged over 80 years, the rate is as high as 50% (5). Total health costs for accidental falls for those aged over 65 years were $406 million, in 1993-94 (6) and are projected to increase exponentially with the ageing of the population. Fractures, loss of confidence and independence, fear, institutionalisation and death contribute to health care costs and are themselves important consequences of falling (7).
Poor nutritional health is a risk factor for accidental falls. Age-associated loss of muscle mass is exacerbated by undernutrition (8) and it has been suggested weakness and gait abnormalities are also related to undernutrition (9). In addition, a tendency to fall is compounded by being undernourished (10). The prevalence of undernutrition among frail older adults is estimated at between 20 and 60% depending on which criteria and cutoff points are adopted (11). Low body weight is a known risk factor for osteoporosis (12) and there is data to suggest that the prevalence of undernutrition in patients admitted to hospital with a fall-related fracture is high (13-15). Aside from increased risk of falls and fall-related fracture, the consequences of undernutrition include longer length of hospital stay, impaired immune response, increased risk of complications, and higher rates of morbidity and mortality (16). These consequences in turn impact on recovery from a fall-related injury.
There is some evidence that an elevated body mass index (BMI > 26 to 28 kg/[m.sup.2]) provides some protection against fall-related fractures as body fat is thought to act as a cushion for bone on impact of a fall, especially in the hip region for women (17). Increased weight is also known to enhance bone mineral maintenance (18). In contrast to this, increased body weight has been shown to increase falls risk. In women, a BMI greater than 30 kg/in2 has been associated with immobility (18-20), osteoarthritis (21) and an increased tendency to fall (22).
There are currently no recommended guidelines for falls clinics but generally these clinics involve a multidisciplinary team and provide individual assessment and management of falls risk factors with the overall aim of reducing an individual's falls, related injuries and associated problems (23). In the Fall and Injury Risk Assessment Clinic patients are assessed at an initial two-hour visit by a rehabilitation medicine or geriatrics registrar, a physiotherapist and a nurse, in order to obtain a history and identify risk factors. This falls clinic uses treatment protocols based on evidence and interventions generally focus on medication advice, exercise programs, footwear advice, home modification and equipment, and gait and balance re-education (24). Currently in Australia, few multidisciplinary falls clinics assess nutritional health and even fewer have dietitians as part of the clinic team (23). At our falls clinic, height and weight are routinely measured at the patient's initial visit. However, there is no standard procedure for interpreting height and weight and referral for nutritional care. The aim of this study was to describe the nutritional health and current nutritional management of patients attending our falls clinic in Adelaide.
In this descriptive study, 90 adults aged 65 years and over were recruited from the Falls Clinic of the Repatriation General Hospital.
All patients scheduled with an appointment to attend the falls clinic over a five-month period (23 April to 27 September 2001) were contacted regarding participation in the study. Each was sent a letter of invitation to participate and patient information sheet explaining what participation in the study would entail. A follow-up telephone call was made to each individual to provide further details of the study and to identify those individuals willing to participate. Written informed consent was obtained at the falls clinic appointment. The Repatriation General Hospital Research and Ethics Committee approved the study protocol.
Demographic data and medical history
Demographic data (age, gender, living situation) and medical history (falls history, dietetic referral and intervention) were collected from medical notes and confirmed by the participant and carers where required.
Nutrition tools and measurements
The Australian Nutrition Screening Initiative (ANSI) was administered to all participants. Responses were self-reported. The screening tool consists of a 12-question checklist developed to assist in the identification of older adults living in the community, at risk of poor nutritional health (25). It is based on a screening tool developed in the US (26) and has been modified for use in Australia (27). Risk factors are shown in Figure 1. The tool has been evaluated among independently-living older Australians and shown to be a significant predictor of the adequacy of food intake (28). Each checklist question incurs a score according to the presence or absence of each risk factor. A total ANSI score is derived by summation of the question scores. This 'total' is used to classify nutritional risk as high ( 6), moderate (4 to 5) or low (0 to 3).
Mid-upper arm circumference (MAC) and triceps skinfold thickness (TSF) were measured for each participant by the same trained investigator (DS). These measurements were performed on the right side of the body, unless affected by disease or disability, using standard techniques (29). A flexible steel tape measure was used to measure MAC to the nearest 0.1 cm. Harpenden skinfold calipers (British Indicators, West Sussex, UK) measured TSF to the nearest 0.2 mm. Measurements were made in triplicate and mean values calculated. As standard Falls Clinic procedure, body weight and height were measured at each patient's initial visit. Weight and height were requested by the investigator if a patient was attending a follow-up appointment. Body weight was measured (to the nearest 0.5 kg) using portable platform medical scales (Propert Australia Pty Ltd, Sydney). Height was measured (to the nearest 0.5 cm) using a wall-mounted measuring tape. All individuals were able to stand in the correct position for the measurement to be made (29).
Body mass index was calculated for each participant. A BMI of less than 22 kg/[m.sup.2] and greater than 30 kg/[m.sup.2] was classified as underweight and overweight respectively. The BMI cut-off points of 22 and 30 kg/[m.sup.2] equate to the 15th and 85th percentiles respectively, of the Australian Longitudinal Study of Ageing data (20). The latter study is a large Adelaide-based longitudinal study of community-dwelling adults aged 65 years and over that aims to identify the factors that influence health and wellbeing in old age (30). Definitions of undernutrition vary between studies. We defined undernourished as a BMI of less than 22 kg/[m.sup.2] and a MAC (males 26.2 cm, females 25.2 cm) or a TSF (males 7.9 mm, females 13.5 mm) less than the 15th percentile (31) of a representative sample of older adults participating in the Australian Longitudinal Study of Ageing (32).
Data were entered into a database and analysed using SPSS (SPSS Inc, Chicago, SPSS for Windows, Advanced Statistics, release 9.0.1 1999). Descriptive statistics were used to summarise the data. Data were expressed as means and standard deviations. To identify significant differences between genders, independent samples t-test was used for continuous data (total ANSI score, BMI, MAC, TSF) and chi-square test of significance for categorical data (age, marital status, accommodation, falls history, ANSI category and each ANSI risk factor). For all statistical tests, a significance level of P < 0.05 was used.
Between 23 April and 27 September 2001, 123 patients were offered falls clinic appointments, either for initial or follow-up visits. Two individuals were under 65 years of age and therefore ineligible to participate. Nine individuals declined consent. Reasons given for non-participation were 'feeling too old' (n = 1), 'too confused' (n = 1), 'too busy' (n = 1), 'project is of no benefit' (n = 1) and five participants gave no reason. Seventeen participants did not attend their appointment and five left the Falls Clinic before they were assessed. Written informed consent and complete data was collected from 90 (74%) participants.
Descriptive characteristics are summarised in Table 1. The largest group of participants was the 75- to 84-year- age category (n = 53). The mean age was 80.2 [+ or -] 5.6 years for females and 80.8 [+ or -] 5.8 years for males (P = 0.64). The majority of participants lived in the community (a = 85). Sixty-five participants had two or more falls in the previous 12 months. The median number of falls in the previous 12 months was three (range 0 to 300; interquartile range 2 to 6), 15 participants had fallen only once.
Current nutritional management
During the study period only one referral was made for a patient to see a dietitian. The dietetic referral was requested by the patient following the research interview due to concern about recent unintentional weight loss and loss of appetite. The patient was seen by a hospital dietitian for an initial and a review appointment. The patient's current weight, weight history and co-morbidities were addressed in these appointments.
Nutrition tools and measurements
The ANSI checklist was completed by all 90 participants. Using the ANSI checklist 41 of 90 participants were assessed as being at 'high nutritional risk', 27 at 'moderate nutritional risk' and 22 at 'low nutritional risk' (see Table 2). There was no significant difference between genders for total ANSI score (P = 0.13), nor was there any significant difference in the number of males and females in each ANSI category (P = 0.12). Figure 1 shows the prevalence of each nutritional risk factor as measured by ANSI. The most common ANSI risk factors were 'taking three or more different medications daily' (n = 65), 'eating alone most of the time' (n = 41), 'unintentional weight change' (n = 28) and 'having an illness or condition that affects dietary intake' (n = 26). The number of females eating alone was significantly greater compared to males (P < 0.001). More males had the risk factor 'three or more glasses of alcohol most days', than females (P = 0.02). The least common risk factors were 'eating no fruit or vege tables most days' (n = 3), and 'not always having enough money to buy food' (n = 2).
Anthropometric measurements are shown in Table 3. The majority of participants had a BMI between 22 to 30 kg/[m.sup.2] (n = 62). There were no significant differences between male (27.0 [+ or -] 2.9 cm) and female (26.7 [+ or -] 3.3 cm) MAC measurements (P = 0.60). Triceps skinfold measurements were significantly lower in males (12.5 [+ or -] 4.1 mm) compared to females (17.1 [+ or -] 4.0 mm) (P <0.001). The total number of participants classified as undernourished (BMI of less than 22 kg/[m.sup.2] and a MAC or a TSF less than the 15th percentile) was 11.
At present there are no Australian data published on the nutritional health of older adults who have been identified as being at high risk of falling and thus referred to a multidisciplinary falls clinic. The results of this study suggest that almost half (n = 41) the older adults attending the Falls Clinic are at 'high nutritional risk' as assessed by ANSI. Using more objective measures to assess nutritional health, one in eight participants had a BMI less than 22 kg/[m.sup.2] (underweight), whereas one in five participants had a BMI of over 30 kg/[m.sup.2] (overweight).
In our study, ANSI implicated a large number of participants as at 'high risk' of poor nutritional health (n = 41). There are no other Australian data reporting on the nutritional health of those having falls, therefore we have compared our findings with a general elderly population. In a previous study of older Adelaide residents, only 30% were identified as being at 'high nutritional risk' (28). In our study the greater number identified as at risk of poor nutritional health may reflect the poorer overall health of the falls clinic sample. The risk factor of taking 'three or more medications daily', can be considered an indicator of poor health. It was the most common risk factor for both studies, but was far more common in the falls clinic sample (72% compared to 46%) (28). This further supports the contention that as expected, patients referred to the falls clinic have poorer health than a general community dwelling group. Notably, taking four or more medications is also an identified risk factor for fall ing (33).
The Australia Nutrition Screening Initiative is a screening tool and as such assesses nutritional risk. Whereas, anthropometric measurements provide objective data which can be used to determine nutritional health. It is for this reason that ANSI implicated such a large number of participants at high risk (n = 41), compared to the actual number of participants classified as undernourished (n = 11).
Although ANSI does not distinguish between weight gain and loss, a third of participants having weight change of at least five kilograms in the preceding six months is of concern. The prevalence of unintentional weight change in this study (31%) was almost double that of a previous study of older Adelaide residents (28). In the elderly, unintentional weight loss is perhaps the most established indicator of nutritional risk. Evidence has shown that weight loss over time, regardless of baseline BMI, is related to poor physical function and decline in mobility (20), and this in turn is likely to influence falls risk. Consequently, in the Falls Clinic, establishing a patient's weight history is equally important as knowing current weight and height. As this was a small cross-sectional study the anthropometric measurements, while a valuable tool, did not provide information on change over time. Caution is required when relying on self-reported weight change, as it can be affected by recall bias. As patients often return to the Falls Clinic for a review appointment, this provides an opportunity to measure weight and to monitor change.
Using BMI in combination with either MAC or TSF we found that the number of study participants classified as undernourished was much less than anticipated. MAC and TSF are indicators of muscle mass and body fat stores respectively and were used with BMI as an indicator of undernutrition, as BMI alone is not considered a sensitive indicator (31). It is well documented that patients at risk of falls are often those who fracture and these in turn are patients often identified as nutritionally depleted (13-15). One possible explanation for the low number of 'undernourished' patients in our study may be that the very frail or ill patients did not attend their appointment. For this reason the patients attending the Falls Clinic may have been less likely to be undernourished compared to those who did not attend their scheduled appointment. Though the results presented in this paper are a reflection of the older adults attending the Falls Clinic (consecutive sample and 74% consent rate), we are unable to establish wh ether the results are a true representation of those actually referred to the Falls Clinic.
One in five of our sample had a BMI greater than 30 kg/[m.sup.2]. There is evidence to suggest that a high BMI is associated with relative immobility (18-20), osteoarthritis (21) and an increased tendency to fall (22). Unintentional weight loss in older adults might not be desirable, even for those with a high BMI (20,34). We cannot find any evidence to suggest that intentional weight loss would be either protective or detrimental in relation to subsequent falls risk, despite evidence suggesting weight loss improves physical function in other patient groups (35). Further research to determine the benefits of a planned weight-loss program in these types of patients is warranted.
While height and weight are routinely measured in our clinic on the initial visit, BMI is not routinely reported or weight monitored, suggesting that interpretation may be lacking. Indeed only one study participant was referred for further nutritional assessment and this was initiated by the patient. Thus it seems that in our clinic nutritional health is unrecognised or not seen as an important factor in the management of older adults who have had falls. A recent review of Australian falls clinics by Hill et al. (23) has documented very few falls clinics routinely undertake nutritional assessment of their patients. Of those falls clinics that do, one clinic used ANSI to assess nutritional risk, one clinic used BMI and two clinics used 'other' nutritional assessment tools that were not specified (23). Interpretation of these nutritional assessment tools and the management of patients identified as being nutritionally 'at risk' were not considered in the review.
Diagnosis of undernutrition is multifactorial and should not be based simply on one nutritional parameter. Although in our study we used a definition of undernutrition that included BMI and MAC or TSF, which is consistent with definitions used in other studies (31), all those participants with a BMI less than 22 kg/[m.sup.2] also had a MAC or TSF less than the 15th percentile, suggesting BMI alone may be sufficient. Weight and height measurements are quick, easy and inexpensive and BMI appears to identify patients that are at the lower end of the distribution for other anthropometric indicators. Caution should be taken when using height measurements in older adults due to loss of height with advancing age. However, currently there are no Australian-specific regression equations to estimate stature using alternative methodologies (for example, demi-span or knee height).
The results of this study have shown that a substantial number of older adults susceptible to falling are at risk of poor nutritional health. The results also highlight the most common risk factors influencing poor nutritional health and the limited nutritional management of this population. Currently there is inconsistency and lack of nutritional assessment between Australian falls clinics and no available evidence of nutritional interventions improving the risk of falls. Yet while weight and height are routinely collected in our Falls Clinic and the possibility to monitor weight is available, there is also an opportunity to raise awareness of the nutritional health of these patients. Weight loss affects function and in other overweight patient groups weight loss improves function. Therefore, educating practitioners in the importance and interpretation of these measurements can only be of benefit to patients. We plan to continue our work in the area of falls and nutrition by prospectively examining outcomes of participants from this study.
[FIGURE 1 OMITTED]
Table 1 Descriptive characteristics of the 90 study participants attending the Repatriation General Hospital Falls Clinic between 23 April and 27 September 2001 Male Female Total P value (a) (n = 40) (n = 50) (n = 90) Age 0.93 65-74 years 6 8 14 75-84 years 23 30 53 85 years and over 11 12 23 Marital status <0.001 Married 30 13 43 Not married 10 37 47 Accommodation 0.84 Community 38 47 85 Residential care 2 3 5 Number of falls in 0.61 previous 12 months No falls 1 2 3 One fall 8 7 15 Multiple falls 26 39 65 Unknown 5 2 7 (a)Comparison between genders using chi-square test of significance Table 2 Distribution of nutritional health risk as assessed by Australian Nutrition Screening Initiative (ANSI) for 90 participants attending the Repatriation General Hospital Falls Clinic between 23 April and 27 September 2001 Male (b) Female (c) Total (d) ANSI nutritional score (a) (n = 40) (n = 50) (n = 90) (%) Low (0-3) 10 12 22 (25) Moderate (4-5) 16 11 27 (30) High (6 or more) 14 27 41 (45) (a)ANSI nutritional score (36) (b)ANSI nutritional score 5.4 [+ or -] 2.5 (mean [+ or -] SD) (c)ANSI nutritional score 6.3 [+ or -] 3.2 (mean [+ or -] SD) (d)ANSI nutritional score 5.9 [+ or -] 2.9 (mean [+ or -] SD) Table 3 Anthropometric measurements for participants attending the Repatriation General Hospital Falls Clinic between 23 April and 27 September 2001. Values are n unless otherwise stated. Male Female (n = 40) (n = 50) BMI Mean [+ or -] SD kg/[m.sup.2] 25.9 [+ or -] 3.8 26.7 [+ or -] 4.3 < 22 5 6 22-30 28 34 > 30 7 10 Mid-upper arm circumference Mean [+ or -] SD (cm) 27.0 [+ or -] 3.0 26.7 [+ or -] 3.3 < 15th percentile (b) 16 15 Triceps skinfold thickness Mean [+ or -] SD (mm) 12.5 [+ or -] 4.1 17.1 [+ or -] 4.0 < 15th percentile (c) 6 10 Classified as undernourished (d) 5 6 Total P value (a) (n = 90) BMI Mean [+ or -] SD kg/[m.sup.2] 26.3 [+ or -] 4.1 0.64 < 22 11 22-30 62 > 30 17 Mid-upper arm circumference Mean [+ or -] SD (cm) 26.9 [+ or -] 3.2 0.60 < 15th percentile (b) 31 0.36 Triceps skinfold thickness Mean [+ or -] SD (mm) 15.0 [+ or -] 4.6 < 0.001 < 15th percentile (c) 16 0.51 Classified as undernourished (d) 11 0.94 (a)Comparison between genders using chi-square test of signification and independent samples t-test. (b)Australian Longitudinal Study of Agein (32), males 26.2 cm, females 25.2 cm. (c)Australian Longitudinal Study of Ageing (32), males 7.9 mm, females 13.5 mm. (d)BMI<22 kg/[m.sup.2] and mid-upper arm circumference < 15th percentile or triceps skinfold thickness < 15th percentile.
We wish to acknowledge the staff of the Repatriation General Hospital Fall and Injury Risk Assessment Clinic for their time and patience during the data collection period. Our many thanks to the clinic patients for giving up their time and providing data for this project. Thanks also to the reviewers for their time and expertise in reviewing this paper.
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Flinders University Department of Rehabilitation and Aged Care, Repatriation General Hospital, Adelaide, South Australia
D. Stolz, BA/BSc, MNutDiet, Dietitian
M. Miller, BSc, MNutDiet, PhD candidate
C. Whitehead, BMBS(Hons) FRACP, Consultant Geriatrician
M. Crotty, BMed, MPH, PhD, FAFRM(RACP), Head Department of Rehabilitation and Aged Care
Nutrition Unit, Flinders University of South Australia, Adelaide
E. Bannerman, BSc(Hons), PhD, SRD, Lecturer
L. Daniels, BSc, GradDipNutDiet, MSc, PhD, GradCertTertEduc, Associate Professor
Correspondence: M. Crotty, Department of Rehabilitation and Aged Care, Repatriation General Hospital, Daws Road, Daw Park SA 5041. Email: email@example.com
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|Publication:||Nutrition & Dietetics: The Journal of the Dietitians Association of Australia|
|Date:||Dec 1, 2002|
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