Mini Nutritional Assessment and Short-form Mini Nutritional Assessment can predict the future risk of falling in older adults--Results of a national cohort study
Alan C. Tsai1,2*, Mei-yen Lai3
1Department of Healthcare Administration, Asia University, Taichung 41354, Taiwan 2Department of Health Services Management, School of Public Health, China Medical University, Taichung 40402, Taiwan
3Nursing Department, Taichung Veterans General Hospital, Taichung, Taiwan
*Corresponding author: Alan C. Tsai, Ph. D., Professor
Dept. of Healthcare Administration, Asia University, 500 Liufeng Rd., Wufeng, Taichung 41354, Taiwan
Tel: 886 4 2332 3456 x1943, Fax: 886 4 2332 1206. E-mail: atsai@umich.edu
Short title: MNA predicts the risk of falling
Contact list:
Tsai AC: Dept. of Healthcare Administration, Asia University, 500 Liufeng Rd., Wufeng, Taichung 41354, Taiwan; Tel: 886 4 2332 3456 x1943, Fax: 886 4 2332 1206. E-mail:
atsai@umich.edu
Lai MY: Nursing Department, Taichung Veterans General Hospital, Taichung, Taiwan; e-mail: bs88877@yahoo.com.tw 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Non-standard abbreviations: CC: calf circumference
MAC: Mid-arm circumference MNA: Mini-Nutritional Assessment
MNA-SF: Short-form Mini-Nutritional Assessment T1: Taiwan version-1
T2: Taiwan version-2
TLSA: Taiwan Longitudinal Survey on Aging 24 25 26 27 28 29 30 31
Abstract
Background & Aims: Falling is a major issue in geriatric health. Tools that identify individuals at risk of falling can help reduce the risk of falling. The study aimed to determine whether the full and short-form-Mini-Nutritional Assessments, two nutritional risk-screening tools, have the ability to predict the risk of falling in older adults.
Methods: Subjects were 3,118 ≥53-year old Taiwanese who completed both the 1999 and 2003 “Taiwan Longitudinal Study on Aging” surveys. We rated these subjects with normalized versions of these scales and applied the standard cut-offs to define under-nutrition (≤23.5 and ≤11 points, respectively). We used multivariate logistic regression analysis to evaluate the ability of these tools to predict the risk of falling three years later.
Results: Older adults rated as at risk of malnutrition with the full scale (OR=1.87, 95% confidence interval= 1.33-2.63, p <0.001) or the short-form (1.39, 1.07-1.80, p=0.014) were associated with increased risk of falling three years later. Both versions significantly predicted the risk of falling and performed slightly better ≥65 years old persons than in the middle-aged (50-64 years old) persons. The short-form performed relatively well compared to the full scale. Conclusions: Results suggest that the full and short-form-Mini-Nutritional Assessments, in addition to rating the risk of malnutrition, also predict the risk of falling in older adults. Although the short-form is slightly less effective than the full scale in predicting the future risk of falling, its simplicity, effectiveness and efficiency make it ideal as a multipurpose screening tool in geriatric clinical settings.
Keywords: elderly; falling, malnutrition; Mini-Nutritional Assessment; predicting falls 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53
Introduction
Falls are a major issue in geriatric health. Falls can often lead to bodily injuries, physical functional disability, cognitive impairment, institutionalization or even death.1,2 Falls also often affect psychological health. Elderly who experienced falling are less likely to go out and may become physically dependent. The cause of falling is complex and multi-factorial.3 People who have multiple risk factors such as physical functional impairment, poor visual acuity, cognitive impairment, frailty, general weakness, postural hypotension or psychotropic medication have increased risk of falling.3-6 Poor nutrition, especially protein-energy malnutrition (PEM), that contributes to general weakness or frailty, also increases the risk of falling.7,8
PEM is common in the elderly and it often accelerates loss of muscle mass, weakens muscle strength or the ability to maintain balance.9 PEM or malnutrition often develops
inconspicuously. It may not be noticed unless screened or examined. Thus, nutrition screening is a necessary step in identifying those who are at risk of malnutrition for early intervention.
The Mini Nutritional Assessment (MNA) is a simple, non-invasive and efficient tool designed for assessing/screening the risk of malnutrition in elderly adults.10,11 It consists of 18 items, and rates anthropometric, dietary, global and self-viewed aspects of nutrition. MNA has a simplified short-form (SF) consisting of 6 key MNA items.12,13 Both scales are multifunctional, and have been reported to predict hospital length of stay, hospitalization outcome, physical functional status and mortality.14-16 Both MNAs include items that assess mobility, weight loss, and dementia that are associated with the risk of falling. Thus, in theory, the scale should be able to predict the risk of falling. Recent studies also have shown that elderly who have poorer
nutritional status have higher risk of falling.1,8,17,18 However, the ability of the MNAs to predict the risk of falling has not been robustly examined in a large prospective study. Thus, the present 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77
study was conducted to examine the abilities of the MNA and the MNA-SF in predicting the future risk of falling in a large sample of older Taiwanese.
Materials and Methods
Source of data
The study analyzed datasets of the “Taiwan Longitudinal Survey on Aging” (TLSA), a population-based cohort study conducted by the Bureau of Health Promotion of Taiwan.19 The survey employed a multi-stage sampling process to draw a population-representative sample of 4,412 ≥60 year-old Taiwanese men and women from non-institutionalized citizens, and 4,049 of these participants completed the initial survey in 1989 (Fig. 1). The cohort was surveyed every 3 or 4 years. In 1996, a second sampling of 2,462 persons, 50-66 years old, drawn with the same methods, was added to the cohort to extend the age range of the cohort. Subjects in the combined cohort were interviewed in 1999 and 2003. The 1999 survey had expanded survey on food intake and included items in the MNA. Thus, the 1999 dataset was chosen as baseline for the present study and the 2003 survey as end point.
In each survey, trained interviewers conducted face-to-face interviews using a structured questionnaire at respondents' residence. In 1999, 4,440 of the combined cohort were successfully interviewed; in 2003, 3,778 were successfully interviewed. Among these subjects, 3,656
completed both surveys (Fig. 1).
The TLSA survey from which the present study is based upon was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects/patients were approved by government-appointed representatives. A detail of survey design and procedure has been described.20
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The outcome measure
The outcome measure was the incidence of falling during the 12-month period prior to the time of the questionnaire interview according to the question "Did you have any fall during the past 12 months?" Those who answered "yes" were considered having fallen for that year regardless of the number of falls.
Rating the baseline nutritional status
We used a normalized and slightly modified MNA (Taiwan version-2, T2) and its short-form (SF), to rate the baseline nutritional status of the participants.21,22 The MNA-T2 was derived from Taiwan version-1 (T1), which was normalized from the original MNA by adopting the population-specific anthropometric cut-off points and dietary features.23 The MNA-T2 further replaced CC and MAC for BMI item in full MNA, and CC for BMI in MNA-SF by transferring 1 of the 3 BMI points to the MAC item and 2 to the CC item.23,24 Therefore, the MNA-T2 is based on 17, rather than 18 items but has the same total score (30 points). The MNA-T2 has been shown to perform at least as well as the MNA-T1.24 With the exception of fluid intake, all items in the MNA were available in the questionnaire. Thus, grading with the MNA-T2 was based on 16 items and the total score was proportionately adjusted to a 30-point basis. A total score <17 was considered as malnourished; 17-23.5, as at risk of malnutrition; ≥24, as normal. The MNA-T2-SF is similar to the original MNA-SF, except item F (BMI) was replaced by item R (CC). A total score ≤7 was considered as malnourished; 8-11, as at risk of malnutrition, and ≥12, as normal.12
Other variables
All other variables were derived from the 1999 datasets. Alcohol drinking status was classified as non-drinker, drinking <1 time/wk, and >1 time/wk; cigarette smoking as never 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123
smokers, current smokers and past smokers; and betel nut chewing was classified as no chewers, current chewers and past chewers. Routine physical activity was classified according the number of times performing physical exercise >30 minutes/day. Body mass index (BMI) was calculated according to kg (weight)/m2 (height). The status of chronic diseases/conditions including
hypertension, diabetes, heart disease, stroke, osteoarthritis, gout, hip fracture, lower-back pain, visual acuity, hearing ability and incontinence was based on self-reported but physician
confirmed answers to each of the specific diseases/conditions.
Statistical analysis
All statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS version 18.0. Chicago, IL). Simple statistics were used to compute descriptive data. Multivariate logistic regression analysis was performed to determine the ability of the baseline nutritional status rated with the MNA and MNA-SF to predict the risk of falling three years later, controlled for confounding factors as indicated in footnote to Table 3. The regression models included all 3,656 subjects who completed both 1999 and 2003 surveys. After excluding those without BMI data (246), fall data (119) and other data (173), the net N was 3,118 (Fig. 1). The analysis was weighting-adjusted according to sampling ratio of each sampling. The ability of baseline nutritional status rated with the MNA or MNA-SF in predicting falling three years later was evaluated with Receiver-Operating Characteristic (ROC) analysis. Statistical significance for all analyses was set at α = 0.05.
Results
Table 1 shows the characteristics of subjects at baseline. Of 4,440 subjects who
completed the 1999 survey, 4,124 had complete data and were the subjects for this analysis. The 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146
sample included slightly more men (53.3%) than women. Most (71.2%) subjects had ≤6 years of formal education; 83% were 19-27 kg/m2; 24.5% were current smokers; 24.7% drank ≥ 1/wk; 52.3% exercised ≥3 times/wk; and 15.8% experienced one or more falls during the past 12 months.
Table 2 shows subjects' MNA item-scoring patterns. About 8.1% of subjects had poor appetite; 13.9% lost weight unexpectedly; 9.3% had psychological stress; 13,3% had pressure sore/skin lesion; 12.2% had inadequate intake of protein foods; 6.6% had inadequate
fruit/vegetable intake; 16.2% had poor self-rated nutritional status; and 41.3% had poor self-rated health. According to MNA-T2, 10.6% were at risk of under-nutrition (MNA score <24) and 89.4% were normal (MNA score ≥24). According to MNA-T2-SF 17.9% were at risk of under-nutrition (MNA-SF score ≤11) and 82.1% were normal (MNA score ≥12).
Table 3 shows the ability of the nutritional status rated with the MNA and MNA-SF in predicting falling three years later in older Taiwanese according to multivariate binary logistic regression models, respectively. Results showed that subjects who were rated as at risk of malnutrition (malnourished and at risk of malnutrition) at baseline were 87% more likely to have falling three years later according to the full-MNA (OR=1.87, 95% confidence interval=1.33-2.63, p<0.001), and 39% more (1.39, 1.07-1.80, p = 0.014) according to MNA-T2-SF. Both models were controlled for the same socio-demographic, lifestyle and health-related variables.
Fig. 1 shows the flowchart of the Taiwan Longitudinal Survey on Aging (TLSA). Fig. 2 shows the Receiver Operating Characteristic (ROC) curves for the MNA-T2 and MNA-T2-SF in 3,118 ≥53-year old Taiwanese stratified by age (53-64 vs. ≥65-year old). For subjects ≥65 years old (Chart A), the area under the curve (AUC) and 95% confidence interval (95%CI) = 0.635 (0.609-0.660), p<0.001, sensitivity = 0.659 and specificity = 0.548 for MNA-T2; and AUC 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169
95%CI = 0.597 (0.570-0.624), p<0.001, sensitivity = 0.504 and specificity = 0.680 for MNA-T2-SF. For subjects <65 years old (Chart B), the respective values were 0.637(0.588-0.685),
p<0.001, 0.720 and 0.498 for MNA-T2; 0.566 (0.514-0.618), p = 0.010, 0.329 and 0.806 for MNA-T2-SF.
Discussion
MNAs predict the risk of falling
Results show that both the MNA and MNA-SF significantly predicted the risk of falling 4 years later in old Taiwanese. Several studies have suggested an association between nutritional status and the risk of falling in older persons. Salvi et al.25 observed that the MNA-SF could identify those with poor clinical outcome and predicted functional decline which is a risk factor of felling in older persons.26,27 Salva et al.1 analyzed the risk factors for falls in community-dwelling adults with dementia and found that fallers had worse nutritional status according to the MNA and worse basic activities of daily-living dependency. Andre et al.17 graded the nutritional status of community-dwelling elderly and found that those who had a fall history had lower MNA score compared with those who did not (MNA score 18.3 vs. 21.0). In a cross-sectional study, Neyens et al.18 found that malnutrition is associated with an increased risk of falling and impaired physical activity in Dutch long-term care residents. These results suggest an association between nutritional status (as rated with the MNA) and the risk of falling in older persons. The present has added further evidence that the MNAs are able predicting the future risk of falling in a large prospective study involving older Taiwanese.
The impact of malnutrition on the risk of falling
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Malnutrition in the elderly usually develops inconspicuously and slowly over a period of years. In a 10-year longitudinal study, Vellas et al.28 observed that the decrease in nutritional intake occurs before hospitalization or clinical disease in elderly patients, and long before the decrease of weight or albumin. Chronic PEM can lead to sarcopenia and osteoporosis, conditions that increase the risk of falling, bone fracture, immobility, and even premature death.9 Vivanti et al.8 examined the association between nutritional status and falls in hospitalized people and found that people who were rated as malnourished had reduced mobility and poorer nutritional status. Zoltick et al.29 found that older men and women who had lower dietary protein intake were associated with higher subsequent falls. Thus, poor nutrition is a risk factor for falling. Early detection of changes in nutritional status is essential for instituting a feeding program.
We have found that older adults who are rated as at risk of malnutrition by the MNA or the MNA-SF have increased future risk of falling and the present study is the first to observe this MNA capability in a large population-based sample. It is particularly important to note that the MNA-SF is quite effective in predicting the risk of falling even three years later. It is probable that the short-term predictive ability would be much stronger. Unfortunately, because the TLSA survey collects data only every three years, we are not able to analyze the shorter-term predictive ability.
We also found that both MNAs are slightly better in predicting the risk of falling in older (≥65-year old) persons than in middle-aged (50-64-year old) persons. This could be due to the fact that older people have higher risk of malnutrition. On the other hand, it is clinically
important to observe that the MNA-SF performs relatively well in both age groups compared to the full MNA. The MNA-SF consists only 1/3 of the items (6 vs.18) and takes about 1/3 of the time (5 vs. 15-20 min) to complete the screening process compared to the full MNA. These 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214
features make the MNA-SF a more acceptable screening tool for routine clinical application than the full MNA. Those who are identified as at risk of malnutrition should be further evaluated for the risk of falling and be given proper intervention.
The MNA and MNA-SF are multi-functional scales
It appears that the MNA and the MNA-SF have multifunctional properties, presumably because both scales include items that reflect functional, mental, neuropsychological, and general health conditions. The MNA and especially the MNA-SF (because of its simplicity effectiveness and efficiency) appear to be well suited to serve as a general screening tool for identifying at risk individuals for nutritional support or fall prevention.14 It is possible that with further
improvements, the MNA-SF can be developed into a simple, effective and efficient multi-purpose screening tool. With the rapid increase in most elderly populations around the world, such a tool would seem to be particularly welcome in both clinical and community settings.
Limitations of the study
The study has some limitations. (a) The survey was carried out every three years and the incidence of falling was for the past 12 months. Thus, no data were available for the years immediately following the baseline survey. It is most probable that the predictive ability would be even better for those immediate follow-up years. (b) Data from surveys are generally "self-report". Self-reports have acceptable accuracy in general, but inaccurate recalls are unavoidable. (c) The present study did not attempt to analyze those who had multiple falls vs. those who had only one during the specific year. (d) The study excluded those subjects who had no data on BMI, falling, or other variables. It is probable that these individuals could have some impact on the overall results.
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Conclusion
Results suggest that older adults who are rated as at risk of malnutrition by the full-MNA or MNA-SF have increased risk of falling three years later, suggesting that the MNA and its short-form are capable of predicting future risk of felling in the elderly. These results underscore the multifunctional nature of the MNA and MNA-SF, However, because of the simplicity, effectiveness, efficiency and non-invasiveness, the MNA-SF appears to be a more useful tool than the full MNA in clinical and community settings.
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Acknowledgments
This study is based on data from the “Taiwan Longitudinal Study on Aging" (TLSA), conducted by the Bureau of Health Promotion of Taiwan. Descriptions or conclusions herein do not represent the viewpoint of the Bureau.
Statement of authorship:
ACT conceived the idea, directed the study, and drafted the manuscript; MYL performed the statistical analysis and reviewed the manuscript.
Conflict of interest statement:
No potential conflicts of interest were disclosed.
Sources of funding:
The study received no financial support from any source. 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264
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Legend to figures:
Figure 1. Flowchart of the Taiwan Longitudinal Survey on Aging (TLSA), the data source of the present study.
Figure 2. Receiver Operating Characteristic (ROC) curves for the full- and short-form-Mini Nutritional Assessment Taiwan Version-2 (MNA-T2 and MNA-T2-SF) in a national cohort of 3,118 male and female ≥53 years old Taiwanese. For subjects ≥65 years old (Chart A), the area under the curve (AUC) and 95% confidence interval (95%CI) = 0.635 (0.609-0.660), p<0.001, sensitivity = 0.659 and specificity = 0.548 for MNA-T2; and AUC 95%CI = 0.597 (0.570-0.624), p<0.001, sensitivity = 0.504 and specificity = 0.680 for MNA-T2-SF. For subjects <65 years old (Chart B), the respective values were 0.637(0.588-0.685), p<0.001, 0.720 and 0.498 for MNA-T2; 0.566 (0.514-0.618), p = 0.010, 0.329 and 0.806 for MNA-T2-SF.
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