ABSTRACT
Background
Malnutrition is common among older adults and is associated with adverse outcomes, yet its impact and relationship with geriatric vulnerability in emergency department (ED) patients remain underrecognized.
Objectives
To determine the prevalence, associated factors, and prognostic impact of malnutrition in noncritically ill older adults in the ED.
Methods
We conducted an observational study of patients aged ≥ 65 years presenting to the ED. Nutritional status was assessed using the Mini Nutritional Assessment–Short Form (MNA‐SF) and categorized as normal, at risk of malnutrition, or malnourished. Comprehensive geriatric assessment included functional status (activities of daily living (ADL)), frailty, cognitive function, and handgrip strength. Multivariable logistic regression identified factors associated with malnutrition. Kaplan–Meier survival analysis and multivariable Cox proportional hazards regression were performed to evaluate the association between nutritional status and 30‐ and 90‐day all‐cause mortality.
Results
Among 1487 patients, 23.3% were malnourished and 46.4% were at risk, with 59.7% overall having impaired nutritional status. Malnourished patients had significantly worse functional status, cognition, and physical performance. Independent factors associated with malnutrition included lower ADL, frailty, and decreased handgrip strength. Malnutrition was associated with significantly lower 30‐ and 90‐day survival (both log‐rank p < 0.001) and remained independently associated with both 30‐day mortality (adjusted HR, 5.32; 95% CI, 1.36–20.73) and 90‐day mortality (adjusted HR, 6.92; 95% CI, 2.16–22.13) after multivariable adjustment.
Conclusions
Malnutrition is highly prevalent among older ED patients and is independently associated with increased short‐term mortality. Functional decline, frailty, and reduced muscle strength are closely linked to both malnutrition and nutritional risk. Integrating nutritional screening with functional and physical assessment in the ED may improve early identification of high‐risk patients and support timely interventions.
Keywords: activities of daily living, emergency department, frailty, handgrip strength, malnutrition, mortality, older adults
1. Introduction
Population aging has become a major global public health challenge, particularly in East Asia, where several countries have already entered or are approaching a super‐aged society, defined as having more than 20% of the population aged 65 years or older. Recent demographic trends indicate that countries in this region, including Taiwan, have reached or are expected to reach this threshold by 2025, reflecting rapid population aging and increasing healthcare demands [1]. As the proportion of older adults increases, age‐related conditions such as frailty, multimorbidity, and malnutrition are expected to become more prevalent, further increasing the burden on acute care systems such as the emergency department (ED).
Malnutrition is a prevalent and clinically significant condition among older adults, associated with increased mortality, prolonged hospital stay, and functional decline. In hospitalized populations, the prevalence of malnutrition has been reported to range from 40% to 55%, with consistent evidence linking poor nutritional status to adverse outcomes, including increased mortality and healthcare utilization [2].
Malnutrition is also common in community‐dwelling older adults, with an estimated prevalence ranging from 10% to 30%, even among free‐living populations with or without formal care services [3]. In addition, population‐based studies have demonstrated that approximately 8% of community‐dwelling older adults are malnourished and nearly 30% are at risk of malnutrition [4]. Importantly, malnutrition in the community is frequently underrecognized and is closely associated with frailty, functional decline, and cognitive impairment, suggesting shared underlying mechanisms and progressive deterioration over time [4].
In the emergency department (ED), older adults represent a particularly vulnerable population characterized by multimorbidity, frailty, cognitive impairment, and functional dependence. These factors place them at high risk for malnutrition and its consequences. Previous studies have reported that malnutrition affects approximately 10% to 30% of older adults presenting to the ED, with up to one‐third classified as malnourished or at risk [5, 6, 7]. Notably, the proportion of older adults with impaired nutritional status identified in the ED is often higher than that observed in community‐based studies. For example, prior studies have reported malnutrition rates of approximately 16%–18% among older ED patients aged ≥ 65–75 years [8]. This higher prevalence likely reflects the accumulation of frailty, acute illness, and functional decline at the time of ED presentation.
Despite this high prevalence, malnutrition remains substantially underrecognized in routine ED practice, with only a small proportion of patients receiving a formal diagnosis [9]. Given its accessibility and role as a point of acute care contact, the ED may serve as a critical setting for identifying previously unrecognized malnutrition and initiating timely interventions. The ED therefore represents a critical transition point where malnutrition becomes clinically evident and actionable.
Emerging evidence suggests that malnutrition is a strong predictor of adverse outcomes in the ED setting. Prospective studies have demonstrated that malnutrition is independently associated with short‐term mortality, with markedly increased risk within the first few months following an ED visit [10]. In addition, malnutrition has been linked to higher rates of hospitalization, readmission, and increased healthcare costs [9]. These findings highlight the potential importance of early identification and intervention in the ED.
Although previous studies have described the prevalence and prognostic significance of malnutrition among older adults in the ED, relatively few have comprehensively evaluated its relationships with multidimensional geriatric assessments, including functional status, frailty, cognitive function, and muscle strength, within a large cohort of non‐critically ill older ED patients.
Therefore, this study aimed to characterize the prevalence of malnutrition, identify geriatric factors associated with nutritional impairment, and evaluate its association with short‐term outcomes in older adults presenting to the ED.
2. Method
2.1. Study Design and Setting
This observational study was conducted in the emergency department (ED) of Taipei Veterans General Hospital, a tertiary medical center with an annual ED census of approximately 83,000 visits. Taiwan's National Health Insurance program provides universal healthcare coverage for more than 99% of the population and allows direct access to emergency departments without referral. Consequently, the ED serves as a major point of access to acute care for older adults, providing an important opportunity for early identification of geriatric syndromes such as malnutrition. The study protocol was reviewed and approved by the Institutional Review Board of Taipei Veterans General Hospital (approval numbers: 2018‐03‐011CC and 2021‐07‐025 AC).
Patients were enrolled from August 2018 to May 2022. Only the first ED visit during the study period was included for each participant.
2.2. Study Population
Patients were eligible for inclusion if they met the following criteria: (1) aged ≥ 65 years; (2) admitted to the ED observation room; (3) in stable clinical condition; (4) awaiting hospital admission or further diagnostic evaluation; and (5) able and willing to provide written informed consent.
Patients were excluded if they met any of the following criteria: (1) inability to complete the assessment due to critical illness or trauma; (2) diagnosis of malignancy within the previous 3 years with unstable disease status, including those receiving active cancer treatment or requiring palliative care; (3) autoimmune disease requiring ongoing immunosuppressive therapy; (4) inability to complete laboratory or physiological assessments; or (5) inability to participate in follow‐up.
2.3. Data Collection and Geriatric Assessment
All participants underwent a comprehensive geriatric assessment (CGA) performed by trained research nurses. Demographic and clinical data collected included age, educational level, marital status, smoking status, body mass index (BMI), Charlson comorbidity index (CCI) [11], and polypharmacy (defined as the use of more than four medications for longer than 2 weeks). Mobility difficulties were assessed by trained research nurses through structured interviews and defined as self‐reported difficulty in independent ambulation during the 2 weeks preceding the ED visit. Participants were categorized as having or not having mobility difficulties.
Cognitive function was assessed using the Chinese version of the Mini‐Mental State Examination (MMSE), with cognitive impairment defined as a score < 24 [12]. Depressive symptoms were evaluated using the 5‐item Geriatric Depression Scale (GDS‐5), with a score ≥ 2 indicating depression [13]. Pain severity was assessed using a visual analog scale [14]. Functional status was evaluated using the Barthel Index for activities of daily living (ADL) [15], while instrumental activities of daily living (IADL) were assessed using the Lawton instrumental activities of daily living scale [16]. Both assessments were conducted by trained research nurses through structured interviews and reflected the participants' usual functional status during the 2 weeks preceding the ED visit.
Frailty was assessed using the fried frailty phenotype [17], which includes five domains: unintentional weight loss, weakness (grip strength), exhaustion, low physical activity, and slow walking speed. Although handgrip strength is one component of the fried frailty phenotype, it was also analyzed separately because it is an objective measure of muscle strength that has been independently associated with adverse clinical outcomes in older adults.
2.4. Nutritional Assessment
Nutritional status was assessed using the Mini Nutritional Assessment Short‐Form (MNA‐SF) [18]. Patients were categorized into three groups based on their scores: normal nutritional status (≥ 12), at risk of malnutrition (8–11), and malnutrition (< 8).
2.5. Outcome Measures
The primary outcome was 30‐ and 90‐day all‐cause mortality following the ED visit. Mortality data were obtained from electronic health records or through telephone follow‐up with patients or their relatives.
2.6. Statistical Analysis
Continuous variables are presented as mean ± standard deviation, and categorical variables as counts and percentages. Comparisons between groups were performed using the Student's t‐test for continuous variables and the chi‐square test or Fisher's exact test for categorical variables, as appropriate. Variables with < 0.01 in univariate analysis were entered into a multivariable logistic regression model using a backward stepwise approach to identify independent predictors. All statistical analyses were performed using IBM SPSS Statistics for Windows, version 21.0 (IBM Corp., Armonk, NY, USA). A two‐sided p < 0.05 was considered statistically significant.
3. Results
3.1. Patient Characteristics
A total of 1487 older adults aged ≥ 65 years were enrolled in the ED observation room between August 2018 and May 2022 (Figure 1). Based on the Mini Nutritional Assessment Short‐Form (MNA‐SF), patients were categorized into three groups: normal nutritional status (n = 450, 30.3%), at risk of malnutrition (n = 690, 46.4%), and malnutrition (n = 347, 23.3%). Overall, 59.7% of patients had impaired nutritional status. As shown in Table 1, patients in the malnutrition group had significantly lower educational levels and were more likely to have different living arrangements compared with the other groups (both p < 0.01).
FIGURE 1.
Flow diagram of the study population.
TABLE 1.
Baseline demographic and social characteristics of study participants stratified by nutritional status (normal nutrition, at risk of malnutrition, and malnutrition) based on the Mini Nutritional Assessment–Short Form (MNA‐SF).
| All (n = 1487) | Normal (n = 450) | At risk of malnutrition (n = 690) | Malnutrition (n = 347) | p | |
|---|---|---|---|---|---|
| Age (mean ± SD) | 82.7 ± 7.9 | 80.9 ± 7.9 | 83.2 ± 7.7 | 84.2 ± 7.7 | < 0.001 |
| Gender | |||||
| Male | 924 (62.1) | 289 (64.2) | 425 (61.6) | 210 (60.3) | 0.470 |
| Female | 563 (37.9) | 160 (35.6) | 265 (38.4) | 138 (39.7) | |
| Education level | 0.002 | ||||
| No formal | 182 (12.5) | 35 (7.9) | 88 (13.1) | 59 (17.5) | |
| Self‐study | 67 (4.6) | 15 (3.4) | 31 (4.6) | 21 (6.2) | |
| Elementary school | 485 (33.4) | 153 (34.6) | 229 (34.0) | 103 (30.5) | |
| Junior high school | 191 (13.1) | 58 (13.1) | 85 (12.6) | 48 (14.2) | |
| Senior high school | 252 (17.3) | 82 (18.6) | 110 (16.3) | 60 (17.8) | |
| University and above | 277 (19.1) | 99 (22.4) | 131 (19.4) | 47 (13.9) | |
| Marital status | 0.084 | ||||
| Single | 93 (6.3) | 17 (3.8) | 50 (7.3) | 26 (7.5) | |
| Married | 940 (63.4) | 303 (67.6) | 434 (63.0) | 203 (58.8) | |
| Separate | 11 (0.7) | 3 (0.7) | 5 (0.7) | 3 (0.9) | |
| Widowed | 398 (26.9) | 110 (24.6) | 181 (26.3) | 107 (31.0) | |
| Divorced | 40 (2.7) | 15 (3.3) | 19 (2.8) | 6 (1.7) | |
| Living floor | 0.471 | ||||
| First floor | 334 (22.5) | 92 (20.5) | 154 (22.4) | 88 (25.4) | |
| Second floor and above without elevator | 576 (38.9) | 186 (41.4) | 262 (38.1) | 128 (37.0) | |
| Elevator apartments | 572 (38.6) | 171 (38.1) | 271 (39.4) | 130 (37.6) | |
| Living arrangement | 0.007 | ||||
| Living alone | 185 (12.4) | 64 (14.3) | 73 (10.6) | 48 (13.8) | |
| With spouse | 230 (15.5) | 74 (16.5) | 117 (17.0) | 39 (11.2) | |
| With domestic helper | 55 (3.7) | 10 (2.2) | 27 (3.9) | 18 (5.2) | |
| With spouse & domestic helper | 31 (2.1) | 2 (0.4) | 19 (2.8) | 10 (2.9) | |
| With family | 821 (55.2) | 262 (58.4) | 371 (53.8) | 188 (54.0) | |
| With others | 7 (0.5) | 1 (0.2) | 4 (0.6) | 2 (0.6) | |
| Live in veterans home | 123 (8.3) | 31 (6.9) | 61 (8.8) | 31 (8.9) | |
| Live in nursing home | 35 (2.4) | 5 (1.1) | 18 (2.6) | 12 (3.4) |
Note: Data are presented as number (%) unless otherwise indicated. p values were calculated using the chi‐square test for categorical variables and one‐way analysis of variance (ANOVA) for continuous variables.
3.2. Clinical Characteristics
As shown in Table 2, the mean age of all participants was 82.7 ± 7.9 years, and patients in the malnutrition group were significantly older than those in the other groups (p < 0.001). Patients in the malnutrition group had significantly lower functional and cognitive performance, including lower ADL, IADL, and MMSE scores. They also had higher CCI and a higher prevalence of frailty, decreased handgrip strength, polypharmacy, mobility difficulties, recent weight loss (≥ 5 kg in the past year), and low physical activity (all p < 0.05).
TABLE 2.
Clinical characteristics, geriatric assessments, and functional measures of participants stratified by nutritional status.
| All (n = 1487) | Normal (n = 450) | At risk of malnutrition (n = 690) | Malnutrition (n = 347) | p | |
|---|---|---|---|---|---|
| Age (mean ± SD) | 82.7 ± 7.9 | 80.9 ± 7.9 | 83.2 ± 7.7 | 84.2 ± 7.7 | < 0.001 |
| CCI | 1.9 ± 1.7 | 1.6 ± 1.6 | 2.0 ± 1.7 | 2.3 ± 1.8 | < 0.001 |
| ADL | 79.6 ± 28.0 | 95.1 ± 9.5 | 79.8 ± 26.0 | 59.2 ± 34.3 | < 0.001 |
| IADL | 3.9 ± 2.7 | 5.3 ± 2.2 | 3.7 ± 2.6 | 2.4 ± 2.5 | < 0.001 |
| MMSE | 19.8 ± 6.1 | 23.3 ± 4.6 | 19.2 ± 5.8 | 15.9 ± 6.0 | < 0.001 |
| Frailty (%) | 711 (48.2) | 90 (20.0) | 348 (50.8) | 273 (80.1) | < 0.001 |
| Decreased handgrip strength | 1110 (77.7) | 261 (59.5) | 537 (81.5) | 312 (94.3) | < 0.001 |
| Male (kg) | 21.1 ± 8.3 | 25.6 ± 7.3 | 20.7 ± 7.9 | 15.6 ± 6.9 | < 0.001 |
| Female (kg) | 13.7 ± 5.5 | 16.7 ± 4.7 | 13.4 ± 5.2 | 10.7 ± 5.0 | < 0.001 |
| Polypharmacy (%) | 338 (23.5) | 73 (16.6) | 170 (25.6) | 95 (28.2) | < 0.001 |
| Mobility difficulties | 815 (55.1) | 158 (35.2) | 390 (56.9) | 267 (77.4) | < 0.001 |
| Fall in past year | 414 (27.9) | 86 (19.2) | 195 (28.3) | 132 (38.4) | < 0.001 |
| Weight loss ≥ 5 kg in past year | 237 (16.5) | 8 (1.8) | 88 (13.2) | 141 (43.8) | < 0.001 |
| Low physical activity | 929 (62.9) | 191 (42.5) | 445 (65.2) | 293 (85.9) | < 0.001 |
Note: Data are presented as mean ± standard deviation or number (%), as appropriate. p values were calculated using one‐way ANOVA for continuous variables and chi‐square tests for categorical variables. Data are presented as mean ± SD unless otherwise indicated. Polypharmacy score ≥ 5.
Abbreviations: ADL, activities of daily living; CCI, Charlson comorbidity index; IADL, instrumental activities of daily living; MMSE, mini‐mental state examination.
3.3. Clinical Outcomes
As shown in Table 3, patients in the malnutrition group had significantly higher rates of hospital admission, in‐hospital mortality, 30‐day mortality, 90‐day mortality, and hospital revisits within 90 days (all p < 0.05).
TABLE 3.
Disposition and clinical outcomes of study participants, including hospital admission, mortality, and hospital revisit rates, stratified by nutritional status.
| All (n = 1487) | Normal (n = 450) | At risk of malnutrition (n = 690) | Malnutrition (n = 347) | p | |
|---|---|---|---|---|---|
| Disposition after ED | < 0.001 | ||||
| ED discharge | 616 (41.4) | 214 (47.7) | 297 (43.0) | 105 (30.2) | |
| Hospital admission | 871 (58.6) | 235 (52.3) | 393 (57.0) | 243 (69.8) | |
| ICU admission | 37 (2.5) | 8 (1.8) | 18 (2.6) | 11 (3.2) | 0.442 |
| In‐hospital mortality | 46 (3.1) | 4 (0.9) | 12 (1.7) | 30 (8.6) | < 0.001 |
| Mortality within 30‐days | 35 (2.4) | 3 (0.7) | 11 (1.6) | 21 (6.0) | < 0.001 |
| Mortality within 90‐days | 87 (5.9) | 7 (1.6) | 28 (4.1) | 52 (14.9) | < 0.001 |
| Hospital revisit within 30‐days | 377 (25.4) | 101 (22.5) | 173 (25.1) | 103 (29.6) | 0.071 |
| Hospital revisit within 90‐days | 574 (38.6) | 151 (33.6) | 270 (39.1) | 153 (44.0) | 0.011 |
Note: Data are presented as number (%). p values were calculated using chi‐square tests.
3.4. Risk Factors for Malnutrition
To identify independent factors associated with malnutrition, variables with p < 0.01 in univariate analyses—including age, CCI, ADL, IADL, frailty, decreased handgrip strength, polypharmacy, mobility difficulties, history of falls in the past year, and low physical activity—were entered into multivariable logistic regression models using a backward stepwise approach (Tables 4 and 5).
TABLE 4.
Univariate and multivariable logistic regression analyses identifying factors associated with malnutrition (malnutrition group vs. normal nutrition group).
| Variable | Univariate | Multivariate | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p | OR | 95% CI | p | |
| Age | 1.06 | [1.037–1.075] | < 0.001 | 1.02 | [0.991–1.041] | 0.222 |
| CCI | 1.21 | [1.139–1.290] | < 0.001 | 1.07 | [0.988–1.157] | 0.099 |
| ADL | 0.93 | [0.914–0.936] | < 0.001 | 0.95 | [0.937–0.963] | < 0.001 |
| IADL | 0.63 | [0.592–0.673] | < 0.001 | 0.95 | [0.863–1.037] | 0.240 |
| Frailty | 15.74 | [11.080–22.354] | < 0.001 | 3.28 | [1.955–5.512] | < 0.001 |
| Decreased handgrip strength | 11.20 | [6.787–18.479] | < 0.001 | 2.56 | [1.437–4.551] | 0.001 |
| Polypharmacy | 1.97 | [1.393–2.781] | < 0.001 | 1.07 | [0.701–1.644] | 0.745 |
| Mobility difficulties | 6.31 | [4.587–8.665] | < 0.001 | 0.82 | [0.522–1.281] | 0.380 |
| Fall in past year | 2.63 | [1.908–3.620] | < 0.001 | 1.43 | [0.959–2.129] | 0.080 |
| Low physical activity | 7.61 | [5.367–10.793] | < 0.001 | 1.24 | [0.753–2.034] | 0.400 |
Note: Variables with p < 0.05 in univariate analysis were entered into multivariable logistic regression using a backward stepwise approach. Results are presented as odds ratios (ORs) with 95% confidence intervals (CIs).
Abbreviations: ADL, activities of daily living; CCI, Charlson comorbidity index; IADL, instrumental activities of daily living.
TABLE 5.
Univariate and multivariable logistic regression analyses identifying factors associated with being at risk of malnutrition (at risk of malnutrition group vs. normal nutrition group).
| Variable | Univariate | Multivariate | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p | OR | 95% CI | p | |
| Age | 1.04 | [1.022–1.054] | < 0.001 | 1.01 | [0.993–1.032] | 0.204 |
| CCI | 1.10 | [1.042–1.169] | 0.001 | 1.02 | [0.957–1.088] | 0.542 |
| ADL | 0.95 | [0.935–0.956] | < 0.001 | 0.96 | [0.952–0.977] | < 0.001 |
| IADL | 0.78 | [0.746–0.823] | < 0.001 | 0.95 | [0.891–1.020] | 0.168 |
| Frailty | 4.11 | [3.119–5.410] | < 0.001 | 1.74 | [1.187–2.556] | 0.005 |
| Decreased handgrip strength | 3.00 | [2.283–3.947] | < 0.001 | 1.60 | [1.165–2.206] | 0.004 |
| Polypharmacy | 1.72 | [1.268–2.338] | < 0.001 | 1.23 | [0.871–1.724] | 0.243 |
| Mobility difficulties | 2.43 | [1.898–3.102] | < 0.001 | 0.80 | [0.582–1.112] | 0.187 |
| Fall in past year | 1.67 | [1.252–2.226] | < 0.001 | 1.22 | [0.879–1.687] | 0.237 |
| Low physical activity | 2.54 | [1.986–3.239] | < 0.001 | 1.01 | [0.733–1.396] | 0.944 |
Note: Variables with p < 0.05 in univariate analysis were included in the multivariable logistic regression model. Results are presented as odds ratios (ORs) with 95% confidence intervals (CIs).
Abbreviations: ADL, activities of daily living; CCI, Charlson comorbidity index; IADL, instrumental activities of daily living.
Compared with participants with normal nutritional status, independent factors associated with malnutrition included frailty (odds ratio [OR], 3.28; 95% confidence interval [CI], 1.96–5.51; p < 0.001), lower ADL score (OR, 0.95; 95% CI, 0.94–0.96; p < 0.001), and decreased handgrip strength (OR, 2.56; 95% CI, 1.44–4.55; p = 0.001) (Table 4).
Among patients at risk of malnutrition, independent factors included frailty (OR, 1.74; 95% CI, 1.19–2.56; p = 0.005), lower ADL score (OR, 0.96; 95% CI, 0.95–0.98; p < 0.001), and decreased handgrip strength (OR, 1.60; 95% CI, 1.17–2.21; p = 0.004) (Table 5).
3.5. Survival Analyses
Kaplan–Meier survival curves stratified by nutritional status (Figure 2) demonstrated that patients with malnutrition had significantly lower survival probabilities than those with normal nutritional status and those with at risk of malnutrition. Significant differences in survival were observed at both the 30‐day (Figure 2A, log‐rank p < 0.001) and 90‐day follow‐up (Figure 2B, log‐rank p < 0.001).
FIGURE 2.
Kaplan–Meier survival curves stratified by nutritional status based on the mini nutritional assessment‐short form (MNA‐SF), including normal nutrition, at risk of malnutrition, and malnutrition groups. (A) 30‐day survival probability according to nutritional status. (B) 90‐day survival probability according to nutritional status. Patients with malnutrition had significantly lower survival probabilities than those with normal nutritional status and those at risk of malnutrition. Differences between groups were assessed using the log‐rank test (p < 0.001 for both comparisons).
To determine whether nutritional status was independently associated with short‐term mortality, multivariable Cox proportional hazards regression analyses were performed after adjustment for age, sex, CCI, frailty, and ADL. Compared with participants with normal nutritional status, malnutrition remained independently associated with both 30‐day mortality (adjusted HR, 5.319; 95% CI, 1.364–20.734; p = 0.016) and 90‐day mortality (adjusted HR, 6.916; 95% CI, 2.161–22.127; p = 0.001). In contrast, patients at risk of malnutrition were not independently associated with either 30‐ or 90‐day mortality after multivariable adjustment (Table 6A,B).
TABLE 6.
Univariate and multivariable Cox proportional hazards regression analyses of factors associated with 30‐ and 90‐day mortality.
| Predictive variables | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|
| HR (95% CI) | p | HR (95% CI) | p | |
| A | ||||
| Malnutrition status | ||||
| Normal | Reference | |||
| At risk of malnutrition | 1.713 (0.454–6.457) | 0.427 | 1.180 (0.296–4.701) | 0.815 |
| Malnutrition | 9.129 (2.701–30.849) | < 0.001 | 5.319 (1.364–20.734) | 0.016 |
| Age | 1.006 (0.958–1.055) | 0.817 | 1.002 (0.950–1.056) | 0.952 |
| Sex | 1.141 (0.550–2.369) | 0.723 | 1.099 (0.512–2.359) | 0.809 |
| CCI | 1.488 (1.266–1.748) | < 0.001 | 1.445 (1.211–1.726) | < 0.001 |
| Frailty | 4.554 (1.861–11.140) | 0.001 | 2.447 (0.870–6.885) | 0.090 |
| ADL | 0.985 (0.975–0.995) | 0.003 | 1.004 (0.991–1.017) | 0.529 |
| B | ||||
| Malnutrition status | ||||
| Normal | Reference | |||
| At risk of malnutrition | 2.416 (0.802–7.279) | 0.117 | 1.989 (0.637–6.211) | 0.236 |
| Malnutrition | 9.170 (3.191–26.348) | < 0.001 | 6.916 (2.161–22.127) | 0.001 |
| Age | 0.996 (0.958–1.036) | 0.845 | 0.988 (0.947–1.031) | 0.587 |
| Sex | 1.187 (0.651–2.164) | 0.577 | 1.098 (0.587–2.056) | 0.770 |
| CCI | 1.441 (1.256–1.654) | < 0.001 | 1.396 (1.203–1.619) | < 0.001 |
| Frailty | 3.048 (1.570–5.918) | 0.001 | 1.570 (0.719–3.428) | 0.258 |
| ADL | 0.986 (0.978–0.995) | 0.002 | 1.002 (0.991–1.013) | 0.686 |
Note: Normal nutritional status was used as the reference category for nutritional status. Multivariable Cox proportional hazards models were adjusted for nutritional status, age, sex, CCI, frailty, and ADL. Statistical significance was defined as p < 0.05.
Abbreviations: ADL, activities of daily living; aHR, adjusted hazard ratio; CCI, Charlson comorbidity index; CI, confidence interval; HR, hazard ratio.
4. Discussion
In this study, we focused on the nutritional status of noncritically ill older adults presenting to the emergency department and evaluated their short‐term outcomes at 30 and 90 days following the ED visit. We found that impaired nutritional status was highly prevalent, affecting nearly 60% of patients. Patients with malnutrition exhibited significantly worse functional status, cognitive performance, and physical capacity. Furthermore, multivariable Cox proportional hazards regression analyses demonstrated that malnutrition remained independently associated with both 30 and 90‐day mortality after adjustment for age, sex, CCI, frailty, and activities of daily living. In addition, geriatric syndromes—including functional dependence (ADL), frailty, and decreased handgrip strength—were identified as independent factors associated with both malnutrition and risk of malnutrition. These findings highlight the close interplay between nutritional status, geriatric vulnerability, and short‐term clinical outcomes in older adults in the ED. Our findings extend previous ED studies by comprehensively evaluating multiple geriatric domains within a single cohort while also demonstrating the independent prognostic value of malnutrition for short‐term mortality.
The prevalence of malnutrition in our study was higher than that reported in community‐dwelling older adults, where only a small proportion are classified as malnourished, although many remain at risk and unrecognized [3, 4]. This discrepancy likely reflects the progressive nature of malnutrition, which develops insidiously in the community but becomes clinically apparent during acute illness [4]. Older adults with underlying malnutrition are more vulnerable to functional decline and frailty, increasing the likelihood of ED visits [4]. The ED therefore represents a point where previously unrecognized malnutrition becomes evident, explaining the higher prevalence observed in this setting [5, 6, 7]. Given its role as a primary entry point into the healthcare system, the ED provides an important opportunity for early identification of malnutrition. However, malnutrition remains underrecognized in this setting [9]. Routine screening using validated tools such as the MNA‐SF may facilitate timely recognition and enable appropriate interventions and follow‐up planning.
In the present study, malnutrition remained independently associated with both 30‐ and 90‐day mortality after adjustment for age, sex, comorbidity burden, frailty, and functional status. These findings indicate that nutritional status provides prognostic information beyond established geriatric risk factors and comorbidity burden, underscoring the importance of routine nutritional assessment in older adults presenting to the ED. CCI also remained independently associated with short‐term mortality in the multivariable models, highlighting the important contribution of underlying comorbidity burden to prognosis in this population. Together, these findings suggest that nutritional status and comorbidity provide complementary prognostic information and support a multidimensional approach to risk stratification in older adults presenting to the ED. Our findings are consistent with previous studies demonstrating that malnutrition is an important predictor of mortality in older adults and remains independently associated with adverse outcomes after adjustment for comorbidities and other clinical factors [10]. Furthermore, ED‐based cohort studies have shown that malnutrition and other geriatric syndromes are important determinants of early mortality among older adults presenting to the emergency department [19, 20]. The association between malnutrition and mortality may be explained by its close relationship with frailty, reduced physiological reserve, immune dysfunction, and increased vulnerability to acute stressors, all of which may impair recovery from acute illness and contribute to early clinical deterioration. Collectively, these findings suggest that malnutrition is not only a marker of baseline health status but also an independent prognostic indicator of short‐term mortality in acute care settings.
An important finding of our study is that functional dependence (ADL), frailty, and decreased handgrip strength were independently associated with both malnutrition and risk of malnutrition. This indicates that nutritional impairment in older adults is not an isolated condition but reflects a multidimensional vulnerability involving functional decline, reduced physiological reserve, and impaired muscle strength.
First, functional dependence has been consistently associated with both malnutrition and mortality in older adults. Previous longitudinal studies have demonstrated that ADL impairment independently predicts mortality and that the coexistence of malnutrition and ADL dependence is associated with the poorest survival outcomes [21]. Malnutrition is associated with functional decline and deterioration in ADL, as well as increased mortality risk [13, 22], and their coexistence synergistically worsens outcomes [13]. In addition, the interaction between malnutrition and frailty has been shown to amplify adverse outcomes [15]. These findings support our observation that ADL is not only a consequence of malnutrition but also an important independent factor associated with both established malnutrition and earlier stages of nutritional risk in the ED setting.
Second, frailty has been shown to strongly interact with malnutrition in predicting adverse outcomes. Large cohort studies have demonstrated that both frailty and malnutrition independently contribute to mortality, while their coexistence markedly increases the risk of death and functional decline [23]. This is consistent with our findings that frailty is independently associated with both malnutrition and the risk of malnutrition, suggesting that frailty may represent an early indicator of nutritional vulnerability rather than merely a downstream consequence.
Third, muscle strength, particularly handgrip strength, plays a critical role in the relationship between malnutrition and mortality. Muscle strength also plays a key role, as the coexistence of malnutrition and low handgrip strength significantly increases mortality risk beyond either condition alone [24, 25]. In addition, studies on malnutrition–sarcopenia syndrome have shown that the coexistence of malnutrition and muscle impairment confers substantially increased mortality risk compared with either condition alone [24, 26]. These findings are in line with our results, in which decreased handgrip strength was independently associated with both malnutrition and risk of malnutrition, highlighting the role of muscle function as an early and clinically relevant marker of nutritional impairment.
Although polypharmacy was included as a candidate variable in our analyses, it was not independently associated with malnutrition after adjustment for other geriatric factors. Nevertheless, polypharmacy remains an important geriatric syndrome that has been associated with dysgeusia, falls, frailty, functional decline, and cognitive impairment. Future studies should further investigate the complex interactions between medication burden, nutritional status, and clinical outcomes in older adults.
These findings have important clinical implications for the care of older adults in the ED. Given the high prevalence of impaired nutritional status and its strong association with short‐term mortality, the ED represents a critical setting for early identification of malnutrition. Routine screening using validated tools such as the MNA‐SF may facilitate rapid risk stratification and improve recognition of high‐risk patients. Importantly, nutritional assessment should be integrated with evaluation of functional status (ADL), frailty, and muscle strength, particularly handgrip strength. This multidimensional approach allows more comprehensive identification of vulnerable patients.
Early identification in the ED may enable timely interventions, including nutritional support, rehabilitation, and multidisciplinary care planning, and may also prompt referral for post‐discharge follow‐up. Together, these strategies may help improve short‐term outcomes in older adults.
4.1. Limitations
This study has several limitations. First, this was a single‐center observational study conducted in a tertiary medical center, which may limit the generalizability of our findings to other healthcare settings with different patient populations or healthcare delivery systems. Second, although we adjusted for multiple clinical and geriatric variables, residual confounding cannot be excluded because of the observational study design. Potential unmeasured confounders, including socioeconomic status, dietary habits, inflammatory status, and post‐discharge nutritional support, may have influenced the observed associations between nutritional status and clinical outcomes. Third, nutritional status was assessed using the MNA‐SF at a single time point in the ED, and changes in nutritional status over time were not evaluated. Fourth, our study population consisted of clinically stable, noncritically ill older adults admitted to the ED observation unit who were able to complete comprehensive geriatric assessments. This selection may have introduced selection bias toward healthier older adults with sufficient functional and cognitive capacity to participate in the study. Therefore, the estimated prevalence of malnutrition and the observed associations may not be generalizable to the broader population of older ED patients, particularly those with critical illness, major trauma, advanced malignancy, or severe cognitive impairment who were excluded from this study. Finally, although we identified associations between malnutrition, functional status, frailty, and muscle strength, causal relationships cannot be established. Further prospective interventional studies are needed to determine whether early identification and targeted management of malnutrition can improve clinical outcomes in older adults.
5. Conclusion
Malnutrition is highly prevalent among older adults in the emergency department and is independently associated with increased short‐term mortality after adjustment for major clinical and geriatric factors. Functional dependence, frailty, and decreased handgrip strength were independently associated with both malnutrition and risk of malnutrition, highlighting the multidimensional nature of nutritional vulnerability. Integrating nutritional screening with functional and physical performance assessments in the ED may facilitate early identification of high‐risk patients and support timely interventions to improve clinical outcomes.
Author Contributions
Conceptualization: Huang HH, Chen YJ. Investigation: Huang HH, Chen YJ, Wang TY, Lin JW, Chiu CL, Hsu CH. Project administration: Huang HH, Chen YJ, Wang TY, Lin JW, Chiu CL, Hsu CH. Writing – original draft: Huang HH, Chen YJ. Writing – review and editing: Huang HH.
Funding
This study was supported by grants from the Ministry of Science and Technology, Taiwan (MOST107‐2314‐B‐075‐053 and MOST108‐2314‐B‐075‐034), the Veterans Affairs Council, Taiwan (107VACS‐002, 108VACS‐002, 109VACS‐002, 110VACS‐009, 111VACS‐009, 112VACS‐009, 113VACS‐009, 114VACS‐009, and 115‐58050), and intramural grants from Taipei Veterans General Hospital, Taiwan (V108C‐123, V111C‐080, and V115C‐235).
Conflicts of Interest
The authors declare no conflicts of interest.
Chen Y.‐J., Wang T.‐Y., Lin J.‐W., Chiu C.‐L., Hsu C.‐H., and Huang H.‐H., “Malnutrition and Geriatric Vulnerability Are Independently Associated With Short‐Term Mortality in Older Emergency Department Patients in Taiwan,” Academic Emergency Medicine 33, no. 8 (2026): e70390, 10.1111/acem.70390.
Supervising Editor: Michael Malone
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.