Highlights
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Dynapenia at admission independently predicts adverse events in older adults.
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Low grip strength is linked to higher mortality, delirium, and readmissions.
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Handgrip strength is a simple bedside tool for early risk stratification.
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Incorporating handgrip strength into routine geriatric evaluation may enhance clinical decisión making.
Keywords: Hand strength, Hospitalization, Mortality, Sarcopenia, Adverse events (source: MeSH NLM)
Abstract
Objectives
To evaluate whether dynapenia at hospital admission predicts adverse events in older adults hospitalized for medical conditions.
Design
Prospective observational cohort study. Setting: Hospital Cayetano Heredia, Lima, Peru. Participants: 120 patients aged ≥60 years admitted for medical reasons between July and December 2024. Measurements: Handgrip strength was assessed within 48 h of admission using a JAMAR® dynamometer. Dynapenia was defined as <12 kg in men and <8 kg in women (sex-specific 25th percentile). Participants were followed for 30 days to identify adverse events, including mortality, delirium, readmission, healthcare-associated infections, pressure ulcers, and falls. Cox regression models estimated hazard ratios (HR).
Results
Median age was 74 years; 49.2% were women. Dynapenia was present in 30% of participants. During follow-up, 45 adverse events were documented: mortality (12.5%), delirium (9.2%), readmission (5.8%), and others (7.4%). Patients with dynapenia had a higher incidence of adverse outcomes (41.7% vs. 16.7%, p < 0.05). Dynapenia was independently associated with adverse events (adjusted HR 2.32; 95% CI: 1.08–4.99). Sensitivity analyses using intrapopulation tertiles and EWGSOP2 thresholds yielded consistent associations.
Conclusion
Dynapenia at admission is an independent predictor of adverse events in hospitalized older adults. Handgrip strength is a simple bedside tool that may improve early risk stratification and support targeted preventive interventions.
1. Introduction
Population aging is one of the main health challenges of the 21 st century, with significant implications for healthcare systems. In Peru, the proportion of older adults increased from 9.1% in 2015 to 13.6% in 2023, leading to a rise in chronic diseases and hospitalizations due to exacerbations of such conditions [1,2]. During hospitalization, this population is particularly vulnerable to adverse events such as infections, delirium, pressure ulcers, falls, and mortality [3,4].
Hospitalization in older adults carries a broad spectrum of risks. Factors such as dehydration, sarcopenia, malnutrition, sensory and sleep deprivation, and loss of social contact contribute to adverse events. These complications increase hospital stay, costs, mortality, and the risk of institutionalization. Studies have shown that hospitalization increases the immediate risk of disability, doubles the likelihood of cognitive decline, and is associated with higher prevalence of depression, readmissions, and frailty [4,5].
Dynapenia, defined as age-related loss of muscle strength not due to neurological or muscular disease, has gained importance as a nutritional and functional marker in geriatrics [6]. Handgrip strength measurement with a dynamometer is a validated, accessible, and reproducible bedside method [7]. Previous studies have shown that dynapenia is associated with functional decline, prolonged hospital stay, and mortality [8,9]. However, evidence on its association with in-hospital events in older adults remains limited.
We hypothesized that low handgrip strength at admission would be independently associated with a higher risk of adverse events during hospitalization and within 30 days of follow-up in older adults admitted for medical conditions.
2. Methods
2.1. Study design and population
We conducted a prospective, observational, single-cohort study between July and December 2024 at Hospital Cayetano Heredia in Lima, Peru. We included older adults (≥60 years) hospitalized for medical reasons, assessed within the first 48 h of admission, capable of following instructions, and without upper limb functional limitations. Exclusion criteria included terminal illness, hemodynamic instability, severe functional dependence (Barthel Index <20), use of home oxygen therapy, acute respiratory failure with severe hypoxemia (PaFiO2 < 150 or paradoxical breathing), or conditions that impeded handgrip assessment.
Follow-up was conducted for 30 days from admission. Daily evaluations were carried out during hospitalization, followed by outpatient visits or phone calls at 30 days. Patients unreachable after three contact attempts were considered censored in survival analysis.
2.2. Outcome
The primary outcome was the occurrence of the first adverse event within 30 days after hospital admission. Adverse events included: (1) in-hospital or 30-day mortality; (2) delirium, assessed using the Confusion Assessment Method (CAM) [10]; (3) unplanned hospital readmission; (5) healthcare-associated infections (pneumonia, urinary tract infection, or catheter-associated infections); (5) pressure ulcers; and (6) falls.
Time-to-event was measured from the date of admission to the date of the first adverse event. Participants who did not experience an event were censored at hospital discharge or at their 30-day follow-up evaluation, whichever occurred later. Patients who could not be reached after three phone-call attempts were censored at the last date they were known to be alive. For patients experiencing more than one event, only the first event was considered in the survival analysis.
2.3. Exposure
The main exposure was dynapenia, defined using sex-specific 25th percentile cut-points derived from the study population (12 kg in men and 8 kg in women). These cut-points were selected because handgrip strength was non-normally distributed and because acute illness in hospitalized adults is known to lower grip strength values compared to community-dwelling populations. Three trials of maximal handgrip strength were recorded using a JAMAR® dynamometer, and the highest value was used [11,12]. Sensitivity analyses were conducted using: intrapopulation tertiles of handgrip strength and the EWGSOP2 cut-points (≤27 kg in men and ≤16 kg in women).
2.4. Covariables
Covariables were selected a priori using a directed acyclic graph (DAG) based on clinical and epidemiological considerations. These included: sex, type 2 diabetes mellitus, chronic kidney disease, creatinine clearance (Cockcroft–Gault), heart failure, anemia severity, and nutritional status assessed with the Mini Nutritional Assessment–Short Form (MNA-SF). Age and body mass index (BMI) were highly collinear; both exceeded acceptable VIF thresholds. Therefore, neither was included in the final multivariable model.
2.5. Sample size and statistical analysis
Sample size was estimated at 120 participants, considering an expected incidence of adverse events of 20.5% in patients with dynapenia and 4.4% in those without, a non-exposed/exposed ratio of 2.5, a significance level of 0.05, and 80% power. Due to the lack of local population data on the composite outcome, we used the mortality rate reported in a previous Peruvian study of hospitalized older adults as a reference [13].
All analyses were performed using STATA v17. Descriptive statistics and bivariate tests were applied according to variable type and distribution. Time-to-event analyses were conducted using Cox proportional hazards regression to estimate crude and adjusted hazard ratios. Time at risk was calculated from the date of hospital admission to the first adverse event. Participants were censored at discharge, at their 30-day follow-up assessment, or at the last date they were known to be alive if they could not be contacted after three attempts.
The adjusted model included sex, anemia severity, malnutrition, creatinine clearance, chronic kidney disease, heart failure, and type 2 diabetes. Proportional hazards and multicollinearity assumptions were assessed, and model specification was evaluated using linktest and Cox-Snell residuals.
2.6. Ethical considerations
The study protocol was approved by the Ethics Committee of Universidad Peruana Cayetano Heredia. The study followed the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants. Confidentiality, anonymity, and the right to withdraw at any time without affecting medical care were guaranteed.
3. Results
We included 120 hospitalized older adults between July and December 2024. Thirteen participants (10.8%) did not complete follow-up and were considered censored in survival analysis. The main variable, handgrip strength, was not normally distributed; thus, sex-specific 25th percentile cut-offs were used (8 kg for women, 12 kg for men) to define dynapenia (Table S1).
Dynapenia was present in 30% of patients at admission. Significant differences were found between patients with and without dynapenia in clinical variables such as age, body mass index, history of stroke, Barthel Index, Charlson Index, albumin levels, lymphocyte count, nutritional risk (MNA-SF), and probable sarcopenia (SARC-F) (Table 1).
Table 1.
Baseline characteristics by dynapenia status.
| Characteristics | Total (N = 120) | No Dynapenia (N = 84) | Dynapenia (N = 36) |
|---|---|---|---|
| Age (years) – Median (IQR) | 74 (67–81) | 72 (67–78) | 80 (70–85.5) ‡, α |
| Sex – n (%) | |||
| Male | 61 (50.8) | 43 (51.2) | 18 (50) ˄ |
| Female | 59 (49.2) | 41 (48.8) | 18 (50) |
| BMI (kg/m2) – Median (IQR) | 24.5 (22–28.7) | 25.3 (22.9–29) | 22.8 (20.2–27.5) ‡, α |
| Comorbidities – n (%) | |||
| Hypertension | 67 (55.8) | 46 (54.8) | 21 (58.3) ˄ |
| Diabetes Mellitus | 37 (30.8) | 26 (30.9) | 11 (30.6) ˄ |
| Chronic Kidney Disease | 16 (13.3) | 10 (11.9) | 6 (16.7) ˄ |
| Atrial Fibrillation | 15 (12.5) | 10 (11.9) | 5 (13.9) ˄ |
| Ischemic Stroke | 12 (10) | 5 (5.9) | 7 (19.4) ‡, ˄ |
| Heart Failure | 11 (9.2) | 7 (8.3) | 4 (11.1) ˄ |
| Creatinine Clearance (mL/min/1.73m²) β – Median (IQR) | 61.8 (36.1–82.3) | 68.3 (40.8–83.7) | 48.6 (26.6–78.8) α |
| Charlson Index – Median (IQR) | 4 (3–5) | 4 (3–5) | 4 [4,5] ‡, α |
| Barthel Index – Median (IQR) | 95 (85–100) | 95 (87.5–100) | 87.5 (65–95) ‡, α |
| Albumin (g/dL) † – Mean ± SD | 3.3 ± 0.7 | 3.4 ± 0.6 | 3.0 ± 0.7 ‡, ¥ |
| Anemia Grades – n (%) | |||
| No anemia (>12 g/dL ♀; >13 g/dL ♂) | 35 (29.2) | 29 (34.5) | 6 (16.7) ˄ |
| Mild (≥10 g/dL) | 40 (33.3) | 25 (29.8) | 15 (41.7) |
| Moderate (8–9.9 g/dL) | 24 (20) | 18 (21.4) | 6 (16.7) |
| Severe (<8 g/dL) | 21 (17.5) | 12 (14.3) | 9 (25) |
| Lymphocytes (cells/μL) – Median (IQR) | 1035 (675–1615) | 1135 (755–1665) | 825 (615–1250) ‡, α |
| MNA-SF – n (%) | |||
| Normal nutritional status (12–14) | 20 (16.7) | 19 (22.6) | 1 (2.9) ‡, ˄ |
| Risk/malnutrition (0–11) | 100 (83.3) | 65 (77.4) | 35 (97.2) ‡ |
| Length of hospital stay (days) – Median (IQR) | 9 (6–14) | 8 (5.5–14) | 10 (6–14) α |
| SARC-F – n (%) | |||
| Low probability (<4) | 76 (63.3) | 60 (71.4) | 16 (44.4) ‡, ˄ |
| High probability (≥4) | 44 (36.7) | 24 (28.6) | 20 (55.6) ‡ |
Abbreviations: IQR, interquartile range; BMI, body mass index; SD, standard deviation; MNA-SF, Mini Nutritional Assessment Short Form; NEWS, National Early Warning Score; CKD, chronic kidney disease; CrCl, creatinine clearance.
Statistically significant difference vs. non-dynapenia group (p < 0.05).
41 missing values.
Calculated using Cockcroft-Gault formula.
Wilcoxon rank-sum test.
Chi-square test.
Student's t-test for independent variables.
During follow-up, 45 adverse events were recorded: 15 deaths (12.5%), 11 cases of delirium (9.2%), 7 readmissions (5.8%), 4 healthcare-associated infections or pressure ulcers (3.3%), and one fall (0.8%) (Table S2). Events were more frequent among patients with dynapenia, as confirmed by Kaplan-Meier curves (log-rank p = 0.001) (Fig. 1).
Fig. 1.
Kaplan–Meier survival curve for adverse events according to the presence of dynapenia.
Cox regression showed a higher risk of adverse events in patients with dynapenia (crude HR: 3.08; 95%CI: 1.48–6.33). After adjusting for sex, anemia severity, comorbidities, and nutritional status, the association remained significant (adjusted HR: 2.32; 95%CI: 1.08–4.99; p = 0.030) (Table 2).
Table 2.
Cox regression for adverse events: Crude and adjusted hazard ratios.
| Characteristics | Events/person-days | Incidence per 100 person-days (95% CI) | Crude HR (95% CI) | Adjusted HR (95% CI) * |
|---|---|---|---|---|
| Dynapenia | ||||
| No | 14/2165 | 0.64 (0.38–1.09) | Ref. | Ref. |
| Yes | 15/745 | 2.01 (1.21–3.33) | 3.03 (1.46–6.30) | 2.32 (1.08–4.99) |
| Sex | ||||
| Male | – | – | Ref. | Ref. |
| Female | – | – | 0.78 (0.37–1.63) | 0.94 (0.41–2.16) |
| Anemia grades | ||||
| Mild anemia | – | – | 1.96 (0.67–5.75) | 1.53 (0.48–4.86) |
| Moderate anemia | – | – | 1.79 (0.54–5.88) | 1.22 (0.33–4.53) |
| Severe anemia | – | – | 2.91 (0.95–8.90) | 1.86 (0.55–6.29) |
| Nutritional risk/malnutrition | – | – | 6.53 (0.88–48.01) | 3.29 (0.41–25.93) |
| Creatinine clearance | – | – | 0.98 (0.97–0.99) | 0.99 (0.97–1.00) |
| Chronic kidney disease | – | – | 2.77 (1.22–6.27) | 1.30 (0.40–4.18) |
| Heart failure | – | – | 3.23 (1.31–7.95) | 2.97 (1.15–7.63) |
| Type 2 Diabetes Mellitus | – | – | 1.15 (0.53–2.48) | 1.06 (0.45–2.50) |
HR: Hazard Ratio; CI: Confidence Interval.
Sensitivity analyses supported the robustness of the association. Excluding patients lost to follow-up yielded similar estimates (adjusted HR 2.23; 95% CI 1.02–4.86) (Table S3). Using intrapopulation tertiles, the lowest-strength tertile showed higher risk of adverse events compared with the highest (adjusted HR 3.00; 95% CI 1.02–8.83) (Table S4). Analyses using EWGSOP2 cut-points showed a consistent direction of effect, although with lower precision (adjusted HR 1.79; 95% CI 0.40–8.05), which was expected given the small number of events and the low prevalence of low grip strength under this definition (Table S5).
Diagnostic tests showed no violations of the proportional hazards assumption or evidence of model misspecification (non-significant linktest) (Table S6). Severe collinearity was identified between age and BMI when both variables were evaluated, and therefore both were excluded from the final model (Table S7, Table S8). Nutritional status was represented using MNA-SF, and the correlation between BMI and handgrip strength was weak. The Cox–Snell residual plot indicated good model fit, particularly for early events (Figure S2).
4. Discussion
This study demonstrates that the presence of dynapenia at hospital admission is an independent predictor of adverse events in older adults hospitalized for medical conditions. Additionally, a high prevalence of malnutrition, nutritional risk, functional dependence, and probable sarcopenia was observed in patients with dynapenia, suggesting a more frail and vulnerable clinical profile.
Among the adverse events analyzed, mortality, readmission, delirium, pressure ulcers, and healthcare-associated infections were more frequent in patients with dynapenia. Our findings are consistent with previous studies by Zhang et al. [14] and Simmonds et al. [15], which showed a higher risk of 30-day hospital readmission in older adults with reduced handgrip strength. These results support the usefulness of handgrip strength as a prognostic functional tool during hospitalization.
Furthermore, the increased risk of mortality observed in our study aligns with findings by Ballesteros-Pomar [16] and Vecchiarino [17], who reported that lower handgrip strength was associated with greater risk of death and 90-day readmission. Notably, Vecchiarino’s study, conducted in patients hospitalized for community-acquired pneumonia, highlights the clinical utility of this functional measure even in acute illness contexts [18].
The high prevalence of malnutrition and functional dependence in our sample underscores the need for simple, objective functional assessment tools. In this context, handgrip dynamometry is a viable alternative for identifying patients at higher risk of adverse outcomes. Its implementation could guide early interventions such as nutritional support, early mobilization, and physical therapy, potentially reducing complications and improving functional recovery [7,19,20].
Handgrip strength values in hospitalized older adults are typically lower than those observed in community-dwelling populations due to acute illness, immobility, systemic inflammation, and reduced physiological reserve [21,22]. Because the distribution of grip strength in our cohort was non-normal, and given the expected downward shift in strength during hospitalization, we used sex-specific 25th percentile cut-points derived from our study population. This percentile-based approach has been applied in other cohorts of older adults and reflects relative weakness within the specific clinical context being studied [23]. Importantly, our sensitivity analyses using intrapopulation tertiles and EWGSOP2 thresholds showed consistent directions of association, reinforcing the robustness of the primary findings.
However, the definition and classification of dynapenia remain heterogeneous [24]. In Latin America, countries such as Brazil and Chile have established national reference values, facilitating clinical implementation [[25], [26], [27]]. This underscores the need for multicenter studies in Peru to establish validated national cut-off points and to integrate handgrip measurement into routine geriatric assessments in hospitals. Standardization would improve clinical decision-making and allow for individualized discharge planning and rehabilitation strategies [18].
This study has several limitations. First, the sample size was modest and derived from a single center, which may limit the precision of some estimates. However, the consistency of the results across multiple sensitivity analyses strengthens confidence in the observed associations. Second, although follow-up losses were relatively low (10.8%), some degree of outcome misclassification cannot be ruled out; nevertheless, analyses excluding these participants produced similar results. Third, dynapenia was defined using percentile-based thresholds derived from this hospitalized cohort, and although this approach reflects relative weakness within the acute-care setting, external validation in larger and more diverse populations is needed. Fourth, residual confounding is possible given the observational design, despite careful covariate selection based on a directed acyclic graph. Finally, because the composite outcome included heterogeneous events, individual components should be interpreted cautiously.
A major strength of this study is the use of a standardized and validated protocol for handgrip measurement with a hydraulic dynamometer, ensuring high reliability and reproducibility [11]. The prospective design, with daily in-hospital assessments and 30-day follow-up, reduces bias and allows for accurate characterization of adverse events. Covariates were carefully selected using a directed acyclic graph, minimizing unnecessary adjustment and enhancing the causal interpretability of the findings. The analysis incorporated comprehensive diagnostic checks for proportional hazards, model specification, and multicollinearity, strengthening confidence in the statistical approach. Multiple sensitivity analyses—using intrapopulation tertiles and EWGSOP2 thresholds—showed consistent results. The focus on dynapenia, rather than full sarcopenia assessment, is especially appropriate for acute-care settings, where simplified functional measures are more feasible [28,29]. Finally, this study provides novel local evidence from a Peruvian hospitalized population, a group underrepresented in the global literature.
5. Conclusions
Dynapenia is an independent prognostic factor for adverse events in older adults hospitalized for medical conditions. Handgrip strength measurement is a simple, reproducible, and feasible bedside tool that can be incorporated into initial geriatric assessments to identify patients at higher risk of complications.
Routine implementation of handgrip dynamometry may enhance the multidisciplinary approach to older adult care, promoting a more proactive, functional, and patient-centered model of care, with potential to improve clinical outcomes and reduce healthcare burden.
CRediT authorship contribution statement
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Giancarlo G. Sante Farfán: Study concept and design, data collection, data analysis and interpretation, drafting of the manuscript, and final approval.
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Roberto I. Zenteno Zeballos: Participant recruitment, clinical supervision, interpretation of findings, and critical revision of the manuscript.
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Leandro Huayanay Falconi: Statistical analysis, methodological guidance, interpretation of results, and critical review of the manuscript for important intellectual content.
Sponsor’s role
This study received no external funding. The sponsor had no role in the design, methods, participant recruitment, data collection, analysis, or preparation of the manuscript.
Declaration of competing interest
Giancarlo G. Sante Farfán: No conflicts to disclose.
Roberto I. Zenteno Zeballos: No conflicts to disclose.
Leandro Huayanay Falconi: No conflicts to disclose.
Acknowledgment
The corresponding author affirms that all individuals who contributed significantly to the work are listed as authors or acknowledged appropriately, and that written consent has been obtained from all acknowledged contributors who are not authors. All coauthors have been informed of the manuscript submission to the The Journal of Nutrition, Health & Aging, any subsequent revisions, and the final editorial decision. The corresponding author also confirms the accuracy of authors’ names, affiliations, and order of authorship.
Footnotes
This manuscript includes data that were previously presented as part of a master’s tesis submitted to the Universidad Peruana Cayetano Heredia, Lima, Perú.
Not presented at any scientific meeting.
This work has not been published as a preprint.
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.jnha.2025.100746.
Appendix A. Supplementary data
The following is Supplementary data to this article:
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Associated Data
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