Skip to main content
NCBI home page
Surgery Open Science logoLink to Surgery Open Science
. 2025 Sep 17;28:13–18. doi: 10.1016/j.sopen.2025.09.008

The association of malnutrition with clinical and financial outcomes of traumatic injuries in older adults: A national retrospective analysis

Troy N Coaston a, Konmal Ali a, Amulya Vadlakonda a, Deep J Mehta a, Sara Sakowitz a, Dariush Yalzadeh a, Areti Tillou a,b, Peyman Benharash a,b,c,⁎; , on behalf of the Academic Trauma Research Consortium (ATRIUM)1
PMCID: PMC12483657  PMID: 41035490

Abstract

Background

Malnutrition is an often underrecognized condition among older adults and carries significant relevance among patients hospitalized with traumatic injuries. The present study aimed to evaluate the association of malnutrition with clinical and financial outcomes among older adult patients admitted with external trauma.

Study design

This was a retrospective cohort study of the 2016–2021 National Inpatient Sample including older adults (≥65 years) hospitalized with traumatic injuries. Patients were stratified by nutritional status (Malnourished and Non-Malnourished). Risk-adjusted logistic and linear regression models were constructed to evaluate the association of malnutrition with outcomes including inpatient mortality, clinical complications, and hospitalization costs.

Results

Of 6,587,907 older adults admitted with traumatic injuries, 7.5 % had malnutrition. The prevalence of malnutrition rose from 5.8 % to 8.6 % over the study period (nptrend<0.001). Patients with malnutrition were more commonly of the lowest income quartile (25.5 vs 24.5 %), non-White (19.4 vs 16.9 %), and male (41.3 vs 39.1 %, all p < 0.001). Following risk-adjustment, malnutrition was linked with increased odds of inpatient mortality (Adjusted Odds Ratio [AOR] 1.92, 95 % Confidence Interval [CI] 1.86–1.98) and infectious complications (AOR 2.30, 95 % CI 2.25–2.35) as well as greater inpatient costs (β + $7400, 95 % CI $7100-7600).

Conclusion

Malnutrition among older adults is associated with poorer clinical outcomes and increased financial burden. Rising prevalence and significant disparities underscore the need for increased screening and culturally relevant nutritional interventions to promote quality, equity, and sustainability in trauma care.

Keywords: Malnutrition, Older adult, Trauma, Costs, Resource use, Outcomes

Graphical abstract

Unlabelled Image

Open in a new tab

Highlights

  • •

    Malnutrition affected 7.5 % of older adults hospitalized with traumatic injuries.

  • •

    Malnourished patients had 92 % higher odds of inpatient mortality.

  • •

    Malnutrition was linked to $7400 higher hospitalization costs.

  • •

    Malnutrition reflects systemic gaps in equitable, preventive care for older adults.

Introduction

By 2050, patients ≥65 years of age are projected to comprise nearly 40 % of all trauma-related hospitalizations [1,2]. While older patients often present with trauma severity comparable to that of younger individuals, they experience twice the risk of mortality as well as greater odds of other postoperative complications [[3], [4], [5]]. Such observations have previously been attributed to a myriad senescent conditions including frailty which is thought to reduce resilience to severe physiologic derangement [6].

Age-related physiological changes notwithstanding, nutritional status remains a critical determinant of outcomes among trauma patients, with nearly 50 % of hospitalized older adults thought to be at risk for malnutrition [[7], [8], [9]]. The hypermetabolism and catabolic stress response following trauma may further exacerbate malnutrition and its sequelae [9]. Indeed, previous studies have established profound associations between poor nutritional status among older trauma patients and increased risk of mortality, infectious complications, and cognitive impairment [2,8,9]. Moreover, serum albumin, an established biomarker of nutrition, has been recognized as a strong predictor of postoperative morbidity across surgical specialties for decades, underscoring its clinical utility in preoperative risk stratification [10]. Despite these implications, national-level characterization of the link between malnutrition and outcomes among older adults hospitalized with traumatic injuries remains sparse, with existing studies relying on single-institution or health system data [2,11,12].

The present study characterized the association of malnutrition with clinical and financial outcomes of hospitalization for trauma among older adults. We hypothesized malnourished status to be independently linked with increased risk-adjusted odds of mortality and complications as well as higher expenditure.

Methods

This was a retrospective cohort study of the 2016–2021 National Inpatient Sample (NIS). Maintained as part of the Healthcare Utilization Project, NIS is the largest publicly available all-payer inpatient repository in the U.S. [13]. Through survey-weighting methodology, the NIS provides accurate estimates for approximately 97 % of hospitalizations, annually. All nonelective older adult (≥65 years) hospitalizations with external traumatic injuries were identified using International Classification of Diseases, 10th Revision (ICD-10) diagnosis codes, as previously described [14]. Records missing key data including sex, hospitalization costs, or mechanism of injury, were removed from analysis (Fig. 1).

Fig. 1.

Fig. 1

Open in a new tab

CONSORT Diagram.

Patient (age, sex, race, income, primary payer) and facility (bed size, teaching status, region) characteristics are reported in accordance with the NIS data dictionary [13]. Importantly, income reflects the median household income of the patient's community, as defined by their ZIP code. The presence of malnutrition status was ascertained using previously reported ICD-10 codes while Subjects were categorized into Malnutrition and Non-Malnutrition cohorts, accordingly [15]. The primary mechanism of injury (fall, motor-related, penetrating, and other blunt mechanism) was identified using ICD-10 codes as reported elsewhere [14]. Frailty was defined using the 11-item Modified Frailty Index (mFI-11), as described by Subramaniam and colleagues [16]. Importantly, the MFI differs from many other indices as it does not include malnutrition as a covariate. The burden of chronic conditions was assessed using the Charlson Comorbidity Index, which similarly does not include malnutrition in its calculation [17]. Injury severity was quantified using the Injury Severity Score (ISS), as reported by Clark et al. [18]. Clinical complications, identified through ICD-10 codes were categorized as cardiac (arrest, ventricular tachycardia, ventricular fibrillation, tamponade, myocardial infarction), infectious, respiratory (pneumonia, pneumothorax, acute respiratory distress, respiratory failure, prolonged ventilation, bronchopleural fistula), and thromboembolic (deep vein thrombosis, pulmonary embolism) [19]. Non-home discharge was defined as disposition to an acute, intermediate care, or nursing facility. Inpatient costs were calculated by applying hospital-specific cost-to-charge ratios to overall charges followed by inflation adjustment to the 2021 Personal Health Index [20].

The primary outcome was inpatient mortality. We further examined factors associated with malnutrition, clinical complications, and makers of resource utilization which included inpatient costs, non-home discharge, inpatient length of stay (LOS).

Patient and hospital factors are reported as proportions, means with standard deviations (SD), or medians with interquartile range (IQR), as appropriate. The significance of between-group differences was determined using the Pearson's Χ2 or Wilcoxon Rank Sum tests for categorical and continuous covariates, respectively. Cuzick's nonparametric test was used to ascertain the significance of temporal trends [21]. To identify independent association of malnourished status with study endpoints, multivariable logistic and linear models were constructed. Elastic net regularization, which aims to reduce collinearity and enhance generalizability, was used to guide variable selection in risk-adjusted models [22]. Goodness-of-fit was assessed using receiver-operating characteristics (C-statistic) for logistic or the coefficient of determination (R2) for linear models. Regression estimates are reported as adjusted odds ratios (AOR) or β coefficients (β), both with 95 % confidence intervals (CI), as appropriate.

Due to its deidentified nature, this study was deemed exempt from full review by the University of California, Los Angeles, Institutional Review Board. All statistical analyses were performed using Stata 18.0 (StataCorp, College Station, TX). Statistical significance was set at α = 0.05.

Results

Of an estimated 6,587,907 older adults admitted with traumatic injuries, 7.5 % comprised the Malnutrition cohort. Over the study period, the prevalence of malnutrition among older injured adults increased significantly, rising from 5.8 % in 2016 to 8.6 % in 2021 (nptrend<0.001; Fig. 2). Compared to others, Malnutrition was less commonly female (58.7 vs 60.9 %, p < 0.001), of White race (80.6 % vs 83.1, p < 0.001), and privately insured (5.6 vs 7.2 %, p < 0.001). Conversely, those with malnutrition were more frequently of the lowest income quartile (25.5 vs 24.5 %, p < 0.001). Furthermore, Malnutrition had a greater burden of comorbidities (Charlson: 2 [1–3] vs 2 [1–4], p < 0.001) and were found to have a marginally higher mFI-11 (2.8 ± 1.4 vs 2.7 ± 1.4, p < 0.001), compared to others. A detailed comparison of patient and hospital characteristics stratified by nutritional status is shown in Table 1.

Fig. 2.

Fig. 2

Open in a new tab

Trend in rate of malnutrition among older adult patients with traumatic injuries.

Table 1.

Demographic, clinical, and hospital characteristics of older adult trauma patients stratified by nutrition status.

Non-Malnutrition
(n = 6,093,827)		 Malnutrition
(n = 494,080)		 p-value
Age (years, median [IQR]) 81 [73–87] 82 [74–88] <0.001
Female (%) 60.9 58.7 <0.001
Charlson Comorbidity Index (median [IQR]) 2 [1–3] 2 [1–4] <0.001
Modified Frailty Index-11 (mean ± SD) 2.7 ± 1.4 2.8 ± 1.4 <0.001
Injury Severity Scale (mean ± SD) 6.7 ± 7.8 6.4 ± 7.9 <0.001
Race (%) <0.001
 White 83.1 80.6
 Black 5.9 7.9
 Hispanic 6.2 5.9
 Asian 2.3 3.0
 Other 2.5 2.6
Income quartile (%) <0.001
 76-100th 23.8 23.6
 51-75th 25.5 25.3
 26-50th 26.1 25.6
 0-25th 24.5 25.5
Insurance coverage (%) <0.001
 Private 7.2 5.6
 Medicare 89.2 90.9
 Medicaid 1.1 1.3
 Other payer 2.5 2.2
Mechanism of Injury (%) <0.001
 Falls 92.8 96.2
 Motor-Related 5.0 2.2
 Penetrating 0.6 0.4
 Other Blunt Mechanism 1.6 1.2
Hospital teaching status (%) <0.001
 Non-metropolitan 8.9 7.5
 Metropolitan non-teaching 21.5 21.2
 Metropolitan teaching 69.6 71.3
Hospital bed size (%) <0.001
 Large 49.6 51.0
 Medium 29.9 29.3
 Small 20.5 19.7
Open in a new tab

Reported as proportions unless otherwise noted. Statistical significance was set at p < 0.05 0. IQR, interquartile range. SD, Standard Deviation.

Following risk-adjustment, increasing age (AOR 1.11 per decade, 95 % CI 1.10–1.13), Medicaid coverage (AOR 1.23, 95 % CI 1.15–1.33; ref.: Private), and Black race (AOR 1.31, 95 % CI 1.27–1.36; ref.: White) were associated with increased odds of malnutrition. Additional factors linked with malnutrition included fall as the primary mechanism of injury (AOR 2.07, 95 % CI 1.97–2.18; ref.: Motor-Related), increasing burden of comorbidities (Charlson: AOR 1.12 per unit, 95 % CI 1.11–1.12), and being of the lowest income quartile (AOR 1.12, 95 % CI 1.08–1.16; ref.: Highest; Fig. 3).

Fig. 3.

Fig. 3

Open in a new tab

Factors associated with malnutrition among older adult patients admitted with traumatic injuries.

After multivariable adjustment for factors including frailty, malnutrition remained independently associated with increased odds of inpatient mortality (AOR 1.92, 95 % CI 1.86–1.98; model c-statistic = 0.72). Additionally, malnutrition increased the odds of infectious (AOR 2.30, 95 % CI 2.25–2.35), respiratory (AOR 1.87, 95 % CI 1.83–1.91), and cardiac complications (AOR 1.33, 95 % CI 1.29–1.36; Fig. 4). Notably, malnourished status was associated with greater resource utilization including hospitalization costs (β + $7400, 95 % CI $7100-7600), LOS (β +3.27 days, 95 % CI 3.19–3.35), and odds of non-home discharge (AOR 1.60, 95 % CI 1.57–1.63; Table 2). A subgroup analysis among those without fall as the primary mechanism of injury yielded a similar pattern of results (Supplemental Table 1).

Fig. 4.

Fig. 4

Open in a new tab

Risk-adjusted incidence of inpatient complications among older adult patients with traumatic injuries stratified by nutrition status.

Table 2.

Clinical and financial outcomes stratified by nutrition status.

Outcome Non-Malnutrition
(n = 6,093,827)		 Malnutrition
(n = 494,080)		 p-value AOR or β 95 % CI p-value
In-hospital mortality (%, AOR) 3.2 6.4 <0.001 1.92 1.86–1.98 <0.001
Complications (%, AOR)
 Thromboembolic 0.9 1.5 <0.001 1.60 1.51–1.69 <0.001
 Cardiac 5.1 7.4 <0.001 1.33 1.29–1.36 <0.001
 Respiratory 7.6 13.4 <0.001 1.87 1.83–1.91 <0.001
 Infectious 5.5 12.7 <0.001 2.30 2.25–2.35 <0.001
Length of stay (days, median, IQR, β) 4 [3–6] 6 [4–10] <0.001 3.27 3.19–3.35 <0.001
Inpatient costs ($1000's, median, IQR, β) $12.2 [$7.3–19.4] $15.6 [$9.2–26.7] <0.001 $7.4 $7.1–7.6 <0.001
Non-Home Discharge (%, AOR) 63.5 73.4 <0.001 1.60 1.57–1.63 <0.001
Open in a new tab

AOR, Adjusted Odds Ratio; CI, Confidence Interval; IQR, Interquartile Range.

Discussion

With the aging U.S. population, surgeons and emergency care providers are increasingly faced with managing older trauma patients who face distinct physiologic challenges. Recent literature has prioritized identifying predictors of poor outcomes and increased costs in this complex population. In this national analysis, we found a rising prevalence of malnutrition in older trauma patients over the six-year study period. Malnutrition was disproportionately more common among individuals of lower income, non-White race, and with Medicaid coverage. Finally, malnutrition was linked with substantially greater resource use. Several of these findings warrant further discussion.

Malnutrition was independently associated with adverse outcomes, even after adjusting for frailty. While this association aligns with previous smaller cohort studies [2,23], the present works provides a more robust, contemporary, and generalizable assessment. The mechanisms underlying this association are likely multifactorial. Malnutrition is known to impair wound healing, increase infection risk, and elevate post-discharge needs [2,23,24]. Moreover, poor nutrition contributes to reduced mobility, greater dependance, and cognitive decline, factors that interact synergistically to undermine rehabilitation and recovery [8]. In addition, the rising prevalence of malnutrition observed over the study period may reflect improved recognition, demographic shifts, or other unmeasured factors, underscoring its growing importance as a clinical and public health concern. Our findings add to the growing body of literature highlighting the critical role of malnutrition in risk stratification among older adults with traumatic injuries.

We noted significant disparities in nutritional status by race and income, echoing prior work regarding individual and structural-level determinants of malnutrition [25,26]. These findings align with previous studies that report an inverse relationship between neighborhood income and food desert severity, which has been associated with increased mortality, higher obesity rates, and a greater prevalence of cardiovascular disease [[27], [28], [29], [30]]. While policy interventions such as food delivery services and incentivizing grocers in underserved areas have shown mixed success, their impact may depend on cultural relevance [[31], [32], [33]]. In qualitative studies, patients expressed frustration with food assistance programs, stating that the initiatives failed to reflect cultural preferences [34]. In contrast, community-engaged, culturally grounded interventions have constantly improved uptake and efficiency [[35], [36], [37]]. Our findings highlight the ongoing need for nutritional equity interventions that are both structurally sound and socially informed.

In the present study, we noted malnutrition to be linked with increased inpatient costs, longer hospitalizations, and higher rates of nonhome discharge. Recent estimates suggest $30 billion in expenditures attributable to trauma care in older adults [38]. With malnutrition affecting 7–22 % of this population, and nearly half being at risk, nutritional status is a likely underscreened yet high-yield target for cost mitigation [2,8,24]. Sufficient evidence supports the cost-effectiveness of nutritional interventions. Wang et al. reported oral supplementation for malnourished hospitalized older adults to reduce per-patient costs by over $3500 annually [39]. Similarly, nutritional therapy has been demonstrated to hasten patient recovery in general. Indeed, Williams and colleagues found that early nutritional supplementation for older adults with hip or femur fractures significantly shortened LOS without increasing costs [40]. Taken together, these findings make a compelling case for routine malnutrition screening and timely nutritional support as strategies to improve patient outcomes and enhance value.

The present study has several important limitations. First, as an administrative database, the NIS is subject to variation in coding practices between centers. Additionally, there is limited granularity, with no data recorded for imaging findings or laboratory values, including albumin and pre-albumin levels. Importantly, in the NIS, we are unable to determine the timing of diagnosis, as such we cannot confirm definitively that malnutrition did not develop during hospitalization. However, in a supplemental analysis of the 2022 California State Inpatient Database, which includes data regarding the presence of a diagnosis upon admission [41], we found that 96.7 % of patients ≥65 years with malnutrition carried that diagnosis at admission. Given that the California State Inpatient Database, like the NIS, is maintained by the Agency for Healthcare Research and Quality, we are confident that most individuals identified as having malnutrition in this study did not develop the condition during hospitalization. Furthermore, although some baseline characteristics (e.g., income quartile, Charlson score, mFI-11) were statistically different between groups, these absolute differences were small and of limited clinical significance. Lastly, malnutrition may be under-coded in this dataset, and patients identified here are likely to represent those with more severe nutritional deficiency. Prior studies have shown wide variability in reported prevalence, making it difficult to estimate the extent of under-capture [2,8,24].

In summary, this study provides a contemporary national perspective on the association of malnutrition with clinical and financial outcomes among older adults with traumatic injuries. Malnutrition was independently associated with disproportionate morbidity, mortality, and financial burden. Given the aging demographic and rising cost of trauma care, understanding and addressing nutritional deficits is crucial. Our findings reinforce the need for early identification and intervention among this vulnerable population. Targeted strategies may improve recovery trajectories while promoting equity and sustainability in trauma care delivery.

The following is the supplementary data related to this article.

Supplemental Table 1

Clinical and financial outcomes stratified by nutrition status, excluding those admitted with falls.

AOR, Adjusted Odds Ratio; CI, Confidence Interval; IQR, Interquartile Range.

mmc1.docx (15.6KB, docx)

Funding/financial support

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

CRediT authorship contribution statement

Troy N. Coaston: Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Conceptualization. Konmal Ali: Writing – review & editing, Writing – original draft, Visualization, Conceptualization. Amulya Vadlakonda: Visualization, Methodology, Data curation, Conceptualization. Deep J. Mehta: Writing – original draft, Visualization, Conceptualization. Sara Sakowitz: Writing – review & editing, Data curation, Conceptualization. Dariush Yalzadeh: Writing – review & editing, Methodology, Investigation, Conceptualization. Areti Tillou: Writing – review & editing, Methodology, Investigation, Conceptualization. Peyman Benharash: Writing – review & editing, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

Ethics statement

This work complies with the standards put forth by Elsevier's Publishing Ethics Policy.

Declaration of competing interest

Author PB received proctor fees from Atricure as a surgical proctor. All other others declare no financial or non-financial competing interests.

References

  • 1.Karam B.S., Patnaik R., Murphy P., et al. Improving mortality in older adult trauma patients: are we doing better? J Trauma Acute Care Surg. 2022;92(2):413. doi: 10.1097/TA.0000000000003406. [DOI] [PubMed] [Google Scholar]
  • 2.Hosseinpour H., Anand T., Bhogadi S.K., et al. The implications of poor nutritional status on outcomes of geriatric trauma patients. Surgery. 2024;176(4):1281–1288. doi: 10.1016/j.surg.2024.06.047. [DOI] [PubMed] [Google Scholar]
  • 3.Hammer P.M., Storey A.C., Bell T., et al. Improving geriatric trauma outcomes: a small step toward a big problem. J Trauma Acute Care Surg. 2016;81(1):162. doi: 10.1097/TA.0000000000001063. [DOI] [PubMed] [Google Scholar]
  • 4.Stonko D.P., Etchill E.W., Giuliano K.A., et al. Failure to rescue in geriatric trauma: the impact of any complication increases with age and injury severity in elderly trauma patients. Am Surg. 2021;87(11):1760–1765. doi: 10.1177/00031348211054072. [DOI] [PubMed] [Google Scholar]
  • 5.Perdue P.W., Watts D.D., Kaufmann C.R., Trask A.L. Differences in mortality between elderly and younger adult trauma patients: geriatric status increases risk of delayed death. J Trauma Acute Care Surg. 1998;45(4) doi: 10.1097/00005373-199810000-00034. https://journals.lww.com/jtrauma/fulltext/1998/10000/differences_in_mortality_between_elderly_and.34.aspx [DOI] [PubMed] [Google Scholar]
  • 6.Panayi A.C., Orkaby A.R., Sakthivel D., et al. Impact of frailty on outcomes in surgical patients: a systematic review and meta-analysis. Am J Surg. 2019;218(2):393–400. doi: 10.1016/j.amjsurg.2018.11.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Orlandoni P., Venturini C., Jukic Peladic N., et al. Malnutrition upon hospital admission in geriatric patients: why assess it? Front Nutr. 2017;4 doi: 10.3389/fnut.2017.00050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Müller F.S., Meyer O.W., Chocano-Bedoya P., et al. Impaired nutritional status in geriatric trauma patients. Eur J Clin Nutr. 2017;71(5):602–606. doi: 10.1038/ejcn.2017.25. [DOI] [PubMed] [Google Scholar]
  • 9.Dijkink S., Meier K., Krijnen P., Yeh D.D., Velmahos G.C., Schipper I.B. Malnutrition and its effects in severely injured trauma patients. Eur J Trauma Emerg Surg. 2020;46(5):993–1004. doi: 10.1007/s00068-020-01304-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Gibbs J., Cull W., Henderson W., Daley J., Hur K., Khuri S.F. Preoperative serum albumin level as a predictor of operative mortality and morbidity: results from the national VA surgical risk study. Arch Surg. 1999;134(1):36–42. doi: 10.1001/archsurg.134.1.36. [DOI] [PubMed] [Google Scholar]
  • 11.Garwe T., Albrecht R.M., Stoner J.A., Mitchell S., Motghare P. Hypoalbuminemia at admission is associated with increased incidence of in-hospital complications in geriatric trauma patients. Am J Surg. 2016;212(1):109–115. doi: 10.1016/j.amjsurg.2015.06.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Gentile S., Lacroix O., Durand A.C., et al. Malnutrition: a highly predictive risk factor of short-term mortality in elderly presenting to the emergency department. J Nutr Health Aging. 2013;17(4):290–294. doi: 10.1007/s12603-012-0398-0. [DOI] [PubMed] [Google Scholar]
  • 13.Healthcare Cost and Utilization Project (HCUP). Overview of the national (nationwide) inpatient sample (NIS). Agency for Healthcare Research and Quality.
  • 14.Tran Z., Madrigal J., Pan C., et al. Impact of opioid use disorder on resource utilization and readmissions after operative trauma. Surgery. 2022;171(2):541–548. doi: 10.1016/j.surg.2021.06.025. [DOI] [PubMed] [Google Scholar]
  • 15.Doley J., Phillips W. Coding for malnutrition in the hospital: does it change reimbursement? Nutr Clin Pract. 2019;34(6):823–831. doi: 10.1002/ncp.10426. [DOI] [PubMed] [Google Scholar]
  • 16.Subramaniam A., Ueno R., Tiruvoipati R., et al. Defining ICD-10 surrogate variables to estimate the modified frailty index: a Delphi-based approach. BMC Geriatr. 2022;22(1):422. doi: 10.1186/s12877-022-03063-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Sundararajan V., Henderson T., Perry C., Muggivan A., Quan H., Ghali W.A. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol. 2004;57(12):1288–1294. doi: 10.1016/j.jclinepi.2004.03.012. [DOI] [PubMed] [Google Scholar]
  • 18.Clark D.E., Black A.W., Skavdahl D.H., Hallagan L.D. Open-access programs for injury categorization using ICD-9 or ICD-10. Inj Epidemiol. 2018;5(1):11. doi: 10.1186/s40621-018-0149-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Coaston T.N., Curry J., Vadlakonda A., et al. Center-level variation in the development of acute kidney injury following cardiac operations. CJC Open. 2025 doi: 10.1016/j.cjco.2025.04.003. Published online. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Using Appropriate Price Indices for Analyses of Health Care Expenditures or Income Across Multiple Years.
  • 21.Cuzick J. A wilcoxon-type test for trend. Stat Med. 1985;4(1):87–90. doi: 10.1002/sim.4780040112. [DOI] [PubMed] [Google Scholar]
  • 22.Zou H., Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Series B Stat Methodol. 2005;67(2):301–320. doi: 10.1111/j.1467-9868.2005.00503.x. [DOI] [Google Scholar]
  • 23.Kregel H.R., Murphy P.B., Attia M., et al. The geriatric nutritional risk index as a predictor of complications in geriatric trauma patients. J Trauma Acute Care Surg. 2022;93(2) doi: 10.1097/TA.0000000000003588. https://journals.lww.com/jtrauma/fulltext/2022/08000/the_geriatric_nutritional_risk_index_as_a.7.aspx [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Maurer E., Wallmeier V., Reumann M.K., et al. Risk of malnutrition in orthopedic trauma patients with surgical site infections is associated with increased morbidity and mortality – a 3-year follow-up study. Injury. 2020;51(10):2219–2229. doi: 10.1016/j.injury.2020.06.019. [DOI] [PubMed] [Google Scholar]
  • 25.Wahid N., Badaracco C., Valladares A.F., Depriest A., Collins A., Mitchell K. The role of inpatient malnutrition care to address health disparities among older adults. J Acad Nutr Diet. 2022;122(10, Supplement):S28–S33. doi: 10.1016/j.jand.2022.06.015. [DOI] [PubMed] [Google Scholar]
  • 26.Sadarangani T.R., Lydia M., Gary Y., Chau T.S., Brody A. Racial disparities in nutritional risk among community-dwelling older adults in adult day health care. J Nutr Gerontol Geriatr. 2019;38(4):345–360. doi: 10.1080/21551197.2019.1647327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Wood E.K., Stamos G., Mitchell A.J., et al. The association between food desert severity, socioeconomic status, and metabolic state during pregnancy in a prospective longitudinal cohort. Sci Rep. 2023;13(1):7197. doi: 10.1038/s41598-023-32783-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Gordon C., Purciel-Hill M., Ghai N.R., Kaufman L., Graham R., Van Wye G. Measuring food deserts in New York City’s low-income neighborhoods. Health Place. 2011;17(2):696–700. doi: 10.1016/j.healthplace.2010.12.012. [DOI] [PubMed] [Google Scholar]
  • 29.Odoms-Young A., Brown A.G.M., Agurs-Collins T., Glanz K. Food insecurity, neighborhood food environment, and health disparities: state of the science, research gaps and opportunities. Am J Clin Nutr. 2024;119(3):850–861. doi: 10.1016/j.ajcnut.2023.12.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Aris I.M., Wu A.J., Lin P.I.D., et al. Neighborhood food access in early life and trajectories of child body mass index and obesity. JAMA Pediatr. 2024;178(11):1172–1182. doi: 10.1001/jamapediatrics.2024.3459. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Engler-Stringer Rachel, Fuller Daniel, Abeykoon A.M. Hasanthi, Olauson Caitlin, Muhajarine Nazeem. An examination of failed grocery store interventions in former food deserts. Health Educ Behav. 2019;46(5):749–754. doi: 10.1177/1090198119853009. [DOI] [PubMed] [Google Scholar]
  • 32.Cantor J., Beckman R., Collins R.L., Dastidar M.G., Richardson A.S., Dubowitz T. SNAP participants improved food security and diet after a full-service supermarket opened in an urban food desert. Health Aff. 2020;39(8):1386–1394. doi: 10.1377/hlthaff.2019.01309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Gany F., Melnic I., Wu M., et al. Food to overcome outcomes disparities: a randomized controlled trial of food insecurity interventions to improve cancer outcomes. J Clin Oncol. 2022;40(31):3603–3612. doi: 10.1200/JCO.21.02400. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.McWhorter J.W., Danho M.P., LaRue D.M., et al. Barriers and facilitators of implementing a clinic-integrated food prescription plus culinary medicine program in a low-income food insecure population: a qualitative study. J Acad Nutr Diet. 2022;122(8):1499–1513. doi: 10.1016/j.jand.2021.11.016. [DOI] [PubMed] [Google Scholar]
  • 35.Livingstone K.M., Love P., Mathers J.C., Kirkpatrick S.I., Olstad D.L. Cultural adaptations and tailoring of public health nutrition interventions in indigenous peoples and ethnic minority groups: opportunities for personalised and precision nutrition. Proc Nutr Soc. 2023;82(4):478–486. doi: 10.1017/S002966512300304X. [DOI] [PubMed] [Google Scholar]
  • 36.Shapiro J., Grajower M.M. The influence of diverse cultures on nutrition, diabetes management and patient education. Nutrients. 2024;16(21) doi: 10.3390/nu16213771. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Katre A., Raddatz B. Low-income families’ direct participation in food-systems innovation to promote healthy food behaviors. Nutrients. 2023;15(5) doi: 10.3390/nu15051271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Fakhry S.M., Shen Y., Biswas S., et al. The public health burden of geriatric trauma: analysis of 2,688,008 hospitalizations from centers for medicare and medicaid services inpatient claims. J Trauma Acute Care Surg. 2022;92:984–989. doi: 10.1097/TA.0000000000003572. Lippincott Williams and Wilkins. [DOI] [PubMed] [Google Scholar]
  • 39.Wang S., Shafrin J., Kerr K.W., Schuetz P. Health economic value of postacute oral nutritional supplementation in older adult medical patients at risk for malnutrition: a US-based modelling approach. BMJ Open. 2024;14(11) doi: 10.1136/bmjopen-2024-086787. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Williams D.G.A., Ohnuma T., Haines K.L., et al. Association between early postoperative nutritional supplement utilisation and length of stay in malnourished hip fracture patients. Br J Anaesth. 2021;126(3):730–737. doi: 10.1016/j.bja.2020.12.026. [DOI] [PubMed] [Google Scholar]
  • 41.Healthcare Cost and Utilization Project (HCUP). Overview of the State Inpatient Databases (SID). Agency for Healthcare Research and Quality. [PubMed]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Table 1

Clinical and financial outcomes stratified by nutrition status, excluding those admitted with falls.

AOR, Adjusted Odds Ratio; CI, Confidence Interval; IQR, Interquartile Range.

mmc1.docx (15.6KB, docx)

Articles from Surgery Open Science are provided here courtesy of Elsevier

RESOURCES