Assessing potential benefits of visits to neighborhoods with higher tree canopy coverage using mobility data: Associations with cardiovascular health outcomes in twenty US metropolitan areas.

BACKGROUND: Research on health benefits due to exposure to green space, such as tree canopy coverage, has predominantly focused on canopy coverage in home neighborhoods. Yet exposures to tree canopy coverage in other spaces visited during the week or on weekends outside the home neighborhoods remains largely unexplored. OBJECTIVES: We examined whether differences in coverage levels of tree canopy in neighborhoods visited compared to home neighborhoods was associated with lower prevalence of coronary heart disease (CHD) and stroke, adjusting for exposure to home canopy coverage. We further investigated if the associations varied across levels of home canopy coverage, and if they were more pronounced on weekdays or weekends. METHODS: We used 2018 mobile phone data from the twenty largest U.S. Metropolitan Statistical Areas (MSAs). For each home census tract, we derived a weighted tree canopy coverage exposure from all visited tracts based on the proportion of visits to other tracts by home tract residents. We subtracted home canopy coverage from the weighted canopy coverage in each of the visited tracts to calculate tract-specific differences. We evaluated associations between differences in tree canopy coverage and prevalence of CHD and stroke via spatial error models, adjusting for tract-level home canopy coverage, MSA, socioeconomic and built environment characteristics. RESULTS: For every ten-percentage-point increase in tree canopy coverage in visited tracts relative to home tracts, there was a 0.32-0.34% decrease in stroke prevalence. Association with CHD prevalence was not observed after adjusting for spatial autocorrelation. Variations between weekdays and weekends were minimal. The difference in tree canopy coverage was associated with CHD prevalence only for home tracts with low tree canopy coverage, while the difference was associated with stroke prevalence across home tracts with low, moderate, and high tree canopy coverage, with diminishing effect size. DISCUSSION: This study identified that greater tree canopy coverage in visited neighborhoods relative to home neighborhoods was associated with lower stroke prevalence, and associations varied across home neighborhoods with different tree canopy coverage levels. It emphasized the need to factor in the neighborhood mobility networks in urban planning initiatives to promote cardiovascular health.

Understanding the Accumulation of Health-Related Inequities Over the Life Course Using the Mean Cumulative Count.

Understanding how health inequities develop over time is necessary to inform interventions, but methods for doing so are underutilized. We provide an example of the accumulation of stressful life events using the mean cumulative count (MCC), which estimates the expected number of events per person as a function of time, allowing for censoring and competing events. Data came from the National Longitudinal Survey of Youth 1997, a nationally representative data set. To compare the MCC with standard practice, we present the proportions of persons experiencing 1, 2, and ≥3 stressful events and the cumulative probability of experiencing at least 1 event by the end of follow-up. Our sample included 6,522 individuals aged 18-33 years who were followed for a median of 14 years. Using the MCC, by age 20 years the expected number of encounters was 56 events per 100 participants for Black non-Hispanic persons, 47 per 100 for White non-Hispanic persons, and 50 per 100 for Hispanic persons. By age 33 years, inequities grew to 117, 99, and 108 events per 100 persons, respectively. The MCC revealed that inequities in stressful events accumulate over the course of early adulthood, partially driven by repeat events; this information was not evident from conventional approaches. This method can be used to identify intervention points for disrupting the accumulation of repeat events to improve health equity.

Identifying and estimating effects of sustained interventions under parallel trends assumptions.

Many research questions in public health and medicine concern sustained interventions in populations defined by substantive priorities. Existing methods to answer such questions typically require a measured covariate set sufficient to control confounding, which can be questionable in observational studies. Differences-in-differences rely instead on the parallel trends assumption, allowing for some types of time-invariant unmeasured confounding. However, most existing difference-in-differences implementations are limited to point treatments in restricted subpopulations. We derive identification results for population effects of sustained treatments under parallel trends assumptions. In particular, in settings where all individuals begin follow-up with exposure status consistent with the treatment plan of interest but may deviate at later times, a version of Robins' g-formula identifies the intervention-specific mean under stable unit treatment value assumption, positivity, and parallel trends. We develop consistent asymptotically normal estimators based on inverse-probability weighting, outcome regression, and a double robust estimator based on targeted maximum likelihood. Simulation studies confirm theoretical results and support the use of the proposed estimators at realistic sample sizes. As an example, the methods are used to estimate the effect of a hypothetical federal stay-at-home order on all-cause mortality during the COVID-19 pandemic in spring 2020 in the United States.

Inequities in life course criminal legal system sanctions: measuring cumulative involvement.

PURPOSE: The impact of incarceration on health is well known. Yet, most studies measure incarceration alone and miss additional exposure to the criminal legal system over time. We evaluated adult criminal legal sanctions - inclusive of arrests, charges, probation, incarceration - from ages 18-35 and inequities by juvenile sanctions and race. METHODS: Using the National Longitudinal Survey on Youth 1997, a nationally representative data set of adolescents followed into their mid-thirties (1997-2017), we calculated the mean cumulative count, or the average number of criminal legal events per person per study visit, stratified by juvenile sanctions and race. RESULTS: Of 7024 participants, 1679 experienced 3,075 encounters. There were seven arrests, 30 charges, nine probation encounters, and 13 incarceration events /100 participants by age 35. Juvenile sanctions were most common for Black individuals. Among those experiencing juvenile sanctions, Black and White individuals had similar numbers of encounters, but Black individuals had more arrests and incarceration stays. For those without juvenile encounters, Black individuals had more encounters than White individuals. CONCLUSIONS: Research on health effects of criminal legal sanctions must consider encounters beyond incarceration and focus on life course trajectories and racial inequities.

Does histologic subtype impact overall survival in observed T1a kidney cancers compared with competing risks? Implications for biopsy as a risk stratification tool.

OBJECTIVES: We sought to assess if adding a biopsy proven histologic subtype to a model that predicts overall survival that includes variables representing competing risks in observed, biopsy proven, T1a renal cell carcinomas, enhances the model's performance. METHODS: The National Cancer Database was assessed (years 2004-2015) for patients with observed T1a renal cell carcinoma who had undergone renal mass biopsy. Kaplan-Meier curves were utilized to estimate overall survival stratified by histologic subtype. We utilized C-index from a Cox proportional hazards model to evaluate the impact of adding histologic subtypes to a model to predict overall survival for each stage. RESULTS: Of 132 958 T1a renal masses identified, 1614 had biopsy proven histology and were managed non-operatively. Of those, 61% were clear cell, 33% papillary, and 6% chromophobe. Adjusted Kaplan-Meier curves demonstrated a difference in overall survival between histologic subtypes (P = 0.010) with greater median overall survival for patients with chromophobe (85.1 months, hazard rate 0.45, P = 0.005) compared to clear cell (64.8 months, reference group). Adding histology to a model with competing risks alone did not substantially improve model performance (C-index 0.65 vs 0.64 respectively). CONCLUSIONS: Incorporation of histologic subtype into a risk stratification model to determine prognostic overall survival did not improve modeling of overall survival compared with variables representing competing risks in patients with T1a renal cell carcinoma managed with observation. These results suggest that performing renal mass biopsy in order to obtain tumor histology may have limited utility. Future studies should further investigate the overall utility of renal mass biopsy for observed T1a kidney cancers.

Interventions on Socioeconomic and Racial Inequities in Respiratory Pandemics: a Rapid Systematic Review.

Purpose of Review: Racial and socioeconomic inequities in respiratory pandemics have been consistently documented, but little official guidance exists on effective action to prevent these. We systematically reviewed quantitative evaluations of (real or simulated) interventions targeting racial and socioeconomic inequities in respiratory pandemic outcomes. Recent Findings: Our systematic search returned 10,208 records, of which 5 met inclusion criteria, including observational (n = 1), randomized trial (n = 1), and simulation (n = 3) studies. Interventions studied included vaccination parity, antiviral distribution, school closure, disinfection, personal protective equipment, and paid sick leave, with a focus on Black (n = 3) and/or Latinx (n = 4) or low-SES (n = 2) communities. Results are suggestive that these interventions might be effective at reducing racial and/or SES disparities in pandemics. Summary: There is a dearth of research on strategies to reduce pandemic disparities. We provide theory-driven, concrete suggestions for incorporating equity into intervention research for pandemic preparedness, including a focus on social and economic policies.

Reporting guidelines for human microbiome research: the STORMS checklist.

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

Overall Survival of Biopsy-confirmed T1B and T2A Kidney Cancers Managed With Observation: Prognostic Value of Tumor Histology.

INTRODUCTION: The natural history of T1b (4-7 cm) or T2a (> 7-10 cm) kidney cancers managed with observation is not well-understood. The aim of our study was to determine if the addition of histologic subtype to a predictive model of overall survival (OS) that includes covariates for competing risks in observed, biopsy-proven, T1b and T2a renal cell carcinomas (RCCs) improves the model's performance. MATERIALS AND METHODS: We queried the National Cancer Database for patients with biopsy-proven stage T1b or T2a RCC and managed nonoperatively between 2004 and 2015. OS was estimated by Kaplan-Meier curves based on histologic subtype. The concordance index (c-index) from a Cox proportional hazards model was used to estimate the extent to which histologic subtypes predict survival for each stage when included in a model along with competing risks of age, gender, race/ethnicity, insurance status, area-level socioeconomic indicators, Charlson-Deyo index, and tumor grade. RESULTS: A total of 937 patients (754 with T1b and 185 with T2a) with biopsy-proven RCC were identified. Kaplan-Meier analysis suggested differences in OS by histologic subtype where sarcomatoid, followed by clear cell, papillary, and chromophobe, had the highest mortality risk at 1, 3, and 5 years. However, there was marginal improvement in the multivariable model of OS using competing risks and histology (c-index, 0.64 and 0.697) compared with competing risks alone (c-index, 0.631 and 0.671) for T1b and T2a RCCs, respectively. CONCLUSIONS: In patients with T1b or T2a RCC managed with observation, incorporation of histologic subtype into a risk-stratification model to determine prognostic OS did not improve modeling of OS compared with variables representing competing risks. Histologic subtype of observed T1b and T2a RCC appears to have prognostic OS value when not considering competing risks. These findings may impact the usefulness of renal biopsy to inform decision-making when managing patients with T1b and T2a renal tumors with observation.

Early Signs of Gut Microbiome Aging: Biomarkers of Inflammation, Metabolism, and Macromolecular Damage in Young Adulthood.

Emerging links between gut microbiota and diseases of aging point to possible shared immune, metabolic, and cellular damage mechanisms, operating long before diseases manifest. We conducted 16S rRNA sequencing of fecal samples collected from a subsample (n = 668) of Add Health Wave V, a nationally representative longitudinal study of adults aged 32-42. An overlapping subsample (n = 345) included whole-blood RNA-seq. We examined associations between fecal taxonomic abundances and dried blood spot-based markers of lipid and glucose homeostasis and C-reactive protein (measured in Wave IV), as well as gene expression markers of inflammation, cellular damage, immune cell composition, and transcriptomic age (measured in Wave V), using Bayesian hierarchical models adjusted for potential confounders. We additionally estimated a co-abundance network between inflammation-related genes and bacterial taxa using penalized Gaussian graphical models. Strong and consistent microbiota associations emerged for HbA1c, glucose, C-reactive protein, and principal components of genes upregulated in inflammation, DNA repair, and reactive oxygen species, with Streptococcus infantis, Pseudomonas spp., and Peptoniphilus as major players for each. This pattern was largely echoed (though attenuated) for immunological cell composition gene sets, and only Serratia varied meaningfully by transcriptomic age. Network co-abundance indicated relationships between Prevotella sp., Bacteroides sp., and Ruminococcus sp. and gut immune/metabolic regulatory activity, and Ruminococcus sp, Dialister, and Butyrivibrio crossotus with balance between Th1 and Th2 inflammation. In conclusion, many common associations between microbiota and major physiologic aging mechanisms are evident in early-mid adulthood and suggest avenues for early detection and prevention of accelerated aging.

Social Media- and Internet-Based Disease Surveillance for Public Health.

Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.

Prognostic Value of Histologic Subtype and Treatment Modality for T1a Kidney Cancers.

INTRODUCTION: To evaluate overall survival (OS) of T1a kidney cancers stratified by histologic subtype and curative treatment including partial nephrectomy (PN), percutaneous ablation (PA), and radical nephrectomy (RN). MATERIALS AND METHODS: We queried the National Cancer Data Base (2004-2015) for patients with T1a kidney cancers who were treated surgically. OS was estimated by Kaplan-Meier curves based on histologic subtype and management. Cox proportional regression models were used to determine whether histologic subtypes and management procedure predicted OS. RESULTS: 46,014 T1a kidney cancers met inclusion criteria. Kaplan Meier curves demonstrated differences in OS by treatment for clear cell, papillary, chromophobe, and cystic histologic subtypes (all p < 0.001), but no differences for sarcomatoid (p = 0.110) or collecting duct (p = 0.392) were observed. Adjusted Cox regression showed worse OS for PA than PN among patients with clear cell (HR 1.58, 95%CI [1.44-1.73], papillary RCC (1.53 [1.34-1.75]), and chromophobe RCC (2.19 [1.64-2.91]). OS was worse for RN than PN for clear cell (HR 1.38 [1.28-1.50]) papillary (1.34 [1.16-1.56]) and chromophobe RCC (1.92 [1.43-2.58]). Predictive models using Cox proportional hazards incorporating histology and surgical procedure alone were limited (c-index 0.63) while adding demographics demonstrated fair predictive power for OS (c-index 0.73). CONCLUSIONS: In patients with pathologic T1a RCC, patterns of OS differed by surgery and histologic subtype. Patients receiving PN appears to have better prognosis than both PA and RN. However, the incorporation of histologic subtype and treatment modality into a risk stratification model to predict OS had limited utility compared with variables representing competing risks.

Gut bacterial taxonomic abundances vary with cognition, personality, and mood in the Wisconsin Longitudinal Study.

Animal studies have shown that the gut microbiome can influence memory, social behavior, and anxiety-like behavior. Several human studies show similar results where variation in the gut microbiome is associated with dementia, depression, and personality traits, though most of these studies are limited by small sample size and other biases. Here, we analyzed fecal samples from 313 participants in the Wisconsin Longitudinal Study, a randomly selected population-based cohort of older adults, with measured psycho-cognitive dimensions (cognition, mood, and personality) and key confounders. 16s V4 sequencing showed that Megamonas is associated with all measured psycho-cognitive traits, Fusobacterium is associated with cognitive and personality traits, Pseudoramibacter_Eubacterium is associated with mood and personality traits, Butyvibrio is associated with cognitive traits, and Cloacibacillus is associated with mood traits. These findings are robust to sensitivity analyses and provide novel evidence of shared relationships between the gut microbiome and multiple psycho-cognitive traits in older adults, confirming some of the animal literature, while also providing new insights. While we addressed some of the weaknesses in prior studies, further studies are necessary to elucidate temporal and causal relationships between the gut microbiome and multiple psycho-cognitive traits in well-phenotyped, randomly-selected population-based samples.

Sick Individuals and Sick (Microbial) Populations: Challenges in Epidemiology and the Microbiome.

The human microbiome represents a new frontier in understanding the biology of human health. While epidemiology in this area is still in its infancy, its scope will likely expand dramatically over the coming years. To rise to the challenge, we argue that epidemiology should capitalize on its population perspective as a critical complement to molecular microbiome research, allowing for the illumination of contextual mechanisms that may vary more across populations rather than among individuals. We first briefly review current research on social context and the gut microbiome, focusing specifically on socioeconomic status (SES) and race/ethnicity. Next, we reflect on the current state of microbiome epidemiology through the lens of one specific area, the association of the gut microbiome and metabolic disorders. We identify key methodological shortcomings of current epidemiological research in this area, including extensive selection bias, the use of noncompositionally robust measures, and a lack of attention to social factors as confounders or effect modifiers.

Teaching yourself about structural racism will improve your machine learning.

In this commentary, we put forth the following argument: Anyone conducting machine learning in a health-related domain should educate themselves about structural racism. We argue that structural racism is a critical body of knowledge needed for generalizability in almost all domains of health research.

Different models for prediction of radical cystectomy postoperative complications and care pathways.

BACKGROUND: Radical cystectomy for bladder cancer has one of the highest rates of morbidity among urologic surgery, but the ability to predict postoperative complications remains poor. Our study objective was to create machine learning models to predict complications and factors leading to extended length of hospital stay and discharge to a higher level of care after radical cystectomy. METHODS: Using the American College of Surgeons National Surgical Quality Improvement Program, peri-operative adverse outcome variables for patients undergoing elective radical cystectomy for bladder cancer from 2005 to 2016 were extracted. Variables assessed include occurrence of minor, infectious, serious, or any adverse events, extended length of hospital stay, and discharge to higher-level care. To develop predictive models of radical cystectomy complications, we fit generalized additive model (GAM), least absolute shrinkage and selection operator (LASSO) logistic, neural network, and random forest models to training data using various candidate predictor variables. Each model was evaluated on the test data using receiver operating characteristic curves. RESULTS: A total of 7557 patients were identified who met the inclusion criteria, and 2221 complications occurred. LASSO logistic models demonstrated the highest area under curve for predicting any complications (0.63), discharge to a higher level of care (0.75), extended length of stay (0.68), and infectious (0.62) adverse events. This was comparable with random forest in predicting minor (0.60) and serious (0.63) adverse events. CONCLUSIONS: Our models perform modestly in predicting radical cystectomy complications, highlighting both the complex cystectomy process and the limitations of large healthcare datasets. Identifying the most important variable leading to each type of adverse event may allow for further strategies to model cystectomy complications and target optimization of modifiable variables pre-operative to reduce postoperative adverse events.

Sociodemographic variation in the oral microbiome.

PURPOSE: Variations in the oral microbiome are potentially implicated in social inequalities in oral disease, cancers, and metabolic disease. We describe sociodemographic variation of oral microbiomes in a diverse sample. METHODS: We performed 16S rRNA sequencing on mouthwash specimens in a subsample (n = 282) of the 2013-2014 population-based New York City Health and Nutrition Examination Study. We examined differential abundance of 216 operational taxonomic units, and alpha and beta diversity by age, sex, income, education, nativity, and race/ethnicity. For comparison, we examined differential abundance by diet, smoking status, and oral health behaviors. RESULTS: Sixty-nine operational taxonomic units were differentially abundant by any sociodemographic variable (false discovery rate < 0.01), including 27 by race/ethnicity, 21 by family income, 19 by education, 3 by sex. We found 49 differentially abundant by smoking status, 23 by diet, 12 by oral health behaviors. Genera differing for multiple sociodemographic characteristics included Lactobacillus, Prevotella, Porphyromonas, Fusobacterium. CONCLUSIONS: We identified oral microbiome variation consistent with health inequalities, more taxa differing by race/ethnicity than diet, and more by SES variables than oral health behaviors. Investigation is warranted into possible mediating effects of the oral microbiome in social disparities in oral and metabolic diseases and cancers.

Tobacco exposure associated with oral microbiota oxygen utilization in the New York City Health and Nutrition Examination Study.

PURPOSE: The effect of tobacco exposure on the oral microbiome has not been established. METHODS: We performed amplicon sequencing of the 16S ribosomal RNA gene V4 variable region to estimate bacterial community characteristics in 259 oral rinse samples, selected based on self-reported smoking and serum cotinine levels, from the 2013-2014 New York City Health and Nutrition Examination Study. We identified differentially abundant operational taxonomic units (OTUs) by primary and secondhand tobacco exposure, and used "microbe set enrichment analysis" to assess shifts in microbial oxygen utilization. RESULTS: Cigarette smoking was associated with depletion of aerobic OTUs (Enrichment Score test statistic ES = -0.75, P = .002) with a minority (29%) of aerobic OTUs enriched in current smokers compared with never smokers. Consistent shifts in the microbiota were observed for current cigarette smokers as for nonsmokers with secondhand exposure as measured by serum cotinine levels. Differential abundance findings were similar in crude and adjusted analyses. CONCLUSIONS: Results support a plausible link between tobacco exposure and shifts in the oral microbiome at the population level through three lines of evidence: (1) a shift in microbiota oxygen utilization associated with primary tobacco smoke exposure; (2) consistency of abundance fold changes associated with current smoking and shifts along the gradient of secondhand smoke exposure among nonsmokers; and (3) consistency after adjusting for a priori hypothesized confounders.

The Charlson Index Is Insufficient to Control for Comorbidities in a National Trauma Registry.

BACKGROUND: The Charlson Comorbidity Index (CCI) is frequently used to control for confounding by comorbidities in observational studies, but its performance as such has not been studied. We evaluated the performance of CCI and an alternative summary method, logistic principal component analysis (LPCA), to adjust for comorbidities, using as an example the association between insurance and mortality. MATERIALS AND METHODS: Using all admissions in the National Trauma Data Bank 2010-2015, we extracted mortality, payment method, and 36 International Classification of Disease, Ninth Revision-derived comorbidities. We estimated odds ratios (ORs) for the association between uninsured status and mortality before and after adjusting for CCI, LPCA, and separate covariates. We also calculated standardized mean differences (SMDs) of comorbidity variables before and after weighting the sample using inverse probability of treatment weights for CCI, LPCA, and separate covariates. RESULTS: In 4,936,880 admissions, most (68.3%) had at least one comorbidity. Considerable imbalance was observed in the unweighted sample (mean SMD = 0.086, OR = 1.17), which was almost entirely eliminated by inverse probability of treatment weights on separate covariates (mean SMD = 0.012, OR = 1.36). The CCI performed similarly to the unweighted sample (mean SMD = 0.080, OR = 1.25), whereas two LPCA axes were better able to control for confounding (mean SMD = 0.04, OR = 1.31). Using covariate adjustment, the CCI accounted for 56.1% of observed confounding, whereas two LPCA axes accounted for 91.3%. CONCLUSIONS: The use of the CCI to adjust for confounding may result in residual confounding, and alternative strategies should be considered. LPCA may be a viable alternative to adjusting for each comorbidity when samples are small or positivity assumptions are violated.

Interfacility Transfer is Associated With Lower Mortality in Undertriaged Gunshot Wound Patients.

BACKGROUND: Treatment at a Level I trauma center yields better outcomes for patients with moderate-to-severe injury as compared with treatment in nontrauma centers. We examined the association between interfacility transfer to a level I or II trauma center and mortality for gunshot wound patients, among patients initially transported to a lower level or undesignated facility. MATERIALS AND METHODS: This retrospective cohort study included all patients from the National Trauma Data Bank (2010-2015) with firearm as the external cause of injury, who met CDC criteria for emergency medical services triage to a higher level (American College of Surgeons [ACS] Level II or above) trauma center. We compared outcomes between patients (a) treated in an ACS level III or below facility and not transferred versus (b) transferred to an ACS level II or above facility, adjusting for confounders using inverse probability of treatment weights. RESULTS: Of the total 62,277 patients, 10,968 (17.6%) were transferred to a level II center or above, and 51,309 (82.4%) were treated at a level III or below or undesignated center. In adjusted analysis comparing transferred versus not transferred patients, risk was lower for mortality (risk ratio [RR] 0.81, 95% confidence interval [CI] 0.70 to 0.95 P = 0.011) but similar for any complication (RR 1.02, 95% CI 0.83 to 1.25 P = 0.87) and the five most common complications. Results were consistent when accounting for data missing at random, and when including state trauma center designations in the definition of Level II or greater versus III and below. CONCLUSIONS: Our study found lower mortality but similar complication risk associated with interfacility transfer for undertriaged gunshot wound patients. This suggests that transfer to a higher level center is warranted among these patients, with improved care potentially outweighing potential harms because of transfer.