HiPhase: jointly phasing small, structural, and tandem repeat variants from HiFi sequencing.

MOTIVATION: In diploid organisms, phasing is the problem of assigning the alleles at heterozygous variants to one of two haplotypes. Reads from PacBio HiFi sequencing provide long, accurate observations that can be used as the basis for both calling and phasing variants. HiFi reads also excel at calling larger classes of variation, such as structural or tandem repeat variants. However, current phasing tools typically only phase small variants, leaving larger variants unphased. RESULTS: We developed HiPhase, a tool that jointly phases SNVs, indels, structural, and tandem repeat variants. The main benefits of HiPhase are (i) dual mode allele assignment for detecting large variants, (ii) a novel application of the A*-algorithm to phasing, and (iii) logic allowing phase blocks to span breaks caused by alignment issues around reference gaps and homozygous deletions. In our assessment, HiPhase produced an average phase block NG50 of 480 kb with 929 switchflip errors and fully phased 93.8% of genes, improving over the current state of the art. Additionally, HiPhase jointly phases SNVs, indels, structural, and tandem repeat variants and includes innate multi-threading, statistics gathering, and concurrent phased alignment output generation. AVAILABILITY AND IMPLEMENTATION: HiPhase is available as source code and a pre-compiled Linux binary with a user guide at https://github.com/PacificBiosciences/HiPhase.

Polishing De Novo Nanopore Assemblies of Bacteria and Eukaryotes With FMLRC2.

As the accuracy and throughput of nanopore sequencing improve, it is increasingly common to perform long-read first de novo genome assemblies followed by polishing with accurate short reads. We briefly introduce FMLRC2, the successor to the original FM-index Long Read Corrector (FMLRC), and illustrate its performance as a fast and accurate de novo assembly polisher for both bacterial and eukaryotic genomes.

Loss of function of FAM177A1, a Golgi complex localized protein, causes a novel neurodevelopmental disorder.

PURPOSE: The function of FAM177A1 and its relationship to human disease is largely unknown. Recent studies have demonstrated FAM177A1 to be a critical immune-associated gene. One previous case study has linked FAM177A1 to a neurodevelopmental disorder in four siblings. METHODS: We identified five individuals from three unrelated families with biallelic variants in FAM177A1. The physiological function of FAM177A1 was studied in a zebrafish model organism and human cell lines with loss-of-function variants similar to the affected cohort. RESULTS: These individuals share a characteristic phenotype defined by macrocephaly, global developmental delay, intellectual disability, seizures, behavioral abnormalities, hypotonia, and gait disturbance. We show that FAM177A1 localizes to the Golgi complex in mammalian and zebrafish cells. Intersection of the RNA-seq and metabolomic datasets from FAM177A1-deficient human fibroblasts and whole zebrafish larvae demonstrated dysregulation of pathways associated with apoptosis, inflammation, and negative regulation of cell proliferation. CONCLUSION: Our data sheds light on the emerging function of FAM177A1 and defines FAM177A1-related neurodevelopmental disorder as a new clinical entity.

Rasch analysis of the modified Fatigue Severity Scale in neuromuscular disorders and comparison between sex, age and diagnoses.

INTRODUCTION/AIMS: Fatigue is a common and debilitating symptom encountered in the neuromuscular clinic. The 7-item Fatigue Severity Scale (FSS-7) is a Rasch-modified assessment validated in inflammatory neuropathies but not across a typical neuromuscular patient population. The aim of this study was to validate this measure in neuromuscular disorders and to compare between patient sex, age and diagnoses. METHODS: The modified FSS-7 was mailed to patients recruited from a specialist neuromuscular clinic at the Walton Centre. Responses were subjected to Rasch analysis and descriptive statistics were performed on the Rasch converted data. RESULTS: The mFSS-7 met the Rasch model expectations with an overall Chi-square probability of 0.4918, a strict unidimensional scale free from differential item functioning (DIF) that satisfied the model with substantial test-retest reliability using Lin's concordance correlation coefficient 0.71 (95% CI 0.63-0.77). A 15.7% ceiling effect was observed in this patient cohort. Post hoc analysis did not show any significant difference in fatigue between sex, age or neuromuscular diagnoses. DISCUSSION: The self-completed Rasch mFSS-7 showed acceptable test-retest reliability across patients with varied disorders under follow-up in a specialist neuromuscular clinic. The ceiling effect constrains its use for those with the most severe fatigue. Future considerations could include assessment of the benefits of clinical interventions, particularly multidisciplinary team input or dedicated fatigue clinics.

Rasch analysis of the Unidimensional Self-Efficacy Scale in Neuromuscular Disorders and comparison between sex, age, and diagnoses.

INTRODUCTION/AIMS: Self-efficacy reflects a person's perceptions of their capabilities for specific tasks and influences motivation and performance. The Unidimensional Self-Efficacy in Neuromuscular Disorders (USE-NM) was modified from the Multiple Sclerosis (MS) USE-MS scale and administered to patients attending a specialist neuromuscular clinic. The aim was to investigate this measure in neuromuscular disorders and to compare between patient sex, age, and diagnosis. METHODS: The USE-NM was posted to patients recruited from a specialist neuromuscular clinic at the Walton Centre. Responses were subjected to Rasch analysis using RUMM2030 software and descriptive statistics were performed using SPSS version 28. RESULTS: One hundred and ninety-eight patients (56.1% male) grouped by age (<50; 50-59; 60-69; and >69 years) and with varied NM disorders returned the USE-NM. It did not meet the Rasch model expectations due to disordered thresholds of items 6 and 8 ("Sometimes I feel inadequate as a person because of my neuromuscular disorder" and "I feel that my social life would be better if I did not have a neuromuscular disorder"). Following item re-scoring, the modified USE-NM satisfied the Rasch model with a unidimensional scale free from differential item functioning and an overall chi-square probability of 0.146 with good reliability and validity. Post hoc nonparametric testing showed no significant difference in fatigue between sex, age, and neuromuscular diagnoses. DISCUSSION: The Rasch-modified USE-NM offers a measure of self-efficacy for neuromuscular disorders encountered in a typical specialist clinic. Future considerations could be given to assessing any benefits of multidisciplinary team input, across a specialist neuromuscular service.

The landscape of reported VUS in multi-gene panel and genomic testing: Time for a change.

PURPOSE: Variants of uncertain significance (VUS) are a common result of diagnostic genetic testing and can be difficult to manage with potential misinterpretation and downstream costs, including time investment by clinicians. We investigated the rate of VUS reported on diagnostic testing via multi-gene panels (MGPs) and exome and genome sequencing (ES/GS) to measure the magnitude of uncertain results and explore ways to reduce their potentially detrimental impact. METHODS: Rates of inconclusive results due to VUS were collected from over 1.5 million sequencing test results from 19 clinical laboratories in North America from 2020 to 2021. RESULTS: We found a lower rate of inconclusive test results due to VUSs from ES/GS (22.5%) compared with MGPs (32.6%; P < .0001). For MGPs, the rate of inconclusive results correlated with panel size. The use of trios reduced inconclusive rates (18.9% vs 27.6%; P < .0001), whereas the use of GS compared with ES had no impact (22.2% vs 22.6%; P = ns). CONCLUSION: The high rate of VUS observed in diagnostic MGP testing warrants examining current variant reporting practices. We propose several approaches to reduce reported VUS rates, while directing clinician resources toward important VUS follow-up.

County-Level Geographic Disparities in Disabilities Among US Adults, 2018.

INTRODUCTION: Local data are increasingly needed for public health practice. County-level data on disabilities can be a valuable complement to existing estimates of disabilities. The objective of this study was to describe the county-level prevalence of disabilities among US adults and identify geographic clusters of counties with a higher or lower prevalence of disabilities. METHODS: We applied a multilevel logistic regression and poststratification approach to geocoded 2018 Behavioral Risk Factor Surveillance System data, Census 2018 county-level population estimates, and American Community Survey 2014-2018 poverty estimates to generate county-level estimates for 6 functional disabilities and any disability type. We used cluster-outlier spatial statistical methods to identify clustered counties. RESULTS: Among 3,142 counties, median estimated prevalence was 29.5% for any disability and differed by type: hearing (8.0%), vision (4.9%), cognition (11.5%), mobility (14.9%), self-care (3.7%), and independent living (7.2%). The spatial autocorrelation statistic, Moran's I, was 0.70 for any disability and 0.60 or greater for all 6 types of disability, indicating that disabilities were highly clustered at the county level. We observed similar spatial cluster patterns in all disability types except hearing disability. CONCLUSION: The results suggest substantial differences in disability prevalence across US counties. These data, heretofore unavailable from a health survey, may help with planning programs at the county level to improve the quality of life for people with disabilities.

Syncope: Evaluation and Differential Diagnosis.

Syncope is an abrupt, transient, and complete loss of consciousness associated with an inability to maintain postural tone; recovery is rapid and spontaneous. The condition is common, resulting in about 1.7 million emergency department visits in 2019. The immediate cause of syncope is cerebral hypoperfusion, which may occur due to systemic vasodilation, decreased cardiac output, or both. The primary classifications of syncope are cardiac, reflex (neurogenic), and orthostatic. Evaluation focuses on history, physical examination (including orthostatic blood pressure measurements), and electrocardiographic results. If the findings are inconclusive and indicate possible adverse outcomes, additional testing may be considered. However, testing has limited utility, except in patients with cardiac syncope. Prolonged electrocardiographic monitoring, stress testing, and echocardiography may be beneficial in patients at higher risk of adverse outcomes from cardiac syncope. Neuroimaging should be ordered only when findings suggest a neurologic event or a head injury is suspected. Laboratory tests may be ordered based on history and physical examination findings (e.g., hemoglobin measurement if gastrointestinal bleeding is suspected). Patients are designated as having lower or higher risk of adverse outcomes according to history, physical examination, and electrocardiographic results, which can inform decisions regarding hospital admission. Risk stratification tools, such as the Canadian Syncope Risk Score, may be beneficial in this decision; some tools include cardiac biomarkers as a component. The prognosis of patients with reflex and orthostatic syncope is good; cardiac syncope is more likely to be associated with adverse outcomes.

Epidemiological and cohort study finds no association between COVID-19 and Guillain-Barré syndrome.

Reports of Guillain-Barré syndrome (GBS) have emerged during the Coronavirus disease 2019 (COVID-19) pandemic. This epidemiological and cohort study sought to investigate any causative association between COVID-19 infection and GBS. The epidemiology of GBS cases reported to the UK National Immunoglobulin Database was studied from 2016 to 2019 and compared to cases reported during the COVID-19 pandemic. Data were stratified by hospital trust and region, with numbers of reported cases per month. UK population data for COVID-19 infection were collated from UK public health bodies. In parallel, but separately, members of the British Peripheral Nerve Society prospectively reported incident cases of GBS during the pandemic at their hospitals to a central register. The clinical features, investigation findings and outcomes of COVID-19 (definite or probable) and non-COVID-19 associated GBS cases in this cohort were compared. The incidence of GBS treated in UK hospitals from 2016 to 2019 was 1.65-1.88 per 100 000 individuals per year. GBS incidence fell between March and May 2020 compared to the same months of 2016-19. GBS and COVID-19 incidences during the pandemic also varied between regions and did not correlate with one another (r = 0.06, 95% confidence interval: -0.56 to 0.63, P = 0.86). In the independent cohort study, 47 GBS cases were reported (COVID-19 status: 13 definite, 12 probable, 22 non-COVID-19). There were no significant differences in the pattern of weakness, time to nadir, neurophysiology, CSF findings or outcome between these groups. Intubation was more frequent in the COVID-19 affected cohort (7/13, 54% versus 5/22, 23% in COVID-19-negative) attributed to COVID-19 pulmonary involvement. Although it is not possible to entirely rule out the possibility of a link, this study finds no epidemiological or phenotypic clues of SARS-CoV-2 being causative of GBS. GBS incidence has fallen during the pandemic, which may be the influence of lockdown measures reducing transmission of GBS inducing pathogens such as Campylobacter jejuni and respiratory viruses.

Reducing Sanger confirmation testing through false positive prediction algorithms.

PURPOSE: Clinical genome sequencing (cGS) followed by orthogonal confirmatory testing is standard practice. While orthogonal testing significantly improves specificity, it also results in increased turnaround time and cost of testing. The purpose of this study is to evaluate machine learning models trained to identify false positive variants in cGS data to reduce the need for orthogonal testing. METHODS: We sequenced five reference human genome samples characterized by the Genome in a Bottle Consortium (GIAB) and compared the results with an established set of variants for each genome referred to as a truth set. We then trained machine learning models to identify variants that were labeled as false positives. RESULTS: After training, the models identified 99.5% of the false positive heterozygous single-nucleotide variants (SNVs) and heterozygous insertions/deletions variants (indels) while reducing confirmatory testing of nonactionable, nonprimary SNVs by 85% and indels by 75%. Employing the algorithm in clinical practice reduced overall orthogonal testing using dideoxynucleotide (Sanger) sequencing by 71%. CONCLUSION: Our results indicate that a low false positive call rate can be maintained while significantly reducing the need for confirmatory testing. The framework that generated our models and results is publicly available at https://github.com/HudsonAlpha/STEVE .

Estimating health service utilization potential using the supply-concentric demand-accumulation spatial availability index: a pulmonary rehabilitation case study.

The potential for a population at a given location to utilize a health service can be estimated using a newly developed measure called the supply-concentric demand accumulation (SCDA) spatial availability index. Spatial availability is the amount of demand at the given location that can be satisfied by the supply of services at a facility, after discounting the intervening demand among other populations that are located nearer to a facility location than the given population location. This differs from spatial accessibility measures which treat absolute distance or travel time as the factor that impedes utilization. The SCDA is illustrated using pulmonary rehabilitation (PR), which is a treatment for people with chronic obstructive pulmonary disease (COPD). The spatial availability of PR was estimated for each Census block group in Georgia using the 1105 residents who utilized one of 45 PR facilities located in or around Georgia. Data was provided by the Centers for Medicare & Medicaid Services. The geographic patterns of the SCDA spatial availability index and the two-step floating catchment area (2SFCA) spatial accessibility index were compared with the observed PR utilization rate using bivariate local indicators of spatial association. The SCDA index was more associated with PR utilization (Morans I = 0.607, P < 0.001) than was the 2SFCA (Morans I = 0.321, P < 0.001). These results suggest that the measures of spatial availability may be a better way to estimate the health care utilization potential than measures of spatial accessibility.

Measuring Alcohol Outlet Density: An Overview of Strategies for Public Health Practitioners.

CONTEXT: Excessive alcohol use is responsible for 88 000 deaths in the United States annually and cost the United States $249 billion in 2010. There is strong scientific evidence that regulating alcohol outlet density is an effective intervention for reducing excessive alcohol consumption and related harms, but there is no standard method for measuring this exposure. PROGRAM: We overview the strategies available for measuring outlet density, discuss their advantages and disadvantages, and provide examples of how they can be applied in practice. IMPLEMENTATION: The 3 main approaches for measuring density are container-based (eg, number of outlets in a county), distance-based (eg, average distance between a college and outlets), and spatial access-based (eg, weighted distance between town center and outlets). EVALUATION: While container-based measures are the simplest to calculate and most intuitive, distance-based or spatial access-based measures are unconstrained by geopolitical boundaries and allow for assessment of clustering (an amplifier of certain alcohol-related harms). Spatial access-based measures can also be adjusted for population size/demographics but are the most resource-intensive to produce. DISCUSSION: Alcohol outlet density varies widely across and between locations and over time, which is why it is important to measure it. Routine public health surveillance of alcohol outlet density is important to identify problem areas and detect emerging ones. Distance- or spatial access-based measures of alcohol outlet density are more resource-intensive than container-based measures but provide a much more accurate assessment of exposure to alcohol outlets and can be used to assess clustering, which is particularly important when assessing the relationship between density and alcohol-related harms, such as violent crime.

VarSight: prioritizing clinically reported variants with binary classification algorithms.

BACKGROUND: When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient's phenotypes. Typically, this is done through annotation, filtering, and then prioritization of variants for manual curation. However, prioritization of variants in rare disease patients remains a challenging task due to the high degree of variability in phenotype presentation and molecular source of disease. Thus, methods that can identify and/or prioritize variants to be clinically reported in the presence of such variability are of critical importance. METHODS: We tested the application of classification algorithms that ingest variant annotations along with phenotype information for predicting whether a variant will ultimately be clinically reported and returned to a patient. To test the classifiers, we performed a retrospective study on variants that were clinically reported to 237 patients in the Undiagnosed Diseases Network. RESULTS: We treated the classifiers as variant prioritization systems and compared them to four variant prioritization algorithms and two single-measure controls. We showed that the trained classifiers outperformed all other tested methods with the best classifiers ranking 72% of all reported variants and 94% of reported pathogenic variants in the top 20. CONCLUSIONS: We demonstrated how freely available binary classification algorithms can be used to prioritize variants even in the presence of real-world variability. Furthermore, these classifiers outperformed all other tested methods, suggesting that they may be well suited for working with real rare disease patient datasets.

Kilquist syndrome: A novel syndromic hearing loss disorder caused by homozygous deletion of SLC12A2.

Syndromic sensorineural hearing loss is multigenic and associated with malformations of the ear and other organ systems. Herein we describe a child admitted to the NIH Undiagnosed Diseases Program with global developmental delay, sensorineural hearing loss, gastrointestinal abnormalities, and absent salivation. Next-generation sequencing revealed a uniparental isodisomy in chromosome 5, and a 22 kb homozygous deletion in SLC12A2, which encodes for sodium, potassium, and chloride transporter in the basolateral membrane of secretory epithelia. Functional studies using patient-derived fibroblasts showed truncated SLC12A2 transcripts and markedly reduced protein abundance when compared with control. Loss of Slc12a2 in mice has been shown to lead to deafness, abnormal neuronal growth and migration, severe gastrointestinal abnormalities, and absent salivation. Together with the described phenotype of the Slc12a2-knockout mouse model, our results suggest that the absence of functional SLC12A2 causes a new genetic syndrome and is crucial for the development of auditory, neurologic, and gastrointestinal tissues.

Small Area Estimates of Populations With Chronic Conditions for Community Preparedness for Public Health Emergencies.

Objectives. To demonstrate a flexible and practical method to obtain near real-time estimates of the number of at-risk community-dwelling adults with a chronic condition in a defined area potentially affected by a public health emergency.Methods. We used small area estimation with survey responses from the 2016 Behavioral Risk Factor Surveillance System together with a geographic information system to predict the number of adults with chronic obstructive pulmonary disease who lived in the forecasted path of Hurricane Florence in North and South Carolina in 2018.Results. We estimated that a range of 32 002 to 676 536 adults with chronic obstructive pulmonary disease resided between 50 and 200 miles of 3 consecutive daily forecasted landfalls. The number of affected counties ranged from 8 to 10 (at 50 miles) to as many as 119 to 127 (at 200 miles).Conclusions. Community preparedness is critical to anticipating, responding to, and ameliorating these health threats. We demonstrated the feasibility of quickly producing detailed estimates of the number of residents with chronic conditions who may face life-threatening situations because of a natural disaster. These methods are applicable to a range of planning and response scenarios.

Racial and ethnic estimates of Alzheimer's disease and related dementias in the United States (2015-2060) in adults aged ≥65 years.

INTRODUCTION: Alzheimer's disease and related dementias (ADRD) cause a high burden of morbidity and mortality in the United States. Age, race, and ethnicity are important risk factors for ADRD. METHODS: We estimated the future US burden of ADRD by age, sex, and race and ethnicity by applying subgroup-specific prevalence among Medicare Fee-for-Service beneficiaries aged ≥65 years in 2014 to subgroup-specific population estimates for 2014 and population projection data from the United States Census Bureau for 2015 to 2060. RESULTS: The burden of ADRD in 2014 was an estimated 5.0 million adults aged ≥65 years or 1.6% of the population, and there are significant disparities in ADRD prevalence among population subgroups defined by race and ethnicity. ADRD burden will double to 3.3% by 2060 when 13.9 million Americans are projected to have the disease. DISCUSSION: These estimates can be used to guide planning and interventions related to caring for the ADRD population and supporting caregivers.

FMLRC: Hybrid long read error correction using an FM-index.

BACKGROUND: Long read sequencing is changing the landscape of genomic research, especially de novo assembly. Despite the high error rate inherent to long read technologies, increased read lengths dramatically improve the continuity and accuracy of genome assemblies. However, the cost and throughput of these technologies limits their application to complex genomes. One solution is to decrease the cost and time to assemble novel genomes by leveraging "hybrid" assemblies that use long reads for scaffolding and short reads for accuracy. RESULTS: We describe a novel method leveraging a multi-string Burrows-Wheeler Transform with auxiliary FM-index to correct errors in long read sequences using a set of complementary short reads. We demonstrate that our method efficiently produces significantly more high quality corrected sequence than existing hybrid error-correction methods. We also show that our method produces more contiguous assemblies, in many cases, than existing state-of-the-art hybrid and long-read only de novo assembly methods. CONCLUSION: Our method accurately corrects long read sequence data using complementary short reads. We demonstrate higher total throughput of corrected long reads and a corresponding increase in contiguity of the resulting de novo assemblies. Improved throughput and computational efficiency than existing methods will help better economically utilize emerging long read sequencing technologies.

Urban-Rural County and State Differences in Chronic Obstructive Pulmonary Disease - United States, 2015.

Chronic obstructive pulmonary disease (COPD) accounts for the majority of deaths from chronic lower respiratory diseases, the third leading cause of death in the United States in 2015 and the fourth leading cause in 2016.* Major risk factors include tobacco exposure, occupational and environmental exposures, respiratory infections, and genetics.† State variations in COPD outcomes (1) suggest that it might be more common in states with large rural areas. To assess urban-rural variations in COPD prevalence, hospitalizations, and mortality; obtain county-level estimates; and update state-level variations in COPD measures, CDC analyzed 2015 data from the Behavioral Risk Factor Surveillance System (BRFSS), Medicare hospital records, and death certificate data from the National Vital Statistics System (NVSS). Overall, 15.5 million adults aged ≥18 years (5.9% age-adjusted prevalence) reported ever receiving a diagnosis of COPD; there were approximately 335,000 Medicare hospitalizations (11.5 per 1,000 Medicare enrollees aged ≥65 years) and 150,350 deaths in which COPD was listed as the underlying cause for persons of all ages (40.3 per 100,000 population). COPD prevalence, Medicare hospitalizations, and deaths were significantly higher among persons living in rural areas than among those living in micropolitan or metropolitan areas. Among seven states in the highest quartile for all three measures, Arkansas, Kentucky, Mississippi, and West Virginia were also in the upper quartile (≥18%) for rural residents. Overcoming barriers to prevention, early diagnosis, treatment, and management of COPD with primary care provider education, Internet access, physical activity and self-management programs, and improved access to pulmonary rehabilitation and oxygen therapy are needed to improve quality of life and reduce COPD mortality.

Multilevel model to estimate county-level untreated dental caries among US children aged 6-9years using the National Health and Nutrition Examination Survey.

Because conducting population-based oral health screening is resource intensive, oral health data at small-area levels (e.g., county-level) are not commonly available. We applied the multilevel logistic regression and poststratification method to estimate county-level prevalence of untreated dental caries among children aged 6-9years in the United States using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2010 linked with various area-level data at census tract, county and state levels. We validated model-based national estimates against direct estimates from NHANES. We also compared model-based estimates with direct estimates from select State Oral Health Surveys (SOHS) at state and county levels. The model with individual-level covariates only and the model with individual-, census tract- and county-level covariates explained 7.2% and 96.3% respectively of overall county-level variation in untreated caries. Model-based county-level prevalence estimates ranged from 4.9% to 65.2% with median of 22.1%. The model-based national estimate (19.9%) matched the NHANES direct estimate (19.8%). We found significantly positive correlations between model-based estimates for 8-year-olds and direct estimates from the third-grade State Oral Health Surveys (SOHS) at state level for 34 states (Pearson coefficient: 0.54, P=0.001) and SOHS estimates at county level for 53 New York counties (Pearson coefficient: 0.38, P=0.006). This methodology could be a useful tool to characterize county-level disparities in untreated dental caries among children aged 6-9years and complement oral health surveillance to inform public health programs especially when local-level data are not available although the lack of external validation due to data unavailability should be acknowledged.

Quantifying spatial accessibility in public health practice and research: an application to on-premise alcohol outlets, United States, 2013.

OBJECTIVE: To assess spatial accessibility measures to on-premise alcohol outlets at census block, census tract, county, and state levels for the United States. METHODS: Using network analysis in a geographic information system, we computed distance-based measures (Euclidean distance, driving distance, and driving time) to on-premise alcohol outlets for the entire U.S. at the census block level. We then calculated spatial access-based measures, specifically a population-weighted spatial accessibility index and population-weighted distances (Euclidean distance, driving distance, and driving time) to alcohol outlets at the census tract, county, and state levels. A multilevel model-based sensitivity analysis was conducted to evaluate the associations between different on-premise alcohol outlet accessibility measures and excessive drinking outcomes. RESULTS: The national average population-weighted driving time to the nearest 7 on-premise alcohol outlets was 5.89 min, and the average population-weighted driving distance was 2.63 miles. At the state level, population-weighted driving times ranged from 1.67 min (DC) to 15.29 min (Arizona). Population-weighted driving distances ranged from 0.67 miles (DC) to 7.91 miles (Arkansas). At the county level, population-weighted driving times and distances exhibited significant geographic variations, and averages for both measures increased by the degree of county rurality. The population-weighted spatial accessibility indexes were highly correlated to respective population-weighted distance measures. Sensitivity analysis demonstrated that population weighted accessibility measures were more sensitive to excessive drinking outcomes than were population weighted distance measures. CONCLUSIONS: These results can be used to assess the relationship between geographic access to on-premise alcohol outlets and health outcomes. This study demonstrates a flexible and robust method that can be applied or modified to quantify spatial accessibility to public resources such as healthy food stores, medical care providers, and parks and greenspaces, as well as, quantify spatial exposure to local adverse environments such as tobacco stores and fast food restaurants.