Miles Of Roadway Research Articles

Exploring the Influence of Drivers’ Visual Surroundings on Speeding Behavior

Despite awareness campaigns and legal consequences, speeding is a significant cause of road accidents and fatalities globally. To combat this issue, understanding the impact of a driver's visual surroundings is crucial in designing roadways that discourage speeding. This study investigates the influence of visual surroundings on drivers in 15 US cities using 3,407,253 driver view images from Lytx, covering 4,264 miles of roadways. By segmenting and analyzing these images along with vehicle-related variables, the study examines factors affecting speeding behavior. After filtering the images, to ensure an accurate representation of the driver’s view, 1,340,035 driver view images were used for analysis. Statistical models, including hurdle beta and bivariate probit models with random driver effects as well as Machine Learning’s eXtreme Gradient Boosting (XGBoost), were employed to estimate speeding behavior. The results indicate that factors within the driver's visual environment, weather conditions, and driver heterogeneity significantly impact speeding. Speeding behavior also varies across geographic locations, even within the same city, suggesting a connection between local context and speeding. The study highlights the importance of the driver's environment, showing that more open spaces encourage speeding, while areas with trees and buildings are associated with reduced speeding. Notably, this research differs from previous studies by utilizing real-time data from dash cameras, providing a dynamic and accurate representation of the driver's visual surroundings. This approach enhances the reliability of the findings and empowers transportation engineers and planners to make informed decisions when designing roadways and implementing interventions to address effectively excessive speeding. In addition to examining speeding behavior, the study also analyzes time-headway, a key factor affecting safety and risky driver behavior, to explore its relationship with speeding. The findings offer valuable insights into the factors influencing speeding and the driver's visual environment. These insights can inform efforts to create environments that discourage speeding (and close car following) and ultimately reduce severe accidents caused by excessive speed (and tailgating).

Comparison of corridor-level fatal and injury crash models with site-level models for network screening purposes on Florida urban and suburban divided arterials

Objective: Develop corridor-level network screening models to identify high-risk corridors where safety improvements could be implemented to reduce fatal and injury (FI) crashes. Methods: A novel corridor definition focused on context classification and lane count was developed and applied to urban and suburban four-lane divided arterial roadways in Florida. Negative binomial regression models were developed for multi- and single-vehicle crashes using 80% of the corridors (training set). Crash frequency predictions were obtained from the developed corridor models and similar site-level models from the Highway Safety Manual (HSM) models for the remaining 20% of the corridors (testing set). Results from all models were adjusted using the empirical Bayes (EB) method. Results: A total of 130 corridors were identified across seven counties. These corridors contained approximately 349 km (217 miles) of roadway and experienced 11,437 multi-vehicle and 746 single-vehicle crashes that resulted in fatalities or injuries from 2017 to 2021. After applying the HSM site-level models and the developed corridor-level models to the testing set (both with and without EB adjustments), the corridor-level models with EB adjustments were the most accurate for corridor crash prediction. Applying the corridor-level models with EB adjustments to the testing set gave a predicted value of 386.44 crashes/year, which was the closest to the observed crash frequency of 383.20 crashes/year. From the corridor-level models, a 3.48-km (2.16-mile) high-risk corridor in Miami-Dade County was identified and analyzed site-by-site using the HSM methodology to identify specific sites within the corridor where safety improvements could provide the most FI crash reductions. Conclusions: The corridor-level models were more accurate and statistically reliable than similar HSM models while being less data intensive. They also only required corridor-level data rather than data for each intersection and segment. By using readily available data, the methods in this paper can be easily replicated by agencies to develop their own network screening corridor-level models and expedite the identification of corridors in need of safety improvements to reduce FI crashes. Existing site-level network screening methods can be used to supplement the developed corridor-level methodology by identifying high-risk sites within identified high-risk corridors.

Analysis of Connected Vehicle Data to Quantify National Mobility Impacts of Winter Storms for Decision Makers and Media Reports

Traditional techniques of monitoring roadway mobility during winter weather have relied on embedded road sensors, roadside cameras, radio reports from public safety staff, or public incident reports. However, widely available connected vehicle (CV) data provides government agencies and media with a unique opportunity to monitor the mobility impact of inclement weather events in near real-time. This study presents such a use case that analyzed over 500 billion CV records characterizing the spatial and temporal impact of a winter storm that moved across the country from 21 to 26 December 2022. The analysis covered 97,000 directional miles of interstate roadway and processed over 503 billion CV records. At the storm’s peak on 22 December at 5:26 PM Eastern Time, nearly 4800 directional miles of interstate roadway were operating under 45 mph, a widely accepted indicator of degraded interstate conditions. The study presents a methodological approach to systematically assess the mobility impact of this winter event on interstate roadways at a national and regional level. The paper then looks at a case study on Interstate 70, a 4350 directional mile route passing through ten states. Statewide comparison showed Ohio was most impacted, with 9% of mile-hours operating below 45 mph on 23 December. High-Resolution Rapid Refresh weather data provided by the National Oceanic and Atmospheric Administration was integrated into the analysis to provide a visualization of the storm’s temporal path and severity. We believe the proposed metrics and visualizations are effective tools for communicating the severity and geographic impact of extreme weather events to broad non-technical audiences.

Exploring Crowdsourced Hard—Acceleration and Braking Event Data for Evaluating Safety Performance of Low-Volume Rural Highways in Iowa

There are over four million miles of two-lane roadways across the United States, of which a substantial portion is low-volume roads (LVR). Traditionally, most traffic safety efforts and countermeasures focus on high-volume high-crash urban locations. This is because LVRs cover an extensive area, and the rarity of crashes makes it challenging to use crash data to monitor the safety performance of LVRs regularly. In addition, obtaining up-to-date roadway information, such as pavement or shoulder conditions of an extensive LVR network, can be exceptionally difficult. In recent times, crowdsourced hard-acceleration and braking event data have become commercially available, which can provide precise geolocation information and can be readily acquired from different vendors. The present paper examines the potential use of this data to identify opportunities to monitor the safety of LVRs. This research examined approximately 12 million hard-acceleration and hard-braking events over a 3-months period and 26,743 crashes, including 9373 fatal injuries over the past 5-year period. The study found a moderate correlation between hard acceleration/hard-braking events with historical crash events. This study conducted a hot spot analysis using hard-acceleration/hard-braking and crash datasets. Hotspot analysis detected spatial clusters of high-risk crash locations and detected 848 common high-risk sites. Finally, this paper proposes a combined ranking scheme that simultaneously considers historical crash events and hard-acceleration/hard-braking events. The research concludes by suggesting that agencies can potentially use the hard-acceleration and hard-braking event dataset along with the historical crash dataset to effectively supervise the safety performance of the vast network of LVRs more frequently.

Measuring Roadway Lane Widths Using Connected Vehicle Sensor Data.

The United States has over three trillion vehicle miles of travel annually on over four million miles of public roadways, which require regular maintenance. To maintain and improve these facilities, agencies often temporarily close lanes, reconfigure lane geometry, or completely close the road depending on the scope of the construction project. Lane widths of less than 11 feet in construction zones can impact highway capacity and crash rates. Crash data can be used to identify locations where the road geometry could be improved. However, this is a manual process that does not scale well. This paper describes findings for using data from onboard sensors in production vehicles for measuring lane widths. Over 200 miles of roadway on US-52, US-41, and I-65 in Indiana were measured using vehicle sensor data and compared with mobile LiDAR point clouds as ground truth and had a root mean square error of approximately 0.24 feet. The novelty of these results is that vehicle sensors can identify when work zones use lane widths substantially narrower than the 11 foot standard at a network level and can be used to aid in the inspection and verification of construction specification conformity. This information would contribute to the construction inspection performed by agencies in a safer, more efficient way.

Methodology to Quantify Statewide Evacuations

Mass evacuations, particularly those at a statewide level, are among the largest single-event highway traffic events. They can last several days, cover thousands of miles of roadway, and include hundreds of thousands of people and vehicles. Often, evacuations are criticized for their inefficiency and poor management. Despite the critical importance and the potential impact on lives and safety, there are no recognized methods systematically to quantify traffic characteristics at statewide scales. This paper documents the development and application of an analytical method to measure statewide mass evacuations. The proposed approach sought to be both practical and cost-effective. The research methods are based on simple, yet widely available, and easily understood traffic count datasets that support both qualitative and quantitative analyses. By spatially and temporally arranging sensor-based statewide traffic volume data from the hurricane Irma (2017) and Michael (2018) evacuations, these methods are applied to describe and answer several key questions about statewide mass evacuations. The methods developed in this research are able to estimate the start and end of the auto-based evacuation, the loading and peaking characteristics of traffic, the total number of vehicles involved in the evacuation, and the effective start and end time of the auto-based reentry. Among the key findings of this work were that the hurricane Irma and Michael evacuations began several days before landfall, peaking two to three days before the storm. It is expected that state departments of transportation and emergency management officials can apply similar methods to assess and better plan future evacuations.

Performance of Hot and Cold Recycled Mixtures with High Reclaimed Asphalt Pavement Content

Florida Department of Transportation yearly maintenance and rehabilitation activities include milling and resurfacing of approximately 2,000 lane miles of roadway, with an average resurfacing depth of about 2.1 in. (55 mm). These activities result in the generation and accumulation of roughly 1.8 million tons of reclaimed asphalt pavement (RAP) each year. The use of elevated quantities of RAP in asphalt pavement provides an environmentally responsible solution to the accumulated RAP surplus in some urban areas, while at the same time offering an economical pavement maintenance and rehabilitation option to local agencies facing budget constraints. The objective of this project was to compare the performance of mixtures with 60% RAP content to be used primarily on low volume roads (average daily traffic <750 vehicles) and suggest adequate test methods within the context of a balanced mix design approach. To accomplish this objective, three types of mixtures were considered: hot, cold with emulsion, and cold with foamed binder. Performance testing included intermediate temperature cracking, rutting, moisture susceptibility, and durability. The hot recycled mixtures showed good moisture susceptibility and cracking resistance, especially when rejuvenators were incorporated. The cold recycled mixtures showed poor moisture susceptibility and durability characteristics, which were alleviated when hydrated lime or Portland cement was incorporated in the emulsified and foamed mixtures, respectively. Most hot recycled mixtures, and all the cold recycled mixtures, exhibited poor rutting behavior, likely because of the harsh conditions of the test. A life-cycle cost analysis demonstrated more favorable savings when cold recycled mixtures were used.

Potential Use of NASA’s Soil Moisture Active Passive Freeze–Thaw Tool to Assist in Minnesota Seasonal Load Restriction Timing

The U.S. encompasses over 4 million roadway miles, with about half of them located in seasonal frost areas. Roads are especially susceptible to damage when the subsurface is saturated with water (i.e., spring thaw). Spring load restrictions (SLR) are important for maintaining the integrity of roads. Routine determinations of road freeze–thaw (FT) state are limited to vertically embedded temperature data probes (TDP). Although TDPs are valuable to departments of transportation for determining SLRs, TDPs only represent individual points within the road network and are costly to install and maintain. Recent updates to spaceborne technology and algorithms made physically based retrievals of FT conditions possible at improved accuracy and temporal resolution (every 3 days) and have potential use for assisting with SLRs. Although instruments such as NASA’s Soil Moisture Active Passive (SMAP) platform cannot resolve individual roads, past comparisons have shown good correspondence with TDPs. The main objective of this study is to provide information on the potential value of NASA’s SMAP FT tool to supplement other methods for making seasonal load restriction decisions. Results are compared against data and protocols by the Minnesota Department of Transportation (MnDOT) at 10 sites in Minnesota, over four winter seasons (2016–2019). Results show that even when a simple criterion is used—the date of the third consecutive thaw from the SMAP afternoon retrieval—those dates typically fell within a week of MnDOT road postings (61% of the time). In addition, SMAP FT typically matches TDP FT states throughout the year (79% of the time).

Development of a QC/QA Process for Caltrans Automated Pavement Condition Survey Data

The California Department of Transportation (Caltrans) awarded a contractor a three-year contract to collect, analyze, and report pavement condition of the state highway system for 2018 and 2019 using automated pavement condition survey (APCS). The contract covers 12 Caltrans districts with roughly 52,000 lane miles of on-system roadways and 6,000 lane miles of off-system roadways. Before investing significant resources on statewide APCS data collection, Caltrans and the contractor initiated a pilot study. The purpose is to establish a workable process for data quality control (QC) and quality assurance (QA), making sure the data collected closely reflect the field condition. The pilot study was conducted on selected routes in Caltrans District 12. The study included a total of 113 lane miles of roadway, representing roughly 5% of the total lane miles in the district. Of these lane miles, 69 lane miles are asphalt pavements and 44 lane miles are jointed plain concrete pavements. The developed data QC/QA process functioned very well. With this process, the contractor was responsible for performing the QC of the APCS data before submitting to Caltrans. Caltrans performed data QA, which included data completeness check; image review; field review and office verification; data upload into Caltrans pavement management system, and year-by-year data consistency check. The joint effort has resolved many data inconsistency issues caused either by interpretation or software issues. The data quality was thus well improved. It is recommended that this QC/QA process be implemented for all APCS data collections in California.

Role of Route Optimization in Benefiting Winter Maintenance Operations

For winter maintenance purposes, the Ohio Department of Transportation (ODOT) deploys a fleet of approximately 1,600 snowplow trucks that maintain 43,000 lane miles of roadway. These trucks are based out of 200 garages, yards, and outposts that also house a combined total of 650,000 tons of salt. The deployment of such a large number of trucks over a vast maintenance area creates an operational problem in determining the optimal maintenance routes and fleet size. Traditionally, ODOT has used county borders as maintenance boundaries for ODOT garages. However, by removing these borders and optimizing the snowplow routes, ODOT may benefit from significant time and cost savings. The results of this project provide ODOT a tool to determine the minimum number of trucks needed to maintain the necessary roadways within Districts 1, 2, and 10. In addition, the project recommends to ODOT a tool to assign assets to specific facilities and the most optimal routes for each truck in a district. This research indicates the possibility of reducing the fleet size within Districts 1, 2, and 10 by a total of 29 trucks while maintaining the same level of service. Apart from fleet size reduction, the route optimization can decrease the amount of time in which to treat each road in the three districts by 17 hours for one iteration.

Recent and Future Outlooks for Nuisance Flooding Impacts on Roadways on the U.S. East Coast

Tidal floods (i.e., “nuisance” flooding) are occurring more often during seasonal high tides or minor wind events, and the frequency is expected to increase dramatically in the coming decades. During these flood events, coastal communities’ roads are often impassable or difficult to pass, thus impacting routine transport needs. This study identifies vulnerable roads and quantifies the risk from nuisance flooding in the Eastern United States by combining public road information from the Federal Highway Administration’s Highway Performance Monitoring System with flood frequency maps, tidal gauge historic observations, and future projections of annual minor tidal flood frequencies and durations. The results indicate that tidal nuisance flooding across the East Coast threatens 7508 miles (12,083 km) of roadways including over 400 miles (644 km) of interstate roadways. From 1996–2005 to 2006–2015, there was a 90% average increase in nuisance floods. With sea level rise, nuisance-flood frequency is projected to grow at all locations assessed. The total induced vehicle-hours of delay due to nuisance flooding currently exceed 100 million hours annually. Nearly 160 million vehicle-hours of delay across the East Coast by 2020 (85% increase from 2010); 1.2 billion vehicle-hours by 2060 (126% increase from 2010); and 3.4 billion vehicle-hours by 2100 (392% increase from 2010) are projected under an intermediate low sea-level-rise scenario. By 2056–2065, nuisance flooding could occur almost daily at sites in Connecticut, New Jersey, Maryland, the District of Columbia, North Carolina, and Florida under an intermediate sea-level-rise scenario.

Cost-Effective Performance Management for Washington State Pavement Assets

The Washington State Department of Transportation (DOT) manages 18,230 lane miles (29,332 lane kilometers) of main-line roadway. In the past several years, the Washington State DOT has gone through an evaluation and modification of its pavement management practices. This paper presents the historical perspective on past Washington State DOT pavement practices and several strategies that were developed to improve the management of pavement assets. The Washington State DOT has been successfully preserving the long life of flexible pavements by applying thin hot-mix asphalt (HMA) mill and inlays on the basis of the concept that cracking in thicker HMA sections will primarily be top-down. Furthermore, using the framework developed by the evaluation of cost-effectiveness, several strategies have been implemented to improve the management of Washington State DOT pavement assets. These strategies are ( a) converting 3,000 lane miles (4,827 km) from asphalt to chip seal resurfacing before the year 2025, ( b) planning $850 million to $1.0 billion for rehabilitation and reconstruction for the aging concrete pavement network for the next 10 years with 50% of the concrete slated for reconstruction to be converted to flexible pavement using a crack and seat plus asphalt overlay process, and ( c) applying strategic maintenance to reduce the annual cost by extending the service life of flexible pavements. These cost-effective strategies are expected to generate an overall annual cost savings of $80 million per year by 2025.

Energy harvesting from pavement via polyvinylidene fluoride: hybrid piezo-pyroelectric effects

In the USA, there are over 4 million miles (6 million km) of roadways and more than 250 million registered vehicles. Energy lost in the pavement system due to traffic-induced vibration and deformation is enormous. If effectively harvested, such energy can serve as an alternative sustainable energy source that can be easily integrated into the transportation system. It is well known that most piezoelectric materials are also pyroelectric materials, which convert temperature change into electricity. However, the potential of polyvinylidene fluoride (PVDF) as a hybrid piezo-pyroelectric energy harvester has been seldom studied. The uniqueness of this study lies in that the electrical responses of PVDF under coupled mechanical and thermal stimulations are investigated. Through a series of well controlled experiments, it is found that there exists an interesting coupling phenomenon between piezoelectric and pyroelectric effects of PVDF: the voltage generated by simultaneous mechanical and thermal stimulations is the algebraic sum of voltages generated by separate stimulations. This means that there is neither strengthening nor weakening coupling effect when the piezoelectric and pyroelectric phenomena are coupled. This also makes the modeling process of the hybrid piezoelectric and pyroelectric effect straightforward. An estimation of power generation through piezoelectric and pyroelectric effect is conducted, and the overall effects of temperature on hybrid piezo-pyroelectric energy harvesting are discussed.

Use of Connected Vehicles to Characterize Ride Quality

The United States relies on the performance of more than 4 million miles of roadways to sustain its economic growth and to support the dynamic mobility needs of its growing population. The funding gap to build and maintain roadways is ever widening. Hence the continuous deterioration of roads from weathering and usage poses significant challenges. Transportation agencies measure ride quality as the primary indicator of roadway performance. The international roughness index is the prevalent measure of ride quality that agencies use to assess and forecast maintenance needs. Most jurisdictions use a laser-based inertial profiler to produce the index. However, technical, practical, and budget constraints preclude that use for some facility types, particularly local and unpaved roads that make up more than 90% of the road network in the United States. This study expands on previous work that developed a method to transform sensor data from many connected vehicles to characterize ride quality continuously, for all facility types and at any speed. The case studies used a certified and calibrated inertial profiler to produce the international roughness index. A smartphone aboard the inertial profiler produced simultaneously the roughness index of the connected vehicle method. The results validate the direct proportionality relationship between the inertial profiler and connected vehicle methods within a margin of error that diminished below 5% and 2% after 30 and 80 traversal samples, respectively.

Examining the relationship between the physical availability of medical marijuana and marijuana use across fifty California cities

BackgroundThe purpose of the current study is to assess statistical associations between individual demographic and personality characteristics, the city-level physical availability of medical marijuana (as measured through densities per roadway mile of storefront dispensaries and delivery services), and the incidence and prevalence of marijuana use. MethodIndividual level data on marijuana use were collected during a telephone survey of 8853 respondents living in 50 mid-size cities in California. Data on medical marijuana dispensaries and delivery services were obtained via six different websites and official city lists. Three outcome variables pertaining to lifetime, past year use, and frequency of past year use were analyzed using random effects logistic models (for lifetime and past year use) and random effects tobit models (for frequency of past 365-day use). ResultsThe current study finds that the total physical availability of medical marijuana through dispensaries and delivery services per roadway mile at the city-level is positively related to current marijuana use and greater frequency of use, controlling for a variety of demographic and personality characteristics. As expected, current physical availability of medical marijuana was unrelated to lifetime use. ConclusionsRegulations on the number and densities of marijuana outlets may be a sufficient means to restrain overall levels of marijuana use within cities. However, alternative use of delivery services may also provide easy access to marijuana and mitigate these effects.

Development prediction of logistics industry in Henan province and its dynamic analysis

Purpose – The purpose of this paper is to establish a group of grey prediction models and relative degree model to study the characteristics and trend of the logistics industry development in Henan province scientifically. The study results can provide references for the development policy of the logistics industry in Henan province. Design/methodology/approach – The paper constructs grey prediction models and grey buffer operator models which are related to the distribution of logistics industry in Henan province, and selects prediction models by comparing model accuracy, and use them to forecast the development trend of logistics industry in future ten years of Henan province. Using the grey relative models, the paper analyses development dynamic and prospect which support the development of logistics industry, and provide some references for transferring the pattern of economic growth of Henan province, forming new economic growth point and formulating relevant policies. High prediction accuracy models are selected to forecast the future development trend of logistics industry in the next ten years. Findings – Results show that the modern logistics industry in Henan province has been a steady growth in overall, the main growth points of the logistics industry development in Henan province are roadway miles (km), roadway (100 million tonnes/km), freight turnover (100 million tonnes/km) and waterway (100 million tonnes), the growth points for the future development of logistics industry in Henan province are the roadway freight volume, roadway passenger volume and waterway freight volume. Practical implications – Regional economic competition has become an important index for measuring a country's economic development level. Logistics industry plays an important role in the regional economic development, such as promoting coordinated development of regional economy and upgrading industrial optimization, and playing a major role in industrial transfer. Hence, logistics industry, which is urgently needed to solve by the government, has become important forces for promoting the growth of economy and a basic pillar industries of regional economy. Originality/value – The paper presents the systematic results of development prediction of modern logistics industry in Henan province and its dynamic analysis by using grey systems theory, not only to predict the trend of the development of the logistics industry, also to analyse the future development of logistics industry in the leading power factors.

Developing a Five-year Maintenance and Rehabilitation (M&R) Plan for HMA and Concrete Pavement Networks

In the face of increased demand and exposure to environmental effects, the condition of road pavements continues to decline while resources for their preservation remain limited. Thus, the task of managing pavements has to be done systematically and objectively. This paper outlines the steps involved in developing a multi-year pavement Maintenance and Rehabilitation (M&R) plan. These include: (1) condition assessment; (2) network inventory and database development; (3) identification of pavement sections requiring M&R; (3) needs analysis; and (4) impact analysis. As a case study, the project was performed on the road network inside the Texas A&M University campus that consists of 13.95 miles of roadway, 80% and 20% of which are concrete and HMA pavements respectively. Condition assessment was done according to ASTM D 6433-07 and using the Pavement Condition Index (PCI) as indicator of pavement performance. Data collected were then entered into a database which also contains information on traffic and roadway characteristics. PCI threshold values were established to identify sections that are in need of M&R and the most cost- effective treatment based on long-term performance benefit and life-cycle cost was proposed for each project. Candidate projects were then prioritized by ranking based on benefit-cost analysis. The needs estimate provides meaningful information on the total amount of budget required to correct all deficiencies in the network. Finally, the impact analysis is used to determine the impact of a reduced budget on network condition as well as the amount of backlog that needs to be addressed.

Do Neighborhood Attributes Moderate the Relationship between Alcohol Establishment Density and Crime?

Although numerous studies have found a positive association between the density of alcohol establishments and various types of crime, few have examined how neighborhood attributes (e.g., schools, parks) could moderate this association. We used data from Minneapolis, MN with neighborhood as the unit of analysis (n = 83). We examined eight types of crime (assault, rape, robbery, vandalism, nuisance crime, public alcohol consumption, driving while intoxicated, underage alcohol possession/consumption) and measured density as the total number of establishments per roadway mile. Neighborhood attributes assessed as potential moderators included non-alcohol businesses, schools, parks, religious institutions, neighborhood activism, neighborhood quality, and number of condemned houses. Using Bayesian techniques, we created a model for each crime outcome (accounting for spatial auto-correlation and controlling for relevant demographics) with an interaction term (moderator × density) to test each potential moderating effect. Few interaction terms were statistically significant. The presence of at least one college was the only neighborhood attribute that consistently moderated the density-crime association, with the presence of a college attenuating the association between the density and three types of crime (assaults, nuisance crime, and public consumption). However, caution should be used when interpreting the moderating effect of college presence because of the small number of colleges in our sample. The lack of moderating effects of neighborhood attributes, except for presence of a college, suggests that the addition of alcohol establishments to any neighborhood, regardless of its other attributes, could result in an increase in a wide range of crime.

Neighborhood socioeconomic characteristics, the retail environment, and alcohol consumption: A multilevel analysis

BackgroundThe neighborhoods where people live can influence their drinking behavior. We hypothesized that living in a neighborhood with lower median income, higher alcohol outlet density, and only liquor stores and no grocery stores would be associated with higher alcohol consumption after adjusting for individual demographic and lifestyle factors. MethodsWe used two self-report measures to assess alcohol consumption in a sample of 9959 adults living in a large Midwestern county: volume of alcohol consumed (count) and binge drinking (5 or more drinks vs.<5 drinks). We measured census tract median annual household income based on U.S. Census data. Alcohol outlet density was measured using the number of liquor stores divided by the census tract roadway miles. The mix of liquor and food stores in census tracts was assessed using a categorical variable based on the number of liquor and number of food stores using data from InfoUSA. Weighted hierarchical linear and Poisson regression were used to test our study hypothesis. ResultsRetail mix was associated with binge drinking. Individuals living in census tracts with only liquor stores had a 46% higher risk of binge drinking than individuals living in census tracts with food stores only after controlling for demographic and lifestyle factors. ConclusionCensus tract characteristics such as retail mix may partly explain variability in drinking behavior. Future research should explore the mix of stores, not just the over-concentration of liquor stores in census tracts.

Relationships between local enforcement, alcohol availability, drinking norms, and adolescent alcohol use in 50 California cities.

This study investigated relationships between local alcohol policies, enforcement, alcohol outlet density, adult alcohol use, and underage drinking in 50 California cities. Eight local alcohol policies (e.g., conditional use permit, social host ordinance, window/billboard advertising) were rated for each city based on their comprehensiveness. Local alcohol enforcement was based on grants received from the California Alcoholic Beverage Control agency for enforcement of underage drinking laws. Outlet density was based on the number of on- and off-premise outlets per roadway mile. Level of adult alcohol use was ascertained from a survey of 8,553 adults and underage drinking (frequency of past-year alcohol use and heavy drinking) from surveys of 1,312 adolescents in 2009 and 2010. Multilevel regression analyses were conducted to examine the effects of policies, enforcement, and other community-level variables on adolescent drinking, controlling for youth demographic characteristics. Mediating effects of adolescents' perceived ease of obtaining alcohol, perceived enforcement, and perceived acceptability of alcohol use also were examined. None of the eight local alcohol-policy ratings were associated with adolescent drinking. Funding for underage drinking enforcement activities was inversely related to frequency of past-year alcohol use, whereas outlet density and adult drinking were positively related to both past-year alcohol use and heavy drinking. These relationships were attenuated when controlling for perceived ease of obtaining alcohol, enforcement, and acceptability of alcohol use, providing evidence formediation. Adolescent alcohol use and heavy drinking appear to be influenced by enforcement of underage drinking laws, alcohol outlet density, and adult alcohol use. These community-level influences may be at least partially mediated through adolescents' perceptions of alcohol availability, acceptability of alcohol use, and perceived likelihood of getting in trouble with local police.