Objective:To review structural interventions in public health, identify distinct approaches to structural interventions, and assess their implications for HIV-prevention interventions.Method:The MEDLINE, HealthStar, PsychInfo and Sociofile databases were searched on specific health issues, types of

Structural interventions in public health.

Road traffic crashes (RTCs) are responsible for a substantial fraction of morbidity and mortality and are responsible for more years of life lost than most of human diseases. In this review, we have tried to delineate behavioral factors that collectively represent the principal cause of three out of five RTCs and contribute to the causation of most of the remaining. Although sharp distinctions are not always possible, a classification of behavioral factors is both necessary and feasible. Thus, behavioral factors can be distinguished as (i) those that reduce capability on a long-term basis (inexperience, aging, disease and disability, alcoholism, drug abuse), (ii) those that reduce capability on a short-term basis (drowsiness, fatigue, acute alcohol intoxication, short term drug effects, binge eating, acute psychological stress, temporary distraction), (iii) those that promote risk taking behavior with long-term impact (overestimation of capabilities, macho attitude, habitual speeding, habitual disregard of traffic regulations, indecent driving behavior, non-use of seat belt or helmet, inappropriate sitting while driving, accident proneness) and (iv) those that promote risk taking behavior with short-term impact (moderate ethanol intake, psychotropic drugs, motor vehicle crime, suicidal behavior, compulsive acts). The classification aims to assist in the conceptualization of the problem that may also contribute to behavior modification-based efforts.

Human factors in the causation of road traffic crashes

Background: Oral fluid (OF) is an exciting alternative matrix for monitoring drugs of abuse in workplace, clinical toxicology, criminal justice, and driving under the influence of drugs (DUID) programs. During the last 5 years, scientific and technological advances in OF collection, point-of-collection testing devices, and screening and confirmation methods were achieved. Guidelines were proposed for workplace OF testing by the Substance Abuse and Mental Health Services Administration, DUID testing by the European Union’s Driving under the Influence of Drugs, Alcohol and Medicines (DRUID) program, and standardization of DUID research. Although OF testing is now commonplace in many monitoring programs, the greatest current limitation is the scarcity of controlled drug administration studies available to guide interpretation.

Content: This review outlines OF testing advantages and limitations, and the progress in OF that has occurred during the last 5 years in collection, screening, confirmation, and interpretation of cannabinoids, opioids, amphetamines, cocaine, and benzodiazepines. We examine controlled drug administration studies, immunoassay and chromatographic methods, collection devices, point-of-collection testing device performance, and recent applications of OF testing.

Summary: Substance Abuse and Mental Health Services Administration approval of OF testing was delayed because questions about drug OF disposition were not yet resolved, and collection device performance and testing assays required improvement. Here, we document the many advances achieved in the use of OF. Additional research is needed to identify new biomarkers, determine drug detection windows, characterize OF adulteration techniques, and evaluate analyte stability. Nevertheless, there is no doubt that OF offers multiple advantages as an alternative matrix for drug monitoring and has an important role in DUID, treatment, workplace, and criminal justice programs.

Oral Fluid Testing for Drugs of Abuse

There is an ongoing debate among transport planners and safety policy makers as to whether there is any association between the level of traffic congestion and road safety. One can expect that the increased level of traffic congestion aids road safety and this is because average traffic speed is relatively low in a congested condition relative to an uncongested condition, which may result in less severe crashes. The relationship between congestion and safety may not be so straightforward, however, as there are a number of other factors such as traffic flow, driver characteristics, road geometry, and vehicle design affecting crash severity. Previous studies have employed count data models (either Poisson or negative binomials and their extensions) while developing a relationship between the frequency of traffic crashes and traffic flow or density (as a proxy for traffic congestion). The use of aggregated crash counts at a road segment level or at an area level with the proxy for congestion may obscure the actual relationship. The objective of this study is to explore the relationship between the severity of road crashes and the level of traffic congestion using disaggregated crash records and a measure of traffic congestion while controlling for other contributory factors. Ordered response models such as ordered logit models, heterogeneous choice models, and generalized ordered logit (partially constrained) models suitable for both ordinal dependent variables and disaggregate crash data are used. Data on crashes, traffic characteristics (e.g., congestion, flow, and speed), and road geometry (e.g., curvature and gradient) were collected from the M25 London orbital motorway between 2003 and 2006. Our results suggest that the level of traffic congestion does not affect the severity of road crashes on the M25 motorway. The impact of traffic flow on the severity of crashes, however, shows an interesting result. All other factors included in the models also provide results consistent with existing studies.

/pdf/road-traffic-congestion-and-crash-severity-econometric-2rrbyxf6f0.pdf

Road Traffic Congestion and Crash Severity: Econometric Analysis Using Ordered Response Models

A study of factors affecting highway accident rates using the random-parameters tobit model.

https://www.nr.no/~aldrin/artikler/AlcoholAndDrugs.AccAnPrev.2008.pdf

Terje Assum

Papers

Prevalence of alcohol and drugs among Norwegian motor vehicle drivers: A roadside survey

Risk compensation--the case of road lighting

Attitudes and road accident risk

Reduction of the blood alcohol concentration limit in Norway-Effects on knowledge, behavior and accidents

Norwegian Roadside Survey of Alcohol and Drug Use by Drivers (2008–2009)