Objective: Drink-driving represents a critical issue on international organizations’ agendas as one of the key behavioral risk factors in road traffic safety, alongside speed and nonuse of motorcycle helmets, seat belts, and child restraints. Changing road user behaviors regarding these 5 factors is a critical component in reducing road traffic injuries and casualties. The objective of this study is the identification of drivers who are more likely to contribute to crashes in the UK while impaired by alcohol to design targeted drink drive compliance campaigns.
Method: To profile drivers with the factor “impaired by alcohol” assigned in collisions, an extensive data set is used, including all reported injury collisions between 2011 and 2015 in the UK (police records), merged with the Experian Mosaic Database. A multilevel mixed-effects logistic regression is conducted, utilizing the hierarchical nature of the data (drivers within Mosaic types).
Results: Using multilevel mixed-effects logistic regression analysis, the finding is that some driver profiles are more likely to contribute to crashes and are assigned the contributory factor “impaired by alcohol.” Drink-related crashes are more common in some circumstances or for some crash-involved driver groups than others. For instance, alcohol-related crashes are more likely to occur on single carriageways and among males and 25- to 35-year-olds. Drink-drive-related crashes are found to be strongly associated with dark lighting conditions and, more specifically, with late night hours (the interval between 3:00 a.m. and 4:00 a.m. accounts for a third of the drink-drive-related collisions). Using the Experian Mosaic Database which divides the UK population into 66 types based on demographic, lifestyle, and behavior characteristics, the finding is that, among crash-involved drivers, some Mosaic types are significantly more likely (e.g., pocket pensions, dependent greys, streetwise singles) and others are significantly less likely (e.g., crowded kaleidoscope, cultural comfort, penthouse chic) to contribute to a drink-related crash.
Conclusions: The outcome is a more nuanced understanding of drivers contributing to drink-related crashes in the UK. The study concludes by discussing the implications for governments and other interested bodies for better targeting and delivery of public education campaigns and interventions. 相似文献
Conservation and development practitioners increasingly promote community forestry as a way to conserve ecosystem services, consolidate resource rights, and reduce poverty. However, outcomes of community forestry have been mixed; many initiatives failed to achieve intended objectives. There is a rich literature on institutional arrangements of community forestry, but there has been little effort to examine the role of socioeconomic, market, and biophysical factors in shaping both land‐cover change dynamics and individual and collective livelihood outcomes. We systematically reviewed the peer‐reviewed literature on community forestry to examine and quantify existing knowledge gaps in the community‐forestry literature relative to these factors. In examining 697 cases of community forest management (CFM), extracted from 267 peer‐reviewed publications, we found 3 key trends that limit understanding of community forestry. First, we found substantial data gaps linking population dynamics, market forces, and biophysical characteristics to both environmental and livelihood outcomes. Second, most studies focused on environmental outcomes, and the majority of studies that assessed socioeconomic outcomes relied on qualitative data, making comparisons across cases difficult. Finally, there was a heavy bias toward studies on South Asian forests, indicating that the literature on community forestry may not be representative of decentralization policies and CFM globally. 相似文献
土壤酶能反映土壤生物化学过程的强度与方向,深入解析土壤酶活性与环境因子的相关性,有助于探索土壤生态过程,为开展土壤系统的科学调控提供科学依据.以塔里木河上游阿拉尔垦区为研究区,选择新开棉田、10 a棉田、30 a棉田、果园、人工林、天然林、荒草地、盐碱地及沙地等不同土地利用类型为研究对象,运用经典统计学分析绿洲土壤酶活性及环境因子的分异规律,并结合冗余分析技术研究土壤酶活性与环境因子相关关系.经典统计学分析显示,土壤过氧化氢酶、脲酶、转化酶、碱性磷酸酶活性均值分别为4.27 m L·g-1、0.34 mg·g-1、2.08 m L·g-1、0.08 mg·g-1.冗余分析结果表明:全氮、有机质、有效磷、土壤含水量、全盐与土壤酶活性呈极显著相关性(P0.01);土壤容重与土壤酶活性表现为显著相关性;其他环境因子与土壤酶活性的相关性均不显著(P0.05).环境因子与土壤酶活性相关性大小排序为全氮有机质有效磷土壤含水量全盐容重速效钾p H. 相似文献