BackgroundMany local authorities in England and Wales have reduced street lighting at night to save money and reduce carbon emissions. There is no evidence to date on whether these reductions impact on public health. We quantified the effect of 4 street lighting adaptation strategies (switch off, part-night lighting, dimming and white light) on casualties and crime in England and Wales.MethodsObservational study based on analysis of geographically coded police data on road traffic collisions and crime in 62 local authorities. Conditional Poisson models were used to analyse longitudinal changes in the counts of night-time collisions occurring on affected roads during 2000–2013, and crime within census Middle Super Output Areas during 2010–2013. Effect estimates were adjusted for regional temporal trends in casualties and crime.ResultsThere was no evidence that any street lighting adaptation strategy was associated with a change in collisions at night. There was significant statistical heterogeneity in the effects on crime estimated at police force level. Overall, there was no evidence for an association between the aggregate count of crime and switch off (RR 0.11; 95% CI 0.01 to 2.75) or part-night lighting (RR 0.96; 95% CI 0.86 to 1.06). There was weak evidence for a reduction in the aggregate count of crime and dimming (RR 0.84; 95% CI 0.70 to 1.02) and white light (RR 0.89; 95% CI 0.77 to 1.03).ConclusionsThis study found little evidence of harmful effects of switch off, part-night lighting, dimming, or changes to white light/LEDs on road collisions or crime in England and Wales.

In the United Kingdom, since 2011 data regarding individual police recorded crimes have been made openly available to the public via the police.uk website. To protect the location privacy of victims these data are obfuscated using geomasking techniques to reduce their spatial accuracy. This paper examines the spatial accuracy of the police.uk data to determine at what level(s) of spatial resolution -if any -it is suitable for analysis in the context of theory testing and falsification, evaluation research, or crime analysis. Police.uk data are compared to police recorded data for one large metropolitan Police Force and spatial accuracy is quantified for four different levels of geography across five crime types. Hypotheses regarding systematic errors are tested using appropriate statistical approaches, including methods of maximum likelihood. Finally, a "best-fit" statistical model is presented to explain the error as well as to develop a model that can correct it. The implications of the findings for researchers using the police.uk data for spatial analysis are discussed.

Financial and carbon reduction incentives have prompted many local authorities to reduce street lighting at night. Debate on the public health implications has centred on road accidents, fear of crime and putative health gains from reduced exposure to artificial light. However, little is known about public views of the relationship between reduced street lighting and health. We undertook a rapid appraisal in eight areas of England and Wales using ethnographic data, a household survey and documentary sources. Public concern focused on road safety, fear of crime, mobility and seeing the night sky but, for the majority in areas with interventions, reductions went unnoticed. However, more private concerns tapped into deep-seated anxieties about darkness, modernity ‘going backwards’, and local governance. Pathways linking lighting reductions and health are mediated by place, expectations of how localities should be lit, and trust in local authorities to act in the best interests of local communities.