Erratum to: Estimating urban water demand under conditions of rapid growth: the case of Shanghai

Regional Environmental Change - Many of the world’s major cities are expected to face significant water shortages in coming decades, largely due to increased demand arising from economic and...     

Injuries associated with the use of riding mowers in the United States, 2002-2007

Context: To examine injuries among patients treated in an emergency department (ED) related to the use of a riding lawn mower.Design and Setting: Data were obtained from the National Electronic Injury Surveillance System for the years 2002-2007. National estimates of ED visits for injuries associated with the use of a riding lawn mower were analyzed. Narrative text entries were categorized to provide a detailed record of the circumstances precipitating the injury. Average annual rates were calculated and logistic regression analyses were employed to determine risk estimates for patient disposition and demographic characteristics related to ED visits for injuries associated with riding mowers.Results: From 2002 through 2007, there were an estimated 66,341 ED visits for injuries related to the use of riding lawnmowers in the U.S., with an average annual rate of 6.0 ED visits per 100,000 males, and 1.6 ED visits per 100,000 females. Older adults had higher rates of ED visits for injuries (7.2/100,000) than younger age groups. The most common injuries involved contusions (24%); sprains/strains (22%) and fractures (17%). The majority of patients (90%) were treated and released the same day. Results of logistic regression analyses revealed that older adults were more likely to be hospitalized when compared to younger age groups; and incidents involving rollovers [OR = 5.45 (95% CI = 3.22-9.23)] and being run over [6.01 (95% CI 3.23-11.17)] were more likely to result in hospitalization when compared to all other circumstances of injury.Conclusions: Riding mowers present injury patterns and circumstances that are different than those reported for push mowers. Circumstances related to injuries and age groups affected were varied, making prevention of riding mower injuries challenging. Application/Impact: Findings support the need to increase awareness and/or change the design of riding mowers with respect to risk of rollover injuries.     

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey

Introduction

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey.

Method

Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P < 0.05 with spatial autocorrelation analyses.

Results

Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P < 0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R² values. Geographically weighted regression provided values of 0.89-0.99 adjusted R² for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions.

Impact on industry

Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.     

The relationship between recruitment processes, familiarity, trust, perceived risk and safety

Introduction and Method

Participants′ perceptions of the safety-related aspects of their organization′s recruitment processes were examined, as were their perceptions of safety aspects associated with new recruits.

Results

One hundred and fifty-four professional fire fighters indicated the trust they held in the safety-related aspects of their organizations′ selection and pre-start training. Perceived trust in pre-start training was negatively correlated (r = -.24, p < .01) with the risk associated with new recruits, and positively correlated (r = .50, p < .01) with ratings of trust in recruits to immediately work safely. Furthermore, trust in recruits to immediately work safely was negatively correlated (r = -.21, p < .01) with crews′ safety behavior toward recruits.

Conclusions

These results are interpreted as particularly dangerous for workers, as new recruits lack familiarity with aspects of their new workplace that cannot be addressed by either selection or pre-start training, making them a risk.

Impact on Industry

Organizations should actively identify new recruits, and encourage existing team members not to immediately trust new recruits to work safely.