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Full moon and traffic accident-related emergency ambulance transport: A nationwide case-crossover study
Abstract
Background:
Several studies have examined the association between environmental factors and traffic accidents. However, the role of a full moon in triggering emergency ambulance transport due to road traffic casualties is unclear. Thus, we aimed to examine whether a full moon contributes to the incidence of emergency transport due to road traffic crashes.
Methods:
We acquired nationwide data on daily emergency transport due to road traffic crashes from all 47 prefectures of Japan from 2010 to 2014. We conducted a time-stratified case-crossover study using conditional Poisson regression to examine the relationship between the occurrence of a full moon and emergency transport due to road traffic crashes for each prefecture. Prefecture-level results were combined using a random-effects meta-analysis to evaluate nation-level estimates.
Results:
There were 842,554 cases of emergency transport due to road traffic crashes across 1826 nights (62 full moon nights: n = 29,584; 1764 control nights: n = 812,970). On days with a full moon, the pooled adjusted relative risk (RR) of emergency transport due to traffic accidents was 1.042 (95% confidence interval [CI], 1.021-1.063). Overall, 4.03% (95% CI: 2.06-5.93) of the cases (1192 cases) were attributable to full moon nights. Stratified analyses revealed a significant increase in emergency transport due to traffic accidents on full moon nights for males, people aged ≥40 years, and before midnight.
Conclusions:
Full moon nights are associated with an increase in the incidence of emergency transport due to road traffic crashes. These results indicate that public health strategies should account for full moon nights to decrease emergency transport due to traffic accidents.
... This section highlights clear recommendations for future works. The reviewed studies provided a number of recommendations on areas such as complimentary research work [39,54,67,78,98,114,115,121,185], drivers' behaviour [139], duration [16,62], area [3], time [84,196], and the use of more precise modelling methods [197]. Many researchers pointed research direction towards longitudinal research in the field of motorcyclists' behaviour and safety and whether such behaviour with different motivations negatively affected road safety [10,63,139]. ...
... The first category, sample size based on social science techniques (Figure 9), focuses on using four groups of different sample sizes. The size of the first group isin the tens and ranges between 10 and 99 participants [12,15,25,75,88,94,121,124,176,191,197,204]. The second group is in the hundredsand ranges between 100 and 999 participants [8,10,27,33,[38][39][40]42,53,54,56,58,60,66,100,119,152,153,156,173,184,186,198,207,210,219,236,241]. ...
... Survey, questionnaires or interview [8,10,12,[15][16][17][18]26,27,32,33,[38][39][40]47,49,50,53,56,58,60,64,66,68,75,76,124,152,153,164,176,186,194,210,219,236,241,242] Medical centres [25,89,92,156,159,161,181,184,187,189,197,198,204] Reports [16,96,151,177,179,188,207] Experiment and observation [3,14,42,51,54,78,84,90,91,95,98,100,[114][115][116]118,120,121,123,127,129,131,139,143,154,157,160,163,173,190,193,199,235,237,238] ...
With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011–2021). A number of digital databases (i.e., IEEE Xplore®, ScienceDirect, Scopus, and Web of Science) were searched and explored to collect reliable peer-reviewed articles. Out of the 2214 collected articles, only 174 articles formed the final set of articles used in the analysis of the motorcyclist research area. The filtration process consisted of two stages that were implemented on the collected articles. Inclusion criteria were the core of the first stage of the filtration process keeping articles only if they were a study or review written in English or were articles that mainly incorporated the driving style of motorcyclists. The second phase of the filtration process is based on more rules for article inclusion. The criteria of inclusion for the second phase of filtration examined the deployment of motorcyclist driver behaviour characterisation procedures using a real-time-based data acquisition system (DAS) or a questionnaire. The final number of articles was divided into three main groups: reviews (7/174), experimental studies (41/174), and social studies-based articles (126/174). This taxonomy of the literature was developed to group the literature into articles with similar types of experimental conditions. Recommendation topics are also presented to enable and enhance the pace of the development in this research area. Research gaps are presented by implementing a substantial analysis of the previously proposed methodologies. The analysis mainly identified the gaps in the development of data acquisition systems, model accuracy, and data types incorporated in the proposed models. Finally, research directions towards ITS are provided by exploring key topics necessary in the advancement of this research area.
... A full moon has been reportedly associated with potential emergency department (ED) visits after traffic accidents [11] and mortality after motorcycle crashes and accidents [12]. However, Stomp et al. reported that phases other than full moon increased ED visits after all kinds of trauma [9]. ...
... However, FIs in metropolitan areas were less affected by lunar phase due to good visibility under night light that offset the effects of lunar phases. A previous study from Japan revealed a significant increase in the risk of emergency transport after traffic accidents on full moon days among those aged �40 years [11]. This finding is consistent with the results of our study showing a significant increase in FIs during full moon days especially in rural areas where the elderly individuals reside under weak artificial lighting at night. ...
Background
Previous studies reported that changes in weather and phases of moon are associated with medical emergencies and injuries. However, such studies were limited to hospital or community level without explaining the combined effects of weather and moon phases. We investigated whether changes in weather and moon phases affected emergency department (ED) visits due to fall injuries (FIs) based on nationwide emergency patient registry data.
Methods
Nationwide daily data of ED visits after FI were collected from 11 provinces (7 metropolitan cities and 4 rural provinces) in Korea between January 2014 and December 2018. The daily number of FIs was standardized into FI per million population (FPP) in each province. A multivariate regression analysis was conducted to elucidate the relationship between weather factors and moon phases with respect to daily FPP in each province. The correlation between weather factors and FI severity was also analyzed.
Results
The study analyzed 666,912 patients (418,135 in metropolitan and 248,777 in rural areas) who visited EDs on weekdays. No regional difference was found in age or gender distribution between the two areas. Precipitation, minimum temperature and wind speed showed a significant association with FI in metropolitan areas. In addition, sunshine duration was also substantial risk factors for FI in rural areas. The incidence of FIs was increased on full moon days than on other days in rural areas. Injury severity was associated with weather factors such as minimum temperature, wind speed, and cloud cover.
Conclusion
Weather changes such as precipitation, minimum temperature, and wind speed are associated with FI in metropolitan and rural areas. In addition, sunshine duration and full moon are significantly associated with FI incidence only in rural areas. Weather factors are associated with FI severity.
... This result held true for all seasons, weekdays, genders and ages. Contrary to a study involving 50,492 non-fatal traffic accidents in Saskatachewan that did not demonstrate a link to the lunar cycle [9], a report from Kyushu (Japan) based on 842,554 traffic accidents did show that there was indeed a significant increase in emergency transports for males aged ≥40 years of age on full moon nights before midnight [20]. An elevated risk during full moon has also been reported for motorcycle-related mortalities in the USA covering 40 years of data [21]. ...
... Geomagnetic storms can trigger strokes [53], and a significantly higher rate of suicides by females but not males during times of geomagnetic storms has been reported [54], in contrast to a finding of a decrease (but in a considerably Ref ( narrower age-group) [29]. For a study on the cosmogeophysical effects in the Arctic, unfortunately involving only male subjects (12 men aged [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38], the conclusion was that despite wide individual differences emotional states were clearly subject to central and autonomous nervous system and humoral effects "modulated…by the cosmogeophysical and meteorological agents" [55]. Pre-and post-menopausal women differ with regard to the menstrual period, which is "a carefully orchestrated sequence of interactions among the hypothalamus, pituitary, ovary, and endometrium" [56]. ...
Suicide data for this study were available for the period of March 1988 to June 2011, and involved 2111 male and 494 female victims from the Finnish province of Oulu. Data for lunar phases during that period were categorised into three groups: new moon (<25% visible), full moon (>75% visible) and other times with values in between. Seasonal effects were controlled with definitions for winter (Nov, Dec, Jan), spring (Feb, Mar, Apr), summer (May, June, July), and autumn (Aug, Sep, Oct). Suicide occurrences during different lunar phases were compared with their expected distribution using multinomial tests with all tests being two-tailed. Statistical significance was set at p < 0.05. No correlation between suicides and moon phase in any of the four seasons was apparent for male victims, but in winter for women it was (p = 0.001). Further analysis of the data revealed that the full moon association was statistically significant only for premenopausal women, defined as female victims younger than 45 years of age. To explain this unexpected finding a number of factors were considered, e.g., the darkness of a northern Finnish winter with increases of SAD and depression especially in premenopausal women, the influence of the lunar periodicity on the menstrual cycle, and cosmogeophysical effects on the humoral and autonomous nervous system.
... Thus, by affecting the movements of wild ungulates, full moon nights are thought to promote road crossings and collisions with vehicles. In addition, there is mounting evidence that full moon may also slightly increase accident risk by affecting drivers' behaviour, through distraction (Onozuka et al., 2018;Redelmeier & Shafir, 2018) or an increase in perceptual errors (Jägerbrand & Sjöbergh, 2016;Singh & Kathuria, 2021). ...
1. Although several studies have focused on the influence of moonlight on deer-vehicle collisions, findings have been inconsistent. This may be due to neglect of the effects of cloud cover, a major impediment to moon illumination and circannual variation in both deer and human activity.
2. We assessed how median cloud cover interacted with the illuminated fraction of the moon in affecting daily roe deer (Capreolus capreolus) roadkill in Slovenia (Central Europe). Data included nationwide roadkill (n = 49,259), collected between 2010 and 2019 by hunters, as required by law.
3. Roadkill peaked under medium to high cloud cover and decreased during nights with low or extremely high cloudiness. This pattern was more pronounced on nights with a full moon. However, the effects of moon illumination and cloud cover had a lower predictive potential than circannual variation, as collisions clearly peaked in April/May, July and August/September
4. Our results suggest that moonlight could influence roe deer movements through compensatory foraging. However, on nights with a full moon, collisions could also be affected by weather. On bright nights, roe deer might be less active due to increased human presence and sustained vehicular traffic. Then, with medium to high cloud cover and also rainfall, human presence in the environment may be low enough to increase deer movements, but vehicular traffic can still be intermediate, maximizing the risk of collisions. Finally, with overcast skies, widespread rainfall can reduce both traffic volume and human outdoor activity, decreasing the risk of collisions.
5. Moon illumination may indeed affect wildlife-vehicle collisions and roadkill, but its effects should be quantified as a function of cloud cover. Moreover, to make studies truly comparable, research about wildlife-vehicle collisions should also account for time of the year.
6. Policy implications. Because collisions with roe deer peak at particular periods of the year, signs should be installed seasonally. By doing so, they would warn drivers about the risk, improve drivers' awareness and increase their safety. Moreover, as collisions also increase on nights with a full moon and overcast skies, interactive warning signs that are activated by ground illumination should also be useful.
... In the 1st category, sample size based upon the social science approaches is focused upon the use of different 4 sample size groups, the size of 1st group ranges from 10 to 99 participants [47,61,79,101,118,132,133,167,189]. The 2nd group is in hundred and ranges from 100 to 999 participants [1,11,12,14,23,24,27,74,96,112,134,159,188,190] The 2nd class has been based on the sample size based on the simulator approaches. ...
There is an increase in motorcycles traffic accidents, while the cause for such accidents has always been associated with aggressive driving behaviors. There has been considerable research attention on how to deal with such driving behavior that causes severe and fatal accidents from the academic perspective; these research works addressed technical, scientific, and social issues. This study systematically searches, reviews, and analyzes the literature associated with motorcycle accidents and driving behaviors. Between the years 2014 and 2021, the next four databases have been searched: ScienceDirect, Scopus, Web of Science, and IEEE Xplore. A total of 108 people were picked depending on certain inclusion and exclusion criteria. Approximately 68% (n=79/108) of the researchers looked at the challenges from a social science perspective, whereas 25% (n=26/108) concentrated on experimental research variables. Only 7% (=3/108) explored the development of Apps & systems. Finally, our contribution comprehensively analyses most of the articles by highlighting challenges associated with motorcycle behavior, motivations, and recommendations. In addition, provide potential research gaps in current studies that require further investigation.
... Our data suggest that more lunar illumination influences animal movement, bringing them in greater contact with roadways, perhaps more than it enhances the ability of drivers to see wildlife and avoid collisions. Many authors have reported on the influence of lunar phases on the number of vehicle accidents, thus indicating the importance of human behavior [17,40,41]. Animal and human behaviors can have an additive effect on WVC patterns at night, especially seasonally when days get shorter and nights longer. ...
We investigated the relationship between lunar illumination based on the percentage of the visible lunar disk (LDP) and the frequency of wildlife–vehicle collisions (WVCs) in Lithuania. We analyzed WVC frequency during ten 10% LDP intervals to more precisely reflect the relationship between LDP and WVC. The 10% LDP interval approach showed a significant trend of increasing WVC frequencies with an increasing LDP at night. We also examined the correlation between the daily numbers of WVCs and LDP for different months and seasons. The relationship seemed to be stronger at night and during the late autumn–winter months, particularly in December, suggesting the importance of lunar illumination on WVCs. There was a weak positive correlation between LDP and overall daily number of WVCs (rs = 0.091; p < 0.001) and between LDP and night WVCs (rs = 0.104; p < 0.001). We found significant positive correlations for winter (December–February) (rs = 0.118; p = 0.012) and autumn (August–November) (rs = 0.127; p = 0.007). Our study suggests that the LDP interval approach may provide more possibilities for the evaluation and quantification of WVCs and lunar light relationships than the traditional lunar phase approach.
... Traffic safety continues to come into focus with the ever-increasing use of cars in modern society, and traffic accidents are becoming a major factor causing human injuries [1]. Although the human, social and economic cost of traffic accidents is largely preventable, there has been insufficient action to combat this global challenge [2]. It has been proven that human factors predict a greater amount of variance in road accidents than vehicle and road factors do [3]. ...
Joining worldwide efforts to understand the relationship between driving emotion and behavior, the current study aimed at examining the influence of emotions on driving intention transition. In Study 1, taking a car-following scene as an example, we designed the driving experiments to obtain the driving data in drivers' natural states, and a driving intention prediction model was constructed based on the HMM. Then, we analyzed the probability distribution and transition probability of driving intentions. In Study 2, we designed a series of emotion-induction experiments for eight typical driving emotions, and the drivers with induced emotion participated in the driving experiments similar to Study 1. Then, we obtained the driving data of the drivers in eight typical emotional states, and the driving intention prediction models adapted to the driver's different emotional states were constructed based on the HMM severally. Finally, we analyzed the probabilistic differences of driving intention in divers' natural states and different emotional states, and the findings showed the changing law of driving intention probability distribution and transfer probability caused by emotion evolution. The findings of this study can promote the development of driving behavior prediction technology and an active safety early warning system.
... A conditional Poisson approach is applied for the proposed analysis, with which the overdispersed Poisson (quasi-Poisson) distribution is assumed. The conditional Poisson approach is superior in adjusting for over-dispersion and autocorrelation, while avoiding estimating the stratum parameters (Armstrong et al., 2014;Onozuka et al., 2018). In the proposed conditional Poisson model, the RR and corresponding 95% confidence intervals (CIs) for the association between casualty count and exposure of interest are estimated based on the sum of the case of every spectrum (i.e. ...
Weather is well recognized as a significant environmental factor contributing to higher risk of road crashes. In the conventional road safety studies, weather effects had been set out either based on the instant weather conditions recorded by the police officer attained or the average of meteorological observations over a relatively long time period, such as daily, weekly or even monthly, etc. To the best of our knowledge, it is rare that the lag effect of weather in the preceding period on the crash risk in the current period was attempted. With the use of high-resolution meteorological data in very short time interval, it is possible to evaluate the role of lagged weather effect on safety. In this study, we propose a novel distributed lag non-linear model (DLNM), integrated with case-crossover design, to evaluate the lag effect of weather on crash incidence. The proposed modelling framework could describe the non-linear relationship between weather and crash and the lag effects. Also, the possible over-dispersion and autocorrelation of the time-series weather and crash data can be controlled for. The model was estimated using an integrated meteorological, traffic and crash dataset in Hong Kong. For instances, high resolution data on temperature, humidity, rain intensity and wind speed in 1-hour interval was available. The bi-dimensional exposure-lag-response surfaces are established to visualize the varying effects of possible weather factors on crash risk, with respect to the lag size. Such relationship between effect size and lag size is often overlooked in the literatures. Results indicate that model with 4 degrees of freedom for both weather condition (knots at equal spaces) and lag time (knots at equal intervals) best fit with the observations, in accordance to Quasi-likelihood Akaike information criterion (Q-AIC). Then, stratified analyses are conducted to evaluate the difference in the association among different clusters. Findings should shed light on the modelling of non-linear exposure-response relationship and lag effects in traffic safety time series analysis.
... Karimi and Kashi [19] investigated the effect of geometric parameters on accident reduction using sensitivity analysis. Onozuka et al. [20] studied whether a full moon contributes to the road traffic accidents using conditional Poisson regression. However, most of these methods are based on linear assumptions. ...
Traffic accidents have been one of the most important global public problems. It has caused a severe loss of human lives and property every year. Studying the influential factors of accidents can help find the reasons behind. This can facilitate the design of effective measures and policies to reduce the traffic fatality rate and improve road safety. However, most of the existing research either adopted methods based on linear assumption or neglected to further evaluate the spatial relationships. In this paper, we proposed a methodology framework based on XGBoost and grid analysis to spatially analyze the leading factors on traffic fatality in Los Angeles County. Characteristics of the collision, time and location, and environmental factors are considered. Results show that the proposed method has the best modeling performance compared with other commonly seen machine learning algorithms. Eight factors are found to have the leading impact on traffic fatality. Spatial relationships between the eight factors and the fatality rates within the Los Angeles County are further studied using the grid-based analysis in GIS. Specific suggestions on how to reduce the fatality rate and improve road safety are provided accordingly.
... Due to the rise of machine learning, corresponding algorithms have been applied to the data analysis of production safety management. In English, there is a study on the relationship between motor vehicle injury degree and hospital-related factors [1], analysis of fire factors in Spain [2], assessment of regional society, economy and environment through hydraulic fracturing activity [3], and study the relation between the full moon and traffic accidents through traffic accident information [4]. However, because of the limitations of some algorithm models, when text data is used in data analysis, most of the information is reduced. ...
Although several studies have focused on the influence of moonlight over deer-vehicle collisions, findings have been inconsistent. This may be due to neglecting the effects of cloud cover, a major impediment to moon illumination, and circannual variation in both deer and human activity.We modeled how median cloud cover interacted with the illuminated fraction of the moon in affecting daily roe deer (Capreolus capreolus) roadkill in Slovenia (Central Europe). Data included nationwide roadkill (n = 49,259), collected between 2010 and 2019 on a mandatory basis by hunters as well-trained citizen scientists.Roadkill peaked for medium-to-high cloud cover, while decreased at nights with low or extremely high cloudiness. This pattern was more pronounced at full moon nights. However, the effects of moon illumination and cloud cover had a lower predictive potential than circannual variation.Our results suggest that moonlight could influence deer movements through compensatory foraging. However, at full moon nights collisions could then be modulated by weather conditions, affecting human movement and vehicle traffic, and likely also road crossing by roe deer.Moon illumination may indeed affect wildlife-vehicle collisions and roadkill, but its effects should be quantified as a function of cloud cover. Because collisions with roe deer, the most common road-killed large mammals in Europe, peak at nights with full moon and casted skies, and at some precise periods of the year, interactive warning signs that detect ground illumination at these periods may improve drivers’ awareness and increase their safety.
Road transportation industry not only promotes economic development, but also brings many environmental issues in China. It is necessary to evaluate the integrated environmental efficiency of road transportation industry, including carbon dioxide emissions, traffic accident and traffic noise which is a Steaming Data. In this study, a parallel DEA model with sub-system preference is proposed to measuring the integrated environmental efficiency of road transportation industry in 2013–2017 considering various undesirable outputs. Then, the convergence analysis approach is employed to investigate the regional differences in terms of efficiency of road transportation. The empirical results show that the overall integrated environmental efficiency underperformed nationwide, and the passenger transportation sub-system outperformed freight transportation when the latter is restricted in some hours. From a regional perspective, the efficiency performances show downward trends in areas eastern, central and western. The passenger transportation sub-system outperforms in eastern area and the freight transportation outperforms in central area. Furthermore, the convergence analysis results indicate that the integrated environmental efficiency in eastern and western areas not only converged to their own stable levels but also that the differences in the integrated environmental efficiency between eastern and western areas are condensing. The contributions of this study lie in not only proposing a parallel DEA model with sub-system preference and considering the streaming data, but also providing suggestions to improving the road transportation industry in terms of integrated environmental efficiency. Finally, the research limitations and further research directions were conducted.
Objective
To test whether a full moon contributes to motorcycle related deaths.
Design
Population based, individual level, double control, cross sectional analysis.
Setting
Nighttime (4 pm to 8 am), United States.
Participants
13 029 motorcycle fatalities throughout the United States, 1975 to 2014 (40 years).
Main outcome measure
Motorcycle fatalities during a full moon.
Results
13 029 motorcyclists were in fatal crashes during 1482 relevant nights. The typical motorcyclist was a middle aged man (mean age 32 years) riding a street motorcycle with a large engine in a rural location who experienced a head-on frontal impact and was not wearing a helmet. 4494 fatal crashes occurred on the 494 nights with a full moon (9.10/night) and 8535 on the 988 control nights without a full moon (8.64/night). Comparisons yielded a relative risk of 1.05 associated with the full moon (95% confidence interval 1.02 to 1.09, P=0.005), a conditional odds ratio of 1.26 (95% confidence interval 1.17 to 1.37, P<0.001), and an absolute increase of 226 additional deaths over the study interval. The increase extended to diverse types of motorcyclists, vehicles, and crashes; was accentuated during a supermoon; and replicated in analyses from the United Kingdom, Canada, and Australia.
Conclusion
The full moon is associated with an increased risk of fatal motorcycle crashes, although potential confounders cannot be excluded. An awareness of the risk might encourage motorcyclists to ride with extra care during a full moon and, more generally, to appreciate the power of seemingly minor distractions at all times.
Bright sunlight may create visual illusions that lead to driver error, including fallible distance judgment from aerial perspective. We tested whether the risk of a life-threatening motor vehicle crash was increased when driving in bright sunlight.
This longitudinal, case-only, paired-comparison analysis evaluated patients hospitalized because of a motor vehicle crash between January 1, 1995 and December 31, 2014. The relative risk of a crash associated with bright sunlight was estimated by evaluating the prevailing weather at the time and place of the crash compared with the weather at the same hour and location on control days a week earlier and a week later.
The majority of patients (n = 6962) were injured during daylight hours and bright sunlight was the most common weather condition at the time and place of the crash. The risk of a life-threatening crash was 16% higher during bright sunlight than normal weather (95% confidence interval: 9–24, P < 0.001). The increased risk was accentuated in the early afternoon, disappeared at night, extended to patients with different characteristics, involved crashes with diverse features, not apparent with cloudy weather, and contributed to about 5000 additional patient-days in hospital. The increased risk extended to patients with high crash severity as indicated by ambulance involvement, surgical procedures, length of hospital stay, intensive care unit admission, and patient mortality. The increased risk was not easily attributed to differences in alcohol consumption, driving distances, or anomalies of adverse weather.
Bright sunlight is associated with an increased risk of a life-threatening motor vehicle crash. An awareness of this risk might inform driver education, trauma staffing, and safety warnings to prevent a life-threatening motor vehicle crash.
Level of evidence: Epidemiologic Study, level III.
The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters.
The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages.
By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression.
Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine stratification.
Distracted driving attributable to the performance of secondary tasks is a major cause of motor vehicle crashes both among teenagers who are novice drivers and among adults who are experienced drivers.
We conducted two studies on the relationship between the performance of secondary tasks, including cell-phone use, and the risk of crashes and near-crashes. To facilitate objective assessment, accelerometers, cameras, global positioning systems, and other sensors were installed in the vehicles of 42 newly licensed drivers (16.3 to 17.0 years of age) and 109 adults with more driving experience.
During the study periods, 167 crashes and near-crashes among novice drivers and 518 crashes and near-crashes among experienced drivers were identified. The risk of a crash or near-crash among novice drivers increased significantly if they were dialing a cell phone (odds ratio, 8.32; 95% confidence interval [CI], 2.83 to 24.42), reaching for a cell phone (odds ratio, 7.05; 95% CI, 2.64 to 18.83), sending or receiving text messages (odds ratio, 3.87; 95% CI, 1.62 to 9.25), reaching for an object other than a cell phone (odds ratio, 8.00; 95% CI, 3.67 to 17.50), looking at a roadside object (odds ratio, 3.90; 95% CI, 1.72 to 8.81), or eating (odds ratio, 2.99; 95% CI, 1.30 to 6.91). Among experienced drivers, dialing a cell phone was associated with a significantly increased risk of a crash or near-crash (odds ratio, 2.49; 95% CI, 1.38 to 4.54); the risk associated with texting or accessing the Internet was not assessed in this population. The prevalence of high-risk attention to secondary tasks increased over time among novice drivers but not among experienced drivers.
The risk of a crash or near-crash among novice drivers increased with the performance of many secondary tasks, including texting and dialing cell phones. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Highway Traffic Safety Administration.).
BACKGROUND: The two-stage time series design represents a powerful analytical tool in environmentalepidemiology. Recently, models for both stages have been extended with the development ofdistributed lag non-linear models (DLNMs), a methodology for investigating simultaneouslynon-linear and lagged relationships, and multivariate meta-analysis, a methodology to pool estimatesof multi-parameter associations. However, the application of both methods in two-stage analyses isprevented by the high-dimensional definition of DLNMs. METHODS: In this contribution we propose a method to synthesize DLNMs to simpler summaries, expressed bya reduced set of parameters of one-dimensional functions, which are compatible with currentmultivariate meta-analytical techniques. The methodology and modelling framework areimplemented in R through the packages dlnm and mvmeta. RESULTS: As an illustrative application, the method is adopted for the two-stage time series analysis oftemperature-mortality associations using data from 10 regions in England and Wales. R code anddata are available as supplementary online material.Discussion and Conclusions
The methodology proposed here extends the use of DLNMs in two-stage analyses, obtainingmeta-analytical estimates of easily interpretable summaries from complex non-linear and delayedassociations. The approach relaxes the assumptions and avoids simplifications required by simplermodelling approaches.
In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure-response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd.
While time series analyses have demonstrated that airborne particles are associated with early death, they have not clarified
how much the deaths are advanced. If all of the pollution-related deaths were advanced by only a few days, one would expect
little association between weekly averages of air pollution and daily deaths. The author used the STL algorithm to classify
data on air pollution, daily deaths, and weather from Boston, Massachusetts (1979–1986) into three time series: one reflecting
seasonal and longer fluctuations, one reflecting short term fluctuations, and one reflecting intermediate patterns. By varying
the cutoff point between short term and intermediate term, it was possible to examine harvesting on different time scales.
For chronic obstructive pulmonary disease, there was evidence that most of the mortality was displaced by only a few months.
For pneumonia, heart attacks, and all-cause mortality, the effect size increased with longer time scales. The percentage increase
in all deaths associated with a 10-μg/m3 increase in PM2.5 rose from 2.1% (95% confidence interval: 1.5, 4.3) to 3.75% (95% confidence interval: 3.2, 4.3) as the focus moved from daily
patterns to monthly patterns. This is consistent with the larger effect seen in prospective cohort studies, rather than harvesting's
playing a major role. Am J Epidemiol 2000;151:440–8.
Despite aggressive efforts in spatial disorientation (SD) research, hardware development, and training, the operational impact of SD in terms of crew and aircraft losses remains significant. Current training in spatial orientation is primarily composed of didactic lectures on the anatomy and physiology of the sensory systems. Significant efforts have been concentrated on reproducing various types of visual and vestibular "illusions" that pilots might encounter in flight, with limited and varying success. Unfortunately, the terms of "SD" and "illusion" have been used synonymously, leading to the general belief that if one were to be exposed to a specific type of illusion, one can prevent or avoid SD mishaps. Another setback is the inability of ground-based devices to reproduce the flight envelope. Often the demonstration of a specific illusion ends abruptly without further explanation or how these illusions can affect pilot performance. Demonstration of illusions seldom deals with the precipitating factors. We should provide pilots with skills to anticipate and assess the risk of SD during mission planning. Pilots should be sensitized to the physical and mental performance decrement during sensory conflicts and inadequacies. Recommendations should also be made on possible ways to recover from SD should they become disoriented. Special attention should be drawn to the properties of various flight displays that may contribute to SD. G tolerance and disorientation should be examined together in high performance aircraft as there is a close relationship between exposure to acceleration and maintaining orientation. The motto for counteracting SD is: anticipate, avoid, and counteract SD.
Environmental epidemiologists often encounter time series data in the form of discrete or other nonnormal outcomes; for example, in modeling the relationship between air pollution and hospital admissions or mortality rates. We present a case study examining the association between pollen counts and meteorologic covariates. Although such time series data are inadequately described by standard methods for Gaussian time series, they are often autocorrelated, and warrant an analysis beyond those provided by ordinary generalized linear models (GLMs). Transitional regression models (TRMs), signifying nonlinear regression models expressed in terms of conditional means and variances given past observations, provide a unifying framework for two mainstream approaches to extending the GLM for autocorrelated data. The first approach models current outcomes with a GLM that incorporates past outcomes as covariates, whereas the second models individual outcomes with marginal GLMs and then couples the error terms with an autoregressive covariance matrix. Although the two approaches coincide for the Gaussian GLM, which serves as a helpful introductory example, in general they yield fundamentally different models. We analyze the pollen study using TRM's of both types and present parameter estimates together with asymptotic and bootstrap standard errors. In several cases we find evidence of residual autocorrelation; however, when we relax the TRM to allow for a nonparametric smooth trend, the autocorrelation disappears. This kind of trade-off between autocorrelation and flexibility is to be expected, and has a natural interpretation in terms of the covariance function for a nonparametric smoother. We provide an algorithm for fitting these flexible TRM's that is relatively easy to program with the generalized additive model software in S-PLUS.
While differences between anterior and inferior acute myocardial infarction have been observed, clinical features of lateral infarction are poorly investigated. However, the impact of gender on clinical course and prognosis after myocardial infarction is not fully understood. Electrocardiographically determined infarct site, demographic and clinical variables were prospectively recorded for 1623 consecutive patients admitted to Clinical Hospital Split between 1990 and 1994 due to a first Q-wave acute myocardial infarction. Anterior infarctions were correlated with a higher prevalence of diabetes (P=4×10−6) or pulmonary venous congestion (P=2×10−12); inferior infarctions were correlated with a lower prevalence of hypertension (P=0.001), hypercholesterolemia (P=0.02) or diabetes (P=10−5), and a higher prevalence of smoking (P=0.001); lateral infarctions were characterized by a smaller infarction size and lower prevalence of pulmonary congestion (P=0.002). Among men under the age of 50 with inferior infarction there were 90% smokers, which was significantly more than among their gender (P=0.005) or infarct site (P=2×10−5) counterparts. After adjustment for age and other confounding factors, the prevalence of inferior infarction was higher in men (P=0.002). Increased age (P=0.002), female gender (P=0.0006), anterior site (P=10−5), diabetes (P=0.0003), greater creatine kinase-MB fraction level (P=0.001) and pulmonary congestion (P=9×10−6) were independent predictors of an adverse hospital outcome. Each site of acute myocardial infarction has relatively specific preinfarction and clinical features. Our results suggest a greater importance of vasoconstriction in the pathophysiology of inferior infarction, especially in young male smokers, and greater importance of advanced atherosclerotic process in occurrence of anterior infarction.
We examined trends in distracted driving fatalities and their relation to cell phone use and texting volume.
The Fatality Analysis Reporting System (FARS) records data on all road fatalities that occurred on public roads in the United States from 1999 to 2008. We studied trends in distracted driving fatalities, driver and crash characteristics, and trends in cell phone use and texting volume. We used multivariate regression analysis to estimate the relation between state-level distracted driving fatalities and texting volumes.
After declining from 1999 to 2005, fatalities from distracted driving increased 28% after 2005, rising from 4572 fatalities to 5870 in 2008. Crashes increasingly involved male drivers driving alone in collisions with roadside obstructions in urban areas. By use of multivariate analyses, we predicted that increasing texting volumes resulted in more than 16,000 additional road fatalities from 2001 to 2007.
Distracted driving is a growing public safety hazard. Specifically, the dramatic rise in texting volume since 2005 appeared to be contributing to an alarming rise in distracted driving fatalities. Legislation enacting texting bans should be paired with effective enforcement to deter drivers from using cell phones while driving.
The time distribution of injuries is not random. To assess the potential impact of weather and the phase of the moon on accidents, adjustment for known periodic and nonperiodic factors may be important. We compared the incidence of injuries with quantitative and qualitative weather variables as well as the lunar cycle, after correction for calendar and holiday-related factors.
We extracted the daily number of trauma patients treated at the emergency department over 36 years (1970-2005) from the trauma database of our regional hospital. For each patient, age, sex, cause of injury, and severity of injury were recorded. This was combined with daily meteorological data including temperature, precipitation, sunshine, humidity, air pressure, and wind as well as the lunar phase. We also related the rate of change of these parameters with the incidence of injuries. A qualitative weather variable derived from temperature, sunshine duration, and precipitation was defined as bad, normal, or good. Periodicities were adjusted for with Poisson regression spline fitting analysis.
Several weather variables were related with the number of injuries. For most of these, better weather conditions were associated with an increase in trauma incidence. Good weather, which was present on 16.5% of the days, resulted in 10.1% (9.3-11.4 95% CI) more traumas compared with normal weather. Full moon was associated with a 2.1% (1.1-3.0 95% CI) lower trauma incidence than new moon.
Better weather conditions contribute to an increased incidence of trauma. Full moon is associated with a slightly lower trauma incidence.
Recent documentation of a circadian variation in acute myocardial infarction (AMI) suggests that AMI is not a random event, but may frequently result from identifiable triggering activities. The possible triggers reported by 849 patients enrolled in the Multicenter Investigation of Limitation of Infarct Size were analyzed. Possible triggers were identified by 48.5% of the population; the most common were emotional upset (18.4%) and moderate physical activity (14.1%). Multiple possible triggers were reported by 13% of the population. Younger patients, men and those without diabetes mellitus were more likely to report a possible trigger than were older patients, women and those with diabetes. The likelihood of reporting a trigger was not affected by infarct size. This study suggests that potentially identifiable triggers may play an important role in AMI. Because potential triggering activities are common in persons with coronary artery disease, yet infrequently result in AMI, further studies are needed to identify (1) the circumstances in which a potential trigger may cause an event, (2) the specific nature of potential triggering activites, (3) the frequency of such activities in individuals who do not develop AMI and (4) the presence or absence of identifiable triggers in various subgroups of patients with infarction.
To determine if there is any effect of the full moon on emergency department (ED) patient volume, ambulance runs, admissions, or admissions to a monitored unit, a retrospective analysis of the hospital electronic records of all patients seen in an ED during a 4-year period was conducted in an ED of a suburban community hospital. A full moon occurred 49 times during the study period. There were 150,999 patient visits to the ED during the study period, of which 34,649 patients arrived by ambulance. A total of 35,087 patients was admitted to the hospital and 11,278 patients were admitted to a monitored unit. No significant differences were found in total patient visits, ambulance runs, admissions to the hospital, or admissions to a monitored unit on days of the full moon. The occurrence of a full moon has no effect on ED patient volume, ambulance runs, admissions, or admissions to a monitored unit.
The case-crossover design is an innovative epidemiologic technique with distinct strengths and limitations. We review the fundamental logic of this self-matching non-randomized design and direct attention to 15 concerns related to the available data, unavailable data, analytic technique, quantitative statistics, and etiologic model. Implications for each concern are discussed in the context of a recent report on whether cellular telephone calls are associated with an increased risk of a motor vehicle collision. We suggest that an understanding of the case-crossover design may help investigators explore selected questions in behavioral medical research.
Although many studies have shown that airborne particles are associated with increased daily death and hospitalization rates, some have questioned whether these events are occurring in persons who would die or enter the hospital within a few days in any case. This hypothesis is usually called the harvesting effect. Harvesting is postulated to occur because the size of the pool of susceptibles decreases as a result of air pollution. I have developed a framework for examining this hypothesis. I used a smoothing technique that allowed me to examine the association between daily deaths and daily hospital admissions net of any such rebound that occurred within a fixed time scale. By varying that time scale I could look at effects net of rebounds on successively larger time scales, ranging from 15 to 60 days. I examined daily deaths and hospital admissions in Chicago for the years 1988-1993. In baseline analyses, particulate matter less than 10 microm in aerodynamic diameter (PM10) was associated with increased daily deaths and hospital admissions for heart disease, pneumonia, and chronic obstructive pulmonary disease. A 10 microg/m3 increase in PM10 was associated with a 0.89% increase in daily deaths (95% confidence interval = 0.61-1.16%), for example. Using smoothing to look at effects net of short-term rebounds, the effect-size estimates for daily deaths and for chronic obstructive pulmonary disease admissions more than doubled. They did not change for pneumonia and heart disease admissions. The increased effect size for daily deaths occurred only for deaths outside of the hospital. These results are consistent with air pollution increasing the size of the risk pool and for most of the deaths being advanced by months to years.
To determine the effect of the phase of the full and new moon on the variation in the number of daily cardiopulmonary resuscitations.
A retrospective analysis of a computerized billing database of emergency department visits in a cohort of seven northern New Jersey (USA) emergency departments.
Consecutive patients seen by emergency department physicians over an 11-year period (1 January 1988 to 31 December 1998). We determined the timing of full and new moon days from the National Oceanographic and Aeronautic Administration website.
Time series regression estimated the independent effect of full and new moon days on the daily variation in cardiopulmonary resuscitations. Tests of statistical significance were made at alpha=0.05.
A total of 2 370 233 emergency department visits were made during the 4018-day period of study. A total of 6827 had an emergency department diagnosis of cardiopulmonary resuscitation. We found no significant difference in the occurrence of cardiopulmonary resuscitations during the full moon (P=0.97). On average there were 6.5% fewer cardiopulmonary resuscitations during new moon days (P=0.02; 95% confidence interval 1.3-11.7%).
Contrary to the traditional belief that more cardiopulmonary resuscitations occur during the full moon, we were unable to identify a significant effect during full moon days. However, there were on average 6.5% fewer cardiopulmonary resuscitations during new moon days than other days.
This article concerns the interpretation of epidemiological studies of air pollution mortality and the choice of indicators for quantifying the impact, for communication with policymakers. It is shown that the total mortality impact (measured by cohort studies) can only be quantified in terms of loss of life expectancy (LLE), not number of premature deaths. Time-series (TS) studies of mortality observe only acute impacts, that is, deaths due to short-term exposure ("acute mortality"); they allow the estimation of a number of deaths without providing any information on the LLE per death. However, even if the average loss per death is as long as 6 mo, acute mortality is only a very small percentage of the total mortality attributable to air pollution. Estimates of the population-average LLE due to air pollution are provided, for acute mortality, total adult mortality, and infant mortality.
The case-crossover design has been widely used to study the association between short-term air pollution exposure and the risk of an acute adverse health event. The design uses cases only; for each individual case, exposure just before the event is compared with exposure at other control (or "referent") times. Time-invariant confounders are controlled by making within-subject comparisons. Even more important in the air pollution setting is that time-varying confounders can also be controlled by design by matching referents to the index time. The referent selection strategy is important for reasons in addition to control of confounding. The case-crossover design makes the implicit assumption that there is no trend in exposure across the referent times. In addition, the statistical method that is used-conditional logistic regression-is unbiased only with certain referent strategies. We review here the case-crossover literature in the air pollution context, focusing on key issues regarding referent selection. We conclude with a set of recommendations for choosing a referent strategy with air pollution exposure data. Specifically, we advocate the time-stratified approach to referent selection because it ensures unbiased conditional logistic regression estimates, avoids bias resulting from time trend in the exposure series, and can be tailored to match on specific time-varying confounders.
A mobile recording system, with integrated laser speed gun, video from CCD-cameras and auxiliary battery system, was used to observe driving behavior at an urban intersection and a suburban analog. After removal of instances of interference, 1538 driving behaviors were recorded. Multiple regression was then utilized to examine the factors affecting approaching speed. Speed limit violation was considered a dichotomous variable with two categories, violation and compliance. Binary logistic regression was also used to examine the risk of speeding as a function of covariates and interaction terms. The results of analysis revealed that the major contributing factors for approaching speed were site, rush-hour-status, traffic light condition, vehicle type and driver gender. In particular, light status was the highest contributor to speed. In addition, the results of logistic regression showed significant sites and rush-hour effects on speeding, with the risk of limit violation in the suburbs nearly six-fold that in urban areas. The relative risk of speeding for travelling in non-rush hours is three times higher than that for rush-hour. In terms of driver characteristics, male drivers under 55 years of age had the greatest speeding propensity in our sample. The results of the present study may provide meaningful information applicable to the design and operation of signalized intersections.
Mind wandering and driving: responsibility case-control study
- C Galera
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- K Bailara
- M Laborey
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- R Ribereau-Gayon
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A UK survey of driving behaviour, fatigue, risk taking and road traffic accidents
- T A Schweizer
- K Kan
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- F Tam
- G Naglie
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