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Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers: The importance of epidemiological representative surveys a
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M. Gonçalves , A.R. Peralta , J. Monteiro Ferreira & Christian Guilleminault a
Centro de Medicina do Sono, Hospital Cuf Porto, Porto, Portugal;
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Santa Maria Hospital, CHLN, EEG/Sleep Lab, Lisboa;
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Centro de Estudos de Doenças Respiratórias e Alérgicas – Coimbra;
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Stanford University Sleep Disorders Clinic, Stanford, USA Accepted author version posted online: 20 Mar 2015.
Click for updates To cite this article: M. Gonçalves, A.R. Peralta, J. Monteiro Ferreira & Christian Guilleminault (2015): Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers: The importance of epidemiological representative surveys, Traffic Injury Prevention To link to this article: http://dx.doi.org/10.1080/15389588.2015.1013535
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ACCEPTED MANUSCRIPT Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers The importance of epidemiological representative surveys M. Gonçalves1; A.R. Peralta2,5; J. Monteiro Ferreira3; Christian Guilleminault4 1
Centro de Medicina do Sono, Hospital Cuf Porto, Porto, Portugal ;
CHLN, EEG/Sleep Lab, Lisboa;
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Santa Maria Hospital,
Centro de Estudos de Doenças Respiratórias e Alérgicas –
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Coimbra; 4 Stanford University Sleep Disorders Clinic, Stanford, USA Corresponding author: Marta Azevedo Gonçalves Email: [email protected] Centro de Medicina de Sono, Hospital Cuf Porto, Porto, Portugal Number of words: 4966 Number of references: 27 Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers The importance of epidemiological representative surveys M Gonçalves1; AR Peralta2,5; J Monteiro Ferreira3; C Guilleminault4 1
Centro de Medicina do Sono, Hospital Cuf Porto Portugal;
EEG/Sleep Lab, Lisboa, Portugal
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Santa Maria Hospital, CHLN,
Centro de Estudos de Doenças Respiratórias e Alérgicas –
Coimbra; 4 Stanford University Sleep Disorders Clinic, Stanford, USA Abstract Objective: Sleepiness is considered to be a leading cause of crashes. Despite the huge amount of information collected in questionnaire studies only some are based on representative samples of the population. Specifics of the populations studied hinder the generalization of these previous findings. For the Portuguese population, data from sleep related car crashes/near misses and
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ACCEPTED MANUSCRIPT sleepiness while driving is missing. The objective of this study is to determine the prevalence of near-miss and non-fatal motor-vehicle crashes related to sleepiness in a representative sample of Portuguese drivers. Methods: Structured phone interview regarding sleepiness and sleep related crashes and near-misses, driving habits, demographic data, sleep quality using the Pittsburgh Sleep Quality Index and sleep apnea risk using the Berlin questionnaire. A multivariate
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regression analysis was used to determine the associations with sleepy driving (feeling sleepy or falling asleep while driving) and sleep related near-misses and crashes. Results: 900 subjects, representing the Portuguese population of drivers, were included. 3.1% acknowledged falling asleep while driving during the previous year; 0.67% recalled sleepiness-related crashes. Higher education, driving more than 15000 km/year, driving more frequently between 0 and 6 AM, fewer years of having a drivers license, less total sleep time per night and higher scores on the Epworth Sleepiness Scale (ESS) were all independently associated with sleepy driving. Sleepiness related crashes and near misses were associated only with falling asleep at the wheel in the previous year. Sleep related crashes occurred more frequently in drivers that had also had sleep related near misses. Conclusion: Portugal has lower self-reported sleepiness at the wheel and sleep related near-misses than most other countries where epidemiological data is available. Different population characteristics, cultural, social and road safety specificities may be involved in these discrepancies. Despite this, Portuguese drivers report sleep related crashes in frequencies similar to drivers in other countries.
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ACCEPTED MANUSCRIPT Introduction Sleepiness contributes to car crashes, though this contribution varies widely depending on the methodology used to study it. Studies analyzing car crash databases underestimate the importance of sleepiness because the authorities attribute accidents to more visible causes. Surveys conducted on crash survivors retrospectively analyzing their pre-accident sleepiness are
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limited to crashes severe enough to require police/insurance involvement.
In these cases,
sleepiness-related near-misses and minor crashes are very frequent (Klauer et al, 2006). Questionnaires applied to regular drivers may overcome these limitations. There is a large amount of data concerning this subject. Surveys have been conducted in representative samples of the population (Sagaspe et al, 2010 - France; National Sleep Foundation (NSF) surveys - US; Traffic Injury Research Foundation (TIRF) surveys - Canada; Papadakakia et al, 2008 - Greece; Gander et al, 2005 - Australia; Maycock et al, 1997 – UK.) or in non representative samples (Phillips and Sagberg, 2012; Sagberg et al, 1999; Stutts et al, 2003; Philip et al, 2010; Hanning and Welsh, 1996; Gander et al, 2005). Direct comparisons of these studies across various countries is difficult given the difference in variables collected, time frames, lack of a standardized definition for sleepy driving and populations studied. In the US, 64% of the drivers acknowledged feeling sleepy while driving the previous year (NSF’s poll 2008; Swanson et al, 2011) and 29%-35% said they had fallen asleep while driving at least once (NSF’s poll 2011; Garder and Alexander, 1995; NSF’s poll 2008; Swanson et al, 2012). Similar figures were reported in a representative survey of New York state drivers (McCartt et al, 1996). The TIRF surveys in Canada also reported rates as high as 38.9% of nodding off while driving. In France, the reported prevalence of severe sleepiness while driving
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ACCEPTED MANUSCRIPT (i.e. requiring cessation of driving) in the previous year varied from 28.2% (Nabi et al, 2006), 36% (Sagaspe et al., 2010) and 57.3% (Philip et al, 2010). In the UK, severe sleepiness also occurred in 29% of the drivers in the previous year (Maycock et al, 1997). In Tokyo 11.4%20.3% of the drivers recalled nodding off and 40.4-67.7% recalled any kind of sleepiness at the wheel in the previous year (Abe et al, 2012, Komada et al, 2010). An overall average shows that
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severe sleepiness and nodding off at the wheel is reported by about 1/4 to 1/3 of drivers in one year. There are, however, conflicting results. A Norwegian survey of drivers involved in crashes, reported that only 8.3% of the not-at-fault drivers acknowledged falling asleep while driving in the previous year (Sagberg et al, 1999). In a recent update, this percentage decreased even further to 2.9 % (Phillips et al, 2013). Despite the different population, this study seems to indicate lower prevalence of severe sleepiness at the wheel in Norway. The prevalence of sleep-related crashes varies more widely. In the US, NSF’s polls have shown a prevalence of 2% for all drivers (NSF poll 2008, Swanson et al, 2011), 1% of non-professionals and 1-6% of professional drivers (NSF’s poll 2011) in one year. Smaller prevalence (0.2%-0.4%) was reported in France (Sagaspe et al, 2010; Philip et al, 2010) and higher prevalence (10,4%) in Tokyo (Komada et al, 2010). As can be concluded from this review of the available data, the generalization of the reported frequencies of sleep related car-crashes/near misses and sleepy driving is not possible. Besides varying methodologies in the different studies, different populations and road/traffic rules from the different countries studied may be responsible for the disparities found. A more detailed mapping of this problem may shed some light in to the factors that contribute to this important public health issue.
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ACCEPTED MANUSCRIPT In Portugal it is not known what is the frequency of sleep related car-crashes/near misses and sleepy driving. The primary objective of this study was to determine the annual frequency of sleepiness while driving, near-misses and motor-vehicle accidents related to sleepiness in a representative sample of Portuguese drivers. We also looked for possible demographic, driving and sleep-related correlations of these variables. Finally, we investigated which measures motor-
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vehicle drivers took when feeling sleepy at the wheel. Methods A - Selection of subjects The report from the National Institute of Statistics in 2006, based on a 2001 census, indicates 60% of the general population had driver’s license (about 6 million drivers). A sample size of 900 subjects was calculated to have a confidence interval of 3%, (confidence level 95%) assuming a prevalence of sleepy driving at around 30%. “Regular drivers” were defined as subjects who drove vehicles at least once per week. The selection of subjects was made through stratified sampling with replacement taking into consideration age, gender, and geographic distribution of the population (region and rural/urban dwelling). Trained interviewers conducted phone interviews. Phone numbers were selected at random, including both landline and mobile phones. Subjects were informed of confidentiality and oral informed consent was obtained. Given the nature of this survey, specific ethics approval was not necessary. B – The Instrument The questionnaire was conducted over the phone by trained interviewers. The core questions were: 1)“During the past year, have you ever driven while feeling sleepy?” 2)“During last year, have you ever fallen asleep while driving?”. Drivers that experienced sleepiness were asked to
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ACCEPTED MANUSCRIPT recall crashes and near-misses related to sleepiness that occurred over the previous year as well as sleepiness counter-measures that they used that time. Accidents were characterized by location type (city, highway, country roads). Countermeasures included opening of the car window, increasing radio volume, setting the air conditioning to cold, drinking caffeinated beverages or water, eating, stopping to rest, stopping to sleep, other behavioural activities or no
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behavioural change. Subjects were given a list and asked to rank the countermeasures from most frequent to least frequent. No limit was set for subject’s responses. For analysis purposes, the preferred measure referred by each subject was selected. For multivariate analysis purposes, a variable named “sleepy driving” was defined to include all subjects that answered yes either to the question related to driving while sleepy or to the question regarding falling asleep at the wheel. In this variable, both feeling sleepy, without any specific severity grading, and falling asleep/dozing off, were analysed together. Also, the variable “accidents and near misses” was defined to include all subjects that answered yes either to the question regarding having previously experienced near-misses or to the question regarding having previously experienced accidents related to sleepiness. The questionnaire also included: 1. Demographic, social and medical information: age; gender; marital status; yearly income; general occupational categories; education (illiterate; 4 years; 6 years; 9 years; 12 years; university; >university); shift work (yes/no), type of shifts (day, night, or both); weight; height; diagnosed sleep disorder (sleep apnea, other); intake of sleeping pills; known chronic illness; habitual daily intake of caffeinated beverages; habitat (city versus country dwelling) and specific geographic location.
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ACCEPTED MANUSCRIPT 2. Driving habits: amount of driving in Km/year (0-5000; 5000-15000; 15000-25000; 2500040000;>40000); percentage of driving between midnight and 6AM; professional driving (yes/no). No specific definition of professional driving was provided and the subjects could interpret this question as having to drive as part of their work. 3. Epworth Sleepiness Scale (ESS) (Santos C.R., 2001) to determine chronic daytime
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sleepiness (sleepiness was defined as a score ≥10) 4. Berlin questionnaire (Vaz et al, 2011) to categorize the likelihood of having sleep apnea. 3. Pittsburgh Sleep Quality Index (PSQI), used to determine sleep quality (cut off ≥5 was used for “bad sleep quality”). The Portuguese version, currently being validated, was used. (Marques at al, 2013). Statistical analyses Descriptive statistics were used to characterize the samples studied. Continuous variables analysed were: age, BMI, years of having one’s driver’s license, percentage of time driving between 0 and 6 AM, number of caffeinated beverages/day, ESS and PSQI. Categorical variables analysed were: gender; education level (analysed according to legal school years in Portugal as ≥9 and 2 (mean of the population studied); Km driven/year: ≤15000 and >15000; diagnosed sleep disorder; intake of sleeping pills: ≤1/week and >1/week (middle category inquired); excessive daytime sleepiness (ESS≥10); Berlin questionnaire (high risk /low risk); Age: ≤ 30 years and >30 years old; BMI: underweight, normal, overweight and obese.
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ACCEPTED MANUSCRIPT Univariate analysis using Pearson Chi-square (or, when appropriate, Fisher exact test) was performed to look for associations between the variables collected and sleepy driving and crashes/near-misses. Sleepy driving was studied in all subjects. Accidents and near misses were analysed within the subgroup that answered yes to the question regarding ever-experiencing sleepiness while driving. For countermeasures analysis, a variable named “effective
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countermeasures” was constructed that included subjects that described first countermeasures as stopping the car, sleeping or drinking coffee (De Valck E & Cluydts 2001; Philip et al, 2006; Reyner & Horne 1996, 1997). For regression analysis, only variables with significant association in univariate analysis (p10 remained as independent factors explaining sleepy drivers, albeit with small odds ratio.
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Near-misses and accidents In the entire population studied, 19 (2.1%) of the subjects reported a near-miss motor vehicle accident due to sleepiness within the last year and 0.67% recalled a traffic accident due to sleepiness during the same period. Among the subgroup sleepy drivers, near-miss crashes were reported by 8.83% of subjects and sleep-related crashes occurred in 2.8%. From the six subjects that recalled sleep-related crashes, two reported three accidents in the preceding year. Five accidents occurred from 00:00-06:00 AM, four accidents occurred from 12:00-18:00 PM and only one occurred between 18:00 PM and 00:00 AM. Most of the accidents occurred on secondary roads (either in or outside the city) and only one accident occurred on the highway. Factors associated with sleep-related crashes and near-misses can be found in table 4. With multiple regression (table A5 in the appendix), the only variable that remained as an independent factor associated with sleepiness-related accidents and near-misses was having ever fallen asleep while driving. Evaluation of countermeasures Overall, 44% of these drivers stopped to rest, 1.9% napped and 54.1% continued driving and used different strategies to counteract sleepiness. The preferred countermeasures employed by
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ACCEPTED MANUSCRIPT drivers while driving sleepy are listed in graph A1 of the appendix. Subjects having a driver’s license for more years, older subjects and males were more likely to use adequate counter measures i.e. stopping to sleep, stopping to take a rest or drinking caffeine beverages. Subjects reporting previous near-miss accidents were also less likely to choose effective countermeasures (Table A6 in the apendix).
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Discussion This is the first study focusing on sleepiness, sleep-related near-misses and accidents in a representative sample population of Portuguese drivers. We found that about 1/4 of the Portuguese population of drivers reported driving sleepy at least once during the previous year and 3.1% had fallen asleep while driving. These findings indicate that Portuguese drivers report less sleepiness while driving than other populations previously studied using similar methodologies (Sagaspe et al, 2010; Philip et al, 2010; NSF and TIRF polls; Maycock et al, 1997, McCartt et al, 1996; Abe et al, 2012; Komada et al, 2010; Garder and Alexander, 1995; Nabi et al, 2006). The reported prevalence of nodding off while driving is similar to the lower figures encountered in Norway (Philips et al, 2013). These results confirm that the prevalence of feeling sleepy while driving varies between countries. These differences may be related to factors related to the type of questions posed in the survey and to special characteristics of the population analyzed. It is relevant to analyse the way the questions were formulated. First, in our study, sleepiness was not defined in terms of severity. In the Portuguese there are several ways to describe sleepiness. It is possible that the question formulated was interpreted as having connotations towards a more severe form of sleepiness. When compared to other surveys (p.e. Sagaspe et al, 2010; Maycock
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ACCEPTED MANUSCRIPT et al, 1997), the prevalence of sleepy driving in our study approaches the prevalence of severe sleepiness (defined as sleepiness so severe as I could easily fall asleep or so severe as to require stopping the car). The formulation of the question is also relevant in Portuguese when analysing the response to the question of falling asleep. It is interesting to note that slightly different formulations of the same question namely the one used as our primary question (“During last
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year, have you ever fallen asleep while driving?”) and the one used during ESS (“How likely are you to doze off or fall asleep in the car, while stopping for few minutes in traffic?”) led to different reported numbers of sleeping while driving. For the first question, 3.1% answered yes, compared to 6% for the last question. Regardless, even this number is below the usual reported prevalence of nodding off while driving, which approaches 25-30%. It is unlikely that potential liability may have prevented drivers from acknowledging their sleepy driving. In Portugal there is no specific legislation regarding this issue, the questionnaire was anonymous and conducted by entities known to the drivers to be independent from law enforcement. It is difficult to compare the characteristics of the population studied in other countries with the Portuguese sample, as most of the analysed variables are not reported in other studies. Here we show a preponderance of male drivers and a fairly even representation of most age groups similar to most other studies (Sagaspe et al, 2010; Philip et al, 2010; Abe et al, 2012; Nabi et al, 2006; Swanson et al, 2012). Our subjects had a very small percentage of diagnosed sleep disorders (1.8%) when compared to the study by Philip et al (2010) where 27.8% of the subjects reported sleep disorders. However, despite the small prevalence of diagnosed sleep disorders, 10% of our sample had a high probability of sleep apnea according to the Berlin questionnaire, and 45% had bad sleep quality on the PSQI. This suggests that sleep disorders may be under-
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ACCEPTED MANUSCRIPT diagnosed in our group. Another important difference is that our population has a high percentage of drivers only driving 0-5000 Km per year (29%) when comparing to other studies (Sagaspe et al, 2010; Philip et al, 2010; Nabi et al, 2006) and trips in Portugal are usually short (it is possible to drive from the northern end to the southern border in about 6 hours). Reduced driving exposure and shorter trips in our group may have contributed to the smaller prevalence of
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drowsy driving. Another important difference between our sample and other samples is the literacy status in Portugal. In 2009, only 15.3% of the population had a university degree and 4.1% were illiterate (PORDATA). In our sample, only 26.6% of the subjects had university degree. In the only study where this data is available, the percentage of subjects with a university degree or higher is 69% (McCartt et al, 1996). It is likely that other studies have similar discrepancies, given the fact that Portugal is one of the OECD countries with the largest proportion of adults without a secondary diploma (65% in contrast with a OECD average of 25%) and the lowest proportion of adults with tertiary education. Given the correlation found between sleepy driving and educational level, it is also possible that this difference contributes to the lower prevalence of sleepy driving in our sample. It remains unclear why higher education was associated in our sample with increased prevalence of self-reported drowsy driving. The same was reported by McCartt et al (1996) and Nabi et al (2006). The importance of education to the subjective feeling of sleepiness while driving is likely related to multifactorial causes. Even though it may be related to age, retirement status, work related issues (like working schedules pressure and shift working), it is interesting that it comes as an independent value in different studies. Further studies are needed to understand the relationship of literacy with an individual’s perception of sleepiness.
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ACCEPTED MANUSCRIPT Other risk factors for sleepy driving in our sample coincide with previous data from questionnaire studies: sleep deprivation (Abe et al, 2012; McCartt et al, 1996) and subjective feelings of not getting enough sleep (Abe et al, 2012); high ESS scores (Maycock et al, 1997); higher annual mileages (Maycock et al, 1997; McCartt et al,1996; Nabi et al, 2006); young adult drivers and those with fewer years of having a driving license (Maycock et al, 1996; Philip et al,
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2010; McCartt et al, 1996; Nabi et al, 2006). Also, daytime driving between 4-6AM has previously been associated with drowsy driving and an increased risk of sleep-related crashes (Akerstedt and Kecklund, 2001). According to our study, sleep-related crashes have a reported annual percentage of 0.67%, as was the case in other studies (Sagaspe et al 2010; Philip et al, 2010, Philips and Sagberg, 2013), despite the lower percentage of self-reported sleepy driving. The reported incidence of sleeprelated near-miss crashes was smaller (2.1%) than in the few studies analyzing this: 5%-15% of the French drivers, in the previous year (Sagaspe et al, 2010; Philip et al 2010). In our sample, falling asleep while driving was the only variable associated with sleep-related crashes and near misses. If we evaluate this behavior as evidence of “severe sleepiness”, this result coincides with previous data (Sagaspe et al, 2010; Philip et al, 2010; Connor et al, 2002; Papadakakia et al, 2008; Gander et al, 2005; Maycock et al, 1997). Also, in our study, as well as in other studies, near-miss crashes were associated with an increased risk of sleep-related crashes (Powel et al, 2007; Sagaspe et al, 2010). The similarity between the reported frequencies of sleep related car crashes in different countries might be related to lesser recall bias of this more serious event. Alternatively, it may indicate that other variables, besides the reported sleepiness while driving, are involved in the sleep related
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ACCEPTED MANUSCRIPT crashes. In line with this hypothesis, it is relevant to analyze the striking lack of sensitivity of the models constructed in multivariate analysis. For near misses and crashes, it can be argued that this arises from the small frequency of these events, accounting for a small statistical power. However, the same is not true for sleepiness at the wheel. An explanation for this may be that our study relies upon retrospective analysis of subjective feelings. This kind of analysis is subject to
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very frequent reporting bias. It has also been previously acknowledged that subjects are not always aware of their sleepiness in general situations but even more so while driving. They recognize sleepiness at the time but have poor recollection of these events (Reyner & Horne, 1998). It is therefore possible that subjects cannot correctly classify themselves as sleepy and non-sleepy drivers. Another possible explanation for the lack of predictive value of the multivariate models comes from the fact that sleepiness frequently has multifactorial causes. It is most likely that a combination of factors including behavioural/clinical/driving related contexts is responsible for a driver’s feeling of sleepiness in a given moment. It is also dependent upon specific sleep-related data of the night predating the occurrence (sleep time, sleep quality, time since last sleep period, etc.). Also details of the road trip such as duration, type of road and driver motivation are relevant factors. Previous studies have shown, for instance, that the driver’s acute sleepiness prior to the accident is correlated to the likelihood of sleep-related accidents (Connor et al. (2002). The number of hours slept the previous night (Connor et al. (2002) and the amount of previous wakefulness (Stutts et al, 2003) are important contributors towards sleep-related crashes. Another important variable not assessed in our questionnaire was the perceived sleep debt, previously associated with an increased risk of sleep-related crashes (Carter et al, 2003). It is relevant to note that insomnia complaints were not specifically addressed; they have
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ACCEPTED MANUSCRIPT previously been associated with an increased risk of accidents (Philip et al, 2010). The retrospective nature of this study does not permit the analysis of the co-occurrence of these different situations. It is also important to acknowledge that the number of severe sleep-related crashes might also be underrepresented in this type of epidemiological surveys due to death or severe injury of subjects that experienced these accidents.
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Looking at the countermeasures subjects reported, it is interesting to note that, as in other studies (Maycock et al, 1997; McCartt et al, 1996) the majority of the subjects continued to drive and did not sleep, despite sleepiness, an indication of the lack of knowledge in the general population regarding the risks of sleepiness while driving and effective countermeasures. In our study, young drivers with fewer years of driving license, known to be at greater risk of sleep–related crashes, were more frequently using inadequate counter measures, as previously reported (Anun et al, 2008). Limitations to this inquiry include the absence of characterization of the context (long vs short trip; driving alone or with other passengers) and the degree of sleepiness (severe with dozing off vs subjective sleepiness). This study has other important limitations. The most important one is that it relies on self and retrospective reports that may be subject to reporting bias, specially concerning driving habits and health related issues. Secondly, the small percentage of crashes and near misses reported renders the multivariate analysis of this sub-sample less reliable. It is also important to acknowledge that information regarding other comorbidities and medications, known to have an effect on self-reported sleepiness, was not collected. Conclusion This epidemiological study conducted in a representative sample of Portuguese drivers
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ACCEPTED MANUSCRIPT demonstrates that sleepy driving and sleep related car crashes are a global phenomenon. However, our data also emphasizes the differences between the reported prevalence of sleepy driving, sleep-related crashes and near-misses between countries. Cultural, environmental, occupational and lifestyle differences as well as different road safety strategies may be involved in variations between countries. In the future it is important that different studies share common
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methodologies, in order to make regional comparisons meaningful. This work was supported with grants from Colunex®, Praxair® and Volkswagen®
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ACCEPTED MANUSCRIPT References 1. Abe T, Komada Y, Inoue Y. Short Sleep Duration, Snoring and Subjective Sleep Insufficiency Are Independent Factors Associated with both Falling Asleep and Feeling Sleepiness while Driving. Intern. Med.. 2012; 51: 3253-3260 2. Akerstedt T, Kecklund G. Age, Gender And Early Morning Highway Accidents. J. Sleep
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ACCEPTED MANUSCRIPT J. Sleep disorders and accidental risk in a large group of regular registered highway drivers. Sleep Med. 2010; 11:973–979 18. Phillips RO, Sagberg F. Road accidents caused by sleepy drivers: Update of a Norwegian survey. Accid. Anal. Prev. 2013; 50:38–146 19. PORDATA statistical database for Portugal www.pordata.pt. Accessed in November
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2013 20. Powell NB, Schechtman KB, Riley RW, Guilleminault C, Ping-Ying Chiang R, Weaver EM. Sleepy Driver Near-Misses May Predict Accident Risks. Sleep. 2007; 30(3):331-342 21. Reyner LA, Horne JA. Falling asleep whilst driving: are drivers aware of prior sleepiness?. Int. J. Legal Med. 1998; 111(3):120-3. 22. Sagaspe P, Taillard J, Bayon V, Lagarde E, Moore N, Boussuge J, Chaumet G, Bioulac B, Philip P. Sleepiness, near-misses and driving accidents among a representative population of french drivers. J. Sleep Res. 2010; 19:578–584 23. Sagberg F. Road accidents caused by drivers falling asleep. Accid. Anal. Prev. 1999; 31:639–649 24. Santos CR, 2001. Avaliação da sonolência diurna excessiva: Adaptação cultural e linguística da escala de sonolência de Epworth para a população portuguesa. Monografia de licenciatura em neurofisiologia. Escola Superior de Tecnologia do Porto. 25. Stutts JC, Wilkins JW, Scott Osberg J, Vaughn BV. Driver risk factors for sleep-related crashes. Accid. Anal. Prev. 2003; 35(3):321-31. 26. Swanson LM, Drake C, Arnedt JT. Employment and Drowsy Driving: A Survey of American Workers. Behavioral Sleep Medicine. 2012; 10:250–257
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ACCEPTED MANUSCRIPT 27. Vaz AP, Drummond M, Caetano Mota P, Severo M, Almeida J, Winck, JC. Tradução do Questionário de Berlim para língua Portuguesa e sua aplicação na identificação da SAOS
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numa consulta de patologia respiratória do sono. Rev Port Pneumol. 2011;17(2):59-65
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ACCEPTED MANUSCRIPT Table 2 – Univariate analysis for sleepy driving. All variables were plotted in two categories when possible to assure validity of statistical tests. P values for Chi square tests of Fischer exact test (when chi square not valid) results are indicated. *Fisher exact test. BMI – Body mass index; PSQI – Pittsburgh Sleep Quality Index; ESS – Epworth Sleepiness Scale
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Sleepy driving Yes
No
n
%
n
%
14 2
25.9%
406
74.1%
Female
73
20.7%
279
79.3%
≤30 years
74
31.2%
163
68.8%
>30 years
14 1
21.3%
522
78.7%
≤ compulsory education
59
15.9%
311
84.1%
Male Gender
Age
p
0.079
0.003
0.000
Schooling > compulsory education
15 6
29.4%
374
70.6%
No
18 3
22.9%
616
77.1%
Yes
32
31.7%
69
68.3%
No
18 8
22.7%
639
77.3%
27
37.0%
Shift work
Night shift Yes
21
0.051
0.009 46
63.0%
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ACCEPTED MANUSCRIPT Underweight
5
33.3%
10
66.7%
Normal
10 4
24.1%
327
75.9%
Overweight
90
23.6%
292
76.4%
Obese
16
22.2%
56
77.8%
≤1 / week
20 3
23.5%
661
76.5%
>1 / week
12
38.7%
19
61.3%
>5 year
18 7
24.1%
590
75.9%
0-5 year
28
22.8%
95
77.2%
Yes
10 4
28.8%
257
71.2%
No
84
30.7%
190
69.3%
≤15000 Km
58
16.2%
300
83.8%
>15000 Km
13 5
31.8%
290
68.2%
No
11 2
18.5%
492
81.5%
BMI
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Sleep pills
Years of driving license
Professional driver
Km/year
Driving between 0-6 AM
0.051
0.753
0.613
0.000
0.000 Yes
Diagnosed sleep No disorder Yes Total sleep time
-
≤6H
22
10 3
34.8%
193
65.2%
21 0
23.8%
674
5
31.2%
11
76.2% 0.553 * 68.8%
84
31.9%
179
68.1% 0.000
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ACCEPTED MANUSCRIPT
Caffeinated beverages
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Global PSQI Score
>6H
12 9
20.7%
493
79.3%
0-2 /day
13 1
22.2%
460
77.8%
>2 /day
84
27.2%
225
72.8%
Good quality
13 4
23.1%
445
76.9%
Bad Quality
81
25.6%
235
74.4%
≤9
17 5
21.4%
643
78.6%
>10
40
48.8%
42
51.2%
Low risk
18 7
23.1%
623
76.9%
28
31.1%
ESS
Berlin Questionnaire
High risk
23
0.094
0.405
0.000
0.090 62
068.9%
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ACCEPTED MANUSCRIPT Table 4: Univariate analysis for accidents and near-miss car accidents. All variables were plotted in two categories when possible to assure validity of statistical tests. P values for Chi-square test or Fischer exact test (when qui square not valid) results are indicated.
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Accidents + near misses No
Gender
Male
p
Yes
n
%
n
%
128
90.1%
14
9.9
0.950
% Female
66
90.4%
7
9.6 %
Age
≤30 years
65
87.8%
9
12.2
0.392
% >30 years
129
91.5%
12
8.5 %
School
≤9 years
49
83.1%
10
16.9
0.029*
% >9 years
145
92.9%
11
7.1 %
Night shifts
No
169
89.9%
19
10.1
1.000
% Yes
25
92.6%
2
7.4 %
BMI
Underweigh
5
t Normal
100.0
0
% 95
24
91.3%
0.0
-
% 9
8.7
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT % Overweight
81
90.0%
9
10.0 %
Obese
13
81.2%
3
18.8 %
Sleeping pills
≤1/week
185
91.1%
18
8.9
0.099*
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% >1x/week
9
75.0%
3
25.0 %
Years of driving license
0-5 years
>5 years
21
173
75.0%
92.5%
7
14
25.0
0.010*
%
*
7.5 %
Professional driver
No
76
90.5%
8
9.5
0.655
% Yes
96
92.3%
8
7.7 %
Km/year
≤15000
49
84.5%
9
15.5
0.124
% >15000
124
91.9%
11
8.1 %
Driving 0 to 6AM
No
101
90.2%
11
9.8
0.978
% Yes
93
90.3%
10
9.7 %
Sleep disorder
No
191
91.0%
19
9.0
0.076
% Yes
3
25
60.0%
2
40.0
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT % Total sleep time
≤6H
75
89.3%
9
10.7
0.735
% ≥7H
117
90.7%
12
9.3 %
Caffeinated beverages
0-2
121
92.4%
10
7.6
0.188
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% >2
73
86.9%
11
13.1 %
PSQI
Good
126
94.0%
8
quality Bad quality
6.0
0.016*
% 68
84.0%
13
16.0 %
ESS
≤9
156
89.1%
19
10.9
0.380
% ≥10
38
95.0%
2
5.0 %
Berlin questionnaire
Low risk
170
90.9%
17
9.1
0.490
% High risk
24
85.7%
4
14.3 %
Have you ever fallen asleep
No
149
95.5%
7
while driving? Yes
45
76.3%
14
4.5
0.000*
%
*
23.7 %
During last year, have you ever
No
177
94.7%
10
fallen asleep while driving? Yes
17
26
60.7%
11
5.3
0.000*
%
*
39.3
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ACCEPTED MANUSCRIPT % Correct countermeasures for sleepy driving
No
89
86.4%
14
13.6
0.070
% Yes
105
93.8%
7
6.2 %
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** p
Traffic Injury Prevention Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gcpi20
Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers: The importance of epidemiological representative surveys a
b
c
M. Gonçalves , A.R. Peralta , J. Monteiro Ferreira & Christian Guilleminault a
Centro de Medicina do Sono, Hospital Cuf Porto, Porto, Portugal;
b
Santa Maria Hospital, CHLN, EEG/Sleep Lab, Lisboa;
c
Centro de Estudos de Doenças Respiratórias e Alérgicas – Coimbra;
d
d
Stanford University Sleep Disorders Clinic, Stanford, USA Accepted author version posted online: 20 Mar 2015.
Click for updates To cite this article: M. Gonçalves, A.R. Peralta, J. Monteiro Ferreira & Christian Guilleminault (2015): Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers: The importance of epidemiological representative surveys, Traffic Injury Prevention To link to this article: http://dx.doi.org/10.1080/15389588.2015.1013535
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ACCEPTED MANUSCRIPT Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers The importance of epidemiological representative surveys M. Gonçalves1; A.R. Peralta2,5; J. Monteiro Ferreira3; Christian Guilleminault4 1
Centro de Medicina do Sono, Hospital Cuf Porto, Porto, Portugal ;
CHLN, EEG/Sleep Lab, Lisboa;
3
2
Santa Maria Hospital,
Centro de Estudos de Doenças Respiratórias e Alérgicas –
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Coimbra; 4 Stanford University Sleep Disorders Clinic, Stanford, USA Corresponding author: Marta Azevedo Gonçalves Email: [email protected] Centro de Medicina de Sono, Hospital Cuf Porto, Porto, Portugal Number of words: 4966 Number of references: 27 Sleepiness and motor vehicle crashes in a representative sample of Portuguese drivers The importance of epidemiological representative surveys M Gonçalves1; AR Peralta2,5; J Monteiro Ferreira3; C Guilleminault4 1
Centro de Medicina do Sono, Hospital Cuf Porto Portugal;
EEG/Sleep Lab, Lisboa, Portugal
3
2
Santa Maria Hospital, CHLN,
Centro de Estudos de Doenças Respiratórias e Alérgicas –
Coimbra; 4 Stanford University Sleep Disorders Clinic, Stanford, USA Abstract Objective: Sleepiness is considered to be a leading cause of crashes. Despite the huge amount of information collected in questionnaire studies only some are based on representative samples of the population. Specifics of the populations studied hinder the generalization of these previous findings. For the Portuguese population, data from sleep related car crashes/near misses and
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ACCEPTED MANUSCRIPT sleepiness while driving is missing. The objective of this study is to determine the prevalence of near-miss and non-fatal motor-vehicle crashes related to sleepiness in a representative sample of Portuguese drivers. Methods: Structured phone interview regarding sleepiness and sleep related crashes and near-misses, driving habits, demographic data, sleep quality using the Pittsburgh Sleep Quality Index and sleep apnea risk using the Berlin questionnaire. A multivariate
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regression analysis was used to determine the associations with sleepy driving (feeling sleepy or falling asleep while driving) and sleep related near-misses and crashes. Results: 900 subjects, representing the Portuguese population of drivers, were included. 3.1% acknowledged falling asleep while driving during the previous year; 0.67% recalled sleepiness-related crashes. Higher education, driving more than 15000 km/year, driving more frequently between 0 and 6 AM, fewer years of having a drivers license, less total sleep time per night and higher scores on the Epworth Sleepiness Scale (ESS) were all independently associated with sleepy driving. Sleepiness related crashes and near misses were associated only with falling asleep at the wheel in the previous year. Sleep related crashes occurred more frequently in drivers that had also had sleep related near misses. Conclusion: Portugal has lower self-reported sleepiness at the wheel and sleep related near-misses than most other countries where epidemiological data is available. Different population characteristics, cultural, social and road safety specificities may be involved in these discrepancies. Despite this, Portuguese drivers report sleep related crashes in frequencies similar to drivers in other countries.
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ACCEPTED MANUSCRIPT Introduction Sleepiness contributes to car crashes, though this contribution varies widely depending on the methodology used to study it. Studies analyzing car crash databases underestimate the importance of sleepiness because the authorities attribute accidents to more visible causes. Surveys conducted on crash survivors retrospectively analyzing their pre-accident sleepiness are
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limited to crashes severe enough to require police/insurance involvement.
In these cases,
sleepiness-related near-misses and minor crashes are very frequent (Klauer et al, 2006). Questionnaires applied to regular drivers may overcome these limitations. There is a large amount of data concerning this subject. Surveys have been conducted in representative samples of the population (Sagaspe et al, 2010 - France; National Sleep Foundation (NSF) surveys - US; Traffic Injury Research Foundation (TIRF) surveys - Canada; Papadakakia et al, 2008 - Greece; Gander et al, 2005 - Australia; Maycock et al, 1997 – UK.) or in non representative samples (Phillips and Sagberg, 2012; Sagberg et al, 1999; Stutts et al, 2003; Philip et al, 2010; Hanning and Welsh, 1996; Gander et al, 2005). Direct comparisons of these studies across various countries is difficult given the difference in variables collected, time frames, lack of a standardized definition for sleepy driving and populations studied. In the US, 64% of the drivers acknowledged feeling sleepy while driving the previous year (NSF’s poll 2008; Swanson et al, 2011) and 29%-35% said they had fallen asleep while driving at least once (NSF’s poll 2011; Garder and Alexander, 1995; NSF’s poll 2008; Swanson et al, 2012). Similar figures were reported in a representative survey of New York state drivers (McCartt et al, 1996). The TIRF surveys in Canada also reported rates as high as 38.9% of nodding off while driving. In France, the reported prevalence of severe sleepiness while driving
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ACCEPTED MANUSCRIPT (i.e. requiring cessation of driving) in the previous year varied from 28.2% (Nabi et al, 2006), 36% (Sagaspe et al., 2010) and 57.3% (Philip et al, 2010). In the UK, severe sleepiness also occurred in 29% of the drivers in the previous year (Maycock et al, 1997). In Tokyo 11.4%20.3% of the drivers recalled nodding off and 40.4-67.7% recalled any kind of sleepiness at the wheel in the previous year (Abe et al, 2012, Komada et al, 2010). An overall average shows that
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severe sleepiness and nodding off at the wheel is reported by about 1/4 to 1/3 of drivers in one year. There are, however, conflicting results. A Norwegian survey of drivers involved in crashes, reported that only 8.3% of the not-at-fault drivers acknowledged falling asleep while driving in the previous year (Sagberg et al, 1999). In a recent update, this percentage decreased even further to 2.9 % (Phillips et al, 2013). Despite the different population, this study seems to indicate lower prevalence of severe sleepiness at the wheel in Norway. The prevalence of sleep-related crashes varies more widely. In the US, NSF’s polls have shown a prevalence of 2% for all drivers (NSF poll 2008, Swanson et al, 2011), 1% of non-professionals and 1-6% of professional drivers (NSF’s poll 2011) in one year. Smaller prevalence (0.2%-0.4%) was reported in France (Sagaspe et al, 2010; Philip et al, 2010) and higher prevalence (10,4%) in Tokyo (Komada et al, 2010). As can be concluded from this review of the available data, the generalization of the reported frequencies of sleep related car-crashes/near misses and sleepy driving is not possible. Besides varying methodologies in the different studies, different populations and road/traffic rules from the different countries studied may be responsible for the disparities found. A more detailed mapping of this problem may shed some light in to the factors that contribute to this important public health issue.
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ACCEPTED MANUSCRIPT In Portugal it is not known what is the frequency of sleep related car-crashes/near misses and sleepy driving. The primary objective of this study was to determine the annual frequency of sleepiness while driving, near-misses and motor-vehicle accidents related to sleepiness in a representative sample of Portuguese drivers. We also looked for possible demographic, driving and sleep-related correlations of these variables. Finally, we investigated which measures motor-
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vehicle drivers took when feeling sleepy at the wheel. Methods A - Selection of subjects The report from the National Institute of Statistics in 2006, based on a 2001 census, indicates 60% of the general population had driver’s license (about 6 million drivers). A sample size of 900 subjects was calculated to have a confidence interval of 3%, (confidence level 95%) assuming a prevalence of sleepy driving at around 30%. “Regular drivers” were defined as subjects who drove vehicles at least once per week. The selection of subjects was made through stratified sampling with replacement taking into consideration age, gender, and geographic distribution of the population (region and rural/urban dwelling). Trained interviewers conducted phone interviews. Phone numbers were selected at random, including both landline and mobile phones. Subjects were informed of confidentiality and oral informed consent was obtained. Given the nature of this survey, specific ethics approval was not necessary. B – The Instrument The questionnaire was conducted over the phone by trained interviewers. The core questions were: 1)“During the past year, have you ever driven while feeling sleepy?” 2)“During last year, have you ever fallen asleep while driving?”. Drivers that experienced sleepiness were asked to
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ACCEPTED MANUSCRIPT recall crashes and near-misses related to sleepiness that occurred over the previous year as well as sleepiness counter-measures that they used that time. Accidents were characterized by location type (city, highway, country roads). Countermeasures included opening of the car window, increasing radio volume, setting the air conditioning to cold, drinking caffeinated beverages or water, eating, stopping to rest, stopping to sleep, other behavioural activities or no
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behavioural change. Subjects were given a list and asked to rank the countermeasures from most frequent to least frequent. No limit was set for subject’s responses. For analysis purposes, the preferred measure referred by each subject was selected. For multivariate analysis purposes, a variable named “sleepy driving” was defined to include all subjects that answered yes either to the question related to driving while sleepy or to the question regarding falling asleep at the wheel. In this variable, both feeling sleepy, without any specific severity grading, and falling asleep/dozing off, were analysed together. Also, the variable “accidents and near misses” was defined to include all subjects that answered yes either to the question regarding having previously experienced near-misses or to the question regarding having previously experienced accidents related to sleepiness. The questionnaire also included: 1. Demographic, social and medical information: age; gender; marital status; yearly income; general occupational categories; education (illiterate; 4 years; 6 years; 9 years; 12 years; university; >university); shift work (yes/no), type of shifts (day, night, or both); weight; height; diagnosed sleep disorder (sleep apnea, other); intake of sleeping pills; known chronic illness; habitual daily intake of caffeinated beverages; habitat (city versus country dwelling) and specific geographic location.
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ACCEPTED MANUSCRIPT 2. Driving habits: amount of driving in Km/year (0-5000; 5000-15000; 15000-25000; 2500040000;>40000); percentage of driving between midnight and 6AM; professional driving (yes/no). No specific definition of professional driving was provided and the subjects could interpret this question as having to drive as part of their work. 3. Epworth Sleepiness Scale (ESS) (Santos C.R., 2001) to determine chronic daytime
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sleepiness (sleepiness was defined as a score ≥10) 4. Berlin questionnaire (Vaz et al, 2011) to categorize the likelihood of having sleep apnea. 3. Pittsburgh Sleep Quality Index (PSQI), used to determine sleep quality (cut off ≥5 was used for “bad sleep quality”). The Portuguese version, currently being validated, was used. (Marques at al, 2013). Statistical analyses Descriptive statistics were used to characterize the samples studied. Continuous variables analysed were: age, BMI, years of having one’s driver’s license, percentage of time driving between 0 and 6 AM, number of caffeinated beverages/day, ESS and PSQI. Categorical variables analysed were: gender; education level (analysed according to legal school years in Portugal as ≥9 and 2 (mean of the population studied); Km driven/year: ≤15000 and >15000; diagnosed sleep disorder; intake of sleeping pills: ≤1/week and >1/week (middle category inquired); excessive daytime sleepiness (ESS≥10); Berlin questionnaire (high risk /low risk); Age: ≤ 30 years and >30 years old; BMI: underweight, normal, overweight and obese.
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ACCEPTED MANUSCRIPT Univariate analysis using Pearson Chi-square (or, when appropriate, Fisher exact test) was performed to look for associations between the variables collected and sleepy driving and crashes/near-misses. Sleepy driving was studied in all subjects. Accidents and near misses were analysed within the subgroup that answered yes to the question regarding ever-experiencing sleepiness while driving. For countermeasures analysis, a variable named “effective
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countermeasures” was constructed that included subjects that described first countermeasures as stopping the car, sleeping or drinking coffee (De Valck E & Cluydts 2001; Philip et al, 2006; Reyner & Horne 1996, 1997). For regression analysis, only variables with significant association in univariate analysis (p10 remained as independent factors explaining sleepy drivers, albeit with small odds ratio.
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Near-misses and accidents In the entire population studied, 19 (2.1%) of the subjects reported a near-miss motor vehicle accident due to sleepiness within the last year and 0.67% recalled a traffic accident due to sleepiness during the same period. Among the subgroup sleepy drivers, near-miss crashes were reported by 8.83% of subjects and sleep-related crashes occurred in 2.8%. From the six subjects that recalled sleep-related crashes, two reported three accidents in the preceding year. Five accidents occurred from 00:00-06:00 AM, four accidents occurred from 12:00-18:00 PM and only one occurred between 18:00 PM and 00:00 AM. Most of the accidents occurred on secondary roads (either in or outside the city) and only one accident occurred on the highway. Factors associated with sleep-related crashes and near-misses can be found in table 4. With multiple regression (table A5 in the appendix), the only variable that remained as an independent factor associated with sleepiness-related accidents and near-misses was having ever fallen asleep while driving. Evaluation of countermeasures Overall, 44% of these drivers stopped to rest, 1.9% napped and 54.1% continued driving and used different strategies to counteract sleepiness. The preferred countermeasures employed by
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ACCEPTED MANUSCRIPT drivers while driving sleepy are listed in graph A1 of the appendix. Subjects having a driver’s license for more years, older subjects and males were more likely to use adequate counter measures i.e. stopping to sleep, stopping to take a rest or drinking caffeine beverages. Subjects reporting previous near-miss accidents were also less likely to choose effective countermeasures (Table A6 in the apendix).
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Discussion This is the first study focusing on sleepiness, sleep-related near-misses and accidents in a representative sample population of Portuguese drivers. We found that about 1/4 of the Portuguese population of drivers reported driving sleepy at least once during the previous year and 3.1% had fallen asleep while driving. These findings indicate that Portuguese drivers report less sleepiness while driving than other populations previously studied using similar methodologies (Sagaspe et al, 2010; Philip et al, 2010; NSF and TIRF polls; Maycock et al, 1997, McCartt et al, 1996; Abe et al, 2012; Komada et al, 2010; Garder and Alexander, 1995; Nabi et al, 2006). The reported prevalence of nodding off while driving is similar to the lower figures encountered in Norway (Philips et al, 2013). These results confirm that the prevalence of feeling sleepy while driving varies between countries. These differences may be related to factors related to the type of questions posed in the survey and to special characteristics of the population analyzed. It is relevant to analyse the way the questions were formulated. First, in our study, sleepiness was not defined in terms of severity. In the Portuguese there are several ways to describe sleepiness. It is possible that the question formulated was interpreted as having connotations towards a more severe form of sleepiness. When compared to other surveys (p.e. Sagaspe et al, 2010; Maycock
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ACCEPTED MANUSCRIPT et al, 1997), the prevalence of sleepy driving in our study approaches the prevalence of severe sleepiness (defined as sleepiness so severe as I could easily fall asleep or so severe as to require stopping the car). The formulation of the question is also relevant in Portuguese when analysing the response to the question of falling asleep. It is interesting to note that slightly different formulations of the same question namely the one used as our primary question (“During last
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year, have you ever fallen asleep while driving?”) and the one used during ESS (“How likely are you to doze off or fall asleep in the car, while stopping for few minutes in traffic?”) led to different reported numbers of sleeping while driving. For the first question, 3.1% answered yes, compared to 6% for the last question. Regardless, even this number is below the usual reported prevalence of nodding off while driving, which approaches 25-30%. It is unlikely that potential liability may have prevented drivers from acknowledging their sleepy driving. In Portugal there is no specific legislation regarding this issue, the questionnaire was anonymous and conducted by entities known to the drivers to be independent from law enforcement. It is difficult to compare the characteristics of the population studied in other countries with the Portuguese sample, as most of the analysed variables are not reported in other studies. Here we show a preponderance of male drivers and a fairly even representation of most age groups similar to most other studies (Sagaspe et al, 2010; Philip et al, 2010; Abe et al, 2012; Nabi et al, 2006; Swanson et al, 2012). Our subjects had a very small percentage of diagnosed sleep disorders (1.8%) when compared to the study by Philip et al (2010) where 27.8% of the subjects reported sleep disorders. However, despite the small prevalence of diagnosed sleep disorders, 10% of our sample had a high probability of sleep apnea according to the Berlin questionnaire, and 45% had bad sleep quality on the PSQI. This suggests that sleep disorders may be under-
11
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ACCEPTED MANUSCRIPT diagnosed in our group. Another important difference is that our population has a high percentage of drivers only driving 0-5000 Km per year (29%) when comparing to other studies (Sagaspe et al, 2010; Philip et al, 2010; Nabi et al, 2006) and trips in Portugal are usually short (it is possible to drive from the northern end to the southern border in about 6 hours). Reduced driving exposure and shorter trips in our group may have contributed to the smaller prevalence of
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drowsy driving. Another important difference between our sample and other samples is the literacy status in Portugal. In 2009, only 15.3% of the population had a university degree and 4.1% were illiterate (PORDATA). In our sample, only 26.6% of the subjects had university degree. In the only study where this data is available, the percentage of subjects with a university degree or higher is 69% (McCartt et al, 1996). It is likely that other studies have similar discrepancies, given the fact that Portugal is one of the OECD countries with the largest proportion of adults without a secondary diploma (65% in contrast with a OECD average of 25%) and the lowest proportion of adults with tertiary education. Given the correlation found between sleepy driving and educational level, it is also possible that this difference contributes to the lower prevalence of sleepy driving in our sample. It remains unclear why higher education was associated in our sample with increased prevalence of self-reported drowsy driving. The same was reported by McCartt et al (1996) and Nabi et al (2006). The importance of education to the subjective feeling of sleepiness while driving is likely related to multifactorial causes. Even though it may be related to age, retirement status, work related issues (like working schedules pressure and shift working), it is interesting that it comes as an independent value in different studies. Further studies are needed to understand the relationship of literacy with an individual’s perception of sleepiness.
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ACCEPTED MANUSCRIPT Other risk factors for sleepy driving in our sample coincide with previous data from questionnaire studies: sleep deprivation (Abe et al, 2012; McCartt et al, 1996) and subjective feelings of not getting enough sleep (Abe et al, 2012); high ESS scores (Maycock et al, 1997); higher annual mileages (Maycock et al, 1997; McCartt et al,1996; Nabi et al, 2006); young adult drivers and those with fewer years of having a driving license (Maycock et al, 1996; Philip et al,
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2010; McCartt et al, 1996; Nabi et al, 2006). Also, daytime driving between 4-6AM has previously been associated with drowsy driving and an increased risk of sleep-related crashes (Akerstedt and Kecklund, 2001). According to our study, sleep-related crashes have a reported annual percentage of 0.67%, as was the case in other studies (Sagaspe et al 2010; Philip et al, 2010, Philips and Sagberg, 2013), despite the lower percentage of self-reported sleepy driving. The reported incidence of sleeprelated near-miss crashes was smaller (2.1%) than in the few studies analyzing this: 5%-15% of the French drivers, in the previous year (Sagaspe et al, 2010; Philip et al 2010). In our sample, falling asleep while driving was the only variable associated with sleep-related crashes and near misses. If we evaluate this behavior as evidence of “severe sleepiness”, this result coincides with previous data (Sagaspe et al, 2010; Philip et al, 2010; Connor et al, 2002; Papadakakia et al, 2008; Gander et al, 2005; Maycock et al, 1997). Also, in our study, as well as in other studies, near-miss crashes were associated with an increased risk of sleep-related crashes (Powel et al, 2007; Sagaspe et al, 2010). The similarity between the reported frequencies of sleep related car crashes in different countries might be related to lesser recall bias of this more serious event. Alternatively, it may indicate that other variables, besides the reported sleepiness while driving, are involved in the sleep related
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ACCEPTED MANUSCRIPT crashes. In line with this hypothesis, it is relevant to analyze the striking lack of sensitivity of the models constructed in multivariate analysis. For near misses and crashes, it can be argued that this arises from the small frequency of these events, accounting for a small statistical power. However, the same is not true for sleepiness at the wheel. An explanation for this may be that our study relies upon retrospective analysis of subjective feelings. This kind of analysis is subject to
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very frequent reporting bias. It has also been previously acknowledged that subjects are not always aware of their sleepiness in general situations but even more so while driving. They recognize sleepiness at the time but have poor recollection of these events (Reyner & Horne, 1998). It is therefore possible that subjects cannot correctly classify themselves as sleepy and non-sleepy drivers. Another possible explanation for the lack of predictive value of the multivariate models comes from the fact that sleepiness frequently has multifactorial causes. It is most likely that a combination of factors including behavioural/clinical/driving related contexts is responsible for a driver’s feeling of sleepiness in a given moment. It is also dependent upon specific sleep-related data of the night predating the occurrence (sleep time, sleep quality, time since last sleep period, etc.). Also details of the road trip such as duration, type of road and driver motivation are relevant factors. Previous studies have shown, for instance, that the driver’s acute sleepiness prior to the accident is correlated to the likelihood of sleep-related accidents (Connor et al. (2002). The number of hours slept the previous night (Connor et al. (2002) and the amount of previous wakefulness (Stutts et al, 2003) are important contributors towards sleep-related crashes. Another important variable not assessed in our questionnaire was the perceived sleep debt, previously associated with an increased risk of sleep-related crashes (Carter et al, 2003). It is relevant to note that insomnia complaints were not specifically addressed; they have
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ACCEPTED MANUSCRIPT previously been associated with an increased risk of accidents (Philip et al, 2010). The retrospective nature of this study does not permit the analysis of the co-occurrence of these different situations. It is also important to acknowledge that the number of severe sleep-related crashes might also be underrepresented in this type of epidemiological surveys due to death or severe injury of subjects that experienced these accidents.
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Looking at the countermeasures subjects reported, it is interesting to note that, as in other studies (Maycock et al, 1997; McCartt et al, 1996) the majority of the subjects continued to drive and did not sleep, despite sleepiness, an indication of the lack of knowledge in the general population regarding the risks of sleepiness while driving and effective countermeasures. In our study, young drivers with fewer years of driving license, known to be at greater risk of sleep–related crashes, were more frequently using inadequate counter measures, as previously reported (Anun et al, 2008). Limitations to this inquiry include the absence of characterization of the context (long vs short trip; driving alone or with other passengers) and the degree of sleepiness (severe with dozing off vs subjective sleepiness). This study has other important limitations. The most important one is that it relies on self and retrospective reports that may be subject to reporting bias, specially concerning driving habits and health related issues. Secondly, the small percentage of crashes and near misses reported renders the multivariate analysis of this sub-sample less reliable. It is also important to acknowledge that information regarding other comorbidities and medications, known to have an effect on self-reported sleepiness, was not collected. Conclusion This epidemiological study conducted in a representative sample of Portuguese drivers
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ACCEPTED MANUSCRIPT demonstrates that sleepy driving and sleep related car crashes are a global phenomenon. However, our data also emphasizes the differences between the reported prevalence of sleepy driving, sleep-related crashes and near-misses between countries. Cultural, environmental, occupational and lifestyle differences as well as different road safety strategies may be involved in variations between countries. In the future it is important that different studies share common
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methodologies, in order to make regional comparisons meaningful. This work was supported with grants from Colunex®, Praxair® and Volkswagen®
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ACCEPTED MANUSCRIPT References 1. Abe T, Komada Y, Inoue Y. Short Sleep Duration, Snoring and Subjective Sleep Insufficiency Are Independent Factors Associated with both Falling Asleep and Feeling Sleepiness while Driving. Intern. Med.. 2012; 51: 3253-3260 2. Akerstedt T, Kecklund G. Age, Gender And Early Morning Highway Accidents. J. Sleep
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ACCEPTED MANUSCRIPT 9. Hanning CD, Welsh M. Sleepiness, snoring and driving habits. J. Sleep Res.1996; 5(1):51-4. 10. Gander PH, Marshall NS, Harris RB, Reid P. Sleep, sleepiness and motor vehicle accidents: a national survey. Aust. N. Z. J. Public Health. 2005; 29:16-21 11. Klauer SG, Dingus TA, Neale VL, Sudweeks JD, Ramsey DJ. The Impact of Driver
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Inattention On Near-Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study Data. National Highway Traffic Safety Administration, DOT HS 810 594, 2006 12. Komada Y, Shiomi T, Mishima K, Inoue Y. Nihon Koshu Eisei Zasshi. [Associated factors for drowsy driving among licensed drivers]. Nihon Koshu Eisei Zasshi. 2010; 57(12):1066-74 [Article in Japanese] 13. Maycock, G. Sleepiness and driving: the experience of U.K. car drivers. Accid. Anal. Prev. 1997; 29 (4):453-462. 14. Mccartt A, Ribner S, Pack A, Mark S, Hammer C. The scope and nature of the drowsy driving problem in New York State. Accid. Anal. Prev. 1996; 28(4):511-517 15. Nabi H, Guéguen A, Chiron M, Lafont S, Zins M, Lagarde E. Awareness of driving while sleepy and road traffic accidents: prospective study in GAZEL cohort. BMJ. 2006; 333(75558):53-4 16. Papadakakia M, Tzamaloukaa G, Darviric C, Chliaoutakis J. Exploring the effects of lifestyle, sleep factors and driving behaviors on sleep-related road risk: A study of Greek drivers. Accid. Anal. Prev. 2008; 40(6):2029–2036 17. Philip P, Sagaspe P, Lagarde E, Leger D, Ohayon MM, Bioulac B, Boussuge J, Taillard
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ACCEPTED MANUSCRIPT J. Sleep disorders and accidental risk in a large group of regular registered highway drivers. Sleep Med. 2010; 11:973–979 18. Phillips RO, Sagberg F. Road accidents caused by sleepy drivers: Update of a Norwegian survey. Accid. Anal. Prev. 2013; 50:38–146 19. PORDATA statistical database for Portugal www.pordata.pt. Accessed in November
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2013 20. Powell NB, Schechtman KB, Riley RW, Guilleminault C, Ping-Ying Chiang R, Weaver EM. Sleepy Driver Near-Misses May Predict Accident Risks. Sleep. 2007; 30(3):331-342 21. Reyner LA, Horne JA. Falling asleep whilst driving: are drivers aware of prior sleepiness?. Int. J. Legal Med. 1998; 111(3):120-3. 22. Sagaspe P, Taillard J, Bayon V, Lagarde E, Moore N, Boussuge J, Chaumet G, Bioulac B, Philip P. Sleepiness, near-misses and driving accidents among a representative population of french drivers. J. Sleep Res. 2010; 19:578–584 23. Sagberg F. Road accidents caused by drivers falling asleep. Accid. Anal. Prev. 1999; 31:639–649 24. Santos CR, 2001. Avaliação da sonolência diurna excessiva: Adaptação cultural e linguística da escala de sonolência de Epworth para a população portuguesa. Monografia de licenciatura em neurofisiologia. Escola Superior de Tecnologia do Porto. 25. Stutts JC, Wilkins JW, Scott Osberg J, Vaughn BV. Driver risk factors for sleep-related crashes. Accid. Anal. Prev. 2003; 35(3):321-31. 26. Swanson LM, Drake C, Arnedt JT. Employment and Drowsy Driving: A Survey of American Workers. Behavioral Sleep Medicine. 2012; 10:250–257
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ACCEPTED MANUSCRIPT 27. Vaz AP, Drummond M, Caetano Mota P, Severo M, Almeida J, Winck, JC. Tradução do Questionário de Berlim para língua Portuguesa e sua aplicação na identificação da SAOS
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numa consulta de patologia respiratória do sono. Rev Port Pneumol. 2011;17(2):59-65
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ACCEPTED MANUSCRIPT Table 2 – Univariate analysis for sleepy driving. All variables were plotted in two categories when possible to assure validity of statistical tests. P values for Chi square tests of Fischer exact test (when chi square not valid) results are indicated. *Fisher exact test. BMI – Body mass index; PSQI – Pittsburgh Sleep Quality Index; ESS – Epworth Sleepiness Scale
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Sleepy driving Yes
No
n
%
n
%
14 2
25.9%
406
74.1%
Female
73
20.7%
279
79.3%
≤30 years
74
31.2%
163
68.8%
>30 years
14 1
21.3%
522
78.7%
≤ compulsory education
59
15.9%
311
84.1%
Male Gender
Age
p
0.079
0.003
0.000
Schooling > compulsory education
15 6
29.4%
374
70.6%
No
18 3
22.9%
616
77.1%
Yes
32
31.7%
69
68.3%
No
18 8
22.7%
639
77.3%
27
37.0%
Shift work
Night shift Yes
21
0.051
0.009 46
63.0%
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ACCEPTED MANUSCRIPT Underweight
5
33.3%
10
66.7%
Normal
10 4
24.1%
327
75.9%
Overweight
90
23.6%
292
76.4%
Obese
16
22.2%
56
77.8%
≤1 / week
20 3
23.5%
661
76.5%
>1 / week
12
38.7%
19
61.3%
>5 year
18 7
24.1%
590
75.9%
0-5 year
28
22.8%
95
77.2%
Yes
10 4
28.8%
257
71.2%
No
84
30.7%
190
69.3%
≤15000 Km
58
16.2%
300
83.8%
>15000 Km
13 5
31.8%
290
68.2%
No
11 2
18.5%
492
81.5%
BMI
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Sleep pills
Years of driving license
Professional driver
Km/year
Driving between 0-6 AM
0.051
0.753
0.613
0.000
0.000 Yes
Diagnosed sleep No disorder Yes Total sleep time
-
≤6H
22
10 3
34.8%
193
65.2%
21 0
23.8%
674
5
31.2%
11
76.2% 0.553 * 68.8%
84
31.9%
179
68.1% 0.000
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Caffeinated beverages
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Global PSQI Score
>6H
12 9
20.7%
493
79.3%
0-2 /day
13 1
22.2%
460
77.8%
>2 /day
84
27.2%
225
72.8%
Good quality
13 4
23.1%
445
76.9%
Bad Quality
81
25.6%
235
74.4%
≤9
17 5
21.4%
643
78.6%
>10
40
48.8%
42
51.2%
Low risk
18 7
23.1%
623
76.9%
28
31.1%
ESS
Berlin Questionnaire
High risk
23
0.094
0.405
0.000
0.090 62
068.9%
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ACCEPTED MANUSCRIPT Table 4: Univariate analysis for accidents and near-miss car accidents. All variables were plotted in two categories when possible to assure validity of statistical tests. P values for Chi-square test or Fischer exact test (when qui square not valid) results are indicated.
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Accidents + near misses No
Gender
Male
p
Yes
n
%
n
%
128
90.1%
14
9.9
0.950
% Female
66
90.4%
7
9.6 %
Age
≤30 years
65
87.8%
9
12.2
0.392
% >30 years
129
91.5%
12
8.5 %
School
≤9 years
49
83.1%
10
16.9
0.029*
% >9 years
145
92.9%
11
7.1 %
Night shifts
No
169
89.9%
19
10.1
1.000
% Yes
25
92.6%
2
7.4 %
BMI
Underweigh
5
t Normal
100.0
0
% 95
24
91.3%
0.0
-
% 9
8.7
ACCEPTED MANUSCRIPT
ACCEPTED MANUSCRIPT % Overweight
81
90.0%
9
10.0 %
Obese
13
81.2%
3
18.8 %
Sleeping pills
≤1/week
185
91.1%
18
8.9
0.099*
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% >1x/week
9
75.0%
3
25.0 %
Years of driving license
0-5 years
>5 years
21
173
75.0%
92.5%
7
14
25.0
0.010*
%
*
7.5 %
Professional driver
No
76
90.5%
8
9.5
0.655
% Yes
96
92.3%
8
7.7 %
Km/year
≤15000
49
84.5%
9
15.5
0.124
% >15000
124
91.9%
11
8.1 %
Driving 0 to 6AM
No
101
90.2%
11
9.8
0.978
% Yes
93
90.3%
10
9.7 %
Sleep disorder
No
191
91.0%
19
9.0
0.076
% Yes
3
25
60.0%
2
40.0
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ACCEPTED MANUSCRIPT % Total sleep time
≤6H
75
89.3%
9
10.7
0.735
% ≥7H
117
90.7%
12
9.3 %
Caffeinated beverages
0-2
121
92.4%
10
7.6
0.188
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% >2
73
86.9%
11
13.1 %
PSQI
Good
126
94.0%
8
quality Bad quality
6.0
0.016*
% 68
84.0%
13
16.0 %
ESS
≤9
156
89.1%
19
10.9
0.380
% ≥10
38
95.0%
2
5.0 %
Berlin questionnaire
Low risk
170
90.9%
17
9.1
0.490
% High risk
24
85.7%
4
14.3 %
Have you ever fallen asleep
No
149
95.5%
7
while driving? Yes
45
76.3%
14
4.5
0.000*
%
*
23.7 %
During last year, have you ever
No
177
94.7%
10
fallen asleep while driving? Yes
17
26
60.7%
11
5.3
0.000*
%
*
39.3
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ACCEPTED MANUSCRIPT % Correct countermeasures for sleepy driving
No
89
86.4%
14
13.6
0.070
% Yes
105
93.8%
7
6.2 %
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** p
