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Changes in Japanese sleep duration and percentage of people staying awake past 11:00 PM. This figure shows the percentage of Japanese people who stay awake past 11:00 PM on weekdays and the average subjective total sleep time from 1960 to 2010. In 1960, 90% of the population were already asleep at 11:00 PM and typically slept for over 8 h. However, sleeping times gradually fell over the surveyed period. In 2010, half of the population remained awake past 11:00 PM with an average sleeping time of 7 h and 14 min. Created by the NHK National Time Life Survey.
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Sleepiness is an important factor in traffic accidents caused by human error. The purpose of this paper is to review a number of studies conducted over the years regarding the effect of the lack of sleep on the incidence of traffic accidents as well as the individual effects of various sleep disorders on accidents. In addition, we discuss recent ad...
Context in source publication
Context 1
... PM and slept for an average of more than 8 h, but the number of people active late at night has gradually risen, resulting in shorter sleeping times. In 2010, half of the population was still awake at 11:00 PM and the mean sleeping time was only 7 h and 14 min, suggesting a reduction of around 1 h of sleeping time compared with 40 years ago [4] (Fig. 1). In a study conducted on the general population (n = 12,000) in Finland, 20.4% of participants were found to have insufficient sleep [5], while a study of 4000 adult subjects in Japan revealed that 28% had fewer than 6 h of sleep each night [6]. Thus, there appears to be a high rate of insufficient sleep in developed countries. Of ...
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Citations
... These include inhibitory control, working memory, task switching, and psychomotor vigilance [21]. Disrupted sleep can also lead to an increased number of accidents due to an increase in daytime sleepiness [22]. ...
Background: This study investigates the intricate interplay between disrupted circadian rhythms, sleep variations, and gut microbiota dynamics, recognizing their bidirectional influences on human health. The relationships are explored through the brain-gut-microbiota axis, emphasizing the importance of maintaining a harmonious balance for overall well-being. Methods: A selection criteria was determined after a thorough literature review across search engines and databases. SANRA guidelines were followed to draft the manuscript. Objectives: To elicit the interplay between sleep patterns, chronobiology, and circadian rhythm influence the composition and functionality of the gut microbiome in human participants. Results: Disruptions in circadian rhythms impact gut microbiota composition, leading to dysbiosis and pathological mechanisms. Reciprocally, variations in sleep duration and quality influence the diversity and function of the gut microbiome. Identified microbial patterns associated with different circadian phases reveal nuanced connections, highlighting the broader implications of circadian rhythm disruption on human health.
... Initiating a work shift after obtaining more than 7 hours of sleep is crucial. Other effective measures include taking frequent rest breaks, consuming coffee, chewing gum, opening car windows for fresh air, engaging in conversation with passengers, taking short naps, listening to the radio, and refraining from smoking [32,38,39]. Unfortunately, many professional drivers only prioritize rest and napping after experiencing a sleep-related RTC. ...
... Policy changes, such as reducing long driving schedules from 12 hours per shift to 8 hours per shift, can be effective in preventing drowsy driving. [9,38,39]. Moreover, educating and encouraging professional drivers to sleep for more than 7 hours daily, especially for night shift drivers, taking daytime naps, and consuming caffeinated drinks in the evening or at night can help prevent insomnia, maintain nocturnal sleep quality, and ensure an adequate amount of sleep [32,39]. ...
... [9,38,39]. Moreover, educating and encouraging professional drivers to sleep for more than 7 hours daily, especially for night shift drivers, taking daytime naps, and consuming caffeinated drinks in the evening or at night can help prevent insomnia, maintain nocturnal sleep quality, and ensure an adequate amount of sleep [32,39]. ...
Introduction: Taxi drivers face unique challenges that can impact their health and safety, including driving behaviors, cardiovascular disease (CVD) risk factors, road traffic crashes (RTC), and fatigue. This study aimed to investigate the associations between these factors and fatigue in urban taxi drivers. Aims: To examine the relationship between driving behaviors, CVD risk factors, RTC, and fatigue in urban taxi drivers and to determine the prevalence of RTC and fatigue levels in this population. Methods: This is a cross-sectional study. A convenience sampling method was used to recruit 130 taxi drivers in San Francisco, United States. Data were collected using structured questionnaires that assessed demographic information, work factors, health characteristics, driving behaviors, and fatigue levels. Statistical analyses, including chi-square tests, were performed to explore associations between variables. Results: The majority of taxi drivers were middle-aged, primarily male, and worked an average of 41 hours per week. About 22% of drivers reported at least one RTC in the past year. Based on perceived fatigue scales (0-10), the mean level of fatigue in the prior week was 3.93 (±2.50), fatigue before bedtime was 5.2 (±2.60), and fatigue upon awakening was 3.5 (±2.40). The overall fatigue level (the sum of the 3 fatigue scales) was 12.7 (±5.98). Perceived high fatigue levels were significantly associated with shorter sleep duration (X 2 =6.66, p=0.01), good or poorer self-rated health (X 2 =9.53, p=0.003), and higher mental exertion (X 2 = 9.51, p=0.002). However, overall fatigue levels were not significantly associated with self-reported RTC. The findings of this study showed that high mean CVD risk factors (≥ 4 risks out of 9). Past and present medical history variables and family history of CVD variable are not statistically associated with abnormal sleep or perceived high fatigue. Conclusion: This study highlights the challenges faced by urban taxi drivers, including high workloads, stress, shorter sleep duration, and fatigue. While perceived high fatigue was associated with certain factors, such as sleep duration and mental exertion, no significant association was found with self-reported RTC. Interventions focusing on sleep hygiene, fatigue management, and policy changes are warranted to improve the health and safety of taxi drivers. Further research with larger samples and longitudinal designs is needed to enhance our understanding of these associations and inform targeted interventions in this population.
... taking frequent rest breaks, drinking coffee, chewing gum, and opening a car window to refresh air) to prevent drowsy driving [18,19]. In addition, talking with passengers, taking a short nap, and listening to the radio were the less frequent measures that have been used to reduce sleepiness during driving [20][21][22]. Unfortunately, professional drivers often do not take the time to rest nor to nap as a preventive approach until they have experienced a sleep-related RTC. ...
... Policy changes that modify long driving schedules from 12 hours/shift to 8 hours/shift for professional drivers may be an effective measure to prevent drowsy driving, deserving of future research. Also, there is an opportunity to educate and encourage professional drivers to sleep > 7 hours daily [16,20,[22][23]. To prevent insomnia and to maintain nocturnal sleep quality and get adequate amount of sleep, the professional drivers who are working night shift should be encouraged to take naps at daytime and drink caffeinated drinks at evening or night. ...
... To prevent insomnia and to maintain nocturnal sleep quality and get adequate amount of sleep, the professional drivers who are working night shift should be encouraged to take naps at daytime and drink caffeinated drinks at evening or night. Similarly, encouraging day shift drivers to sleep more than 7 hours/night is advised, and to avoid caffeinated drinks before sleeping [21,22]. ...
Introduction: Road traffic crashes (RTC) and road traffic injuries (RTI) are major health problems facing taxi drivers. Shorter sleep duration (≤7 hours/day) and sleepiness during driving are two risk factors for RTC and RTI. Aims: Identify the associations between shorter sleep duration and sleepiness during driving a taxi and RTC in taxi drivers. Methods: A cross-sectional design and convenience sampling method were used to recruit a total of 130 taxi drivers in San Francisco (California, United States). Data was collected from taxi drivers via interview, using a structured questionnaire. Results: Based on the Epworth Sleepiness Scale (ESS) total score, 14% of the subjects had abnormal sleepiness (ESS >10). On average, the subjects slept 7 hours daily, with 64% reporting sleeping ≤7 hours/day. About 22% of participants (n=29) reported at least one crash in the prior 12 months while driving their cab, totaling 45 crashes. Factors associated with abnormal sleep (≤7 hours/day) included not taking pain medication ≥1 time/week, not attending a health and safety training session for taxi driving, and not eating five cups of fruits and vegetables each day. Shorter sleep duration, overall fatigue and higher ESS scores were not significantly associated with RTC. Conclusion: Drivers reported abnormal sleep duration. Twenty-two percent of taxi drivers reported at least one crash in the prior 12-months; 11.5% RTI were reported in the prior 12-months. There were no significant bivariate associations between RTC and ESS, and abnormal sleep. There are opportunities to further explore interventions to enhance sleep hygiene in professional drivers. Clinical Relevance: Recognition of sleepiness in professional drivers is an important public health measure. The most important countermeasure to mitigate drowsy driving is to begin a work shift after sleeping more than 7 hours. Frequent rest breaks, drinking coffee, chewing gum, and opening a car window to refresh air are additional evidence-based countermeasures.
... As previous researches show, one of the main factors associated with unsafe driving behavior is driver sleepiness (Komada et al., 2013;Radun et al., 2015;Sadeghniiat-Haghighi et al., 2015). Sleep deprivation increases risk of traffic accident (Komada et al., 2013) and remarkably weakens the inhibition of violation (Kahn-Greene et al., 2006). ...
... As previous researches show, one of the main factors associated with unsafe driving behavior is driver sleepiness (Komada et al., 2013;Radun et al., 2015;Sadeghniiat-Haghighi et al., 2015). Sleep deprivation increases risk of traffic accident (Komada et al., 2013) and remarkably weakens the inhibition of violation (Kahn-Greene et al., 2006). ...
This paper aims to examine the key factors influencing driving risk perception in Iran. We conducted separate surveys for two groups of Iranian drivers, namely passenger car drivers and truck drivers. In order to assess driving risk perception, respondents were asked what they think about their Probability of Having a Road Accident (PHRA) and if they eventually have an accident as a driver, what they think about the Probability of it being Fatal or causing Severe Injury (PFSI). A Bivariate Ordered Probit model, which considers the possible correlation between PHRA and PFSI, was developed to explain the observed driving risk perception using type of vehicle, driving experience, socio-demographic information, and driving behaviour. According to the results, vehicle type, vehicle age, driving experience, sleep quality, at-fault accidents over the past three years, vehicles safety-related equipment, and education level have significant effects on driving risk perception (p-value < 0.05). In addition, this paper compares the driving risk perception of truck and passenger car drivers. The results show that truck drivers have a higher perception of PHRA and PFSI compared with passenger car drivers (p-value < 0.05). The results may convince policy-makers to consider the characteristics of the two categories of drivers when designing regulations.
... Although this phenomenon is one of the main factors leading to accidents (in fact it is called the "silent killer), most people are not aware of its possible harms (Guangnan et al. 2016). Thus, the connection between drivers' fatigue and road accidents has been analyzed in many studies (Pizza et al. 2010;Komada et al. 2013;Bunn et al 2017). Thus, long trips on uniform roads, such as expressways, because more fatigue, which applies especially to heavy-vehicle drivers due to their long drives (Philip 2005;Howard et al. 2004). ...
The significant increase in transportation and heavy vehicle traffic has caused freeway routes with heavy traffic to face a decrease in safety levels. Furthermore, fatigue and sleepiness are proven to be two of the main reasons of road accidents, and therefore focus on these issues is crucial. Factors such as "use of engineering (safety) technology for road transport", "informing the drivers on various educational methods", "controlling the drivers' work hours", "use of different routes (alignment inconsistency)" and "observing the drivers' mental health" should be approached to reduce the accidents caused by fatigue and sleepiness. Given the complex interrelationships between these variables and the number of road accidents, structural equation modelling has been used in this study to estimate the effect and relationships between multiple variables. Data were collected during a 5-month period by interviewing heavy vehicle drivers (2765 filled-out questionnaires). The Confirmatory Factor Analysis (CFA) has also been used to ascertain the validity of the questionnaires. The mentioned factors affecting the drivers' fatigue were analyzed using SPSS 24.0 package, which allowed ascertaining that the drivers' mental health is the factor of greater influence on road accidents caused by fatigue and drowsiness. Therefore, actions to improve the drivers' mental and emotional health (by improving the currently used engineering (safety) technology and alignment inconsistency) should be enhanced rather than excessive controls on the drivers' work hours by using GPS, work papers and inspections.
... Although this phenomenon is one of the main factors leading to accidents (in fact it is called the "silent killer), most people are not aware of its possible harms (Guangnan et al. 2016). Thus, the connection between drivers' fatigue and road accidents has been analyzed in many studies (Pizza et al. 2010;Komada et al. 2013;Bunn et al 2017). Thus, long trips on uniform roads, such as expressways, because more fatigue, which applies especially to heavy-vehicle drivers due to their long drives (Philip 2005;Howard et al. 2004). ...
The significant increase in transportation and heavy vehicle traffic has caused freeway routes with heavy traffic to face a decrease in safety levels. Furthermore, fatigue and sleepiness are proven to be two of the main reasons of road accidents, and therefore focus on these issues is crucial. Factors such as “use of engineering (safety) technology for road transport”, “informing the drivers on various educational methods”, “controlling the drivers’ work hours”, “use of different routes (alignment inconsistency)” and “observing the drivers’ mental health” should be approached to reduce the accidents caused by fatigue and sleepiness. Given the complex interrelationships between these variables and the number of road accidents, structural equation modelling has been used in this study to estimate the effect and relationships between multiple variables. Data were collected during a 5-month period by interviewing heavy vehicle drivers (2765 filled-out questionnaires). The Confirmatory Factor Analysis (CFA) has also been used to ascertain the validity of the questionnaires. The mentioned factors affecting the drivers’ fatigue were analyzed using SPSS 24.0 package, which allowed ascertaining that the drivers’ mental health is the factor of greater influence on road accidents caused by fatigue and drowsiness. Therefore, actions to improve the drivers’ mental and emotional health (by improving the currently used engineering (safety) technology and alignment inconsistency) should be enhanced rather than excessive controls on the drivers’ work hours by using GPS, work papers and inspections.
... Multiple scholars (Kumarage et al., 2000;Komba., 2006;Komada et al., 2013) have carried out many studies to recognize the elements associated with fatal accidents. Among them, Kumarage et al. (2000) claimed that accidents related to speed are the most contributory to deadly accidents in Sri Lanka. ...
... Furthermore, Komba (2006), stated that defects in vehicles, driving aggressively, and driving on the wrong side of the road were major contributors of deadly accidents in Tanzania. A study done by Komada et al. (2013) found that slept deprivation among drivers is a significant contributor to fatal accidents. Parallel findings have also been made by Lucidi et al. (2013); stated that sleep related accidents are avoidable yet remain a major cause of traffic accidents. ...
Road Traffic Accidents (RTAs) are one of the most prominent public health problems as it is a leading cause of death by injury and all deaths globally. This study therefore intended determine the factors associated with severity of RTAs in Sri Lanka (2005-2019) based on data driven decision making (DDDM) which would be useful for decision makers. Analysis of frequency tables with Chi-square statistics and binary logistic regression analysis were applied to derive the required inferences. When the variables were considered separately, all attributes of road characteristics, time & environmental characteristics vehicle characteristics and human & accident characteristics have significant association with severity of accident except gender of the driver. The fitted binary logistic model revealed that wet road surface, night with improper street lighting, night with good street lighting, rural area, normal weekend, holiday, alcohol test not tested, accidents due to the lack of attention of the driver, two wheels vehicles, age of vehicle less than 10 years and driver's age under the age of 18 years have significantly contributed to occurrences of fatal accidents. The odds of happening fatal accidents in wet road surface 1.109 times higher than that it occurs in dry road surface. The odds of happening fatal accidents during night with improper street lighting is 1.518 times higher than that it occurs during daylight. The inferences derived from this study would be very useful for policy makers in order to minimize RTAs in Sri Lanka.
... Drowsiness is an important factor for road crash deaths and injuries, with significant efforts required to mitigate its effects. A case study conducted in Sweden found approximately 8-15% of crashes were caused by drivers experiencing acute sleepiness (Kecklund et al., 2011), while other research has highlighted the influence of sleep disorders on road crashes (Komada et al., 2013). According to the Australian National Road Safety Strategy during the 2011-2020 session, drowsiness while driving is responsible for 20-30% of road crash deaths and acute injuries (Australian Transport Council, 2011). ...
Introduction:
Drowsiness is one of the main contributors to road-related crashes and fatalities worldwide. To address this pressing global issue, researchers are continuing to develop driver drowsiness detection systems that use a variety of measures. However, most research on drowsiness detection uses approaches based on a singular metric and, as a result, fail to attain satisfactory reliability and validity to be implemented in vehicles.
Method:
This study examines the utility of drowsiness detection based on singular and a hybrid approach. This approach considered a range of metrics from three physiological signals - electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG) - and used subjective sleepiness indices (assessed via the Karolinska Sleepiness Scale) as ground truth. The methodology consisted of signal recording with a psychomotor vigilance test (PVT), pre-processing, extracting, and determining the important features from the physiological signals for drowsiness detection. Finally, four supervised machine learning models were developed based on the subjective sleepiness responses using the extracted physiological features to detect drowsiness levels.
Results:
The results illustrate that the singular physiological measures show a specific performance metric pattern, with higher sensitivity and lower specificity or vice versa. In contrast, the hybrid biosignal-based models provide a better performance profile, reducing the disparity between the two metrics.
Conclusions:
The outcome of the study indicates that the selected features provided higher performance in the hybrid approaches than the singular approaches, which could be useful for future research implications. Practical Applications: Use of a hybrid approach seems warranted to improve in-vehicle driver drowsiness detection system. Practical applications will need to consider factors such as intrusiveness, ergonomics, cost-effectiveness, and user-friendliness of any driver drowsiness detection system.
... Prolonged sleep loss is a rising problem in modern societies and is a risk factor for a broad range of disorders, from psychological (Okun et al., 2018), neurological (Phua et al., 2017), and neurodegenerative diseases (Olsson et al., 2018) to metabolic and cardiovascular disorders (Joukar et al., 2013;Reutrakul and Van Cauter, 2018). The increased risk of car accidents, as well as increased damage risk among the shift workers, could be attributed to the cognitive deficits resulting from insufficient sleep (Geiger-Brown et al., 2012;Komada et al., 2013). ...
Background
The weight of evidence suggests that sleep is essential for the processes of memory consolidation and sleep deprivation (SD) impairs the retention of long-term memory in both humans and experimental animals, which is associated with oxidative stress damage within the brain. Green tea polyphenols have revealed carcinogenic, antioxidant, anti-, and anti-mutagenic properties. We aimed to investigate the possible protective effect of green tea extract (GTE) and its main active catechin, epigallocatechin-3-gallate (EGCG), on post-training total sleep deprivation (TSD) -induced spatial memory deficits and oxidative stress profile in the hippocampus of the rat.
Methods
Male rats were treated with saline, GTE ( 100 and 200 mg/kg/day), and EGCG (50 mg/kg/day) intraperitoneally for 21 days and then trained in Morris water maze (MWM) in a single day protocol. Immediately after the end of MWM training, animals were sleep deprived for 6 h by the gentle handling method, and then evaluated for spatial memory. Hippocampal levels of malondialdehyde, (MDA), and thiol was assessed as oxidant and antioxidant markers.
Results
Spatial memory was impaired in the TSD group and GTE at the dose of 200 mg/kg/day as well as EGCG at the dose of 50 mg/kg/day could reverse the impairment to the saline-treated levels. Despite the unchanged MDA levels, hippocampal total thiol was significantly decreased after TSD and EGCG increased it to the basal levels.
Conclusion
In conclusion, green tea and its main catechin, EGCG, could prevent memory impairments during 6 h of TSD; probably through normalizing the antioxidant thiol defense system which was impaired during TSD.
... However, few sleep hours and long working hours are considered normal in modern societies [17,18]. For example, Komada et al. [19] reported that in the 1960s, 90% of Japanese people went to sleep at 11 p.m. and for periods of at least 8 h, while in 2010 more than half of the people were still awake by that time and slept an average of 7 h and 14 min. These antecedents could be associated with the observed chronic lack of sleep in developed countries, a situation that leads to excessive daytime sleepiness [12,20,21]. ...
... Regarding sleep quantity, sleeping less than 6 hours is a risk factor for traffic accidents in all drivers [19] and professional truck drivers [12]. Additionally, Carter et al. [25] found that traffic accidents, either recreational or commuting to work, and workplace accidents, were related to lack of sleep using self-report accidents among Swedish men. ...
... This raises an essential question about causation: are detriments in sleep quantity causing commuting accidents, or are worse sleep hours a by-product of having had commuting accidents? Although our research does not clarify the direction of the relationship, robust previous evidence shows that sleep problems are a predisposing factor for accidents [11,19,24,25,27]. ...
Background
This study aimed to verify the relationships between sleep problems and both commuting and workplace accidents in workers of both sexes.
Methods
The study was carried out with a sample of workers ( n = 2993; 50.2% female) from the Chilean Quality of Life Survey (ENCAVI) 2015–2016, while the rates of both workplace and commuting accidents were extracted from the statistics of the Superintendence of Social Security (SUSESO 2015; 180,036 and 52,629 lost-time accidents, respectively).
Results
Chilean workers sleep less than the rest of the people in the country ( M W = 7.14 vs. M O = 7.33; t (6789) = − 5.19; p < .001), while the Chilean people as a whole sleep less compared to those of other countries (7.24 h per day). Likewise, it was found that sleep problems are more strongly related to commuting than to workplace accidents. In this vein, sleep quantity can explain 24% of the variance in commuting accidents’ rates (Stepwise Method; R ² = .30, F (1.14) = 5.49, p < .05; β = −.55, p < .05), by using aggregated data with all types of commuting roles (driver of a vehicle, a passenger of public or private transport, or as a pedestrian).
Conclusions
Our findings show that sleep quantity has a more robust relationship with commuting than workplace accidents, a neglected issue so far. Future prevention programs should emphasize sleep hygiene and focus on commuting to and from work.
