Gender Differences in Prevalence of Sleepy Driving Among Young Drivers in Saudi Arabia

Yousef D Alqurashi,1 Abdullah S Alqarni,1 Faisal Maher Albukhamsin,1 Abdullah Abdulaziz Alfaris,1 Bader Ibrahim Alhassan,1 Waleed Khalid Ghazwani,1 Abdulaziz Abdulrahman Altammar,1 Mutlaq Eid Aleid,1 Hayfa Almutary,2 Abdulelah M Aldhahir,3 Saleh A Alessy,4 Rayyan Almusally,5 Abir Alsaid,5 Mahmoud Ibrahim Mahmoud,5 Hatem Othman Qutub,5 Tunny Sebastian,6 Suliman Alghnam,7 Michael I Polkey8 1Respiratory Care Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; 2Medical Surgical Nursing Department, King Abdulaziz University, Jeddah, Saudi Arabia; 3Respiratory Therapy Department, Faculty of Applied Medical Sciences, Jazan University, Jazan, Saudi Arabia; 4Department of Public Health, College of Health Sciences, Saudi Electronic University, Jeddah, Saudi Arabia; 5Internal Medicine Department, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Khobar, Saudi Arabia; 6Clinical Nutrition Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia; 7Population Health Section-King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Saudi Arabia; 8Royal Brompton Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London, UKCorrespondence: Yousef D Alqurashi, Respiratory Care Department, College of Applied Medical Sciences, Imam Abdulrahman Bin Faisal University, Dammam, 34221, Saudi Arabia, Email [email protected]: Sleepy driving is associated with Motor Vehicles Accidents (MVAs). In Saudi Arabia, previous studies have addressed this association among men only. Therefore, the aim of this study was to compare the prevalence of sleepy driving and associated factors between genders.Methods: In a cross-sectional study design, we offered a self-administered online questionnaire to 3272 participants from different regions of Saudi Arabia. The questionnaire included 46 questions covering sociodemographics, driving habits, sleeping habits, Epworth Sleepiness Scale, and Berlin questionnaire to assess the risk of sleep apnea. Univariable and multivariable logistic regression analyses were used to determine the significant factors associated with self-reported sleepy driving, defined as operating a motor vehicle while feeling sleepy in the preceding six months.Results: Of the 3272 invitees, 2958 (90%) completed the questionnaire, of which 1414 (48%) were women. The prevalence of sleepy driving in the preceding six months was 42% (men: 50% and women 32%, p< 0.001). Specifically, participants reported the following: 12% had had to stop their vehicle due to sleepiness (men: 16.2% and women 7%, p< 0.001), 12.4% reported near-miss accidents (men: 16.2% and women: 8.2%, p< 0.001) and 4.2% reported an accident due to sleepiness (men: 4.3% and women: 4%, p=0.645). In multivariable analysis, being male, younger age, use of any type of medications, shift working, working more than 12 hours per day, driving duration of 3– 5 hours per day, driving experience of more than 2 years, excessive daytime sleepiness and risk of having obstructive sleep apnea were all associated with increased likelihood of falling asleep while driving in the preceding 6 months.Conclusion: Sleepy driving and MVA are prevalent in both gender but was higher in men. Future public health initiatives should particularly focus on men, since men reported a greater likelihood of both sleep-related MVA and “near miss” events.Keywords: sleepiness, driving, obstructive sleep apnea, OSA, gender difference

Evaluation of Nanofluidics Technology for High-Throughput SNP Genotyping in a Clinical Setting

The current need for high-throughput genotyping platforms for targeted validation of disease-associated single nucleotide polymorphisms (SNPs) motivated us to evaluate a novel nanofluidics platform for genotyping DNA extracted from peripheral blood and buccal wash samples. SNP genotyping was performed using a Fluidigm 48.48 Dynamic Array biochip on the BioMark polymerase chain reaction platform and results were compared against standard TaqMan assays and DNA sequencing. Pilot runs using these dynamic arrays on 90 samples against 20 SNP assays had an average call rate of 99.7%, with 100% call rates for 16 of the assays. Manual TaqMan genotyping of these samples against three SNPs demonstrated 100% correlation between the two platforms. To understand the influence of DNA template variability, three sources of blood samples (CH-1, n = 20; CH-2, n = 47; KK, n = 47) and buccal washes (n = 37) were genotyped for 24 SNPs. Although both CH-1 and CH-2 batches showed good base calling (≥98.8%), the KK batch and buccal wash samples exhibited lower call rates (82.1% and 94.0%). Importantly, repurification of the KK and buccal wash samples resulted in significant improvements in their call rates (to ≥97.9%). Scale-up for genotyping 1698 cases and controls for 24 SNPs had overall call rates of 97.6% for KK and 99.2% for CH samples. The Dynamic Array approach demonstrated accuracy similar to that of TaqMan genotyping, while offering significant savings in DNA, effort, time, and costs