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216 Ki-Bong Kim, et al. Sleep Disorder and Sleepy Drivers ORIGINAL ARTICLE Korean J Clin Lab Sci. 2015, 47(4):216-224 http://dx.doi.org/10.15324/kjcls.2015.47.4.216 pissn 1738-3544 eissn 2288-1662 Correlation between Sleep Disorders and Sleepy Drivers Ki-Bong Kim 1, Hyun-Ho Sung 2, Sang-Nam Park 3, Bok-Jo Kim 3, and Chang-Eun Park 4 1 Section of Neurophysiology Laboratory, Samsung Medical Center, Seoul 06351, Korea 2 Department of Clinical Laboratory Science, Dongnam Health University, Suwon 16328, Korea 3 Department of Clinical Laboratory Science, Kyungwoon University, Gumi 39160, Korea 4 Department of Biomedical Laboratory Science, Namseoul University, Cheonan 31020, Korea 수면장애와졸음운전의상관성 김기봉 1, 성현호 2, 박상남 3, 김복조 3, 박창은 4 1 삼성서울병원신경과검사실, 2 동남보건대학교임상병리과, 3 경운대학교임상병리학과, 4 남서울대학교임상병리학과 This study aims to identify the prevalence of sleep related disease in those who experienced car accidents caused by drowsy driving. To this end, a survey of usual sleep habits, polysomnography, and multiple sleep latency tests were conducted in 34 persons who experienced an accident after normal sleep (Group 1), 22 persons who experienced an accident after abnormal sleep (Group 2), and 17 persons who was proven to be normal as a result of polysomnography and had no accident (Group 3). In all, 192 persons responded to the preliminary survey and the results were compared and analyzed. Crossover analysis was conducted to test the homogeneity of statistical characteristics, and the physical characteristics by age were analyzed. In the survey of sleeping habits, there was a significance between groups in how often they woke up while asleep (p<0.01), how difficult it was to go back to sleep again after waking up from sleep (p<0.05), how early they woke up in the morning (p<0.05), how difficult it was to get up in the morning (p<0.05), how sleepy they felt in the daytime (p<0.01), and how tired they felt in the daytime (p<0.01). Furthermore, among 56 subjects who had an accident during drowsy driving, 94.6% (53 persons) were found to have sleep related diseases. This suggests that car accidents during drowsy driving is not simply caused by temporary lack of sleep but by sleep related diseases even when sleep is adequate, leading to car accidents. Therefore, this study is significant identifying the association between car accidents during drowsy driving and sleep related disorders. Furthermore, the data would be considered basic to prepare social measures against drowsy driving related to such sleep related disorders. Keywords: Drowsy driving, Daytime sleepiness, Sleep apnea, Multiple sleep latency test Corresponding author: Chang-Eun Park Department of Biomedical Laboratory Science, Namseoul University, Cheonan 31020, Korea Tel: 82-41-580-2722 E-mail: eun2777@hanmail.net This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright 2015 The Korean Society for Clinical Laboratory Science. All rights reserved. Received: October 8, 2015 Revised 1 st : October 12, 2015 Revised 2 nd : October 12, 2015 Accepted: October 12, 2015 서론교통사고는다양한원인에의해발생하는데 (Pandi-Perumal 등, 2006), 첫번째원인은전체교통사고원인의약 1 25% 를차지하고있는졸음운전으로알려져있다 (Ward 등, 2013). 그러나, 졸음운전에대해서는아직사회적인식이부족하다 (Jo와 Lee, 2014). 졸음운전의가장대표적인원인은수면의결핍 (lack of sleep time) 과수면의연속성결여 (sleep fragmentation) 때문이며 (Lee, 2003), 이러한수면시간의감소로인한졸음운전은환경및습관의개선으로해결이가능하지만, 수면관련질환으로치료중인사람이나또는치료를받지않은사람에게나타나는수면의연속성결여는환경이나습관의개선으로해결이어렵고, 치사율이높은교통

Korean J Clin Lab Sci. Vol. 47, No. 4, Dec. 2015 217 사고가발생할가능성이크다고보고되었다 (Siedlecka 등, 2012). 졸음운전사고의발생은수면중무호흡-저호흡지수가높은사람이나, 또는, 운전중에느끼는졸림의정도가심한사람일수록높아진다고알려져있다 (Choi와 Kim, 2013). 수면무호흡증은수면중호흡의중단으로산소공급이저하되고, 수면의연속성이이어지지않으며, 수면의질저하와주간졸음증을유발하게된다 (Lee, 2003). 기면증또한, 수면과각성의주기장애가있는질환으로주간졸음증을유발한다. 기면증을치료하지않으면자신의생각과상관없이 2 3 시간간격으로 10 20 분간급작한졸음에빠지게되고, 갑자기몸에힘이빠지는탈력발작 (cataplexy) 에의해서교통사고가발생할수있다고보고되었다 (Siedlecka 등, 2012). 한해에발생하는졸음운전에의한교통사고사망률과직ㆍ간접적인피해를고려해볼때, 매우중요한문제이지만아직까지국내의졸음운전에대한분류조사는미비한실정이다 (Collop 등, 2011). 본연구에서는졸음운전교통사고를경험한사람중에서정상적인수면시간을갖은대상군과수면시간이부족한대상군에서수면다원검사의결과가정상판정을받은군과비교하여졸음운전사고와수면관련질환의상관성을관찰하고자하였다. 재료및방법 1. 연구대상연구의대상은 2014년 8월부터 12월까지서울소재 1개종합병원수면센터를방문하여설문에응답한 200명의성인중에서운전을하지않는사람을제외한 192명을대상으로조사하였다 (Table 1). 이들중졸음교통사고를경험한군 56명과검사결과정상이면서교통사고를경험하지않은군 17명을대상으로조사하였으며, 교통사고를경험한군 56명중에서사고전날 6시간이상정상수면을취한 34명 (Group 1), 사고전날 6시간이하수면을취한 22명 (Group 2), 검사결과가정상이면서교통사고를경험하지않은 17 명 (Group 3) 로분류하였다. 그리고본연구에포함된대상자는모두자발적동의를하였고, 수면관련질환을알아보기위하여수면 다원검사 (PSG; Polysomnography study), 다중수면잠복기검사 (MSLT; Multiple sleep latency test) 를시행하였다. 2. 수면습관에대한설문 수면습관은평상시수면습관에관한평가로평균수면시간, 평일과주말의수면시간차이, 잠자리에누운후잠이들때까지걸리는시간, 주관적인수면의문제점, 수면중특이사항및낮의졸림정도등을파악하였고수면과운전과의관계에서는졸음운전사고경험과평상시수면시간, 사고전날수면시간, 졸음운전사고시총운전시간및현재의수면습관이운전에얼마나영향주고있는지에대해설문을시행하였다. 3. 수면의분류및질환판정 수면의분류및수면질환의판정은미국수면의학회 (AASM; American academy of sleep medicine) 의수면분류법에따라분석하고, 신경과수면전문의사가최종판정하였다. 수면의단계와각성빈도를측정하여수면의질을평가하기위해서뇌파 (EEG; Electroencephalography) 전극배치법 (10 20 system) 에따라 F3, F4, C3, C4, O1, O2의뇌파전극을사용하였고, 기준전극으로 Table 1. General characteristic of attendees Age group Gender N (%) M±SD X 2 /p All Male 169 (80.5) 47.47±10.05 2.452/.784 Female 23 (12.0) 50.39±9.46 20 Male 1 (0.5) 18.00±0.00 Female 0 (0.0) - 21 30 Male 10 (5.2) 27.60±2.22 Female 2 (1.0) 30.00±0.00 31 40 Male 30 (15.6) 35.47±3.26 Female 2 (1.0) 37.50±2.12 41 50 Male 55 (28.6) 46.56±2.81 Female 6 (3.1) 47.50±2.58 51 60 Male 62 (32.3) 54.73±2.64 Female 11 (5.7) 55.70±2.79 60 Male 11 (5.7) 64.64±3.07 Female 2 (1.0) 63.00±2.82 Fig. 1. EEG electrodes for sleep stage classification. The F3, F4 waves is frontal activity, C3, C4 wave of the central activity and O1, O2 wave is occipital activity (alpha rhythm). This record is sensitivity 5 7 V/mm, HF (high filter) 70 Hz, LF (low filter) 0.3 Hz, paper speed 10 mm/sec (30 sec/page).

218 Ki-Bong Kim, et al. Sleep Disorder and Sleepy Drivers M1와 M2를사용하였다 (Fig. 1). REM (Rapid eye movement) 수면에서안구의수평운동을관찰하기위해서좌우눈가에서 1 cm씩상방과하방으로전극을부착하고, 안구의상하움직임을관찰하기위하여안와상연 (supraorbital) 과안와하연 (infraorbital) 에전극을추가로부착하여기록하였다 (Fig. 2). REM 수면분류를위하여턱위 (mentalis) 와턱아래 (sub-mentalis) 에 chin EMG (Electromyography) 전극 2개를부착하고, 야간근연축 (noctural myoclonus) 에의한각성반응 (arousal reaction) 을기록하기위해서앞정강근 (tibialis anterior EMG) 에좌, 우각각 2 개의전극을부착하였다. 자발적호흡노력 (respiratory effort) 을관찰하기위해서늑골사이 (intercostal) 에 EMG 전극 2개를추가로 부착하여기록하였다 (Fig. 3). 수면중호흡상태의관찰은 Fig. 4와같이, 코의온도센서와압력센서를동시에사용하였고, 가슴과복부에벨트로된압력측정기 (strain gauge) 를사용하여호흡근육의자발적호흡노력을기록하였다. 기타혈중산소포화도 (O 2 saturation), 코골이 (snoring), 심전도 (EKG; Electrocardiogram), 체위등을수면과동시에기록하여수면의질을측정하였다. 연구대상자들은평소수면습관에따라잠자리에들었고, 총수면시간 (TST; Total sleep time) 이 6시간이상이되도록배려하였다. 연구대상자의총수면시간을미국수면의학회의수면분류법에따라 S1, S2, S3 및 REM 수면으로분류하였다. 또한, 안정된수면을방해하는코골이, 수면무호흡, 다리움직임 (PLMD; Periodic limb Fig. 2. The channel for identifying eye movement. Upper/downward and leftward/rightward movement of pupils was analyzed by using 4 electrodes. This record shows the movement of the pupils during the REM sleep. Fig. 3. The electrodes for EMG measurements. The chin EMG (mentalissubmentalis muscle), tibialis anterior EMG and intercostal EMG. This recorde is sensitivity 50 V, HF (high filter) 30~35 Hz, LF (low filter) 0.3 Hz. Fig. 4. A sensor for measuring respiratory effort. This record shows the air flow (nasal thermistor and pressure) and respiratory effort measured in the chest and abdomen, and measurements of oxygen saturation (SpO 2) and snoring. This record related to obstructive sleep apnea patients indicates that oxygen saturation fell as a result of blocked respiratory flow towards the upper airway.

Korean J Clin Lab Sci. Vol. 47, No. 4, Dec. 2015 219 movement during sleep), 체위등을분석하여 Fig. 5와같이다이아그람을작성하고, 잠이들기까지의시간 (SL; Sleep latency), 잠이들고첫번째 REM 수면까지의시간 (RL; REM latency), 각성반응지수 (TAI; Total arousal index) 와무호흡지수 (AHI; Apnea hypopnea index) 를계산하였다. S1 (stage 1)= 얕은수면 ( 정상성인 : TST의 10% 이하 ) S2 (stage 2)= 중간수면 ( 정상성인 : TST의 44 59%) S3 (stage 3)= 깊은수면 ( 성인기준정상 : TST의 9.5 12%) TAI= 총 arousal 수 /(TST/ 60) AHI=( 총 apnea 수 + 총 hypopnea 수 )/(TST/ 60) 주간졸음증측정을위해서다중수면잠복기검사를시행하였고, 검사후, 미국수면의학회의수면분류법에따라서분석하고, 신경 과수면전문의사가최종판정하였다. 수면다원검사가끝난후, 수면단계를분류할수있는뇌파전극 (F3, F4, C3, C4, O1, O2, M1, M2) 과 REM 수면판단을위한안구운동 (EOG) 전극, mentalis와 sub-mentalischin의근전도전극을남기고모두제거하였다. 그리고완전한각성이유지된상태에서 30분동안수면을유도하고, 1시간 30분동안다시각성을유지하는 2시간의검사주기를 5회반복하여실시하였다 (Fig. 6). 각각의검사주기에서수면을유도한후잠이들기까지걸린시간 (sleep latency) 의평균 (mean sleep latency) 을구하였고, 잠이든후 REM수면이나올때까지걸린시간 (REM sleep latency) 의평균 (mean REM sleep latency) 을계산하였다. 5회반복한검사중에서 SOREM (sleep onset REM) 이 2회이상나오고, mean REM sleep latency가 <15 min 가충족이되면기면증 (narcolepsy) 으로진단하였다. Fig. 5. The graphical representation of the sleep state of obstructive sleep apnea patients for 6 hours and 10 minutes. Classification and analysis of EEG with arousal reaction, PLMD, body position, SpO 2, snoring, heart rate, respiration event, etc., is displayed can evaluate the aspects of the overall sleep.

220 Ki-Bong Kim, et al. Sleep Disorder and Sleepy Drivers Mean sleep latency=sleep latency의합 / 검사시행수 Mean REM sleep latency=rem sleep latency 의합 / SOREM 수다중수면잠복기검사를위해서대상자들은당일심한운동및카페인이함유된음료를제한하였고, 자극제또는, REM수면억제약물은 2주전부터중단하였다. 각각의검사주기에서 30분동안수면유도후, 1시간 30분동안잠을잘수없도록관리하였다. 4. 통계분석통계의자료분석은 SPSS, PC. Version 21.0 (SPSS Inc, Chicago, IL, USA) 프로그램을사용하였다. 연구대상자들의인구통계학적특성의동질성을검정하고자교차분석을시행하였고, 연령대별신체적특성을분석하고변수에따른모든정량데이터와수면다원검사결과의차이를검정하기위해평균 (M) 과표준편차 (SD) 를산출하여독립 t-검정과일원배치분산분석을실시하였다. 각각의설문변인에따른차이를검정하기위해교차분석을통해카이제곱검정을실시하였다. 그리고모든통계적유의수준은 p=0.05 로설정하였다. 결과 1. 수면설문의분석연구대상자의평소수면시간에대한설문결과는 Table 2과같이, 그룹 1은 404.54(±67.13) 분, 그룹 2는 356.19±(59.78) 분, 그룹 3은 336.00±(108.87) 분이었다. 그룹 1은그룹 2보다그룹 2는그룹 3보다수면시간이길게나타났으며, 그룹 1과 3에서유의한차이가있었다 (p<0.05). Table 3의평소수면습관에관한주관적질문에서코골이 ( 그룹 1>그룹2>그룹3) (p<0.05), 수면무호흡증 ( 그룹1>그룹2>그룹 3) (p<0.01), 수면중꿈을꾸는여부 ( 그룹2>그룹1>그룹3) (p< 0.05) 에관한설문결과에서도그룹간에독립된집단으로유의성이확인되었다. 또한, 수면중각성 ( 그룹2>그룹1>그룹3) (p< 0.01), 수면각성후재수면이어려운정도 ( 그룹1>그룹2>그룹3) (p<0.05), 아침에일찍잠이깨는정도 ( 그룹1>그룹2>그룹3) (p< 0.05), 아침에기상하기어려운정도 ( 그룹1>그룹2>그룹3) (p< 0.05), 낮에졸리운정도 ( 그룹1>그룹2>그룹3) (p<0.01), 낮에피곤한정도 ( 그룹1>그룹2>그룹3) (p<0.01) 에관한설문결과 Fig. 6. The records from multiple sleep latency test (MSLT). They were carried out 5 times based on time cycle. The patients were diagnosed with narcolepsy as they showed 2 episodes of sleep-onset REM sleep (SOREM) with mean REM latency<15 min (9 min). Table 2. Differences of average daily sleep time among groups F/p N=192 N=34 N=22 N=17 Average daily sleep time (min) 323.02±98.62 404.54±67.13 356.19±59.78 336.00±108.87 5.100/.009 a>c a, sleep more than six hours, traffic accidents Group (Group 1); b, sleep less than six hours, traffic accidents Group (Group 2); c, normal, accident-free group (Group 3).

Korean J Clin Lab Sci. Vol. 47, No. 4, Dec. 2015 221 Table 3. Differences of sleep habits questionnaire among groups Variables Total Group 1 Group 2 Group 3 N=192 (%) N=34 (%) N=22 (%) N=17 (%) X 2 /p Snoring A 5 (2.6) 1 (2.9) 0 (0.0) 2 (11.8) 22.30/.012 N 8 (4.2) 1 (2.9) 1 (4.5) 3 (17.6) U 14 (7.3) 1 (2.9) 1 (4.5) 3 (17.6) S 41 (21.4) 9 (26.5) 4 (18.2) 5 (29.4) G 111 (57.9) 20 (58.8) 15 (68.2) 1 (5.9) Missing: 13 (6.8%) Sleep Apnea A 15 (7.7) 2 (5.9) 3 (13.6) 6 (35.3) 35.40/.000* N 20 (10.4) 3 (8.8) 1 (4.5) 2 (11.8) U 23 (12.0) 1 (2.9) 3 (13.6) 2 (11.8) S 56 (29.1) 12 (35.3) 7 (31.8) 2 (11.8) G 52 (27.1) 11 (32.4) 6 (27.3) 0 (0.0) Missing: 26 (13.5%) Many dream sleep A 18 (9.3) 6 (17.6) 1 (4.5) 1 (5.9) 27.64/.035 N 40 (20.9) 5 (14.7) 4 (18.2) 3 (17.6) U 60 (31.3) 10 (29.4) 6 (27.3) 6 (35.3) S 29 (15.1) 6 (17.6) 3 (13.6) 1 (5.9) G 28 (14.6) 3 (8.8) 6 (27.3) 3 (17.6) Missing: 9 (4.7%) Waking up frequently during sleep A 19 (9.9) 7 (20.6) 2 (9.1) 3 (17.6) 40.28/.000* N 38 (19.8) 7 (20.6) 1 (4.5) 4 (23.5) U 44 (22.9) 9 (26.5) 6 (27.3) 0 (0.0) S 41 (21.4) 4 (11.8) 6 (27.3) 4 (23.5) G 36 (18.8) 4 (11.8) 6 (27.3) 3 (17.6) Missing: 14 (7.3%) Wake up early morning A 16 (8.3) 3 (8.8) 1 (4.5) 2 (11.8) 25.73/.028 N 20 (10.4) 3 (8.8) 4 (18.2) 0 (0.0) U 63 (32.9) 15 (44.1) 5 (22.7) 4 (23.5) S 29 (15.2) 3 (8.8) 3 (13.6) 5 (29.4) G 33 (17.2) 2 (5.9) 2 (9.1) 2 (11.8) Missing : 31 (16.1%) Hard to get up in the morning A 27 (14.0) 2 (5.9) 2 (9.1) 3 (17.6) 27.05/.019 N 40 (20.9) 7 (20.6) 4 (18.2) 3 (17.6) U 51 (26.6) 13 (38.2) 9 (40.9) 2 (11.8) S 32 (16.7) 4 (11.8) 3 (13.6) 5 (29.4) G 29 (15.1) 6 (17.6) 3 (13.6) 2 (11.8) Missing : 13 (6.8%) Sleepiness during the day A 6 (3.0) 0 (0.0) 0 (0.0) 0 (0.0) 30.42/.001* N 13 (6.7) 2 (5.9) 1 (4.5) 1 (5.9) U 39 (20.3) 6 (17.6) 3 (13.6) 4 (23.5) S 80 (41.7) 13 (38.2) 12 (54.5) 4 (23.5) G 46 (24.0) 12 (35.3) 5 (22.7) 6 (35.3) Missing : 8 (4.2%) Tiredness during the day A 2 (1.0) 0 (0.0) 0 (0.0) 0 (0.0) 30.59/.001* N 19 (9.9) 2 (5.9) 1 (4.5) 2 (11.8) U 35 (18.2) 5 (14.7) 1 (4.5) 3 (17.6) S 52 (27.0) 9 (26.5) 8 (36.4) 2 (11.8) G 55 (28.6) 11 (32.4) 5 (22.7) 6 (35.3) Missing : 29 (15.1%) Abbreviation: A, absolutely not; N, no; U, usually; S, slightly; G, greatly. Group 1, sleep more than six hours, traffic accidents Group; Group 2, sleep less than six hours, traffic accidents Group; Group 3, normal, accident-free group.

222 Ki-Bong Kim, et al. Sleep Disorder and Sleepy Drivers 에서도그룹간유의성이확인되었다. 2. 수면다원검사연구대상자들의수면다원검사에서수면분류의결과는 Table 4와같이, S1은그룹 1에서 28.01±(15.10), 그룹 2에서 20.20±(10.12), 그룹 3에서 11.62±(4.94) 로조사되었다. 그룹별차이는그룹 1과그룹 2, 그룹 3의순으로높았으며, 통계적으로는그룹 1과그룹 3과의차이가유의한결과를보였다 (p<0.01). S2 의결과는그룹 1에서 51.86±(12.86), 그룹 2에서 59.05±(11.46), 그룹 3에서 63.31±(9.51) 로그룹 1과그룹 2, 그룹 3의순으로낮았으며, 통계적으로는그룹 1과그룹 3과의차이가유의한결과를보였다 (p<0.01). S3와 REM sleep은그룹간유의한차이를보이지않았다. AHI의결과는그룹 1에서 36.41±(25.35), 그룹 2에서 28.44±(20.78), 그룹 3에서 3.21±(2.21) 로그룹별차이는그룹 1과그룹 2, 그룹 3의순으로높았으며, 그룹 1과그룹 3의차이가유의한결과를보였다 (p<0.01). 또한, TAI 의결과는그룹 1에서 31.84±(19.27), 그룹 2에서 26.21±(12.06), 그룹 3에서 14.21± (7.94) 로나타났고, 그룹별차이는그룹 1과그룹 2, 그룹 3의순으로낮았으며, 통계적으로는그룹 1, 그룹 2의두집단모두그룹 3과유의한결과를보였다 (p<0.01). 3. 수면질환유병율연구대상자의그룹간수면장애유병율을 Table 5에요약하였다. 전체 73명중정상소견이 20명 (27.4%) 이고, 53명 (72.6%) 에서비정상소견을보였다. 그룹 1의 34명중정상소견은 2명 (5.9%), 비정상소견은 32명 (94.1%) 으로조사되었고, 그룹 2는정상소견이 1 명 (4.5%), 비정상소견이 21명 (95.5%) 이었다. 그룹 3의결과는 17 명모두정상이었으며, 그룹간의유의한차이를보였다 (p<0.01). 4. 졸음운전과수면관련질환연구대상자의졸음운전사고경험자그룹 1+2와사고경험이없으면서수면다원검사결과정상판정을받은그룹 3과의수면다원검사결과에대한비교분석은 Table 6과같다. 얕은수면 S1은그룹 1+2에서 24.94±13.81, 그룹 3은 11.62±4.94 (p<0.01), 중간 Table 4. Differences of the polysomnography among groups Variables F/p N=192 N=34 N=22 N=17 SL 10.92±14.16 6.97±6.71 25.80±25.80 13.97±17.18 1.274/.286 RL 103.04±61.30 102.47±70.78 99.09±41.31 90.26±50.49.245/.783 S1 23.63±12.52 28.01±15.10 20.20±10.12 11.62±4.94 10.86/.000 a>c* S2 54.38±11.52 51.86±12.86 59.05±11.46 63.31±9.51 6.003/.004 a<c* S3 2.90±4.69 1.86±4.08 3.41±4.71 5.37±8.19 2.383/.100 REM Sleep 19.47±7.84 18.25±5.51 17.28±8.38 19.68±6.36.620/.541 AHI 31.71±23.54 36.41±25.35 28.44±20.78 3.12±2.21 14.64/.000 a>c* TAI 29.44±16.05 31.84±19.27 26.21±12.06 14.21±7.94 7.55/.001 a,b>c* Abbreviation: SL, sleep Latency (normal<15~20 min); RL, REM Latency. a, sleep more than six hours, traffic accidents group (group 1); b, sleep less than six hours, traffic accidents group (group 2); c, normal, accident-free group (group 3). S1, Stage 1 (normal<10%); S2, Stage 2 (normal=44 59%); S3, Stage 3 (normal=9.5 12%); REM Sleep, normal=19 26%; AHI, Apnea Hypopnea Index (normal<10); TAI: Total Arousal Index (normal<10). Table 5. Results of the prevalence of sleep disorders by groups Variables Total Group 1 Group 2 Group 3 N=73 (%) N=34 (%) N=22 (%) N=17 (%) X 2 /p Sleep Diagnosis Normal 20 (27.4) 2 (5.9) 1 (4.5) 17 (100) 58.738/.000* Abnormal 53 (72.6) 32 (94.1) 21 (95.5) 0 Group 1, sleep more than six hours, traffic accidents Group; Group 2, sleep less than six hours, traffic accidents Group; Group 3, normal, accident-free group.

Korean J Clin Lab Sci. Vol. 47, No. 4, Dec. 2015 223 Table 6. Results of the prevalence of sleep disorders by Drowsy driving accident experiences Variables Total Group 1 + 2 Group 3 N=73 N=56 N=17 F t SL 11.60±17.09 9.23±17.00 13.97±17.18.950 1.004 RL 95.70±55.49 101.14±60.50 90.26±50.49.138.673 S1 18.28±9.37 24.94±13.81 11.62±4.94 11.255* 6.049* S2 58.99±11.11 54.68±12.72 63.31±9.51 1.090 2.578 S3 3.92±6.27 2.47±4.36 5.37±8.19 8.966 1.402 REM Sleep 18.77±6.54 17.87±6.73 19.68±6.36.006.984 AHI 18.20±13.00 33.28±23.79 3.12±2.21 38.764* 9.352* TAI 21.92±12.42 29.63±16.91 14.21±7.94 4.549 5.191* 수면 S2는그룹 1+2에서 54.68±12.72, 그룹 3은 63.31±9.51 (p<0.05), AHI 는그룹 1+2에서 33.28±23.79, 그룹 3은 3.12±2.21 (p<0.01) 이었고, TAI 결과는그룹 1+2에서 29.63±16.91, 그룹 3 은 14.21±7.94 (p<0.05) 로그룹간유의한차이를보였다. SL, RL, S3, REM sleep에서는그룹간유의한차이가보이지않았다. 고찰본연구는졸음운전으로교통사고또는, 사고의위험을경험한일반운전자를대상으로수면관련질환의유병율을확인하기위해시행하였다. 연구결과, 졸음운전사고를경험한실험대상자 56명의수면다원검사결과에서폐쇄성수면무호흡증후군유병율이그룹 1에서 32명 (94.1%), 그룹 2에서 21명 (95.5%) 으로나타났으며, 다중수면잠복기검사결과에서 2명 (28.6%) 이기면증진단소견을보였다. 이러한결과들은졸음운전사고와수면관련질환의유병율이높은연관성 (p<0.01) 이있다는것을증명하였다. 주간졸음에대한선행연구결과에서도 Sassani 등 (2004) 은자동차사고위험성이정상인보다 1.7 7.4 배까지증가된다고하였으며, Choi와 Kim (2013) 는기면증은수면과각성주기에장애가있는질환으로주간졸음증을유발한다고하였다. Kang 등 (2011) 은폐쇄성수면무호흡증후군 (OSA; obstructive sleep apnea) 이대표적인수면분절의원인으로잠을자는동안심한코골이와무호흡으로수면장애를일으키고, 낮에심한졸림과피로감을일으킬수있다고보고하였고, Shiomi 등 (2002) 도수면무호흡증에의한주간졸음으로교통사고나업무중에위험을증가시키는것으로보고하였다. 수면다원검사결과에서도그룹 1은그룹 3과 S1 (p<0.01), S2 (p<0.01), AHI (p<0.01), TAI (p<0.01) 등의결과에서그룹2 보다증가되어있었으며, 수면의질이떨어지는것으로조사되었다. 따라서이러한결과로볼때, 그룹 2의일시적인수면부족으로인한교통사고보다정상시간의수면을취하고도수면관련질환때문에 생기는주간졸음증의영향으로졸음교통사고를유발하는그룹1에주목할필요가있다고사료된다. 이와관련하여 Kim과 Kim (2007) 은 AHI와의상관관계는목둘레가체질량지수보다더높았으며이는폐쇄성수면무호흡-저호흡증후군의원인으로전반적인비만도보다목과상기도의국소적인지방의두께가더중요할뿐만아니라혈압 (Kim, 2014), 염증반응 (Lee와 Kim, 2015) 과의연관성을찾을수있을것으로사료된다. 한편체위성수면무호흡환자는경증과중증도환자에서두드러지며, 체위성환자의중요지표는나이와 REM % 가증가할수록, 무호흡-저호흡지수가감소할수록체위성환자로보고한결과와유사성을찾을수있었다 (Kim 등, 2012). 수면습관에대한설문에서는잠자는동안얼마나자주깨는지 ( 그룹2>그룹1>그룹3) (p<0.01), 한번잠에서깬후다시잠들기얼마나어려운지 ( 그룹1>그룹2>그룹3) (p<0.05), 아침에얼마나빨리깨는지 ( 그룹1>그룹2>그룹3) (p<0.05), 아침에일어나기어려운정도 ( 그룹1>그룹2>그룹3) (p<0.05), 낮에졸리운정도 ( 그룹1>그룹2>그룹3) (p<0.01), 낮에피곤한정도 ( 그룹1> 그룹2>그룹3) (p<0.01) 를묻는질문에그룹간유의한차이를보였다. 이러한결과들을토대로수면질환과관련된주간졸음증을사전에감별을할수있는설문지를개발한다면, 주간졸음증에대한척도로활용이가능하고, 설문분석을통해수면질환에대한치료를받을수있게유도할수있는용도로사용할수있다고생각한다. 일반적으로졸음운전을전반적인수면시간의부족, 즉제한된수면으로평가하여졸음쉼터설치와같이, 충분한휴식을취하고운전을하도록안내및홍보를하고있는수준이지만, 교통사고의치사율과관련된심각한문제는수면관련질환에의한수면의분절로졸음운전을하게되는경우를간과하고있다고생각한다. 향후에는졸음운전사고경험자를대상으로수면다원검사와다중수면잠복기검사를시행하여수면관련질환의유병률을분석하는역학조사가진행될수있기를기대한다.

224 Ki-Bong Kim, et al. Sleep Disorder and Sleepy Drivers 결론적으로졸음운전교통사고경험자 56명 ( 그룹 1+2) 의 94.6% (53명) 에서수면질환에유병률을보였고, 그룹 1+2는그룹 3보다많은정상적인수면시간을가졌음에도깊은수면 (S3) 의분포는적고, 얕은수면 (S1) 이증가되어있었으며, TAI, AHI 지수는높아져서수면의질은떨어져있었다. 요약본연구는졸음운전사고경험자들의수면관련질환에관한유병율을조사하기위하여설문에응답한 192명중에서정상수면후사고경험자 34명 ( 그룹 1), 비정상수면후사고경험자 22명 ( 그룹 2), 수면다원검사결과가정상이면서사고경험이없는 17명 ( 그룹 3) 을대상으로평상시수면습관에대한설문결과와수면다원검사, 다중수면잠복기검사결과를비교분석하였다. 수면습관에대한설문에서잠자는동안얼마나자주깨는지 (p<0.01), 한번잠에서깬후다시잠들기얼마나어려운지 (p<0.05), 아침에얼마나빨리깨는지 (p<0.05), 아침에일어나기어려운정도 (p<0.05), 낮에졸리운정도 (p<0.01), 낮에피곤한정도 (p<0.01) 에서그룹간유의성이확인되었다. 또한, 졸음운전교통사고경험이있는연구대상자 56명중, 94.6% (53명) 에서수면관련질환이확인되었다. 따라서졸음운전교통사고가단순하게일시적수면부족만이원인이아니라수면시간이충분해도수면관련질환의영향으로주간졸음증이발생하고, 그로인해교통사고등이발생한다는것을확인하였다. 따라서본연구는졸음운전교통사고와수면관련질환사이의연관성에대해확인해보는것에의의가있었다. 또한이데이터들은수면질환과관련된졸음운전에대하여사회적대책마련을강구하는데필요한기초자료가되리라고사료된다. Acknowledgements: None Funding: None Conflict of interest: None References 1. Choi SJ, Kim KS. Structural equation modeling on health-related quality of life in patients with obstructive sleep apnea. J Korean Acad Nurs. 2013, 43:81-90. 2. Collop N. The effect of obstructive sleep apnea on chronic medical disorders. Cleve Clin J Med. 2007, 74:72-78. 3. Jo GH, Lee MS. The relation of commercial motor vehicle driver's fatigue and traffic accident. Korean Review of Crisis and Emergency Management. 2014, 10:1-14. 4. Kang SG, Kim SH, Park SJ, Kim HN, Park YJ, Song SW. The effects of non-surgical weight reduction on daytime sleepiness and fatigue in patients with obstructive sleep anpea. Journal of Korean Society for the Study of Obesity. 2011, 20:177-184. 5. Kim CS. The association between blood pressure and obstructive sleep apnea-hypopnea syndrome. Korean J Clin Lab Sci. 2014, 46:106-110. 6. Kim CS, Kim DS. Correlation of body mass index and neck circumference in patients with obstructive sleep apnea-hypopnea syndrome. Korean J Clin Lab Sci. 2007, 39:141-146. 7. Kim CS, Lee YS, Cho CU, Pae SH, Lee SA. The prevalence and characteristics of positional obstructive sleep apnea. Korean J Clin Lab Sci. 2012, 44:52-58. 8. Lee SH. Drowsy driving and traffic accidents. Sleep Med Psychophysiol. 2003, 10:84-87. 9. Lee SJ, Kim J. Inflammation and insufficient or disordered sleep. Korean J Clin Lab Sci. 2015, 47:97-104. 10. Pandi-Perumal SR, Verster JC, Kayumov L, Lowe AD, Santana MG, Pires ML, et al. Sleep disorder, sleepiness and traffic safety: a public health menace. Braz J Med Biol Res. 2006, 39:863-871. 11. Sassani A, Findly L, Kryger M, Goldlust E, George C, Davidson T. Reducing motor-vehicle collisions, costs, and fatalities by treating obstructive sleep apnea syndrome. Sleep. 2004, 27:453-458. 12. Shiomi T, Arita AT, Sasanabe R, Banno K, Yamakawa H, Hasegawa R, et al. Falling asleep while driving and automobile accidents among patients with obstructive sleep apnea-hypopnea syndrome. Psychiatry Clin Neurosci. 2002, 56:333-334. 13. Siedlecka J, Bortkiewicz A. Driving simulators in risk assessment of traffic accident among drivers with obstructive sleep apnea. Med Pr. 2012, 63:229-236. 14. Ward KL, Hillman DR, James A, Bremner AP, Simpson L, Cooper MN, et al. Excessive daytime sleepiness increases the risk of motor vehicle crash in obstructive sleep apnea. J Clin Sleep Med. 2013, 9:1013-1021.