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Abstract

The association between motor vehicle accidents (MVAs) and obstructive sleep apnea syndrome (OSAS) has always been quantified as risk of MVAs for individual drivers with OSAS. We evaluated the expected injured patients per year attributable to OSAS-dependent MVAs in a general population. By combining OSAS prevalence and OSAS-dependent MVAs odds ratio, we assessed the population attributable fraction (PAF), an epidemiological tool that can be used to quantify the proportion of road traffic injuries (RTIs) attributable to OSAS. For an apnea hypopnea index >5, the weighed median and combined average of OSAS prevalence were 4.4 (95% confidence interval (CI): 3.7–7.5) and 4.7 (95% CI: 4.2–5.2), respectively; values of risk of OSAS-dependent MVAs were 2.83 (95% CI: 2.72–3.08) and 2.52 (95% CI: 2.07–3.08), respectively. The PAF showed weighed median and combined average values of 6.6 (95% CI: 4.3–9.8) and 7.3% (95% CI: 6.0–13.5), respectively. Our results show that about 7% of RTIs for a population of male drivers involved in MVAs are attributable to OSAS. This value can be used to assess the potential impact, on the reduction of incidence of the motor vehicle injuries, of prevention programs aimed at reducing the number of subjects with an undiagnosed and/or untreated OSAS.

Keywords

Obstructive sleep apnea syndrome road traffic injuries motor vehicle accidents population attributable fraction public health

Introduction

Obstructive sleep apnea syndrome (OSAS) is a chronic respiratory disease characterized by recurrent sleep-related obstruction of the upper airway.¹ OSAS prevalence is estimated to range between 3.1% and 7.5% of the adult male population,² and the most common symptoms are habitual snoring (HS), observed apnea, and excessive daytime sleepiness (EDS).³ Subjects with OSAS have a two- to seven-fold increased risk of being involved in motor vehicle accidents (MVAs).^{4

–13} The treatment of OSAS with continuous positive airway pressure reduces the number of MVAs compared to the number observed in the general population¹⁴ with saving of lives and reduction in direct and indirect medical costs.¹⁵ In view of the increasing impact that OSAS-dependent MVAs has on health and social systems¹⁶ in Australia, the National Transport Commission and Austroads have indicated the medical standards for drivers with OSAS, aimed at reducing the risk of MVAs.¹⁷ Similarly, in the United States, a protocol has been validated for the screening and monitoring of commercial vehicle drivers with a clinical suspicion or diagnosis of OSAS.¹⁸ Very recently, the Commission Directive 2014/85/EU¹⁹ updated the previous one²⁰ by including the OSAS among the clinical conditions of Annex III. This update certifies that the management of OSAS is a public health problem for the European Union and will determine the need for a new approach to health systems on physical and mental qualifications for applicants or drivers with OSAS.

Identifying risk factors is a starting point from which to determine the epidemiological elements for diagnosis, treatment, and monitoring of any event that could affect health. It should be a major priority of medical assessment centers as a public safety policy. Methodologically, the analysis of morbidity and mortality due to known risk factors has frequently been conducted in the context of individual risk factors and in a limited number of settings. According to this analysis, the association between MVAs and OSAS has always been quantified by means of the odds ratio (OR)^6,8,9 or the relative risk (RR),^11,12 which have proven the increased risk of MVAs for individual drivers with OSAS. Although OR and RR are effective tools for measuring the individual risk of MVAs in OSAS drivers, they do not assess the incidence of MVAs, that is, the new cases expected in a specific temporal window in a general population. This methodological approach, which allows the overall risk for a general population to be inferred from the individual risk, has been proposed as the most appropriate for the development of prevention programs in the interest of public health.²¹ In agreement with this methodological approach, the population attributable fraction (PAF) is a specific epidemiological tool that can be used to quantify the proportion of road traffic injuries (RTIs) attributable to OSAS.²¹

The aim of this study was to estimate the overall risk for MVAs attributable to OSAS in a general population of male drivers. We then calculated the OSAS prevalence and risk of OSAS-dependent MVA OR. By combining these results, we assessed the PAF to quantify the proportion of RTIs attributable to OSAS. The evaluation of these parameters establishes the percentage of MVAs attributable to OSAS in a specific temporal window and adds value to specific prevention programs aimed at reducing the number of subjects with an undiagnosed and/or untreated OSAS.

Methods

Identification of studies

A systematic literature search was performed by using PubMed MEDLINE (up to April 2014). Articles were identified by using keywords (sleep apnea, obstructive sleep apnea, OSAS, prevalence, car accident, traffic accidents, road accidents and vehicle accidents) separately or in combination. Only the full-text articles showing prevalence data on OSAS in adult males and/or quantitative evaluation of the risk of MVAs, by means of OR or RR, have been considered in this study.

According to the definition of OSAS proposed by the American Academy of Sleep Medicine,²² we used the criteria of the apnea hypopnea index (AHI) >5 cutoff in the presence of EDS as a main symptom among the other possible ones. We did not distinguish whether EDS was assessed on a subjective basis, that is, Epworth Sleepiness Scale, or objective basis, that is, multiple sleep latency test or maintenance of wakefulness test. For our scope, according to Ip,²³ it was sufficient that the subject was indicated in the studies as suffering from EDS.

For the prevalence data, only population-based studies were considered with the following inclusion criteria: (a) sampling method representative of general population of adult males; (b) subject aged between 20 and 70 years; (c) visit or questionnaire to detect the main features (HS, obstructive apnea, EDS, obesity and systemic hypertension) suggestive of OSAS; and (d) full nighttime polysomnography (PSG) with the assessment of AHI for all the subjects with a clinical suspicion of OSAS or for a large sample of symptomatic subjects representative of all of them. With regard to population representativeness, two main sampling methods were considered acceptable for inclusion: (1) participation in the study of all office-based workers included in a work health insurance program or working for one or more large agencies; and (2) random or cluster sampling in the general population of an entire territory and/or community. With the first method, categories particularly at risk of MVAs due to OSAS, such as professional drivers, are automatically excluded. Similar to the second method, risky groups are not overrepresented.

The criteria for the inclusion of articles on the risk of MVAs associated with OSAS were as follows: (a) male subjects mean group aged between 40 and 60 years (standard deviation approximately + 10 years); (b) at least case–control type studies; (c) the number of controls not fewer than around 20% of cases; (d) explicit criteria for defining controls as non-OSAS subjects; (e) questionnaire or register for reporting MVAs in the observational period; and (f) full nighttime PSG with the assessment of AHI for all cases but not necessarily for controls.

Seven articles for OSAS prevalence^{3,23

–28} and nine for risk of MVAs associated with OSAS^{4

–9,11
–13} have met the above-mentioned criteria and were then retained for the meta-analysis.

Statistical analysis and epidemiological analysis model

According to Young et al.,²⁵ we explored three levels of AHI cutoff in assessing OSAS prevalence: AHI > 5; AHI > 10; AHI > 15 in the presence of EDS. We did it for each study depending on the study data. The proportions of OSAS cases in the observed samples were considered as measures of prevalence.

According to the nine studies^{4

–9,11
–13} remaining for the meta-analysis of the risk of OSAS-dependent MVAs, the following three levels of AHI cutoff were explored: >5; >10; >20. For studies not showing the number of OSAS, controls, OSAS and controls >1 MVA, we have calculated these data by using the percentage of males and the number of OSAS and controls with or without a MVA shown in the same studies. For the MVAs risk studies, the risk comparison of cases (OSAS subjects) versus controls (non-OSAS subjects) was made on the probability of having at least 1 MVA in the observed period. As most of the risk studies we considered had a case–control design, the OR was assumed to be a proper measure of risk.

In both of the analyses (prevalence and risk), the measures (proportions and ORs) from the different studies were compared with each other for levels and significance. The confidence intervals (CIs) for the prevalence measures were calculated based on Wald normal standardized distribution for proportions. The CIs for the risk measures were calculated based on Fisher’s exact probability distribution for combined mean ORs and standardized Student’s t-test distribution (standard error corrected for median) for weighed median ORs. The values of p < 0.05 were considered significant.

OSAS prevalence and MVA ORs have been calculated on the whole meta-analysis sample obtained by merging the basic data derived from the studies taken into consideration (Tables 1 and 2). The data on the observed subjects (OSAS, controls, and the number of subjects with MVAs) were then combined in meta-analysis indicators (combined average prevalence and combined OR) to obtain a unique response from this study combining the whole observed data. This methodological approach reduces the uncertainty of the estimate but exhibits the risk of biased results when the basic data are obtained from studies with a larger number of observed subjects or with outliers. To control this risk, we have calculated the prevalence and risk measures for each included study obtaining the weighed median prevalence and weighed median OR. When the median and the combined average values of the prevalence or risk indicator are concordant, the estimate is considered not distorted. Once the OSAS prevalence and risk of MVAs associated with OSAS in the adult male population had been obtained, we assessed the PAF. The PAF is the share of RTIs attributable to OSAS given the prevalence (P) of this factor in the population and its RR:

Table 1.

Characteristics of the OSAS prevalence studies in male subjects.

Author and reference number	Population studied—sampling criteria	Age (years)	Questionnaires and/or visits (N)	PSG sampling	PSG (N)
Cirignotta²⁴	Survey population	30–69	1170	Randomized: 40 every-night snorers	40
Young²⁵	Office-based workers Three-state agencies	30–60	1670	Randomized: 25%: no habitual snorers 100%: habitual snorers	352
Bixler²⁶	General population Two counties’ age-stratified random sampling	20–100	4364	Symptoms: HS, EDS, obesity, and hypertension 3%: no symptoms 9%: 1 symptom 32%: 2 symptoms 45%: 3 symptoms 70%: 4 symptoms	741
Duran³	General population One town cluster sampling	30–70	1050	Randomized: 54%: no OSAS 82%: OSAS	324
Ip²³	Office-based workers Three public offices	30–60	784	20%: natural 100%: concordance age and BMI for habitual snorers and nonhabitual snorers	153
Udwadia²⁷	Consecutive patients work insurance health check	35–65	658	Randomized: 25%: no habitual snorers 100%: habitual snorers	250
Kim²⁸	All residents Ansan community	40–69	2523	Randomized: 20%: non-HS 50% HS	309

OSAS: obstructive sleep apnea syndrome; PSG: polysomnography; HS: habitual snoring; EDS: excessive daytime sleepiness; BMI: body mass index.

Table 2.

Characteristics of the OSAS-related MVA risk studies in male subjects.

Author and reference number	Type of study	Age (years)	OSAS	Sleepiness	Controls	Case–control matching	MVA observational period
Aldrich⁴	Case–control	>16	Consecutive patients sleep unit	MSLT	Medical center employees, spouses of patients with sleep disorders	Age and sex	3 years, retrospective
Young⁵	Longitudinal	30–60	Office employees Three-state agencies	ESS MSLT	Office employees Three-state agencies		5 years, prospective
Barbè⁶	Case–control	>18	Consecutive patients sleep unit AHI > 20 and EDS	ESS	Nonmedical workers or visitors, nonsnorers, and no OSAS	Age and sex	3 years, retrospective
George⁷	Case–control	>25	Consecutive patients sleep unit AHI > 10		Subset ministry of transportation accident database	Age and sex	5 years, retrospective
Teràn-Santos⁸	Case–control	30–70	All patients with AHI ≥ 5	ESS	Random patients primary health care center	Age and sex	11 months, prospective
Horstmann⁹	Case–control	>18	Consecutive patients AHI > 10	ESS	Outpatient osteoarticular diseases	Age and sex	3 years, retrospective
Barbè¹¹	Case–control	>18	Consecutive patients sleep unit AHI > 20 and EDS	ESS	Nonmedical workers or visitors, nonsnorers, and no OSAS	Age and sex	2 years, retrospective; and 2 years, prospective
Mulgrew¹²	Case–control	>18	Consecutive patients sleep unit	ESS	Insurance database	Age, sex, residence, and type driving license	3 years, retrospective
Komada¹³	Case–control	>18	Consecutive patients AHI > 5	ESS	Drivers renewing license	Age, sex	5 years, retrospective

OSAS: obstructive sleep apnea syndrome; MVA: motor vehicle accident; MSLT: multiple sleep latency test; ESS: Epworth Sleepiness Scale; AHI: apnea hypopnea index; EDS: excessive daytime sleepiness.

P A F = \frac{P (R R - 1)}{P (R R - 1) + 1},

where P is the observed prevalence of OSAS. In our analysis based on case–control studies, we can correctly assume RR = OR.

In order to quantify the effect of OSAS on RTIs, we have to assume that the risk of injury is not smaller than that of the MVAs. It is a conservative approach. In effect, data from the existing studies confirm that the risk of RTIs associated with OSAS is greater than that with MVAs.^9,12 These observed data are consistent with the assumption that the greater risk of injury in the presence of OSAS factor is determined by the expected greater severity of the consequences of an accident in those who fell asleep, because not having the possibility of reacting to the crashing event in order to reduce or avoid it, they are expected to more likely incur in severe injury or death.

Lastly, the prevalence of OSAS is generally assessed in general population samples. In order to calculate the PAF, we have to assume that the prevalence of OSAS in the general population is similar to the one assessed in the drivers’ population. A good benchmark for this purpose is the study of Philip et al. In a large sample of registered highway drivers (n = 35,004), 5.2% of them reported OSAS.²⁹

Results

The characteristics of studies identified for the meta-analysis are shown in Tables 1 and 2, respectively. In assessing the OSAS prevalence, the figures of weighed median and combined average prevalence for adult men at the three OSAS severity levels are shown in Table 3. For some studies, it is possible to calculate OSAS prevalence only at some AHI levels. For an AHI ≥ 5, the estimated prevalence of OSAS expressed as weighed median and combined average was 4.4 and 4.7%, respectively. The strict concordance among these values makes it possible to consider the estimated prevalence of OSAS not distorted. A strict concordance was also found for the other AHI levels.

Table 3.

OSAS prevalence studies and meta-analysis results.^a

	Subjects	AHI > 5		AHI > 10		AHI > 15
Author and reference number	N	%Prevalence	95% CI	%Prevalence	95% CI	%Prevalence	95% CI
Cirignotta²⁴	40	na	na	2.7	2.0–3.6	na	na
Young²⁵	1670	3.7	2.9–4.7	2.3	1.7–3.2	1.4	0.9–2.1
Bixler²⁶	236	na	na	1.2	0.7 -1.9	na	na
Duran³	1050	5.5	4.2–7.1	3.4	2.4–4.7	na	na
Ip²³	777	4.1	2.8–5.8	3.2	2.1–4.7	3.1	2.0–4.6
Udwadia²⁷	658	7.5	5.6–9.7	6.1	4.4–8.2	5.4	3.9–7.5
Kim²⁸	2523	4.4	3.6–5.2	na	na	na	na
Weighed median		4.4	3.7–7.5	3.2	1.6–5.7	3.1	1.4–5.4
Combined average		4.7	4.2–5.2	3.1	2.7–3.5	2.7	2.1–3.3

OSAS: obstructive sleep apnea syndrome; AHI: apnea hypopnea index; CI: confidence interval; na: not applicable.

^aIn assessing OSAS prevalence, the figures of weighed median and combined average prevalence for adult men are shown at three OSAS severity levels.

Table 4 shows the results of the meta-analysis carried out with the data obtained from the OSAS-dependent MVAs of the selected studies. The risk of MVA, expressed as OR with CI of at least 1 MVA for OSAS subjects versus non-OSAS subjects, we calculated for each study ranges from 1.45 (95% CI: 1.08–1.95), using the data from the study of George et al.⁷, to 6.00 (95% CI: 1.93–21.98), with the data from Teràn-Santos et al.⁸ The weighed median OR independent of OSAS severity level is 2.83 (95% CI: 2.34–3.65). It is the same value that we observed for an AHI ≥ 5 cutoff. For combined average OR, we observed a slightly lower value of 1.86 (95% CI: 1.61–2.15) due to the lower risk difference among OSAS and non-OSAS subjects observed in the large George et al.’s study sample.⁷ In any case in the studies with AHI ≥ 5 cutoff for the OSAS severity, the combined average OR is equal to 2.52 (95% CI: 2.07–3.08). The strict concordance among AHI ≥ 5 median and combined values shows that the estimated risk of MVAs associated with OSAS can be considered not distorted.

Table 4.

Results of the meta-analysis carried out with the data obtained from the OSAS-dependent MVAs of the selected studies.^a

Author and reference number	AHI cutoff	OSAS (N)	Controls (N)	OSAS >1 MVA (N)	Controls >1 MVA (N)	OR	95% CI	p
Aldrich⁴	na	181	35	24	2	2.52	0.58–22.99	0.20
Young⁵	>5	353	560	114	75	3.08	2.19–4.35	<0.001
Barbè⁶	>20	59	59	19	10	2.33	0.90–6.24	<0.05
George⁷	>10	405	523	136	135	1.45	1.08–1.95	<0.01
Teràn-Santos⁸	>10	19	169	15	56	6.00	1.93–21.98	<0.001
Horstmann⁹	>10	114	129	12	4	3.68	1.21–11.13	<0.02
Barbè¹¹	>20	76	73	24	9	3.28	1.32–8.69	<0.005
Mulgrew¹²	>5	643	643	160	75	2.72	1.97–3.77	<0.001
Komada¹³	>5	616	600	75	28	2.83	1.81–4.43	<0.001
Totals
Weighed median
AHI > 5		1612	1803	349	178	2.83	2.72–3.08
AHI > 10		538	820	163	195	3.68	1.45–6.00
AHI > 20		135	132	43	19	2.81	2.33–3.28
Total		2466	2791	579	394	2.83	2.34–3.65
Combined average
AHI > 5		1612	1803	349	178	2.52	2.07–3.08
AHI > 10		538	820	163	195	1.39	1.08 -1.79
AHI > 20		135	132	43	19	2.78	1.46–5.40
Total		2466	2791	579	394	1.86	1.61–2.15

OSAS: obstructive sleep apnea syndrome; MVA: motor vehicle accident; na: not applicable; AHI: apnea hypopnea index; OR: odds ratio; CI: confidence interval.

^aThe risk of MVAs is expressed as OR with CI of at least one MVA for OSAS subjects versus controls. The figures of weighed median and combined average prevalence are shown at three OSAS severity levels.

As described below, the attributable-to-OSAS risk fraction values of MVAs are 6.6% (95% CI: 4.3–9.8) and 7.3% (95% CI: 6.0–13.5) using combined and median values, respectively.

\begin{aligned} ^{OSAS} {P A F}_{c o m b i n e d} = 100 \times \frac{0.047 \times 2.5 - 0.047}{1 + (0.047 \times 2.5 - 0.047)} \\ = 100 \times 0.066 = 6.6 % \\ (95 % C I : 4.3 - 9.8) \end{aligned}

\begin{aligned} ^{OSAS} {P A F}_{m e d i a n} = 100 \times \frac{0.044 \times 2.8 - 0.044}{1 + (0.044 \times 2.8 - 0.044)} \\ = 100 \times 7.3 = 7.3 % \\ (95 % C I : 6 .0 - 13.5) \end{aligned}

Discussion

The meta-analysis of the known data on the prevalence of OSAS in male drivers^{3,23

–28} and on the risk of MVAs associated with OSAS^{4

–9,11
–13} showed estimated values of 4.4–4.7% (Table 3) and of 2.8–2.5% (Table 4), respectively. The present results, being within the ranges reported in scientific literature, are consistent with the previously published data. This has been observed at any severity levels of OSAS and individual risk for OSAS-dependent MVAs. By combining these results, we detected PAF values of 6.6–7.3%. The prevalence data in the literature do not refer to the prevalence of OSAS in drivers only, but refer to that in the general population. As the general population includes drivers and nondrivers, these prevalence data could not be directly used in the calculation of the fraction of risk of MVAs attributable to OSAS, which depends on the drivers alone. The values of median (4.4%) and combined (4.7%) prevalence found in the general population are consistent with the OSAS prevalence (5.2%) observed in 35,004 highway drivers, the largest sample of drivers ever studied to date.²⁹ It is correct to assume that the prevalence of OSAS in drivers is approximately the same as that observed in the general population including drivers and nondrivers. We can use the data on prevalence in the general population to detect the PAF as we did, to quantify the share of RTIs attributable to OSAS.

The PAF value we found shows that around 7%, ranging from 6.6% to 7.3%, of RTIs for adult male drivers involved in a MVA are attributable to OSAS. This is neither a simple measure of the presence of OSAS in the population nor a measure of individual risk of OSAS-dependent RTIs. This percentage value allows us to quantify the expected number of new injured patients per year attributable to OSAS. If we apply this proportion to the total number (24,228) of fatal RTIs per year for adult male drivers observed in the EU member states,³⁰ we obtain an incidence of 1696 fatal RTIs in adult male drivers. This is a very conservative assessment of the impact of OSAS on RTI incidence for different reasons. Firstly, the adult male drivers are not the only driving group affected by OSAS. Secondly, the accidents attributable to OSAS drivers may also affect passengers in the same vehicle, the occupants of other involved vehicles, or pedestrians. The data available in the studies considered for the current analysis do not consent to completely address these aspects. Furthermore, in a conservative approach we assumed the risk of injury attributable to a MVA to be roughly equal to the risk of MVAs. In reality, as discussed in the “Methods” section, we expect that the risk of severe injury or death is not just equal but greater than the risk of MVAs in case of OSAS. Therefore, the figures indicated above represent the minimal assessment of death cases attributable to OSAS.

The PAF method enables us to estimate not only the number of RTIs attributable to OSAS but also the number of avoidable trauma cases. According to the World Health Organization’s injury pyramid,³¹ the above-mentioned measures are fundamental measures of the burden of OSAS in the population, in terms of mortality and morbidity. The fatal and nonfatal injuries classified by diagnosis would permit an assessment of the impact of OSAS, in terms of trauma severity and disability, in specific population groups or in the whole population, supplying the tools for the estimation of the healthcare (incidence-based or bottom-up approach) and societal costs (human capital approach) due to the loss of productivity in disabled or dead persons. The existence of these complex indicators calculable on the basis of the OSAS-related trauma incidence obtained with the PAF method enables us to assess the effectiveness of prevention intervention on the OSAS effects, in terms of a reduction in the number and level of severity of OSAS-related injuries and likewise in the costs of health and social care. In other words, the percentage value we found by means of the PAF epidemiological method is a measure of the impact of OSAS on the health status of the entire adult male population in an observed country in a specific temporal window.

We did not take into account the potential confounding effects, such as other risk factors influencing sleepiness or performance at the wheel (alcohol consumption, drug use, visual-refraction disorders, diabetes, etc.), present in the same subjects affected by OSAS or in the controls. Indeed, most of the studies that we considered to calculate the prevalence of OSAS and the risk of MVAs associated with OSAS had already taken into account the major confounding factors. Nevertheless, our estimation of the incidence of RTIs associated with OSAS doesn’t exclude that it could at least partially be affected by the effect of other possible confounding factors.

This is the first study using the PAF to quantify new cases of RTIs attributable to OSAS expected in a specific temporal window. The value of about 7% is a measure of the share of MVA incidence in male drivers determined by OSAS. Therefore, it is an assessment of the maximum potential impact of prevention actions on these people targeted at reducing the number of OSAS subjects that have not been diagnosed or treated. Consequently, it is an assessment of the proportion of the potentially avoidable trauma cases.

Footnotes

Conflict of interest

The authors declared no conflicts of interest.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Motor vehicle accidents and obstructive sleep apnea syndrome