Associations Between Weekly Commute Time, Weekday Sleep Duration, and Driving Fatigue Among Working Adults in Israel

Abstract

Background

Long commutes are recognized as an occupational health risk and road safety risk. In high-traffic countries, prolonged commuting may represent a potentially significant yet underexplored public health concern, particularly with respect to gender-specific vulnerability patterns. This study thus examines the association between weekly commute time, weekday sleep duration, and driving fatigue via a gender-based analysis.

Methods

Data relating to 3,387 employed adults were drawn from the 2023 Israel Social Survey. Long commuting was defined as ≥15 hours/week; 20.2% of the survey respondents were long commuters, 54.7% were women, and 45.3% were men. Outcomes measured included insufficient sleep duration (<6.5 hours) and self-reported driving fatigue. Multivariable logistic regression models were stratified by gender and adjusted for demographic and work-related variables.

Results

Long commuting was linked to insufficient sleep duration [odds ratio (OR) = 1.56] and increased driving fatigue (OR = 1.71) among women and with driving fatigue (OR = 2.13) but not significantly with sleep duration among men. Health behaviors differed according to gender, with women with long commutes engaging in more physical activity (46.2% vs. 40.3%) and exhibiting lower obesity rates (18.1% vs. 19.3%) and men being less active, more obese, and smoking more frequently.

Conclusion

Extended weekly commuting appears to be an independent gender-specific occupational health risk factor, exerting effects on sleep, fatigue, and health behaviors. Women report more sleep disruption, while men experience higher fatigue and adverse health behaviors. These findings highlight the need for gender-sensitive health interventions, flexible work policies, improved transportation infrastructure, and recognition of commuting as an important modifiable determinant of worker health.

1. Introduction

As urban sprawl, housing shortages around employment centers, and persistent spatial inequalities have led to longer daily travel for many workers, commuting has become a major feature of working populations across the globe. Multiple national studies [[1], [2], [3], [4]] document the association between extended commuting and adverse physical/psychological health effects. A lengthy commute time also often coincides with high traffic congestion, making daily travel more stressful and unpredictable. What was once perceived as a neutral or unavoidable aspect of work is thus now recognized as a meaningful social determinant of health and well-being with serious implications for both physical and mental health [2,3].

A growing body of epidemiological and occupational health research demonstrates that long commutes—particularly those exceeding one hour per direction or reaching 15 hours per week—are associated with reduced physical activity and poorer sleep quality [2,5,6]. Commuting by car rather than active or public transport is similarly linked with increased psychological distress, lower life satisfaction [4], and higher rates of overweight and obesity [2,7]. Commuting may reduce opportunities for health-promoting activities, social interaction, and restorative rest; these effects may be direct (physiological fatigue and time scarcity) or indirect [1,8].

While numerous studies have explored the health implications of long commuting, most have focused on Western Europe and North America, paying relatively limited attention to smaller, high-traffic-density countries with constrained public transportation systems, such as Israel [[2], [3], [4]]. Given its high population density and centralized employment structure, Israel constitutes a prime test case for examining the health effects of long commuting. According to the 2023 Israel Social Survey [9], one in five employed adults in Israel commutes more than 15 hours per week.

To our knowledge, this is the first nationally representative study in Israel to jointly examine the interrelated effects of weekly commute duration, weekday sleep duration, and driving-related fatigue via a gender-stratified approach. Driving fatigue doubling or tripling accident risk, these outcomes are directly relevant to both road safety and public health [10]. Gender differences in commuting-related stress and coping mechanisms may create distinct vulnerability patterns [3,11].

One of the most critical links between lengthy commute time and adverse health outcomes is sleep disruption. Sleep is a biological necessity, vital to cognitive performance, emotional regulation, immune function, and cardiovascular health. Empirical evidence indicates that each additional hour of daily commuting reduces weekday sleep by about 15 minutes, increasing cumulative “sleep debt” and potential functional impairment [6]. Actigraphy-based measurements evince that workers, who commute long distances, report significantly reduced sleep duration, with commutes of 60 minutes or more being associated with approximately 15 minutes less weekday sleep.

Long commuting also affects sleep quality and regularity. Workers with lengthy commutes frequently report symptoms of insomnia, difficulty falling asleep, and frequent awakenings [5,12]. According to a large-scale Korean study, employees with commutes exceeding 120 minutes per day were significantly more likely to experience insomnia symptoms, particularly when long commuting coincided with working long hours [10].

Long commuting is also associated with irregular sleep schedules and circadian misalignment, both of which contribute to poorer sleep quality and high fatigue levels among long-distance commuters [6,7]. Mechanistically, these disruptions arise from both time constraints and the cumulative stress caused by lengthy commuting. Commute-related stress may extend into the evening, impairing the ability to unwind and recover from work demands [8].

On the biological level, the association between long commuting, sleep disruption, and adverse health outcomes may reflect links between chronic insomnia and elevated evening cortisol levels. These may delay the onset of the quiescent phase of hypothalamic–pituitary–adrenal axis activity [13,14]. Stress and poor sleep thus mutually reinforce one another, creating a self-perpetuating cycle that undermines health, safety, and productivity [12,10].

Driving fatigue represents another critical dimension of long commuting direct health risk. Experimental and epidemiological studies demonstrate that poor sleep quality and sleep deprivation significantly impair driving performance, leading to slower reaction times, reduced attention, and poorer decision-making. These effects are comparable to the effect of moderate alcohol intoxication [15].

Work-related time pressure and occupational stress also contribute to cognitive failure, near-accidents, and commuting-related road injuries, in particular among working-age individuals traveling in private vehicles [[16], [17], [18]]. Job-related stress heightens the risk of driving incidents [17], underscoring the well-established importance of addressing occupational factors in road safety. Recognizing commuting accidents as occupational hazards, the European Agency for Safety and Health at Work highlights their relevance for employers and public health systems alike [18].

The health consequences of commuting can be interpreted via the allostatic load model, according to which repeated exposure to stressors such as long, unpredictable, or uncomfortable commutes creates a cumulative physiological burden [19,20]. These effects—including dysregulated cortisol levels, impaired sleep, and chronic fatigue—are unevenly gender distributed, with women often experiencing the combined demands of paid work and unpaid domestic responsibilities, limiting recovery time and increasing stress [21].

Complementarily, gender differences in commuting behavior can be further understood through the Job Demands–Resources (JD-R) model, which conceptualizes long commuting as a job-related demand that depletes personal resources such as time and energy [22]. According to this framework, strain increases when recovery resources—such as flexible working hours, rest periods, and emotional support—are limited. Gender-stratified analyses indicate that women often experience greater discomfort, lower travel satisfaction, and more pronounced time constraints, all of which heighten commuting-related stress [11].

Integrating the JD-R model with allostatic load theory provides a comprehensive framework for understanding commuting as a structural stressor. While this paradigm focuses on the depletion of psychosocial resources, allostatic load theory explains how repeated exposure to such demands leads to cumulative physiological wear and tear. Together, these perspectives suggest that long commuting is associated with sleep disruption and driving fatigue, with women potentially being more vulnerable due to constrained recovery time related to their greater share in domestic responsibilities.

This study thus examines the relationship between weekly commute time, weekday sleep duration, and driving-related fatigue among employed adults in Israel. Using gender-stratified analyses and accounting for sociodemographic and occupational factors, we assess whether long weekly commutes (≥15 hours) are associated with reduced sleep and increased driving fatigue.

2. Materials and methods

2.1. Data source

The data were drawn from the 2023 Israel Social Survey conducted by the Israel Central Bureau of Statistics (CBS) [9]. This annual, nationally representative, cross-sectional survey of individuals aged 20+ years is designed to monitor quality of life, health, employment, and social integration. The data were collected through face-to-face interviews by means of a multistage stratified sampling design, thereby ensuring adequate representation by age, sex, ethnicity, geographic location, and socioeconomic background. Each respondent was assigned a population weight (expansion factor). All the analyses incorporated these weights, allowing the analytical sample to represent approximately 3.2 million employed adults in Israel.

Fig. 1 illustrates the stepwise inclusion and exclusion process adopted in order to derive the final analytic sample. Of the 6,474 survey respondents, 5,888 were aged 20–74 years. After excluding nonemployed individuals, 3,948 respondents were employed. Professional drivers were subsequently excluded, yielding 3,842 employed nonprofessional workers (from the professional driving point of view). The final analytic sample consisted of 3,387 workers who physically commuted to their workplace at least three times per week.

Fig. 1.

Flowchart of participant selection and derivation of the final analytic sample from the 2023 Israel Social Survey.

2.2. Study population

The analytical sample consisted of 3,387 employed nonprofessional drivers aged 20–74 years, who commuted to work at least three times per week. This age range corresponds to the working-age population covered by the Israel Social Survey. Professional drivers were excluded to avoid confounding related to occupational driving exposure and fatigue patterns that differ substantially from those of nonprofessional commuters. Using population weights provided by the Israel CBS, the sample represents approximately 3.2 million employed adults in Israel.

2.3. Weekly commute time

Weekly commute time was calculated by multiplying the number of workplace attendance days per week by the reported one-way commute time, the result being doubled in order to account for round trips. A respondent working three on-site days with a 45-minute one-way commute thus had a total of 4.5 commuting hours per week. Long commuting was defined as ≥15 hours per week (upper quartile), representing workers at the greatest estimated risk of adverse health effects. Defined a priori, this cutoff was chosen in order to isolate workers with the highest exposure to commuting-related time burden, in line with previous epidemiological studies linking prolonged commuting with adverse sleep, fatigue, and health outcome.

2.4. Outcome variables

Primary outcomes included weekday sleep duration (continuous and dichotomized: ≥6.5 h vs. < 6.5 h) and self-reported driving fatigue (yes/no), based on questions from the Israel CBS Social Survey. Weekday sleep duration was assessed by the following question: “On a typical weekday, how many hours do you sleep?” and insufficient sleep by the following question: “Do you usually get enough sleep on weekdays?”

Driving fatigue was measured via the following question: “In the past month, to what extent has fatigue endangered your safety while driving?” Participants who responded “to a great extent” were classified as having high-risk driving fatigue. This item refers specifically to fatigue while driving; analyses of driving fatigue were restricted to respondents who commute by private vehicle. The 6.5-hour cutoff followed the American Academy of Sleep Medicine guidelines [23].

2.5. Covariates

The covariates were selected a priori on the basis of a review of the literature. They were considered potential confounders of the associations between weekly commute time, weekday sleep duration, and driving fatigue. All models controlled for known sociodemographic and occupational factors—age, ethnicity (Jewish/Arab), academic education, per capita household income, managerial position, and weekly working hours. Interview timing relative to 7 October, 2023 (before/after the Iron Swords War), was included to account for potential effects of the national crisis on reported working conditions, sleep, and stress.

2.6. Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics. The interaction between commute time and gender being statistically significant (p < 0.001), separate gender-stratified multivariable logistic regression models were estimated for insufficient sleep duration and high-risk driving fatigue. The results were presented as adjusted odds ratios (AORs) with 99 percent confidence intervals (CIs), with a p value < 0.001 being considered statistically significant.

Four sequential models were constructed using a stepwise approach in order to assess the robustness of the association between weekly commute time and the outcomes of interest. Model 1 included weekly commute time only (≤14 h vs. ≥15 h). Model 2 also adjusted for demographic variables (age and ethnicity). Model 3 further adjusted for occupational variables (managerial position and weekly working hours). Model 4 incorporated weekday sleep duration as a proximal behavioral factor, potentially linking long commuting to driving fatigue. In this model, academic education and per capita household income were entered alternately rather than simultaneously. Hereby, we sought to avoid multicollinearity between these two indicators of socioeconomic position. All the models related to interview timing that took 7 October 2023 into account. The results are presented as AORs with 99% CIs. Statistical significance was set at p < 0.001 to account for multiple testing.

3. Results

The total sample included 3,387 respondents—1,853 (54.7%) women and 1,534 (45.3%) men. A total of 683 participants (20.2%) were classified as long commuters (≥15 hours per week) and 2,704 (79.8%) as short commuters. Examination of background characteristics revealed significant differences between women with short/long commutes, the former being more likely to hold managerial positions (23.5% vs. 20.3%), earn more (77.5% vs. 60.7% earning >4,000 New Israeli Shekels (NIS) per capita), and work longer weekly hours (20.6% vs. 12.6% working 50+ hours weekly). Health outcomes evinced a clear pattern, showing fewer long commuters sleeping adequately on weekdays (48.2% vs. 58.8% sleeping ≥6.5 hours), more long commuters reporting insufficient sleep duration (29.7% vs. 22.8%), and experiencing driving fatigue (9.6% vs. 5.2%) (Table 1).

Table 1.

Background characteristics and outcomes by commute time—women

Variable		Short commute (≤14 h/week)	Long commute (≥15 h/week)	p
20- to 44-year age bracket		59.5%	60.4%	0.014
Median age (years)		40–44	40–44	—
Arab ethnicity		13.3%	11.2%	0.007
Academic education		46.8%	49.4%	<0.001
≥13 years of education		69.2%	71.5%	<0.001
Income >4,000 NIS per capita		60.7%	77.5%	<0.001
Managerial position		20.3%	23.5%	<0.001
Weekly working hours	Up to 34	31.4%	17.4%	<0.001
	35–49	56.0%	61.9%
	50+	12.6%	20.6%
Very good self-rated health		60.6%	55.0%	<0.001
Worsened health in past year		13.8%	17.6%	<0.001
Weekday sleep duration ≥6.5 h		58.8%	48.2%	<0.001
Insufficient sleep		22.8%	29.7%	<0.001
Driving fatigue		5.2%	9.6%	<0.001

NIS, New Israeli Shekels.

Long commuters, in contrast, were more likely to come from the Arab population (29.8% vs. 19.9%), hold managerial positions (39.1% vs. 33.9%), have gained an academic education (39.7% vs. 32.4%), and have worked extended weekly hours (46.8% vs. 35.8% working 50+ hours weekly). Fewer male long commuters enjoyed sufficient sleeping hours during the week (49.2% vs. 51.7% sleeping ≥6.5 hours) and more were suffering from insufficient sleeping hours (26.5% vs. 18.7%) and experiencing greater levels of driving fatigue (11.3% vs. 5.5%) than their female counterparts (Table 2).

Table 2.

Background characteristics and outcomes by commute time—men

Variable		Short commute (≤14 h/week)	Long commute (≥15 h/week)	p
Age: 20–44 years		57.4%	59.7%	0.009
Median age (years)		40–44	40–44	—
Arab ethnicity		19.9%	29.8%	<0.001
Academic education		32.4%	39.7%	0.007
≥13 years of education		57.8%	60.0%	<0.001
Income >4,000 NIS per capita		67.5%	62.6%	<0.001
Managerial position		33.9%	39.1%	<0.001
Weekly working hours	Up to 34	16.1%	9.2%	<0.001
	35–49	48.1%	43.9%
	50+	35.8%	46.8%
Very good self-rated health		58.4%	51.9%	<0.001
Worsened health in past year		11.5%	15.2%	<0.001
Weekday sleep ≥6.5 h		51.7%	49.2%	<0.001
Insufficient sleep		18.7%	26.5%	<0.001
Driving fatigue		5.5%	11.3%	<0.001

NIS, New Israeli Shekels.

A sequential logistic regression analysis for driving fatigue among women revealed consistent findings across the four models (Table 3):

• a)Model 1 indicates that long commuters were 89% more likely to experience driving fatigue [odds ratio (OR) = 1.892, CI: 1.857–1.927].
• b)Commuting maintained a similar strength in Model 2 (OR = 1.859, CI: 1.825–1.894), wherein Arab ethnicity exhibited a possible protective effect (OR = 0.934).
• c)Long commuting remained significant (OR = 1.863, CI: 1.828–1.898) in Model 3, evincing increased risk among those holding managerial positions (OR = 1.328) and working 50+ hours per week (OR = 1.484).
• d)Long commuting remained a significant independent predictor (OR = 1.708, CI: 1.675–1.741) in Model 4, with insufficient sleep duration (<6.5 hours) emerging as the strongest risk factor (OR = 2.849, CI: 2.802–2.898) herein.

Table 3.

Logistic regression models predicting driving fatigue—women

Variable		Model 1 OR (99% CI)	Model 2 OR (99% CI)	Model 3 OR (99% CI)	Model 4 OR (99% CI)
Commute time	≤14 h/week	1.00	1.00	1.00	1.00
	≥15 h/week	1.90∗ (1.86–1.93)	1.86∗ (1.83–1.89)	1.86∗ (1.83–1.90)	1.71∗ (1.68–1.74)
Ethnicity	Jewish		1.00	1.00	1.00
	Arab		0.93∗ (0.91–0.96)	0.94∗ (0.91–0.96)	1.02 (0.99–1.04)
Academic education	No		1.00	1.00	1.00
	Yes		1.64∗ (1.61–1.67)	1.59∗ (1.56–1.62)	1.62∗ (1.59–1.64)
Managerial position	No			1.00	1.00
	Yes			1.33∗ (1.30–1.35)	1.33∗ (1.31–1.36)
Weekly working hours	Up to 34			1.00	1.00
	35–49			1.02∗ (1.00–1.04)	0.92∗ (0.91–0.95)
	50 and more			1.48∗ (1.45–1.52)	1.46∗ (1.43–1.49)
Weekday night sleep	Up to 6.5 h				1.00
	6.5 h or more				2.85∗ (2.80–2.90)

CI, confidence interval; OR, odds ratio.

Age and interview timing were adjusted (before/after 7 October, 2023).

^∗Statistically significant at p < 0.001.

Model 1 evinces that long commuting more than doubled the risk of driving fatigue (OR = 2.185, CI: 2.156–2.215).

The commuting effect remained virtually unchanged in Model 2 (OR = 2.182, CI: 2.152–2.212), Arab ethnicity being associated with an increased risk (OR = 1.680).

Model 3 indicates sustained commuting effects (OR = 2.151, CI: 2.122–2.181), managerial positions increasing the risks (OR = 1.186) and working 50+ hours weekly further heightening odds for experiencing driving fatigue (OR = 1.231).

Long commuting remained the strongest predictor of driving fatigue among men (OR = 2.125, CI: 2.096–2.154) in Model 4, with insufficient sleep duration having a more modest role in comparison with women commuters (OR = 1.345, CI: 1.326–1.363).

4. Summary of findings

This gender-stratified analysis of 3,387 Israeli workers reveals that long commuting (≥15 hours/week) significantly increases the risk of sleep insufficiency and driving fatigue along distinct gender lines. Women with long commutes slept insufficiently (AOR = 1.56) and experienced more driving fatigue (AOR = 1.71), both associations remaining significant after full adjustment. Men with long commutes suffered even greater levels of driving fatigue (AOR = 2.13). Surprisingly, the adjusted models displayed no significant association with sleep duration.

Women evinced greater vulnerability to sleep disruption due to commuting, while men evinced higher levels of driving fatigue. Women with long commutes were more likely to hold managerial positions and earn more than men with long commutes, the latter being likely to come from the Arab sector and working extended hours (50+ weekly). This disparity is probably due to occupational gender differences. Insufficient sleep duration emerged as the strongest predictor of driving fatigue among women (OR = 2.85) in the regression models. This association was weaker among men (OR = 1.35) suggesting that commuting probably affects driving fatigue via divergent gender pathways.

With the findings demonstrating that commuting functions as a potential independent occupational health risk factor, this study uniquely evinces gender-specific pathways in the Israeli working population, requiring tailored gender-specific interventions. The gender-stratified regression results are summarized in Fig. 2, presenting adjusted ORs with 99% CIs from Model 4 (Table 3, Table 4), with the fully adjusted multivariable logistic regression models predicting driving-related fatigue. The significant correlation between gender and commute time (p < 0.001) prompted creation of separate gender models.

Fig. 2.

Adjusted odds ratios for driving fatigue according to selected predictors among men and women (Model 4). Men = blue, women = red.

Table 4.

Logistic regression models predicting driving fatigue—men

Variable		Model 1 OR (99% CI)	Model 2 OR (99% CI)	Model 3 OR (99% CI)	Model 4 OR (99% CI)
Commute time	≤14 h/week	1.00	1.00	1.00	1.00
	≥15 h/wk	2.19∗ (2.16–2.2)	2.18∗ (2.15–2.21)	2.15∗ (2.12–2.18)	2.13∗ (2.10-2.15)
Ethnicity	Jewish		1.00	1.00	1.00
	Arab		1.68∗ (1.65–1.71)	1.68∗ (1.66–1.70)	1.84∗ (1.810–1.866)
Academic education	No		1.00	1.00	1.00
	Yes		1.72∗ (1.70–1.75)	1.74∗ (1.72–1.77)	1.69∗ (1.67–1.72)
Managerial position	No			1.00	1.00
	Yes			1.19∗ (1.17–1.24)	1.16∗ (1.15–1.18)
Weekly working hours	Up to 34			1.00	1.00
	35–49			0.95∗ (0.94–0.97)	0.93∗ (0.91–0.94)
	50+			1.231∗ (1.20–1.26)	1.23∗ (1.20–1.26)
Weekday night sleep	Up to 6.5 h				1.00
	6.5 h +				1.35∗ (1.33–1.36)

CI, confidence interval; OR, odds ratio.

Age and interview timing were adjusted (before/after 7 October, 2023).

^∗Statistically significant at p < 0.001.

The data enable us to directly compare the effects across key predictors—including weekly commute duration (≥15 h vs. ≤14 h), demographic factors (Arab ethnicity and academic education), occupational characteristics (managerial position and working hours), and sleep duration (<6.5 h vs. ≥6.5 h). OR values greater than 1 indicate greater odds of driving fatigue; values less than 1 indicate decreased odds and possible protective effects. The vertical dashed line represents the null value (OR = 1).

5. Discussion

This study examined the association between weekly commuting time, sleep duration, and driving-related fatigue, among employed adults in Israel on the basis of nationally representative data from the 2023 Israel Social Survey. The findings demonstrate that long weekly commuting (≥15 hours) is associated with an increased likelihood of both insufficient sleep duration and driving fatigue with significant gender differences observed. Supporting international evidence linking extended commuting to adverse health outcomes [[1], [2], [3], [4],7], they highlight the public health relevance of commuting patterns—in particular in small, densely populated countries with limited public transportation, such as Israel.

The gender-stratified analysis reveals that long commuting affects men and women differently. Among men, long commuting was strongly associated with driving fatigue; among women, it was more closely linked with insufficient sleep duration. This divergence may be explained by the role of gendered time use and domestic responsibilities in shaping commuting-related health risks [3,11].

5.1. Gendered impact of time scarcity and sleep disruption

Consistent with previous studies [3,[10], [11], [12]], women reported shorter sleep duration and higher rates of insufficient sleep than men. This pattern can be understood through the concept of time scarcity, whereby the total female workload—combining paid employment and unpaid domestic chores—leaves limited time for adequate rest and recovery. Despite working fewer paid hours on average, women carry heavier home-based responsibilities; this contributes to cumulative fatigue and lower sleep quality [21].

Commuting compounds this burden by reducing discretionary time and schedule flexibility. Long commuting hours often force women to sleep less in order to engage in caregiving or household duties. The results align with Western European findings according to which women’s well-being is more adversely affected by commuting due to higher stress, lower perceived control, and greater exposure to multitasking demands [3,11].

Sleep deprivation is not only a behavioral outcome but also a physiological stress response. Repeated periods of insufficient sleep can disrupt endocrine balance, elevating cortisol levels and contributing to allostatic overload [[13], [14], [19], [20]]. Over time, these processes may explain gender disparities in fatigue, cardiovascular risk, and mental health outcomes associated with prolonged commuting.

5.2. Commuting, chronic stress, and allostatic load

The findings can also be interpreted through the lens of allostatic load theory, according to which chronic exposure to environmental and occupational stressors causes cumulative physiological wear and tear [19,20]. Long commutes—in particular those characterized by congestion and schedule unpredictability—put pressure on the stress response system, affecting sleep, fatigue, and overall health.

The JD-R model complements this framework by conceptualizing commuting as a job-related demand that depletes time and energy resources while limiting recovery opportunities [22]. Gender-specific analyses evince that women experience higher cumulative stress because of more constrained resources—time, flexibility, and social support. This dual exposure, which combines external demands with limited recovery capacity, generates a higher allostatic burden.

The combination of allostatic load and JD-R perspectives could explain why long commuting disproportionately affects sleep among women and fatigue among men. Among the latter group, fatigue may result from long driving hours, stress-related occupational performance, and traffic exposure [10,[15], [16], [17], [18]]. Among women, the physiological toll of cumulative stress, reduced recovery time, and social expectations to maintain domestic duties may amplify sleep disruption.

This interpretation further highlights the intersection between work and home domains in the worker’s life. While commuting serves as both a physical and psychological boundary between those two domains, it functions as an additional source of strain for many workers—especially women—rather than a restorative transition. The inability to recover from work-related stress contributes to chronic fatigue, potentially increasing the risk of accidents, absenteeism, and long-term health deterioration [7,12,16,17].

5.3. Behavioral and public safety implications of fatigue

Driving fatigue is as a major gendered health and safety concern. The higher levels of fatigue reported by men endangered their safety while driving; this finding aligns with the indication in earlier studies that male drivers are over-represented in fatigue-related road accidents [10,[15], [16], [17], [18]]. Although less likely to result in driving accidents, female fatigue manifests as a chronic exhaustion that accumulates across work and family domains, influencing long-term health outcomes.

The findings underscore the dual nature of commuting-related fatigue—acute fatigue linked to immediate safety risks and chronic fatigue linked to long-term health decline. Both dimensions are shaped by working hours, commuting conditions, and recovery opportunities. Public health strategies should therefore target both immediate and cumulative effects through transportation planning, work-life balance restoration policies, and fatigue risk management.

Efforts to reduce commuting burden might include more remote and hybrid work options, improved public transport accessibility, and flexible scheduling. Male interventions might focus on addressing driving fatigue and improving sleep hygiene and female interventions on structural supports—such as subsidized childcare, improved public transport safety, and reduced work–family conflict—that may alleviate sleep deprivation and cumulative stress.

Beyond individual interventions, the results highlight that commuting constitutes a social determinant of occupational health. The distribution of commuting-related risks reflects broader gender, spatial, and socioeconomic inequalities. Workers living in peripheral areas or low-income communities often need longer commutes to distant workplaces, have less control over work schedules, and are more reliant on private cars—all factors that compound health inequities [4,11].

Finally, the study supports an expanded framework for understanding the health consequences of commuting—one that integrates biological stress mechanisms (allostatic load), psychosocial demands (JD-R), and gendered social roles. Together, these frameworks explain how prolonged commuting could produce both physiological and social exhaustion, undermining wellbeing and safety in daily life.

6. Limitations and implications for future research

The study suffers from several limitations. The cross-sectional design precludes causal inference, and longitudinal data are required to establish temporal relationships between commuting and health outcomes. Self-reported measures of sleep and fatigue may introduce reporting bias—although such indicators have been validated in population studies [6,7,12].

The findings rest on nationally representative government survey data; future research should seek to complement self-reported measures with longitudinal designs and objective data sources, in order to strengthen causal inference and measurement precision.

Contextual factors such as transport mode, traffic density, and family composition, which are likely to moderate the effect of commuting, were unavailable. Driving fatigue was assessed only among respondents who commute by private vehicle; therefore, the findings related to this outcome may not be fully generalizable to commuters who rely exclusively on public or active transport.

Future studies should incorporate objective measures of sleep (e.g., actigraphy), driving behavior (telematics), and stress biomarkers to better capture allostatic processes. Cross-country transportation infrastructure research might clarify whether Israel’s unique commuting conditions are expected to amplify or mitigate health effects.

Despite these limitations, this study provides valid evidence from a national dataset that links long weekly commuting with insufficient sleep duration and driving fatigue. It thus highlights the importance of addressing commuting time as a modifiable determinant of occupational health and the implications thereof for policy, workplace regulation, and road safety.

7. Implications for practice

• a)Long commuting (≥15 hours/week) should be recognized as an occupational health-risk factor, warranting targeted prevention strategies among working populations.
• b)Gender-stratified approaches are essential for addressing commute-related health impacts in light of the differential gender vulnerability patterns.
• c)Workplace policies—in particular those affecting employers of long-distance commuters—should take commute time into consideration when developing driving-fatigue management strategies and flexible/hybrid work arrangements.
• d)Public health and road-safety initiatives should explicitly account for commute-related driving-fatigue risks—especially for workers having to travel long distances/commuting hours.
• e)Investment in transportation infrastructure and congestion reduction measures should be viewed also as a public-health intervention with potential occupational safety benefits.

CRediT authorship contribution statement

Ronit Pinchas-Mizrachi: Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Formal analysis, Conceptualization. Sara Cohen: Writing – review & editing, Project administration, Data curation. Dan Bouhnik: Writing – review & editing, Software, Investigation, Formal analysis. Raz Dekel: Writing – review & editing, Writing – original draft, Visualization, Supervision, Methodology, Investigation, Conceptualization.

Ethics statement

This study used anonymized secondary data from the Israel Central Bureau of Statistics (Israel Social Survey 2023) and did not require ethical approval.

Statement on the use of AI

During the preparation of this work, the authors used ChatGPT (OpenAI, San Francisco, CA, USA) to assist in language editing, phrasing refinement, and formatting of supporting materials (e.g., title page and cover letter). After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the final version of the manuscript.

Funding

No external funding was received for this study.

Conflicts of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.