The WTS Health Questionnaire
Participants started engaging in WTS at a relatively younger age- 43% began when they were under 18, and an additional 39% began between 19 and 25 (Figure 2). This indicates that WTS became increasingly popular among Israeli Arabs mainly over the last decade. In addition, the majority of respondents reported engaging on WTS on a regular basis, rather than only during weekends (Figure 3). This suggests WTS has become a regular part of the respondents’ lifestyle.
Figure 2: Distribution of participants’ age when first smoking a hookah.
Figure 3: The day of the week on which the subject usually smoke a hookah.
Figure 4 shows the degree of agreement to the statement that prolonged smoking of a water-pipe may lead to addiction, with 7– strongly believe and 1 – completely disagrees. About half of the participants agree and strongly agrees that prolonged waterpipe smoking may lead to addiction. There is a positive correlation between the frequency of WTS and the belief that prolonged WTS may lead to its addiction, with participants who believe that prolonged smoking of a hookah may lead to its addiction being less likely to participate in WTS(p=0.061, r=0.617).
Figure 4: Distribution of the participant according their agreement to the statement that prolonged smoking of a water-pipe may lead to addiction.
All questionnaire items underwent factor analysis (principal component analysis with Varimax variation), giving rise to several clusters corresponding to the TPB model. Table 2 summarizes the results. Notably, this process generated a distinction between subjective norms relating to friends and to parents. This is consistent with recent studies suggesting that parents’ influence on WTS may be significant and separate from the influence of the peer group [25].
Factor |
Statement |
Mean |
S.D |
Cronbach’s alpha (α) |
Health risk perception |
I believe that smoking a water-pipe may cause serious harm to health |
6.1 |
1.709 |
0.689 |
I believe that smoking a water-pipe may injure my ability to perform mental and physical activities |
3.92 |
2.381 |
I believe that a prolonged smoking of a water-pipe may injure my lungs |
6.1 |
1.775 |
Personal behavioral control |
I believe that even if my friends are addicted to smoking a water-pipe, I can spend time with them without smoking |
4.507 |
2.408 |
0.813 |
It is possible for me to avoid smoking a water-pipe |
5.403 |
1.967 |
If I want, I can avoid smoking a water-pipe even though everybody around me smoke |
4.656 |
2.501 |
Subjective norms(friends) |
Smoking a water-pipe with my friends helps me to be more popular in society |
2.104 |
1.876 |
0.811 |
I believe that smoking a water-pipe will make me feel more relaxed and open with my friends |
2.194 |
1.69 |
I believe that smoking a water-pipe will make me feel more at liberty with members of the other sex |
1.955 |
1.637 |
If I smoke the water-pipe, I will have more friends |
2.642 |
2.274 |
Subjective norms(parents) |
Smoking a water-pipe with my family will help to become more popular in my family” |
1.621 |
1.506 |
0.691 |
I believe that smoking a water-pipe will make me feel more relaxed and open with my family |
1.611 |
1.337 |
Table 2: Summary of the factor analysis.
Table 3 shows the estimated results of the WTS model featuring the TPB components. The model is a logistic regression in which the dependent variable has two alternatives – engaging in WTS frequently (at least every two weeks) or rarely (once a month). Participants with a higher level of Personal Behavioral Control (PBC) were significantly less likely to engage in WTS. Subjective norms relating to friends did not gain a significant impact on the frequency of WTS, while subjective norms relating to parents had a negative and significant impact on the frequency of WTS.
Variable |
β |
T-Statistic |
Sig. |
95% C.I. for EXP(B) |
|
Self – control (ordinal) |
-0.884 |
2.135 |
0.033 |
0.931 |
0.183 |
|
|
Subjective norms-friends |
0.435 |
1.089 |
0.277 |
3.382 |
0.705 |
|
|
Subjective norms-parents [reversed] |
-0.995 |
2.319 |
0.02 |
0.857 |
0.16 |
|
|
Health risk perception |
1.15 |
1.912 |
0.055 |
10.233 |
0.975 |
|
|
I believe that prolonged smoking of a water-pipe may lead to addiction to that sort of smoking (ordinal) |
-1.356 |
2.07 |
0.041 |
0.949 |
0.07 |
|
Marital status (dummy, Married =1) |
2.106 |
1.663 |
0.096 |
98.247 |
0.686 |
|
Income (ordinal) |
0.133 |
0.185 |
0.853 |
4.651 |
0.28 |
|
|
Education (ordinal) |
-3.099 |
1.989 |
0.047 |
0.956 |
0.002 |
|
|
Work status (dummy, salaried=1) |
-1.356 |
2.136 |
0.033 |
0.681 |
0 |
|
Constant |
10.434 |
1.912 |
0.056 |
|
|
|
-2 Log likelihood- final |
31.519 |
Statistical summary |
|
Chi-square |
22.331 |
|
Sig. |
0.008 |
|
Cox & Snell R Square |
0.42 |
|
Nagelkerke R Square |
0.574 |
|
Table 3: Logistic regression risk of WTS status (high/low usage).
Surprisingly, health risk perception has been shown to have a significant positive impact on the WTS frequency, with participants with elevated health risk perception more likely to engage in WTS. In contrast, concerns about addiction were instrumental in participants’ decision to avoid WTS.
In regards to the socio-economic characteristics, the estimated results show that married people are more likely to engage frequently in WTS. In contrast, people with a high education levels and are employed are less likely to engage in WTS frequently.
The Experiment
Driving behavior using the average of the measures in the three main driving scenarios (prior to WPS, immediately following WPS and half an hour subsequent to WPS) were calculated. These measures are the outcome of the driving scenarios for every participant and every scenario. Table 4 presents the means of the various driving measures for the experimental group and control groups only pre-WTS. The measures include total number of road crashes, road crashes (self crash), car accidents, pedestrian accidents, surpassing the speed limit (this measure tested the number of times the driver exceeded the speed limit), the total number of traffic light violations, centerline crossings, road shoulder crossings and speed limit violations (% time). This measure indicates the percentage of time relative to the total driving time the driver surpasses the speed limit. The final measure was for not driving within the lane (% time) which showed the percentage of time relative to the total driving time the driver drove over the center divider and the shoulder boundary. Table 4 shows that the driving measures within both groups the experimental before WPS and the control “scenario-1” are relatively similar and the differences between the measures are statistically insignificant at to a (p-value of 0.05).
Accidents (road) |
2.13 |
1.5 |
1.95 |
1.77 |
0.542 |
|
|
Accident (car) |
2.61 |
2.47 |
2.86 |
2.99 |
0.381 |
|
Accident (pedestrian) |
0.75 |
1.3 |
0.91 |
1.3 |
0.982 |
|
Exceeding the speed limit |
6.75 |
8.6 |
7.22 |
10.48 |
0.228 |
|
Total number of traffic light tickets |
0.98 |
1.27 |
1.07 |
1.21 |
0.742 |
|
Centerline crossings |
4.73 |
5.87 |
6.53 |
7.03 |
0.382 |
|
Shoulder crossings |
5.09 |
6.3 |
6.72 |
7.65 |
0.327 |
|
Exceeding the speed limit (% time) |
9.27 |
10.09 |
10.75 |
13.38 |
0.128 |
|
Not being in within the lane (% time) |
6.01 |
6.38 |
6.67 |
7.22 |
0.539 |
Table 4: Mean of the various driving measures for the experimental group and control groups pre-WTS.
While immediately after WPS and half an hour after smoking all the driving measures were higher within the experimental group than the control group, which meaning more crashes, more violation and more risky driving [18].
The pre-WTS condition was used in order to control the socioeconomic characteristics, amongst which were age (experiment group 29.5 and control 36.33), and driving experience (9.7 and 14.5 respectively).
It is important to note that comparing means is not sufficient in examining the significance of the changes in driving behavior, since during the driving process, the participants - both those who smoke a hookah and those who do not, generate an experience. Therefore, to provide a control for the drivers’ driving experience, the odds ratio test is used.
Table 5 demonstrates that the influence of WTS on WTS users increased the risk of a crash by approximately 30% in the immediate condition (p=0.05; CI=1.008, 1,776). Even 30 minutes after engaging in WTS, WTS users still had a significantly higher risk of being involved in a crash - 28% more than non-WTS users (p=0.1, CI=0.961, 1.705). WTS users were also exposed to a higher risk of crossing centerlines (OR=1.306, p=0.05, CI=1.016, 1.679) and spent more time outside their lane (OR=1.329, p=0.05, CI=1.025, 1.772).
Variable |
Scenario 1 - Scenario 2 |
Scenario 2 - Scenario 3 |
Odds Ratio |
95% Confidence Interval |
Odds Ratio |
95% Confidence Interval |
Lower |
Upper |
Lower |
Upper |
Accidents |
1.333** |
1.01 |
1.78 |
1.28* |
0.96 |
1.71 |
Accidents (road) |
1.23 |
0.71 |
2.11 |
1.32 |
0.66 |
2.63 |
Accident (car) |
1.35 |
0.91 |
2 |
1.29 |
0.88 |
1.88 |
Accident (pedestrian) |
1.29 |
0.63 |
2.62 |
1.2 |
0.61 |
2.35 |
Exceeding the speed limit |
0.91 |
0.74 |
1.11 |
0.96 |
0.79 |
1.18 |
Total number of traffic light tickets |
1.65 |
0.91 |
3.02 |
1.5 |
0.73 |
3.08 |
Centerline crossings |
0.94 |
0.75 |
1.19 |
1.306** |
1.02 |
1.68 |
Shoulder crossings |
0.87 |
0.68 |
1.11 |
1 |
0.76 |
1.32 |
Exceeding the speed limit (% time) |
0.85 |
0.72 |
1.01 |
1 |
0.83 |
1.19 |
Not being in within the lane (% time) |
0.95 |
0.76 |
1.19 |
1.329** |
1.03 |
1.72 |
Table 5: Summary of the odds ratio test results.
Table 6 provides the results of the physiological indicators, i.e. pulse and blood oxygenation (saturation). There were no significant differences between the groups in the pre-WTS condition but, again, WTS users were much more influenced by WTS than non-users in the following conditions, manifested in significantly higher pulse and levels of saturation compared to the pre-WTS condition. The direction of change was similar for the control group, but the results were not statistically significant. These findings support the hypothesis that the reduction in driving ability is due to hypoxia.
Sample |
Scenario Pairs |
T Statistic |
Sig. (2-Tailed) |
Confidence Interval of Paired Differences (95%) |
Mean |
Std. Deviation |
Control group |
Pulse 1- pulse 2 |
2.36 |
0.03 |
0.21, - 2.99 |
1.6 |
3.71 |
Saturation 1 – saturation 2 |
-0.57 |
0.57 |
-0.31, -0.17 |
-.07 |
0.64 |
Pulse 1- pulse 3 |
1.97 |
0.07 |
-0.31, 5.64 |
2.67 |
4.68 |
Saturation 1 – saturation 3 |
-0.56 |
0.59 |
-0.41, 0.24 |
-.08 |
0.51 |
Experimental group |
Pulse 1- Pulse 2 |
−11.84 |
0 |
-17.14, -12.2 |
-14.67 |
10.29 |
Saturation 1 – Saturation 2 |
3.02 |
0 |
0.2, 0.96 |
0.58 |
1.59 |
Pulse 1- Pulse 3 |
−5.54 |
0 |
-10.11, -4.73 |
-7.42 |
9.46 |
Saturation 1 – Saturation 3 |
3.01 |
0 |
0.16, 0.8 |
0.48 |
1.13 |
Table 6: Mean differences between the three scenarios.
Discussion and Conclusion
The results of the experimental part suggest that WTS users are at a higher risk for crashes and violations even before engaging in WTS directly (i.e., before the session), particularly due to driving outside their lane. The physiological indicators are in line with those identified with hypoxia in terms of blood saturation and pulse rates. These results support the study’s initial hypothesis: WTS creates a condition of hypoxia, thus harming motor and cognitive abilities and leading to reduced driving ability. Even if one is to dispute this physiological mechanism [18] the finding that WTS can be temporally linked to a greater driving risk still must be accounted for.
Previous studies of WTS behavior have applied Ajzen’s Theory of Reasoned Action (TRA), which examines attitudes and subjective norms [2,21]. In contrast, the current study used the TPB model, which is a later variant of the TRA model including the PBC component. The advantage of PBC is that it may suggest that if one feels unable to avoid WTS one is more likely to engage in WTS. This finding has both practical and theoretical implications. The TPB model distinguishes between one’s perceived ability to carry out a certain task and one’s actual ability to do so, assuming that experience reduces the gap between these components [22]. However, in this case, unlike drunk driving, it was found that WTS has greater influence on experienced users. Thus, paradoxically, experience increases the risk represented by a certain behavior rather than vice versa. This finding demonstrates the complex relations between psychological and physiological conditions, suggesting that health behavior models should be adjusted to account for the particularities of specific behaviors and their conditions. At the policy level, awareness campaigns should be designed in a way as to stress this finding, since it is only reasonable to assume that experienced users are likely to believe that their experience serves as a buffer from risk.
The study had several limitations. First, the water-pipe session was limited to 30 minutes, even though it can last as long as an hour [17]. This suggests that our results consist of a minimal threshold, leaving open the question of just how much more influence would a longer session have. Second, the study population all came from the same cultural background. Similarly, to other health behaviors, WTS has been shown to have a strong cultural component [25]. This can be read as strength of the current design, as it rules out the confounding influence of cross-cultural differences. At the same time however, the nature of the relations between WTS and culture is left unexplored. The role of cultural factors mediating the manifest influence of psychoactive substances, as such alcohol, is well established and should serve as a motivator for exploring the same in regards to WTS [26]. Thus, researchers should be wary of quick generalizations and future studies should include cross-cultural comparisons. Finally, the sample used here was not very large and was mostly male (89% of WTS smokers and 77% of non-smokers). Larger and more gender-equal samples would have strengthened the validity of the results.
As the social nature of WTS is considered to be one of its main attractions, it is possible that the tendency to engage in WTS reflects a tendency to engage in other activities susceptible to peer pressure, such as the consumption of alcohol. However, in the current sample 81% of WTS smokers reported they did not drink alcohol; thus, a link between WTS and alcohol consumption seems highly unlikely. Thus, it seems that each health behavior must be examined on its own terms.
From a broader view, the current study joins the ongoing theoretical discussion within the field of traffic safety regarding the conceptualization of traffic accidents. Historically, traffic accidents were perceived as either the fault of unsafe drivers (known as the “nut behind the wheel” narrative) or as a chance event, often termed “an act of god” [27]. Different experts, most notably from the public health field, have been disputing this perception, suggesting that accidents were the result of a complex interaction of multiple factors and therefore were not truly “accidental”; in order to stress this, they suggest replacing the term “accident”, which implies an element of chance, with “crash”, which provides a more neutral description of the event [28-29]. The current study provides a causal mechanism demonstrating how a seemingly un-related behavior such as WTS contributes to shaping driving behaviors. Understanding the mechanisms underlying them is a necessary step on the road to transforming traffic accidents - currently the 9thleading global cause of death [30] - to calculable, amenable traffic crashes, the target of informed and effective traffic policies.
Given the current empirical demonstration, showing that the health implications of WTS go beyond direct bodily influences and include second-order effects such as risky driving, it is clearly necessary to raise awareness to what many consider a rising global epidemic [10,16]. The finding that frequent WTS users are more sensitive to its influences is especially significant, as it stands to reason that people believe that their ability to control a certain effect grows with experience.
In addition, Personal Behavioral Control (PBC), overlooked by previous models [2,21], should be included in future research. Moreover, policymakers and educators who wish to conduct more effective campaigns should target PBC directly.