|Year : 2020 | Volume
| Issue : 4 | Page : 252-256
Predictors and prevalence of social jet lag among King Saud employees and their families
Jumana Fatani1, Reema Alnasser1, Nouf Aljomah1, Sarah Alhusaini1, Ahmad Hersi2
1 College of Medicine, King Saud University, Riyadh, Saudi Arabia
2 Department of Cardiology, King Saud University, Riyadh, Saudi Arabia
|Date of Submission||17-Jan-2020|
|Date of Decision||23-Mar-2020|
|Date of Acceptance||10-Apr-2020|
|Date of Web Publication||25-Jun-2020|
Department of Cardiology, King Saud University Medical City, Riyadh
Source of Support: None, Conflict of Interest: None
Background: Sleep is a crucial element in human beings' development and sustainment of a healthy lifestyle; any chronic misalignment between the sleep–wake cycles could be associated with numerous physical and mental disturbances. Social jet lag (SJL) is the discrepancy between the midpoints of sleep in workdays and free days. Up to date, there is a scarcity of studies conducted regarding this disorder in the Middle East. Hence, we aimed toward studying the prevalence and predictors of SJL. Methods: This was an observational cross-sectional study. The sample size was 328 participants who are King Saud University employees and their families. Saudi individuals aged 18 years and above were included in the study. Pregnant women were excluded from the study. Data were collected using an interview-administered questionnaire (Munich ChronoType Questionnaire). SJL was calculated as the absolute difference between the midpoints of sleep on free days and workdays. The association between SJL and predictors was assessed using the Chi-square test. Results: A sample of 226 females and 62 males were analyzed. SJL was categorized into three groups, which are <1 h, 1–2 h, and >2 h. Our results showed that SJL of >2 h represents approximately half of the participants (49.7%) and appeared to be more among the 18–33 years' age group (56.5%). Participants with >2 h were found to have a significant difference between sleep durations on work and free days (5.9 ± 1.8 vs. 8.67 ± 1.91 h, P < 0.001, respectively). Conclusion: Lower SJL hours are associated with factors such as increased age and similar sleep duration on work and free days, in addition to alarm use on free days. Whereas, younger age, inflexible work schedule, smoking, and soft drinks' consumption are linked with higher SJL hours. Our future aim is to increase the awareness of controlling the factors which lead to higher SJL hours and the importance of having a balanced sleep.
Keywords: Sleep, social jet lag, sleep-wake cycles
|How to cite this article:|
Fatani J, Alnasser R, Aljomah N, Alhusaini S, Hersi A. Predictors and prevalence of social jet lag among King Saud employees and their families. J Nat Sci Med 2020;3:252-6
|How to cite this URL:|
Fatani J, Alnasser R, Aljomah N, Alhusaini S, Hersi A. Predictors and prevalence of social jet lag among King Saud employees and their families. J Nat Sci Med [serial online] 2020 [cited 2020 Oct 19];3:252-6. Available from: https://www.jnsmonline.org/text.asp?2020/3/4/252/287702
| Introduction|| |
Sleep is a crucial element in human beings' natural development and sustainment of a healthy functional lifestyle; any chronic misalignment between the sleep–wake cycles could be associated with numerous physical and mental disturbances, e.g., depression, reduced performance, metabolic abnormalities, hormone imbalances, diabetes, and even cardiovascular disease. Due to the social obligations and work demands, individuals may suffer from lack of sleep during the week, therefore compensating this cumulative sleep debt on off days.
As a result, a major sleep problem “social jet lag (SJL)” will gradually develop. SJL is defined as the discrepancy between the midpoints of sleep in workdays and off days. It is hypothesized that SJL is linked with sociodemographic characteristics and certain lifestyle habits. Therefore, SJL is a matter of concern for public health.
Despite the negative influences of SJL and its widely demonstrated preponderance in the Western population, there is a scarcity of studies conducted regarding this particular disorder in our region. Hence, we aim to study the prevalence and predictors of SJL among Saudi population.
| Methods|| |
The Research Ethics Committee of King Khalid University Hospital (KKUH), Riyadh, approved the study, and consent was obtained from all participants. The study is observational quantitative cross-sectional. It was conducted from November 2016 to March 2017. King Saud University employees and their families were recruited (n = 328); all Saudi males and females aged 18 and above were included, and those under 18 years old, non-Saudi people, and pregnant women were excluded. The sampling process is done by multiple methods: (1) database of volunteers having previously participated in prior studies contacted through phone calls and (2) simple random sampling from KKUH and King Saud University campus through a face-to-face interview.
The data on SJL were obtained using an interview-administered questionnaire (Munich ChronoType Questionnaire “[MCTQ]”) which is validated and reliable as it has been widely used in most of the prior studies assessing SJL and chronotypes. The MCTQ main domains include demographic data and information regarding sleep hours on work and off days and work schedule, in addition to sun exposure and stimulants' consumption.
The questionnaire was clearly explained to those who are incapable of reading English.
Data were analyzed through the Statistical Package for the Social Sciences (SPSS) version 21.0, statistical software for Windows (IBM Inc., Chicago IL, USA). Descriptive statistics were calculated, and continuous variables were reported as means and standard deviations and categorical variables as percentages. SJL was calculated as the absolute difference between the midpoints of sleep on free days versus workdays. The midpoint of sleep is the point between sleep onset and wake onset, and it was calculated separately for each workday and free day.
The association between SJL and predictors was assessed using the Chi-square test. P ≤ 0.05 was considered statistically significant.
| Results|| |
The sample population applied in the study was equal to 328, with a response rate of 87.8% in 226 females and 62 males. Hence, females were dominating the sample by a percentage of (78.5%). Majority of our participants' ages were in the 18–33 years' age group (55.9%).
SJL was categorized into three groups, which are <1 h, 1–2 h, and >2 h. The prevalence of the >2-h group represents roughly half of the participants (49.7%), whereas <1 h and 1–2 h of SJL are representing similar proportions of 25.7% and 24.7%, respectively, as illustrated in [Table 1].
Furthermore, a significant association between SJL and age was observed, and it is more likely that younger people will have >2-h SJL compared to those who are older.
Moreover, participants with <1 h are found to have approximately the same sleep duration on both work and free days (6.63 ± 1.81 vs. 6.86 ± 2.17 h, P < 0.001), respectively. However, the sleep durations on work and free days in the >2-h SJL group are 5.9 ± 1.8 and 8.67 ± 1.91 h (P < 0.001), respectively.
Although we hypothesized that there would be an association between some personal factors that may contribute to delaying sleep hours in free days such as social obligations such as family gatherings or having children at home and higher SJL hours, there were not any statistically significant associations. We noticed that 56.9% of the participants who mentioned that their sleep is delayed on free days because of social obligations have >2 h of SJL. However, 48.2% of those who mentioned that their sleep is not restricted by any factors have >2-h SJL as well.
In addition, the study shows that people who organize their sleep by setting the alarm on free days have less SJL hours. On the other hand, using the alarm on workdays shows no significant association with SJL.
Individuals with regular work schedule (this includes being, for example, a housewife or househusband) have more SJL hours in comparison with irregular work (this includes those who work 7 days/week). Likewise, those who mentioned that their work schedule is “very inflexible” or “rather inflexible” showed higher social jet hours.
Another important set of predictors is stimulants' exposure; a significant association between SJL and smoking or soft drinks' consumption is found, and participants who smoke an average of 24.9 cigarettes per week are more prone to >2-h SJL. There is no significant association found between SJL and coffee, black tea consumption, or minutes of sun exposure, as shown in [Table 2]. In addition, there is no linkage found between SJL and sleep medication usage, although this might not be an accurate representation, as participants who were on sleep medications were only 6.9% of the population.
|Table 2: Participantsf characteristics in categories of social jet lag and associations between social jet lag, sleep behavior, and work.related factors|
Click here to view
| Discussion|| |
Our study proved that this sleep disturbance is very widely distributed among participants, with a prevalence of 49.7% in the >2-h group in comparison with only 26% in another study done in The Netherlands. Furthermore, the <1-h and 1–2-h groups represent similar proportions in both studies of 25.7% and 24.7%, respectively, in this study and 37% in both groups in The Netherlands.
As shown in [Table 3], SJL is inversely related to the age, and this supports what has previously been found., We noticed that SJL was more allocated among young adults.
The relation between gender and SJL is not certainly identified yet. For instance, a previous study in Germany stated that they did not find any association between gender and SJL. However, another study had opposite findings in which they have found that SJL was higher among females. Our study has a total of 328 sample sizes, with a response rate of 87.8% in 226 females and 62 males. Although females were dominating the sample by a percentage of (78.5%), our research did not detect any association between the two, as represented in [Table 3].
In the same manner, there was no significant association between SJL and body mass index (BMI), which is compatible with what a previous study has proved.
Contrarily, there has been an association with BMI established in other studies.,
We noted a significant correlation between a person's sleep duration and SJL. The <1-h SJL group had roughly the same sleep duration on both work and free days. However, the difference in duration in those who have >2-h SJL is 3.47 h of more sleep on free days, which is acceptable given that they compensate the accumulated debt on free days, and this will lead to this discrepancy discussed earlier. Previous studies had similar results in terms of sleep duration.,,
Likewise, those who mentioned that their work schedule is inflexible, had recorded higher social jet hours, which is hypothesized to be due to the strict waking hours providing less sleep duration on workdays. Participants with regular and more flexible work schedule have lower SJL hours in comparison with irregular or no work schedule or less flexible. Surprisingly, there was no significant association found between shift work and SJL.
Furthermore, there is no significant association found between sleep restrictions and SJL.
The association between SJL and stimulants' exposure was assessed. A significant association between SJL and smoking and soft drinks' consumption is shown. Participants who smoke an average of 24.9 cigarettes per week are more prone to >2-h SJL. There is no significant association found between SJL and coffee or minutes of sun exposure [Table 4].
|Table 4: Participants' characteristics in categories of social jet lag as well as associations between social jet lag and stimulants' exposure|
Click here to view
| Conclusion|| |
In conclusion, SJL has proven to be highly distributed among our population, as almost half of the sample suffers from >2-h SJL.
To sum up the correlation between SJL and predictors, lower SJL hours are associated with factors such as increased age, similar sleep duration on both work and free days, in addition to alarm use on free days. Whereas, younger age, inflexible work schedule, smoking, and soft drinks' consumption are linked with higher SJL hours.
In the future, we advise making an equally distributed sample between genders. Due to cultural reasons, we did not take alcohol consumption into consideration.
Researchers may inspect more sociodemographic predictors such as marital status, naps, and physical activities, in addition to some chronic diseases, as we suspect a relation between SJL and these factors.
Regarding the significant correlation between SJL and stimulants' consumption (cigarettes and soft drinks), we assume that minimizing smoking and soft drinks is considered a potential factor to aid with better sleep organization.
We would like to thank our participants for giving the time to be a part of our study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Wong PM, Hasler BP, Kamarck TW, Muldoon MF, Manuck SB. Social Jetlag, chronotype, and cardiometabolic risk. J Clin Endocrinol Metab 2015;100:4612-20.
Wittmann M, Dinich J, Merrow M, Roenneberg T. Social jetlag: Misalignment of biological and social time. Chronobiol Int 2006;23:497-509.
Rutters F, Lemmens SG, Adam TC, Bremmer MA, Elders PJ, Nijpels G, et al
. Is social jetlag associated with an adverse endocrine, behavioral, and cardiovascular risk profile? J Biol Rhythms 2014;29:377-83.
Reutrakul S, Hood MM, Crowley SJ, Morgan MK, Teodori M, Knutson KL, et al
. Chronotype is independently associated with glycemic control in type 2 diabetes. Diabetes Care 2013;36:2523-9.
Haraszti RÁ, Ella K, Gyöngyösi N, Roenneberg T, Káldi K. Social jetlag negatively correlates with academic performance in undergraduates. Chronobiol Int 2014;31:603-12.
Collado Mateo MJ, Díaz-Morales JF, Barreno CE, Prieto PD, Randler C. Morningness-eveningness and sleep habits among adolescents: Age and gender differences. Psicothema 2012;24:410-5.
Roenneberg T, Allebrandt KV, Merrow M, Vetter C. Social jetlag and obesity. Curr Biol 2012;22:939-43.
Malone SK, Zemel B, Compher C, Souders M, Chittams J, Thompson AL, et al
. Characteristics associated with sleep duration, chronotype, and social jet lag in adolescents. J Sch Nurs 2016;32:120-31.
[Table 1], [Table 2], [Table 3], [Table 4]