Sleep is crucial for optimum health. During sleep, our body is able to rest and recharge. Sleep is an excellent indicator of health status in both general and sick populations [1]. Quality of sleep is not only a determinant of health but is also an important component of a good quality of life [2]. American sleeping habits have been significantly affected in recent years, with 15.6% of young adults sleeping less than 7 hours/day in 1960, rising to 43% in 2009 (National Sleep Foundation of America). Furthermore, poor sleep habits lead to social, economic, and health problems. Specific health problems include issues such as vascular problems, cerebrovascular diseases, development of neurodegenerative, and obesity. American adults reported around 27.5% to 29. 1% short sleep duration [3]. Various studies have examined relationships between sleep and obesity risk in adults [4].

Noticeable body composition difference has been reported between males and females around the world regardless of ethnicity, region, religion, culture, environment, lifestyle, age, and body size. Females have comparatively higher percentage (25%) of body fat than males (15%), and males tend to have a higher percentage (43%) of muscle mass than females (36%) [5]. Males have greater lean mass and a more central fat pattern while females have peripheral fat distribution, identified as fat accumulated in hips and limbs, predominantly into the lower body [6].

Males and females experience sleep differently throughout their life. They face different challenges to sleep. Females are more prone to insomnia, while males are more likely to suffer from a sleep disorder like sleep apnea and snoring [7]. Galland et al. found that 56% of adolescents had poor sleep quality with a higher prevalence among females (63.1% vs. 44.5% among males), and sleep hygiene was significantly worse in females [8]. The insomnia (sleeplessness) enhanced from 3.4% to 12.2% in females and from 4.3% to 9.1% in males [9]. Ohayon and Zulley reported that the prevalence of global dissatisfaction of sleep increased with age and was higher in females [10]. A significant age difference was found to be related to sleep disturbance and habitual sleep patterns in 15 years of age or older adolescents. A number of studies have found that sleep duration is inversely related to BMI [11]. The studies on sleep and body composition in Saudi Arabia on adolescents found an inverse association between poor sleep duration (less than seven hours per day) and obesity/overweight [12, 13]. Inadequate sleep also reduces the burning of calories throughout the day, leading to weight gain and an unhealthier body. Earlier research assessing the relationship between obesity and sleep duration used BMI or weight gain as outcomes, and limited research measured body fat or abdominal obesity [14, 15]. Mahfouz et al., conducted a cross-sectional study in Saudi Arabia revealed that female university students have poor sleep quality (69.1%) as they slept a mean of 4.77 hours/night [16]. Epidemiological studies had shown a contrary correlation between BMI and sleep duration [17]. Sleep medicine in Saudi Arabia emphasizes the need for further sleep investigation to address the prevalence of various sleep disorders amongst the Saudi population according to their lifestyle and body composition [18].

Research findings regarding gender differences have been inconsistent. Genders not only diverge in height and weight but also multiple anthropometric indices and sleep habits. An increasing body of evidence from various populations demonstrates that there are adverse associations between anthropometric indices and sleep habits. Therefore, this investigation set up to evaluate the association between multiple anthropometric indices and sleep habits for males and females students. We also hypothesized that sleep and multiple anthropometric indices are significantly associated with both genders.

Table 2 details the mean and standard deviation of all variables by gender. The percentage of body fat is higher in females 30.01(6.49) than males 27.93(9.21). The visceral fat area is lower in female 57.38(31.27) than in male 102.51(7) participants. Males 93.19(21.51) have a wider waist circumference than female 76.65(8.82) participants. The hip circumference of males 108.02(11.43) is wider than the females 97.53(4.74). The waist-hip ratio is higher 0.85(.11) in males than the females 0.78(.06). The waist-height ratio is also greater in males 0.56(.12) than females 0. 49(.06). All the multiple anthropometric variables are significant at 0.05.

Table 3 shows the mean rank between males and females for multiple anthropometric indices and sleep habits (PSQI & ESS). The results show that all variables are significant. The significant differences existed at 0.05 levels among males and female participants.

Table 4 shows the correlation (Spearman-correlation (2-tails) among multiple anthropometric indices and sleep habits. There was a negative relationship found between sleep habits and PBF. No significant relationship has been found among any anthropometric indices for sleep quality, and daytime sleepiness also showed an insignificant.

Table 5 reveals that there is a very low positive correlation (Spearman-correlation (2-tails) among multiple anthropometric indices and sleep quality and daytime sleepiness for male and female participants. Whereas, daytime sleepiness for female participants shows low negative correlation among multiple anthropometric indices except for hip circumference. The relationship is insignificant for multiple variables.

This research examines the relationship between selected anthropometric indices and sleep habits among male and female subjects. The results of this research demonstrated that there was a significant difference between male and female participants for multiple anthropometric variables, but no significant correlation among any anthropometric indices with sleep habits. Only the percentage of body fat was higher in females than males.

Regarding the gender differences for anthropometric indices, sleep habits, and daytime sleepiness, a prevalence of excess BMI, VFA, WC, HC, WHR, WHtR was observed among males, whereas females had an excess percentage of body fat. Öztürk and Yabanc Ayhan did not find any association between body fat, body fat percentage, BMI, WC, and sleep quality, in a cross-sectional study of Turkish women [25]. In another Turkish study, no association between BMI and sleep quality was found [26]. Similarly, it was noticed in China that sleep quality and BMI do not have a significant association in older people [27]. In this study, males represented 45% of the sample and had a higher BMI 27.06(8.11) and better sleep habits 8.14(2.24) and daytime alertness 10.92(3.62) than females. Females were more likely than males to report both poor sleep habits 7.75(2.45) and daytime sleepiness 9.84(4.05). These findings are different from the Chinese study where obese adults are more likely to have a short sleep duration than their non-obese counterparts [28]. Most of the females have less daytime sleepiness and poorer sleep habits during the night due to biological and psychological factors such as hormonal makeup, enhanced risk of depression, rearing demands, and overall greater ease of disclosing sleep-related intricacies [29].

In the present study, females represent 55% of the sample and exhibited more percentage of body fat 30.01(6.49) than males 27.93(9.21). There was a significant difference, but no significant association was observed between the percentage of body fat and sleep habits in either males or females, but females had a negative correlation. These findings are similar to Rontoyanni et al. [30]. They reported a negative correlation between sleep duration and fat percentage in healthy females, supporting the idea that sleep duration significantly correlated with body fat. Daytime sleepiness is the lowest in underweight people, whereas the highest in obese participants. In a study Wang et al. that engaged 5518 children aged 9-12,found that girls had significantly lower weight, BMI, and WHtR, but a higher percentage of body fat than boys. Yen et al. observed a negative and insignificant association between self-reported short sleep duration and the percentage of body fat among Chinese men and women [31]. Ozturk and Yabanc Ayhan [25] also did not find any relationship between sleep quality and body fat percentage in a cross-sectional study on Turkish women.

In the present study, males exhibited more Visceral Fat Area (VFA) 102.51(70) than females 57.38(31.27). There was a significant difference, but insignificant association was noted between VFA and sleep habits in both genders, but females had a negative correlation for daytime sleepiness. Visceral fat area corresponds to 10-20% of total body fat in men, and 5-8% of total body fat in women, increasing after menopause [32]. It has been seen that the number of obesity-related risk factors increases with the visceral fat area [33]. A six-year longitudinal analysis on sleep and visceral adiposity revealed that the change in sleep duration was not associated with visceral adiposity changes in adults [34]. A study revealed gender differences for VFA and Obstructive Sleep Apnea (OSA), found there is an independent association with VFA only in men, but not women [35].

In the present study, males measured larger Waist Circumference (WC) 93.19(21.51) than females 76.65(8.83). There was a significant difference, but no significant association was seen between WC and sleep habits in either male or female. Waist circumference is highly dependent on the quantity of visceral adipose tissue [36]. The results are in line with some earlier findings in that they did not notice an association between sleep duration and any of obesity indicators among male and female throughout any distribution of BMI and WC [37, 25]. In contrast, Mathews et al. identified a significant association between high waist circumference and poor sleep quality for university students [38]. Rahe et al. also observed a significant correlation between high waist circumference and poor sleep quality [39]. Davidson et al. have revealed that WC correlates most significantly with sleep duration for both women and men in a cohort of 414 patients [40].

In this study, males showed wider hip circumference 108.02(11.4) than females 97.53(4.74). There was a significant difference, but no noteworthy association was seen between the hip circumference and sleep habits in either males or females. Mathiyalagen et al. performed a cross-sectional study in a Non-communicable disease clinic of a rural health training center in South India. In their study, they found that there was a significant difference in the hip circumference between the group considered to be at low risk and high risk of developing OSA [41]. A cohort study examines anthropomorphic measures concerning obstructive sleep apnea for men (47%) and women (53%). The stepwise linear regression analysis showed explanatory variable of hip circumference was not significant (P=.064) [42]. A cross-sectional study conducted on105 women aged ranged 20-25 years at a public institution found that HC was not different between groups (P <.05). (25). A study was conducted by analyzing the medical records of 952 adults from hospitals. They found that hip circumference was most positively correlated (CC: .403) with apnea-hypopnea index for men and women, (CC:0.420, P ˂ .001) and (CC:.188, P ˂ .001) respectively [43].

In this study, males showed a greater waist-hip ratio .85(.11) than female .78(.06). There was a significant difference, but no significant association was seen between waist-hip ratio and sleep habits in either males or females. WHR is a feasible and straight forward measure to estimate abdominal fat. A study conducted on Taif University students showed a significant positive correlation of sleep disturbance scale and daytime sleepiness with waist-to-hip ratio, and the daytime sleepiness was more prevalent in females than males [44]. A study conducted in Turkey showed no statistically significant differences for WHR with poor sleep quality and good sleep quality in women; they also have a waist-hip ratio within normal limits [25]. Andreeva et al. revealed that there was no significant association was observed with WHR for men, but for women, a significant association existed between WHR and chronic insomnia [45]. Turkish adults do not indicate any significant relationship between anthropometric indices and WHR, either males or females too. The lack of relationship between sleep and WHR may be the result of a significant association between any anthropometric indices.

In this study, males indicated a greater waist-height ratio .56(.12) than females .49(.06). There was a significant difference, but no significant association seen between the waist-height ratio (WHtR) for sleep habits in either males or females. Earlier research by Hazzaz illustrated that sleep duration was more affected by the joint, abdominal obesity, and general obesity rather than low WHtR and High BMI or High WHtR and low BMI of adolescents [46]. In other research, the waist-height ratio measured to be higher in obstructive sleep apnea syndrome patients. Correlation analysis of anthropometric measurement (WHtR) did not reveal any difference in either of the gender [47]. A cross-sectional study of South Korean adolescents indicated that there was no significant association between sleep duration and WHtR for girls. Whereas a decreased sleep duration was associated significantly with increased WHtR for boys [48]. These findings are in contrast with earlier researches indicating a negative relationship between WHtR and sleep duration [49].

The study concludes on analysis for the anthropometric indices, sleep quality, and daytime sleepiness in regard to gender. All are positively associated with each other, but there is an insignificant difference. Such studies could be helpful in evaluating the role of anthropometric measurement in predicting the quality of sleep and daytime sleepiness between male and female participants.