Sleep deprivation adversely affects memory, attention, mood management [1], cognition, motor reactions to stimuli [2], and performance in professional or academic settings [3]. During their time at college, students encounter a newfound sense of independence since they are no longer under the direct control of their parents. However, they also face the challenge of managing a more demanding academic workload and unpredictable schedules [4,5]. Several variables, such as an imbalanced diet, harmful habits like alcohol use, smoking, and insufficient sleep, as well as continuous use of mobile devices, can negatively impact the well-being of students [6–8]. According to reports from both children and adults, it is usual for them to use cell phones at night [9, 10]. It has emerged as a significant obstacle to health progress [11, 12]. Sleep plays a crucial role in regulating neuroendocrine function and glucose metabolism in both children and adults [13, 14]. Insufficient sleep disrupts both metabolic and endocrine processes, resulting in lower glucose levels, reduced insulin sensitivity [15, 16], elevated nighttime cortisol levels [17, 18], and lowered levels of leptin. Cortisol is commonly referred to as the "stress hormone." Nevertheless, it exerts numerous significant effects and fulfills various roles throughout the body, apart from its role in regulating the body's stress response. The precise mechanism by which cortisol regulates blood pressure in humans remains uncertain. Nevertheless, excessive amounts of cortisol can lead to hypertension, whereas insufficient quantities of cortisol might result in hypotension. Consequently, these factors lead to increased hunger and appetite [19]. Short sleep duration is associated with higher body mass index (BMI) and elevated blood pressure (BP) [20]. In recent decades, adolescents' sleep patterns have changed in response to social restraints, increased peer interaction, school demands, and extracurricular activities. Elevated blood pressure in childhood serves as a predictor for the occurrence of coronary artery disease in adulthood [21]. Researchers have linked short sleep duration to both hypertension and coronary artery disease in adults. Hypertension, as stated by the World Health Organisation (WHO), is a leading contributor to early mortality on a global scale [22]. Global data indicates that in India, the prevalence of hypertension was 20.6% among men and 20.9% among women in 2005. By 2025, projections indicate that these rates will rise to 22.9% for men and 23.6% for women [23, 24]. The notable rise in BMI among medical college students associated with insufficient sleep duration prompted the planning of this study. Furthermore, numerous epidemiological studies have consistently demonstrated a statistical correlation between excessive sleep and both morbidity and death [25, 26]. Chronic partial sleep deprivation results in a state of weariness, which can subsequently lead to a decrease in physical activity. Sleep deprivation can also cause neuro-hormonal changes that lead to an increase in calorie consumption [27]. Sleep not only plays a crucial role in maintaining appropriate brain function but also has a significant impact on regulating various other bodily systems. This becomes more apparent while experiencing sleep deprivation [28]. Hence, sleep has a crucial role in regulating the functions of neuroendocrine and glucose metabolism. Therefore, this study aimed to assess the correlation between body mass index and sleep quality among medical college students.

A cross-sectional study was carried out at Indira Gandhi Institute of Medical Sciences, located in Patna, Bihar, India. The Institute Ethics Committee granted ethical approval. The study was conducted following the principles outlined in the Declaration of Helsinki standards. Consent was gained from the participants after providing them with relevant information.

Inclusion criteria: Healthy male and female undergraduate MBBS students between the age group of 18-25 years were included.

Exclusion criteria: The study excluded MBBS students who had a history of prolonged use of medicine for acute or chronic illnesses, a history of hypertension, those who had consumed tea or coffee or had a substantial breakfast, and those who had exercised within 30 minutes of blood pressure measurement.

Sample size calculation: The sample size was determined using a single population proportion with a power of 95% and a significance level of 5%, as suggested by Bisht RS et al., [29]. The calculation utilized G* power and determined a sample size of 138.

Study Procedure:

The participants' demographic data encompassed age, gender, sleep duration, family history of hypertension, presence of other medical conditions, smoking behavior, alcohol intake, level of physical activity, and medication usage. The individuals' sleep quality was assessed using the PSQI [30, 31]. The assessment comprises seven elements: • Subjective assessment of sleep quality; • Time taken to fall asleep; • Duration of sleep; • Regular sleep efficiency; • Disruptions during sleep; • Use of sleep-inducing medications; • Daytime impairment experienced in the past month. We assess each item on a scale from 0 to 3. We calculate the global PSQI score by summing the scores of the seven components, which results in a total score ranging from 0 to 21. A number below 5 indicates better sleep quality, whereas a score of 5 or more indicates poor sleep quality.

We assessed the subjects' weight, and height using the weighing scale and stadiometer tools. We measured the participants' weight when they were barefoot and wearing lightweight clothing. We measured the participants' height with a stadiometer while they were barefoot, their heels, hips, shoulders, and head in a neutral position. We computed the BMI by dividing the weight in kilograms by the square of the body height in meters (kg/m2). The Health Ministry and diabetes foundation of India established a body type categorization in 2015 to categorize the body mass index (BMI) of students. The categories included normal weight (18.5≤24.9), overweight (25≤29.9), moderately obese (30≤34.9), severely obese (35≤39.9), and very seriously obese (>40 kg/m2) [32,33].

Statistical Analysis: The collected data was organized into a table using Microsoft Excel 2019. Subsequently, the data was transferred to GraphPad version 8.4.3 for further statistical analysis. The frequency and proportion of sleep quality and BMI were examined using descriptive statistics.  The link between BMI and sleep quality was determined using Karl Pearson's correlation coefficient. The researchers employed a chi-square test to examine the correlation between sleep quality and the demographic characteristics of the subjects.

We overview the Body Mass Index (BMI) distribution among males and females in Table 1. First, it categorizes individuals into four BMI categories: underweight, normal, overweight, and obesity. There are 22 males (15.94%) and 24 females (17.39%) who are underweight, totalling 46 individuals (33.33%). In the normal weight category, there are 36 males (26.09%) and 35 females (25.36%), making up 71 individuals (51.45%). For the overweight category, there are 10 males (7.25%) and 8 females (5.81%), totalling 18 individuals (13.06%). Lastly, in the obesity category, there are 2 males (1.44%) and 1 female (0.72%), totalling 3 individuals (2.16%). Overall, there are 138 individuals in the study, with 70 males (50.72%) and 68 females (49.28%). We observed no significant difference in BMI distribution between males and females [chi-square value 0.627 and p-value 0.89].

Table 1: Showing gender-wide body mass index of students

 [* Statistically not significant]

In Table 2; we observed that in the underweight category, males have a mean BMI of 16.25 ± 0.95 and a mean sleep score of 3.12 ± 1.36, while females have a mean BMI of 16.27 ± 0.99 and a mean sleep score of 2.99 ± 1.34. Both groups demonstrated a statistically significant p-value of <0.0001. Among those with normal weight, males have a mean BMI of 20.74 ± 1.70 and a mean sleep score of 3.01 ± 1.12. Females in this category have a mean BMI of 21.38 ± 1.78 and a mean sleep score of 3.37 ± 1.16. Both subgroups had a significant p-value of <0.0001. For the overweight group, males have a mean BMI of 27.10 ± 1.99 and a mean sleep score of 4.35 ± 2.85. Females have a mean BMI of 26.58 ± 1.75 and a mean sleep score of 5.32 ± 2.15. The p-value for both genders in this category was <0.0001, indicating statistical significance. In the obesity category, the males have a mean BMI of 33.58 ± 0.72 and a mean sleep score of 5.42 ± 0.17, with a p-value of 0.003. Females have a mean BMI of 33.21 and a mean sleep score of 6.11, with a p-value of <0.0001. These results suggest significant variations in sleep scores across different BMI categories and genders, with all groups showing statistically significant differences in their respective p-values.

Table 2: Showing the association of Body Mass Index (BMI) classification and mean sleep score among students

[# Statistically significant]

We found a strong positive correlation between the mean BMI and mean Sleep Score among the MBBS students (Pearson’s r = 0.339, p-value < 0.0001). Consequently, our study indicates a negative association between the mean BMI and sleep quality in these students.

A total of 138 samples were analyzed to provide anthropometric measures, specifically weight, and height. The sleep quality of obese male students was indicated by a mean sleep score of 5.42, while obese female students had a mean sleep score of 6.11, both of which suggest poor sleep quality. Our observation reveals that boys in the underweight category have a sleep score with a mean value of 3.12 ± 1.36, whereas girls in the same category have a sleep score with a mean value of 2.99 ± 1.34. Among individuals who have a healthy weight, the average sleep score for males is 3.01 ± 1.12. Women in this group have an average sleep score of 3.37 ± 1.16. In the overweight category, the average sleep score for males is 4.35 ± 2.85. On average, females have a sleep score of 5.32 ± 2.15. Regarding obesity, males have an average sleep score of 5.42 ± 0.17, while females have an average sleep score of 6.11. A recent study conducted on healthcare students, focusing on BMI, BP, and sleep, revealed a strong and statistically significant correlation between shorter sleep duration and greater BMI, as well as higher systolic blood pressure (SBP). The duration of sleep was found to have a significant association with diastolic blood pressure (DBP) in both male and female student participants [29]. A longitudinal study discovered that females exhibited longer sleep duration and higher blood pressure, but no significant correlation was observed in males. Additionally, sleep durations below 8 hours were linked to an elevated risk of hypertension [8,14]. Over the past twenty years, high BMI has emerged as a major global public health issue. A body mass index (BMI) higher than 25 kg/m2 in the general population has been well-documented as a risk factor for cardiovascular, metabolic, and musculoskeletal illnesses [30]. Additional research studies reported that 81.5%, 73.2%, 64.84%, and 52.4% of the subjects exhibited favorable sleep quality [31-35]. High-quality sleep is associated with a range of beneficial effects, such as improved physical health, decreased daytime tiredness, heightened well-being, and enhanced psychological functioning. Persistent insomnia is characterized by a low quality of sleep [36]. Although the idea of sleep quality is commonly employed, a comprehensive analysis of the empirical literature indicates that it remains incompletely comprehended. The current investigation revealed a statistically significant correlation between the number of hours of sleep and the sleep quality scores of the subjects. This phenomenon may be attributed to the increased utilization of smartphones at night by medical students, who are occupied with clinical duties in the morning and devote more time to fulfilling academic obligations during the night [36]. Research has demonstrated a notable correlation between the length of sleep, body mass index (BMI), and blood pressure (BP) [37,38]. The evaluation of our sleep is determined by the self-reported quality of sleep, using the PSQI as a reference. Nevertheless, numerous prior research has employed the same instrument to evaluate sleep quality, which has consistently demonstrated superior measurement of sleep quality on a global scale.

The present study found that overweight and obese MBBS students had shown poor sleep quality. Good sleep quality was found with normal BMI and underweight MBBS students. Subsequent follow-up of sleep quality and weight gain over time would be ideal for combating the promotion of healthy sleep among the students.

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