The effects of different types of undergraduate education on body weight,appetite,and physical activity habits in normal-weight Saudi female students

Abstract

Objective:

Overweight and obesity are highly prevalent in Saudi Arabia, likely due to a combination of poor dietary choices and sedentary lifestyles. Young Saudi females face increasing societal pressure related to family life and higher education. Previous studies suggest that the transition to higher education at the university level, particularly in health-related disciplines, is a critical period for the development of unhealthy lifestyle. In this study, we aimed to evaluate changes in weight, appetite, and physical activities among medical students over time and compare them with those of nonmedical students.

Methods:

In this 5-month prospective cohort study, we evaluated changes in weight, appetite, and physical activity among normal-weight females enrolled in medical (n = 25) and business (n = 26) programs at the University of Jeddah, Saudi Arabia, during a single academic semester.

Results:

Business students experienced a small but significant weight loss (approximately 1.7%, p = 0.03), while medical students showed no change in weight (p = 0.83). However, in both groups, waist circumference increased significantly (3%–4%; p = 0.012), suggesting a shift toward central fat accumulation. Total physical activity, particularly low-intensity activity, decreased significantly in both groups (p < 0.03). Sedentary time increased in business students but decreased among medical students (time-by-group interaction, p = 0.003). Diastolic blood pressure followed an opposite pattern; it decreased significantly in business students (−6.3%) and increased significantly in medical students (+3.0%; time-by-group interaction, p = 0.003).

Conclusions:

Different academic disciplines were not associated with weight gain among initially normal-weight Saudi females. Both groups experienced an unfavorable shift in body fat redistribution (increased waist circumference), likely driven by reduced physical activity. These changes may exacerbate long-term health risks even in the absence of overt obesity, underscoring the need for lifestyle interventions.

Keywords

Women’s health obesity university education medical students

Introduction

According to the World Health Organization, the population of overweight or obese adults is nearing 2.5 billion worldwide (44% female and 43% male).¹ In Saudi Arabia, the prevalence of obesity among adults is 20.2% and that of overweight is 38.2%.² Several local factors, including sociocultural influences and environmental conditions, such as high temperatures, likely contribute to a predominantly sedentary lifestyle and a high prevalence of obesity, particularly among Saudi females.³ In Saudi Arabia, cultural barriers between males and females are contributing factors to reduced physical activity among females, as special requirements are needed for outdoor activities.^4,5 Importantly, the Saudi population exhibits a large variability in physical activity habits, with reduced physical activity being more detrimental for body weight homeostasis in females than in males.⁶

This gender gradient can be exacerbated by the societal pressure for young females to start a family and become mothers³ and by the increasing demand for obtaining a university education, which can be stressful for some students, thus worsening the already suboptimal lifestyle habits and weight gain.^7,8 A meta-analysis concluded that two-thirds of university students exhibited an average of 3.4 kg of weight gain.⁹

Overweight and obesity are highly prevalent among Saudi university students,¹⁰ and several studies have evaluated the association between overweight, obesity, and dietary habits. An undergraduate medical education is particularly stressful, leading to poor dietary habits, particularly regarding a healthy meal selection.^11,12 Physical activity is also an important aspect of body weight homeostasis.¹³ Besides unhealthy dietary habits, sedentary lifestyles have emerged as a leading cause of obesity among Saudi students, perhaps to a greater extent than a high frequency of snack consumption.^14,15

Most studies evaluating obesity in undergraduate Saudi medical students were cross-sectional studies.^9,10 Hence, we conducted this prospective cohort study to evaluate the changes in weight, appetite, and physical activities among medical students over time and compare them with those of nonmedical students to evaluate whether these changes are specific to the demanding medical education or to university students in general. We recruited medical students at the University of Jeddah because they experience heavy educational load. The medical curriculum includes an intensive timetable, several subjects, and frequent examinations throughout the semester. Moreover, medical students are required to attend lectures, laboratory sessions, and clinical training daily at the university. For comparison, we recruited business students as “controls.” Compared with medical students, business students typically have fewer contact hours, have a lighter course load, and are not required to attend classes every day.

Methods

Study design and participants

This was a prospective cohort study. A total of 51 female students were recruited from 2 university faculties: 25 female participants from the College of Medicine and 26 female participants from the College of Business, all in their third academic year at the University of Jeddah, Saudi Arabia. This study was reported according to Strengthening the Reporting of Observational studies in Epidemiology guidelines.¹⁶

Ethics approval

Ethical approval for this study was obtained from the Bioethics Committee for Scientific and Medical Research at the University of Jeddah, Jeddah, Saudi Arabia (application number: UJ-Rec-179, dated November 26, 2023). The study was conducted in accordance with the Helsinki Declaration of 1975, as revised in 2024.

Recruitment

Participants were recruited through WhatsApp messages and in-person announcements delivered by senior medical students prior to the commencement of the second academic semester. The follow-up measurements were conducted at the end of the second academic semester. Trial registration is not applicable as our study did not include any intervention. No formal sample size calculation was performed. We were required to enroll the maximum feasible number of students for this study. All participants were selected randomly. All participants’ details are de-identified. Each potential participant received an information sheet outlining the study objectives and procedures.

Written informed consent

Written informed consent was obtained from those who agreed to participate before the initial measurements were taken. No minors were included in this study.

Inclusion and exclusion criteria

Healthy female students with a normal body mass index (BMI) between 18.5 and 24.9 kg/m² were recruited. The reason for focusing on normal-weight participants was to evaluate the effects of different types of education in the absence of prior established overweight or obesity. Students with chronic diseases, those receiving medications or supplements that affect weight and appetite, those who are overweight or obese (BMI ⩾25 kg/m²), and those who had undergone bariatric surgery were excluded (Table 1).

Table 1.

Exclusion criteria.

N	Reasons
32 BMI	9 Obese (BMI ⩾30) 19 Overweight (BMI 25–29.9) 4 Underweight (<18.5)
10 Medical conditions	4 Polycystic ovary syndrome 3 Diabetes mellitus 1 Crohn’s disease 1 Chronic constipation 1 Mitral regurgitation
7, Medications	1 Metoclopramide 1 Amitriptyline 2 Semaglutide 2 Metformin 1 Lisinopril
1 Surgery	Bariatric surgery

BMI: body mass index.

Study period

Data collection started at the beginning of February 2024 and concluded at the end of June 2024. Measurements were taken and questionnaires were administered at the beginning and end of the study, that is, the start and end of the second academic semester (Supplementary File).

Data collection

Data were collected through direct measurements and standardized questionnaires, administered at two time points: the beginning and end of the semester. The research team was trained on standardized procedures to ensure consistency in and reliability of the obtained data. All measurements were conducted in the morning between 7:00 a.m. and 9:00 a.m., prior to the start of their first lecture, by senior medical students.

Anthropometric and physiological measurements

The measurements included weight, height, BMI, waist and hip circumferences, waist/hip ratio, blood pressure, and random blood glucose test (without controlling for the preceding fasting period).

Body weight was measured using the Eufy Smart Scale (Anker Innovations, Changsha, China).¹⁷ Participants stood barefoot and upright at the center of the scale platform, maintaining a stable posture and full contact with the electrodes. Measurements were taken under standardized conditions, with participants barefooted and wearing light clothing. Waist and hip circumstances were measured with a flexible non-elastic tape.

Blood glucose levels were assessed using the EasyMax Self-Monitoring Blood Glucose System (EasyMax, Hsinchu, Taiwan). Participants were instructed to wash their hands prior to sampling, and a small drop of blood was obtained from the fingertip using a sterile lancet. The blood sample was then applied to a disposable test strip inserted into the glucose meter, and readings were displayed within a few seconds. All measurements were performed according to the manufacturer’s instructions.

Blood pressure (systolic and diastolic) was measured using the Geratherm Smart Blood Pressure Measuring Device (Geratherm Medical AG, Geratal, Germany). Participants were seated comfortably with their arm supported at heart level, and measurements were taken after a minimum rest period of 5 min. An appropriately-sized cuff was placed around the upper arm, and readings were obtained following the manufacturer’s recommendations.

Self-perceived appetite

Appetite (hunger and satiety) was assessed using standard visual analog scales (VAS).¹⁸ The questionnaire included four questions: How hungry are you? How satisfied are you? How full do you feel? How strong is your desire to eat? Responses were recorded on a horizontal line anchored with two extreme answers (“not at all” to “extremely”), allowing participants to indicate their subjective feelings.

Stress assessment

The Perceived Stress Scale questionnaire, validated in Arabic,¹⁹ was used to evaluate participants’ perceived stress, overall psychological state, and mental well-being.

The International Physical Activity Questionnaire

Physical activity levels were assessed using the Arabic version of the International Physical Activity Questionnaire (IPAQ).²⁰ The questionnaire evaluated the frequency and duration of physical activity over the past 7 days, including high- and medium-intensity activities, walking, and sedentary behavior.

Statistical analysis

Data were tested for normality using the Shapiro–Wilk test and log-transformed for analysis if they were not normally distributed. Differences between the two groups and the start and end of the study were evaluated using repeated measures analysis of variance with one within-subject factor with two levels (time: before versus after) and one between-subject factor with two levels (group: medical versus business). Interactions between group and time at p < 0.10 were followed using paired comparisons (Least Significant Difference test) within each group, as there were only two time points. Statistical significance was set at p ⩽ 0.05. All analyses were performed using SSPS version 29 (IBM SPSS, Chicago, IL, USA). There were no missing data in this study.

Results

A total of 51 female students were recruited from both faculties. The interaction terms for weight and hip circumference approached significance (p = 0.08). Business students exhibited a significant reduction in weight from 51.8 ± 8.9 to 50.9 ± 8.2 kg (p = 0.030), whereas weight remained stable among medical students (p = 0.828; Table 2). Nonetheless, variability was observed in weight changes in both groups (Figure 1).

Table 2.

Characteristics of students in the business and medical faculties.

Parameter	Business (n = 26)		Medicine (n = 25)		RANOVA p-values
Parameter	Pre	Post	Pre	Post	Time	Group	Interaction
Weight (kg)	51.8 ± 1.7	50.9 ± 1.6*	55 ± 1.6	54.9 ± 1.6	0.050	0.128	0.084
Height (cm)	1.55 ± 0.01		1.59 ± 0.01		—	0.015	—
BMI (kg/m²)	21.5 ± 0.6	20.4 ± 1	21.8 ± 0.6	21.8 ± 0.7	0.184	0.427	0.154
Waist (cm)	62 ± 1.1	63.7 ± 1.3	66.3 ± 1.3	68.9 ± 1.9	0.012	0.012	0.595
Hip (cm)	89.2 ± 1.5	90.1 ± 1.4	92.7 ± 1.7	95.8 ± 1.6*	0.002	0.032	0.082
WHR	0.70 ± 0.01	0.71 ± 0.01	0.72 ± 0.01	0.72 ± 0.01	0.426	0.236	0.507
Random glucose (mg/dL)	98.5 ± 2.6	93.8 ± 1.6	95.9 ± 1.6	92.6 ± 3.1	0.069	0.456	0.743
PSS score	19.8 ± 1.2	20.9 ± 1.3	23.2 ± 0.9	21.8 ± 1.2	0.881	0.113	0.202
VAS, A	4.3 ± 0.5	4.7 ± 0.5	4.8 ± 0.5	5 ± 0.4	0.379	0.455	0.857
VAS, B	6.5 ± 0.5	6 ± 0.5	5 ± 0.6	4.8 ± 0.4	0.413	0.014	0.773
VAS, C	3.7 ± 0.6	4.2 ± 0.5	3.1 ± 0.6	3.9 ± 0.6	0.254	0.468	0.791
VAS, D	4 ± 0.7	3.2 ± 0.6	5.5 ± 0.6	5.8 ± 0.6	0.607	0.004	0.329
IPAQ, overall	1.19 ± 0.15	0.81 ± 0.17	0.72 ± 0.16	0.60 ± 0.20	0.027	0.101	0.239
IPAQ, low MET-min/week	1334.6 ± 242.5	769.8 ± 149.2	931.9 ± 252.4	660.7 ± 182.3	0.028	0.279	0.431
IPAQ, mod MET-min/week	613.8 ± 322.6	764.6 ± 264.1	258.4 ± 77.8	360 ± 172	0.512	0.16	0.898
IPAQ, vig MET-min/week	1104.6 ± 370.9	649.2 ± 280.8	489.6 ± 245.7	624 ± 244.4	0.503	0.347	0.221
IPAQ, total MET-min/week	3053.1 ± 674.7	2183.7 ± 579.4	1679.9 ± 478.7	1644.7 ± 438.6	0.307	0.148	0.345
IPAQ, sedentary hours	6.9 ± 0.5	8.8 ± 0.7*	11.4 ± 0.6	9.9 ± 0.6*	0.737	<0.001	0.003
SBP (mmHg)	115.1 ± 1.8	112.4 ± 1.3	111.3 ± 1.9	110.4 ± 2.1	0.116	0.208	0.457
DBP (mmHg)	77.2 ± 1.6	72.3 ± 1.2*	74.6 ± 1.7	76.8 ± 1.2	0.247	0.580	0.003

Data are means ± SEM. VAS—How hungry are you? (VAS, A), How satisfied do you feel? (VAS, B), How full do you feel? (VAS, C), How much do you desire to eat? (VAS, D). IPAQ—Overall activities (IPAQ, overall), low-intensity activities (IPAQ, low MET-min/week), moderate-intensity activities (IPAQ, mod MET-min/week), vigorous-intensity activities (IPAQ, vig MET-min/week). ANOVA: Repeated Measures Analysis of Variance; BMI: body mass index; WHR: waist-to-hip ratio; PSS: Perceived Stress Scale; VAS: visual analog scale; IPAQ: International Physical Activity Questionnaire; SBP: systolic blood pressure; DBP: diastolic blood pressure; SEM: standard error of the mean.

p ⩽ 0.05, indicates a significant within-group change (these comparisons were performed only when for interaction terms with p < 0.01.

Figure 1.

Individual changes in body weight among students in the business and medical faculties.

Despite the reduction in weight, business students experienced a significant increase in waist circumference from 62.0 ± 5.5 to 63.7 ± 6.6 cm (p = 0.012); however, no change in hip circumference (p = 0.203) was noted. Medical students experienced a significant increase in both waist (p = 0.012) and hip circumference (p = 0.005).

A trend of decreasing glucose concentration (p = 0.069) was noted in both groups. Systolic blood pressure did not change, but a significant interaction was observed for diastolic blood pressure (p = 0.003), which showed significant decrease among business students (p = 0.003) but nonsignificant increase among medical students (p = 0.200; Table 2).

A significant decrease in total physical activity was observed in both groups (IPAQ overall activity score; p = 0.027), which was exclusively attributed to a reduction in low-intensity physical activity (p = 0.028). Moderate- and vigorous-intensity activities remained stable and did not differ between groups (Table 2). A significant interaction was found for sedentary time, which increased among the business students (p = 0.027) but decreased among the medical students (p = 0.047; Table 2).

The mean differences in the within-group changes, with 95% confidence intervals, along with corresponding effect sizes (Cohen’s d) are shown in Table 3.

Table 3.

Differences between students in the business and medical faculties.

Parameter	Change in business (n = 26)	Change in medicine (n = 25)	95% CI of the difference	Cohen’s d
Weight (kg)	−0.86 ± 0.37	−0.06 ± 0.26	−0.81 (−1.72, 0.11)	−0.49
BMI (kg/m²)	−1.12 ± 0.77	0.04 ± 0.14	−1.16 (−2.76, 0.45)	−0.41
Waist (cm)	1.69 ± 0.91	2.56 ± 1.35	−0.87 (−4.12, 2.39)	−0.15
Hip (cm)	0.92 ± 0.71	3.1 ± 1.01	−2.18 (−4.64, 0.29)	−0.50
WHR	0.01 ± 0.01	0 ± 0.01	0.01 (−0.02, 0.04)	0.19
Random glucose (mg/dL)	−4.69 ± 2.15	−3.28 ± 3.76	−1.41 (−10.02, 7.2)	−0.09
PSS score	1.08 ± 1.47	−1.36 ± 1.17	2.44 (−1.35, 6.23)	0.36
VAS, A	0.42 ± 0.62	0.28 ± 0.49	0.14 (−1.45, 1.73)	0.05
VAS, B	−0.5 ± 0.68	−0.24 ± 0.57	−0.26 (−2.06, 1.54)	−0.08
VAS, C	0.5 ± 0.76	0.8 ± 0.83	−0.3 (−2.56, 1.96)	−0.07
VAS, D	−0.77 ± 0.81	0.24 ± 0.62	−1.01 (−3.06, 1.05)	−0.28
IPAQ, overall	−0.38 ± 0.18	−0.12 ± 0.12	−0.26 (−0.71, 0.18)	−0.33
IPAQ, low MET-min/week	−565 ± 276	−271 ± 243	−294 (−1036, 449)	−0.22
IPAQ, mod MET-min/week	151 ± 330	102 ± 186	49 (−719, 817)	0.04
IPAQ, vig MET-min/week	−455 ± 426	134 ± 199	−590 (−1546, 367)	−0.35
IPAQ, total MET-min/week	−869 ± 776	−35 ± 381	−834 (−2588, 919)	−0.27
IPAQ, sedentary hours	1.88 ± 0.8	−1.52 ± 0.73	3.4 (1.23, 5.58)	0.88
SBP (mmHg)	−2.65 ± 1.47	−0.96 ± 1.72	−1.69 (−6.23, 2.84)	−0.21
DBP (mmHg)	−4.88 ± 1.49	2.24 ± 1.7	−7.12 (−11.66, −2.59)	−0.89

Data are means ± SEM for within-group changes, and means with 95% confidence intervals for the difference between groups. VAS—How hungry are you? (VAS, A), How satisfied do you feel? (VAS, B), How full do you feel? (VAS, C), How much do you desire to eat? (VAS, D). IPAQ—Overall activities (IPAQ, overall), low-intensity activities (IPAQ, low MET-min/week), moderate-intensity activities (IPAQ, mod MET-min/week), vigorous-intensity activities (IPAQ, vig MET-min/week). BMI: body mass index; WHR: waist-to-hip ratio; PSS: Perceived Stress Scale; VAS: visual analog scale; IPAQ: International Physical Activity Questionnaire; SBP: systolic blood pressure; DBP: diastolic blood pressure; SEM: standard error of the mean.

Changes in body weight for all enrolled participants (n = 51) correlated positively with changes in waist and hip circumference (Spearman’s rho = 0.317 and 0.450, respectively; both p < 0.025) and with the subjective desire to eat, as assessed by the VAS (rho = 0.297, p = 0.034), but not with changes in perceived stress (rho = −0.079, p = 0.58).

Discussion

In this prospective cohort study, changes in the lifestyle and physical activity of Saudi female students from business and medical colleges were evaluated during a single academic semester (5 months). Contrary to our expectations, we observed that body weight decreased among the business students but did not change among the medical students. Despite the minimal weight loss (approximately 1.7%) in the former and the weight stability in the latter, waist circumference increased in both groups by 3%–4%. This suggests a redistribution of fat toward the upper body, that is, toward an unhealthier pattern (central obesity). These observations do not support the notion that medical education has a more unfavorable effect on body weight regulation and anthropometrics than that had by other types of university education. Nevertheless, they highlight the occurrence of unfavorable changes in fat distribution among young females even in the absence of obesity.

Several studies worldwide have reported an increase in weight among medical students during their university education. Cross-sectional studies from Greece, India, Ghana, and Southeast Europe have reported high rates of overweight and obesity among their medical students.^21–26 In Saudi Arabia, many cross-sectional studies from different universities, such as Qassim University, King Khalid University, Northern Border University, and Jazan University, have reported high rates of overweight and obesity among their medical students.^15,27–29 A recent cohort study by Szemik et al. followed up Polish medical students for 2 years and found that regardless of the academic year, the prevalence of obesity increased over time.³⁰ In contrast, our cohort study found a small amount of weight loss among the business students and no weight changes among the medical students in Saudi Arabia. The possibility of cultural differences accounting for this discrepancy remains to be investigated. The increase in waist circumference in both groups is particularly unsettling, as it coincided with small weight loss (business group) or weight stability (medicine group). This indicates a redistribution of fat within the body and possibly heightened risk of chronic diseases, such as type 2 diabetes, hypertension, and hyperlipidemia.^31–33 Still, with respect to measured risk factors, random glucose tended to decrease, systolic blood pressure did not change, and diastolic blood pressure decreased in business students and increased in medical students. The latter could relate to differing stress levels, sleep patterns, or other unmeasured physiological factors between the two groups. Overall, however, these observations suggest that central fat accumulation in these young females did not lead to unanimous unfavorable alterations in cardiometabolic risk factor profile.

Regarding physical activity, business students spent on average approximately 3000 min per week compared with approximately half of that among medical students, which is extremely lower than that reported in countries such as Poland and Hungary, where students spent approximately 6000 min per week on physical activities.³⁴ This difference reinforces the concept that physical inactivity may be an important contributor to obesity among Saudi university students.⁶ However, our estimates similar to those reported for students in Turkey and Russia (approximately 3000 min/week on physical activities).^35,36 Interestingly, low-intensity physical activity (walking) was the main contributor to the reduction in total physical activity among both groups. As exercise is known to specifically mobilize intra-abdominal fat,³⁷ the reduction is physical activity could be etiologically linked to the increase in waist circumference. Furthermore, group-specific changes were observed in sedentary time, which decreased significantly among the medicine group but increased significantly among the business group. This finding implies that the demands of different university education imprint on students’ physical activity and inactivity patterns in a different manner. Nonetheless, this reduction in sedentary time was not counterbalanced by an increase in other physical activities, which is likely due to the inability of the IPAQ to accurately capture physical activity and inactivity patterns. Overall, efforts should be directed at adopting and promoting a healthier and more physically active lifestyle among university students.³⁸

Our study has several limitations. Due to the relatively small sample size, our comparisons—particularly for outcomes with large within- and between-person variability—may have been underpowered. Other limitations include the lack of dietary and body composition data, absence of comprehensive bloodwork, the possibility of seasonal effects (although these were equally present in the two groups), and the subjective nature of the IPAQ. The lack of dietary information, in particular, prevents a comprehensive understanding of the drivers of central fat accumulation. Furthermore, our findings may not be generalizable to other populations. More studies are needed to investigate the effect of different university education on the health and lifestyles of students, particularly in countries such as Saudi Arabia where overweight and obesity are widespread even at younger ages.

Conclusion

Our study documented education-specific changes in body weight homeostasis, general unhealthy changes in body fat distribution, and a lack of sufficient physical activity among both medical and business female students in Saudi Arabia. Increasing the awareness about healthy lifestyle choices among university students is urgently. This growing concern may warrant a revision of the curriculum to more effectively integrate wellness education.

Supplemental Material

sj-pdf-1-smo-10.1177_20503121251404829 – Supplemental material for The effects of different types of undergraduate education on body weight, appetite, and physical activity habits in normal-weight Saudi female students

Supplemental material, sj-pdf-1-smo-10.1177_20503121251404829 for The effects of different types of undergraduate education on body weight, appetite, and physical activity habits in normal-weight Saudi female students by Ahmad H. Alzahrani, Waad Waleed Khalifa, Nouf Khalied Eldabai, Jawad Fathi Alghamdi, Alwaleed Talal Alshehri, Sulafa Alqutub, Mohammed Qashqary and Faidon Magkos in SAGE Open Medicine

Supplemental Material

sj-pdf-2-smo-10.1177_20503121251404829 – Supplemental material for The effects of different types of undergraduate education on body weight, appetite, and physical activity habits in normal-weight Saudi female students

Supplemental material, sj-pdf-2-smo-10.1177_20503121251404829 for The effects of different types of undergraduate education on body weight, appetite, and physical activity habits in normal-weight Saudi female students by Ahmad H. Alzahrani, Waad Waleed Khalifa, Nouf Khalied Eldabai, Jawad Fathi Alghamdi, Alwaleed Talal Alshehri, Sulafa Alqutub, Mohammed Qashqary and Faidon Magkos in SAGE Open Medicine

Footnotes

Acknowledgements

We would like to thank all medical and business student participants. We would also like to thank the medical and business colleges at Jeddah University for their help and support.

ORCID iD

Ahmad H. Alzahrani

Ethical considerations

Consent to participate

Written informed consent was obtained from those who agreed to participate before the initial measurements were taken. No minors were included in this study.

Consent for publication

Informed consent was obtained from those who agreed to participate before the initial measurements were taken for publication.

Author contributions

Conceptualization, A.A., W.K., N.E., J.A., A.A., S.A., M.Q., and F.M.; methodology, A.A., W.K., N.E., J.A., A.A., S.A., M.Q., and F.M.; software, A.A., J.A., A.A., F.M.; formal analysis, A.A., J.A., A.A., F.M.; investigation, A.A., W.K., N.E., J.A., A.A., S.A., M.Q., and F.M.; resources, A.A., W.K., N.E., J.A., A.A., S.A., M.Q., and F.M.; data curation, A.A., W.K., N.E., J.A., A.A., S.A., M.Q., and F.M.; writing—original draft preparation, A.A., W.K., N.E., J.A., A.A., S.A., M.Q., and F.M. writing—review and editing, A.A., J.A., A.A., F.M.; visualization, A.A.; supervision, A.A., S.A., M.Q., and F.M.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by the University of Jeddah, Jeddah, Saudi Arabia under Grant no. UJ-23-DR-230. The authors would like to thank the University of Jeddah for technical and financial support.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Supplemental material

Supplemental material for this article is available online.

References

World Health Organization. Obesity and overweight, https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (2024, accessed 23 October 2024).

Ministry of Health (Saudi Arabia). The National Health Information Survey, https://www.moh.gov.sa/en/awarenessplateform/ChronicDisease/Pages/Obesity.aspx (2019, accessed 13 June 2025).

Aldubikhi

Obesity management in the Saudi population. Saudi Med J 2023; 44(8): 725–731.

Sharara

Akik

Ghattas

, et al. Physical inactivity, gender and culture in Arab countries. BMC Public Health 2018; 18(1): 639.

Al-Hazzaa

HM.

Physical inactivity in Saudi Arabia revisited. Int J Health Sci (Qassim) 2018; 12(6): 50–64.

Althoff

Sosič

Hicks

, et al. Large-scale physical activity inequality. Nature 2017; 547(7663): 336–339.

Barbayannis

Bandari

Zheng

, et al. Academic stress and mental well-being among university students. Front Psychol 2022; 13: 886344.

Caso

Miriam

Rosa

, et al. Unhealthy eating and academic stress. Health Psychol Open 2020; 7(2): 2055102920975274.

Vadeboncoeur

Townsend

Foster

Weight gain in first-year university students. BMC Obes 2015; 2: 22.

10.

Makkawy

Alrakha

Almubarak

, et al. Overweight and obesity among health sciences students. J Fam Med Prim Care 2021; 10(2): 961–967.

11.

Voltmer

Köslich-Strumann

Voltmer

, et al. Stress and behavior patterns during medical education. BMC Med Educ 2021; 21(1): 454.

12.

Almogbel

Aladhadh

Almotyri

, et al. Stress-associated dietary behaviours among university students. Open Access Maced J Med Sci 2019; 7(13): 2182–2188.

13.

World Health Organization. Physical activity, https://www.who.int/news-room/fact-sheets/detail/physical-activity (2024, accessed 13 June 2025).

14.

Aljefree

Shatwan

Almoraie

NM.

Snacks and obesity among university students. Healthcare (Basel) 2022; 10(2): 400.

15.

Al-Rethaiaa

Fahmy

AEA

Al-Shwaiyat

NM.

Obesity and eating habits among college students. Nutr J 2010; 9: 39.

16.

von Elm

Altman

Egger

, et al. The STROBE statement. J Clin Epidemiol 2008; 61(4): 344–349.

17.

Frija-Masson

Mullaert

Vidal-Petiot

, et al. Accuracy of smart scales on body composition. JMIR Mhealth Uhealth 2021; 9(4): e22487.

18.

Flint

Raben

Blundell

, et al. Visual analogue scales for appetite sensations. Int J Obes 2000; 24(1): 38–48.

19.

Ali

Hendawy

Ahmad

, et al. Arabic version of the Perceived Stress Scale. Brain Sci 2021; 11(4): 419.

20.

Craig

Marshall

Sjöström

, et al. International Physical Activity Questionnaire reliability and validity. Med Sci Sports Exerc 2003; 35(8): 1381–1395.

21.

Yorke

Agyei

Boima

. Overweight and obesity among medical students in Ghana. Afr J Health Sci 2024; 35(2): 99–113.

22.

Ilić

Pang

Vlaški

, et al. Overweight and obesity among medical students in the Western Balkans. BMC Public Health 2024; 24: 29.

23.

Jha

Yadav

Shrestha

. Body mass index among Nepalese medical students. J Nepal Med Assoc 2021; 59(235): 280–283.

24.

Purohit

Shah

Harsoda

. Obesity and cardiovascular risk in medical students. Kathmandu Univ Med J 2015; 13(4): 341–345.

25.

Amatya

. Body mass index of Nepalese medical students. Int J Dev Res 2014; 4(3): 746–748.

26.

Bertsias

Mammas

Linardakis

, et al. Cardiovascular risk factors among medical students in Crete. BMC Public Health 2003; 3(3): 3.

27.

Mahfouz

Alsaleem

, et al. Obesity among medical students at King Khalid University. Medicina (Kaunas) 2024; 60(3): 347.

28.

Syed

Meraya

, et al. Dietary behaviours associated with overweight and obesity among Saudi university students. PLoS One 2020; 15(9): e0238458.

29.

Mehmood

Al-Swailmi

Al-Enazi

, et al. Prevalence of obesity and comorbidities among medical students. Pak J Med Sci 2016; 32(6): 1528–1532.

30.

Szemik

Zieleń-Zynek

Szklarek

, et al. Determinants of overweight and obesity in medical students: a two-year observation. Front Nutr 2024; 11: 1437292.

31.

Borel

Coumes

Reche

, et al. Cardiometabolic risk markers in women with severe obesity. PLoS One 2018; 13(11): e0206617.

32.

Lee

Sui

Church

, et al. Cardiorespiratory fitness, body fatness and cardiovascular risk. J Am Coll Cardiol 2012; 59(7): 665–672.

33.

Cameron

Magliano

Shaw

, et al. Hip circumference and mortality risk. Int J Epidemiol 2012; 41(2): 484–494.

34.

Bergier

Niźnikowska

, et al. Physical activity and nutrition-related behaviours in European students. Ann Agric Environ Med 2018; 25(1): 176–181.

35.

Bednarek

Pomykała

Bigosińska

, et al. Physical activity among Polish and Turkish university students. Cent Eur J Sport Sci Med 2016; 16(5): 13–22.

36.

Osipov

Potop

Nagovitsyn

, et al. Physical activity and fitness among Russian university students. Phys Educ Stud 2020; 24(1): 40–46.

37.

Verheggen

Maessen

Green

, et al. Effects of exercise versus hypocaloric diet on visceral adipose tissue. Obes Rev 2016; 17(8): 664–690.

38.

Leman

Claramita

Rahayu

GR.

Defining a healthy role-model in medical schools. J Multidiscip Healthc 2020; 13: 1325–1335.

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