Abstract

This study examines the impact of obesity on the current health and academic performance of college students, with potential long-term implications for their overall well-being. Using survey data from 300 students at a university in the Arab Gulf of Oman, the study finds that over 27% of students are classified as overweight or obese. The analysis reveals a significant negative relationship between obesity and academic performance, with obese students showing a 6.6% decrease in academic grades compared to their peers of healthy weight. The findings suggest that the likelihood of earning lower academic grades is 2.54 times higher among obese students than those with normal weight. Additionally, the study indicates that obese students face an 8.5% higher burden of obesity-related health issues and are 5.77 times more likely to develop such conditions compared to normal-weight students. These results highlight that obesity affects both academic achievement and health, with potential long-term consequences for students鈥� well-being. To address these issues, educational institutions and communities should prioritize promoting healthy lifestyles, including proper nutrition and weight management support.

Introduction

The growing rate of obesity among children, adolescents, and early adulthood has significant health and economic consequences. Gaining excess weight or being overweight during childhood and adolescence increases the risk of developing chronic health conditions at an earlier age, including psychiatric, psychological, and psychosocial disorders, early-onset type 2 diabetes, and obesity-related comorbidities [1,2,3,4,5,6]. Overweight children, for instance, are 50% more likely to develop obesity later in life, particularly by the age of 35 or older [7]. Moreover, the growing obesity rates represent a substantial economic threat, with rising prevalence, incidence, and the broader financial impact on national economies [8].

Over 2.1 billion people around the world are currently classified as overweight or obese, a condition that contributes to 4.7 million premature deaths annually [9,10,11,12]. During 1990 and 2017, the number of deaths attributed to obesity doubled, rising from 1.2 million in 1990 to 2.4 million in 2017 [13]. The global prevalence of obesity among children, adolescents, and young adults has increased fourfold since 1975. Further, Zhong et al. (2024) observed that the prevalence rate of obesity increased 1.5-fold during 2012 to 2023 compared to 2000 to 2011 [14, 15]. Obesity during early life鈥攚hether in childhood, adolescence, or early adulthood鈥攃an have severe and long-term health consequences throughout life [16]. Early-age obesity is particularly concerning because it is closely linked to obesity in adulthood and an increased risk of obesity-related comorbidities. It is also difficult to lose weight gained during childhood, making early obesity a significant public health issue [14, 16,17,18,19]. The recent COVID-19 pandemic further underscored the risks of obesity, with studies showing that obesity and its associated comorbidities were strongly linked to higher mortality rates from the virus [20,21,22].

On the other hand, children who are not obese are less likely to develop obesity later in life [8]. Further, studies show that healthy children are 13% more likely to perform better academically than their overweight peers, suggesting a negative impact of obesity on educational achievement [14, 23,24,25,26]. Numerous studies conducted in the United States have also found that obesity is associated with higher rates of absenteeism among school children aged 6 to 11 [27] and adolescents aged 12 to 17 [27,28,29,30], which in turn contributes to lower academic performance [31, 32]. These academic setbacks can have long-term consequences on a child's future economic well-being.

In contrast, several studies have suggested that there is no strong link between obesity and academic performance. However, many of these studies fail to account for other important factors, such as socioeconomic and demographic characteristics. For instance, a study by Carey et al. (2015) in the United States found that while obesity may initially appear to affect academic performance, the relationship disappeared once other confounding variables were controlled for [28]. Similarly, a study in Spain showed that the relationship between obesity and test scores in children aged 9 to 11 vanished after adjusting for confounders [33]. Another study found a negative association between obesity and academic performance among schoolchildren aged 14鈥�15, but this was attenuated once factors like parents' education and occupation were considered [30]. A recent systematic review on obesity and academic achievement in the tertiary sector concluded that university students are less affected by socioeconomic factors than school-age students when it comes to academic performance [34].

In recent year, Arab Gulf region has seen a significant rise in obesity rates, with countries such as Kuwait, Bahrain, Saudi Arabia, and the United Arab Emirates ranking among the top ten countries worldwide for obesity prevalence [35]. In Oman, 66% of the adult population is either overweight or obese [36], and data from the NLiS Country Profile-Oman indicates that 32.5% of schoolchildren and adolescents aged 5鈥�19听years are overweight or obese [14]. A recent study by Al Yazeedi (2020) revealed that from 2012 to 2018, the prevalence of overweight and obesity among schoolchildren increased significantly: from 3.5% to 4.2% in children aged 6鈥�7听years; from 12.8% to 15% in children aged 12鈥�13听years; and from 12.5% to 16.7% in children aged 15鈥�16听years [37]. This early-life obesity will likely persist into adulthood, influencing long-term health and academic outcomes.

Several factors contribute to the rising rates of obesity, including global environmental changes, the adoption of unhealthy lifestyles, poor dietary habits, and a lack of physical activity. The growing obesity epidemic places an additional burden on national healthcare systems. Beyond the direct healthcare costs, obesity also leads to significant productivity losses, including school and college dropout rates, absenteeism, presenteeism, lower academic performance, and long-term disability. These consequences highlight the need for policymakers to understand the full scope of the economic burden of obesity鈥攂oth direct and indirect鈥攐n healthcare systems and national economies. To inform policy decisions, it is essential to quantify the impact of obesity and its associated consequences. This study aims to estimate the effect of overweight and obesity using a modeling framework that will be valuable for policymakers and healthcare regulators in Oman. By estimating the effect of obesity among college students, this research will help prioritize healthcare policies, allocate resources effectively, and encourage evidence-based actions to address obesity at a national level. Specifically, the study seeks to assess how overweight and obesity affect academic performance among college students in Oman.

Materials and methods

Survey design

The study estimated the prevalence of obesity, overweight, and underweight based on Body Mass Index (BMI), calculated from data collected through a primary survey. The survey covered 300 students randomly selected from four colleges at the University of Nizwa, Oman: the College of Economics, Management and Information Systems (CEMIS), the College of Arts and Science (CAS), the College of Health Sciences (CHS), and the College of Engineering (CE). Data collection was carried out using a structured questionnaire specifically designed for this study. Prior to the main survey, a pilot survey was conducted to evaluate the questionnaire's consistency, validity, and reliability. A small group of students participated in the pilot survey, and the collected data were analyzed using STATA software. To assess the questionnaire's reliability and validity, Cronbach鈥檚 alpha statistical test was applied (Table听1). The questionnaire included questions regarding students' socioeconomic and demographic characteristics, such as family background, parents' education, income level, and the location of their household (rural or urban).

Table听1 Descriptive statistics of the variables

The survey also collected detailed information about each student's height, weight, Cumulative Grade Point Average (CGPA), number of credit hours completed, health status including any diseases or health problems related to obesity, and any treatments they were receiving. Additionally, the survey inquired about productivity losses due to obesity, such as absenteeism, presenteeism, and the number of days students were absent from university or study due to obesity or related comorbidities. The final version of the questionnaire was digitized using Google Forms, and a link to the survey was sent randomly to over 500 students via email or WhatsApp. The sample size was determined using a sample size calculation formula, based on the prevalence of obesity among college students in Oman as estimated in a previous study [38]. We received 300 completed responses. However, 18 of these responses were incomplete and were excluded from the analysis.

Analytical methods

We estimate obesity, overweight, and underweight based on students' Body Mass Index (BMI). BMI is calculated by dividing a person鈥檚 weight in kilograms by the square of their height in meters. The BMI categories are as follows: a healthy or normal BMI is between 18.5 and 24.9, underweight is less than 18.5, overweight is between 25 and 29.9, and obesity is defined as a BMI of 30 or higher [39, 40].

To examine the relationship between BMI and academic performance, we use logistic regression techniques, with Cumulative Grade Point Average (CGPA) treated as a categorical dependent variable. The logistic regression model evaluates how overweight and obesity influence academic performance. CGPA was categorized into three groups: Low-CGPA (0鈥�2.45, indicating lower academic performance), Moderate-CGPA (2.46鈥�3.0, representing moderate performance), and High-CGPA (3.1鈥�4.0, reflecting high academic performance). Similarly, BMI was divided into four categories: Underweight, Normal weight, Overweight, and Obesity. For analysis, binary variables were created for each category. For instance, the binary variable for obesity is coded as 1 if the student is obese and 0 otherwise, while the binary variable for Low-CGPA is coded as 1 if the student falls in the low-CGPA range and 0 otherwise.

The logistic regression model developed in this study uses Low-CGPA as the dependent variable, with obesity and overweight as independent variables (with normal weight as the reference category). Control variables include gender, age, household size, parental income, and the student's place of residence. Formally, let Lg denote the binary outcome variable for Low-CGPA, where Lg鈥�=鈥�1 indicates a low CGPA and Lg鈥�=鈥�0 indicates high or moderate CGPA. The probability of Lg鈥�=鈥�1 is denoted as p, i.e., $p=P\left(Lg=1\right)$. The logistic regression equation for Lg can then be expressed as:

$$logit\left(Lg\right)=\text{log}\left(\frac{p}{1-p}\right)={\beta }_{0}+{\beta }_{1}{x}_{1}+ {\beta }_{2}{x}_{2}+..\dots + {\beta }_{k}{x}_{k}$$

(1)

where, ${\beta }_{0} ,{\beta }_{1}\dots \dots .,{\beta }_{k}$ are the coefficient and ${x}_{1}, {x}_{2},\dots \dots .,{x}_{k}$ are the explanatory variables such as obesity and overweight, underweight (keeping normal weight as reference variable) and control variables are gender, age, household size, parents income, and location or the place of resident.

Further, we examine the effect of overweight and obesity on current health status among the college going student where the dependent variable is current health status whether the student facing any obesity related health issues or related comorbidities. This is a binary dependent variable [0, 1]鈥攙alues 1 if currently facing any health issues, otherwise 0. The logistic regression equation for estimating the impact of obesity or overweight on current health status can be written as:

$$logit\left(Oc\right)=\text{log}\left(\frac{p}{1-p}\right)={\alpha }_{0}+{\alpha }_{1}{y}_{1}+ {\alpha }_{2}{y}_{2}+..\dots + {\alpha }_{k}{y}_{k}$$

(2)

where, O_C鈥�=鈥塷besity related comorbidities, ${\alpha }_{0} ,{\alpha }_{1}\dots \dots .,{\alpha }_{k}$ are the coefficient and ${y}_{1}, {y}_{2},\dots \dots .,{y}_{k}$ are the explanatory variables鈥攐besity[0,1], overweight[0,1], underweight[0,1] (keeping normal weight as reference variable) and control variables are gender, age, household size, parents鈥� income, and location or the place of resident (rural or urban).

Results

The study found that the average Cumulative Grade Point Average (CGPA) of students is 2.49, with a range from a minimum of 0 to a maximum of 4, and the highest CGPA recorded is 3.94. The average weight of students is 61听kg, with the heaviest student weighing 141听kg. The mean BMI is 23.04, with a minimum of 11.25 and a maximum of 57.20. In terms of location, 55% of students reside in urban areas, while 44% live in rural areas. The majority of respondents are female, which aligns with the university's overall student population, where 90% are female. Regarding BMI categories, 56.58% of students have a normal BMI, while 27% are either overweight or obese. Additionally, 16% of students are classified as underweight. More than 38% of students have a lower CGPA, and 8.5% of students report living with at least one obesity-related comorbidities.

Overweight and obesity are more prevalent in urban areas than rural counterpart. In urban areas, over 10% of students are classified as obese, compared to 8.6% in rural areas. This suggests that obesity is more common in urban areas. Additionally, overweight and obesity rates are clearly higher among male students compared to female students. The data also reveals that obesity is disproportionately more prevalent among students from low-income families. Over 13% of students living with obesity belong to the lowest income category, while obesity rates in the highest income categories range from 0 to 10%. Furthermore, the study shows a clear association between age and overweight status, with older students tending to have higher BMI values or are more likely to be overweight. However, there is no consistent pattern between obesity and age. The obesity rate is relatively lower among students in the youngest age group (17鈥�20听years), at 12.82%, while 20% of students in the oldest age group (31听years and above) are obese (Table听2).

Table听2 Percentage of students living with Overweight and Obesity across the socioeconomic groups

Table 3 presents the academic performance of students across the four BMI categories鈥攗nderweight, normal weight, overweight, and obesity. Academic performance is measured by the average Cumulative Grade Point Average (CGPA) for each category, with CGPA values ranging from 0 to 4. The results show that students in the normal weight and overweight categories have substantially higher average CGPAs, while the average CGPA for students in the underweight (2.69) and obesity (2.68) categories is notably lower than that of students in the normal or healthy weight categories. Additionally, the data indicates that male students have slightly higher average CGPAs than female students, though the difference is not significant. Furthermore, students from higher-income families tend to earn higher CGPAs compared to those from lower-income families.

Table听3 Average CGPA of the student based on their BMI categories

We measure how academic grades change in relation to being overweight and obese among students by comparing the average CGPA of overweight, obese, and underweight students compared to normal-weight students. Table 4 shows the deviation in CGPA due to overweight, obese, and underweight relative to normal-weight students, with normal weight as the baseline (100%). The results indicate that underweight and obese students earn more than 6.5% lower academic grades compared to normal-weight students. Obese students living in rural areas, for example, earned 9% lesser CGPA (5% lesser CGPA in urban) than their normal weight counterparts. Similarly, students in the 17鈥�20 age group who are obese had a 15.6% lower CGPA compared to normal weight students.

Table听4 Percentage changes of CGPA for underweight, overweight and obesity categories (CGPA for normal weight鈥�=鈥�100)

Further, we analyzed the relationship between academic performance and BMI categories graphically. Based on CGPA, students were classified into three categories: Low-CGPA, Moderate-CGPA, and High-CGPA. The graph (Fig.听1) reveals that most students with obesity fall into the Low-CGPA category, while students with normal or healthy weight tend to earn higher or moderate grades. Similarly, underweight students generally do not achieve high or moderate CGPAs, with most of their grades falling into the Low-CGPA category. However, overweight students tend to earn higher grades compared to other categories, with very few falling into the Low-CGPA category. This suggests that the majority of overweight students secure either High or Moderate CGPAs.

Fig.听1

Percentage distribution of students based on CGPA and BMI Categories

There are significant differences in obesity and academic performance between rural and urban areas. In rural areas, 75% of obese students fall into the low academic grade category, compared to 46% of obese students in urban areas. Similarly, overweight and obese male students in urban areas tend to earn considerably higher grades than their rural counterparts. Additionally, the study reveals that the majority of obese students (64.3%) from low-income families fall into the low academic grade category, compared to those from high-income families (Table听5). The analysis also shows that age has a significant impact on both obesity and academic performance. Obese students in the 17鈥�20 age group tend to have much lower academic performance compared to those in the 21鈥�24 age group. Specifically, 75% of obese students in the 17鈥�20 age group fall into the low CGPA category, while only 45% of obese students in the 21鈥�24 age group fall into this category.

Table听5 Percentage distribution of students under BMI and CGPA categories

The study found a statistically significant negative correlation between CGPA and BMI (Table听6), meaning that students with higher BMI tend to earn lower CGPAs. In contrast, age has a positive correlation with CGPA, suggesting that older students are more likely to earn higher academic grades. Similarly, parent income is negatively associated with lower academic grade鈥攕tudents from higher-income families may tend to secure higher CGPAs. Furthermore, parental income is negatively correlated with BMI, meaning that students from wealthier families generally maintain a lower BMI. Additionally, other variables such as BMI, household size, location, and gender are negatively correlated with CGPA. This suggests that students with higher BMI are more likely to earn lower CGPAs, indicating that obese students may perform worse academically than their normal-weight peers.

Table听6 Logistic regression results鈥攈ow obesity affects student鈥檚 academic performances (low academic performances) and categories of BMI

The logistic regression results show that the odds ratio for the dependent variable low-CGPA and the independent variable obesity (with non-obese as the reference category) is 2.28 (Model 1). This means that the probability of earning a low CGPA is 2.28 times higher for obese students compared to non-obese students. Conversely, the odds ratio for overweight (with non-overweight as the reference category) is 0.36, which is statistically significant at the 10% level. This indicates that the probability of earning a low CGPA is 0.36 times lower for overweight students compared to non-overweight students, suggesting that overweight students tend to secure higher academic grades than non-overweight students.

The odds ratio for the control variable age is 0.79, which is statistically significant. This suggests that the likelihood of earning a low CGPA is 0.79 times lower for students in the higher age group (21鈥�24听years) compared to those in the younger age group (17鈥�20听years), implying that older students tend to perform better academically.

Similarly, the odds ratio for parental income is 0.99, which is also statistically significant. This indicates that students from higher-income families are 0.99 times less likely to earn a low CGPA compared to students from lower-income families, suggesting that parental income has a minimal or negligible effect on academic performance.

In further analysis, we classified parental income into three categories: low-income, middle-income, and high-income groups, and included these as predictor variables in model-2. The results from this model confirm that obesity is significantly associated with a higher likelihood of earning a low CGPA. However, it also reveals that students from low-income families are more likely to have lower academic performance compared to those from high-income families. The odds ratio for the low-income group is 3.32, meaning that students from low-income families are 3.32 times more likely to earn a low CGPA compared to students from high-income families.

To examine the independent effect of obesity, we added an interaction term between parental income and obesity as a moderator in model-3. The results showed that obesity is significantly associated with poorer academic performance (odds ratio: 4.83, significant at the 5% level), while the interaction between obesity and parental income had no significant impact on academic performance. This suggests that obesity directly affects students' academic performance, even after controlling for parent income. Other control variables, such as student residence, showed no significant impact on academic performance. While the odds ratio for students living in rural areas is 1.12, indicating a higher likelihood of achieving lower academic grades compared to those living in urban areas, these results were statistically insignificant across all three models.

The study also examined the impact of obesity on current health status. We collected data on whether students were currently suffering from any obesity-related health conditions. A list of 19 obesity-related diseases was provided, including hypertension, hypercholesterolemia, type-2 diabetes, stroke, coronary heart disease (CHD), cancers, osteoarthritis, sleep apnea, depression, anxiety, asthma, and others [41,42,43,44]. The results show that 17.78% of overweight students and 16.67% of obese students are currently suffering from at least one obesity-related comorbidity.

We used logistic regression to analyze how overweight and obesity affect the likelihood of suffering from obesity-related diseases. The dependent variable was the presence of obesity-related comorbidities (coded as 1 if the student is suffering from any obesity-related condition, and 0 if not). The independent variables included obesity, overweight, and underweight, with normal weight as the reference category. The results show that the estimated odds ratio for obesity is 5.34 (Table听7), meaning that the probability of acquiring obesity-related diseases is 5.34 times higher for obese students compared to non-obese students. In other words, obese students are at a much higher risk of developing obesity-related comorbidities.

Table听7 Logistic regression results鈥攈ow overweight and obesity increases the risk of obesity related co-morbidities

Similarly, overweight students are also at a significantly higher risk of obesity-related comorbidities, with an odds ratio of 5.77, indicating that they are 5.77 times more likely to acquire these diseases than normal-weight students (Table听7). However, no significant differences were found in the likelihood of acquiring obesity-related diseases based on gender, or the student's location (rural vs. urban).

Discussion

The study revealed that over a quarter of college students are either overweight (16.37%) or obese (10.68%). Additionally, the prevalence of overweight and obesity is notably higher among students living in urban areas. This increased burden of obesity in urban settings is largely attributed to a sedentary lifestyle鈥攃haracterized by limited physical activity, extended periods of sitting at home, and a diet high in fast food, salty snacks, and sugary products [45,46,47,48]. In contrast, rural areas tend to have less access to obesity-promoting foods and facilities. Furthermore, many rural residents adhere to traditional lifestyles that contribute to better overall health and BMI management.

The study also highlighted that overweight and obese students are disproportionately from low-income families. The primary factors contributing to this trend are economic and social determinants of health. Low-income families typically have less access to resources, quality food, food security, and adequate living conditions [49, 50]. Additionally, limited awareness of health and dietary behaviors is a significant issue within these families [51, 52]. Previous research has shown that low-income individuals are more likely to experience higher levels of psychosocial stress, including reduced control over their lives, insecurity, social isolation, stress, and mental health disorders [51, 53].

It is widely recognized that the main factor driving the rise in overweight and obesity among college students is the sudden shift in their lifestyle, including changes in diet, eating habits, and physical activity levels [54, 55]. Many college students transition from adolescence to early adulthood, often accompanied by changes in their dietary behavior, such as frequent consumption of sugary snacks and beverages. These age-related changes, combined with lifestyle shifts, significantly influence current and future behaviors [56,57,58,59,60]. Such behavioral changes not only affect students' health but also have long-term economic consequences, including potential negative impacts on academic performance, work productivity, and an increased risk of developing non-communicable diseases (NCDs) later in life. Overweight during early adulthood may intensify the risk of obesity in the future, further contributing to reduced productivity and overall well-being.

High BMI significantly impacts academic performance, with overweight students generally earning higher academic grades compared to those who are obese or underweight. While being overweight appears to have a positive effect on academic performance, obesity is linked to a significant decline in grades, with many obese students falling into the low-CGPA category. However, this finding contrasts with other studies suggesting that overweight students also experience negative academic effects [32, 61, 62]. Further, some research has found a weak association between higher weight and lower educational attainment among children and young people [25, 63,64,65]. The difference in academic performance between overweight and normal-weight students is minimal, which could imply that the real-world effects on academic test scores are not substantial.

There is substantial evidence linking childhood obesity to lower levels of physical activity, reduced social interaction, and impaired cognitive functioning, all of which can negatively affect academic performance [32, 66,67,68]. However, the impact of obesity on academic performance remains a debatable topic. A few studies support the view that obesity negatively affects students' academic achievements [32, 69,70,71]. On the other hand, some research shows that obesity is significantly associated with academic performance, but this relationship disappeared when it was controlled with other confounding variables such as parents' income or residence (rural or urban) of the student [28, 30, 33]. The present study, as discussed in model-3, confirmed the negative association between obesity and academic performance even after controlling the students' background characteristics.

Evidence suggests that obesity may contribute to poor academic results, potentially due to factors like higher rates of absenteeism, lower self-esteem, and social stigma [72,73,74,75]. Several studies indicate that children with higher BMI often struggle with concentration, energy, and classroom engagement [67, 76]. Additionally, research shows that obese students are more likely to have lower academic scores, possibly as a result of bullying, depression, and other emotional or psychological difficulties associated with obesity [77]. Moreover, the study identified significant differences in obesity-related academic performance between rural and urban students. A higher proportion of rural obese students fell into the low-CGPA category compared to their urban counterparts [78,79,80]. Although the prevalence of obesity is lower in rural areas than in urban areas, the academic performance of rural obese students remains considerably lower. This disparity is largely attributed to differences in socioeconomic backgrounds, as rural parents typically have lower average incomes than those in urban areas, which significantly affects their children's academic outcomes.

These findings suggest that obesity among college students has serious implications, not only for their current academic performance but also for their long-term health, economic and well-being outcomes. Obese students may struggle with lower grades, which could negatively impact their future earnings once they enter the workforce. Furthermore, obesity increases the risk of related comorbidities, and this study found that more than 16% of students suffer from at least one obesity-related health issue. The likelihood of an obese student having at least one comorbidity is five times higher than that of a non-obese student. The additional burden of obesity-related comorbidities contributes to increased healthcare costs and reduced labor productivity, ultimately impacting the national economy.

Finally, the study acknowledges some limitations. Due to the unavailability of longitudinal data, a cross-sectional design was employed, which may limit the ability to draw causal conclusions between obesity and academic performance. Longitudinal studies would be more suitable for establishing causal relationships over time. Additionally, the student population at the University of Nizwa is highly skewed, with ninety percent of students being female, which limits the generalizability of the findings. Further, the limitation of the data is that students' height, weight, and parental income were self-reported, which may introduce bias or inaccuracies. Respondents may underreport or overreport their height, weight, or income, leading to potential measurement errors that could affect the reliability and validity of the findings. Lastly, the use of online surveys introduces the potential for selection bias, and the health outcome analysis is limited, focusing only on a narrow range of obesity-related comorbidities.

Conclusion

The study concludes that one quarter of the college going students aged 18 to 24听years are over-weight or obese, which may significantly affect their current health status and academic performance. Obese students are more likely to achieve lower academic grades compared to their non-obese peers. Additionally, more than eight percent of students with overweight or obesity are experiencing multiple obesity-related comorbidities and face a 5.7 times higher risk of developing obesity-related diseases compared to their non-obese peers. These findings highlight the urgent need for policy interventions. Obesity among college students not only affects their immediate health and academic outcomes but it may also lead to long-term consequences on their overall health and economic well-being throughout their life course.

These findings underscore the urgent need for immediate policy interventions. Universities and policymakers can help mitigate the negative effects of obesity on students' academic performance and health, leading to improved long-term well-being by adopting the following proactive measures: (1) Educational institutions, including schools, colleges, and universities, should implement programs to raise awareness about the health risks of obesity and its impact on academic performance and overall well-being; (2) Universities should offer wellness programs that promote healthy lifestyle choices. This could include providing nutritious meal options, offering fitness facilities, and organizing physical activity sessions; (3) Colleges should implement early intervention strategies for students showing signs of unhealthy weight gain. Counseling services should be made available to address emotional and psychological issues related to body image and self-esteem, helping to reduce the social stigma and mental health challenges faced by overweight and obese students; and (4) Finally policymakers should consider developing and enforcing national or regional policies to address the increasing prevalence of obesity among college students. These policies could focus on improving access to healthier food options, physical activity opportunities, and health education at the university level.