Impact of Social Media Engagement and Food Marketing Exposure on Cardiovascular Risk Factors in Jordanian Adults: A Cross-Sectional Study

Impact of Social Media Engagement and Food Marketing Exposure on Cardiovascular Risk Factors in Jordanian Adults: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Impact of Social Media Engagement and Food Marketing Exposure on Cardiovascular Risk Factors in Jordanian Adults: A Cross-Sectional Study Eman Alhasan, Maysoun Qutob, Shatha Hammad This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7724259/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cardiovascular diseases (CVDs) are a leading cause of mortality globally and in Jordan, with lifestyle factors such as physical inactivity, unhealthy diet, obesity, and smoking contributing substantially. Social media use has increased among young adults, raising concerns about its influence on lifestyle and exposure to food marketing. Methods : A cross-sectional study was conducted among 222 participants (aged 18–45 years) at the Applied Science Private University in Jordan. Data were collected via a validated online questionnaire on sociodemographic characteristics, lifestyle behaviors, dietary habits, and social media use. Anthropometric measures were obtained at the university clinic. Associations between social media use and outcomes were analyzed using chi-square tests and ANCOVA. Results : Most participants were female (75.2%) with a mean age of 21.4 ± 4.9 years. Two-thirds spent 3–6 hours daily on social media. Longer social media use was significantly associated with physical inactivity (p = 0.027), interrupted sleep (p = 0.036), and increased appetite and food cravings (p = 0.021). Exposure to food advertisements was linked to more frequent dining out (p < 0.001) and ordering ready-to-eat foods (p = 0.045). No significant association was found with BMI or body composition. Conclusions : Intensive social media use among young adults is associated with adverse effects on certain lifestyle behaviors and unhealthy eating patterns, which may increase cardiovascular risk. These findings underscore the necessity of incorporating social media exposure into public health interventions and dietary counseling efforts. Health sciences/Risk factors Scientific community and society/Scientific community Biological sciences/Computational biology and bioinformatics Social media Cardiovascular Diseases Risk Factors Eating Habits Food Marketing Figures Figure 1 Key Messages What is already known on this topic Social media use is highly prevalent among young adults and has been linked globally to physical inactivity, disrupted sleep, and unhealthy eating behaviors. However, little is known about these associations in Jordanian adults, particularly with regard to exposure to food marketing. What this study adds This study demonstrates that greater time spent on social media is significantly associated with physical inactivity, poor sleep, increased appetite, and unhealthy food choices. Exposure to food advertisements further influenced cravings, dining out, and ordering ready-to-eat foods. How this study might affect research, practice or policy The findings highlight the need for clinicians, dietitians, and policymakers to consider the influence of social media when addressing cardiovascular risk factors. They also suggest that stricter regulations of food marketing on social media and targeted health promotion campaigns are warranted. Introduction Social media has become an integral component of daily life, significantly impacting individuals’ lives [ 1 ]. Platforms such as WhatsApp, Instagram, Facebook, Snapchat, and Twitter serve as essential communication tools worldwide [ 2 ]. According to the latest data from the April Global Overview, the time spent on social media has increased over the years; over half of the global population (62.6%) engages with social media, totaling 5.07 billion users who spend an average of 2 hours and 20 minutes daily on these platforms [ 3 ]. In Jordan, there were 10.33 million internet users at the beginning of 2024, reflecting an internet penetration rate of 91.0%, with 56.2% of the population (6.38 million) utilizing social media [ 4 ]. Cardiovascular diseases (CVDs), which encompass a range of disorders affecting the heart and blood vessels, are among the leading causes of death globally [ 5 ][ 6 ]. A global estimate by the World Health Organization (WHO) in 2017 indicated that 17.5 million individuals succumb to CVDs each year [ 7 ], representing approximately one-third of all global fatalities [ 8 ], More than 75% of these deaths occur in low- and middle-income countries [ 7 ]. CVDs also rank as a primary cause of mortality in Jordan, with a cause-specific mortality rate of 18.6% reported by WHO in 2020 [ 9 ]. Furthermore, Jordan has witnessed a significant increase in the prevalence of cardiovascular diseases, rising from 38% in 2009 to 48.2% in 2020. However, there remains a notable gap in the availability of the epidemiological profile for Arab countries, including Jordan [ 10 ]. There is an increasing demand for a comprehensive understanding of the demographic profile of cardiovascular diseases (CVDs) and their associated risk factors within populations. This understanding can guide the development of strategies and policies that effectively address the unique public health needs of these communities through public health systems. Numerous factors—such as genetic, demographic, and environmental influences—are recognized as significant contributors to CVDs [ 11 ]. Notably, approximately 50% of CVD risk is linked to modifiable factors, including sedentary behavior, unhealthy dietary patterns characterized by excessive caloric intake, overweight or obesity, and smoking [ 12 ]. In response, there is a growing emphasis on the concept of “Healthy Living Medicine” (HLM), which highlights the critical role of lifestyle and modifiable factors in both the prevention and treatment of CVDs. Despite widespread awareness and educational initiatives, many individuals still struggle to modify these risk factors, even after the onset of chronic diseases that increase their susceptibility to cardiovascular complications [ 13 ]. Body mass index (BMI) is not a perfect measure, as it cannot differentiate between fat and muscle mass [ 14 ]. Therefore, it's crucial to highlight the importance of recognizing abdominal obesity through waist circumference (WC) and waist-to-hip ratio (WHR), which are associated with the development of cardiovascular disease in individuals with "normal-weight obesity"—those with excess fat who do not meet the obesity criteria based on BMI [ 15 , 16 ]. Additionally, there is a biological connection between fat distribution and cardiovascular diseases (CVDs) [ 17 ]; A higher volume of visceral adipose tissue (VAT) is linked to increased cardiovascular risk factors over time, including insulin resistance, which BMI does not fully account for [ 18 – 20 ]. Social media provides new avenues for social connection and data exchange; however, it can also adversely affect physical and mental health. It serves as a marketing platform for numerous food and beverage companies that engage in influencer advertising [ 21 ] [ 22 ], which creates a complex relationship between authentic social media content and marketing, especially when disseminated by influencers [ 23 ]. As a result, the influence of social media on eating behavior is deteriorating, given that the most widely used platforms often lack stringent regulations regarding the advertising of unhealthy foods, such as ultra-processed items and tobacco [ 24 – 28 ], which are increasingly promoted through home delivery services [ 29 , 30 ]. Moreover, exposure to mobile screens at night while browsing social media can lead to diminished sleep quality and various sleep-related issues [ 31 ]. The blue light emitted from screens may disrupt glucose metabolism, particularly in women, potentially contributing to obesity [ 32 ]. This condition has direct negative implications for cardiac structure and function and elevates the risk of developing cardiovascular diseases [ 33 ]. This study aims to examine the impact of social media platform usage on risk factors associated with cardiovascular diseases, such as sedentary lifestyle and eating behaviors, including the influence of exposure to food/ drink marketing on social media on appetite and food cravings among a group of Jordanian adults. Materials and Methods 2.1. Study Design and Study Population A cross-sectional study utilizing an online survey was conducted with 222 participants aged 18 to 45 years residing in Jordan. After excluding 161 participants for various reasons—withdrawal of consent (n = 10), incomplete questionnaires (n = 15), and ineligibility due to age (n = 7), as detailed in the supplementary figure.1 —The final sample consisted of individuals who were students and employees at the Applied Science Private University in Amman, Jordan. Recruitment occurred between December 24, 2023, and April 25, 2024, during which participants completed the online survey along with other study requirements. 2.2. Sampling Strategy A convenience sample of eligible participants was recruited through a weekly post shared over a two-month period, utilizing a survey link distributed across major social media platforms (Facebook, Instagram, WhatsApp, and Teams), in collaboration with university groups and community pages. To enhance outreach, reminders were posted eight times, and messages were resent to active groups. No monetary incentives were provided; thus, all participants voluntarily consented to participate in the study by indicating their agreement in the online questionnaire through the selection of the "yes, I agree, and hereby give my informed consent" option. The inclusion criteria specified that participants must be aged between 18 and 45 years, possess no cognitive disabilities, and for women, must not be pregnant or lactating. Additionally, participants should not have been diagnosed with cardiovascular diseases (CVDs) such as myocardial infarction, stroke, or coronary heart disease, nor should they have eating disorders or any conditions that affect appetite. Furthermore, individuals who had taken corticosteroids within the past month were also included in the study. Conversely, anyone who did not meet the inclusion criteria or failed to complete the questionnaire was excluded from the study. 2.3. Sample Size The target sample size was calculated using the Cochrane formula: n = (Z² * P * (1-P)) / d², where Z represents the confidence level (95%, z = 1.96), P is estimated from previous studies (0.56 or 56%, based on national statistics), and d is the margin of error (0.05 or 5%) [ 34 ]. Consequently, the required sample size was determined to be 378 participants. 2.4. Questionnaire Tool This study developed and adapted a self-administered, validated questionnaire to meet its objectives. The questionnaire comprised 56 items organized into six sections. The first section (11 items) inquired about the participants' personal and sociodemographic characteristics. The second section (4 items) collected anthropometric information, including current weight and height, and whether participants had experienced any changes in their body weight over the past month. The third section examined lifestyle factors, including physical activity, sleep patterns, and smoking habits. The following section (11 items) focused on participants' medical history and health status. The next section (9 items) addressed eating habits over the previous month. The final section (10 items) investigated the impact of social media usage. 2.5. Assessment of Physical Activity Physical activity was assessed using the validated Seven-Day Physical Activity Recall questionnaire, measured in Metabolic Equivalent of Task (METs) [ 36 ]. Data on the number of hours spent at various activity levels were collected through this questionnaire, developed by Sallis et al. (1985) [ 37 ], and subsequently converted into MET values. The average MET values were designated as follows: moderate activity = 3.3 METs, vigorous activity = 8 METs, and extreme activity = 10 METs. The MET-minutes per week score was calculated using the equation: (MET level × minutes of activity per day × days per week). The total physical activity (MET-minutes/week) was then aggregated to facilitate categorical analysis: inactive, minimally active, and health-enhancing physical activity (HEPA). Categorization was conducted according to the standard scoring protocol of the International Physical Activity Questionnaire (version 2, 2004) [ 38 ]. 2.6. Body Composition Measurements Participants who completed the online questionnaire were invited to the Nutrition Clinic at the Applied Science Private University to fulfill the requirements of their involvement in the study. Prior to their appointment, participants received recommended instructions, which included fasting for a minimum of three hours, wearing lightweight clothing, avoiding exercise before measurements, and, for female participants, not being in their menstrual cycle. Trained examiners measured participants’ height and body composition using standardized techniques. Height was measured with a BSM 170 device to the nearest 0.1 cm, with two measurements taken to calculate an average. Body weight (kg), body composition metrics including fat mass (kg) and skeletal muscle mass (kg), visceral fat levels, and abdominal obesity parameters—waist circumference (cm) and waist-to-hip ratio (cm)—were assessed using the InBody 770 device. 2.7. Social Media Use The assessment of social media encompassed multiple dimensions, including average daily time spent on various platforms, type of engagement (active versus passive), time of day most frequently used, primary platforms accessed, main purposes of use, types of content deemed most influential, and the perceived impact of social media on concentration and appetite, particularly concerning food recipes and restaurant advertisements. These variables were treated as distinct exposures to facilitate a more precise examination of their differential associations with dietary behaviors, lifestyle patterns, and cardiovascular risk factors. The social media questions addressed the time spent on these platforms over the past month. 3. Statistical Analysis The associations between the time spent on social media and body composition and dietary and lifestyle habits were performed using the SPSS statistical package version 26. Descriptive statistics were performed for all of the variables and presented as mean and standard deviation for continuous variables and as n (%) for categorical variables. The normality of the distribution was assessed using histogram plots. Analysis of Covariance (ANCOVA) was used to assess the effects of the time spent on social media on body composition. Pre-specified covariates, including age, sex, and educational levels, were incorporated into statistical models. Chi-square was used to evaluate the association between the time spent on social media and categorical variables. Statistical significance was set at P < 0.05 for all analyses. Results 4.1. Study Participants’ Characteristics A total of 222 participants were involved in this study. Their demographic and anthropometric characteristics are detailed in the Supplementary Table 1, along with the sociodemographic characteristics and lifestyle habits presented in Table 1. These tables collectively summarize the participants' anthropometric, sociodemographic, and lifestyle attributes, including dietary and physical habits. The majority of participants were young, healthy adults with a mean age of 21.39 ± 4.93 years, and a significant proportion identified as non-smokers (86.9%). Additionally, the participants were predominantly female (75.2%), single (91.0%), and either students or bachelor's degree holders (91.4%), with a notable percentage being unemployed (82.9%). Approximately half of the participants were classified as having normal weight (50.9%), followed by those classified as overweight (24%), with underweight and obese individuals representing similar proportions (13.2% and 12%, respectively). In terms of lifestyle habits, a majority of participants did not engage in regular physical activity (68%), and there was considerable variability in the levels of physical activity among those who did, with a mean metabolic equivalent of physical activity of 575.16 ± 1224.57 METs. Furthermore, nearly half of the participants reported consuming two main meals daily (54.5%) and dining out 1-3 times per month (46.8%), while most reported consuming two snacks between meals daily (71.1%). Table 1. Sociodemographic characteristics and lifestyle habits of study participants n(%), n=222 Variable Options n(%) Sex Female 167(75.2) Male 55(24.8) Marital status Singles 202(91.0) Married 18(8.1) Divorced 1(0.5) Widowed 1(0.5) Educational level Higher Education Msc/PhD 10(4.5) Bachelor 193(86.9) College/Diploma 7(3.2) High school 8(3.6) Middle school 2(0.9) Primary school 2(0.9) Employment Employed 38(17.1) unemployed 184(82.9) Monthly income (Jordanian Dinar) 1000 23(10.4) Undetermined 4(1.8) Smoking Yes 24(10.8) No 193(86.9) Previously 5(2.3) BMI categories (Kg/m 2) Underweight (<18.5 kg/m 2) 22(13.2) Normal (18.5-24.9 Kg/m 2 ) 85(50.9) Overweight (25-29.9 Kg/m 2 ) 40(24) Obese (≥ 30) 20(12) Physical activity performance Yes 71(32.0) No 151(68.0) Insomnia Usually 35(15.8) Sometimes 89(40.1) Rarely 98(44.1) Interrupted sleep Usually 35(15.8) Rarely 116(52.3) Number of main meals per day One 25(11.3) Two 121(54.5) Three 60(27.0) > Three 16(7.2) Cont.Table 1. Sociodemographic characteristics and lifestyle habits of study participants n(%), n=222 Number of snacks per day One 84(37.8) Two 74(33.3) Three 30(13.5) > Three 19(8.6) None 15(6.8) The number of times you are dining out Never 13(5.9) < 1/month 36(16.2) 1-3/ month 104(46.8) 1-3/week 52(23.4) 4-6/week 6(2.7) Daily 11(5.0) 4.2. Trends in Social Media Use Among Study Participants An overview of social media usage among the study participants is presented in Table 2. Among the various social media platforms, Instagram emerged as the most widely utilized, with 68% of participants indicating usage, while Pinterest was the least used at 1.8%. The data also revealed that the highest reported duration of social media use was between 3 and 5 hours per day, primarily for entertainment purposes (37.4%), followed by social communication (33.1%). Although the ≤1 hour/day category included a limited number of participants (n=8), it was maintained as a distinct group due to its representation of minimal exposure, consistent with previous literature that designates 1 hour or less as a reference category. This approach facilitates transparent reporting of the full spectrum of social media use [38]. Nearly half of the participants reported using social media in the afternoon, specifically between 7:00 PM and 12:00 AM. Conversely, approximately 20% of participants indicated being more influenced by advertisements from social media influencers compared to those from companies and applications. Table 2: Trends of social media use among the study participants n (%), n=222 Variable Options n(%) Time spent on social media (hours) ≤1 8(3.6) 1-3 33(14.9) 3≥-5 83(37.4) 5≥-7 63(28.4) ≥7 35(15.8) The period during which social media is most used 6:00- <11:00 am 4 (1.8) 11:00 am- < 3:00 pm 11(5) 3:00 pm- < 7:00 pm 38(17.1) 7:00-12:00 pm 120(54.1) Other 49(22.1) Most used platform Instagram 156(68) Facebook 18(8.1) YouTube 9(3.6) Twitter 9(3.6) Pinterest 6(1.8) Snapchat 19(7.2) WhatsApp 12(5.0) The main purpose of using social media To get health, medical, and scientific information 40(10.84) Following or publishing religious issues 29(7.86) For social communication 122(33.06) for entertainment 138(37.4) for marketing and displaying products for advertising and publicity 5(1.36) Follow up political issues 30(8.13) None of the above 5(1.38) Which of the following has most affected you? Social media influencer’s advertisement 45 (20.3) Company advertisements 13(5.9) Advertisements for applications used on the phone 14(6.3) Appetite and craving for food increase when watching food advertisements None of the above 150(67.6) Yes 93(41.9) No 38(17.1) Sometimes 91(41.0) Cont. Table 2. Trends of social media use among the study participants n (%), n=222 Do you think about health and body weight when watching food advertisements? Yes 117(52.7) No 105(47.3) When participants were asked whether their appetite and cravings increased upon viewing food advertisements on social media, 41.9% acknowledged being influenced by such advertisements, and nearly half of the participants reported considering their health and food choices while engaging with these advertisements. 4.3. The Effect of Differences in Time Spent on Social Media and Sociodemographic, Lifestyle, and Body Composition Factors Table 3 illustrates the impact of time spent on social media in relation to demographic and lifestyle habits. Factors such as sex, insomnia, and smoking showed no significant association with time spent on social media. In contrast, regular physical activity was significantly associated with time spent on social media (p-value = 0.027). Additionally, the time spent on social media did not influence the frequency of main meals (p-value = 0.32) or snacks (p-value = 0.969) consumed daily. However, it was associated with increased appetite and cravings for food when viewing food advertisements (p-value = 0.021), the frequency of dining out (p-value = 0.000), and the likelihood of ordering ready-to-eat foods (p-value = 0.045), as shown in Figure 1. The data also revealed a correlation between time spent on social media and interrupted sleep (p-value = 0.036) as presented in Table 3. Another significant finding suggests that considerations regarding health and body weight play a role in the decision to cease ordering ready-to-eat meals, as shown in Figure 1. Table 4 displays the associations between BMI and certain dietary habits related to social media use, indicating that higher BMI values are significantly associated with greater self-control in ordering ready-to-eat foods (p-value = 0.032). Thinking about health and body weight when watching food advertisements (p-value=0.008), and the lack of snack consumption (p-value=0.007). Further, the amount of water consumed daily had a significant but weak correlation with BMI (0.134, p-value 0.046) (data not shown). Table 3: The effect of differences between the time spent on social media and sociodemographic data, and lifestyle habits. Time spent on social media Variable The options ≤ 1 hour n 1-3 hours n 3≥-5 hours N 5≥-7 hours n ≥7 hours n P- value Sex Female 4 27 61 51 24 0.903 Male 4 6 22 12 11 Smoking Yes 2 2 6 9 5 0.07 No 5 29 75 54 30 Previously 1 2 2 0 0 Regular Physical Activity Yes 5 9 32 20 5 0.027 No 3 24 51 43 30 Insomnia Usually 0 3 11 12 9 0.527 Sometimes 3 16 33 25 12 Rarely 5 14 39 26 14 Interrupted sleep Usually 0 4 7 12 12 0.036 A chi-square test was performed to assess the association between variables. Data are presented as numbers of participants. Statistical significance was set at p -value< 0.05. Table 4: The body mass index and selected dietary habits (Mean ± SD), n=222 Dietary habits Options Body mass index (Mean±SD) P -value Number of main meals per day One 26.02±5.30 0.286 Two 24.10±5.10 Three 23.77±4.91 > Three 24.52±4.18 Cont.Table 4: The body mass index and selected dietary habits (Mean ± SD), n=222 Number of snacks per day One 24.14±4.92 a 0.007 Two 24.27±5.46 a Three 22.62±3.45 a > Three 24.00±4.06 a None 28.45±5.38 b Dining out Never 26.01±5.73 0.762 < Once/month 23.96±4.65 1-3/ month 23.99±5.34 1-3/week 24.69±4.85 4-6/week 23.25±3.73 Daily 24.14±4.04 Appetite and craving for food when watching food advertisements Yes 23.97±5.36 0.765 No 24.34±3.74 Sometimes 24.51±5.17 No 23.32±4.83 If you think about health and body weight, did this stop you from ordering ready-to-eat food Yes 25.28±5.50 0.032 No 23.70±4.82 An ANOVA test was performed to assess the association between BMI and dietary habits. Data are presented as mean±SD. Statistical significance was set at p -value< 0.05. The Least Significant Difference was used for post-hoc analysis, different superscript letters within the same variable indicate statistical significance. A statistically significant association was observed between total physical activity (PA) MET and the time spent on social media (p=0.001). Specifically, participants who spent less than 1 hour on social media reported a significantly higher mean total PA MET (2250.00±2173.06a) compared to all other groups. Those spending 1-3 hours (660.66±1494.02b), 3≥-5 hours (607.01±1213.75b), 5≥-7 hours (379.04±762.12b), and ≥7 hours (374.59±1100.96b) on social media showed significantly lower and comparable levels of total PA MET. In contrast, no statistically significant differences were found across social media usage groups for weekday sleep times (p=0.153) or weekend sleep times (p=0.636). Similarly, water intake (p = 0.226) did not show a significant association with social media use, as presented in Supplementary Table 2. Discussion This cross-sectional study among Jordanian adults provides novel evidence regarding the association between social media use and risk factors for cardiovascular diseases (CVDs); lifestyle and anthropometric factors. The mean age of participants was 21.39 ± 4.93 years, reflecting the predominance of young adults in social media engagement. Most participants were single (91%), consistent with previous findings that being single increases vulnerability to the influence of social media on eating behaviours. Ismail et al. (2024) reported a 3.2% greater effect of social media among singles [38]. A significant negative association was found between time spent on social media and physical activity (p = 0.027), aligning with Saudi Arabian research linking sedentary behavior to media use [39]. Conversely, other studies reported potential benefits of social media, such as peer encouragement and improved adherence to weight management interventions [40-44]. In our study, the highest prevalence of physical inactivity occurred among participants who used social media for 3–5 hours per day. Previous research has shown that using the internet or social media for more than four hours daily adversely affects physical activity, sleep, and overall health [45]. In line with this, our findings demonstrated that longer social media use was significantly associated with disturbed sleep (p = 0.036), supporting evidence that links social media to poor sleep quality, daytime sleepiness, and insomnia [46-48]. Dietary outcomes were also affected. Social media use significantly influenced appetite and food cravings (p = 0.021), frequency of dining out (p = 0.00), and ordering ready-to-eat meals (p = 0.045), particularly when participants were exposed to food advertising. These findings correspond with previous studies demonstrating a positive relationship between social media exposure and altered eating habits [49-51]. Heavy users (>4 hours/day) have been reported to skip meals [52], while exposure to food-related content increased snacking among adolescents and adults [53]. Although our study found no significant association between social media and the total number of meals or snacks consumed, meal skipping and greater responsiveness to food marketing were most common among participants using social media 3–5 hours daily. This group was more likely to consume foods high in saturated fat, cholesterol, and sodium, thereby elevating CVD risk [54]. The cue reactivity theory offers a possible explanation, suggesting that exposure to food marketing activates responses that shape eating behavior, food choices, and purchasing patterns across media platforms [55, 56]. Food advertisements may trigger brain activity in response to visual cues, thereby increasing snacking and predicting weight gain [57, 58]. Moreover, food-related posts linked to social contexts, such as dining out with friends, may further reinforce the influence of social media on food cravings [59]. Despite the high educational level of most participants (91.4% held a bachelor’s degree or higher), susceptibility to misleading content from influencers and companies was evident. This reliance on social media for food-related decisions contributes to emotional eating, disordered behaviors, obesity, and chronic disease [39, 60]. As it was observed in our study, no significant effect of social media on BMI, body weight, or body composition. These findings are consistent with some prior studies [61–63], though others reported associations between screen time and higher BMI, waist circumference, waist-to-hip ratio, and body fat [64]. Interestingly, participants reporting no snacking had the highest BMI, which may reflect under-reporting, meal skipping with compensatory overeating, or reverse causality. While some participants with higher BMI avoided snacks as a weight-control strategy, other studies found that obese individuals were more likely to purchase food or beverages after viewing related advertisements [53]. Participants spending 3–5 hours per day on social media also had the highest mean waist-to-hip ratio (WHR), exceeding the cut-off thresholds (>0.8 for females, >0.95 for males) [65], despite having a mean BMI within the normal range (23.96 ± 4.72). WHR is an established indicator of central obesity, which is associated with metabolic abnormalities and heightened CVD risk [66]. Moreover, previous research links excessive social media use (>3 hours/day) to mental health problems such as depression, stress, and anxiety [67]. These conditions in turn increase cardiometabolic risk factors, including hypertension, dyslipidemia, and diabetes, thereby mediating the relationship between mental health and CVDs [68]. Notably, studies suggest that restricting social media use to less than 30 minutes per day may improve overall health and well-being [67]. To our knowledge, this is the first study in Jordan to evaluate the associations between social media use and multiple CVD risk factors, including anthropometric, dietary, and lifestyle variables, using validated questionnaires and more precise adiposity measures beyond BMI. Strengths and Limitations The main strengths of this study include its novelty within the Jordanian context and the use of validated instruments to capture social media’s influence on health-related behaviors. Nonetheless, several limitations must be acknowledged. The cross-sectional design precludes causal inference. Reliance on self-reported data may have introduced recall and social desirability bias, and web-based recruitment could contribute to selection bias. Females accounted for 75.2% of participants, which limits sex-stratified analyses and generalizability, as females are generally more affected by social media than males [39, 69]. Additionally, the small sample size in the <1 hour/day group (n = 8) reduces estimate reliability, although it was retained to ensure comparability with previous research. Testing multiple outcomes increases the likelihood of type I error; thus, findings should be interpreted with caution. Physical activity may have acted as both a confounder and an outcome, which could not be fully disentangled. Other limitations include the absence of laboratory tests, blood pressure measurements, genetic predisposition, family history of CVDs, or specific dietary requirements. Attrition during study stages also limited the final sample for body composition analysis. Conclusion In conclusion, excessive social media use among Jordanian adults is associated with unhealthy dietary behaviors, meal skipping, reduced physical activity, and disturbed sleep, collectively increasing the risk of obesity and cardiovascular diseases. Despite no significant association with BMI, elevated waist-to-hip ratio and susceptibility to food marketing highlight critical public health concerns, underscoring the need for balanced media use and healthier lifestyle promotion. Declarations Authors’ contribution: Eman Alhasan and Maysoun Qutob contributed to the conceptualization, investigation, data gathering, methodology, writing the original draft, and supervision. Shatha Hammad analyzed the data and interpreted the results. All authors have reviewed and approved the published version of the manuscript. Acknowledgments : The authors would like to thank Dr. Anfaal Dalaeen, the head of the Nutrition Department at the Allied Medical Science Faculty, Applied Science Private University, for their assistance in preparing the manuscript and support in accessing the participants. Conflicts of interest : The authors declare that they have competing interests. Ethics Approval and Consent to Participate: All participants were informed about the aims and procedures of the study, and informed consent was obtained through the electronic questionnaire. The FAMS Ethics Committee approved this study for ethical approval of research projects at the Allied Medical Science Faculty in the Applied Science Private University. Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Competing interests The authors declare no competing interests. Author contributions EO Alhasan: Conceptualization, methodology, investigation, writing – original draft, supervision. MS Qutob: Conceptualization, methodology, writing – review & editing, supervision. SS Hammad: Data analysis, interpretation, writing – review & editing. Patient consent Patient consent for publication: Not required as the study did not involve personal medical information about identifiable individuals. Data sharing Data sharing statement: The technical appendix, statistical code, and anonymised dataset are available from the corresponding author on reasonable request. References Tripathi, M., et al., Effect of social media on human health . Virology & Immunology Journal, 2018. 2(2): p. 1–3. Jane, M., et al., Social media for health promotion and weight management: a critical debate . BMC public health, 2018. 18: p. 1–7. Chaffey, D. Global social media statistics research summary May 2024 . Digital marketing statistics 2024; Available from: https://www.smartinsights.com/social-media-marketing/social-media-strategy/new-global-social-media-research/ . KEMP, S. Digital 2024: Jordan . Global Digital Reports 2024; Available from: https://datareportal.com/reports/digital-2024-jordan . Ali, S., et al., The burden of cardiovascular diseases in Ethiopia from 1990 to 2017: evidence from the Global Burden of Disease Study . International Health, 2021. 13(4): p. 318–326. Sharma, S. and M.J. Wood, The global burden of cardiovascular disease in women . Current Treatment Options in Cardiovascular Medicine, 2018. 20: p. 1–9. Kaptoge, S., et al., World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions . The Lancet global health, 2019. 7(10): p. e1332-e1345. Tsao, C.W., et al., Heart disease and stroke statistics—2022 update: a report from the American Heart Association . Circulation, 2022. 145(8): p. e153-e639. Sawalha, K., et al., Profiling Cardiometabolic health in Jordan: a call to action to improve cardiovascular health . Cureus, 2023. 15(5). Al-Ajlouni, Y.A., et al., The burden of Cardiovascular diseases in Jordan: a longitudinal analysis from the global burden of disease study, 1990–2019 . BMC Public Health, 2024. 24(1): p. 879. Foundation, B.H. Health Diseases . 2014 [cited 2021 11 February]; Available from: https://www.bhf.org.uk/old-starts-with-your-heart/heart-diseases Khot, U.N., et al., Prevalence of conventional risk factors in patients with coronary heart disease . Jama, 2003. 290(7): p. 898–904. Arena, R., et al., Applying precision medicine to healthy living for the prevention and treatment of cardiovascular disease . Current problems in cardiology, 2018. 43(12): p. 448–483. Humphreys, S., The unethical use of BMI in contemporary general practice . British Journal of General Practice, 2010. 60(578): p. 696–697. Gómez-Ambrosi, J., et al., Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity . International journal of obesity, 2012. 36(2): p. 286–294. De Koning, L., et al., Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: meta-regression analysis of prospective studies . European heart journal, 2007. 28(7): p. 850–856. Neeland, I.J., et al., Body fat distribution and incident cardiovascular disease in obese adults . Journal of the American College of Cardiology, 2015. 65(19): p. 2150–2151. Pou, K.M., et al., Visceral and subcutaneous adipose tissue volumes are cross-sectionally related to markers of inflammation and oxidative stress: the Framingham Heart Study . Circulation, 2007. 116(11): p. 1234–1241. Hamdy, O., S. Porramatikul, and E. Al-Ozairi, Metabolic obesity: the paradox between visceral and subcutaneous fat . Current diabetes reviews, 2006. 2(4): p. 367–373. Abraham, T.M., et al., Association between visceral and subcutaneous adipose depots and incident cardiovascular disease risk factors . Circulation, 2015. 132(17): p. 1639–1647. Cernat, D., How social media influences our food consumption. 2022. De Veirman, M., V. Cauberghe, and L. Hudders, Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude . International journal of advertising, 2017. 36(5): p. 798–828. Sacks, G. and E.S.Y. Looi, The advertising policies of major social media platforms overlook the imperative to restrict the exposure of children and adolescents to the promotion of unhealthy foods and beverages . International journal of environmental research and public health, 2020. 17(11): p. 4172. Organization, W.H., Food marketing exposure and power and their associations with food-related attitudes, beliefs and behaviours: a narrative review. 2022. Grilo, G., E. Crespi, and J.E. Cohen, A scoping review on disparities in exposure to advertising for e-cigarettes and heated tobacco products and implications for advancing a health equity research agenda . International journal for equity in health, 2021. 20: p. 1–13. Rossi, R., et al., “Get a£ 10 Free Bet Every Week!”—gambling advertising on Twitter: volume, content, followers, engagement, and regulatory compliance . Journal of public policy & marketing, 2021. 40(4): p. 487–504. Thomas, S.L., et al., Young people’s awareness of the timing and placement of gambling advertising on traditional and social media platforms: a study of 11–16-year-olds in Australia. Harm reduction journal, 2018. 15: p. 1–13. Barry, A.E., et al., Alcohol advertising on social media: Examining the content of popular alcohol brands on Instagram . Substance use & misuse, 2018. 53(14): p. 2413–2420. Monitoring and restricting digital marketing of unhealthy products to children and adolescents . Activities 2018; Available from: https://www.who.int/europe/activities/monitoring-and-restricting-digital-marketing-of-unhealthy-products-to-children-and-adolescents . Coalition, O.P., Under the radar: harmful industries' digital marketing to Australian children. 2020. Nakshine, V.S., et al., Increased screen time as a cause of declining physical, psychological health, and sleep patterns: a literary review . Cureus, 2022. 14(10). Park, Y.-M.M., et al., Association of exposure to artificial light at night while sleeping with risk of obesity in women . JAMA internal medicine, 2019. 179(8): p. 1061–1071. Valenzuela, P.L., et al., Obesity and the risk of cardiometabolic diseases . Nature reviews cardiology, 2023. 20(7): p. 475–494. Pourhoseingholi, M.A, Vahedi. M, Rahimzadeh M. Sample size calculation in medical studies .Gastroenterology and Hepatology From Bed to Bench, 2013. 6(1): p.14 – 7. Washburn, R.A., et al., The validity of the Stanford seven-day physical activity recall in young adults . Medicine & Science in Sports & Exercise, 2003. 35(8): p. 1374–1380. Sallis, J.F., et al., Physical activity assessment methodology in the Five-City Project . American journal of epidemiology, 1985. 121(1): p. 91–106. Craig, C.L., et al., International physical activity questionnaire: 12-country reliability and validity . Medicine & science in sports & exercise, 2003. 35(8): p. 1381–1395. Ismail, L.C., et al., The association of social media with dietary behaviors among adults in the United Arab Emirates . Heliyon, 2024. 10(15). Alwafi, H., et al., The impact of social media influencers on food consumption in Saudi Arabia, a cross-sectional web-based survey . Journal of Multidisciplinary Healthcare, 2022: p. 2129–2139. Abioye, A.I., K. Hajifathalian, and G. Danaei, Do mass media campaigns improve physical activity? a systematic review and meta-analysis . Archives of Public Health, 2013. 71: p. 1–10. Hill, E., College Student Social Media Use and its relation to health behaviors . 2013, The Ohio State University. Laranjo, L., et al., The influence of social networking sites on health behavior change: a systematic review and meta-analysis . Journal of the American Medical Informatics Association, 2015. 22(1): p. 243–256. Santtila, M., et al., Impact of a social media exercise service on individuals and employees . Biomedical human kinetics, 2016. 8(1): p. 65. King, K.M. and G.B. Gonzalez, Increasing physical activity using an ecological model . ACSM's Health & Fitness Journal, 2018. 22(4): p. 29–32. Hudimova, A., et al., Research on the relationship between excessive use of social media and young athletes' physical activity . Journal of Physical Education and Sport, 2021. 21(6): p. 3364–3373. Ilham, N.A., et al., Impact of intense social media usage on sleeping pattern . Bulletin of Social Informatics Theory and Application, 2022. 6(2): p. 120–131. Lissak, G., Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study . Environmental research, 2018. 164: p. 149–157. Cain, N. and M. Gradisar, Electronic media use and sleep in school-aged children and adolescents: A review . Sleep medicine, 2010. 11(8): p. 735–742. Blanchard, L., et al., Associations between social media, adolescent mental health, and diet: A systematic review . Obesity reviews, 2023. 24: p. e13631. Filippone, L., R. Shankland, and Q. Hallez, The relationships between social media exposure, food craving, cognitive impulsivity and cognitive restraint . Journal of Eating Disorders, 2022. 10(1): p. 184. Holland, G. and M. Tiggemann, A systematic review of the impact of the use of social networking sites on body image and disordered eating outcomes . Body image, 2016. 17: p. 100–110. Kim, J.H., et al., Brief report: predictors of heavy Internet use and associations with health-promoting and health risk behaviors among Hong Kong university students . Journal of adolescence, 2010. 33(1): p. 215–220. Aljefree, N.M. and G.T. Alhothali, Exposure to food marketing via social media and obesity among university students in Saudi Arabia . International journal of environmental research and public health, 2022. 19(10): p. 5851. (CDC), C.f.D.C.a.P. Heart Disease Risk Factors . [cited 2024 December 2]; Available from: https://www.cdc.gov/heart-disease/risk-factors/index.html . Boswell, R.G. and H. Kober, Food cue reactivity and craving predict eating and weight gain: a meta-analytic review . Obesity reviews, 2016. 17(2): p. 159–177. Boyland, E., et al., Associations between everyday exposure to food marketing and hunger and food craving in adults: An ecological momentary assessment study . Appetite, 2024. 196: p. 107241. Lawrence, N.S., et al., Nucleus accumbens response to food cues predicts subsequent snack consumption in women and increased body mass index in those with reduced self-control . Neuroimage, 2012. 63(1): p. 415–422. Yokum, S., J. Ng, and E. Stice, Attentional bias to food images associated with elevated weight and future weight gain: an fMRI study . Obesity, 2011. 19(9): p. 1775–1783. Qutteina, Y., et al., What do adolescents see on social media? A diary study of food marketing images on social media . Frontiers in psychology, 2019. 10: p. 2637. Zhang, J., et al., The relationship between SNS usage and disordered eating behaviors: A meta-analysis . Frontiers in Psychology, 2021. 12: p. 641919. Biddle, S.J., E. García Bengoechea, and G. Wiesner, Sedentary behaviour and adiposity in youth: a systematic review of reviews and analysis of causality . International Journal of Behavioral Nutrition and Physical Activity, 2017. 14: p. 1–21. Sampasa-Kanyinga, H., J.-P. Chaput, and H.A. Hamilton, Associations between the use of social networking sites and unhealthy eating behaviours and excess body weight in adolescents . British Journal of Nutrition, 2015. 114(11): p. 1941–1947. Alley, S., et al., Impact of increasing social media use on sitting time and body mass index . Health Promotion Journal of Australia, 2016. 28(2): p. 91–95. Suchert, V., R. Hanewinkel, and B. Isensee, Screen time, weight status and the self-concept of physical attractiveness in adolescents . Journal of adolescence, 2016. 48: p. 11–17. Center, B.C.H. Waist/ Hip Ratio and Cardiac Disease Risk . 2016 [cited 2025 May 5]; Available from: https://bchealth.org/waist-hip-ratio-cardiac-disease-risk/ . Ahmad, M.I., et al., Waist to hip ratio modifies the cardiovascular risk of lipoprotein (a): Insights from MESA . Progress in Cardiovascular Diseases, 2025. Riehm, K.E., et al., Associations between time spent using social media and internalizing and externalizing problems among US youth . JAMA psychiatry, 2019. 76(12): p. 1266–1273. Civieri, G., et al., Anxiety and Depression Associated with Increased Cardiovascular Disease Risk Through Accelerated Development of Risk Factors . JACC: Advances, 2024. 3(9_Part_1): p. 101208. Wilksch, S.M., et al., The relationship between social media use and disordered eating in young adolescents . International Journal of Eating Disorders, 2020. 53(1): p. 96–106. Additional Declarations There is NO conflict of interest to disclose. Supplementary Files SupplementaryTable1.docx Supplementary table 1. the Demographic and anthropometric data of study participants (Mean±SD), n=222 SupplementaryTable2.docx Supplementary table 2: Time spent on social media, lifestyle habits, and body composition (Mean±SD), n=222 SupplementaryFigure.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":93690,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e)The relationship between the time spent on social media and the number of meals that the participants took per day, \u003cem\u003eP\u003c/em\u003e=0.32. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e-value\u0026lt; 0.05. (\u003cstrong\u003eb)\u003c/strong\u003eThe relationship between the time spent on social media and the number of snacks that the participants took per day, P=0.969. Statistical significance was set at p-value\u0026lt; 0.05. \u003cstrong\u003e(c)\u003c/strong\u003e Illustrates the food craving and or increasing appetite when watching food advertisements on social media, \u003cem\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e=0.021\u003c/strong\u003e. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e-value\u0026lt; 0.05 \u003cstrong\u003e(d)\u003c/strong\u003eThe relationship between time spent on social media and times of dinning out, \u003cem\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e=0.000\u003c/strong\u003e. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e-value\u0026lt; 0.05. \u003cstrong\u003e(e) \u003c/strong\u003eThe effect of thinking about health and body weight on stop ordering ready-to-eat food, \u003cem\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e=0.045\u003c/strong\u003e. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e-value\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7724259/v1/0496a7cc48054e269295fa08.png"},{"id":96708068,"identity":"6613fd04-94c0-4530-ac11-a3acb84ed1fa","added_by":"auto","created_at":"2025-11-25 09:54:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1806094,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7724259/v1/09acb418-d632-4993-b6a4-ed1d45efe3e9.pdf"},{"id":94047976,"identity":"3cbd4490-3578-4b1a-a638-55bafc351305","added_by":"auto","created_at":"2025-10-21 23:19:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16277,"visible":true,"origin":"","legend":"Supplementary table 1. the Demographic and anthropometric data of study participants (Mean\u0026#x00B1;SD), n=222","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7724259/v1/5ee070c3cd35f4541a8e8357.docx"},{"id":94047977,"identity":"dee3459b-951f-472d-acd3-8c4deefea454","added_by":"auto","created_at":"2025-10-21 23:19:11","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18934,"visible":true,"origin":"","legend":"Supplementary table 2: Time spent on social media, lifestyle habits, and body composition (Mean\u0026#x00B1;SD), n=222","description":"","filename":"SupplementaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7724259/v1/45a6bdf96d3ba3f506862f1d.docx"},{"id":94047986,"identity":"2d34d14c-1c60-4f1a-aec5-e3a1a707c655","added_by":"auto","created_at":"2025-10-21 23:19:11","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":281635,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-7724259/v1/5e9ac9b6fcd8ba2d57ce7bba.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Impact of Social Media Engagement and Food Marketing Exposure on Cardiovascular Risk Factors in Jordanian Adults: A Cross-Sectional Study","fulltext":[{"header":" Key Messages","content":"\u003cp\u003e\u003cstrong\u003eWhat is already known on this topic\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSocial media use is highly prevalent among young adults and has been linked globally to physical inactivity, disrupted sleep, and unhealthy eating behaviors. However, little is known about these associations in Jordanian adults, particularly with regard to exposure to food marketing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study demonstrates that greater time spent on social media is significantly associated with physical inactivity, poor sleep, increased appetite, and unhealthy food choices. Exposure to food advertisements further influenced cravings, dining out, and ordering ready-to-eat foods.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHow this study might affect research, practice or policy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings highlight the need for clinicians, dietitians, and policymakers to consider the influence of social media when addressing cardiovascular risk factors. They also suggest that stricter regulations of food marketing on social media and targeted health promotion campaigns are warranted.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eSocial media has become an integral component of daily life, significantly impacting individuals\u0026rsquo; lives [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Platforms such as WhatsApp, Instagram, Facebook, Snapchat, and Twitter serve as essential communication tools worldwide [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to the latest data from the April Global Overview, the time spent on social media has increased over the years; over half of the global population (62.6%) engages with social media, totaling 5.07\u0026nbsp;billion users who spend an average of 2 hours and 20 minutes daily on these platforms [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In Jordan, there were 10.33\u0026nbsp;million internet users at the beginning of 2024, reflecting an internet penetration rate of 91.0%, with 56.2% of the population (6.38\u0026nbsp;million) utilizing social media [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCardiovascular diseases (CVDs), which encompass a range of disorders affecting the heart and blood vessels, are among the leading causes of death globally [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. A global estimate by the World Health Organization (WHO) in 2017 indicated that 17.5\u0026nbsp;million individuals succumb to CVDs each year [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], representing approximately one-third of all global fatalities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], More than 75% of these deaths occur in low- and middle-income countries [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. CVDs also rank as a primary cause of mortality in Jordan, with a cause-specific mortality rate of 18.6% reported by WHO in 2020 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Furthermore, Jordan has witnessed a significant increase in the prevalence of cardiovascular diseases, rising from 38% in 2009 to 48.2% in 2020. However, there remains a notable gap in the availability of the epidemiological profile for Arab countries, including Jordan [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThere is an increasing demand for a comprehensive understanding of the demographic profile of cardiovascular diseases (CVDs) and their associated risk factors within populations. This understanding can guide the development of strategies and policies that effectively address the unique public health needs of these communities through public health systems. Numerous factors\u0026mdash;such as genetic, demographic, and environmental influences\u0026mdash;are recognized as significant contributors to CVDs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Notably, approximately 50% of CVD risk is linked to modifiable factors, including sedentary behavior, unhealthy dietary patterns characterized by excessive caloric intake, overweight or obesity, and smoking [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In response, there is a growing emphasis on the concept of \u0026ldquo;Healthy Living Medicine\u0026rdquo; (HLM), which highlights the critical role of lifestyle and modifiable factors in both the prevention and treatment of CVDs. Despite widespread awareness and educational initiatives, many individuals still struggle to modify these risk factors, even after the onset of chronic diseases that increase their susceptibility to cardiovascular complications [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBody mass index (BMI) is not a perfect measure, as it cannot differentiate between fat and muscle mass [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, it's crucial to highlight the importance of recognizing abdominal obesity through waist circumference (WC) and waist-to-hip ratio (WHR), which are associated with the development of cardiovascular disease in individuals with \"normal-weight obesity\"\u0026mdash;those with excess fat who do not meet the obesity criteria based on BMI [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, there is a biological connection between fat distribution and cardiovascular diseases (CVDs) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]; A higher volume of visceral adipose tissue (VAT) is linked to increased cardiovascular risk factors over time, including insulin resistance, which BMI does not fully account for [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSocial media provides new avenues for social connection and data exchange; however, it can also adversely affect physical and mental health. It serves as a marketing platform for numerous food and beverage companies that engage in influencer advertising [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which creates a complex relationship between authentic social media content and marketing, especially when disseminated by influencers [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. As a result, the influence of social media on eating behavior is deteriorating, given that the most widely used platforms often lack stringent regulations regarding the advertising of unhealthy foods, such as ultra-processed items and tobacco [\u003cspan additionalcitationids=\"CR25 CR26 CR27\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], which are increasingly promoted through home delivery services [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Moreover, exposure to mobile screens at night while browsing social media can lead to diminished sleep quality and various sleep-related issues [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The blue light emitted from screens may disrupt glucose metabolism, particularly in women, potentially contributing to obesity [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This condition has direct negative implications for cardiac structure and function and elevates the risk of developing cardiovascular diseases [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study aims to examine the impact of social media platform usage on risk factors associated with cardiovascular diseases, such as sedentary lifestyle and eating behaviors, including the influence of exposure to food/ drink marketing on social media on appetite and food cravings among a group of Jordanian adults.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Study Design and Study Population\u003c/h2\u003e\u003cp\u003eA cross-sectional study utilizing an online survey was conducted with 222 participants aged 18 to 45 years residing in Jordan. After excluding 161 participants for various reasons\u0026mdash;withdrawal of consent (n\u0026thinsp;=\u0026thinsp;10), incomplete questionnaires (n\u0026thinsp;=\u0026thinsp;15), and ineligibility due to age (n\u0026thinsp;=\u0026thinsp;7), as detailed in the supplementary figure.1 \u0026mdash;The final sample consisted of individuals who were students and employees at the Applied Science Private University in Amman, Jordan. Recruitment occurred between December 24, 2023, and April 25, 2024, during which participants completed the online survey along with other study requirements.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Sampling Strategy\u003c/h2\u003e\u003cp\u003eA convenience sample of eligible participants was recruited through a weekly post shared over a two-month period, utilizing a survey link distributed across major social media platforms (Facebook, Instagram, WhatsApp, and Teams), in collaboration with university groups and community pages. To enhance outreach, reminders were posted eight times, and messages were resent to active groups. No monetary incentives were provided; thus, all participants voluntarily consented to participate in the study by indicating their agreement in the online questionnaire through the selection of the \"yes, I agree, and hereby give my informed consent\" option.\u003c/p\u003e\u003cp\u003eThe inclusion criteria specified that participants must be aged between 18 and 45 years, possess no cognitive disabilities, and for women, must not be pregnant or lactating. Additionally, participants should not have been diagnosed with cardiovascular diseases (CVDs) such as myocardial infarction, stroke, or coronary heart disease, nor should they have eating disorders or any conditions that affect appetite. Furthermore, individuals who had taken corticosteroids within the past month were also included in the study. Conversely, anyone who did not meet the inclusion criteria or failed to complete the questionnaire was excluded from the study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Sample Size\u003c/h2\u003e\u003cp\u003eThe target sample size was calculated using the Cochrane formula: n = (Z\u0026sup2; \u003cem\u003e* P\u003c/em\u003e * (1-P)) / d\u0026sup2;, where Z represents the confidence level (95%, z\u0026thinsp;=\u0026thinsp;1.96), P is estimated from previous studies (0.56 or 56%, based on national statistics), and d is the margin of error (0.05 or 5%) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Consequently, the required sample size was determined to be 378 participants.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Questionnaire Tool\u003c/h2\u003e\u003cp\u003eThis study developed and adapted a self-administered, validated questionnaire to meet its objectives. The questionnaire comprised 56 items organized into six sections. The first section (11 items) inquired about the participants' personal and sociodemographic characteristics. The second section (4 items) collected anthropometric information, including current weight and height, and whether participants had experienced any changes in their body weight over the past month. The third section examined lifestyle factors, including physical activity, sleep patterns, and smoking habits. The following section (11 items) focused on participants' medical history and health status. The next section (9 items) addressed eating habits over the previous month. The final section (10 items) investigated the impact of social media usage.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Assessment of Physical Activity\u003c/h2\u003e\u003cp\u003ePhysical activity was assessed using the validated Seven-Day Physical Activity Recall questionnaire, measured in Metabolic Equivalent of Task (METs) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Data on the number of hours spent at various activity levels were collected through this questionnaire, developed by Sallis et al. (1985) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and subsequently converted into MET values. The average MET values were designated as follows: moderate activity\u0026thinsp;=\u0026thinsp;3.3 METs, vigorous activity\u0026thinsp;=\u0026thinsp;8 METs, and extreme activity\u0026thinsp;=\u0026thinsp;10 METs. The MET-minutes per week score was calculated using the equation: (MET level \u0026times; minutes of activity per day \u0026times; days per week). The total physical activity (MET-minutes/week) was then aggregated to facilitate categorical analysis: inactive, minimally active, and health-enhancing physical activity (HEPA). Categorization was conducted according to the standard scoring protocol of the International Physical Activity Questionnaire (version 2, 2004) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Body Composition Measurements\u003c/h2\u003e\u003cp\u003eParticipants who completed the online questionnaire were invited to the Nutrition Clinic at the Applied Science Private University to fulfill the requirements of their involvement in the study. Prior to their appointment, participants received recommended instructions, which included fasting for a minimum of three hours, wearing lightweight clothing, avoiding exercise before measurements, and, for female participants, not being in their menstrual cycle. Trained examiners measured participants\u0026rsquo; height and body composition using standardized techniques. Height was measured with a BSM 170 device to the nearest 0.1 cm, with two measurements taken to calculate an average. Body weight (kg), body composition metrics including fat mass (kg) and skeletal muscle mass (kg), visceral fat levels, and abdominal obesity parameters\u0026mdash;waist circumference (cm) and waist-to-hip ratio (cm)\u0026mdash;were assessed using the InBody 770 device.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7. Social Media Use\u003c/h2\u003e\u003cp\u003eThe assessment of social media encompassed multiple dimensions, including average daily time spent on various platforms, type of engagement (active versus passive), time of day most frequently used, primary platforms accessed, main purposes of use, types of content deemed most influential, and the perceived impact of social media on concentration and appetite, particularly concerning food recipes and restaurant advertisements. These variables were treated as distinct exposures to facilitate a more precise examination of their differential associations with dietary behaviors, lifestyle patterns, and cardiovascular risk factors. The social media questions addressed the time spent on these platforms over the past month.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003e3.\tStatistical Analysis\u003c/h3\u003e\n\u003cp\u003eThe associations between the time spent on social media and body composition and dietary and lifestyle habits were performed using the SPSS statistical package version 26. Descriptive statistics were performed for all of the variables and presented as mean and standard deviation for continuous variables and as n (%) for categorical variables. The normality of the distribution was assessed using histogram plots. Analysis of Covariance (ANCOVA) was used to assess the effects of the time spent on social media on body composition. Pre-specified covariates, including age, sex, and educational levels, were incorporated into statistical models. Chi-square was used to evaluate the association between the time spent on social media and categorical variables. Statistical significance was set at P \u0026lt; 0.05 for all analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e4.1. Study Participants\u0026rsquo; Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 222 participants were involved in this study. Their demographic and anthropometric characteristics are detailed in the Supplementary Table 1, along with the sociodemographic characteristics and lifestyle habits presented in Table 1. These tables collectively summarize the participants\u0026apos; anthropometric, sociodemographic, and lifestyle attributes, including dietary and physical habits. The majority of participants were young, healthy adults with a mean age of 21.39 \u0026plusmn; 4.93 years, and a significant proportion identified as non-smokers (86.9%). Additionally, the participants were predominantly female (75.2%), single (91.0%), and either students or bachelor\u0026apos;s degree holders (91.4%), with a notable percentage being unemployed (82.9%). Approximately half of the participants were classified as having normal weight (50.9%), followed by those classified as overweight (24%), with underweight and obese individuals representing similar proportions (13.2% and 12%, respectively). In terms of lifestyle habits, a majority of participants did not engage in regular physical activity (68%), and there was considerable variability in the levels of physical activity among those who did, with a mean metabolic equivalent of physical activity of 575.16 \u0026plusmn; 1224.57 METs. Furthermore, nearly half of the participants reported consuming two main meals daily (54.5%) and dining out 1-3 times per month (46.8%), while most reported consuming two snacks between meals daily (71.1%).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"728\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 728px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSociodemographic characteristics and lifestyle habits of study participants\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003en(%), n=222\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOptions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e167(75.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e55(24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSingles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e202(91.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMarried\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e18(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eDivorced\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e1(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eWidowed\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e1(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eEducational level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eHigher Education Msc/PhD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e10(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eBachelor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e193(86.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eCollege/Diploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e7(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e8(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMiddle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e2(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e2(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003eEmployment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eEmployed\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e38(17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eunemployed\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e184(82.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMonthly income (Jordanian Dinar)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e115(51.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e260-459\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e52(23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e460-659\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e12(5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e660-859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e8(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e860-1000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e8(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026gt;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e23(10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eUndetermined \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e4(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSmoking\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e24(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e193(86.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003ePreviously\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e5(2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eBMI categories (Kg/m\u003csup\u003e2)\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eUnderweight (\u0026lt;18.5 kg/m\u003csup\u003e2)\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e22(13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNormal (18.5-24.9 Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e85(50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eOverweight (25-29.9 Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e40(24)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eObese (\u0026ge; 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e20(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003ePhysical activity performance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e71(32.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e151(68.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eInsomnia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eUsually\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e35(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSometimes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e89(40.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e98(44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eInterrupted sleep\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eUsually\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e35(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eRarely\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e116(52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNumber of main meals per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eOne\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e25(11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e121(54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eThree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e60(27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026gt; Three\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e16(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 728px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCont.Table 1. Sociodemographic characteristics and lifestyle habits of study participants n(%), n=222\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNumber of snacks per day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eOne\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e84(37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTwo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e74(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eThree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e30(13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026gt; Three\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e19(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e15(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 255px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe number of times you are dining out\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e13(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt; 1/month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e36(16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e1-3/ month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e104(46.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e1-3/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e52(23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e4-6/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e6(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eDaily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e11(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e4.2. Trends in Social Media Use Among Study Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn overview of social media usage among the study participants is presented in Table 2. Among the various social media platforms, Instagram emerged as the most widely utilized, with 68% of participants indicating usage, while Pinterest was the least used at 1.8%. The data also revealed that the highest reported duration of social media use was between 3 and 5 hours per day, primarily for entertainment purposes (37.4%), followed by social communication (33.1%). Although the \u0026le;1 hour/day category included a limited number of participants (n=8), it was maintained as a distinct group due to its representation of minimal exposure, consistent with previous literature that designates 1 hour or less as a reference category. This approach facilitates transparent reporting of the full spectrum of social media use [38]. Nearly half of the participants reported using social media in the afternoon, specifically between 7:00 PM and 12:00 AM. Conversely, approximately 20% of participants indicated being more influenced by advertisements from social media influencers compared to those from companies and applications.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"718\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 718px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2: Trends of social media use among the study participants n (%), n=222\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOptions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en(%)\u003c/strong\u003e\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTime spent on social media (hours)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e8(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e1-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e33(14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e3\u0026ge;-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e83(37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e5\u0026ge;-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e63(28.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026ge;7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e35(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe period during which social media is most used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e6:00- \u0026lt;11:00 am\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e4 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e11:00 am- \u0026lt; 3:00 pm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e11(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e3:00 pm- \u0026lt; 7:00 pm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e38(17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e7:00-12:00 pm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e120(54.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e49(22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMost used platform\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eInstagram\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e156(68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFacebook\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e18(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eYouTube\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e9(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTwitter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e9(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003ePinterest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e6(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSnapchat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e19(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eWhatsApp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e12(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe main purpose of using social media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eTo get health, medical, and scientific information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e40(10.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFollowing or publishing religious issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e29(7.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFor social communication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e122(33.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003efor entertainment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e138(37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003efor marketing and displaying products for advertising and publicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e5(1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFollow up political issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e30(8.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNone of the above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e5(1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWhich of the following has most affected you?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSocial media influencer\u0026rsquo;s advertisement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e45 (20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eCompany advertisements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e13(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eAdvertisements for applications used on the phone\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e14(6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003eAppetite and craving for food increase when watching food advertisements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNone of the above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e150(67.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e93(41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e38(17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e91(41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 718px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCont. Table 2. Trends of social media use among the study participants n (%), n=222\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 246px;\"\u003e\n \u003cp\u003eDo you think about health and body weight when watching food advertisements?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e117(52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 265px;\"\u003e\n \u003cp\u003e105(47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWhen participants were asked whether their appetite and cravings increased upon viewing food advertisements on social media, 41.9% acknowledged being influenced by such advertisements, and nearly half of the participants reported considering their health and food choices while engaging with these advertisements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3. The Effect of Differences in Time Spent on Social Media and Sociodemographic, Lifestyle, and Body Composition Factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 illustrates the impact of time spent on social media in relation to demographic and lifestyle habits. Factors such as sex, insomnia, and smoking showed no significant association with time spent on social media. In contrast, regular physical activity was significantly associated with time spent on social media (p-value = 0.027). Additionally, the time spent on social media did not influence the frequency of main meals (p-value = 0.32) or snacks (p-value = 0.969) consumed daily. However, it was associated with increased appetite and cravings for food when viewing food advertisements (p-value = 0.021), the frequency of dining out (p-value = 0.000), and the likelihood of ordering ready-to-eat foods (p-value = 0.045), as shown in Figure 1. The data also revealed a correlation between time spent on social media and interrupted sleep (p-value = 0.036) as presented in Table 3. Another significant finding suggests that considerations regarding health and body weight play a role in the decision to cease ordering ready-to-eat meals, as shown in Figure 1. Table 4 displays the associations between BMI and certain dietary habits related to social media use, indicating that higher BMI values are significantly associated with greater self-control in ordering ready-to-eat foods (p-value = 0.032).\u003c/p\u003e\n\u003cp\u003eThinking about health and body weight when watching food advertisements (p-value=0.008), and the lack of snack consumption (p-value=0.007). Further, the amount of water consumed daily had a significant but weak correlation with BMI (0.134, p-value 0.046) (data not shown).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"710\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 710px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3: The effect of differences between the\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003etime spent on social media and sociodemographic data, and lifestyle habits. \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 345px;\"\u003e\n \u003cp\u003eTime spent on social media\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 345px;\"\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe options\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026le; 1 hour\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1-3 hours\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e3\u0026ge;-5 hours\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e5\u0026ge;-7 hours\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026ge;7 hours\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003ePreviously\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eRegular Physical Activity\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003eInsomnia\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp dir=\"RTL\"\u003e\u003cstrong\u003e\u003cspan dir=\"LTR\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eUsually\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eRarely\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInterrupted sleep\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eUsually\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.036\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 710px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eA chi-square test was performed to assess the association between variables. Data are presented as numbers of participants. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e-value\u0026lt; 0.05.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"718\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 718px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Table 4:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe body mass index and selected dietary habits (Mean\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD), n=222\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Dietary habits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Options\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Body mass index (Mean\u0026plusmn;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of main meals per day\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eOne\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e26.02\u0026plusmn;5.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eTwo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.10\u0026plusmn;5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eThree\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e23.77\u0026plusmn;4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026gt; Three\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.52\u0026plusmn;4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 718px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCont.Table 4:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe body mass index and selected dietary habits (Mean\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD), n=222\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of snacks per day\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eOne\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.14\u0026plusmn;4.92\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eTwo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.27\u0026plusmn;5.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eThree\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e22.62\u0026plusmn;3.45\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026gt; Three\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.00\u0026plusmn;4.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eNone\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e28.45\u0026plusmn;5.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDining out\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eNever\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e26.01\u0026plusmn;5.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt; Once/month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e23.96\u0026plusmn;4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1-3/ month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e23.99\u0026plusmn;5.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e1-3/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.69\u0026plusmn;4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e4-6/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e23.25\u0026plusmn;3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eDaily\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.14\u0026plusmn;4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAppetite and craving for food when watching food advertisements\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e23.97\u0026plusmn;5.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.34\u0026plusmn;3.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eSometimes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e24.51\u0026plusmn;5.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e23.32\u0026plusmn;4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIf you think about health and body weight, did this stop you from ordering ready-to-eat food\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e25.28\u0026plusmn;5.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; 0.032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 266px;\"\u003e\n \u003cp\u003e23.70\u0026plusmn;4.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 718px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;An ANOVA test was performed to assess the association between BMI and dietary habits.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eData are presented as mean\u0026plusmn;SD.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eStatistical significance was set at \u003cem\u003ep\u003c/em\u003e-value\u0026lt; 0.05. The Least Significant Difference was used for post-hoc analysis, different superscript letters within the same variable indicate statistical significance.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA statistically significant association was observed between total physical activity (PA) MET and the time spent on social media (p=0.001). Specifically, participants who spent less than 1 hour on social media reported a significantly higher mean total PA MET (2250.00\u0026plusmn;2173.06a) compared to all other groups. Those spending 1-3 hours (660.66\u0026plusmn;1494.02b), 3\u0026ge;-5 hours (607.01\u0026plusmn;1213.75b), 5\u0026ge;-7 hours (379.04\u0026plusmn;762.12b), and \u0026ge;7 hours (374.59\u0026plusmn;1100.96b) on social media showed significantly lower and comparable levels of total PA MET.\u003c/p\u003e\n\u003cp\u003eIn contrast, no statistically significant differences were found across social media usage groups for weekday sleep times (p=0.153) or weekend sleep times (p=0.636). Similarly, water intake (p = 0.226) did not show a significant association with social media use, as presented in Supplementary Table 2.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional study among Jordanian adults provides novel evidence regarding the association between social media use and risk factors for cardiovascular diseases (CVDs); lifestyle and anthropometric factors. The mean age of participants was 21.39 ± 4.93 years, reflecting the predominance of young adults in social media engagement. Most participants were single (91%), consistent with previous findings that being single increases vulnerability to the influence of social media on eating behaviours. Ismail et al. (2024) reported a 3.2% greater effect of social media among singles [38].\u003c/p\u003e\n\u003cp\u003eA significant negative association was found between time spent on social media and physical activity (p = 0.027), aligning with Saudi Arabian research linking sedentary behavior to media use [39]. Conversely, other studies reported potential benefits of social media, such as peer encouragement and improved adherence to weight management interventions [40-44]. In our study, the highest prevalence of physical inactivity occurred among participants who used social media for 3–5 hours per day. Previous research has shown that using the internet or social media for more than four hours daily adversely affects physical activity, sleep, and overall health [45]. In line with this, our findings demonstrated that longer social media use was significantly associated with disturbed sleep (p = 0.036), supporting evidence that links social media to poor sleep quality, daytime sleepiness, and insomnia [46-48].\u003c/p\u003e\n\u003cp\u003eDietary outcomes were also affected. Social media use significantly influenced appetite and food cravings (p = 0.021), frequency of dining out (p = 0.00), and ordering ready-to-eat meals (p = 0.045), particularly when participants were exposed to food advertising. These findings correspond with previous studies demonstrating a positive relationship between social media exposure and altered eating habits [49-51]. Heavy users (\u0026gt;4 hours/day) have been reported to skip meals [52], while exposure to food-related content increased snacking among adolescents and adults [53]. Although our study found no significant association between social media and the total number of meals or snacks consumed, meal skipping and greater responsiveness to food marketing were most common among participants using social media 3–5 hours daily. This group was more likely to consume foods high in saturated fat, cholesterol, and sodium, thereby elevating CVD risk [54].\u003c/p\u003e\n\u003cp\u003eThe cue reactivity theory offers a possible explanation, suggesting that exposure to food marketing activates responses that shape eating behavior, food choices, and purchasing patterns across media platforms [55, 56]. Food advertisements may trigger brain activity in response to visual cues, thereby increasing snacking and predicting weight gain [57, 58]. Moreover, food-related posts linked to social contexts, such as dining out with friends, may further reinforce the influence of social media on food cravings [59]. Despite the high educational level of most participants (91.4% held a bachelor’s degree or higher), susceptibility to misleading content from influencers and companies was evident. This reliance on social media for food-related decisions contributes to emotional eating, disordered behaviors, obesity, and chronic disease [39, 60].\u003c/p\u003e\n\u003cp\u003eAs it was observed in our study, no significant effect of social media on BMI, body weight, or body composition. These findings are consistent with some prior studies [61–63], though others reported associations between screen time and higher BMI, waist circumference, waist-to-hip ratio, and body fat [64]. Interestingly, participants reporting no snacking had the highest BMI, which may reflect under-reporting, meal skipping with compensatory overeating, or reverse causality. While some participants with higher BMI avoided snacks as a weight-control strategy, other studies found that obese individuals were more likely to purchase food or beverages after viewing related advertisements [53].\u003c/p\u003e\n\u003cp\u003eParticipants spending 3–5 hours per day on social media also had the highest mean waist-to-hip ratio (WHR), exceeding the cut-off thresholds (\u0026gt;0.8 for females, \u0026gt;0.95 for males) [65], despite having a mean BMI within the normal range (23.96 ± 4.72). WHR is an established indicator of central obesity, which is associated with metabolic abnormalities and heightened CVD risk [66]. Moreover, previous research links excessive social media use (\u0026gt;3 hours/day) to mental health problems such as depression, stress, and anxiety [67]. These conditions in turn increase cardiometabolic risk factors, including hypertension, dyslipidemia, and diabetes, thereby mediating the relationship between mental health and CVDs [68]. Notably, studies suggest that restricting social media use to less than 30 minutes per day may improve overall health and well-being [67].\u003c/p\u003e\n\u003cp\u003eTo our knowledge, this is the first study in Jordan to evaluate the associations between social media use and multiple CVD risk factors, including anthropometric, dietary, and lifestyle variables, using validated questionnaires and more precise adiposity measures beyond BMI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main strengths of this study include its novelty within the Jordanian context and the use of validated instruments to capture social media’s influence on health-related behaviors. Nonetheless, several limitations must be acknowledged. The cross-sectional design precludes causal inference. Reliance on self-reported data may have introduced recall and social desirability bias, and web-based recruitment could contribute to selection bias. Females accounted for 75.2% of participants, which limits sex-stratified analyses and generalizability, as females are generally more affected by social media than males [39, 69].\u003c/p\u003e\n\u003cp\u003eAdditionally, the small sample size in the \u0026lt;1 hour/day group (n = 8) reduces estimate reliability, although it was retained to ensure comparability with previous research. Testing multiple outcomes increases the likelihood of type I error; thus, findings should be interpreted with caution. Physical activity may have acted as both a confounder and an outcome, which could not be fully disentangled. Other limitations include the absence of laboratory tests, blood pressure measurements, genetic predisposition, family history of CVDs, or specific dietary requirements. Attrition during study stages also limited the final sample for body composition analysis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, excessive social media use among Jordanian adults is associated with unhealthy dietary behaviors, meal skipping, reduced physical activity, and disturbed sleep, collectively increasing the risk of obesity and cardiovascular diseases. Despite no significant association with BMI, elevated waist-to-hip ratio and susceptibility to food marketing highlight critical public health concerns, underscoring the need for balanced media use and healthier lifestyle promotion.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors’ contribution:\u003c/strong\u003e Eman Alhasan and Maysoun Qutob contributed to the conceptualization, investigation, data gathering, methodology, writing the original draft, and supervision. Shatha Hammad analyzed the data and interpreted the results.\u0026nbsp;All authors have reviewed and approved the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e: The authors would like to thank Dr. Anfaal Dalaeen, the head of the Nutrition Department at the Allied Medical Science Faculty, Applied Science Private University, for their assistance in preparing the manuscript and support in accessing the participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e: The authors declare that they have competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate:\u003c/strong\u003e All participants were informed about the aims and procedures of the study, and informed consent was obtained through the electronic questionnaire. The FAMS Ethics Committee approved this study for ethical approval of research projects at the Allied Medical Science Faculty in the Applied Science Private University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEO Alhasan: Conceptualization, methodology, investigation, writing – original draft, supervision.\u003cbr\u003e\u0026nbsp;MS Qutob: Conceptualization, methodology, writing – review \u0026amp; editing, supervision.\u003cbr\u003e\u0026nbsp;SS Hammad: Data analysis, interpretation, writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient consent for publication: Not required as the study did not involve personal medical information about identifiable individuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData sharing statement: The technical appendix, statistical code, and anonymised dataset are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTripathi, M., et al., \u003cem\u003eEffect of social media on human health\u003c/em\u003e. Virology \u0026amp; Immunology Journal, 2018. 2(2): p. 1\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJane, M., et al., \u003cem\u003eSocial media for health promotion and weight management: a critical debate\u003c/em\u003e. BMC public health, 2018. 18: p. 1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChaffey, D. \u003cem\u003eGlobal social media statistics research summary May 2024\u003c/em\u003e. Digital marketing statistics 2024; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.smartinsights.com/social-media-marketing/social-media-strategy/new-global-social-media-research/\u003c/span\u003e\u003cspan address=\"https://www.smartinsights.com/social-media-marketing/social-media-strategy/new-global-social-media-research/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKEMP, S. \u003cem\u003eDigital 2024: Jordan\u003c/em\u003e. Global Digital Reports 2024; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://datareportal.com/reports/digital-2024-jordan\u003c/span\u003e\u003cspan address=\"https://datareportal.com/reports/digital-2024-jordan\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAli, S., et al., \u003cem\u003eThe burden of cardiovascular diseases in Ethiopia from 1990 to 2017: evidence from the Global Burden of Disease Study\u003c/em\u003e. International Health, 2021. 13(4): p. 318\u0026ndash;326.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharma, S. and M.J. Wood, \u003cem\u003eThe global burden of cardiovascular disease in women\u003c/em\u003e. Current Treatment Options in Cardiovascular Medicine, 2018. 20: p. 1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaptoge, S., et al., \u003cem\u003eWorld Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions\u003c/em\u003e. The Lancet global health, 2019. 7(10): p. e1332-e1345.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsao, C.W., et al., \u003cem\u003eHeart disease and stroke statistics\u0026mdash;2022 update: a report from the American Heart Association\u003c/em\u003e. Circulation, 2022. 145(8): p. e153-e639.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSawalha, K., et al., \u003cem\u003eProfiling Cardiometabolic health in Jordan: a call to action to improve cardiovascular health\u003c/em\u003e. Cureus, 2023. 15(5).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAl-Ajlouni, Y.A., et al., \u003cem\u003eThe burden of Cardiovascular diseases in Jordan: a longitudinal analysis from the global burden of disease study, 1990\u0026ndash;2019\u003c/em\u003e. BMC Public Health, 2024. 24(1): p. 879.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFoundation, B.H. \u003cem\u003eHealth Diseases\u003c/em\u003e. 2014 [cited 2021 11 February]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bhf.org.uk/old-starts-with-your-heart/heart-diseases\u003c/span\u003e\u003cspan address=\"https://www.bhf.org.uk/old-starts-with-your-heart/heart-diseases\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhot, U.N., et al., \u003cem\u003ePrevalence of conventional risk factors in patients with coronary heart disease\u003c/em\u003e. Jama, 2003. 290(7): p. 898\u0026ndash;904.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArena, R., et al., \u003cem\u003eApplying precision medicine to healthy living for the prevention and treatment of cardiovascular disease\u003c/em\u003e. Current problems in cardiology, 2018. 43(12): p. 448\u0026ndash;483.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHumphreys, S., \u003cem\u003eThe unethical use of BMI in contemporary general practice\u003c/em\u003e. British Journal of General Practice, 2010. 60(578): p. 696\u0026ndash;697.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eG\u0026oacute;mez-Ambrosi, J., et al., \u003cem\u003eBody mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity\u003c/em\u003e. International journal of obesity, 2012. 36(2): p. 286\u0026ndash;294.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Koning, L., et al., \u003cem\u003eWaist circumference and waist-to-hip ratio as predictors of cardiovascular events: meta-regression analysis of prospective studies\u003c/em\u003e. European heart journal, 2007. 28(7): p. 850\u0026ndash;856.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNeeland, I.J., et al., \u003cem\u003eBody fat distribution and incident cardiovascular disease in obese adults\u003c/em\u003e. Journal of the American College of Cardiology, 2015. 65(19): p. 2150\u0026ndash;2151.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePou, K.M., et al., \u003cem\u003eVisceral and subcutaneous adipose tissue volumes are cross-sectionally related to markers of inflammation and oxidative stress: the Framingham Heart Study\u003c/em\u003e. Circulation, 2007. 116(11): p. 1234\u0026ndash;1241.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHamdy, O., S. Porramatikul, and E. Al-Ozairi, \u003cem\u003eMetabolic obesity: the paradox between visceral and subcutaneous fat\u003c/em\u003e. Current diabetes reviews, 2006. 2(4): p. 367\u0026ndash;373.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbraham, T.M., et al., \u003cem\u003eAssociation between visceral and subcutaneous adipose depots and incident cardiovascular disease risk factors\u003c/em\u003e. Circulation, 2015. 132(17): p. 1639\u0026ndash;1647.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCernat, D., \u003cem\u003eHow social media influences our food consumption.\u003c/em\u003e 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Veirman, M., V. Cauberghe, and L. Hudders, \u003cem\u003eMarketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude\u003c/em\u003e. International journal of advertising, 2017. 36(5): p. 798\u0026ndash;828.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSacks, G. and E.S.Y. Looi, \u003cem\u003eThe advertising policies of major social media platforms overlook the imperative to restrict the exposure of children and adolescents to the promotion of unhealthy foods and beverages\u003c/em\u003e. International journal of environmental research and public health, 2020. 17(11): p. 4172.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrganization, W.H., \u003cem\u003eFood marketing exposure and power and their associations with food-related attitudes, beliefs and behaviours: a narrative review.\u003c/em\u003e 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGrilo, G., E. Crespi, and J.E. Cohen, \u003cem\u003eA scoping review on disparities in exposure to advertising for e-cigarettes and heated tobacco products and implications for advancing a health equity research agenda\u003c/em\u003e. International journal for equity in health, 2021. 20: p. 1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRossi, R., et al., \u003cem\u003e\u0026ldquo;Get a\u0026pound; 10 Free Bet Every Week!\u0026rdquo;\u0026mdash;gambling advertising on Twitter: volume, content, followers, engagement, and regulatory compliance\u003c/em\u003e. Journal of public policy \u0026amp; marketing, 2021. 40(4): p. 487\u0026ndash;504.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThomas, S.L., et al., \u003cem\u003eYoung people\u0026rsquo;s awareness of the timing and placement of gambling advertising on traditional and social media platforms: a study of 11\u0026ndash;16-year-olds in Australia.\u003c/em\u003e Harm reduction journal, 2018. 15: p. 1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarry, A.E., et al., \u003cem\u003eAlcohol advertising on social media: Examining the content of popular alcohol brands on Instagram\u003c/em\u003e. Substance use \u0026amp; misuse, 2018. 53(14): p. 2413\u0026ndash;2420.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMonitoring \u003cem\u003eand restricting digital marketing of unhealthy products to children and adolescents\u003c/em\u003e. Activities 2018; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/europe/activities/monitoring-and-restricting-digital-marketing-of-unhealthy-products-to-children-and-adolescents\u003c/span\u003e\u003cspan address=\"https://www.who.int/europe/activities/monitoring-and-restricting-digital-marketing-of-unhealthy-products-to-children-and-adolescents\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCoalition, O.P., \u003cem\u003eUnder the radar: harmful industries' digital marketing to Australian children.\u003c/em\u003e 2020.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakshine, V.S., et al., \u003cem\u003eIncreased screen time as a cause of declining physical, psychological health, and sleep patterns: a literary review\u003c/em\u003e. Cureus, 2022. 14(10).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark, Y.-M.M., et al., \u003cem\u003eAssociation of exposure to artificial light at night while sleeping with risk of obesity in women\u003c/em\u003e. JAMA internal medicine, 2019. 179(8): p. 1061\u0026ndash;1071.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eValenzuela, P.L., et al., \u003cem\u003eObesity and the risk of cardiometabolic diseases\u003c/em\u003e. Nature reviews cardiology, 2023. 20(7): p. 475\u0026ndash;494.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePourhoseingholi, M.A, Vahedi. M, Rahimzadeh M. \u003cem\u003eSample size calculation in medical studies\u003c/em\u003e.Gastroenterology and Hepatology From Bed to Bench, 2013. 6(1): p.14\u0026thinsp;\u0026ndash;\u0026thinsp;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWashburn, R.A., et al., \u003cem\u003eThe validity of the Stanford seven-day physical activity recall in young adults\u003c/em\u003e. Medicine \u0026amp; Science in Sports \u0026amp; Exercise, 2003. 35(8): p. 1374\u0026ndash;1380.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSallis, J.F., et al., \u003cem\u003ePhysical activity assessment methodology in the Five-City Project\u003c/em\u003e. American journal of epidemiology, 1985. 121(1): p. 91\u0026ndash;106.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCraig, C.L., et al., \u003cem\u003eInternational physical activity questionnaire: 12-country reliability and validity\u003c/em\u003e. Medicine \u0026amp; science in sports \u0026amp; exercise, 2003. 35(8): p. 1381\u0026ndash;1395.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIsmail, L.C., et al., \u003cem\u003eThe association of social media with dietary behaviors among adults in the United Arab Emirates\u003c/em\u003e. Heliyon, 2024. 10(15).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlwafi, H., et al., \u003cem\u003eThe impact of social media influencers on food consumption in Saudi Arabia, a cross-sectional web-based survey\u003c/em\u003e. Journal of Multidisciplinary Healthcare, 2022: p. 2129\u0026ndash;2139.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbioye, A.I., K. Hajifathalian, and G. Danaei, \u003cem\u003eDo mass media campaigns improve physical activity? a systematic review and meta-analysis\u003c/em\u003e. Archives of Public Health, 2013. 71: p. 1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHill, E., \u003cem\u003eCollege Student Social Media Use and its relation to health behaviors\u003c/em\u003e. 2013, The Ohio State University.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLaranjo, L., et al., \u003cem\u003eThe influence of social networking sites on health behavior change: a systematic review and meta-analysis\u003c/em\u003e. Journal of the American Medical Informatics Association, 2015. 22(1): p. 243\u0026ndash;256.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSanttila, M., et al., \u003cem\u003eImpact of a social media exercise service on individuals and employees\u003c/em\u003e. Biomedical human kinetics, 2016. 8(1): p. 65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKing, K.M. and G.B. Gonzalez, \u003cem\u003eIncreasing physical activity using an ecological model\u003c/em\u003e. ACSM's Health \u0026amp; Fitness Journal, 2018. 22(4): p. 29\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHudimova, A., et al., \u003cem\u003eResearch on the relationship between excessive use of social media and young athletes' physical activity\u003c/em\u003e. Journal of Physical Education and Sport, 2021. 21(6): p. 3364\u0026ndash;3373.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIlham, N.A., et al., \u003cem\u003eImpact of intense social media usage on sleeping pattern\u003c/em\u003e. Bulletin of Social Informatics Theory and Application, 2022. 6(2): p. 120\u0026ndash;131.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLissak, G., \u003cem\u003eAdverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study\u003c/em\u003e. Environmental research, 2018. 164: p. 149\u0026ndash;157.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCain, N. and M. Gradisar, \u003cem\u003eElectronic media use and sleep in school-aged children and adolescents: A review\u003c/em\u003e. Sleep medicine, 2010. 11(8): p. 735\u0026ndash;742.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlanchard, L., et al., \u003cem\u003eAssociations between social media, adolescent mental health, and diet: A systematic review\u003c/em\u003e. Obesity reviews, 2023. 24: p. e13631.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFilippone, L., R. Shankland, and Q. Hallez, \u003cem\u003eThe relationships between social media exposure, food craving, cognitive impulsivity and cognitive restraint\u003c/em\u003e. Journal of Eating Disorders, 2022. 10(1): p. 184.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHolland, G. and M. Tiggemann, \u003cem\u003eA systematic review of the impact of the use of social networking sites on body image and disordered eating outcomes\u003c/em\u003e. Body image, 2016. 17: p. 100\u0026ndash;110.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, J.H., et al., \u003cem\u003eBrief report: predictors of heavy Internet use and associations with health-promoting and health risk behaviors among Hong Kong university students\u003c/em\u003e. Journal of adolescence, 2010. 33(1): p. 215\u0026ndash;220.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAljefree, N.M. and G.T. Alhothali, \u003cem\u003eExposure to food marketing via social media and obesity among university students in Saudi Arabia\u003c/em\u003e. International journal of environmental research and public health, 2022. 19(10): p. 5851.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e(CDC), C.f.D.C.a.P. \u003cem\u003eHeart Disease Risk Factors\u003c/em\u003e. [cited 2024 December 2]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/heart-disease/risk-factors/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/heart-disease/risk-factors/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoswell, R.G. and H. Kober, \u003cem\u003eFood cue reactivity and craving predict eating and weight gain: a meta-analytic review\u003c/em\u003e. Obesity reviews, 2016. 17(2): p. 159\u0026ndash;177.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoyland, E., et al., \u003cem\u003eAssociations between everyday exposure to food marketing and hunger and food craving in adults: An ecological momentary assessment study\u003c/em\u003e. Appetite, 2024. 196: p. 107241.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLawrence, N.S., et al., \u003cem\u003eNucleus accumbens response to food cues predicts subsequent snack consumption in women and increased body mass index in those with reduced self-control\u003c/em\u003e. Neuroimage, 2012. 63(1): p. 415\u0026ndash;422.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYokum, S., J. Ng, and E. Stice, \u003cem\u003eAttentional bias to food images associated with elevated weight and future weight gain: an fMRI study\u003c/em\u003e. Obesity, 2011. 19(9): p. 1775\u0026ndash;1783.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQutteina, Y., et al., \u003cem\u003eWhat do adolescents see on social media? A diary study of food marketing images on social media\u003c/em\u003e. Frontiers in psychology, 2019. 10: p. 2637.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, J., et al., \u003cem\u003eThe relationship between SNS usage and disordered eating behaviors: A meta-analysis\u003c/em\u003e. Frontiers in Psychology, 2021. 12: p. 641919.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBiddle, S.J., E. Garc\u0026iacute;a Bengoechea, and G. Wiesner, \u003cem\u003eSedentary behaviour and adiposity in youth: a systematic review of reviews and analysis of causality\u003c/em\u003e. International Journal of Behavioral Nutrition and Physical Activity, 2017. 14: p. 1\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSampasa-Kanyinga, H., J.-P. Chaput, and H.A. Hamilton, \u003cem\u003eAssociations between the use of social networking sites and unhealthy eating behaviours and excess body weight in adolescents\u003c/em\u003e. British Journal of Nutrition, 2015. 114(11): p. 1941\u0026ndash;1947.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlley, S., et al., \u003cem\u003eImpact of increasing social media use on sitting time and body mass index\u003c/em\u003e. Health Promotion Journal of Australia, 2016. 28(2): p. 91\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSuchert, V., R. Hanewinkel, and B. Isensee, \u003cem\u003eScreen time, weight status and the self-concept of physical attractiveness in adolescents\u003c/em\u003e. Journal of adolescence, 2016. 48: p. 11\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCenter, B.C.H. \u003cem\u003eWaist/ Hip Ratio and Cardiac Disease Risk\u003c/em\u003e. 2016 [cited 2025 May 5]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bchealth.org/waist-hip-ratio-cardiac-disease-risk/\u003c/span\u003e\u003cspan address=\"https://bchealth.org/waist-hip-ratio-cardiac-disease-risk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAhmad, M.I., et al., \u003cem\u003eWaist to hip ratio modifies the cardiovascular risk of lipoprotein (a): Insights from MESA\u003c/em\u003e. Progress in Cardiovascular Diseases, 2025.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRiehm, K.E., et al., \u003cem\u003eAssociations between time spent using social media and internalizing and externalizing problems among US youth\u003c/em\u003e. JAMA psychiatry, 2019. 76(12): p. 1266\u0026ndash;1273.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCivieri, G., et al., \u003cem\u003eAnxiety and Depression Associated with Increased Cardiovascular Disease Risk Through Accelerated Development of Risk Factors\u003c/em\u003e. JACC: Advances, 2024. 3(9_Part_1): p. 101208.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilksch, S.M., et al., \u003cem\u003eThe relationship between social media use and disordered eating in young adolescents\u003c/em\u003e. International Journal of Eating Disorders, 2020. 53(1): p. 96\u0026ndash;106.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Social media, Cardiovascular Diseases, Risk Factors, Eating Habits, Food Marketing","lastPublishedDoi":"10.21203/rs.3.rs-7724259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7724259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCardiovascular diseases (CVDs) are a leading cause of mortality globally and in Jordan, with lifestyle factors such as physical inactivity, unhealthy diet, obesity, and smoking contributing substantially. Social media use has increased among young adults, raising concerns about its influence on lifestyle and exposure to food marketing.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e: A cross-sectional study was conducted among 222 participants (aged 18\u0026ndash;45 years) at the Applied Science Private University in Jordan. Data were collected via a validated online questionnaire on sociodemographic characteristics, lifestyle behaviors, dietary habits, and social media use. Anthropometric measures were obtained at the university clinic. Associations between social media use and outcomes were analyzed using chi-square tests and ANCOVA.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e: Most participants were female (75.2%) with a mean age of 21.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 years. Two-thirds spent 3\u0026ndash;6 hours daily on social media. Longer social media use was significantly associated with physical inactivity (p\u0026thinsp;=\u0026thinsp;0.027), interrupted sleep (p\u0026thinsp;=\u0026thinsp;0.036), and increased appetite and food cravings (p\u0026thinsp;=\u0026thinsp;0.021). Exposure to food advertisements was linked to more frequent dining out (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and ordering ready-to-eat foods (p\u0026thinsp;=\u0026thinsp;0.045). No significant association was found with BMI or body composition.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e: Intensive social media use among young adults is associated with adverse effects on certain lifestyle behaviors and unhealthy eating patterns, which may increase cardiovascular risk. These findings underscore the necessity of incorporating social media exposure into public health interventions and dietary counseling efforts.\u003c/p\u003e","manuscriptTitle":"Impact of Social Media Engagement and Food Marketing Exposure on Cardiovascular Risk Factors in Jordanian Adults: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 23:19:06","doi":"10.21203/rs.3.rs-7724259/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"81c24f67-99cd-4e03-930c-f5ffa4dbaff7","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55961805,"name":"Health sciences/Risk factors"},{"id":55961806,"name":"Scientific community and society/Scientific community"},{"id":55961807,"name":"Biological sciences/Computational biology and bioinformatics"}],"tags":[],"updatedAt":"2025-11-13T15:27:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 23:19:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7724259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7724259","identity":"rs-7724259","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}