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Social Networking Sites use, Lifestyle Index and Disordered Eating Behaviors During the Era of COVID 19: A Cross Sectional Study among Female Students of Taif University, Saudi Arabia

Journal of Research in Medical and Dental Science
eISSN No. 2347-2367 pISSN No. 2347-2545

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Research - (2022) Volume 10, Issue 6

Social Networking Sites use, Lifestyle Index and Disordered Eating Behaviors During the Era of COVID 19: A Cross Sectional Study among Female Students of Taif University, Saudi Arabia

Abdulaziz R Alotaibi1, Nermin A Osman2, Abdullah Muidh Alqethami3 and Nesrin Kamal Abd El-Fatah4*

*Correspondence: Nesrin Kamal Abd El-Fatah, Department of Nutrition, High Institute of Public Health, Alexandria University, Egypt, Email:

Author info »

Abstract

Background: Disordered Eating Behaviours (DEB) is a nutritional public health challenge because it may contribute to poor physical and mental health consequences among college students. More studies should be directed towards DEBs screening and exploring their associations for directing preventive efforts. Therefore, this study aimed to estimate the prevalence of DEBs among Saudi female university students and their relationships with SNSs usage and composite lifestyle behaviors during the COVID-19 unprecedented time. Methods: This cross-sectional study was conducted on 445 females recruited by stratified random sampling. Participants self-reported demographic, social, medical, and lifestyle data by completing the validated Arabic version of eating attitudes Test-26, Social Networking Sites Usage, Bergen Social Media Addiction Scale, and Body Shape Questionnaires. Results: The prevalence of disordered eating behaviors was estimated to be 27.2% among the female students in Taif University. There are significant higher SNSs navigation rate among the risky group (36.4%) from pre-pandemic stage to current time among compared to the normal group (20.4%) (X2=30.015, p=0.001). Regression analysis revealed that females with a marked body image concern, SNSs friendship, frequently visiting their SNSs sites, those social dependent information seeking were more prone to develop disordered eating behavior (Overall Model: Chi Square X2=158.071, p<0.000**). Conclusions: There is an association between social networking sites use and disordered eating behaviors during the period of COVID 19. Although, the composite lifestyle did not exert an obvious association with the eating disorder among the female students in Taif University.

Keywords

Social networking, Disordered eating, Female, Social media, COVID-19, Lifestyle behaviors, College, Saudi Arabia

Introduction

Disordered eating behaviors (DEBs) refer to troublesome eating habits, which are less severe in their behavioral manifestations than those required to meet the full criteria for the diagnosis of an eating disorder (ED) using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). It encompasses unhealthy eating habits that may include fasting, restrictive dieting, skipping meals, compulsive overeating, unbalanced eating, vomiting, and misuse of laxatives, diuretics, enemas, and use of diet pills to lose weight [1].

Problematic eating behaviors have been proven as risk factors for ED. Dieting and other obsessive weight control practices, fears of fatness and negative body image, intensive food, and weight preoccupation are forms of eating impairment with a great potential to facilitate the development of anorexia and bulimia nervosa [2]. Many studies confirmed that eating disorders make people more vulnerable to psychiatric illnesses, diabetes, weight fluctuations, poor nutritional intake and quality, obesity, suicide, and other forms of premature mortality. A systematic review of population-based studies published in 2019 concluded that dis-ordered eating decreased health-related quality of life among children and adolescents [3].

The latest global prevalence of eating disorders was 1.01% [4]. Although the prevalence of clinically diagnosed eating disorders seems low, disordered eating behaviors are very frequent among adolescents in college settings and young women [5]. In a recent systematic review and meta-analysis conducted on the Middle East (16 countries including Saudi Arabia) including only high-quality studies, the overall prevalence rate of DEBs was 22.07% appeared to be slightly higher than the global prevalence rate [6]. Previous studies by Abd El-Azeem AA, et al., Alwosaifer AM, et al., and Fatima W, et al. (2018) on female Saudi university students using EAT-26 test reported that 35.4%, 29.4 and 25.4% having disordered eating attitudes, respec-tively [7-9].

In a recent study conducted during the COVID pandemic (2022), 1004 females from a university in Saudi Arabia provided responses on the EAT-26 and about 31.5% of respondents were at risk of developing an ED [10]. Studies of DEBs associated factors focus mainly on socio- demographic (e.g., College-aged women), sociocultural factors (e.g., perceived pressure from family and peers), lifestyle factors, social media, concern about body image, society’s thin ideal, weight status as well as personality traits, psychological, genetics, and biology [11,12]. In addition, female university students with family stress to lose weight, overweight or obese, married, those with poor eating habits, having high levels of activity, and females studying in health science colleges reported having experienced DEBs [7-10]. Research on DEBs among Saudi university students is still limited.

Social Networking Sites (SNSs) are defined as web- based services that allow individuals to construct a public or semi-public profile and share connections with a certain list of other users. The SNSs have captured the interest of many adolescents and young adults and become a novel area of research interest. The existing rise of SNSs use, like Facebook, Twitter, and Instagram, provides various prospects for the promotion of beauty ideals, social comparisons, drive for thinness, among female college students [13]. In the last years, due to rapid sociocultural changes Western influences, and SNSs use, the Arab population’s desire to be thin has started to be more popular [12]. A recently published meta-analysis found a positive correlation between the use of SNSs and disordered eating behaviors, however, some discrepancies have been found that there is no connection between both [14,15]. During the critical time of the coronavirus disease 2019 (COVID-19) pandemic and the resulting mandated social isolation measures, a lot of research concluded that there was a great impact on population mental health, lifestyle behaviors, and increase utilization of SNSs for socialization and keeping up with local and global event. According to the internet world stats released in 2021, 90.1% of Saudi Arabia population uses the internet. Research from Global Web Index indicates that time spent on social media has increased in Saudi Arabia between 2017 and 2021 and users spend 25 percent more time on social media over the past four years. Saudi spent an average of 196 minutes a day on social media in 2021 with an increase of 10 minutes over 2019 [16].

Given the potential for DEBs to develop into an eating disorder with serious consequences. Therefore, Exploring DEBs magnitude and their associations is crucial, so that preventive measures could be contem- plated. To date, this is the first study that determines the magnitude of DEBs among Saudi female college students during the COVID-19 pandemic era and assesses their relationships with students’ lifestyle behaviors and SNSs use. In addition, clustering of unhealthy lifestyle behaviors has synergistic and more detrimental effect on health than would be anticipated from the individual effects of health behaviors [17]. Accordingly, the aim of this study was to determine the prevalence of DEBs among Saudi female university students, as well as their relationships with SNSs usage, composite lifestyle behaviors, and self-perception of body image during the unprecedented COVID-19 time.

Materials and Methods

Design and study population

A cross-sectional study was carried out on female students at the University of Taif, Saudi Arabia, be-tween January 17th and 30th 2022. Four out of 13 faculties of Taif University were selected, targeting students in all grade levels during the academic year 2021–2022. Using EPI-INFO 2002 software, a minimum required sample of 351 samples was determined, based on a prevalence rate of 35.4% disordered eating behaviors among female student using EAT26 tool with a precision of 3%, confidence level of 95% and an error of 0.05. A multistage stratified random sampling technique was used; stratification was based on the type of faculty (practical vs. theoretical) and the grade level. The predetermined sample was proportionally allocated on the selected faculties: the faculty of Medicine (45 students), the Faculty of Engineering (24 students), the Faculty of Literature (152 students), and the Faculty of Sharia and Regulation (224 students). In subsequent stages, the allocated sample for each faculty was allocated equally on all grades. Thus, the total number of females in-cluded in this study was 445. Pregnant Students and who affiliated to university branches outside Taif city were excluded. It is noteworthy to mention that the response rate was almost 100%. The research received institutional ethical approval. A written consent was taken from all the participants before they answered the questions and confidentiality was assured. Research was conducted in accordance with the Declaration of Helsinki.

Measures

Female students self-reported their demographic, medical, lifestyle, weight and height information and completed validated questionnaires about disordered eating behaviors (Eating attitudes Test (EAT-26) [18], Social Networking Sites (SNSs) Usage Questionnaire [19], Bergen Social Media Addiction Scale (BSMAS) [20], and Body Shape Questionnaire [21].

Eating attitudes test: EAT-26

The EAT-26 is a worldwide used screening tool used to spot individuals who present attitudes associated with abnormal eating behavior or risk for developing eating disorders. It has been established as a reliable and valid instrument in Arabic (Cronbach’s α=0•89) [22]. Additionally, the Arabic version of EAT-26 was validated among female students in Saudi Arabia [23], And it was used among adolescents aged between 12 and 18 years and women in some Arab countries such as Egypt, Jordan, Lebanon, Saudi Arabia, Oman, and the United Arab Emirates. Eat-26 comprises of twenty-six questions each with six response options, varying from infrequently/almost never/ never (0) to always (3). The scale contains three subscales, Dieting and Bulimia/Food Preoccupation and oral control. It also includes four additional behavior questions that assess self-reported binge eating, self-induce vomiting, use of laxatives or diuretics and treatment of an eating dis-order. Females scored 20 or more or answered affirmatively to any of the behavioral questions are classified as being at risk of disordered eating and higher scores indicate greater disordered eating behaviors [18].

Social networking sites (snss) usage questionnaire

A valid self-report questionnaire was used [19]. It included featured and affective SNSs usage. The featured subscale included 13-items assessing basic (questions on the frequency of use, the average extent of time of use, and the number of friends), interactive (frequency of sending messages, updating status, sharing or resending profiles, visiting a friend’s homepage, and commenting on others’ photos and comments), and Self-display usage ( writing notes/ blogs, updating profile image, and posting photos) on a 7-point scale (1=never, 7=multiple times a day). In affective SNSs usage items Participants rate the frequency of experiencing eight negative and positive emotions whilst using SNSs. All items are rated using a 0–7 scale where higher scores indicate higher usage or frequency of emotions. The measure has been validated with young adults with good internal consistency (α=0.82). Three questions were added to explore exposure type and duration of social networks including, no (0) or yes (1) responses to the following question “Please indicate which of the following accounts you have?” (Twitter, Snap Chat, Facebook, YouTube, WhatsApp and Instagram); in context of the most used SNS sites in Saudi Arabia, what social networking site do you use the most? And ‘since when did you create your first account on social networking sites?

Some questions related to SNSs usage to fulfill specific gratifications related to weight loss/dieting, fitness/ exercise, cooking, fashion, bariatric surgeries were added. These were adapted from N. Park and col- leagues (2009) and Lee HR el al. (2014). They included three types for SNSs use: information seeking (e.g., ‘‘I visit SNSs to gather information about weight loss/ dieting, cooking, fashion, bariatric surgery and fit-ness/ exercise, with a dichotomous (i.e., yes or no) response for each.), self-status seeking (e.g. ‘In the past three months, I posted messages on my own SNS with the intent to express my ideas and opinions about weight loss/dieting, fitness/exercise, cooking, fashion, bariatric surgeries, with a dichotomous (i.e., yes or no) response for each), and socializing use (e.g. On average, how many messages or comments do you post on others’ postings with a desire to interact with another individual about weight loss/dieting, fitness/exercise, cooking, fashion, bariatric surgeries? with six responses varying from never (0) to many times per day (7) [24]. Questions frequencies for each type for SNSs use were summed to obtain each participant’s general tendency to use SNSs for Information seeking, self-status seeking, and socializing use. In addition, the participants answer a question related to why they use SNSs in relation to weight loss/dieting, fitness/exercise, cooking, fashion, bariatric surgeries by checking the appropriate response. Responses range from very rarely (1) to very often (5) and its score ranges from 11 to 55. Higher scores indicate higher motive to use social related to weight loss/dieting, fitness/exercise, and body appearance [24,25].

Social networking sites dependence

The SNSs Dependence was assessed by Bergen Social Media Addiction Scale (BSMAS) for university students. It is a valid and reliable questionnaire to assess the use of social media activities more generally rather than on one specific platform [20] The scale consists of six items that indicate addiction criteria, such as withdrawal, salience, mood modification, conflict, tolerance, and relapse. Items are assessed by a five-point scale ranges from strongly Disagree (1) to strongly agree (5) and their score ranging from 11 to 55. A score of 24 was set as a clinical cut-off point, based on the gold standard of clinical diagnosis.

Body shape questionnaire (BSQ-8)

The BSQ-8 is an 8-item with six response options on a Likert scale ranging from never=1 to always=6 [21]. It showed adequate reliability among females as evaluated by Cronbach’s alpha (α=0.91) to evaluate body image problems such as fears of weight gain, desires for weight loss, body shape concern, and low self-esteem due to one’s physical appearance was used to assess body shape concerns. Item responses were summed. Scores less than 19 indicate no concern with shape, between 19 to 25 indicate mild concern with shape, and between 26 to 33 indicate moderate concern with shape and over 33 indicate marked concern with shape [26].

Adoption and validation procedures

According to Guidelines of Beaton et al. (2000), forward translation was initially performed by two na-tive Arabic language bilingual translators, who are fluent in English. A backward translation was then per-formed by two native English speaker translators, fluent in Arabic and unfamiliar with the concepts of the scales. The back-translated English questionnaire was subsequently compared with the original English one, then inconsistencies between the two versions were solved, to assure that the translation did not affect the validity of the questionnaire. Additionally, the validity and reliability of the final drafts were tested on 50 students. In the current study, the overall reliability of the Arabic version of EAT-26 was Cronbach’s α=0.86. Meanwhile, (SNSs) Usage Questionnaire demonstrated good reliability Cronbach’s alpha=0.78 for featured use, α=0.80 for affective; α=0.85 for dependence scale.

Content validity was assessed to ensure the necessity of each item in the collected pilot using qualitative and quantitative methods by five expert panel of a psychologist, two statisticians, nutritionist, and Public health specialist. For qualitative evaluation, we submitted just Arabic translation without substitution. For quantitative measuring of content validity, Content Validity Index (CVI) and Content Validity Ratio (CVR) were calculated to the scales holistically. CVI [0.90; ranged (0.86-1)] and CVR [0.85; ranged (0.80-1)] showed satisfactory results.

Composite lifestyle index (CLI)

Five lifestyle behaviors were selected for inclusion in this study (i.e., physical activity, sleep, sitting, smoking, BMI and dietary habits). The first four lifestyle behaviors assessment and their index value or risk category calculation protocol were reported in a previous study [27]. Adapted from Alkhaldy AA et al, 14 food items were used to develop a diet risk category, based on the Saudi Food-based Dietary Guidelines [28]. Participants reported on how servings per day they had vegetables and fruits and 3 servings daily was assigned as optimal. The remaining 12 food items assessed on weekly frequency of consuming full-fat dairy products; non- refined cereals and bread; legumes, nuts; fish and seafood; red meat and other meat products; poultry; butter or margarine; fast foods; sweets; potato chips or French fries; sugar sweetened drinks/soft drinks; and energy drinks. Five options for the eating frequency were established: “daily;” “5–6 times a week;” “3–4 times a week;” “1-2 time a week,” and “never or rarely. The responses ranged from 0 to 4 (for food items recom- mended in the Saudi dietary guidelines) or the reverse (for food items should be limited in the Saudi dietary guidelines). the total scores ranged from 0 to 56. The total score was subsequently classified into three tertiles by the following equation (first tertile=Lower limit (11) + 0.33 * 32=21.56, Second tertile=Lower limit (11) + 0.66 * 32=32.12). A score of one was generated for those below 21.56 (first level tertile or poor diet) and from 21.56 to less than 32.12 (second level tertile or average diet); a score of zero for those Above 32.12 (Third level tertile or better diet). These tertiles were then subsequently classified into lower-risk (0=Third tertile) and high risk (1=First and Second tertile) consistent with previous research (29). Sleep, sitting, and smoking behaviors were dichotomized into healthy (low risk) and unhealthy (high risk) categories and scored 1 and 0, respectively, while Physical activity was scored into 0 (high PA), 1 (Moderate PA) and 2 (high PA). Finally, BMI was calculated and categorized then was scored into 1 (Underweight/overweight/obese) and zero (normal BMI). Summing the scores of the five behaviors was done.

Statistical analysis

Statistical analyses were performed using IBM (SPSS) Statistics Version 24.0* software programs. The descriptive statistics, including frequencies and percentages, were used for categorical variables; median and range were used for continuous variables after determining the normality using Shapiro test. The rate of healthy and unhealthy dichotomies was calculated for each lifestyle behavior and the rate of the sample engaging in one to seven unhealthy lifestyle behaviors were also calculated. Body Mass Index (kg/ m2) was computed based on the given weight and height and classified according to WHO guidelines. The overall reliability of the Arabic version of EAT-26 was assessed in which Cronbach’s α=0.825. Meanwhile, (SNSs) Usage Questionnaire demonstrated good reliability with Cronbach’s alpha=0.813 for featured use, α=0.755 for affective use; and α=0.815 for dependence scale.

Chi- square test was used to compare between the eating disorder categories and Monte Carlo Exact test was used instead in case of violation of chi square assumption. Spearman Rho correlation coefficients were determined to test the association between the continuous variables and Mann Whitney U test was submitted to test the difference in the motivation score between those with normal eating disorder and those at risk. Logistic regression model for the eating disorder variable (dummy variable) were conducted to determine the significant contributors. For all statistical tests, a significance level was determined below 5% and quoted as two-tailed hypothesis tests.

Results

A total of 445 university female students was involved in the study and classified according to the EAT-26 cutoff value into normal group [n=324, 72.8%] and DEBs or risky group [n=121, 27.2%]. Around half of them were affiliated to College of Sharia and Regulations (50.3%) and the rest were affiliated to faculty of literature (34.2%), faculty of medicine (10.1%), and faculty of engineering (5.4%). The majority were single, living with their families, and not working outside the study time reporting a median age of 21 years. The socioeconomic status did not exert a significant difference between the normal and risky group. For the medical status, risky group showed a significant higher rate of psychological illnesses, regular medication intake, and familial history of obesity than the normal group [Proportional Differences=8.1%, 7.2%, and 14.5%, respectively, p value<0.05] as shown in Table 1.

  Total EAT – 26 Statistical test p
Normal At Risk
N=445 (n =324 ,72.8%) (n=121, 27.2%)
Faculty
Faculty of Medicine 45 (10.1%) 36 (11.1%) 9 (7.4%) 2.254 0.521 a
Faculty of literature 152 (34.2%) 111(34.3%) 41(33.9%)
Faculty of Engineering 24 (5.4%) 19 (5.9%) 5 (4.1%)
College of Sharia and Regulations 224 (50.3%) 158 (48.7%) 66 (54.6%)
Age (years)
<19 years 111(24.9%) 84(25.9%) 27(22.3%) 1.928 0.381 a
19-21 140(31.5%) 96(29.6%) 44(36.4%)
22 and more 194(43.6%) 144(44.5%) 50(41.3%)
Age Median (Range) 21(17-30) 21(17-30) 21(17-27) -0.318 0.751c
Marital Status
Single 396(89.0%) 286(88.3%) 110(90.9%) 1.836 0.593 b
Married (Non-Pregnant) 34(7.6%) 27(8.4%) 7(5.8%)
Married (Pregnant) 8(1.8%) 5(1.6%) 3(2.5%)
Divorced 7(1.6%) 6(1.7%) 1(0.8%)
Residence
Living with my family 424(95.3%) 309(95.4%) 115(95.0%) 1.681 0.62 b
Living with foreign 7(1.6%) 6(1.8%) 1(0.8%)
Living alone in a private home 10(2.2%) 7(2.2%) 3(2.5%)
Living with relatives or friends 4(0.9%) 2(0.6%) 2(1.7%)
Working outside the study time?
No 397(89.2%) 290(89.5%) 107(88.4%) 1.561 0.514 b
Yes, Partial Time 28(6.3%) 18(5.6%) 10(8.3%)
Yes, Full time 20(4.5%) 16(4.9%) 4(3.3%)
Father Work
Not working 24(5.4%) 20(6.2%) 4(3.3%) 4.589 0.309 b
Governmental Sector Employer 159(35.7%) 109(33.6%) 50(41.3%)
Free Lancer 45(10.2%) 34(10.5%) 11(9.1%)
Private Sector Employer 21(4.7%) 17(5.2%) 4(3.3%)
Retired 183(41.1%) 133(41.0%) 50(41.3%)
Died 13(2.9%) 11(3.5%) 2(1.7%)
Mother Work
Housewife 293(65.8%) 216(66.7%) 77(63.6%) 3.747 0.125 b
Governmental Sector Employer 119(26.7%) 88(27.2%) 31(25.6%)
Student 13(2.9%) 7(2.2%) 6(5.0%)
Private Sector Employer 16(3.7%) 11(3.4%) 5(4.2%)
Died 4(0.9%) 2(0.5%) 2(1.6%)
Father Education
Illiterate 16(3.6%) 10(3.1%) 6(5.0%) 4.003 0.678 b
Primary 50(11.2%) 36(11.1%) 14(11.4%)
Preparatory 62(13.9% 50(15.4%) 12(10.0%)
Secondary 123(27.6%) 91(28.1%) 32(26.4%)
Diploma 19(4.3%) 12(3.7%) 7(5.8%)
University 138(31.0%) 98(30.2%) 40(33.0%)
Higher Education 37(8.4%) 27(8.4%) 10(8.4%)
Mother Education
Illiterate 64(14.4%) 46(14.2%) 18(14.9%) 8.973 0.173 b
Primary 79(17.8%) 60(18.5%) 19(15.7%)
Preparatory 37(8.3%) 31(9.6%) 6(5.0%)
Secondary 88(19.8%) 60(18.5%) 28(23.1%)
Diplome 16(3.6%) 14(4.3%) 2(1.6%)
University 136(30.6%) 99(30.6%) 37(30.6%)
Higher Education 25 (5.5%) 14(4.3%) 11(9.1%)
Family Income
5000 or less 116(26.1%) 89(27.5%) 27(22.3%) 1.735 0.773 a
5001-10,000 125(28.1%) 91(28.1%) 34(28.1%)
10,001-15,000 91(20.4%) 66(20.4%) 25(20.7%)
15,001-20,000 56(12.6%) 38(11.7%) 18(14.9%)
20,001 or more 57(12.8%) 40(12.3%) 17(14.0%)
Social Status for mother and father
Divorced 28(6.3%) 20(6.2%) 8(6.6%) 6.672 0.074 b
Together 380(85.4%) 276(85.2%) 104(85.9%)
Both Died 6(1.3%) 2(0.6%) 4(3.3%)
Father Died 31(7%) 26(8.0%) 5(4.2%)
Psychological Disease history 51(11.5%) 30(9.3%) 21(17.4%) 5.849 0.016* a
Regular medication intake 43(9.7%) 25(7.7%) 18(14.9%) 5.17 0.023*a
Family History of Obesity 122(27.4%) 76(23.5%) 46(38.0%) 9.358 0.002*a
Family History of psychological disorders 31(7.0%) 20(6.2%) 11(9.1%) 1.157 0.228a
Have you ever been infected with COVID (with confirmed Positivity) 154(34.6%) 120(37.0%) 34(28.1%) 3.11 0.07a
Family and peer Support concerning Body weight 295(66.3%) 214(66.0%) 81(66.9%) 0.031 0.85a
a: Chi-square test, b: Monte-Carlo corrected p-value, c: Mann Whitney U test, * p-value<0.05

Table 1: Sociodemographic characteristics among female university students, classified according to EAT-26.

Table 2 illustrates the lifestyle characteristics and body image concern among the female students. The majority (74.8%) showed low level of physical activity, although the risky group showed a lower rate of low physical activity and a greater rate of high physical activity compared to the normal group [Proportional Differences=7.5%, and 7.3%, respectively, p value =0.018]. Half of the students were normo-weight, however the probability of being overweight and obese is quite high in the risky group (p =0.008). Hence, there is an observed body image marked concern among the risky group (37.2%). The normal group exerted a higher rate of non and mild body image concern and lower rate of moderate body image concern compared to the risky group [Proportional Differences=15.6%, 2.9%, and 3.2%, respectively, p value =0.001]. There is no statistically significant difference between the eating disorder categories regarding the smoking habits, dietary habits, sleeping habits and the overall composite lifestyle score (p > 0.05).

  Total EAT – 26 Statistical test p
Normal At Risk
N=445 (n =324 ,72.8%) (n=121, 27.2%)
Level of physical activity
Low 333(74.8%) 249(76.9%) 84(69.4%) 8.01 0.018*
Moderate 84(18.9%) 61(18.8%) 23(19%)
High 28(6.3%) 14(4.3%) 14(11.6%)
Sitting time
Meeting recommendations 386(86.7%) 282(63.4%) 104(23.4%) 0.09 0.764
Sleeping
Meeting recommendations 79(17.8%) 56(17.3%) 23(19.0%) 0.179 0.672
BMI (kg/m2)
Underweight 86(19.6%) 72(22.4%) 14(12%) 11.767 0.008*
Overweight 87(19.8%) 56(17.4%) 31(26.5%)
Obese 32(7.3%) 19(5.9%) 13(11.1%)
Smoking
Non-smoking or Ex-smoker 18 (4.0%) 11(3.4%) 7(5.8%) 1.297 0.255
Smoker 427(96.0%) 313(96.6%) 114(94.2%)
Optimal fruit intake per day 282(63.4%) 198(61.1%) 84(69.4%) 2.621 0.105
Optimal Vegetables intake /day 418(93.6%) 303(93.5%) 115(95%) 0.358 0.549
Optimal Fast-food intake (Never/rarely) 44(9.9%) 29(9%) 15(12.4%) 1.174 0.279
Sweets (Never/rarely) 22(4.9%) 16(4.9%) 6(5%) 0.001 0.993
Energy drinks 59(13.3%) 44(13.6%) 15(12.4%) 0.107 0.743
French fries 73(16.4%) 57(17.6%) 16(13.2%) 1.227 0.268
Diet risk category
Lowest tertile (Poorer diet) 78 (17.5%) 62 (19.1%) 16 (13.2%) 2.3 0.317
Middle tertile (Average diet) 321 (72.1%) 228 (70.4%) 93 (76.9%)
Highest tertile (better diet) 46 (10.4%) 34 (10.5%) 12 (9.9%)
Composite lifestyle Score
1 – 2 Unhealthy Behavior 20 (4.5%) 12 (3.7%) 8 (6.6%) 2.22 0.333
3 – 4 Unhealthy Behaviors 256 (57.5%) 191(59.0%) 65 (53.7%)
5 – 7 Unhealthy Behaviors 169 (38.0%) 121(37.3%) 48 (39.7%)
Body image concern
Mild concern 138 (31.0%) 103(31.8%) 35(28.9%) 15.822 0.001*
Moderate Concern 19 (4.3%) 11(3.4%) 8(6.6%)
Marked concern 116(26.1%) 71(21.9%) 45(37.2%)
p-value<0.05 was considered significant using chi-square test

Table 2: Lifestyle characteristics and body image concern among female university students, classified according to EAT-26.

Table 3 illustrates the detailed social networking sites use among the female students. All the studied students had a SNS account that was created by most of them (62%) 7 years ago or more. Snapchat was the most commonly used application with 367 (82.5%) users, followed by YouTube with 315 (70.8%) users and TikTok with 308 (69.2%) users. When we asked them to rank the frequency of social media use, Snapchat came first (27.3%), then Tiktok (21.6%), followed by Instagram (17.8%). There is no difference exerted between the eating disorder categories for the number of years and the preference of social network sites usage. Moreover, two thirds (68%) of them extremely visited SNSs (frequency of use that is once or more an hour), and nearly 40% of them spent from 30 minutes to 3 hours in each access and 30% of students spent more than 3 hours. For the featured usage, the risky group showed a higher frequency rate of account checking, duration of using, and number of friends on the different SNSs compared to the normal group (p<0.05). For the affective usage, the unhappiness is significantly linked with the risky eating disorder (p =0.007). For the addictive usage, there is no statistical difference between the eating disorder categories. However, the median motivation score to use SNSs in relation to weight loss/dieting, fitness/exercise, cooking, fashion, bariatric surgeries is highly significant among the risky group (p<0.001). In addition, there is a significant difference in the SNSs navigation rate from pre-pandemic stage to current time among the risky group compared to the normal group [Proportional Differences in the high use, and less use=16%, 13.1%, respectively, p value=0.001]. The details of the affective, featured use and addiction of the SNSs were displayed in supplementary file [S1].

  Total EAT – 26 [n.199] Statistical test p
Normal At Risk
N=445 (n =324, 72.8%) (n=121, 27.2%)
Instagram Use 201(45.2%) 143(44.1%) 58(47.9%) 0.379 0.538 a
Twitter Use 125(28.1%) 90(27.8%) 35(28.9%) 0.012 0.913 a
WhatsApp Use 40(9%) 27(8.3%) 13(10.7%) 3.535 0.06 a
Facebook Use 18(4%) 15(4.6%) 3(2.5%) 0.107 0.734 a
Snapchat Use 367(82.5%) 273(84.3%) 94(77.7%) 2.63 0.105 a
YouTube Use 315(70.8%) 222(68.5%) 93(76.8%) 2.964 0.085 a
LinkedIn Use 21(4.7%) 15(4.6%) 6(4.9%) 0.021 0.884 a
TikTok Use 308(69.2%) 226(69.8%) 82(67.8%) 0.163 0.678 a
Telegram Use 36(8.1%) 25(7.7%) 11(9.1%) 0.224 0.636 a
What social networking site do you use the most?
Instagram 79(17.8%) 53(16.4%) 26(21.5%) 9.934 0.270 b
WhatsApp 50 (11.3%) 39(12.1%) 11(9.1%)
Facebook 11(2.5%) 10(3.1%) 1(0.8%)
TikTok 96(21.6%) 72(22.2%) 24(19.8%)
You tube 42(9.5%) 30(9.3%) 12(10.0%)
Twitter 43(9.7%) 30(9.3%) 13(10.7%)
Snapchat 123(27.3%) 90(27.3%) 33(27.3%)
Telegram 1(0.3%) 0(0.0%) 1(0.8%)
Holding SNS account (year)
Less than two years 34 (7.6%) 23(7.1%) 11(9.1%) 5.303 0.258a
More than 10 years 104(23.4%) 73(22.5%) 31(25.6%)
Featured Usage: 1- Basic SNSs usage factor
SNS account check (times)
Never 10(2.2%) 5(1.5%) 5(4.1%) 14.942 0.034*b
Extreme use (once or more an hour) 303(68.1%) 217(67.0%) 86(71.0%)
Duration of using SNSs
15min or less 39(8.8%) 31(9.6%) 8(6.6%) 17.257 0.008*b
More than 4h 138(31.0%) 86(26.6%) 52(42.9%)
Number of friends
1 -<50 285(64%) 222(68.5%) 63(52.1%) 19.868 0.003*b
More than 500 23(5.2%) 15(4.8%) 8(6.6%)
Featured Usage: 2- Interaction usage
Sending private message
Never 61(13.7%) 44(13.6%) 17(14.0%) 4.98 0.551 b
Multiple times a day 122(27.4%) 92(28.3%) 30(24.9%)
Updating status
Never 126(28.3%) 90(27.8%) 36(29.7%) 12.601 0.051 b
Multiple times a day 16(3.6%) 11(3.4%) 5(4.1%)
Visiting profiles          
Never 91(20.4%) 70(21.6%) 21(17.4%) 7.282 0.07 b
Multiple times a day 22(4.9%) 16(4.9%) 6(4.9%)
Comment on others’ notes or photos
Never 102(22.9%) 75(23.1%) 27(22.4%) 12.223 0.057 a
Multiple times a day 26(5.8%) 17(5.3%) 9(7.4%)
Sharing or re-send others’ profiles          
Never 106(23.8%) 82(25.3%) 24(19.8%) 9.415 0.152 a
Multiple times a day 38(8.6%) 24(7.4%) 14(11.6%)
Checking others’ comments or message on your profiles
Never 156(35.1%) 117(36.1%) 39(32.2%) 4.466 0.614 a
Multiple times a day 36(8.1%) 21(6.3%) 15(12.4%)
Featured Usage: 3- Display usage
Writing notes/blogs          
Never 122(27.4%) 90(27.8%) 32(26.4%) 7.007 0.319 b
Multiple times a day 15(3.4%) 12(3.7%) 3(2.6%)
Posting photos
Never 167(37.5%) 127(39.2%) 40(33.0%) 8.676 0.188 b
Multiple times a day 10(2.2%) 6(1.9%) 4(3.4%)
Updating profile image
Never 104(23.4%) 68(21.0%) 36(29.7%) 11.597 0.072 b
Multiple times a day 6(1.3%) 2(0.6%) 4(3.3%)
Affective use when using SNSs: Unhappiness          
Never 64(14.4%) 45(13.9%) 19(15.7%) 17.661 0.007*b
Always 17(3.8%) 8(2.5%) 9(7.4%)
Happiness          
Never 30(6.7%) 17(5.2%) 13(10.7%) 19.899 0.092 a
Always 45(10.2%) 33(10.2%) 12(9.9%)
Depression          
Never 119(26.7%) 91(28.1%) 28(23.1%) 8.331 0.216 b
Always 15(3.4%) 11(3.4%) 4(3.3%)
Joy          
Never 33(7.4%) 19(5.9%) 14(11.6%) 7.723 0592 a
Always 47(10.6%) 32(9.9%) 15(12.5%)
Angry
Never 80(18.0%) 61(18.8%) 19(15.7%) 10.513 0.102 b
Always 16(3.6%) 9(2.9%) 7(5.9%)
Contentment
Never 31(7.0%) 19(5.8%) 12(9.9%) 7.324 0.292 a
Always 50(11.2%) 35(10.9%) 15(12.4%)
Anxiety
Never 101(22.7%) 81(25.0%) 20(16.5%) 7.53 0.224 b
Always 18(4.1%) 12(3.7%) 6(5.0%)
Cheer
Never 64(14.4%) 41(12.6%) 23(19.0%) 4.372 0.626 a
Always 41(9.2%) 30(9.4%) 11(9.2%)
Addiction of SNSs
Non-Disordered users 355(79.8%) 258(79.6%) 97(80.2%) 0.16 0.900 a
Disordered users (SMD) 90(20.2%) 66(20.4%) 24(19.8%)
Motivation Score 35 34 37
Median (Range) (14 – 53) (14 – 53) (20 – 53) 13238 0.000 c
SNSs use change from pre-pandemic stage to current time
Yes, I navigate it less than before 112 (25.2%) 70 (21.6%) 42 (34.7%) 30.015 0.001a
No change 223 (50.1%) 188 (58.0%) 35 (28.9%)
Yes, I navigate it more than before 110 (24.7%) 66 (20.4%) 44 (36.4%)
a : Chi-square test , b : Monte-Carlo corrected p-value, c : Mann Whitney U test , * p-value <0.05

Table 3: Social network sites use (type, featured usage, affective use, SMD social media disorder and motive of SNSs use) among female university students, classified according to EAT-26.

Spearman’s Rank correlation depicted significant bivariate association between the disordered eating behaviors score and the other scores, except for the dependence score. Basic, interactive, Self-display and feature SNSs usage as a whole showed mild positive correlation with the EAT-26 score [p value=0.004, 0.034, 0.029, and 0.026, respectively]. There were strong positive association between the basic, interactive, self-display and feature SNSs use independently. Participant’s general tendency to use SNSs for Information seeking, self-status seeking, and socializing use to fulfill specific gratifications related to weight loss/dieting, fitness/ exercise, cooking, fashion, bariatric surgeries showed significant positive correlation with the EAT-26 score [p value<0.001]. Similarly, Motivation score showed significant positive correlation with the EAT-26 score [rs=0.220, p value<0.001]. Unlikely, the positive affective SNSs use showed significant positive correlation with the DEBs score [rs=0.187, p value<0.001]. Likewise, the negative affective SNSs use showed significant negative correlation with the EAT-26 score [rs=-0.115, p value =0.015] as shown in Table 4.

    EAT 26 Score Basic use Interactive use Self-display use Featured use Positive Affective use Negative Affective Dependence score Motivation score Total MET Minutes Per Week SNSs Information Seeking use   SNSs Self- status Seeking use SNSs Socialization use
EAT 26 Score rs 1 .135** .196* .178* .106* .187** -.115* -0.017 .220** .123**   .178** .173** .265**
p . 0.004 0.034 0.029 0.026 0 0.015 0.716 0 0.009   0 0 0
Basic use rs .135** 1 .213** .228** .754** .129** 0.07 0.093 .094* 0.088   0.049 -0.007 0.063
p 0.004 . 0 0 0 0.006 0.143 0.051 0.047 0.063   0.307 0.878 0.182
Interactive use rs .196* .213** 1 .606** .924** .204** .132** .157** .275** 0.068   .115* .235** .189**
p 0.034 0 . 0 0 0 0.005 0.001 0 0.153   0.015 0 0
Self-display use rs .178* .228** .606** 1 .776** .139** .096* 0.072 .245** .105*   0.083 .207** .212**
p 0.029 0 0 . 0 0.003 0.043 0.128 0 0.027   0.081 0 0
Featured use rs .106* .754** .924** .776** 1 .215** .143** .144** .283** .100*   .108* .226** .207**
p 0.026 0 0 0 . 0 0.003 0.002 0 0.035   0.023 0 0
Positive affective use rs .187** .129** .204** .139** .215** 1 .166** .399** 0.063 -0.053   .147** .108* -0.045
p 0 0.006 0 0.003 0 . 0 0 0.184 0.26   0.002 0.023 0.345
Negative affective use rs -.115* 0.07 .132** .096* .143** .166** 1 .163** -0.055 0.019   0.006 -0.075 -.234**
p 0.015 0.143 0.005 0.043 0.003 0 . 0.001 0.248 0.696   0.893 0.114 0
Dependence score rs -0.017 0.093 .157** 0.072 .144** .399** .163** 1 .100* -.094*   .149** .138** 0.037
p 0.716 0.051 0.001 0.128 0.002 0 0.001 . 0.035 0.047   0.002 0.003 0.431
Motivation score rs .220** .094* .275** .245** .283** 0.063 -0.055 .100* 1 0.079   .169** .219** .209**
p 0 0.047 0 0 0 0.184 0.248 0.035 . 0.096   0 0 0
Total MET Minutes Per Week rs .123** 0.088 0.068 .105* .100* -0.053 0.019 -.094* 0.079 1   0.085 0.083 .154**
p 0.009 0.063 0.153 0.027 0.035 0.26 0.696 0.047 0.096 .   0.074 0.08 0.001
SNSs Information Seeking use rs .178** 0.049 .115* 0.083 .108* .147** 0.006 .149** .169** 0.085   1 .566** .242**
p 0 0.307 0.015 0.081 0.023 0.002 0.893 0.002 0 0.074   . 0 0
SNSs Self- status Seeking use rs .173** -0.007 .235** .207** .226** .108* -0.075 .138** .219** 0.083   .566** 1 .335**
p 0 0.878 0 0 0 0.023 0.114 0.003 0 0.08   0 . 0
SNSs Socialization use rs .265** 0.063 .189** .212** .207** -0.045 -.234** 0.037 .209** .154**   .242** .335** 1
p 0 0.182 0 0 0 0.345 0 0.431 0 0.001   0 0 .
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
# p value is illustrated in italic format
SNSs: Social Networking Sites
Total MET: total metabolic equivalents minutes

Table 4: Spearman's rank correlation matrix of the bivariate variables in relation to EAT-26 score.

The significant contributing factors of DEBs categories (Risky/Normal) were illustrated using adjusted ORs and their confidence intervals in Table 5. Female students who navigate the SNSs sites more in the current time compared to the pre-pandemic time were more prone to develop disordered eating [adjusted OR=4.225, 95% CI=(3.114–5.446), p value<0.001]. Participants who had a higher number of SNSs friends and those visited their SNSs once or more an hour was more likely to develop disordered eating. Participants reported high motivation score to use SNSs in relation to weight loss/ dieting, fitness/exercise, etc. [adjusted OR=5.032, 95% CI=(3.677–6.432), p value<0.001], marked body image concern [adjusted OR=6.034, 95% CI=(4.791–16.097), p value=0.003], and those exerted SNSs Information seeking in relation to weight loss/dieting, fitness/ exercise, etc. general tendency [adjusted OR=2.130, 95% CI=(2.048–3.219), p value=0.001] were more likely to develop DEBs. On the other hand, Participants with regular drug use showed positive factor against developing disordered eating manifestations [adjusted OR=0.277, 95% CI=(0.106 – 0.726), p value=0.009]. SNSs self-status seeking found to be a neutral factor [adjusted OR=0.933, 95% CI=(0.871–0.999), p value=0.045].

  Wald df Sig. Odds Ratio 95% C.I. for Odds Ratio
Lower Upper
Do you use drugs on regular basis? 6.814 1 .009** 0.277 0.106 0.726
SNSs Habits change from pre-pandemic stage to current time 21.069 2 .000**      
No Change (1) 0.15 1 0.699 0.864 0.413 1.809
Yes, navigate more than before (2) 18.299 1 .000** 4.225 3.114 5.446
In your favorite SNSs, how many friends do you have? 14.174 6 .028*      
50 – Less than 100 (1) 0.643 1 0.423 0.598 0.17 2.1
100 – Less than 200 (2) 0.102 1 0.342 1.24 0.331 4.637
200 – Less than 300 (3) 0.818 1 0.366 0.469 0.091 2.419
300 – Less than 400 (4) 3.183 1 0.467 0.407 0.036 4.589
400 – Less than 500 (5) 1.509 1 .030* 1.24 1.331 4.637
More than 500 (6) 0.528 1 .025* 4.26 2.867 20.937
On average, each time you visit SNS, how long would you spend on it? 21.411 6 .002**      
More than 4h (1) 6.825 1 0.199 0.538 0.208 1.387
3-4h (2) 0.714 1 0.398 0.615 0.2 1.897
2-3h (3) 6.668 1 .010* 0.195 0.057 0.675
1-2h (4) 8.857 1 .003** 0.139 0.038 0.51
0.5-1 h (5) 8.658 1 .003** 0.123 0.03 0.496
15-30 min (6) 11.229 1 .001** 0.165 0.058 0.473
Motivation score 12.307 1 .000** 5.032 3.677 6.432
Body image concern 16.581 4 .002**      
Mild Concern (1) 0.415 1 0.519 1.368 0.527 3.548
Moderate Concern (2) 5.716 1 .015* 3.275 2.145 8.179
Marked Concern (3) 8.837 1 .003** 6.034 4.791 16.097
SNU information seeking 10.114 1 .001** 2.13 2.048 3.219
SMU Self-status seeking 4.008 1 .045* 0.933 0.871 0.999
Constant 4.002 1 0.045 0.061    
# Logistic Regression: Outcome: Eating Disorder (Chi Square X2=158.071, p<0.000**)
# Predictors: Do you have any Psychological Disease? (Reference: No), Do you use drugs on regular basis? (Reference: No), Do any of your family member suffer from Obesity? (Reference: No), BMI in Kg/m2, SNSs Habits change from pre-pandemic stage to current time (Reference: Yes, navigate less than before), 1-How frequently do you use SNSs? (Reference: Never), 3- In your favorite SNSs, how many friends do you have? (Reference: Less than 50), 2-On average, each time you visit SNS, how long would you spend on it? (Reference: 15min or less), Affective use: Unhappiness, Motivation score, Total MET in minutes per week, featured use, Positive affective use, Negative affective use, SNU information seeking, SMU Self-status seeking, SMU Socializing, Body image concern (Reference: No)

Table 5: Regression analysis of usage patterns of social networking sites and disordered eating behaviors among the female university students.

Discussion

In this research, we explored DEBs magnitude among Saudi female college students during the COVID-19 pandemic era and their associations with students’ lifestyle behaviors and SNSs use. Results showed that more than quarter of the studied college females (27.2%) had problematic eating behaviors. This finding was in contrast to a recently published study on Saudi college females, which reported slightly higher rates of DEBs during COVID-19 pandemic [10]. This difference may be accounted for the timing of data collection, differences in the population characteristics (70% of scientific colleges), and population resilience with the pandemic progress. With the spread of COVID-19, more governmental attention should be paid to its potentially harmful effects on the mental health as recommended by WHO guidelines. Pandemic induced psychological distress may potentiate change in dietary behaviors as an adaptive mechanism for anxiety and stress [27- 30]. However, a slightly lower prevalence was reported on Middle East countries meta-analysis (22.07%) which was appeared to be slightly higher than the global prevalence rates with rapid social changes and acculturation occurring in many of the Arab countries [6]. Some studies before pandemic on Saudi female university students using EAT-26 test shows higher rates than reported on the current study (35.4% and 29.4), While others showed slightly lower rates 25.4% (9) of disordered eating attitudes (7, 8). These variations may be due to the study timing, different methodological factors include study setting (university or school or different cultures), sample selection (gender and age), size, and assessment methods (self-reported or inter- views).

Previous studies among female university students found significant relationships between EAT-26 scores exceeding 20 and peer or family stress to lose weight, marital status, studying in health science colleges, positive psychological illnesses history, overweight or obesity, poor eating habits, vegetarians, as well as having high levels of activity [7-11]. The reported association of poor psychiatric states and disordered eating among the studied females was coherent with Dooley-Hash et al., [31] who found an association between eating disorders and depression in females. psychiatric distress triggers emotional eating and unhealthy food choices as a coping mechanism [32]. Nevertheless, the current study did not establish a statistically significant difference between the disordered eating groups regarding faculty’s type, family and peer support, dietary, smoking and sleeping habits and the overall composite lifestyle score. Consistent with Alwosaifer et al. [8] results found no significant risk among different specialty colleges. This could be explained by the fact that all college students may have similarly experienced the consequences of the pandemic. Badrasawi et al. also showed that eating disorder risk was not correlated with fast food consumption, which was consistent with our results [33]. The only significantly associated lifestyle behavior is physical activity, where disordered eating is more prevalent among those practicing high physical activities as noted in a previous study [34].Notable explanation for this finding could be attributed to the pressure to perform well and often acquire a certain appearance puts athletes at a higher risk of developing disordered food and exercise behaviors. Our study also depicts that probability of being overweight and obese, body image marked concern or having familial histories of obesity is quite high in the risky group. This finding was consistent with many published research [5,7,9]. Plausible explanation for such finding could be attributed to psychological co-occurrences of high BMI such as body concern or dissatisfaction, and weight stigma contributes to the increasing burden of disordered eating [35]. Body image concern is thought to be a risk factor for eating- disordered behavior.

The current study highlighted the relationship between patterns of SNSs use and disordered eating atti-tude/ behaviors. It shows that Female students who navigate the SNSs sites more in the current time compared to the pre-pandemic time were more prone to develop disordered eating and disordered eating behaviors were significant more encountered among those with higher basic (higher frequency rate of account checking, duration of using and number of friends on the different SNSs), interactive and Self-display use rather than addictive SNSs use. This is concordant with A recently published meta-analysis in line with the results of several previous studies [14]. Specific SNS actions were recognized as a particularly troublesome drive for thinness and eating concerns, such as viewing and uploading images, seeking negative comments via status updates, making comments on other SNSs users’ photos and statuses [36] was related to higher drive for thinness and appearance comparison. Body dissatisfaction may influence disordered eating behavior when SNSs are used. Body image disturbance and disordered eating behavior have been connected to exposure to media messages advocating the thin ideal body. Murray et al. (2016) explained that body esteem indicators mediate the relationship between SNS use and disordered eating; greater use of SNS is associated with more severe weight and appearance dissatisfaction, which is in turn associated with more severe disordered eating [37]. Cohen et al. (2018) determined that engaging in photo-based activities (e.g., posting and sharing photos of oneself and friends) rather than general SNS use, shows an association with eating concerns [38]. On the other hand, other studies have found that the use of SNSs was not directly related to disordered eating be-haviors [15]. Our results were different from Ferguson et.al, (2014) that measured the influence of SNS use and peer competition on body satisfaction and eating disorder symptoms among teenage girls with a six-month follow- up period. They found no concurrent or prospective correlation between SNS use and body dissatis-faction or eating disorder symptoms. This lack of relationship may have been due to their measure of SNS use, which included activities like online gaming and blogging, or the fact that the majority of participants were Latino (94.1%) [39].

In line to findings that highlighted the positive correlation between disordered eating and participant’s motivation and general tendency to use SNSs for information seeking, self-status seeking, and socialization to fulfill specific gratifications related to weight loss/ dieting, fitness/exercise, body image and promoting standards of beauty that are often unrealistic. Easton et al. (2018) found that viewing Inspiration posts encouraged the studied sample obsession with calorie counting [40]. In addition, few believed that some of the diet related material could even instigate an eating disorder, especially if they were unable to recognize that their habits were becoming unhealthy. Likewise, Lee et al. (2014) concluded that social media use for in- formation about body image is negatively related to body satisfaction and body satisfaction has positive effects on disordered eating [24]. In agreement with the present study, Lee et al. (2013) presented their participants with profile pictures of underweight or overweight users on Facebook. They found that Korean undergraduates who witnessed an under-weight peer make online comments about a desire to lose weight, demonstrated lower body satisfaction than those who witnessed an overweight peer’s desire to lose weight [41].

Previous studies focused on the influence of SNS activity on well-being, but seldom considered the potential effects of SNS affective experience that may predict psychological well-being [42]. Regardless of individual activity on SNSs, it is likely that SNS users would be more satisfied and happier when they experience more positive and fewer negative affects online. If, however, navigating SNSs evoked negative feelings, then a decrease in life satisfaction or psychological well-being would be expected. Our finding that unhappiness, and negative affective experiences among participants were significantly linked with the risky eating disorder is coherent with Fabris et al. (2020) who concluded that it is possible that adolescents with higher levels of negative effects may be at greater risk for excessive social media use aimed at restoring gratification or compensation with respect to perceived needs and accordingly may increase probability for psychological consequences and disordered eating among the young population. [14, 43].

Conclusions

It is the first study to link the different perspectives of social network use and eating disorder behavior taking into consideration the composite unhealthy lifestyle behaviors at the time of COVID pandemic. It is crucial to watch over net usage among the adolescent population and especially those with ED, because the high use and the context of the social media can be considered almost as a significant risk factor and females are more vulnerable to be affected by the social media. There are a number of strengths of this study, including the calculation of sample size, random sample was recruited from different faculties, and use of validated questionnaires. In addition, targeting college age is very essential as disordered eating tends to be greater in this life phase. However, there are also some limitations to consider. Firstly, all data are self-reported which may involve recall bias. Secondly, our data are based on a cross-sectional and therefore causality cannot be inferred. Thirdly, results are not representative of female university students across KSA but only students at one university. Therefore, the results cannot be generalized to other settings. Finally, we used self-reported weight and height to calculate BMI, which may bias to underestimate it, although previous studies found there is quite little differences between self-reported BMI and measured BMI in females and males. Longitudinal studies are recommended to assess causality between SNSs use and disordered eating behaviors.

Supplementary Materials

Supplementary File S1: detailed analysis of Social Network Sites use (Featured Use, Affective use, and addiction of SNSs) among female university students, classified according to EAT-26.

Author Contributions

Abdulaziz R. Alotaibi and Nesrin Kamal Abd El Fattah designed the Study proposal and questionnaire and collect research data. Nesrin Kamal Abd El Fattah, Abdulaziz R. Alotaibi, Abdullah Muidh Alqethami and Nermin A. Osman share in article writing. Nermin A. Osman and Nesrin Kamal Abd El Fattah analyzed data.

Funding

Self-funded.

Institutional Review Board Statement

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the Research Ethics Committee of Taif Health Affairs, Ministry of Health, Saudi Arabia approved this study (IRB. HAP-02-T-067, 653). Written informed consent was obtained from all study participants.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgements

We would like to thank residents, colleagues, and administrative staff at Taif joint Program of Preventive Medicine, Public Health Administration, Taif Health Affairs, Ministry of Health, Saudi Arabia, for their help in dissemination of our survey.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Author Info

Abdulaziz R Alotaibi1, Nermin A Osman2, Abdullah Muidh Alqethami3 and Nesrin Kamal Abd El-Fatah4*

1Public Health Administration, Taif Health Affairs, Ministry of Health, Saudi Arabia
2Department of Biomedical Informatics and Medical Statistics, Medical Research Institute, Alexandria University, Egypt
3Taif Joint Postgraduate Tainting Program for Preventive Medicine, Ministry of Health, Saudi Arabia
4Department of Nutrition, High Institute of Public Health, Alexandria University, Egypt
 

Citation: Abdulaziz R Alotaibi, Nermin A Osman, Abdullah Muidh Alqethami, Nesrin Kamal Abd El-Fatah, Social Networking Sites use, Lifestyle Index and Disordered Eating Behaviors During the Era of COVID 19: A Cross Sectional Study among Female Students of Taif University, Saudi Arabia, J Res Med Dent Sci, 2022, 10 (6):21-34

Received: 24-May-2022, Manuscript No. JRMDS-22-64809; , Pre QC No. JRMDS-22-64809 (PQ); Editor assigned: 26-May-2022, Pre QC No. JRMDS-22-64809 (PQ); Reviewed: 10-Jun-2022, QC No. JRMDS-22-64809 ; Revised: 15-Jun-2022, Manuscript No. JRMDS-22-64809 (R); Published: 22-Jun-2022

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