{"paper_id":"42028bb4-2fb2-43bb-bbb4-efc6582cd7d1","body_text":"The Impact of COVID-19-Related Stress on Diet and Eating Behaviors in US College Students: 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 Research Article The Impact of COVID-19-Related Stress on Diet and Eating Behaviors in US College Students: A Cross-Sectional Study Olufisayo Atanda-Ogunleye, Shuxian Hua, Bianca Borsarini, Sarah Ann Duck, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6196663/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background The COVID-19 pandemic exposed the US population, including college students, to stress posing challenges to psychological and behavioral health. Previous studies have demonstrated that stress can promote unhealthy eating behaviors among college students. This study aimed to examine the relationships of pandemic-related stress with changes in diet and eating behaviors experienced by college students during the Fall 2020 semester. Methods 758 college students in the Mid-Atlantic region of the US completed an online survey in November 2020. The survey assessed multiple dimensions of pandemic-related stress, diet, and eating behaviors, as well as measures of psychological health and social support. Results Pandemic-related stress, particularly academic stress, was correlated with less healthy dietary profiles and potentially maladaptive eating behaviors, including emotional eating and late-night eating. Associations between stress and dietary intake were stronger in females than males, whereas males showed stronger associations between stress and food responsiveness. Pandemic-related stress was associated with perceived changes in diet quality, frequency of eating, and amount of food consumed compared to since before the semester started. Conclusion Academic stress during the pandemic had a negative impact on diet and eating behaviors among college students. Our results argue for interventions targeting academic stress in everyday contexts as well as potential future public health crises, to prevent negative impacts on students’ eating profiles that may in turn negatively impact health. COVID-19 pandemic stress eating behaviors dietary intake nutrition academic performance young adults 1. Introduction The COVID-19 pandemic caused a global decline in psychological health, resulting in what some have described as a psychiatric epidemic (Gloster et al., 2020 ; Hossain et al., 2020 ). Evidence suggests that populations experienced increasing levels of stress, depression, and anxiety stemming from pandemic-related psychosocial stressors such as diminished social support and anxiety regarding COVID-19 exposure (Gloster et al., 2020 ; Hossain et al., 2020 ). College students are known to experience poor psychological health outcomes, and the pandemic introduced additional stressors impacting both their academic and personal lives (Wang et al., 2023 ). During periods of heightened stress, college students are susceptible to changes in dietary intake and eating habits (Errisuriz et al., 2016 ; Pelletier et al., 2016 ). For instance, increased stress among college students has been associated with changes in eating patterns that may negatively impact health, including increased rates of meal skipping and late-night eating (Pelletier et al., 2016 ), as well as greater consumption of unhealthy snacks and fast food (Errisuriz et al., 2016 ). Such dietary and behavioral changes during young adulthood can have long-term consequences, including elevated risks of type 2 diabetes and poorer mental health, as suggested by other studies of COVID-19 impacts (Hussein & Soliman, 2023 ; Rogers et al., 2021 ). Despite the uniquely stressful experiences college students underwent during the pandemic, the impact of COVID-19-related stress on their diet and eating behaviors has not been comprehensively investigated. A few studies found that social isolation and online learning during the pandemic posed challenges (e.g., changes to learning environments, job searches, and the ability to afford treatments) and resulted in increased stress with concomitant effects on diet and eating behaviors among college students (Amatori et al., 2020 ; Huber et al., 2021 ; LaCaille et al., 2021 ). However, findings have been heterogeneous, with some reports of increased consumption of bread and sweets, decreased intake of legumes and low-fat meat, and larger portion sizes, but other reports of healthier dietary choices such as eating more fiber-rich foods, like fruit and vegetables (Amatori et al., 2020 ; Dhammawati et al., 2023 ; Huber et al., 2021 ; LaCaille et al., 2021 ). These conflicting results highlight the complexity of stress-related dietary responses and the potential role of individual differences in eating behaviors during the pandemic. Although changes in diet and eating behaviors among youth during the pandemic have been extensively studied across different cultural contexts (Amatori et al., 2020 ; Galali, 2021 ; Huber et al., 2021 ; Imaz-Aramburu et al., 2021 ; Jia et al., 2021 ; Kołota & Głąbska, 2021 ; LaCaille et al., 2021 ), few studies have examined how these changes relate to underlying psychological factors, such as stress (Elsalem et al., 2020 ). Furthermore, much of the existing research has focused on documenting behavioral shifts without identifying the specific stressors responsible for these changes among young populations (Imaz-Aramburu et al., 2021 ; Jehi et al., 2023 ; Jia et al., 2021 ; Kołota & Głąbska, 2021 ; Pung et al., 2021 ). For example, compared to before the pandemic, healthier eating behaviors and more consistent meal patterns were reported in some studies (Duong et al., 2020 ; Rafraf et al., 2023 ), while others have reported an increased intake of high-energy foods and less healthy foods, along with higher rates of binge eating, emotional eating, meal skipping, unhealthy snacking, and food insecurity (Coakley et al., 2021 ; Elsalem et al., 2020 ; Jehi et al., 2023 ; Pung et al., 2021 ). These inconsistencies underscore the need for further research to examine how different aspects of COVID-19-related stress (e.g., academic pressures, financial hardships, risk of exposure) may have influenced diet and eating behaviors among college students. The current study aimed to address some of the research gaps outlined above by comprehensively investigating the relationships of COVID-19-related stress with dietary intake and eating behaviors via a survey conducted in a large, ethnically diverse sample of US undergraduates during the Fall 2020 semester. Our overarching hypothesis was that increased pandemic-related stress would be associated with higher consumption of less healthy foods (e.g., sweets, savory snacks, fast food, sugar-sweetened beverages) and potentially adverse eating behaviors (e.g., emotional eating, emotional overeating, and late-night eating). Based on previous evidence suggesting stronger relationships between stress and both eating behaviors of food eaten among women (Degroote et al., 2024 ; Zellner et al., 2006 ), and higher rates of binge eating in women (Rosenbaum & White, 2015 ), we additionally explored sex differences in associations of stress with diet and eating behaviors. 2. Methods 2.1. Participants and Procedure A cross-sectional survey was distributed between November and early December 2020 to undergraduate students (N = 758, M age = 18.38±1.31; 70.1% female; see Table 1 for further demographic information) at a medium-sized Mid-Atlantic university, as well as some additional undergraduate students from other universities using a listserv. The survey included questions about dietary intake, eating behaviors, social support, overall psychological health status, and COVID-19-related stress during the Fall mid-semester. Participants were entered into a draw to win a $ 50 Amazon gift card upon completing the survey. The study was approved by the Johns Hopkins Institutional Review Board (IRB: NA_00092328). Table 1 Sample characteristics . N (%) Year in university (n = 758) Freshman/First-year undergraduate 262 (34.6%) Sophomore/Second-year undergraduate 171 (22.6%) Junior/Third-year undergraduate 175 (23.1%) Senior/Fourth-year undergraduate 143 (18.9%) Fifth year or more undergraduate 7 (0.9%) Sex assigned at birth (n = 757) Male 224 (29.6%) Female 531 (70.1%) Prefer not to say 2 (0.3%) Race (n = 757) Black 68 (9.0%) White 209 (27.6%) Hispanic/Latin (identify solely this way) 41 (5.4%) Native Hawaiian/ Pacific Islander 1 (0.1%) Asian 293 (38.7%) Mixed 125 (16.5%) Other 8 (1.1%) Decline to Answer 12 (1.6%) Age group (n = 757) 17 15 (2.0%) 18 223 (29.5%) 19 173 (22.9%) 20 180 (23.8%) 21 134 (17.7%) 22 28 (3.7%) 23 3 (0.4%) Older than 25 1 (0.1%) BMI (excluding outliers, n = 481) Underweight, BMI < 18.5 40 (8.3%) Healthy weight, BMI 18.5–24.9 331 (68.8%) Overweight, BMI 25.0–29.9 99 (20.6%) Obesity, BMI > 30 11 (12.3%) Note: Totals for each characteristic may not equal the overall sample size of 758 due to missing or incomplete data for some variables. BMI: body mass index. 2.2. Measures 2.2.1. Demographics and Self-Reported Weight and Height Standard demographic information, including age, race, sex assigned at birth, and year in university, was collected. Participants were also asked to report their weight and height, which were used to calculate body mass index (BMI). 2.2.2. COVID-19-Related Stress To measure COVID-19-related stress, questions were adapted from a previous study (Sadler et al., 2021 ), focusing on three main components: a. Academic Stress Induced by the COVID-19 Pandemic (ASIP) : Stress related to factors such as compulsory online learning, the negative impact of isolation measures on academic performance, and changes in career prospects. b. Financial Stress Induced by the COVID-19 Pandemic (FSIP) : Stress related to factors such as job loss, financial instability, and health insurance costs. c. COVID-19 Exposure-Related Stress (CERS) : Stress related to concerns about contracting COVID-19 personally or someone they know being affected. The questions used to measure each stressor category are presented in Table 2 . The final measure consisted of 19 items, grouped as follows: Table 2 COVID-19-Related Stressors Measures a) ASIP, b) FSIP, and c) CERS. a) ASIP question: How stressed are you about the following? 1. My academic performance will be or is being negatively impacted by the COVID-19 pandemic 2. The new layout of my classes (all online, all in-person, online & in-person) will affect or has affected my ability to succeed in courses 3. Being unable to concentrate on school activities due to your learning environment OR fearing that you will be unable to concentrate on school activities in the future 4. Being unable to complete assignments due to your learning environment OR fearing you will be unable to complete assignments due to your learning environment 5. Being unable to get a job/internship 6. My GPA will drop due to the circumstances of this semester (COVID-19 pandemic, financial stability, bad learning environment, inability to work at home, etc.) 7. Decreased productivity with schoolwork or school-related activities 8. Ongoing need for social isolation due to COVID-19 pandemic 9. Future job/career prospects 10. Changing plans as to reopening of schools (i.e., uncertainty of knowing whether the school would have in-person, online, or hybrid(in-person/online) classes) b) FSIP question: How stressed are you about the following? 1. Not being able to pay for basic needs (rent/mortgage, food, etc.) 2. Losing my job 3. Someone I depend upon for income losing their job 4. I will be unable to access medical care for myself or my family 5. My family/I will be unable to pay for my college tuition c) CERS question: How stressed are you about the following? 1. I will get COVID-19 2. A relative (e.g. grandparent) or close family friend will get COVID-19 3. Someone I live with will get COVID-19 Note: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic; and CERS: COVID-19 exposure-related stress. Response options for all questions were rated on a 5-point Likert scale: Not at all (1), Slightly (2), Somewhat (3), Moderately (4), and Extremely (5). ASIP Score : 10 items, Cronbach’s alpha = 0.88; FSIP Score : 6 items, Cronbach’s alpha = 0.78; CERS Score : 3 items, Cronbach’s alpha = 0.80. The mean score for each stress variable was used in the analyses. 2.2.3. Dietary Intake Students reported their consumption of various food categories in the past 7 days as described in Sadler et al. ( 2021 ). Participants estimated their frequency of consuming sweets/desserts (e.g., chocolate, cookies, doughnuts, ice cream), chips/savory snacks (e.g., regular or low-fat chips, salty snacks), fast food (e.g., McDonald’s), and servings of fruits and vegetables. Response ranged from “Never” to “6 or more times per day.” Intake was reported as weekly frequency or servings. A “junk food intake” variable was calculated by summing servings of sweets, savory snacks, fast foods, and sweetened beverages consumed. 2.2.4. Eating Behaviors Students reported perceived changes since before the semester in the frequency of eating, the amount of food eaten, and health of diet. They also reported on late-night eating behavior in the past 7 days. Four subscales from the Adult Eating Behavior Questionnaire (AEBQ) (Hunot et al., 2016 ) assessed food responsiveness, satiety responsiveness, emotional overeating, and emotional undereating, using a 5-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree). An adapted Revised Emotional Eating Scale with Boredom (REES-B) (Koball et al., 2012 ) assessed emotional eating related to four emotions (“bored,” “sad,” “anxious,” and “stressed”) on a 5-point scale from “Never” to “Very Often,” with average scores calculated. 2.2.5. Psychological Health Stress levels were measured using the 4-item Perceived Stress Scale (PSS-4) (Herrero & Meneses, 2006 ), which asked about perceived control, confidence, and feelings of overwhelm. Responses ranged from “Never” to “Very Often,” and average scores were calculated. Depression was assessed with the 10-item Center of Epidemiologic Studies Depression Scale (CES-D-10) (Andresen et al., 1994 ), where participants indicated the frequency of depressive symptoms over the past week. 2.2.6. Social Support The Perceived Support Questionnaire (PSQ) (Lin et al., 2019 ) assessed perceptions of social security, safety, and a personal community of support. Participants rated six statements on a 5-point scale (1 = Strongly Disagree to 5 = Strongly Agree). A more detailed overview of all measures and questionnaire is provided in the Supplementary Materials ( link to Supplementary Data ). 2.3. Statistical Analyses Statistical analyses were conducted using IBM SPSS Statistics version 27 (IBM SPSS Statistics for Windows). Due to the nonparametric distribution of most responses, Spearman’s correlations were used to assess bivariate relationships between COVID-19-related stress and dietary intake and eating behaviors. ASIP, FSIP, and CERS variables were categorized into Low, Moderate, and High Stress based on tertiles. Chi-square tests (χ²) examined associations between stress levels and perceived changes in eating behaviors from pre- to mid-semester. Additional chi-square tests assessed sex-based differences in perceived changes in eating behaviors. 3. Results 3.1. Sample Characteristics Sample characteristics are presented in Table 1 . The distribution of participants across university years was relatively even, with slightly more freshmen (34.6%). The sample was predominantly female (70.1%) and consisted largely of first-year undergraduate students (34.6%), with a mean age of 18.38±1.31 years. The majority of participants fell within the healthy weight range (68.8%), with a mean BMI of 22.28±3.11. Psychological health and social support measures and related statistics are reported in Table 3 . The highest mean scores on pandemic-related stress were observed for ASIP (3.78±0.85), followed by CERS (3.46±1.02) and then FSIP (2.12±0.89). Table 3 Median and Mean (SD) Scores for Psychological Health and Social Support Variables . Variables Median Mean (SD) Pandemic-related stressors ASIP 4.00 3.78 (0.85) FSIP 2.00 2.12 (0.89) CERS 3.67 3.46 (1.02) Psychological health CES-D-10 14.00 14.50 (6.10) PSS-4 3.25 3.30 (0.73) Social support PSQ 22.00 22.20 (4.60) Note: SD: standard deviation; CERS: COVID-19 exposure-related stress (range: 1–5); FSIP: financial stress induced by the COVID-19 pandemic (range: 1–5); ASIP: academic stress induced by the COVID-19 pandemic (range: 1–5); CES-D-10: Center of Epidemiologic Studies Depression Scale (range: 10–40); PSS-4: 4-item Perceived Stress Scale (range: 1–5); PSQ: Perceived Support Questionnaire (range: 6–30). 3.2. Relationship between COVID-19-Related Stress and Dietary Intake Correlations between COVID-19-related stress and dietary intake in the past 7 days are described below (Table 4 ). Table 4 Spearman’s Correlations (ρ) and 95% CIs Between COVID-19-Related Stressors and Dietary Intake Over the Past 7 Days in Whole Sample, Males, and Females. COVID-19-Related Stressors Junk Food Intake Fruit and Vegetable Intake Fast Food Intake Sweets Intake Whole sample Males Females Whole sample Males Females Whole sample Males Females Whole sample Males Females ASIP 0.092* (.01, .17) -0.026 (-.18, .13) 0.16* (.06, .26) -0.037 (-.12, .05) 0.11 (-.05, .26) -0.12* (-.22, − .02) 0.13* (.04, .21) 0.014 (-.14, .17) 0.19** (.09, .28) 0.091* (.0, .17) -0.007 (-.16, .14) 0.14* (.04, .23) CERS 0.001 (-.08, .08) -0.126 (-.27, .03) 0.062 (-.04, .16) -0.011 (-.10, .07) 0.053 (-.10, .21) -0.055 (-.15, .05) 0.048 (-.04, .13) 0.063 (-.09, .22) 0.055 (-.05, .16) -0.003 (-.09, .08) -0.15* (-.30, .00) 0.058 (-.04, .16) FSIP 0.016 (-.07, .10) -0.018 (-.17, .13) 0.047 (-.05, .15) - 0.037 (-.12, .05) 0.063 (-.09, .22) -0.11* (-.21, − .01) 0.10* (.02, .19) 0.038 (-.12, .19) 0.14* (.04, .24) 0.035 (-.05, .12) -0.015 (-.17, .14) 0.060 (-.04, .16) Note: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic; CERS: COVID-19 exposure-related stress. Significant differences (p < 0.05) are bolded. *p < 0.05, **p < 0.001. Junk food includes sweet and savory snacks, fast food, and sugar-sweetened beverages. Confidence intervals (CI) are presented in parentheses. 3.2.1. ASIP As shown in Table 4 , higher ASIP was correlated with increased intake of junk food (ρ = 0.092, p < 0.05), fast food (ρ = 0.13, p < 0.05), and sweets (ρ = 0.091, p < 0.05) in the past 7 days. Among females, higher ASIP was correlated with increased consumption of fast food (ρ = 0.19, p < 0.001) and sweets (ρ = 0.14, p < 0.05) and decreased consumption of fruits and vegetables (ρ = -0.12, p < 0.05), while no significant associations were observed for males. 3.2.2. FSIP FSIP was positively associated with fast food intake (ρ = 0.10, p < 0.05) in the past 7 days (Table 4 ). Among females, higher FSIP correlated with increased fast food consumption (ρ = 0.14, p < 0.05) and decreased fruit and vegetable intake (ρ = -0.11, p < 0.05). No significant associations were observed for males. 3.2.3. CERS CERS showed no significant overall associations with dietary intake in the past 7 days for any food group (Table 4 ). However, one significant relationship was observed among males, such that higher CERS was correlated with lower sweets intake (ρ = -0.15, p < 0.05). 3.3. Relationship between COVID-19-Related Stress and Eating Behaviors Correlations between COVID-19-related stress and eating behaviors, including emotional eating, emotional overeating, food responsiveness, and late-night eating, are described below (Table 5 a and Table 5 b). Table 5 a. Spearman’s Correlations (ρ) and 95% CIs Between COVID-19-Related Stressors and Eating Behaviors in Whole Sample, Males, and Females . COVID-19-Related Stressors REES B Emotional Eating AEBQ Emotional Overeating AEBQ Food Responsiveness Whole sample Males Females Whole sample Males Females Whole sample Males Females ASIP 0.34** (.25, .41) 0.28** (.13, .42) 0.36** (.26, .44) 0.16** (.07, .24) 0.13 (-.03, .28) 0.16* (.06, .26) 0.078 (-.01, .16) 0.24* (.09, .39) 0.003 (-.10, .11) CERS 0.17** (.08, .25) 0.17* (.01, .32) 0.16* (.06, .26) 0.086* (.00, .17) 0.066 (-.09, .22) 0.093 (-.01, .19) 0.12* (.03, .20) 0.17* (.01, .31) 0.088 (-.01, .19) FSIP 0.26** (.18, .34) 0.28** (.12, .42) 0.25** (.15, .34) 0.16** (.07, .24) 0.19* (.03, .34) 0.14* (.04, .24) 0.11* (.02, .19) 0.22* (.06, .36) 0.061 (-.04, .16) Note: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic; CERS: COVID-19 exposure-related stress; REES B: Revised Emotional Eating Scale with Boredom and Emotions Experienced; AEBQ: Adult Eating Behavior Questionnaire. Significant differences (p < 0.05) are bolded. *p < 0.05, **p < 0.001. Confidence intervals (CI) are presented in parentheses. Table 5 b. Chi-Square Tests (χ²) of Associations Between COVID-19-Related Stressors (tertiles) and Late-Night Eating in the Past 7 Days. ASIP and Late-Night Eating ASIP Less than half of diet consumed after dinner About half of diet consumed after dinner More than half of diet consumed after dinner χ 2 = 26.79, p < 0.001 Low stress 172 (39.8%) 25 (27.2%) 9 (16.1%) Moderate stress 150 (34.7%) 37 (40.2%) 16 (28.6%) High stress 110 (25.5%) 30 (32.6%) 31 (55.4%) FSIP and Late-Night Eating FSIP Less than half of diet consumed after dinner About half of diet consumed after dinner More than half of diet consumed after dinner χ 2 = 25.57, p < 0.001 Low stress 165 (38.2%) 26 (28.3%) 14 (25.0%) Moderate stress 145 (33.6%) 24 (26.1%) 10 (17.9%) High stress 122 (28.2%) 42 (45.7%) 32 (57.1%) Note: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic. 3.3.1. ASIP Higher ASIP was correlated with heightened scores on scales assessing maladaptive eating behaviors. Specifically, ASIP was positively associated with emotional overeating (ρ = 0.16, p < 0.001) and with eating in response to a range of emotions, such as boredom, worry, nervousness, and stress (ρ = 0.34, p < 0.001). A positive correlation between ASIP and food responsiveness (ρ = 0.24, p < 0.05) was observed among males only, while a positive correlation with emotional overeating was found among females only (ρ = 0.16, p < 0.05). Additionally, higher ASIP was significantly associated with an increased frequency of late-night eating episodes, as indicated by greater food consumption after dinner (β = 26.79, p < 0.001). 3.3.2. FSIP Higher FSIP was correlated with eating in response to a range of emotions (ρ = 0.26, p < 0.001), emotional overeating (ρ = 0.16, p < 0.001), and food responsiveness (ρ = 0.11, p < 0.05). The correlations for eating in response to emotions and emotional overeating were apparent in both males and females, whereas the association with food responsiveness was observed only in males (ρ = 0.22, p < 0.05) and not in females. Similar to ASIP, higher FSIP was associated with an increased occurrence of late-night eating episodes, as reflected by elevated food intake after dinner (β = 25.57, p < 0.001). 3.3.3. CERS Higher CERS was correlated with eating in response to a range of emotions (ρ = 0.17, p < 0.001), emotional overeating (ρ = 0.086, p < 0.05), and food responsiveness (ρ = 0.12, p < 0.05) (Table 4 ). A positive association between CERS and food responsiveness was observed in males (ρ = 0.17, p < 0.05) but not in females. 3.4. Perceived Changes in Eating Behaviors Correlations between COVID-19-related stress and perceived change in eating behaviors from pre-semester to mid-semester, including changes in diet quality, frequency of eating, and the amount of food consumed are described below (Table 6 ). Higher ASIP was associated with a perceived less healthy diet (β = 15.94, p = 0.003) since before the semester started. Furthermore, higher ASIP was associated with changes in the frequency of eating (β = 26.79, p < 0.001), with students experiencing greater academic stress reporting both increases and decreases in their eating frequency. Higher FSIP was associated with a perceived lower amount of food consumed (β = 10.43, p = 0.034), and a perceived lower eating frequency (β = 15.45, p = 0.004). No associations of CERS with perceived change from pre- to mid-semester were observed. Table 6 Chi-Square Tests (χ²) of Associations Between COVID-19-Related Stressors (tertiles) and Perceived Change in Eating Behaviors from Pre- to Mid-Semester. ASIP and Perceived Change in Health of Diet ASIP Eating less healthily Eating equally healthy Eating more healthily χ 2 = 15.94, p = 0.003 Low stress 81 (28.8%) 63 (45.7%) 51 (42.5%) Moderate stress 100 (35.6%) 43 (31.2%) 40 (33.3%) High stress 100 (35.6%) 32 (23.2%) 29 (24.2%) ASIP and Perceived Change in Frequency of Eating ASIP Eating less frequently Same eating frequency Eating more frequently χ 2 = 26.79, p < 0.001 Low stress 84 (32.1%) 52 (50.0%) 58 (33.7%) Moderate stress 91 (34.7%) 33 (31.7%) 59 (34.3%) High stress 87 (33.2%) 19 (18.3%) 55 (32.0%) FSIP and Perceived Change in Amount of Food Consumed FSIP Eating less food Eating about the same amount of food Eating more food χ 2 = 10.43, p = 0.034 Low stress 64 (28.8%) 62 (41.1%) 62 (37.6%) Moderate stress 66 (29.7%) 46 (30.5%) 54 (32.7%) High stress 92 (41.4%) 43 (28.5%) 49 (29.7%) FSIP and Perceived Change in Frequency of Eating FSIP Eating less frequently Same eating frequency Eating more frequently χ 2 = 15.45, p = 0.004 Low stress 77 (29.4%) 51 (49.0%) 60 (34.9%) Moderate stress 83 (31.7%) 22 (21.2%) 60 (34.9%) High stress 102 (38.9%) 31 (29.8%) 52 (30.2%) Note: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic. Further analyses examining sex differences (Table 7 ) revealed notable variations in eating behavior changes during the COVID-19 period. Females were more likely to report changes in both the amount of food consumed (β = 8.55, p = 0.014) and the frequency of eating (β = 6.88, p = 0.032), whether increases or decreases. In contrast, males were more likely to report stability in their eating behaviors over the same period. Table 7 Chi-Square Tests (χ²) for Associations Between Sex and Perceived Change in Eating Behaviors from Pre- to Mid-Semester . Relationship between Sex and Perceived Change in Amount of Food Consumed Eating Less Food Eating About the Same Amount of Food Eating More Food χ 2 = 8.55, p = 0.014 Male 52 (23.4%) 56 (37.1%) 53 (32.1%) Female 170 (76.6%) 95 (62.9%) 112 (67.9%) Relationship between Sex and Perceived Change in Frequency of Eating Eating Less Frequently Same eating frequency Eating more frequently χ 2 = 6.88, p = 0.032 Male 70 (26.7%) 42 (40.4%) 49 (28.5%) Female 192 (73.3%) 62 (59.6%) 123 (71.5%) 4. Discussion We aimed to investigate the impact of COVID-19-related stress on the diet and eating behaviors of US college students during the Fall 2020 semester and explore sex differences within the sample. Our primary research hypothesis was that COVID-19-related stress levels would be associated not only with unhealthy dietary patterns but also with potentially maladaptive eating behaviors. Consistent with our prediction, our primary findings indicate that several different types of COVID-19-related stress was associated with potentially maladaptive eating behaviors and less healthy dietary profiles. Specifically, COVID-19-related academic and financial stress were positively associated with fast food consumption and negatively associated with fruit and vegetable intake in females. All three COVID-19 stressors — academic (ASIP), financial (FSIP), and COVID-19 exposure (CERS) — were positively associated with emotional eating in both males and females. Additionally, stress was positively associated with food responsiveness in males. ASIP emerged as the most influential COVID-19-related stressor (Mean ASIP = 3.78±0.85, range: 1–5). ASIP components included changes in class formats, difficulty concentrating on schoolwork and activities, social isolation, and concerns about the impact on future careers. In line with our findings, another study on 843 US college students reported a link between academic stress levels and worsened psychological health as a consequence of COVID-19 (Barbayannis et al., 2022 ). A likely cause of this is the abrupt transition from traditional in-person classroom settings to remote learning, which led to isolation, a decrease in outdoor extracurricular activities and interpersonal exchange, and disturbances in sleep patterns, likely partly driven by (and a contributor to) the concurrent increases in stress, anxiety, and depression among college and high education students (Nano et al., 2022 ; Son et al., 2020 ; Tahir et al., 2021 ). We specifically found that COVID-19-related academic stress was positively associated with junk food consumption and negatively associated with fruit and vegetable intake, particularly among females. Although our findings indicate a poorer dietary profile under pandemic-related stress, studies in other populations have reported the opposite, potentially reflecting pre-existing differences in nutrition and daily dietary patterns. For instance, one study found increased unhealthy food consumption among Italian students, while junk food consumption decreased among French students (Caso et al., 2020 ). Similarly, studies in Spain and Croatia observed increased vegetable and fruit consumption during the lockdown, with students adhering more closely to Mediterranean Diet guidelines than in pre-pandemic times (Dragun et al., 2020 ; Imaz-Aramburu et al., 2021 ). These contradictory findings highlight the influence of cultural context (e.g., dietary patterns) and cross-country differences in pandemic responses. Meanwhile, we found that increased ASIP was linked to greater emotional eating in both males and females. This aligns with pre-pandemic reports showing that low academic self-esteem and increased academic worries are more prevalent among emotional eaters than non-emotional eaters (Chamberlin et al., 2018 ). Stress related to the potential consequential risks of virus exposure (i.e. CERS), such as concerns about one’s own or loved ones’ health after having contracted COVID-19, was rated high in our study (Mean CERS = 3.46±1.02, range: 1–5). Exposure stress was also positively associated with emotional eating and food responsiveness, especially in males, indicating a degree of psychological deterioration. However, the associations with emotional eating were weaker than those observed with academic stress. Nevertheless, our results align with other findings among emerging adults in the US, which reported weaker associations between pandemic-related health stress (both self and for close others) and impaired psychological health compared to financial and educational-related stress in this population (Kujawa et al., 2020 ). Financial stress induced by the pandemic (FSIP) scored the lowest, as compared to other COVID-19-related stressors, among college students (Mean FSIP = 2.12±0.89, range: 1–5). This is likely because many college students in our sample were relying primarily on household income, student loans, and scholarships and were not (yet) working as full-time employees, buffering them from the immediate impacts of financial stress. However, despite this relatively lower financial stress, significant associations with dietary intake were observed. Specifically, FSIP was negatively associated with fruit and vegetable intake and positively associated with fast food intake among females, highlighting a shift toward less healthy and more affordable food options. These effects are likely influenced by broader systemic factors, including the economic challenges, food access disparities, and inflation brought about by COVID-19. Notably, during the pandemic, grocery prices for fresh fruits and vegetables rose disproportionately compared to the prices of fast food in the US, potentially intensifying these dietary shifts (Volpe et al., 2024 ). Such economic disparities were particularly evident in low-income school districts, which faced significant challenges in accessing primary goods and emergency nutrition programs during the pandemic, contributing to increased malnutrition rates and poorer dietary variety among students (Hall et al., 2022 ; McLoughlin et al., 2020 ). Additionally, lower family income was found to be associated with greater emotional eating in a population of healthy Saudi Arabian female students, suggesting that the financial environment can indeed increase the risk of potentially pathological eating behaviors (Al-Musharaf, 2020 ). In our study, higher levels of FSIP were linked to a perceived reduction in food consumption and less frequent eating, further indicating food insecurity among university students experiencing greater stress over financial situations (Bruening et al., 2018 ). Our sample consisted predominantly of healthy-weight college students (72%). This is noteworthy since a large amount of the existing literature linking emotional eating and stress suggests that employing food to manage distress is more common among individuals with obesity and overweight (Burnatowska et al., 2022 ; Cecchetto et al., 2021 ; Dakanalis et al., 2023 ). The effects we observed may therefore potentially be stronger in a sample including a greater proportion of individuals with higher body weight. In our investigation, we additionally explored sex differences in the impacts of pandemic-related stress on diet and eating behaviors. Our results suggest female students appeared to be slightly more susceptible to expressing distress associated with the pandemic via maladaptive eating habits and unhealthy diets compared to males. This predominant female vulnerability is coherent with previous analogous evidence within young populations (Ulloa et al., 2022 ). This study has several limitations. First, being cross-sectional, it is unable to determine the causal relationship of interest. Second, there is potential for recall bias, as some questions required participants to remember their behaviors prior to the semester in order to compare them with the current behaviors (mid-semester). Third, our study largely relied on responses from an private Mid-Atlantic university where ethnic diversity is high but the socioeconomic status of participants is generally higher than the average American college student (Gregor Aisch et al., 2017; JHU Report on Undergradute Student Composition, 2023). The higher socioeconomic status of these participants may explain why financial COVID stress ranked as the lowest concern. Possibly, in a different population, financial stress could have been a more prominent source of COVID-19-related stress. Also, these findings might reflect a US-specific situation, considering that US, and even each state within the US, had a different approach to regulations compared to Europe. Lastly, our study did not investigate whether the relationship between COVID-19-related stressors and eating behaviors differs by weight status. In conclusion, our findings suggest that the unique concerns introduced by the abrupt and stressful COVID-19 pandemic, and in particular academic stress, significantly impacted not only dietary quality but also eating behaviors (especially eating in response to emotions and late-night eating) of college students, with effects varying between sexes. These results illuminate young adults’ susceptibility to different types of stress generated by a population-level health event and the detrimental impact of such stress on dietary health, as well as the development of potentially pathological eating behaviors. These behaviors may carry long-term risks, including an increased likelihood of metabolic syndrome and depression (Gallant et al., 2012 ; Graybeal et al., 2023 ; Gu et al., 2020 ; Tuncay & Sarman, 2024 ). Our results suggest that support measures aimed at tackling stress and providing resources for stress management and maintenance of health behaviors during stress are warranted. Such interventions could be of value not only in extreme circumstances but to help students navigate normative academic and educational environments while maintaining physical and psychological health. Abbreviations Body Mass Index (BMI) Academic Stress Induced by the COVID-19 Pandemic (ASIP) Financial Stress Induced by the COVID-19 Pandemic (FSIP) COVID-19 Exposure-Related Stress (CERS) Adult Eating Behavior Questionnaire (AEBQ) Revised Emotional Eating Scale with Boredom (REES-B) 4-item Perceived Stress Scale (PSS-4) 10-item Center of Epidemiologic Studies Depression Scale (CES-D-10) Perceived Support Questionnaire (PSQ) Declarations Ethics approval and consent to participate This study was approved by the Johns Hopkins University School of Medicine Institutional Review Board (IRB: NA_00092328) and all procedures were performed in accordance with relevant guidelines and regulations. All participants provided written informed consent. Consent for publication All participants provided written informed consent for the publication of anonymized data. No identifying personal information is included in this publication. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Conflict of interest S.C. declares previous research funding from Eli Lilly for a project unrelated to the current work. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This project was funded by a grant from the Woodrow Wilson National Fellowship Foundation awarded to O.A., with additional support for S.C. and the team from the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK136602 and R01DK113286). Credit authorship contribution statement O.A.O. : Conceptualization, Funding acquisition, Investigation, Data curation, Formal analysis, Project administration, Writing – original draft. S.H. : Formal analysis, Writing – review and editing. B.B. : Writing – review and editing. S.A.D. : Writing – review and editing. E.J. : Conceptualization, Methodology, Formal analysis, Supervision, Writing – review and editing. S.C. : Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Writing – review and editing. Acknowledgments O.A. would like to thank Natalie Strobach, the director of the Woodrow Wilson Fellowship program, for her support of this study. Supplementary material Supplementary material for this article can be found online at xxxxx. References Al-Musharaf, S. (2020). Prevalence and Predictors of Emotional Eating among Healthy Young Saudi Women during the COVID-19 Pandemic. 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S.C. declares previous research funding from Eli Lilly for a project unrelated to the current work. Supplementary Files SupplementarymaterialsBMCPH0310.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 13 Jun, 2025 Reviewers agreed at journal 23 Apr, 2025 Reviewers invited by journal 20 Apr, 2025 Editor invited by journal 13 Mar, 2025 Editor assigned by journal 12 Mar, 2025 Submission checks completed at journal 12 Mar, 2025 First submitted to journal 10 Mar, 2025 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6196663\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":428577425,\"identity\":\"430dd685-95d7-4534-bd7c-1ebaff54bf1a\",\"order_by\":0,\"name\":\"Olufisayo Atanda-Ogunleye\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Johns Hopkins University School of Medicine\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Olufisayo\",\"middleName\":\"\",\"lastName\":\"Atanda-Ogunleye\",\"suffix\":\"\"},{\"id\":428577426,\"identity\":\"40a877cf-07ae-432c-a541-2d0b1790ef52\",\"order_by\":1,\"name\":\"Shuxian Hua\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Johns Hopkins University School of Medicine\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shuxian\",\"middleName\":\"\",\"lastName\":\"Hua\",\"suffix\":\"\"},{\"id\":428577427,\"identity\":\"b86ad735-3793-4387-9573-e2400a8f48c2\",\"order_by\":2,\"name\":\"Bianca Borsarini\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Johns Hopkins University School of Medicine\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Bianca\",\"middleName\":\"\",\"lastName\":\"Borsarini\",\"suffix\":\"\"},{\"id\":428577429,\"identity\":\"1a787328-542b-4b2a-a607-64bbf2736003\",\"order_by\":3,\"name\":\"Sarah Ann Duck\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Johns Hopkins University School of Medicine\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sarah\",\"middleName\":\"Ann\",\"lastName\":\"Duck\",\"suffix\":\"\"},{\"id\":428577431,\"identity\":\"3e94062b-ef1a-4798-a6e4-b356245977ac\",\"order_by\":4,\"name\":\"Elena Jansen\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Johns Hopkins University School of Medicine\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Elena\",\"middleName\":\"\",\"lastName\":\"Jansen\",\"suffix\":\"\"},{\"id\":428577432,\"identity\":\"50ae0c33-486d-4117-9296-bdef6810f830\",\"order_by\":5,\"name\":\"Susan Carnell\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYJADxgMPKtgSGJiBTB5i9RxIOEOylsQ2hgQwC58W+RnpDz8XMNjJm89uPnAgcR5fnm47A+ODt224tRjcyDGWnsGQbDjnzrGEA4nb2IrNDjMwG87Fp0Uih0Gah+EA4wyJHAOQlsRthxnYpHnxaAE67PFvoBb7GRL5Hw4kzgFrYf+NTwvDjQQzkC2JQFuAZAPEFmZ8WgzOvDGz5jFITp4hkWZwIOEYSAtjs+Scc3gc1p7++DZPhZ3tDInkhw8+1BxL3Hb+8MEPb8rwOAxiF5x1DIgZGwipRwE1JKkeBaNgFIyCkQEAXalRvWyVc1wAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Johns Hopkins University School of Medicine\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Susan\",\"middleName\":\"\",\"lastName\":\"Carnell\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-03-10 14:53:14\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6196663/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6196663/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":78529619,\"identity\":\"5148db4f-a40e-465b-a68d-4dbe502a2fc3\",\"added_by\":\"auto\",\"created_at\":\"2025-03-14 13:52:15\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1653746,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6196663/v1/282bb78f-ae18-4784-924e-999b9c10c13e.pdf\"},{\"id\":78528165,\"identity\":\"0b7eddfa-1ea8-4807-b3ee-425026533e00\",\"added_by\":\"auto\",\"created_at\":\"2025-03-14 13:36:15\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":26600,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementarymaterialsBMCPH0310.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6196663/v1/b568a7914c5776aae748d6c9.docx\"}],\"financialInterests\":\"Competing interest reported. S.C. declares previous research funding from Eli Lilly for a project unrelated to the current work.\",\"formattedTitle\":\"The Impact of COVID-19-Related Stress on Diet and Eating Behaviors in US College Students: A Cross-Sectional Study\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eThe COVID-19 pandemic caused a global decline in psychological health, resulting in what some have described as a psychiatric epidemic (Gloster et al., \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Hossain et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Evidence suggests that populations experienced increasing levels of stress, depression, and anxiety stemming from pandemic-related psychosocial stressors such as diminished social support and anxiety regarding COVID-19 exposure (Gloster et al., \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Hossain et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). College students are known to experience poor psychological health outcomes, and the pandemic introduced additional stressors impacting both their academic and personal lives (Wang et al., \\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). During periods of heightened stress, college students are susceptible to changes in dietary intake and eating habits (Errisuriz et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e; Pelletier et al., \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). For instance, increased stress among college students has been associated with changes in eating patterns that may negatively impact health, including increased rates of meal skipping and late-night eating (Pelletier et al., \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e), as well as greater consumption of unhealthy snacks and fast food (Errisuriz et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). Such dietary and behavioral changes during young adulthood can have long-term consequences, including elevated risks of type 2 diabetes and poorer mental health, as suggested by other studies of COVID-19 impacts (Hussein \\u0026amp; Soliman, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Rogers et al., \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eDespite the uniquely stressful experiences college students underwent during the pandemic, the impact of COVID-19-related stress on their diet and eating behaviors has not been comprehensively investigated. A few studies found that social isolation and online learning during the pandemic posed challenges (e.g., changes to learning environments, job searches, and the ability to afford treatments) and resulted in increased stress with concomitant effects on diet and eating behaviors among college students (Amatori et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Huber et al., \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; LaCaille et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). However, findings have been heterogeneous, with some reports of increased consumption of bread and sweets, decreased intake of legumes and low-fat meat, and larger portion sizes, but other reports of healthier dietary choices such as eating more fiber-rich foods, like fruit and vegetables (Amatori et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Dhammawati et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Huber et al., \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; LaCaille et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). These conflicting results highlight the complexity of stress-related dietary responses and the potential role of individual differences in eating behaviors during the pandemic. Although changes in diet and eating behaviors among youth during the pandemic have been extensively studied across different cultural contexts (Amatori et al., \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Galali, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Huber et al., \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Imaz-Aramburu et al., \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Jia et al., \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Kołota \\u0026amp; Głąbska, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; LaCaille et al., \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e), few studies have examined how these changes relate to underlying psychological factors, such as stress (Elsalem et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Furthermore, much of the existing research has focused on documenting behavioral shifts without identifying the specific stressors responsible for these changes among young populations (Imaz-Aramburu et al., \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Jehi et al., \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Jia et al., \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Kołota \\u0026amp; Głąbska, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Pung et al., \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). For example, compared to before the pandemic, healthier eating behaviors and more consistent meal patterns were reported in some studies (Duong et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Rafraf et al., \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), while others have reported an increased intake of high-energy foods and less healthy foods, along with higher rates of binge eating, emotional eating, meal skipping, unhealthy snacking, and food insecurity (Coakley et al., \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Elsalem et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Jehi et al., \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Pung et al., \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). These inconsistencies underscore the need for further research to examine how different aspects of COVID-19-related stress (e.g., academic pressures, financial hardships, risk of exposure) may have influenced diet and eating behaviors among college students.\\u003c/p\\u003e \\u003cp\\u003eThe current study aimed to address some of the research gaps outlined above by comprehensively investigating the relationships of COVID-19-related stress with dietary intake and eating behaviors via a survey conducted in a large, ethnically diverse sample of US undergraduates during the Fall 2020 semester. Our overarching hypothesis was that increased pandemic-related stress would be associated with higher consumption of less healthy foods (e.g., sweets, savory snacks, fast food, sugar-sweetened beverages) and potentially adverse eating behaviors (e.g., emotional eating, emotional overeating, and late-night eating). Based on previous evidence suggesting stronger relationships between stress and both eating behaviors of food eaten among women (Degroote et al., \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e; Zellner et al., \\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e), and higher rates of binge eating in women (Rosenbaum \\u0026amp; White, \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e), we additionally explored sex differences in associations of stress with diet and eating behaviors.\\u003c/p\\u003e\"},{\"header\":\"2. Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1. Participants and Procedure\\u003c/h2\\u003e \\u003cp\\u003eA cross-sectional survey was distributed between November and early December 2020 to undergraduate students (N\\u0026thinsp;=\\u0026thinsp;758, \\u003cem\\u003eM\\u003c/em\\u003e \\u003csub\\u003e \\u003cem\\u003eage\\u003c/em\\u003e \\u003c/sub\\u003e = 18.38\\u0026plusmn;1.31; 70.1% female; see Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e for further demographic information) at a medium-sized Mid-Atlantic university, as well as some additional undergraduate students from other universities using a listserv. The survey included questions about dietary intake, eating behaviors, social support, overall psychological health status, and COVID-19-related stress during the Fall mid-semester. Participants were entered into a draw to win a \\u003cspan\\u003e$\\u003c/span\\u003e50 Amazon gift card upon completing the survey. The study was approved by the Johns Hopkins Institutional Review Board (IRB: NA_00092328).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eSample characteristics\\u003c/em\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eN (%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"4\\\" rowspan=\\\"5\\\"\\u003e \\u003cp\\u003eYear in university (n\\u0026thinsp;=\\u0026thinsp;758)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFreshman/First-year undergraduate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e262 (34.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSophomore/Second-year undergraduate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e171 (22.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eJunior/Third-year undergraduate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e175 (23.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSenior/Fourth-year undergraduate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e143 (18.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFifth year or more undergraduate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7 (0.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eSex assigned at birth (n\\u0026thinsp;=\\u0026thinsp;757)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e224 (29.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e531 (70.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePrefer not to say\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2 (0.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"7\\\" rowspan=\\\"8\\\"\\u003e \\u003cp\\u003eRace (n\\u0026thinsp;=\\u0026thinsp;757)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBlack\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e68 (9.0%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eWhite\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e209 (27.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHispanic/Latin (identify solely this way)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e41 (5.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNative Hawaiian/ Pacific Islander\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1 (0.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAsian\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e293 (38.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMixed\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e125 (16.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eOther\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8 (1.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eDecline to Answer\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12 (1.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"7\\\" rowspan=\\\"8\\\"\\u003e \\u003cp\\u003eAge group (n\\u0026thinsp;=\\u0026thinsp;757)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e15 (2.0%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e223 (29.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e173 (22.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e180 (23.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e134 (17.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e28 (3.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e23\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3 (0.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eOlder than 25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1 (0.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eBMI (excluding outliers, n\\u0026thinsp;=\\u0026thinsp;481)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eUnderweight, BMI\\u0026thinsp;\\u0026lt;\\u0026thinsp;18.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e40 (8.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHealthy weight, BMI 18.5\\u0026ndash;24.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e331 (68.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eOverweight, BMI 25.0\\u0026ndash;29.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e99 (20.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eObesity, BMI\\u0026thinsp;\\u0026gt;\\u0026thinsp;30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11 (12.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"3\\\"\\u003e\\u003cem\\u003eNote: Totals for each characteristic may not equal the overall sample size of 758 due to missing or incomplete data for some variables. BMI: body mass index.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2. Measures\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.1. Demographics and Self-Reported Weight and Height\\u003c/h2\\u003e \\u003cp\\u003eStandard demographic information, including age, race, sex assigned at birth, and year in university, was collected. Participants were also asked to report their weight and height, which were used to calculate body mass index (BMI).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.2. COVID-19-Related Stress\\u003c/h2\\u003e \\u003cp\\u003eTo measure COVID-19-related stress, questions were adapted from a previous study (Sadler et al., \\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e), focusing on three main components:\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003ea. Academic Stress Induced by the COVID-19 Pandemic (ASIP)\\u003c/b\\u003e: Stress related to factors such as compulsory online learning, the negative impact of isolation measures on academic performance, and changes in career prospects.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eb. Financial Stress Induced by the COVID-19 Pandemic (FSIP)\\u003c/b\\u003e: Stress related to factors such as job loss, financial instability, and health insurance costs.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003ec. COVID-19 Exposure-Related Stress (CERS)\\u003c/b\\u003e: Stress related to concerns about contracting COVID-19 personally or someone they know being affected.\\u003c/p\\u003e \\u003cp\\u003eThe questions used to measure each stressor category are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e. The final measure consisted of 19 items, grouped as follows:\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eCOVID-19-Related Stressors Measures a) ASIP, b) FSIP, and c) CERS.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"1\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ea) ASIP question: How stressed are you about the following?\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1. My academic performance will be or is being negatively impacted by the COVID-19 pandemic\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e2. The new layout of my classes (all online, all in-person, online \\u0026amp; in-person) will affect or has affected my ability to succeed in courses\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e3. Being unable to concentrate on school activities due to your learning environment OR fearing that you will be unable to concentrate on school activities in the future\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e4. Being unable to complete assignments due to your learning environment OR fearing you will be unable to complete assignments due to your learning environment\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e5. Being unable to get a job/internship\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e6. My GPA will drop due to the circumstances of this semester (COVID-19 pandemic, financial stability, bad learning environment, inability to work at home, etc.)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e7. Decreased productivity with schoolwork or school-related activities\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e8. Ongoing need for social isolation due to COVID-19 pandemic\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e9. Future job/career prospects\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e10. Changing plans as to reopening of schools (i.e., uncertainty of knowing whether the school would have in-person, online, or hybrid(in-person/online) classes)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eb) \\u003cb\\u003eFSIP question: How stressed are you about the following?\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1. Not being able to pay for basic needs (rent/mortgage, food, etc.)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e2. Losing my job\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e3. Someone I depend upon for income losing their job\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e4. I will be unable to access medical care for myself or my family\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e5. My family/I will be unable to pay for my college tuition\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ec) \\u003cb\\u003eCERS question: How stressed are you about the following?\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1. I will get COVID-19\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e2. A relative (e.g. grandparent) or close family friend will get COVID-19\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e3. Someone I live with will get COVID-19\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"1\\\"\\u003e\\u003cem\\u003eNote: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic; and CERS: COVID-19 exposure-related stress. Response options for all questions were rated on a 5-point Likert scale: Not at all (1), Slightly (2), Somewhat (3), Moderately (4), and Extremely (5).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cul\\u003e \\u003cli\\u003e \\u003cp\\u003e \\u003cb\\u003eASIP Score\\u003c/b\\u003e: 10 items, Cronbach\\u0026rsquo;s alpha\\u0026thinsp;=\\u0026thinsp;0.88;\\u003c/p\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cp\\u003e \\u003cb\\u003eFSIP Score\\u003c/b\\u003e: 6 items, Cronbach\\u0026rsquo;s alpha\\u0026thinsp;=\\u0026thinsp;0.78;\\u003c/p\\u003e \\u003c/li\\u003e \\u003cli\\u003e \\u003cp\\u003e \\u003cb\\u003eCERS Score\\u003c/b\\u003e: 3 items, Cronbach\\u0026rsquo;s alpha\\u0026thinsp;=\\u0026thinsp;0.80.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/ul\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe mean score for each stress variable was used in the analyses.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.3. Dietary Intake\\u003c/h2\\u003e \\u003cp\\u003eStudents reported their consumption of various food categories in the past 7 days as described in Sadler et al. (\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). Participants estimated their frequency of consuming sweets/desserts (e.g., chocolate, cookies, doughnuts, ice cream), chips/savory snacks (e.g., regular or low-fat chips, salty snacks), fast food (e.g., McDonald\\u0026rsquo;s), and servings of fruits and vegetables. Response ranged from \\u0026ldquo;Never\\u0026rdquo; to \\u0026ldquo;6 or more times per day.\\u0026rdquo; Intake was reported as weekly frequency or servings. A \\u0026ldquo;junk food intake\\u0026rdquo; variable was calculated by summing servings of sweets, savory snacks, fast foods, and sweetened beverages consumed.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.4. Eating Behaviors\\u003c/h2\\u003e \\u003cp\\u003eStudents reported perceived changes since before the semester in the frequency of eating, the amount of food eaten, and health of diet. They also reported on late-night eating behavior in the past 7 days. Four subscales from the Adult Eating Behavior Questionnaire (AEBQ) (Hunot et al., \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e) assessed food responsiveness, satiety responsiveness, emotional overeating, and emotional undereating, using a 5-point Likert scale (1\\u0026thinsp;=\\u0026thinsp;Strongly Disagree to 5\\u0026thinsp;=\\u0026thinsp;Strongly Agree). An adapted Revised Emotional Eating Scale with Boredom (REES-B) (Koball et al., \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e) assessed emotional eating related to four emotions (\\u0026ldquo;bored,\\u0026rdquo; \\u0026ldquo;sad,\\u0026rdquo; \\u0026ldquo;anxious,\\u0026rdquo; and \\u0026ldquo;stressed\\u0026rdquo;) on a 5-point scale from \\u0026ldquo;Never\\u0026rdquo; to \\u0026ldquo;Very Often,\\u0026rdquo; with average scores calculated.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.5. Psychological Health\\u003c/h2\\u003e \\u003cp\\u003eStress levels were measured using the 4-item Perceived Stress Scale (PSS-4) (Herrero \\u0026amp; Meneses, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e), which asked about perceived control, confidence, and feelings of overwhelm. Responses ranged from \\u0026ldquo;Never\\u0026rdquo; to \\u0026ldquo;Very Often,\\u0026rdquo; and average scores were calculated. Depression was assessed with the 10-item Center of Epidemiologic Studies Depression Scale (CES-D-10) (Andresen et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e1994\\u003c/span\\u003e), where participants indicated the frequency of depressive symptoms over the past week.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e2.2.6. Social Support\\u003c/h2\\u003e \\u003cp\\u003eThe Perceived Support Questionnaire (PSQ) (Lin et al., \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e) assessed perceptions of social security, safety, and a personal community of support. Participants rated six statements on a 5-point scale (1\\u0026thinsp;=\\u0026thinsp;Strongly Disagree to 5\\u0026thinsp;=\\u0026thinsp;Strongly Agree).\\u003c/p\\u003e \\u003cp\\u003eA more detailed overview of all measures and questionnaire is provided in the Supplementary Materials (\\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003elink to Supplementary Data\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3. Statistical Analyses\\u003c/h2\\u003e \\u003cp\\u003eStatistical analyses were conducted using IBM SPSS Statistics version 27 (IBM SPSS Statistics for Windows). Due to the nonparametric distribution of most responses, Spearman\\u0026rsquo;s correlations were used to assess bivariate relationships between COVID-19-related stress and dietary intake and eating behaviors. ASIP, FSIP, and CERS variables were categorized into Low, Moderate, and High Stress based on tertiles. Chi-square tests (χ\\u0026sup2;) examined associations between stress levels and perceived changes in eating behaviors from pre- to mid-semester. Additional chi-square tests assessed sex-based differences in perceived changes in eating behaviors.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1. Sample Characteristics\\u003c/h2\\u003e \\u003cp\\u003eSample characteristics are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. The distribution of participants across university years was relatively even, with slightly more freshmen (34.6%). The sample was predominantly female (70.1%) and consisted largely of first-year undergraduate students (34.6%), with a mean age of 18.38\\u0026plusmn;1.31 years. The majority of participants fell within the healthy weight range (68.8%), with a mean BMI of 22.28\\u0026plusmn;3.11.\\u003c/p\\u003e \\u003cp\\u003ePsychological health and social support measures and related statistics are reported in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e. The highest mean scores on pandemic-related stress were observed for ASIP (3.78\\u0026plusmn;0.85), followed by CERS (3.46\\u0026plusmn;1.02) and then FSIP (2.12\\u0026plusmn;0.89).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eMedian and Mean (SD) Scores for Psychological Health and Social Support Variables\\u003c/em\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVariables\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMedian\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eMean (SD)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003ePandemic-related stressors\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eASIP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.78 (0.85)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFSIP\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2.12 (0.89)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCERS\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.67\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.46 (1.02)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003ePsychological health\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCES-D-10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e14.50 (6.10)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePSS-4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3.30 (0.73)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSocial support\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003ePSQ\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e22.20 (4.60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u003cem\\u003eNote: SD: standard deviation; CERS: COVID-19 exposure-related stress (range: 1\\u0026ndash;5); FSIP: financial stress induced by the COVID-19 pandemic (range: 1\\u0026ndash;5); ASIP: academic stress induced by the COVID-19 pandemic (range: 1\\u0026ndash;5); CES-D-10: Center of Epidemiologic Studies Depression Scale (range: 10\\u0026ndash;40); PSS-4: 4-item Perceived Stress Scale (range: 1\\u0026ndash;5); PSQ: Perceived Support Questionnaire (range: 6\\u0026ndash;30).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2. Relationship between COVID-19-Related Stress and Dietary Intake\\u003c/h2\\u003e \\u003cp\\u003eCorrelations between COVID-19-related stress and dietary intake in the past 7 days are described below (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eSpearman\\u0026rsquo;s Correlations (ρ) and 95% CIs Between COVID-19-Related Stressors and Dietary Intake Over the Past 7 Days in Whole Sample, Males, and Females.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"13\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCOVID-19-Related Stressors\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c4\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eJunk Food Intake\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c7\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eFruit and Vegetable Intake\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c10\\\" namest=\\\"c8\\\"\\u003e \\u003cp\\u003eFast Food Intake\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c13\\\" namest=\\\"c11\\\"\\u003e \\u003cp\\u003eSweets Intake\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eWhole sample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eWhole sample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eWhole sample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003eWhole sample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eASIP\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.092*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.01, .17)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-0.026\\u003c/p\\u003e \\u003cp\\u003e(-.18, .13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.16*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.06, .26)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-0.037\\u003c/p\\u003e \\u003cp\\u003e(-.12, .05)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.11\\u003c/p\\u003e \\u003cp\\u003e(-.05, .26)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-0.12*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(-.22, \\u0026minus;\\u0026thinsp;.02)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.13*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.04, .21)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.014\\u003c/p\\u003e \\u003cp\\u003e(-.14, .17)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.19**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.09, .28)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.091*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.0, .17)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e-0.007\\u003c/p\\u003e \\u003cp\\u003e(-.16, .14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.14*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.04, .23)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eCERS\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003cp\\u003e(-.08, .08)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-0.126\\u003c/p\\u003e \\u003cp\\u003e(-.27, .03)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.062\\u003c/p\\u003e \\u003cp\\u003e(-.04, .16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-0.011\\u003c/p\\u003e \\u003cp\\u003e(-.10, .07)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.053\\u003c/p\\u003e \\u003cp\\u003e(-.10, .21)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e-0.055\\u003c/p\\u003e \\u003cp\\u003e(-.15, .05)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.048\\u003c/p\\u003e \\u003cp\\u003e(-.04, .13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.063\\u003c/p\\u003e \\u003cp\\u003e(-.09, .22)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.055\\u003c/p\\u003e \\u003cp\\u003e(-.05, .16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e-0.003\\u003c/p\\u003e \\u003cp\\u003e(-.09, .08)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-0.15*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(-.30, .00)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.058\\u003c/p\\u003e \\u003cp\\u003e(-.04, .16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eFSIP\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.016\\u003c/p\\u003e \\u003cp\\u003e(-.07, .10)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e-0.018\\u003c/p\\u003e \\u003cp\\u003e(-.17, .13)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.047\\u003c/p\\u003e \\u003cp\\u003e(-.05, .15)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-\\u003c/b\\u003e0.037\\u003c/p\\u003e \\u003cp\\u003e(-.12, .05)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.063\\u003c/p\\u003e \\u003cp\\u003e(-.09, .22)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-0.11*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(-.21, \\u0026minus;\\u0026thinsp;.01)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.10*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.02, .19)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.038\\u003c/p\\u003e \\u003cp\\u003e(-.12, .19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.14*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.04, .24)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.035\\u003c/p\\u003e \\u003cp\\u003e(-.05, .12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e-0.015\\u003c/p\\u003e \\u003cp\\u003e(-.17, .14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.060\\u003c/p\\u003e \\u003cp\\u003e(-.04, .16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"13\\\"\\u003e\\u003cem\\u003eNote: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic; CERS: COVID-19 exposure-related stress.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"13\\\"\\u003e\\u003cem\\u003eSignificant differences (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) are bolded. *p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, **p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"13\\\"\\u003e\\u003cem\\u003eJunk food includes sweet and savory snacks, fast food, and sugar-sweetened beverages.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"13\\\"\\u003e\\u003cem\\u003eConfidence intervals (CI) are presented in parentheses.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.2.1. ASIP\\u003c/h2\\u003e \\u003cp\\u003eAs shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, higher ASIP was correlated with increased intake of junk food (ρ\\u0026thinsp;=\\u0026thinsp;0.092, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), fast food (ρ\\u0026thinsp;=\\u0026thinsp;0.13, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), and sweets (ρ\\u0026thinsp;=\\u0026thinsp;0.091, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) in the past 7 days. Among females, higher ASIP was correlated with increased consumption of fast food (ρ\\u0026thinsp;=\\u0026thinsp;0.19, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) and sweets (ρ\\u0026thinsp;=\\u0026thinsp;0.14, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) and decreased consumption of fruits and vegetables (ρ = -0.12, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), while no significant associations were observed for males.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.2.2. FSIP\\u003c/h2\\u003e \\u003cp\\u003eFSIP was positively associated with fast food intake (ρ\\u0026thinsp;=\\u0026thinsp;0.10, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) in the past 7 days (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). Among females, higher FSIP correlated with increased fast food consumption (ρ\\u0026thinsp;=\\u0026thinsp;0.14, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) and decreased fruit and vegetable intake (ρ = -0.11, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). No significant associations were observed for males.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.2.3. CERS\\u003c/h2\\u003e \\u003cp\\u003eCERS showed no significant overall associations with dietary intake in the past 7 days for any food group (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). However, one significant relationship was observed among males, such that higher CERS was correlated with lower sweets intake (ρ = -0.15, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05).\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3. Relationship between COVID-19-Related Stress and Eating Behaviors\\u003c/h2\\u003e \\u003cp\\u003eCorrelations between COVID-19-related stress and eating behaviors, including emotional eating, emotional overeating, food responsiveness, and late-night eating, are described below (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab6\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003ea and Table\\u0026nbsp;\\u003cspan refid=\\\"Tab6\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003eb).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ea. Spearman\\u0026rsquo;s Correlations (ρ) and 95% CIs Between COVID-19-Related Stressors and Eating Behaviors in Whole Sample, Males, and Females\\u003c/em\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"10\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCOVID-19-Related Stressors\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c4\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eREES B Emotional Eating\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c7\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eAEBQ Emotional Overeating\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c10\\\" namest=\\\"c8\\\"\\u003e \\u003cp\\u003eAEBQ Food Responsiveness\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eWhole sample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eWhole sample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eWhole sample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eMales\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eFemales\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eASIP\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.34**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.25, .41)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.28**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.13, .42)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.36**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.26, .44)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.16**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.07, .24)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.13\\u003c/p\\u003e \\u003cp\\u003e(-.03, .28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.16*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.06, .26)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.078\\u003c/p\\u003e \\u003cp\\u003e(-.01, .16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.24*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.09, .39)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003cp\\u003e(-.10, .11)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eCERS\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.17**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.08, .25)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.17*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.01, .32)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.16*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.06, .26)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.086*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.00, .17)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.066\\u003c/p\\u003e \\u003cp\\u003e(-.09, .22)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.093\\u003c/p\\u003e \\u003cp\\u003e(-.01, .19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.12*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.03, .20)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.17*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.01, .31)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.088\\u003c/p\\u003e \\u003cp\\u003e(-.01, .19)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eFSIP\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.26**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.18, .34)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.28**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.12, .42)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.25**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.15, .34)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.16**\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.07, .24)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.19*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.03, .34)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.14*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.04, .24)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.11*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.02, .19)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.22*\\u003c/b\\u003e\\u003c/p\\u003e \\u003cp\\u003e\\u003cb\\u003e(.06, .36)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e0.061\\u003c/p\\u003e \\u003cp\\u003e(-.04, .16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"10\\\"\\u003e\\u003cem\\u003eNote: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic; CERS: COVID-19 exposure-related stress; REES B: Revised Emotional Eating Scale with Boredom and Emotions Experienced; AEBQ: Adult Eating Behavior Questionnaire.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"10\\\"\\u003e\\u003cem\\u003eSignificant differences (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) are bolded. *p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05, **p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"10\\\"\\u003e\\u003cem\\u003eConfidence intervals (CI) are presented in parentheses.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eb. Chi-Square Tests (χ\\u0026sup2;) of Associations Between COVID-19-Related Stressors (tertiles) and Late-Night Eating in the Past 7 Days.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eASIP and Late-Night Eating\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eASIP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eLess than half of diet consumed after dinner\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eAbout half of diet consumed after dinner\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eMore than half of diet consumed after dinner\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;26.79, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e172 (39.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e25 (27.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9 (16.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e150 (34.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e37 (40.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e16 (28.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e110 (25.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e30 (32.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e31 (55.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eFSIP and Late-Night Eating\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eFSIP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eLess than half of diet consumed after dinner\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eAbout half of diet consumed after dinner\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eMore than half of diet consumed after dinner\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;25.57, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e165 (38.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26 (28.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e14 (25.0%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e145 (33.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e24 (26.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10 (17.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e122 (28.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42 (45.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e32 (57.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003e\\u003cem\\u003eNote: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.1. ASIP\\u003c/h2\\u003e \\u003cp\\u003eHigher ASIP was correlated with heightened scores on scales assessing maladaptive eating behaviors. Specifically, ASIP was positively associated with emotional overeating (ρ\\u0026thinsp;=\\u0026thinsp;0.16, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) and with eating in response to a range of emotions, such as boredom, worry, nervousness, and stress (ρ\\u0026thinsp;=\\u0026thinsp;0.34, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). A positive correlation between ASIP and food responsiveness (ρ\\u0026thinsp;=\\u0026thinsp;0.24, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) was observed among males only, while a positive correlation with emotional overeating was found among females only (ρ\\u0026thinsp;=\\u0026thinsp;0.16, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). Additionally, higher ASIP was significantly associated with an increased frequency of late-night eating episodes, as indicated by greater food consumption after dinner (β\\u0026thinsp;=\\u0026thinsp;26.79, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec20\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.2. FSIP\\u003c/h2\\u003e \\u003cp\\u003eHigher FSIP was correlated with eating in response to a range of emotions (ρ\\u0026thinsp;=\\u0026thinsp;0.26, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), emotional overeating (ρ\\u0026thinsp;=\\u0026thinsp;0.16, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), and food responsiveness (ρ\\u0026thinsp;=\\u0026thinsp;0.11, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). The correlations for eating in response to emotions and emotional overeating were apparent in both males and females, whereas the association with food responsiveness was observed only in males (ρ\\u0026thinsp;=\\u0026thinsp;0.22, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) and not in females. Similar to ASIP, higher FSIP was associated with an increased occurrence of late-night eating episodes, as reflected by elevated food intake after dinner (β\\u0026thinsp;=\\u0026thinsp;25.57, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec21\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.3. CERS\\u003c/h2\\u003e \\u003cp\\u003eHigher CERS was correlated with eating in response to a range of emotions (ρ\\u0026thinsp;=\\u0026thinsp;0.17, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), emotional overeating (ρ\\u0026thinsp;=\\u0026thinsp;0.086, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), and food responsiveness (ρ\\u0026thinsp;=\\u0026thinsp;0.12, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). A positive association between CERS and food responsiveness was observed in males (ρ\\u0026thinsp;=\\u0026thinsp;0.17, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) but not in females.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec22\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.4. Perceived Changes in Eating Behaviors\\u003c/h2\\u003e \\u003cp\\u003eCorrelations between COVID-19-related stress and perceived change in eating behaviors from pre-semester to mid-semester, including changes in diet quality, frequency of eating, and the amount of food consumed are described below (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab7\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e). Higher ASIP was associated with a perceived less healthy diet (β\\u0026thinsp;=\\u0026thinsp;15.94, p\\u0026thinsp;=\\u0026thinsp;0.003) since before the semester started. Furthermore, higher ASIP was associated with changes in the frequency of eating (β\\u0026thinsp;=\\u0026thinsp;26.79, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), with students experiencing greater academic stress reporting both increases and decreases in their eating frequency. Higher FSIP was associated with a perceived lower amount of food consumed (β\\u0026thinsp;=\\u0026thinsp;10.43, p\\u0026thinsp;=\\u0026thinsp;0.034), and a perceived lower eating frequency (β\\u0026thinsp;=\\u0026thinsp;15.45, p\\u0026thinsp;=\\u0026thinsp;0.004). No associations of CERS with perceived change from pre- to mid-semester were observed.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab7\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 6\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eChi-Square Tests (χ\\u0026sup2;) of Associations Between COVID-19-Related Stressors (tertiles) and Perceived Change in Eating Behaviors from Pre- to Mid-Semester.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eASIP and Perceived Change in Health of Diet\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eASIP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating less healthily\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating equally healthy\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating more healthily\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;15.94, p\\u0026thinsp;=\\u0026thinsp;0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e81 (28.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e63 (45.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e51 (42.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e100 (35.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e43 (31.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e40 (33.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e100 (35.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e32 (23.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e29 (24.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eASIP and Perceived Change in Frequency of Eating\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eASIP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating less frequently\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eSame eating frequency\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating more frequently\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;26.79, p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e84 (32.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e52 (50.0%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e58 (33.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e91 (34.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e33 (31.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e59 (34.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e87 (33.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e19 (18.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e55 (32.0%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eFSIP and Perceived Change in Amount of Food Consumed\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eFSIP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating less food\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating about the same amount of food\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating more food\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;10.43, p\\u0026thinsp;=\\u0026thinsp;0.034\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e64 (28.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e62 (41.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e62 (37.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e66 (29.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e46 (30.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e54 (32.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e92 (41.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e43 (28.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e49 (29.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eFSIP and Perceived Change in Frequency of Eating\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eFSIP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating less frequently\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eSame eating frequency\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating more frequently\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;15.45, p\\u0026thinsp;=\\u0026thinsp;0.004\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e77 (29.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e51 (49.0%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e60 (34.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e83 (31.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22 (21.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e60 (34.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh stress\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e102 (38.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e31 (29.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e52 (30.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"5\\\"\\u003e\\u003cem\\u003eNote: ASIP: academic stress induced by the COVID-19 pandemic; FSIP: financial stress induced by the COVID-19 pandemic.\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eFurther analyses examining sex differences (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab8\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e) revealed notable variations in eating behavior changes during the COVID-19 period. Females were more likely to report changes in both the amount of food consumed (β\\u0026thinsp;=\\u0026thinsp;8.55, p\\u0026thinsp;=\\u0026thinsp;0.014) and the frequency of eating (β\\u0026thinsp;=\\u0026thinsp;6.88, p\\u0026thinsp;=\\u0026thinsp;0.032), whether increases or decreases. In contrast, males were more likely to report stability in their eating behaviors over the same period.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab8\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 7\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eChi-Square Tests (χ\\u0026sup2;) for Associations Between Sex and Perceived Change in Eating Behaviors from Pre- to Mid-Semester\\u003c/em\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eRelationship between Sex and Perceived Change in Amount of Food Consumed\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating Less Food\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating About the Same Amount of Food\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating More Food\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;8.55, p\\u0026thinsp;=\\u0026thinsp;0.014\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e52 (23.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56 (37.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e53 (32.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e170 (76.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e95 (62.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e112 (67.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"5\\\" nameend=\\\"c5\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eRelationship between Sex and Perceived Change in Frequency of Eating\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating Less Frequently\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eSame eating frequency\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eEating more frequently\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003eχ\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;6.88, p\\u0026thinsp;=\\u0026thinsp;0.032\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e70 (26.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42 (40.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e49 (28.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e192 (73.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e62 (59.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e123 (71.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eWe aimed to investigate the impact of COVID-19-related stress on the diet and eating behaviors of US college students during the Fall 2020 semester and explore sex differences within the sample. Our primary research hypothesis was that COVID-19-related stress levels would be associated not only with unhealthy dietary patterns but also with potentially maladaptive eating behaviors.\\u003c/p\\u003e \\u003cp\\u003eConsistent with our prediction, our primary findings indicate that several different types of COVID-19-related stress was associated with potentially maladaptive eating behaviors and less healthy dietary profiles. Specifically, COVID-19-related academic and financial stress were positively associated with fast food consumption and negatively associated with fruit and vegetable intake in females. All three COVID-19 stressors \\u0026mdash; academic (ASIP), financial (FSIP), and COVID-19 exposure (CERS) \\u0026mdash; were positively associated with emotional eating in both males and females. Additionally, stress was positively associated with food responsiveness in males.\\u003c/p\\u003e \\u003cp\\u003eASIP emerged as the most influential COVID-19-related stressor (Mean \\u003csub\\u003eASIP\\u003c/sub\\u003e = 3.78\\u0026plusmn;0.85, range: 1\\u0026ndash;5). ASIP components included changes in class formats, difficulty concentrating on schoolwork and activities, social isolation, and concerns about the impact on future careers. In line with our findings, another study on 843 US college students reported a link between academic stress levels and worsened psychological health as a consequence of COVID-19 (Barbayannis et al., \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). A likely cause of this is the abrupt transition from traditional in-person classroom settings to remote learning, which led to isolation, a decrease in outdoor extracurricular activities and interpersonal exchange, and disturbances in sleep patterns, likely partly driven by (and a contributor to) the concurrent increases in stress, anxiety, and depression among college and high education students (Nano et al., \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; Son et al., \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Tahir et al., \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eWe specifically found that COVID-19-related academic stress was positively associated with junk food consumption and negatively associated with fruit and vegetable intake, particularly among females. Although our findings indicate a poorer dietary profile under pandemic-related stress, studies in other populations have reported the opposite, potentially reflecting pre-existing differences in nutrition and daily dietary patterns. For instance, one study found increased unhealthy food consumption among Italian students, while junk food consumption decreased among French students (Caso et al., \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Similarly, studies in Spain and Croatia observed increased vegetable and fruit consumption during the lockdown, with students adhering more closely to Mediterranean Diet guidelines than in pre-pandemic times (Dragun et al., \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Imaz-Aramburu et al., \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). These contradictory findings highlight the influence of cultural context (e.g., dietary patterns) and cross-country differences in pandemic responses. Meanwhile, we found that increased ASIP was linked to greater emotional eating in both males and females. This aligns with pre-pandemic reports showing that low academic self-esteem and increased academic worries are more prevalent among emotional eaters than non-emotional eaters (Chamberlin et al., \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eStress related to the potential consequential risks of virus exposure (i.e. CERS), such as concerns about one\\u0026rsquo;s own or loved ones\\u0026rsquo; health after having contracted COVID-19, was rated high in our study (Mean \\u003csub\\u003eCERS\\u003c/sub\\u003e = 3.46\\u0026plusmn;1.02, range: 1\\u0026ndash;5). Exposure stress was also positively associated with emotional eating and food responsiveness, especially in males, indicating a degree of psychological deterioration. However, the associations with emotional eating were weaker than those observed with academic stress. Nevertheless, our results align with other findings among emerging adults in the US, which reported weaker associations between pandemic-related health stress (both self and for close others) and impaired psychological health compared to financial and educational-related stress in this population (Kujawa et al., \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eFinancial stress induced by the pandemic (FSIP) scored the lowest, as compared to other COVID-19-related stressors, among college students (Mean \\u003csub\\u003eFSIP\\u003c/sub\\u003e = 2.12\\u0026plusmn;0.89, range: 1\\u0026ndash;5). This is likely because many college students in our sample were relying primarily on household income, student loans, and scholarships and were not (yet) working as full-time employees, buffering them from the immediate impacts of financial stress. However, despite this relatively lower financial stress, significant associations with dietary intake were observed. Specifically, FSIP was negatively associated with fruit and vegetable intake and positively associated with fast food intake among females, highlighting a shift toward less healthy and more affordable food options. These effects are likely influenced by broader systemic factors, including the economic challenges, food access disparities, and inflation brought about by COVID-19. Notably, during the pandemic, grocery prices for fresh fruits and vegetables rose disproportionately compared to the prices of fast food in the US, potentially intensifying these dietary shifts (Volpe et al., \\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Such economic disparities were particularly evident in low-income school districts, which faced significant challenges in accessing primary goods and emergency nutrition programs during the pandemic, contributing to increased malnutrition rates and poorer dietary variety among students (Hall et al., \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; McLoughlin et al., \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). Additionally, lower family income was found to be associated with greater emotional eating in a population of healthy Saudi Arabian female students, suggesting that the financial environment can indeed increase the risk of potentially pathological eating behaviors (Al-Musharaf, \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e). In our study, higher levels of FSIP were linked to a perceived reduction in food consumption and less frequent eating, further indicating food insecurity among university students experiencing greater stress over financial situations (Bruening et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eOur sample consisted predominantly of healthy-weight college students (72%). This is noteworthy since a large amount of the existing literature linking emotional eating and stress suggests that employing food to manage distress is more common among individuals with obesity and overweight (Burnatowska et al., \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; Cecchetto et al., \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Dakanalis et al., \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). The effects we observed may therefore potentially be stronger in a sample including a greater proportion of individuals with higher body weight.\\u003c/p\\u003e \\u003cp\\u003eIn our investigation, we additionally explored sex differences in the impacts of pandemic-related stress on diet and eating behaviors. Our results suggest female students appeared to be slightly more susceptible to expressing distress associated with the pandemic via maladaptive eating habits and unhealthy diets compared to males. This predominant female vulnerability is coherent with previous analogous evidence within young populations (Ulloa et al., \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThis study has several limitations. First, being cross-sectional, it is unable to determine the causal relationship of interest. Second, there is potential for recall bias, as some questions required participants to remember their behaviors prior to the semester in order to compare them with the current behaviors (mid-semester). Third, our study largely relied on responses from an private Mid-Atlantic university where ethnic diversity is high but the socioeconomic status of participants is generally higher than the average American college student (Gregor Aisch et al., 2017; JHU Report on Undergradute Student Composition, 2023). The higher socioeconomic status of these participants may explain why financial COVID stress ranked as the lowest concern. Possibly, in a different population, financial stress could have been a more prominent source of COVID-19-related stress. Also, these findings might reflect a US-specific situation, considering that US, and even each state within the US, had a different approach to regulations compared to Europe. Lastly, our study did not investigate whether the relationship between COVID-19-related stressors and eating behaviors differs by weight status.\\u003c/p\\u003e \\u003cp\\u003eIn conclusion, our findings suggest that the unique concerns introduced by the abrupt and stressful COVID-19 pandemic, and in particular academic stress, significantly impacted not only dietary quality but also eating behaviors (especially eating in response to emotions and late-night eating) of college students, with effects varying between sexes. These results illuminate young adults\\u0026rsquo; susceptibility to different types of stress generated by a population-level health event and the detrimental impact of such stress on dietary health, as well as the development of potentially pathological eating behaviors. These behaviors may carry long-term risks, including an increased likelihood of metabolic syndrome and depression (Gallant et al., \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e; Graybeal et al., \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e; Gu et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e; Tuncay \\u0026amp; Sarman, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Our results suggest that support measures aimed at tackling stress and providing resources for stress management and maintenance of health behaviors during stress are warranted. Such interventions could be of value not only in extreme circumstances but to help students navigate normative academic and educational environments while maintaining physical and psychological health.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eBody Mass Index (BMI)\\u003c/p\\u003e \\u003cp\\u003eAcademic Stress Induced by the COVID-19 Pandemic (ASIP)\\u003c/p\\u003e \\u003cp\\u003eFinancial Stress Induced by the COVID-19 Pandemic (FSIP)\\u003c/p\\u003e \\u003cp\\u003eCOVID-19 Exposure-Related Stress (CERS)\\u003c/p\\u003e \\u003cp\\u003eAdult Eating Behavior Questionnaire (AEBQ)\\u003c/p\\u003e \\u003cp\\u003eRevised Emotional Eating Scale with Boredom (REES-B)\\u003c/p\\u003e \\u003cp\\u003e4-item Perceived Stress Scale (PSS-4)\\u003c/p\\u003e \\u003cp\\u003e10-item Center of Epidemiologic Studies Depression Scale (CES-D-10)\\u003c/p\\u003e \\u003cp\\u003ePerceived Support Questionnaire (PSQ)\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was approved by the Johns Hopkins University School of Medicine Institutional Review Board (IRB: NA_00092328) and all procedures were performed in accordance with relevant guidelines and regulations. All participants provided written informed consent.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll participants provided written informed consent for the publication of anonymized data. No identifying personal information is included in this publication.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConflict of interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eS.C. declares previous research funding from Eli Lilly for a project unrelated to the current work.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDeclaration of competing interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis project was funded by a grant from the Woodrow Wilson National Fellowship Foundation awarded to O.A., with additional support for S.C. and the team from the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK136602 and R01DK113286).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCredit authorship contribution statement\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eO.A.O.\\u003c/strong\\u003e: Conceptualization, Funding acquisition, Investigation, Data curation, Formal analysis, Project administration, Writing – original draft. \\u003cstrong\\u003eS.H.\\u003c/strong\\u003e: Formal analysis, Writing – review and editing. \\u003cstrong\\u003eB.B.\\u003c/strong\\u003e: Writing – review and editing. \\u003cstrong\\u003eS.A.D.\\u003c/strong\\u003e: Writing – review and editing. \\u003cstrong\\u003eE.J.\\u003c/strong\\u003e: Conceptualization, Methodology, Formal analysis, Supervision, Writing – review and editing. \\u003cstrong\\u003eS.C.\\u003c/strong\\u003e: Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Writing – review and editing.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eO.A. would like to thank Natalie Strobach, the director of the Woodrow Wilson Fellowship program, for her support of this study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSupplementary material\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSupplementary material for this article can be found online at xxxxx.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAl-Musharaf, S. (2020). Prevalence and Predictors of Emotional Eating among Healthy Young Saudi Women during the COVID-19 Pandemic. \\u003cem\\u003eNutrients\\u003c/em\\u003e, \\u003cem\\u003e12\\u003c/em\\u003e(10), 2923. https://doi.org/10.3390/nu12102923\\u003c/li\\u003e\\n\\u003cli\\u003eAmatori, S., Donati Zeppa, S., Preti, A., Gervasi, M., Gobbi, E., Ferrini, F., Rocchi, M. B. L., Baldari, C., Perroni, F., Piccoli, G., Stocchi, V., Sestili, P., \\u0026amp; Sisti, D. (2020). Dietary Habits and Psychological States during COVID-19 Home Isolation in Italian College Students: The Role of Physical Exercise. \\u003cem\\u003eNutrients\\u003c/em\\u003e, \\u003cem\\u003e12\\u003c/em\\u003e(12), 3660. https://doi.org/10.3390/nu12123660\\u003c/li\\u003e\\n\\u003cli\\u003eAndresen, E. M., Malmgren, J. A., Carter, W. B., \\u0026amp; Patrick, D. L. (1994). 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Hungry to learn: The prevalence and effects of food insecurity on health behaviors and outcomes over time among a diverse sample of university freshmen. \\u003cem\\u003eInternational Journal of Behavioral Nutrition and Physical Activity\\u003c/em\\u003e, \\u003cem\\u003e15\\u003c/em\\u003e(1), 9. https://doi.org/10.1186/s12966-018-0647-7\\u003c/li\\u003e\\n\\u003cli\\u003eBurnatowska, E., Surma, S., \\u0026amp; Olszanecka-Glinianowicz, M. (2022). Relationship between Mental Health and Emotional Eating during the COVID-19 Pandemic: A Systematic Review. \\u003cem\\u003eNutrients\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(19), 3989. https://doi.org/10.3390/nu14193989\\u003c/li\\u003e\\n\\u003cli\\u003eCaso, D., Miriam, C., Rosa, F., \\u0026amp; Mark, C. (2020). Unhealthy eating and academic stress: The moderating effect of eating style and BMI. \\u003cem\\u003eHealth Psychology Open\\u003c/em\\u003e, \\u003cem\\u003e7\\u003c/em\\u003e(2), 2055102920975274. https://doi.org/10.1177/2055102920975274\\u003c/li\\u003e\\n\\u003cli\\u003eCecchetto, C., Aiello, M., Gentili, C., Ionta, S., \\u0026amp; Osimo, S. A. (2021). Increased emotional eating during COVID-19 associated with lockdown, psychological and social distress. \\u003cem\\u003eAppetite\\u003c/em\\u003e, \\u003cem\\u003e160\\u003c/em\\u003e, 105122. https://doi.org/10.1016/j.appet.2021.105122\\u003c/li\\u003e\\n\\u003cli\\u003eChamberlin, A., Nguyen‐Rodriguez, S., Gray, V. B., Reiboldt, W., Peterson, C., \\u0026amp; Spruijt‐Metz, D. (2018). 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The Association of Emotional Eating with Overweight/Obesity, Depression, Anxiety/Stress, and Dietary Patterns: A Review of the Current Clinical Evidence. \\u003cem\\u003eNutrients\\u003c/em\\u003e, \\u003cem\\u003e15\\u003c/em\\u003e(5), 1173. https://doi.org/10.3390/nu15051173\\u003c/li\\u003e\\n\\u003cli\\u003eDegroote, C., Renner, B., Wickl, J., Leven, A., \\u0026amp; Wirtz, P. H. (2024). Eating After Acute Psychosocial Stress in Healthy Men and Women: Sex Differences and Endocrine Mechanisms. \\u003cem\\u003eThe Journal of Clinical Endocrinology \\u0026amp; Metabolism\\u003c/em\\u003e, \\u003cem\\u003e109\\u003c/em\\u003e(2), e543\\u0026ndash;e551. https://doi.org/10.1210/clinem/dgad578\\u003c/li\\u003e\\n\\u003cli\\u003eDhammawati, F., Fagerberg, P., Diou, C., Mavrouli, I., Koukoula, E., Lekka, E., Stefanopoulos, L., Maglaveras, N., Heimeier, R., Karavidopoulou, Y., \\u0026amp; Ioakimidis, I. (2023). 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Food prices in the United States during COVID-19: Generalized facts on price inflation and volatility. \\u003cem\\u003eBritish Food Journal\\u003c/em\\u003e, \\u003cem\\u003e126\\u003c/em\\u003e(13), 415\\u0026ndash;431. https://doi.org/10.1108/BFJ-05-2023-0421\\u003c/li\\u003e\\n\\u003cli\\u003eWang, C., Wen, W., Zhang, H., Ni, J., Jiang, J., Cheng, Y., Zhou, M., Ye, L., Feng, Z., Ge, Z., Luo, H., Wang, M., Zhang, X., \\u0026amp; Liu, W. (2023). Anxiety, depression, and stress prevalence among college students during the COVID-19 pandemic: A systematic review and meta-analysis. \\u003cem\\u003eJournal of American College Health\\u003c/em\\u003e, \\u003cem\\u003e71\\u003c/em\\u003e(7), 2123\\u0026ndash;2130. https://doi.org/10.1080/07448481.2021.1960849\\u003c/li\\u003e\\n\\u003cli\\u003eZellner, D. A., Loaiza, S., Gonzalez, Z., Pita, J., Morales, J., Pecora, D., \\u0026amp; Wolf, A. (2006). Food selection changes under stress. \\u003cem\\u003ePhysiology \\u0026amp; Behavior\\u003c/em\\u003e, \\u003cem\\u003e87\\u003c/em\\u003e(4), 789\\u0026ndash;793. https://doi.org/10.1016/j.physbeh.2006.01.014\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-public-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"pubh\",\"sideBox\":\"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/pubh/default.aspx\",\"title\":\"BMC Public Health\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"COVID-19 pandemic, stress, eating behaviors, dietary intake, nutrition, academic performance, young adults\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6196663/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6196663/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eThe COVID-19 pandemic exposed the US population, including college students, to stress posing challenges to psychological and behavioral health. Previous studies have demonstrated that stress can promote unhealthy eating behaviors among college students. This study aimed to examine the relationships of pandemic-related stress with changes in diet and eating behaviors experienced by college students during the Fall 2020 semester.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003e758 college students in the Mid-Atlantic region of the US completed an online survey in November 2020. The survey assessed multiple dimensions of pandemic-related stress, diet, and eating behaviors, as well as measures of psychological health and social support.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003ePandemic-related stress, particularly academic stress, was correlated with less healthy dietary profiles and potentially maladaptive eating behaviors, including emotional eating and late-night eating. Associations between stress and dietary intake were stronger in females than males, whereas males showed stronger associations between stress and food responsiveness. Pandemic-related stress was associated with perceived changes in diet quality, frequency of eating, and amount of food consumed compared to since before the semester started.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e \\u003cp\\u003eAcademic stress during the pandemic had a negative impact on diet and eating behaviors among college students. Our results argue for interventions targeting academic stress in everyday contexts as well as potential future public health crises, to prevent negative impacts on students\\u0026rsquo; eating profiles that may in turn negatively impact health.\\u003c/p\\u003e\",\"manuscriptTitle\":\"The Impact of COVID-19-Related Stress on Diet and Eating Behaviors in US College Students: A Cross-Sectional Study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-03-14 13:36:10\",\"doi\":\"10.21203/rs.3.rs-6196663/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-13T18:15:54+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"250122865564502731263246508809247714896\",\"date\":\"2025-04-23T14:15:23+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-04-20T10:30:30+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-03-13T07:50:15+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-03-12T11:00:05+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-03-12T10:56:27+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Public Health\",\"date\":\"2025-03-10T14:39:44+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-public-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"pubh\",\"sideBox\":\"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/pubh/default.aspx\",\"title\":\"BMC Public Health\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"355e079d-bc05-47dd-9847-e2ac42c4d20f\",\"owner\":[],\"postedDate\":\"March 14th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-03-14T13:36:10+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-03-14 13:36:10\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6196663\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6196663\",\"identity\":\"rs-6196663\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}