Unveiling night eating syndrome: how it connects to mental health, insomnia, and quality of life in university students—a cross-sectional study

Abstract

Background

Night Eating Syndrome (NES) is a type of eating disorder that’s often overlooked, yet it can seriously impact mental health, sleep quality, and overall well-being. Despite its significance, research on NES—especially among university students—remains limited.

Objective

This study set out to determine how common NES is among university students in Jordan and explore its connections to mental health issues like depression, anxiety, and stress, as well as insomnia and overall quality of life.

Methods

This cross-sectional study involving a total of 1214 university students (average age: 22.73 ± 3.4 years). NES was identified using the Night Eating Questionnaire (NEQ), with a clinical cutoff score of ≥ 25. Mental health was assessed using the Depression Anxiety Stress Scale-21 (DASS-21), while insomnia levels were measured through the Insomnia Severity Index (ISI). To dig deeper into these relationships, we ran logistic regression analyses.

Results

NES was found to be highly prevalent, affecting 58.2% of participants in this study. Women were 1.94 times more likely to have NES than men (p-value < 0.001). Considering obese individuals as a reference category, overweight individuals had significantly higher odds of NES (B = 1.17, Exp(B) = 3.21, 95% CI 1.78, 5.78, p-value < 0.001), being approximately 3.2 times more likely to have NES. In contrast, individuals within the healthy BMI range (18.5–24.9 kg/m²) had a dramatically reduced likelihood of NES (B = -2.08, Exp(B) = 0.13, 95% CI 0.07, 0.22, p-value < 0.001), indicating an 87% reduction in NES risk compared to obese individuals. Compared to the reference category (never smokers), current smokers were significantly more likely to have NES (B = 1.02, Exp(B) = 2.78, 95% CI 1.77–4.39, p-value < 0.001), indicating that their odds of NES were approximately 2.8 times higher than those of never smokers. The former smokers demonstrated an even stronger association with NES (B = 2.60, Exp(B) = 13.43, 95% CI 8.16–22.12, p-value < 0.001), indicating that their odds of developing NES were approximately 13 times higher compared to never smokers.

Conclusion

This study highlights how widespread NES is among university students and sheds light on its strong ties to gender, BMI, smoking, physical activity, and stress levels. Given these findings, it’s clear that targeted efforts—like mental health screenings, smoking cessation programs, and stress management initiatives—are needed to help students improve their well-being and reduce NES risk.

Plain language summary

Night Eating Syndrome (NES) refers to the consumption of a large amount of food after dinner or waking up in the night to eat. We were interested in the question of how prevalent it is among Jordanian students of the university and whether it correlates with mental health, sleeping disturbances, and day-to-day well-being. Short, simple questionnaires were used to survey 1,214 Jordanian university students on NES, mood, stress, sleep, activity, and quality of life. Over fifty percent of the students were positive on NES. Females had a higher chance of having NES than males. NES was more frequently reported to occur among students who were smokers (particularly former smokers). Students who engaged in light physical activity were more likely to have a NES compared to those who were very active. The most evident psychological variable that was related to NES was stress, and depression, anxiety, insomnia, and quality of life were not significantly different between students with and without NES in our analyses. The results of such studies indicate that night eating and student well-being can be positively affected by the introduction of simple NES screening and stress-management, smoking-cessation, and physical-activity services in the context of student health.

Introduction

University students are particularly vulnerable to disordered eating behaviors due to the multiple stressors they experience, including academic pressure, disrupted sleep patterns, financial strain, and social influences (Solly et al. 2023). These factors significantly contribute to the development of irregular eating patterns and increase the risk of eating disorders, particularly Night Eating Syndrome (NES) (Gundogdu and Erdogdu Yildirim 2023; Hamdan et al. 2023). Although NES was gaining recognition, it was manifested by large food consumption in the evenings or nighttime and was commonly accompanied by mood disorders, stress and anxiety, sleeping problems, and weight becoming uncontrolled (Matsui et al. 2021); however, such NES remains poorly understood among university students and in Middle Eastern Population particularly (Lavery and Frum-Vassallo 2022). Recent epidemiological studies highlight the concerning prevalence of mental health issues and obesity-related conditions among university students. According to data from the American College Health Association (2016) and recent systematic review and metanalysis (Degasperi et al. 2024), 30.3% of students report sleep difficulties, 20.4% experience high levels of stress, 14.6% suffer from depression, and 16.3% have excessive obesity, all of which are key contributors to disordered eating patterns (American College Health 2016). Several studies have drawn connections between sleep disturbances, stress, weight gain, and depression, yet few have specifically addressed NES within this framework (Cooper et al. 2020; Tavolacci et al. 2015). A study involving 3,457 college students found that 52.8% were at risk for eating disorders, stress, and depression, with 26.3% reporting being on a diet, emphasizing the link between psychological distress and eating behavior (Tavolacci et al. 2015).

Albert Stunkard was the first to describe NES in 1955, where he reported tendencies of eating at night where some individuals incurred anxiety and psychological distresses (Stunkard et al. 1955). NES was originally identified as part of Eating Disorders Not Otherwise Specified (EDNOS), but was later categorized separately in DSM-5 in the same disorder group(American Psychiatric Association 2013; Kaur et al. 2022a; Widiger and Costa 2013). NES is characterized by evening hyperphagia, where ≥ 25% of daily caloric intake occurs after dinner, or nocturnal ingestion, defined as waking up to eat at least twice per week (Allison et al. 2010). Other diagnostic criteria are the morning anorexia, insomnia, and increased desire to eat at night as well as the concept that a person has to eat to be able to sleep (Gundogdu and Erdogdu Yildirim 2023).

The prevalence rates of NES vary widely, due to study design, geographic area and assessments instruments used despite the classification of NES as one of the prevalent diseases among the population of advanced age in the world (Galmiche et al. 2019). Recent Literature demonstrates an NES prevalence between 1 and 2% in the general population and up to 8.2% in clinical populations such as those with obesity or undergoing bariatric surgery (Kaur et al. 2022b; Lavery and Frum-Vassallo 2022). Notably, a Palestinian study with 475 participants in universities found that 29.7% of the respondents were NES, which indicates that the cultural patterns of the diet, stress, and sleep disturbances could be the reasons for obtaining such higher rates in the said annotation (Hamdan et al. 2023). Despite the emerging international interest in Night Eating Syndrome (NES), there is no recent university student level research that is conducted in Jordan on a national level. Such a lack represents a humongously big gap in knowledge, and casts a huge doubt as to how NES can be understood in this profoundly critical age group. There have been no national studies that comprehensively examine this issue generally in the country so far, and there is a burning need to find solutions to stop it since it affects health interventions in the region. Social-cultural aspects, such as habitual eating patterns and societal norms, influence youth eating behaviors, mental health, and lifestyle options (Monterrosa et al. 2020). In Middle Eastern societies, late-night social gatherings and communal eating traditions may reinforce nighttime food consumption, further increasing NES susceptibility (Zboun and Abu 2017). Additionally, mental health stigma may discourage students from seeking help for stress, anxiety, and depression, exacerbating their risk for NES (Sprake et al. 2018). The recognition of these factors is essential to formulating specific prevention and intervention programs that best suit the needs of such population (Gundogdu and Erdogdu Yildirim 2023).

This study aims to provide a comprehensive examination of its prevalence and associated psychological and lifestyle factors. Specifically, it seeks to determine the prevalence of NES among university students in Jordan and compare it with global estimates. Additionally, it will explore the relationship between the psychological factors and NES, including depression, anxiety, stress, and insomnia, to assess their impact on NES risk. Furthermore, the study will investigate the role of lifestyle factors, such as BMI, smoking status, physical activity levels, and academic discipline, in contributing to NES susceptibility.

By addressing these gaps, this research aims to generate evidence-based insights that could inform the development of targeted prevention and intervention strategies tailored to university students at risk of NES. Based on these objectives, this study hypothesizes that NES prevalence among Jordanian university students is comparable to or higher than global estimates. In addition, this research posits that there is a link between NES and mental health conditions (depression, anxiety, stress), and suggests that lifestyle factors, including BMI, smoking, and physical activity, could be important to the risk of NES. These findings could help to gain a deeper insight into the issue of NES in the Middle East and contribute to the development of future research and reduction policy related to addressing the effects of the phenomenon on young adults.

Methodology

Study design, participants and setting

This cross-sectional study was conducted between December 2023 and February 2024 across 15 universities in Jordan to assess the prevalence of Night Eating Syndrome (NES) and its associations with mental health indicators and lifestyle factors. A convenience sample was adopted in recruiting the participants via institutional email lists, university/student portals, and student and social media, ensuring broad representation. The convenience sampling method was used as a means to speed up, and minimize participant recruitment time, as a large number of participants from various universities across Jordan were recruited. This approach made the diversity of the sample feasible within the scope of time and budget, yet it yielded useful information on the prevalence of Night Eating Syndrome (NES) and its relations to mental Health and Lifestyle variables in a student population. Eligible participants were actively enrolled university students aged 18–35 years, with access to the internet to complete the survey. Students who were following a specialized diet, taking psychiatric medications that could influence eating behavior, or diagnosed with chronic diseases, severe mental disorders, or an eating disorder were excluded to minimize confounding variables. Participation was voluntary, and students were informed that they could withdraw at any time without consequences. To enhance participation, academic advisors and student organizations assisted in disseminating the study link and promoting participation. The study was approved by the Research Ethics Committee of the Faculty of Pharmacy and Medical Sciences at the University of Petra (Grand number: S/12/12/2023), and all procedures obeyed with the Declaration of Helsinki and STROBE guidelines (Shrestha 2012). Before participation, students provided informed consent through a digital form, and all responses were anonymized and stored securely to maintain confidentiality.

Data collection

This study implemented rigorous procedures to minimize selection and ensured that the findings were accurate and reliable. Following official approval from participating universities, the survey link was strategically embedded in authorized university platforms, ensuring secure access and preventing unauthorized participation. To maintain consistency, the activation and deactivation of participation links were synchronized across all institutions, ensuring all responses were collected within the same timeframe. The study intentionally included a diverse range of universities, representing both private and public institutions across Jordan, to enhance comprehensive national representation. By distributing the questionnaire uniformly across all universities and setting a strict deadline for survey completion, the study further reduced the potential for sampling bias. To preserve data integrity, extensive verification processes were applied, including cross-checking participant details such as age, gender, academic program, and year of study to detect and eliminate duplicate entries. The survey design included mandatory fields, ensuring that all required data were provided, thereby preventing missing responses and enhancing the completeness and reliability of the dataset. These measures collectively strengthened the validity and broader relevance of the findings, ensuring a robust and unbiased analysis of NES prevalence among Jordanian university students.

Sample size calculations

The minimum sample size required in this study was calculated using the Raosoft web-based power calculator using the strength of 50% power (www.raosoft.com/samplesize2025), a tool specifically designed for population-based surveys. Based on an estimated total student population of 344,796 registered in Jordanian universities for the 2022/2023 academic year (“Ministry of Higher Education & Scientific Research. Jordan”, 2023), the minimum possible sample size was determined to be 385 respondents, which allows sustaining the level of confidence of 95% and a margin of error of 5. This estimation aligns with established methodologies for cross-sectional survey designs, as outlined by (Kasiulevičius et al. 2006; McCrum-Gardner 2010). Given the variability in NES prevalence across different university settings, a larger sample size was targeted to enhance statistical power and account for potential non-response rates. Prior studies on NES among university students have reported substantial differences in prevalence estimates, reinforcing the need for a representative sample that accurately reflects the diversity of Jordan’s higher education landscape. To increase external validity and reduce selection bias, participants were proportionally distributed across public and private universities, ensuring balanced geographic representation and an equitable mix of students from various disciplines. To further refine the sampling strategy, previous research on NES prevalence among university students in neighboring regions was reviewed, revealing variability in prevalence rates influenced by stress levels, dietary habits, and socioeconomic background (Hamdan et al. 2023). This informed the decision to stratify participants based on key demographic and lifestyle factors, strengthening the generalizability of the findings and ensuring a more robust analysis of NES in the Jordanian university student population.

Study questionnaire

The online questionnaire used in this study consisted of five key sections, designed to comprehensively assess factors related to NES and its associated health impacts. Section one covered the demographic characteristics, including age, sex (gender) income, adapted from (Yahia et al. 2017a). The second section focused on NES assessment, utilizing a validated Arabic version of the Night Eating Questionnaire (NEQ). The third section measured health-related quality of life (HRQOL), while the fourth evaluated mental health status, assessing depression, anxiety, and stress using standardized scales. Finally, the fifth section addressed insomnia severity as a key sleep-related factor.

NES questionnaire

The original version of the Night Eating Questionnaire (NEQ) is a 14-item questionnaire, which was developed by (Allison et al. 2008), and its aim is to measure the main characteristics of NES. Participants were asked about their morning appetite, eating habits during the evening and nighttime, cravings, sleep disturbances related to eating behaviors, and mood patterns during nighttime eating episodes. Each item was rated on a five-point Likert scale, generating a total score ranging from 0 to 52 (Allison et al. 2008). To ensure cultural and linguistic validity, this study used the Arabic version validated by (Hamdan et al. 2023), which incorporates a clinical cut-off score of 25 for NES diagnosis. The current version proved to have an excellent internal reliability with 0.71 for Cronbach’s alpha and was specifically adapted for Arabic-speaking populations, enhancing the reliability and applicability of the assessment within the study’s target demographic.

Mental health assessment

The Depression, Anxiety and Stress Scale-21 (DASS-21) is a multidimensional self-report questionnaire developed to measure psychological distress in three domains (Henry and Crawford 2005). The scale consists of 21 items divided into three subscales, each containing seven items. Depression subscale measures symptoms that include dysphoria, hopelessness, self-depreciation, anhedonia, and fatigue. The anxiety subscale controls autonomic reaction, state of anxiety, and physiological issues such as muscle tension. The stress subscale is related to irritability, overreacting, impatience, and lack of ability to relax. Each item is rated on a four-point Likert scale, with scores summed to generate a total and subscale-specific scores. For this study, the validated Arabic version of DASS-21, adapted for Jordanian adults, was employed to ensure linguistic and cultural appropriateness. For this study, the validated Arabic version of the DASS-21, translated and psychometrically assessed by (Moussa et al. 2017), was used to ensure linguistic accuracy and cultural relevance. Each subscale of the DASS-21 is scored by summation of its individual item scores with higher scores representing more psychological distress. The intensity of the symptoms is then rated by the classification of the score of each of the subscales. It is categorized as follows on the depression subscale: 0–9 (normal), 10–13 (mild), 14–20 (moderate), 21–27 (severe) and 28–42 (extremely severe). The categories for the anxiety subscale are 0–7 (normal), 8–9 (mild), 10–14 (moderate), 15–19 (severe), 20–42 (extremely severe). The same is true for the stress subscale that is classified as: 0–14 (normal), 15–18 (mild), 19–25 (mod), 26–33 (severe), 34–42 (extremely severe). These categories allow for the categorization of each participant’s psychological distress severity and helps in interpreting the results from the perspective of the present study.

Physical activity level assessment

Physical activity outcomes were estimated using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), a validated instrument for measuring the level of physical activity among various populations (Craig et al. 2003). The seven items in the questionnaire assess the frequency and time spent doing walking, moderate- and vigorous-intensity activities over the seven days before recruitment (Lee et al. 2011). These activities are categorized into different domains, including leisure-time physical activity, domestic and gardening tasks, work-related activity, and transport-related activity (Al-Hazzaa 2007). Physical activity scores were quantified into Metabolic Equivalent of Task (MET) scores, according to IPAQ standard scoring: walking activity = 3.3 METs score; moderate-intensity activity = 4.0 METs score; and vigorous-intensity activity = 8.0 METs score (IPAQ Research Committee 2004). The total physical activity score was computed as the sum of MET-minutes per week, with individuals categorized into low, moderate, or high physical activity levels according to established IPAQ criteria (Forde 2018). Given its widespread validation, the Arabic-translated and validated version of the IPAQ-SF was used to ensure linguistic and cultural appropriateness for Jordanian university students (Hamdan et al. 2023). To enhance reliability, we followed IPAQ data cleaning and truncation rules, excluding unrealistic values (e.g., physical activity durations exceeding 16 h per day) and standardizing all reported activity to weekly MET-minutes (IPAQ Research Committee 2004). This approach minimizes reporting bias and ensures consistency in physical activity assessment.

Insomnia severity index (ISI) assessment

The Insomnia Severity Index (ISI), developed by (Morin et al. 2011), is a widely used self-report instrument designed to assess the severity and impact of insomnia. This 7-item questionnaire evaluates multiple aspects of sleep disturbances, including difficulty with sleep onset, sleep maintenance, early morning awakenings, dissatisfaction with sleep quality, interference with daily functioning, perceived noticeability of sleep difficulties by others, and distress caused by sleep disturbances. Each item is rated on a 5-point Likert scale ranging from 0 (no problem) to 4 (very severe problem), generating a total score ranging from 0 to 28 (Morin et al. 2011; Suleiman and Yates 2011). Based on established cutoff scores, total ISI scores were classified as 0–7, no clinically significant insomnia, 8–14, subthreshold insomnia, 15–21, moderate clinical insomnia, and 22–28, severe clinical insomnia (Morin et al. 2011). To ensure cultural relevance and linguistic accuracy, we utilized the validated Arabic version of the ISI, which was translated and adapted by (Suleiman and Yates 2011) following the back-translation method (Suleiman and Yates 2011). This version demonstrated strong internal consistency (Cronbach’s α = 0.84) and was validated against other sleep measures, including the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS), reinforcing its reliability for use in Arabic-speaking populations (Suleiman and Yates 2011). The ISI was administered as part of the broader study questionnaire, with participants instructed to recall their sleep experiences over the past month to provide an accurate assessment of their insomnia symptoms.

Health-related quality of life (HRQOL) assessment

Health-Related Quality of Life (HRQOL) was assessed by the Arabic translations of the 12-Item Short-Form Health Survey (SF-12) questionnaire, which is the commonly known instrument to measure the mental and physical status of different populations (Haddad et al. 2021). The SF-12 consists of 12 items that generate two composite scores: the Physical Component Summary (PCS-12) and the Mental Component Summary (MCS-12), both of which have demonstrated strong validity and reliability across diverse populations (Ware 2003). The Arabic version used in this study has been previously validated in Middle Eastern populations, including Lebanon and Saudi Arabia, confirming its suitability for assessing HRQOL among Arabic-speaking individuals (Haddad et al. 2021). SF-12 measures eight general health domains, including: physical functioning, role limitations due to physical problems, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and mental health (Ware 2003). These dimensions are condensed into the PCS-12 and MCS-12 scores that span the range 0–100, with higher scores indicating a better health status. A PCS-12 of less than 50 has been generally accepted as the indicator of a physical health issue, whereas an MCS-12 of less than 42 is linked with clinical depression (Haddad et al. 2021). To ensure cultural and linguistic appropriateness, the Arabic SF-12 was administered in its validated format, maintaining the standardized scoring algorithm. This adaptation enhances the applicability of findings to Arabic-speaking university students while ensuring comparability with international HRQOL assessments.

Statistical analysis

All the statistical analysis was done using by means of IBM SPSS statistics Mac 25 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to report demographic and clinical characteristics expressed as mean ± SD and n (%). Besides the aforementioned methods of statistics, there was performing all necessary statistical checks on assumptions to confirm the sound results. The Shapiro-Wilk test confirmed the normality assumption and it was justified to use parametric tests for continuous variables. Levene’s test was carried out to assess homogeneity of variance, and this was not violated, thus the use of parametric tests was not cautioned about. In the multivariate analysis, various issues of multicollinearity have been evaluated with calculation of the Variance Inflation Factor (VIF) and all the predictors should be within the acceptable level of VIF (< 5). The goodness of fit of the model was also assessed using the Hosmer–Lemeshow goodness of fit test which indicates that the model fit the data suitably. Furthermore, the Wald backward stepwise method was used to improve the model by stepwise removal of non-significant predictors. Adjusted odds ratios (ORs) and 95% confidence intervals (CI) of predictors to Night Eating Syndrome (NES) were reported to quantify strength of associations between predictors and Night Eating Syndrome (NES). Univariate analyses were performed to explore relationships between NES and demographic and lifestyle as well as psychological factors. The multivariate logistic regression model was produced with variables with significant associations (p ≤ 0.05) from the univariate analysis to determine the independent predictors of NES. The choice of statistical methods is robust and reliable, and this corresponds to other NES research in the selection, and provides solid basis for findings.

Results

Prevalence, gender disparities, and sociodemographic factors associated with night eating syndrome among university students

Figure 1 illustrates how NES was distributed among the participants of the present study. As the findings indicated, more than half of the university learners who had participated in this study were at risk of developing NES. Importantly, a gender disparity in the prevalence of NES was observed in that 66.9% of participants were diagnosed with NES female as shown in Fig. 2. This result gives the impression that women are more at risk of developing NES in this study population. It was also observed that sociodemographic characteristics showed a notable association with NES, as shown in Table 1. The BMI categories between groups differed. Among NES participants, 62.5% were overweight and 16.4 classified as class I obese, with only 21.1% recorded as healthy within the BMI range. In contrast, most of the non-NES participants (87.6%) were healthy in terms of BMI (p ≤ 0.001). In addition, smoking habits were strongly correlated with NES with 58.1% of NES participants being never smokers which was significantly more than 21.2% (p ≤ 0.001) in the non-NES group. A lower proportion of postgraduate students were also identified in the NES group (21.7%), compared to the non-NES group (29.1%) (p ≤ 0.001). In addition, the differences between groups in the pattern of physical activities were also significant (p ≤ 0.001). 26% of NES participants reported performing Light activity compared with 70.1% of non-NES participants, whereas moderate activity was reported more among NES participants (54.0% vs. 16.4%). The intensive activity was higher in the NES group (19.1% and 13.5%).

Fig. 1.

Distribution of Night Eating Syndrome (NES) Among the Study Participants (n = 1214)

Fig. 2.

Gender Distribution of Night Eating Syndrome (NES) Among Study Participants (n = 1214)

Table 1.

Univariate analysis of sociodemographic characteristics and NES prevalence among study participants (n = 1,214)

Characteristic	Categories	All participants	Participants with NES (n = 706)	Participants without NES (n = 508)	p-value
Age (years mean ± SD)		22.73 ± 3.4	22.42 ± 3.24	22.95 ± 3.48	0.15 b
Gender	Male	446 (36.7)	234 (33.1)	212 (41.7)	≤ 0.001 a
	Female	768 (36.7)	472 (66.9)	296 (58.3)
BMI (mean kg/m2 ± SD)		34.4 ± 25.0	22.42 ± 1.63	27.76 ± 2.05	≤ 0.001 b
BMI categories	Healthy	594 (48.9)	149 (21.1)	445 (87.6)	≤ 0.001 a
	Overweight	488 (40.2)	441 (62.5)	47 (9.3)
	Class I obesity	132 (10.9)	116 (16.4)	16 (3.1)
Smoking status	Current	356 (29.3)	145 (28.5)	211 (29.9)	≤ 0.00 a
	Former	413 (34.0)	68 (13.4)	345 (48.9)
	Never smoked	445 (36.7)	295 (58.1)	150 (21.2)
Status	Single	804 (66.2)	479 (67.8)	352 (64.0)	0.23 a
	Married	386 (31.8)	216 (30.6)	170 (33.5)
	Other*	24 (2.0)	11 (1.6)	13 (2.6)
Field	Medical	743 (61.2)	332 (47.0)	411 (80.9)	≤ 0.001 a
	Non-medical	471 (38.8)	374 (53.0)	97 (19.1)
Education level	Undergraduate	913 (75.2)	553 (78.3)	360 (70.9)	≤ 0.001 a
	Postgraduate	301 (24.8)	153 (21.7)	148 (29.1)
Personal monthly income (JOD)	< 500	307 (25.3)	163 (23.1)	144 (28.3)	0.94 a
	500–1000	646 (53.2)	391 (55.4)	255 (50.2)
	> 1000	261 (21.5)	152 (21.5)	109 (21.5)
Living status	Off campus family home	1039 (85.6)	430 (84.6)	609 (86.3)	0.69 a
	Off campus apartment	119 (9.8)	52 (10.2)	67 (9.5)
	On campus	56 (4.6)	26 (5.1)	30 (4.2)
Physical activity (MET levels)	Light (< 3 MET)	627 (51.6)	132 (26.0)	495 (70.1)	≤ 0.001 a
	Moderate (< 3–6 MET)	395 (32.5)	279 (54.0)	116 (16.4)
	Vigorous (> 6MET)	192 (15.8)	97 (19.1)	95 (13.5)

Continuous variables are expressed as mean ± SD (standard deviation) and categorical variables are expected as frequency (percent). MET: Metabolic Equivalent for Task. BMI: Body Mass Index. BMI classification: Healthy weight (BMI:18.5–24.9 kg/m2), Overweight (BMI 25–29.9 kg/m2), Obese (BMI 30 kg/m2). * Divorced or widowed. ^a Chi-squared test. ^b independent t test. P-vale ≤ 0.005

Psychological distress, sleep patterns, and health-related quality of life among NES and Non-NES participants

As shown in Table 2, 28.4% of participants had normal depression levels, with no significant difference between those with NES (30.0%) and those without NES (26.2%). The distribution of depression severity categories (normal, mild, moderate, severe, and extremely severe) did not differ significantly between the two groups (p = 0.62). Similarly, 25.3% of participants had normal anxiety levels, with no significant difference between NES participants (26.6%) and non-NES participants (23.4%) (p = 0.60). The distribution of anxiety severity categories also showed no statistically significant differences between the two groups. However, there was a significant difference (p ≤ 0.001) in the stress level when comparing the participants with and without NES. The percentage of NES of severe (31.7%) and extremely severe (27.8%) stress was higher as opposed to the percentage of the non-NES who had severe (15.0%) and extremely severe (11.4%) stress. Notably, a lower percentage of NES participants had normal stress levels (5.1%) compared to non-NES participants (39.2%). Regarding insomnia, no significant difference was observed in its prevalence between NES and non-NES participants (p = 0.47). The distribution of insomnia severity categories (subthreshold, moderate clinical insomnia, and severe clinical insomnia) was similar between the two groups. Additionally, there were no significant differences in physical (PCS-12) and mental (MCS-12) health scores between NES and non-NES participants, nor were any statistically significant group differences observed.

Table 2.

Univariate analysis of mental health indicators, insomnia severity index (ISI), and health-Related quality of life (HRQOL) in relation to NES prevalence (n = 1,214)

Characteristic	Categories	All participants	Participants with NES (n = 706)	Participants without NES (n = 508)	p-value
Depression	Normal	345 (28.4)	212 (30.0)	133 (26.2)	0.62a
	Mild	164 (13.5)	96 (13.6)	68 (13.4)
	Moderate	379 (31.2)	211(29.9)	168 (33.1)
	Severe	154 (12.7)	89 (12.6)	65 (12.8)
	Extremely severe	172 (14.2)	98 (13.9)	74 (14.6)
Anxiety	Normal	307 (25.3)	188 (26.6)	119 (23.4)	0.60a
	Mild	96 (7.9)	56 (7.9)	40 (7.9)
	Moderate	291 (24.0)	172 (24.4)	119 (23.4)
	Severe	177 (14.6)	96 (13.6)	81 (15.9)
	Extremely severe	343 (28.3)	194 (27.5)	149 (29.3)
Stress	Normal	235 (19.4)	36 (5.1)	199 (39.2)	≤ 0.00a
	Mild	147 (12.1)	66 (9.3)	81 (15.9)
	Moderate	278 (22.9)	184 (26.1)	94 (18.5)
	Severe	300 (24.7)	224 (31.7)	76 (15.0)
	Extremely severe	254 (20.9)	196 (27.8)	58 (11.4)
Insomnia	No clinically insomnia	192 (15.8)	80 (15.7)	112 (15.9)	0.47a
	Subthreshold insomnia	517 (42.6)	210 (41.3)	307 (43.5)
	Clinical insomnia (moderate)	386 (31.6)	173 (34.1)	213 (30.2)
	Clinical insomnia (severe)	119 (9.8)	45 (8.9)	74 (10.5)
HRQOL	Physical health (PCS-12)	56.56 ± 10.44	56.96 ± 10.43	56.0 ± 10.45	0.90b
	Mental (MCS-12)	59.37 ± 13.0	59.75 ± 12.99	58.83 ± 13.0	0.48b

Categorical variables are expected as frequency (percent). The classification for Depression, Anxiety, and Stress (DASS 21) scores is as follows: Normal: Depression (0–9), Anxiety (0–7), Stress (0–14); Mild: Depression (10–13), Anxiety (8–9), Stress (15–19); Moderate: Depression (14–20), Anxiety (10–14), Stress (19–25); Severe: Depression (21–27), Anxiety (15–19), Stress (26–33); Extremely Severe: Depression (28+), Anxiety (20+), Stress (34+). The Total Score Categories for insomnia are defined as follows: 0–7: No clinically significant insomnia; 8–14: Subthreshold insomnia;15–21: Clinical insomnia (moderate severity);22–28: Clinical insomnia (severe). ^a Chi-squared test. ^b independent t test. HRQOL: Health-Related Quality of Life Scale. MCS: Mental Health Component Scale. PCS: Physical Health Component Scale. P-vale ≤ 0.005

Logistic regression analysis of NES-associated factors

The results of the binary logistic regression analysis identifying factors associated with Night Eating Syndrome (NES) are presented in Table 3. The regression model included sex, field of study, education level, smoking history, physical activity levels (MET), stress levels, and BMI categories, with statistical significance set at p ≤ 0.005. Sex differences remained a strong predictor, as female participants had significantly higher odds of NES (Exp(B) = 1.94, 95% CI 1.30–2.88, p < 0.001) compared to males. Regarding BMI categories, individuals with optimum BMI had significantly lower odds of NES (Exp(B) = 0.13, 95% CI 0.07–0.22, p < 0.001) compared to those in the obese category. However, overweight participants had a greater likelihood of having NES (Exp(B) = 3.21, 95% CI 1.78–5.78, p < 0.001) than the reference category, obese. Participants enrolled in medical fields had lower odds of NES (Exp(B) = 0.40, 95% CI 0.27–0.60, p < 0.001) than those in non-medical fields. Smoking history was significantly associated with NES risk. The odds of the current smokers for NES were elevated (Exp(B) = 2.78, 95% CI 1.77 4.39, p < 0.001) when compared to the nonsmokers. Former smokers also had an even greater odds (Exp[B] = 13.43, 95%: 8.1622.12, p < 0.001) compared to non-smokers. For physical activity levels, participants engaged in light-intensity sports had significantly higher odds of NES (Exp(B) = 7.37, 95% CI 4.42–12.30, p < 0.001) compared to those engaging in high-intensity sports. However, moderate-intensity sports were not significantly associated with NES (p = 0.58). Stress levels were also a critical factor in NES risk. Participants with normal stress levels had lower odds of NES (Exp(B) = 0.07, 95% CI 0.04–0.14, p < 0.001) compared to those experiencing extremely severe stress. Those with mild stress also had significantly lower odds (Exp(B) = 0.18, 95% CI: 0.09–0.36, p < 0.001). However, neither moderate (Exp(B) = 0.76, 95% CI 0.44–1.30, p = 0.31) nor severe stress (Exp(B) = 1.14, 95% CI 0.67–1.97, p = 0.63) were significantly associated with NES.

Table 3.

Logistic regression analysis of factors associated with night eating syndrome (NES) among study participants (n = 1,214)

	B	S.E.		Sig.	Exp(B)	95% C.I. EXP(B)
						Lower	Upper
Gender (Female)	0.66		0.20	≤ 0.001	1.94	1.30		2.88
Gender Male	Reference category
BMI (optimum)	−2.08		0.29	≤ 0.001	0.13	0.07		0.22
BMI (overweight)	1.17		0.30	≤ 0.001	3.21	1.78		5.78
BMI (obese)	Reference category
Field (Medical)	−0.92		0.20	≤ 0.001	0.40	0.27		0.60
Field (non- Medical)	Reference category
Smoking (current)	1.02		0.23	≤ 0.001	2.78	1.77		4.39
Smoking (former)	2.60		0.26	≤ 0.001	13.43	8.16		22.12
Smoking (never)	Reference category
Physical activity (light)	1.99		0.26	≤ 0.001	7.37	4.42		12.30
Physical activity (moderate)	−0.16		0.28	0.58	0.86	0.50		1.48
Physical activity (high)	Reference category
Normal stress level	−2.65		0.34	≤ 0.001	0.07	0.04		0.14
Mild stress level	−1.70		0.34	≤ 0.001	0.18	0.09		0.36
Moderate stress level	−0.28		0.27	0.31	0.76	0.44		1.30
Sever stress level	0.14		0.28	0.63	1.14	0.67		1.97
Extremely sever stress level	Reference category

Variable(s) entered on step 1 (the significant outcome of the univariate analysis): Gender, Field, Education Level, Smoking, Sport level (MET), Stress level groups and BMI categories. P-vale ≤ 0.005. MET: Metabolic Equivalent for Task. BMI: Body Mass Index. BMI classification: Healthy (BMI 18.5–24.9 kg/m2), Overweight (BMI 25–29.9 kg/m2), Obese (BMI 30 kg/m2)

Discussion

The prevalence of NES

To our knowledge, this comprehensive research is the first undertaking that explores the NES among Jordanian college students and its relation to various sociodemographic and psychosocial factors. The prevalence percentage of NES reported in this nation is 58.2%, which is substantially higher compared to the numbers recorded among various populations worldwide. The most recent study done on the Brazilian students of the university has given the prevalence of NES to be 16.8% (Dias Cavalcante Abreu et al. 2023). On the other hand, among Palestinian university exhibited a 29.7% prevalence (Hamdan et al. 2023). The results of an Egyptian study even put NES prevalence further down, at 1.2% (Yahia et al. 2017b), thus confirming the strong regional difference in that matte. Most recent epidemiological evidence indicates an immensely high prevalence of NES among university students in Jordan. Evening after-work parties, late fast-food restaurants, and the tradition of spending evenings together due to social practice may contribute improper hour circadian rhythm and the increased amount of consumed calories at night time. (Hamdan et al. 2023). Furthermore, high academic demands, working at odd hours, and the social permissibility to pursue extended academic activity or hang out at the night time pose a further challenge to the risk of NES (Yahia et al. 2017b). Appropriately, all of these findings provide evidence that the urbanized environment in Jordan, along with its availability to ultra-processed food items and fast academic rhythm of the academic setting, may be related to behavioral and neurobiological aspects as well, which have been proposed in prior studies as contributing to NES. The existing Literature supports a significant difference in gender distribution of the NES prevalence, as 66.9% of the affected subjects are women. The trend is consistent with past meta-analyses, which systematically report higher prevalence rates amongst women compared to men (Miraj et al. 2022). Such gender disparity may be related to a complex interplay of biological, psychological, and sociocultural factors. Fluctuations in hormonal levels, especially in estrogen, progesterone, and testosterone have been suggested to influence the food habits and rhythms and control of the circadian rhythm (Culbert et al. 2021). Emotional eating, body-image dissatisfaction, and disordered eating behaviors are more frequent during the reproductive years of women, which may contribute to their vulnerability to NES (Root et al. 2010a, b). On the contrary, some studies observe higher odds of NES in men and higher prevalence in those with higher energy demands, stress-coping discrepancies, and night-shift-related eating habits (Colles et al. 2007; Guo et al. 2020; He et al. 2019). In other studies, however, results do not show any meaningful gender differences (Meule et al. 2014). Such contrasting results point to the culturally specific depiction of NES expression, which is influenced by societal norms, nutritional habits, and socioeconomic conditions. Moreover, genetic research has revealed NES-binge eating disorder (BED) overlap, specifically in women, supporting the hypothesis of a possible biological basis of gender disparity in NES (Root et al. 2010).

Sociodemographic and lifestyle predictors

This evidence base shows that psychosocial stressors, such as academic pressure, emotional distress, and expectations of society on their body weight, disproportionately affect females compared to males, which further places them at a higher risk of developing maladaptive coping responses such as night eating (Culbert et al. 2021). In turn, the gender specific mediator of night eating will be better understood by the analysis of the biological, psychological, and environmental factors that interact across different populations. In addition to psychosocial stressors, lifestyle and sociodemographic variables are also key determinants of NES vulnerability in university students.

The current analysis provided details regarding connections between NES and sociodemographic factors, thus highlighting a complex relationship involving BMI, smoking status, physical activity levels, and academic attainment. There was also a different distribution of BMI categories, with the overweight group having an increased likelihood of NES and the healthy BMI group having a lower likelihood of NES than the obese reference group. Participants with a history of smoking (current or former) increased their chances of having NES by some significant margins as compared to the participants who have never smoked. Additionally, light physical activity did show an increased likelihood of NES, but moderate physical activity did not. Compared to vigorous physical activity, however, neither light nor moderate showed a significant association with NES. Logistic regression revealed that gender, BMI, field of study, smoking history, and sports involvement were main predictive factors of NES, which significantly contributed to the epidemiological patterns and social-behavioral predictors of the disorder.

An observation from the current research was that subjects with NES demonstrated a lower mean BMI than their non-NES counterparts. This finding challenges the traditional assumption that NES is commonly associated with higher BMI. A review of 11 studies by Bruzas and Allison (2019) had mixed findings: five studies found a significant relationship between NES and BMI, five did not and one reported incongruent result. Likewise, a further analysis of 12 studies of the review revealed that BMI was more in NES participants in five studies and did not prove significant differences in seven studies (Bruzas and Allison 2019).

The evidence suggests that the relationship between NES-BMI is multifactorial and dependent on number of factors as the population, the criteria of diagnostic assessment of physical states and patterns of behavior (Gallant et al. 2012). There is some evidence that the changes in weight related to NES may not be directly observed in the short term, but may connect with longer term trends on circadian misalignment and late day high calorie consumption (Gallant et al. 2012). In line with this view, Meule, Allison, and Brahren (2014) noted that the effects of higher BMI in NES as compared to the non-NES subjects were more prominent in older groups of people but not in younger age cohorts, Like in university students under 31 years of age, attributable to the comparatively short length of exposure to NES (Meule et al. 2014).

There are contravening pieces of evidence, displaying that there is a positive association amid NES and obesity-related practices. In a study of Malaysian university students, NES was found to be correlated with an increased consumption of calories above the daily energy requirement, followed by weight gain and a subsequent increase in BMI over a longer period (Elsahoryi et al. 2023; Kwan et al. 2021). Such discrepant results also support the need to conduct longitudinal studies that will help to evaluate whether NES has a long-term effect on body-weight control, especially in young adults, where NES started at recently and might not have yet resulted in weight changes that are measurable yet (Kwan et al. 2021).

The current study contributes to the knowledge of the NES-BMI interaction. Despite NES being associated with overeating, its direct effects on BMI do not seem to be keenly felt among the younger populations. The current data also illuminate the dynamic between circadian misalignment, energy balance, and compensatory eating behaviors in the context of determining this relationship, which should be examined further and particularly in Middle Eastern university students whose unique cultural and nutritional habits increase this association. The results indicated that smoking was significantly associated with NES, with both current and former smokers showing higher odds of this disorder compared to non-smokers. Lundgren et al. (2010), in their study of 2,217 participants, found similar results to the current study, with smoking being more prevalent among night eaters (51.4%). A similar relation was noted in one of the previous works (Provini et al. 2008). Nicotine has been proposed to affect dose regulation of appetite by inhibiting appetite and stimulating energy usage, which may be the basis of compensatory nighttime food consumption and craving (Perkins et al. 1992). These findings suggest the possibility of a behavioral/physiological connection between smoking and NES, which should be further investigated to understand the relevant mechanisms.

Neurobehavioral and psychological associations

The findings of this study suggest that there was a relationship between physical activity and the presence of NES with a varied pattern at different levels of activity. The odds of having NES was the greatest when the participants participated in light physical activity and significantly reduced when the participants did vigorous physical activity, thus a protective relationship may be indicated. Interestingly, our results diverge from previous studies, including those by (Nolan and Geliebter 2016; Striegel-Moore et al. 2006; Yahia et al. 2017b), which found no significant differences in physical activity levels between students with and without NES. Additionally, a recent study by Lent et al. (2022) reported that a higher NES score was associated with increased odds of engaging in moderate-to-vigorous physical activity (p = 0.005) (Lent et al. 2022). These conflicting results highlight the complexity of the relationship between NES and physical activity, as demonstrated in a scoping review by (Sakthivel et al. 2023), which analyzed six studies with varying findings (Hamdan et al. 2023; Hamurcu 2022; Lent et al. 2022; Yahia et al. 2017b). Possible explanations for these discrepancies include differences in assessment tools, sample sizes, and age groups. Another plausible explanation lies in modern lifestyle changes. Li (2022) emphasized that advancements in technology, the prevalence of food delivery services, and the reduction in daily physical movement may contribute to a more sedentary lifestyle, thereby increasing the risk of night eating due to greater accessibility to food during nighttime hours (Li 2021). The present findings are consistent with this viewpoint, with implications indicating that decreased physical activity can cause the energy imbalance and raised evening caloric consumption, which can relate to NES behaviors. Educational attainment and NES showed important trends in our study as well. However, a lower prevalence of NES was observed in Postgraduate students, possibly due to a high level of health awareness, better time management, and disciplined eating patterns. This contrasts with findings by (Latzer et al. 2020; Runfola et al. 2014), who reported no significant association between educational level and NES prevalence. Conversely, Abo El-Ela et al. (2022) found an opposing trend, where NES symptoms were more prevalent among individuals with higher education levels (OR = 2.33, P-value = 0.046) (Abo El-Ela et al. 2022). These findings point to the need for further research on this issue, as well as for universities and other educational institutions to integrate groups at greater risk for obesity and eating disorders into educational programs and initiatives focused on increasing nutritional awareness and building healthy behaviors. Additionally, the field of study emerged as a key determinant of NES risk, with significantly higher NES prevalence among students in non-medical fields. Logistic regression further confirmed that being enrolled in a medical program served as a protective factor against NES. However, despite this protective effect, a substantial proportion (47%) of NES-diagnosed students in our study were enrolled in medical fields. This aligns with findings by (Zaidi et al. 2020), who reported a similar NES prevalence of 49.36% among medical students in Karachi, Pakistan. These findings suggest that while medical education may foster greater awareness of healthy behaviors, academic stress and irregular schedules may still contribute to NES development among medical students. The interplay between NES and psychological factors remains a critical area of exploration. Contrary to expectations, our study found that stress was the only psychological variable significantly associated with NES, whereas depression, anxiety, insomnia, and health-related quality of life (HRQoL) did not show significant differences between NES and non-NES participants. This deviates from previous studies that have consistently demonstrated strong associations between NES and various psychological disorders. For example, Riccobono et al. (2019) reported a significant link between NES and depression among Italian adolescents (Riccobono et al. 2019), while Sevincer et al. (2016) documented a positive association between NES symptoms and both depression and anxiety (Sevincer et al. 2016). Abo El-Ela et al. (2022) found that NES was significantly correlated with the Insomnia Severity Index, anxiety, and depressive symptoms (Abo El-Ela et al. 2022), while Kim et al. (2023) reported lower HRQoL scores among individuals with NES (β = − 4.85, p < 0.001) in a nationwide study of Korean adults (Kim et al. 2023). In the current research, the relations between NES and depressive or anxiety-related outcomes were not notable and this fact should be stressed to refer to the factors of cultural or environmental aspects in these relations further. Stress, however, emerged as a primary predictor of NES in our study, aligning with previous research. Nolan and Geliebter (2012) emphasized that individuals experiencing high stress levels are more likely to engage in nocturnal eating as a coping mechanism for negative emotions (Nolan and Geliebter 2012). Similarly, Gan et al. (2019) found that being a stressed university student was a significant risk factor for NES (OR = 3.58, 95% CI 1.149–11.151) (Gan et al. 2019). Moreover, Person (2014) reported that NES severity increased in tandem with perceived stress levels (Person 2014), while Wichianson et al. (2009) found that there was a significant positive correlation between the perception of stress with NES symptoms (Wichianson et al. 2009). Such findings support the idea that stress is an influential factor in NES, and therefore, stress-management interventions should be suggested as a preventive strategy.

Conclusion

Findings of the current study may be useful in informing the prevalence and related variables of Night Eating Syndrome (NES) among Jordanian university students. The results suggested that NES was more prevalent in females and is associated with decreased BMI, smoking, low physical activity, and increased stress levels. The significant psychological factor that emerged during this research regarding NES is stress, which is contrary to the previous studies that have indicated depression and anxiety to be correlated with NES. These findings illustrate the intricate interrelations of behavioral, environmental and biological mechanisms behind NES in young adults. The high prevalence of NES in this population it is indicated that early screening and interventions of mental health for university students, particularly those with elevated stress is an urgent task. Results of the present study could be used in implementing interventions that consider the differences of gender as well as physical activities, and stress management as components of risk reduction to NES and its long-term effects. Therefore, future studies need to take a longitudinal design in order to determine causal relationships between hyperactivity and other contextual factors, including academic stressors and dietary behavior, which in turn might be implicated in the development of NES. These efforts may lead to developing evidence-based preventive strategies and management for the young adults with NES.

Strengths and limitations of the study

This study makes a significant contribution to the growing body of research on NES by examining its associations with a broad range of socio-demographic, lifestyle, and psychological predictors. By incorporating a diverse sample of university students from multiple institutions across Jordan, the study enhances the generalizability and applicability of its findings. The use of validated Arabic-language assessment tools further strengthens the reliability of the data. Moreover, rigorous statistical methodologies, including logistic regression, were employed to provide a robust analysis of NES predictors. Despite these strengths, certain limitations should be acknowledged. Using the online questionnaires that are based on self-report could have resulted in the recall and social desirability bias, and the increased prevalence of NES when compared with a clinical method of diagnosis was possible. Additionally, while efforts were made to control for confounding variables, factors such as seasonal variations, dietary intake, and exam-related stress were not explicitly accounted for, potentially influencing NES prevalence. To clarify NES processes, future studies are recommended to use longitudinal designs, objective dietary or sleep indicators, and examine the contextual factors associated with NES-related changes. Additionally, no objective measures of sleep or diet intake were present and seasonal effects (exam periods) were not considered.

Clinical implications

This study may have significant clinical and public health implications, as there could be multidisciplinary interventions to deal with NES in university students. Key recommendations include: Gender-Tailored could be Screened: Given the higher prevalence of NES in females, screening protocols should be sex-specific, integrating NES risk assessment into routine health check-ups for young adults. BMI Monitoring & Lifestyle Adjustments: Healthcare providers may consider regularly assess BMI and provide personalized lifestyle interventions to help at-risk individuals maintain a healthy weight and eating habits. Smoking Cessation Programs: Given the strong association between NES and smoking, targeted smoking cessation support could be incorporated into preventive and treatment plans. Promotion of Physical Activity: Encouraging moderate to high-intensity exercise as a protective factor against NES could be a key component of public health initiatives targeting young adults. Stress Management Interventions: Implementing cognitive-behavioral therapy (CBT), mindfulness training, and other stress-reduction techniques may help mitigate NES risk and improve mental well-being among university students. By integrating these strategies into university health programs and broader public health policies, the burden of NES could be effectively reduced, leading to improved physical and psychological health outcomes for young adults.

Author contributions

Nour Amin Elsahoryi developed the study concept, designed the methodology, supervised the data analysis, and led the manuscript writing. Mohammed O. Ibrahim provided oversight during the writing process and played a key role in data collection. Fadwa Hammouh was responsible for organizing and managing the collected data. Omar Amin Alhaj and Sara Al-Basha actively contributed to writing and refining the manuscript. All authors reviewed and approved the final version of the manuscript.

Funding statement

This study was carried out without an external grant. The authors have not been financially supported to conduct the research, write any part of the manuscript, or publish the article.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

The study received ethical approval from the Research Ethics Committee of the Faculty of Pharmacy and Medical Sciences at the University of Petra (Grant number: S/12/12/2023). Prior to participation, all students provided informed consent through a secure digital form, ensuring voluntary and ethical involvement in this study.

Consent for publication

Informed consent of all the participants was given to the anonymous publication of the study findings. Information that could be attributed to the participants was not collected or disclosed at all to provide anonymity.

Competing interests

The authors declare no competing interests.