Emotional eating is associated with premenstrual syndrome among university students in Palestine: A cross-sectional study

Abstract

Background:

Emotional eating is an abnormal eating behavior triggered by emotional states rather than physical hunger. It has been linked to various physiological, psychological, and lifestyle factors and is notably prevalent among females.

Objective:

This study aimed to examine the association between emotional eating and premenstrual syndrome symptoms among female university students in Palestine.

Design:

A cross-sectional study was conducted at Palestine Polytechnic University in the West Bank, Palestine, involving a sample of 450 female students.

Methods:

Data were collected through a structured, self-administered questionnaire comprising sections on sociodemographic characteristics, medical history, lifestyle behaviors, and nutrition-related information. Standardized instruments included The International Physical Activity Questionnaire to assess physical activity levels, The Mediterranean Diet Adherence Screener to evaluate dietary habits, The Emotional Eating Scale to measure emotional eating behavior, and The Arabic Premenstrual Syndrome Scale to assess the presence and severity of premenstrual syndrome symptoms.

Results:

A significant association was observed between emotional eating and the severity of premenstrual syndrome symptoms (p < 0.05), particularly within the psychological and behavioral domains. Emotional eating was most prevalent among participants with moderate psychological premenstrual syndrome symptoms (79.0%) and least prevalent among those without such symptoms (42.9%). Similarly, participants with mild overall premenstrual syndrome symptoms reported a high rate of emotional eating (77.3%), while those with no premenstrual syndrome symptoms had the lowest prevalence of emotional eating (25.0%). These findings suggest a gradient relationship between premenstrual syndrome symptom severity and emotional eating behaviors. No significant associations were identified between emotional eating and participants’ medical history, lifestyle characteristics, weight status, or dietary habits (p > 0.05).

Conclusion:

Emotional eating is significantly associated with premenstrual syndrome symptoms across multiple domains. These findings highlight the need for targeted interventions to manage premenstrual syndrome and reduce the risk of disordered eating behaviors among young women.

Short Summary

This study explored how emotional eating – eating in response to feelings rather than hunger – relates to premenstrual syndrome among female university students in Palestine. A total of 450 students from Palestine Polytechnic University completed questionnaires about their eating habits, physical activity, and premenstrual syndrome symptoms. The results showed that students who experienced stronger premenstrual syndrome symptoms were more likely to report emotional eating, especially when they had mood or behavior-related premenstrual syndrome symptoms. Emotional eating was least common among those without premenstrual syndrome. However, emotional eating was not linked to weight, lifestyle, or diet quality. These findings suggest that premenstrual syndrome may increase the likelihood of emotional eating, emphasizing the importance of supporting young women through education and strategies to manage mood and eating behaviors during the menstrual cycle.

Keywords

emotional eating premenstrual syndrome (PMS)university students Palestine

Introduction

Premenstrual syndrome (PMS) is the cluster of emotional, physical, and behavioral symptoms that arise around the end of the luteal phase and disappear at the beginning of menstruation or within a few days thereafter,¹ patients suffering from PMS exhibit a variety of symptoms such as mood swings, irritability, stress and anxiety, tiredness and trouble sleeping, bloating or abdominal pain, and changes in appetite.² Although its pathophysiology remains incompletely understood, proposed mechanisms include progesterone’s effects on neurotransmitter levels and action, hormonal imbalances, and stress-induced changes in uterine contractility.³ A recent meta-analysis estimated that nearly half of women worldwide experience PMS (47.8%),⁴ and studies within the university-aged population report rates exceeding 60% in countries such as Iran and Turkey,^5–7 especially among females with non-healthy eating habits, especially the western eating habits.⁸ Furthermore, a higher occurrence of PMS was shown among young Arab women compared to European woman.⁹

Emotional eating (EE) – defined as the tendency to consume food in response to negative emotions or stress – has been linked to bulimia nervosa, binge eating, and obesity,¹⁰ which has a proposed effect in other abnormal eating behaviors such as bulimia nervosa, binge eating, and obesity¹¹ with an increased rates of incidence and prevalence among females in comparison to males¹² and levels rise under elevated stress.¹³ Hormonal fluctuations during the luteal phase may further amplify this behavior in women with PMS.^14,15 Despite these connections, only a handful of Western-based studies have directly quantified the EE-PMS link,¹⁶ and none have adjusted for lifestyle factors such as physical activity and dietary adherence.

Based on identified gaps in the literature, it is hypothesized that higher EE scores will be independently associated with greater PMS symptom severity after controlling for physical activity and diet quality, and that lower adherence to a Mediterranean-style diet will be linked to both increased EE and more pronounced PMS symptoms. To investigate these associations, a cross-sectional study involving 450 Palestinian university women was carried out.

Methodology

Study design and sample size

A cross-sectional design was utilized in the present study. The sample size was determined using G Power software, taking into consideration an alpha level of 0.05 (two-sided), 80% power, where Beta equals 0.2. Based on a Lebanese study reporting 32.4% of severe EE,¹⁷ allowing a 10% absolute difference, 280 participants were required to evaluate the prevalence of EE. In addition, the sample size calculation considered the purpose of determining the association between EE and PMS, the following parameters were established: a moderate effect size of about Cohen’s d of 0.5, a level of significance or type I error of 0.05 (5%), and a power or type II error or (1 − β) of 0.8 (80%). The estimates for the sample size indicated that a minimum of 410 participants would be sufficient for the analysis. Considering the dropouts, the sample size was increased to 450 participants.

Ethics approval

This study protocol was approved by the Faculty of Scientific Research Ethical Committee, Palestine Polytechnic University (PPU), Palestine (Ref. no. KA/41/2021). Informed consent was taken from the participants to join the study. A written consent was stated at the beginning of the questionnaire that the participants signed. The study was conducted in accordance with the Declaration of Helsinki. All the collected information was kept secret and only used for research, allowing only the principal investigators and the study analyst to evaluate and conduct the proper statistical analysis. No reward was given to the participants.

Study population

The study was conducted at the PPU in Hebron, West Bank, Palestine. PPU is a medium-sized university enrolling ~6000–6999 students across six faculties (applied sciences, medicine and health sciences, engineering, information technology and computer engineering, administration sciences and information systems, and applied professions).

Participants who were included in this study are female PPU students aged between 18 and 18–25 years old. Exclusion criteria included pregnant females, those currently using a prescription of hypnotics, psychotropics, or hormonal medications, or those who refused to join the study.

Data collection

Data were collected between November 1 and December 31, 2021. Female undergraduates from various faculties were recruited using convenience sampling during regularly scheduled classes and university events. The estimated minimum sample size was 410 participants. A total of 450 invited students agreed to participate and completed the questionnaire, yielding a 100% completion rate among respondents. The exceptionally high response rate may be attributed to the questionnaire’s concise and user-friendly design and the fact that it was administered during students’ free time on campus. Participation was voluntary, with no incentives provided. Data collection occurred through self-administered questionnaires distributed in person under the supervision of trained researchers. The collected data included students’ sociodemographic information, medical history, lifestyle, dietary habits, physical activity, EE, and PMS-related data. All participants were verbally briefed about the study’s objectives and given written consents by the researchers. Only participants who signed the consent form were included in the data collection. The timeframe for the reported symptoms was the preceding luteal phase of the most recent menstrual cycle, based on self-reported cycle timing.

Study tools

A structured questionnaire consisting of two sections – a question-based component and an instrument-based section – was self-administered by female university students. The questionnaire covered the following topics: sociodemographic information (age, place of residence, number of family members, nature of housing, marital status, family income, year of study, faculty, study funding), medical history (chronic diseases, any previous surgical interventions, any medications, either regularly or occasionally), lifestyle characteristics (smoking status, type of smoking, sleeping pattern (napping and sleep troubles), and dietary behaviors (dieting, time of dieting, reason of diet, nutritional information source, and nutritional supplements).

Height, weight, body mass index (BMI), and body composition were among the anthropometric measurements taken. A measuring tape was fastened to the wall, and the height was measured to the nearest 0.5 cm. Weight was recorded to the nearest 0.1 kg on an electronic scale. BMI was computed by multiplying weight (kg) by height (m²). Then, classified according to World Health Organization guidelines, 18.5 is underweight, 18.5–24.99 is normal weight, 25–29.99 is overweight, and ⩾30 is obese.¹⁸ All of the equipment was calibrated, and the measurements were taken in accordance with industry standards. The measurements were taken twice more, and the average was taken.

The used questionnaire is validated and is largely adapted from previously validated instruments, including the International Physical Activity Questionnaire (IPAQ),¹⁹ Mediterranean Diet Adherence Screener (MEDAS),²⁰ Emotional Eating Scale (EES),¹⁷ and Arabic PMS Scale (A-PMS).²¹

International Physical Activity Questionnaire

The physical activity of participants was evaluated by the IPAQ. IPAQ is a self-administered tool designed for measuring physical activity in adults aged 16–69. The long IPAQ form that was used in this study is a 27-item questionnaire that included five activity domains: job-related physical activity, transportation physical activity, housework, house maintenance, caring for family, recreation, sport, leisure-time physical activity, and time spent sitting. For each domain, the respondent should answer the questions based on their vigorous and moderate activities during the last 7 days.²² IPAQ levels of physical activity are expressed as the categories (low: <600 MET-min/week, medium: 600–3000 MET-min/week, and high: >3000 MET-min/week) activity levels.²³ Scoring was done by an automatic spreadsheet.²⁴ The validated Arabic version of IPAQ was used in this study.¹⁹

Mediterranean Diet Adherence Screener

Participants’ adherence to Mediterranean lifestyle habits was assessed using the MEDAS, a validated tool. It includes 14 items on food consumption frequency. The questionnaire was translated into Arabic using a standard forward-backward translation method. Content validity was checked by an expert reference group (one nutritionist and two researchers), who agreed to delete one item, “alcohol consumption,” due to its cultural inapplicability in Arab populations. In the current study, each item was scored as 0 or 1, with a total score ranging from 0 to 14. Scores were then categorized into adherence levels based on tertiles as follows: low adherence: score 0–4, moderate adherence: score 5–9, and high adherence: score 10–14. Participants in the lowest tertile were considered to have low adherence to Mediterranean lifestyle habits.²⁰

Emotional Eating Scale

The EES was used to assess the prevalence of EE among female university students. EES is a validated tool designed to evaluate the tendency to overeat in response to specific negative emotions. It is composed of 25 items related to distinct emotions (e.g., discouragement, irritation, and anger), grouped into three subscales: anger/frustration, anxiety, and depression. Participants rated their desire to eat in response to each emotion on a five-point scale: no desire, small desire, moderate desire, strong urge, and overwhelming urge to eat.²⁵ Higher scores on each subscale indicate a higher tendency to eat in response to that emotional state. In this study, participants were classified as either normal eaters or emotional eaters based on their total EES score. Those with scores equal to or less than the sample median were categorized as normal eaters, while those with scores above the median were considered emotional eaters.²⁶ The Arabic version of EES, developed and validated by Rahme et al., was employed.¹⁷ It is important to note that the EES measures urge intensity of EE but does not assess the types of food consumed.

Arabic Premenstrual Syndrome Scale

A PMS diagnostic tool developed and validated by Algahtani and Jahrami was used for assessing PMS symptoms prevalence and severity. This tool included 23 items that cover psychological (depressed mood, hopelessness, feeling guilty, anxiety or worry, affective labiality, increased sensitivity toward others, feeling angry, easily irritated or agitated, lack of interest, difficulty in concentrating, loss of control, and feeling overwhelmed); physical (lethargy, fatigue, decreased energy, increased appetite, craving certain foods, hypersomnia, insomnia, breast tenderness, breast engorgement or weight gain, headache, muscle, joint, abdominal, and back pain, and acne); and behavioral (symptoms interfering with relationships, work or school, or daily routine). Each item is rated on a five-point Likert scale (never, sometimes, often, always, and severely), with each response assigned a specific score. For each participant, a mean symptom score is calculated across all items. Based on this mean score, respondents are categorized into the following PMS severity groups (no symptoms: mean score <1.0, mild PMS: mean score 1.0–1.9, moderate PMS: mean score 2.0–2.9, and severe PMS: mean score ⩾3.0).²¹ A-PMS symptoms were assessed for the luteal phase of the most recent menstrual cycle, as detailed in the “Data Collection” section.

The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology statement (Supplemental Material).²⁷

Statistical analysis

The IBM Corporation Statistical Package for the Social Sciences software, version 23, was utilized to perform the analysis of the data. The absolute frequency and percentages for categorical variables, as well as the mean and standard deviation for quantitative measurements, were utilized in the process of conducting a descriptive analysis. The relationships between the study’s variables and EE were evaluated by the chi-square test. Participants’ ages were categorized using 20 years as the cutoff (<20 versus ⩾20 years) to distinguish between late adolescence and emerging adulthood, a developmental stage typically beginning around age 20,²⁸ to explore potential age-related differences in EE patterns.

Results

Participants’ sociodemographic characteristics

The mean age of study participants was 19.1 ± 1.3 (18–23) years old. The majority of participants were single (89.8%), living with their families (97.1%), and their study was funded by their families (94.4%). Half of the participants were in their first academic year (56.4%), and most of them were recruited from the applied sciences faculty (33.1%), medicine and health sciences faculty (32.4%), and engineering faculty (18.9%). Detailed sociodemographic characteristics are presented in Table 1.

Table 1.

Participants’ sociodemographic characteristics (n = 450).

Variable		Number (n)	Percentage (%)
Marital status	Single	404	89.8
	Married	34	7.6
	Other	12	2.7
Area of living	City	304	67.6
Area of living	Villages and camps	146	32.4
Type of housing	With family	437	97.1
	Student housing	11	2.4
	Other	2	0.4
Faculties (degree programs)	Applied sciences	149	33.1
	Medicine and health sciences	146	32.4
	Engineering	85	18.9
	Information technology and computer engineering	48	10.7
	Administration sciences and information systems	15	3.3
	Applied professions	7	1.6
Academic year	First	236	52.4
	Second	108	24.0
	Third	36	8.0
	Fourth	65	14.4
	Fifth	5	1.1
Family income (NIS)	<1500	27	6.0
	1500–3000	94	20.9
	3000–5000	180	40.0
	More than 5000	149	33.1
Study funding source	Family	425	94.4
	Scholarship	16	3.6
	Other	9	2.0

Note. Percentages may not total 100% due to rounding.

NIS: New Israeli Shekel.

Participants’ medical history and lifestyle

Table 2 presents the medical history and lifestyle characteristics of the analyzed participants. The majority of them have no chronic illness (98%), have had previous surgery (84.1%), and are on medication (95.8%). Moreover, most of them were non-smokers (92%) and self-reported having no sleeping problems (79.1%). Regarding their physical activity, half of them were classified as moderately active based on the IPAQ score.

Table 2.

Participants’ medical history and lifestyle characteristics (n = 450).

Variable		Number (n)	Percentage (%)
Chronic disease	Yes	9	2.0
Chronic disease	No	441	98.0
Prior surgical intervention	Yes	69	15.3
Prior surgical intervention	No	381	84.7
Medication	Yes	19	4.2
Medication	No	431	95.8
Smoking status	Non-smoker	414	92.0
	Irregular smoker	26	5.8
	Regular smoker	10	2.2
Type of smoking	Cigarette	2	5.6
	Pipe (shisha)	28	77.8
	Both	6	16.7
Taking a nap (days/week)	Always (everyday)	60	13.3
	Most of the time (5–7 days)	108	24.0
	Sometimes (3–5 days)	41	9.1
	Few times (1–2 days)	94	20.9
	Never	147	32.7
Sleep problems	Yes	94	20.9
Sleep problems	No	356	79.1
Physical activity level	Low	158	35.1
	Moderate	228	50.7
	High	64	14.2

Note. Percentages may not total 100% due to rounding.

Participants’ body weight status and dietary habits

More than two-thirds of participants had a normal body weight (70.4%) based on their BMI. Similarly, more than two-thirds of participants stated that they had never been on a diet, while the internet and social media were the most common sources of nutritional information among more than half of the participants (56.7%). According to the MEDAS score, the majority of the participants are showing moderate adherence to the Mediterranean diet, as presented in Table 3.

Table 3.

Weight status and dietary habits of study participants (n = 450).

Variable		Number (n)	Percentage (%)
BMI	Underweight	65	14.4
	Normal	317	70.4
	Overweight	53	11.8
	Obese	15	3.3
Been on a diet	Yes	130	28.9
Been on a diet	No	320	71.1
Diet time^a	Currently	23	17.7
Diet time^a	Before and stopped	107	82.3
Reason for diet^a	Weight loss or gain	118	90.8
	Therapeutic	2	1.5
	Other	10	7.7
Nutritional information source	Dietitians	100	22.2
	Internet and social media	255	56.7
	Health workers (doctors or nurses)	25	5.6
	Books	21	4.7
	Other	49	10.9
Nutritional supplements	Yes, regularly	28	6.2
	Yes, irregularly	79	17.6
	Never	343	76.2
MEDAS	Low	99	22.0
	Moderate	258	57.3
	High	93	20.7

Note. Percentages may not total 100% due to rounding.

BMI: body mass index; MEDAS: Mediterranean Diet Adherence Screener.

n = 130 participants who had ever been on a diet.

Participants’ EE prevalence

EE related to frustration was prevalent among more than two-thirds of participants, with a prevalence of 71.8% (95% CI: 0.676–0.759). Anxiety–EE was observed among 42.7% of participants (95% CI: 0.380–0.472). None of the participants scored above the cutoff for EE in the depression subscale of EES, as illustrated in Figure 1.

Figure 1.

Prevalence of emotional eating related to frustration, anxiety, and depression.

Prevalence of PMS symptoms among participants

PMS symptoms were highly prevalent among 99.1% (95% CI: 0.982–1.00) of study participants, with psychological and physical symptoms being the most common, reported by 98.4% (95% CI: 0.973–0.995) and 98.9% (95% CI: 0.979–0.999) of participants, respectively, while behavioral symptoms were observed among 82.2% (95% CI: 0.793–0.863) of participants, as detailed in Figure 2.

Figure 2.

The prevalence of PMS symptoms and their severity among study participants.

EE and sociodemographic characteristics

The participants’ academic years showed a significant difference in anxiety–EE (p = 0.004). The highest prevalence of anxiety–EE was among the third year (55.6%) and fourth/fifth year (51.4%), while it was the least prevalent among first year students (34.7%). By contrast, no significant relationship was found between academic year and EE related to frustration (p = 0.087). Table 4 shows no significant association between EE and other sociodemographic characteristics.

Table 4.

Relationship between EE and participants’ sociodemographic characteristics.

Variable	Frustration–EE (n (%))		p value	Anxiety–EE (n (%))		p value
Variable	High	None	p value	High	None	p value
Age			0.372			0.107
⩽20 years	233 (72.4)	89 (27.6)		131 (40.7)	191 (59.3)
>20 years	90 (70.3)	38 (29.7)		61 (47.7)	67 (52.3)
Marital status			0.958
Single	290 (71.8)	114 (28.2)		168 (41.6)	236 (58.4)	0.269
Married	24 (70.6)	10 (29.4)		19 (55.9)	15 (44.1)
Other	9 (75.0)	3 (25.0)		5 (41.7)	7 (58.3)
Area of living			0.473			0.582
City	215 (70.7)	89 (29.3)		127 (41.8)	177 (58.2)
Villages and camps	108 (74.0)	38 (26.0)		65 (44.5)	81 (55.5)
Type of housing			0.676			0.408
With family	313 (71.6)	124 (28.4)		185 (42.3)	252 (57.7)
Student housing or others	10 (76.9)	3 (23.1)		7 (53.8)	6 (46.2)
Faculties (degree programs)			0.803			0.053
Medicine and health sciences	110 (75.3)	36 (24.7)		68 (46.6)	78 (53.4)
Engineering	59 (69.4)	26 (30.6)		33 (38.8)	52 (61.2)
Information technology and computer engineering	34 (70.8)	14 (29.2)		11 (22.9)	37 (77.1)
Administration sciences and information systems	10 (66.7)	5 (33.3)		8 (53.3)	7 (46.7)
Applied sciences	104 (69.8)	45 (30.2)		68 (45.6)	81 (54.4)
Applied professions	6 (85.7)	1 (14.3)		4 (57.1)	3 (42.9)
Academic year			0.087			0.004*
First	159 (67.4)	77 (32.6)		82 (34.7)	154 (65.3)
Second	87 (80.6)	21 (19.4)		54 (50.0)	54 (50.0)
Third	27 (75.0)	9 (25.0)		20 (55.6)	16 (44.4)
Fourth or fifth	50 (71.4)	20 (28.6)		36 (51.4)	34 (48.6)
Family income (NIS)			0.750			0.694
<1500	19 (70.4)	8 (29.6)		11 (40.7)	16 (59.3)
1500–3000	71 (75.5)	23 (24.5)		42 (44.7)	52 (55.3)
3000–5000	130 (72.2)	50 (27.8)		81 (45.0)	99 (55.0)
More than 5000	103 (69.1)	46 (30.9)		58 (38.9)	91 (61.1)
Study funding source			0.980			0.127
Family	305 (71.8)	120 (28.2)		185 (43.5)	240 (56.5)
Scholarship or other	18 (72.0)	7 (28.0)		7 (28.0)	18 (72.0)

Note. Percentages may not total 100% due to rounding.

EE: emotional eating; NIS: New Israeli Shekel.

p < 0.05 (chi-square test).

EE and medical history, lifestyle, and nutrition-related variables

No significant association was found between EE and participants’ medical history, lifestyle, and nutrition-related variables (p > 0.05), as demonstrated in Table 5.

Table 5.

Relationship between EE and participants’ medical history, lifestyle, and nutrition-related variables.

Variable	Frustration–EE (%)		p value	Anxiety–EE (%)		p value
Variable	High	None	p value	High	None	p value
Chronic disease			0.686			0.567
Yes	77.8	22.2		33.3	66.7
No	71.7	28.3		42.9	57.1
Surgery			0.891			0.907
Yes	72.5	27.5		42.0	58.0
No	71.7	28.3		42.8	57.2
Medication			0.740			0.600
Yes	68.4	31.6		36.8	63.2
No	71.9	28.1		42.9	57.1
Smoking status			0.694			0.650
Non-smoker	71.3	28.7		42.0	58.0
Irregular smoker	76.9	23.1		50.0	50.0
Regular smoker	80.0	20.0		50.0	50.0
Type of smoking			0.603			0.667
Cigarette	50.0	50.0		50.0	50.0
Pipe (shisha)	78.6	21.4		46.4	53.6
Both	83.3	16.7		66.7	33.3
Taking a nap (days/week)			0.444			0.182
Always (everyday)	81.7	18.3		55.0	45.0
Most of the time (5–7 days)	68.5	31.5		44.4	55.6
Sometimes (3–5 days)	73.2	26.8		34.1	65.9
Few times (1–2 days)	71.3	28.7		37.2	62.8
Never	70.1	29.9		42.2	57.8
Sleep problems			0.515			0.980
Yes	74.5	25.5		42.6	57.4
No	71.1	28.9		42.7	57.3
Physical activity level			0.644			0.657
Low	70.3	29.7		43.0	57.0
Moderate	73.7	26.3		43.9	56.1
High	68.8	31.3		37.5	62.5
BMI			0.159			0.587
Underweight	75.4	24.6		46.2	53.8
Normal	71.9	28.1		42.9	57.1
Overweight	73.6	26.4		41.5	58.5
Obese	46.7	53.3		26.7	73.3
Been on a diet			0.696			0.340
Yes	73.1	26.9		46.2	53.8
No	71.3	28.7		41.3	58.8
Diet time			0.676			0.777
Currently	69.6	30.4		43.5	56.5
Before and stopped	73.8	26.2		46.7	53.3
Reason for diet			0.167			0.291
Weight loss or gain	74.6	25.4		44.9	55.1
Therapeutic	100.0	0.0		100.0	0.0
Other	50.0	50.0		50.0	50.0
Nutritional information source			0.086			0.354
Dietitians	64.0	36.0		38.0	62.0
Internet/social media	72.5	27.5		41.6	58.4
Health workers (doctors or nurses)	64.0	36.0		48.0	52.0
Books	85.7	14.3		42.9	57.1
Other	81.6	18.4		55.1	44.9
Nutritional supplements			0.700			0.567
Yes, regularly	78.6	21.4		35.7	64.3
Yes, irregularly	72.2	27.8		46.8	53.2
Never	71.1	28.9		42.3	57.7
MEDAS			0.211			0.146
Low	72.7	27.3		49.5	50.5
Moderate	74.0	26.0		42.6	57.4
High	64.5	35.5		35.5	64.5

Note. Not significant at p > 0.05 (chi-square test). Percentages may not total 100% due to rounding.

BMI: body mass index; EE: emotional eating; MEDAS: Mediterranean Diet Adherence Screener.

EE and PMS

A significant association was found between frustration–EE and psychological (p = 0.006), behavioral (p = 0.012), and overall PMS symptoms (p = 0.005). Participants with moderate psychological symptoms (79%), mild (77.3%) and moderate (73.5%) behavioral symptoms, and moderate overall symptoms (78.3%) reported higher percentages of EE related to frustration. No significant association was observed between EES anxiety scores and any PMS categories (p > 0.05), as shown in Table 6. In addition, a correlation analysis between EES scores and PMS severity scores was conducted, but no significant correlations were observed.

Table 6.

Relationship between EE and PMS symptoms.

Symptoms type	Frustration–EE (%)		p value	Anxiety–EE (%)		p value
Symptoms type	High	None	p value	High	None	p value
Psychological			0.006*			0.258
None	42.9	57.1		42.9	57.1
Mild	63.6	36.4		35.6	64.4
Moderate	79.0	21.0		43.4	56.6
Severe	69.2	30.8		48.3	51.7
Physical			0.125			0.970
None	40.0	60.0		40.0	60.0
Mild	69.6	30.4		40.9	59.1
Moderate	75.6	24.4		43.6	56.4
Severe	66.7	33.3		42.7	57.3
Behavioral			0.012*			0.285
None	57.5	42.5		33.8	66.3
Mild	77.3	22.7		44.9	55.1
Moderate	73.5	26.5		42.4	57.6
Severe	71.0	29.0		48.4	51.6
Overall PMS symptoms			0.005*			0.657
None	25.0	75.0		25.0	75.0
Mild	67.3	32.7		39.8	60.2
Moderate	78.3	21.7		42.5	57.5
Severe	64.5	35.5		46.7	53.3

Note. Percentages may not total 100% due to rounding.

EE: emotional eating; PMS: premenstrual syndrome.

p < 0.05 (chi-square test).

Discussion

This study highlights a high prevalence of EE and PMS among Palestinian female university students, with 71.8% reporting EE during frustration and 42.7% during anxiety. These findings mirror stress-eating pattern observed in other student populations^29,30 and likely reflects dysregulation of reward/motivation circuits and inhibitory control pathways,^31,32 which, in turn, drive cravings for energy-dense, nutritionally poor foods.³³ EE is widely documented across Western and other Asian populations. Studies from Western countries have reported that negative EE is prevalent among college students by up to 56%, with higher levels among female students with stress, depression, and anxiety. However, studies from central China reported EE prevalence between 14.5% and 52.7% among undergraduate students.³⁴ These global findings suggest that EE is a cross-cultural phenomenon with shared psychological and physiological mechanisms.

The near-universal occurrence of PMS (99.1%) in our sample, characterized by both physical and psychological symptoms, is similarly noteworthy. These findings parallel reports from the UAE (95%)³⁵ and exceeds rates in Lebanon (63%),³⁶ and contrasts sharply with lower prevalence rates in Brazil (46.9%),¹⁶ Ethiopia (37%),³⁷ and Taiwan (39.9%).³⁸ Nevertheless, the high prevalence of PMS among our sample may be attributed to sample characteristics, in which certain age populations were included and are prone to higher PMS due to high lifestyle stress. In addition, self-reported data may have introduced recall bias or overreporting. However, the variation in the prevalence of PMS is thought to be attributed to genetic and dietary factors, community-adopted practices, and the differences in social meaning or construction for particular embodied and psychological experiences as a disorder associated with the reproductive body among young adults.³⁵

Our study found a graded relationship between EE and PMS severity, particularly within psychological and behavioral symptom domains. This aligns with prior literature showing that severe PMS is associated with heightened EE tendencies.^15,39 Recurrent reliance on “comfort” foods during emotional distress may exacerbate inflammatory processes and glycemic instability, which, in turn, can aggravate PMS symptoms.^32,33 While our study did not assess the type of food consumed during menstruation, previous research suggests that women with PMS may be more sensitive to hormonal fluctuations, resulting in higher consumption of simple carbohydrates and energy-dense food. This behavior is thought to serve as a counterregulatory mechanism for low mood by promoting serotonin and dopamine release in the brain.⁹ Considering the high prevalence of PMS and its association with EE among our study sample raises concerns about dietary choices and their long-term health implications for Palestinian women, which might contribute to weight gain and increase the risk of metabolic disorders. Future studies should incorporate dietary intake assessments to further understand the nutritional patterns associated with EE and PMS.

Notably, a significant association was found between academic year and anxiety-driven EE. EE due to anxiety was least prevalent among first-year students and more frequent among third and fourth-/fifth-year students, suggesting that students at higher academic years may experience more academic stress due to increased workload, examination, and future-related pressures. This finding aligns with previous studies indicating that curricular load and grade point average (GPA)-related pressure are associated with anxiety⁴⁰ and maladaptive coping behaviors, including EE and changes in eating or drinking habits.^41,42 However, they contrast with findings from a Malaysian study that identified the earlier academic year as a primary predictor of anxiety.⁴³ These variations might be attributed to differences in sampling methods, participants’ characteristics, or measurement tools.

Interestingly, although our main analyses examined age categorically (⩽20 versus <20 years), no significant associations were found between age groups and EE. This indicates that situational stressors such as academic workload and emotional burden may have a greater impact on EE than age per se.

Methodologically, chi-square tests were used to examine associations between categorical variables; however, as chi-square does not measure effect size, future work should report metrics such as Cramer’s V or adjusted odds ratios to better quantify associations.¹⁶ The use of Arabic-validated versions of the EES and A-PMS scales, in combination with tools like the IPAQ and MEDAS, represents a novel contribution in the Palestinian context.

Given these insights, comprehensive campus interventions that integrate cognitive–behavioral strategies for emotion regulation, stress-reduction techniques (e.g., mindfulness), Mediterranean-style dietary counseling, and targeted micronutrient supplementation (e.g., vitamin D, magnesium) may mitigate both EE and PMS symptoms, thereby improving student well-being and academic performance.^39,40,44

Strength and limitations

The study has several strengths, including a sufficient sample size and the use of widely accepted, validated tools that were adapted and validated in Arabic. However, this study has some limitations, including the cross-sectional design that limits the ability to establish causality between PMS and EE. Self-report questionnaires may have introduced recall bias. Moreover, most participants were enrolled in health sciences and applied sciences programs, which may have influenced their awareness of health-related behaviors and EE patterns, which may limit the generalizability of the findings to students from other academic disciplines. In addition, the lack of detailed data on surgical interventions, as well as the broad categorization of medication used in our study, limits our ability to evaluate their direct relationship with EE. Furthermore, cultural perceptions of emotional expression, dietary habits, and menstruation may potentially influence both behaviors and self-reporting accuracy among Palestinian female students who participated in this study.

Conclusion

This study demonstrates a significant association between EE – particularly anxiety-driven eating – and the severity of PMS symptoms among Palestinian university students, even after adjusting for physical activity and dietary quality. The high prevalence of PMS and high rates of EE during frustration and anxiety underscore the urgent need for targeted interventions on campus. Multimodal programs that combine cognitive–behavioral strategies for stress and emotion regulation, mindfulness-based stress reduction, nutritional education emphasizing anti-inflammatory Mediterranean-style diets, and targeted micronutrient supplementation hold promise for reducing both EE behaviors and PMS burden. By employing validated Arabic versions of the EES and A-PMS scales and controlling for key lifestyle factors (IPAQ, MEDAS), this work covers a gap in non-Western research and provides an understanding of how academic stressors interact with nutrition and hormonal fluctuations. Future longitudinal and intervention studies should incorporate objective dietary assessments, and evaluate the effectiveness of culturally tailored, theory-driven programs in reducing EE and improving menstrual health and quality of life.

Supplemental Material

sj-docx-1-whe-10.1177_17455057251401811 – Supplemental material for Emotional eating is associated with premenstrual syndrome among university students in Palestine: A cross-sectional study

Supplemental material, sj-docx-1-whe-10.1177_17455057251401811 for Emotional eating is associated with premenstrual syndrome among university students in Palestine: A cross-sectional study by Reem Abu Al Wafa, Mohammad Taleb Abed, Mohammed Jaber, Daad Mahdi, Aya Khallaf, Marwa Idesat, Tamarh Alzayat, Worood Qafisheh and Manal Badrasawi in Women's Health

Footnotes

Acknowledgements

The authors would like to acknowledge the students who participated in the study and agreed to join the study.

ORCID iDs

Reem Abu Al Wafa

Mohammad Taleb Abed

Manal Badrasawi

Ethical considerations

This study protocol was approved by the faculty of scientific research Ethical Committee – Palestine Polytechnic University, Palestine (Ref. no. KA/41/2021). The study was conducted in accordance with the Declaration of Helsinki.

Consent to participate

Informed consent was taken from the participants to join the study. A written consent was stated at the beginning of the questionnaire that the participants signed. All the collected information was kept secret and only used for research allowing only the principal investigators and the study analyst to evaluate and conduct the proper statistical analysis. No reward was given to the participants.

Consent of publication

Not applicable.

Author contributions

Reem Abu Al Wafa: Writing – original draft.

Mohammad Abed: Formal analysis; Writing – review & editing.

Mohammed Jaber: Formal analysis; Writing – review & editing.

Daad Mahdi: Conceptualization; Data curation; Supervision; Writing – review & editing.

Aya Khallaf: Data curation; Investigation; Methodology.

Marwa Idesat: Data curation; Investigation; Writing – review & editing.

Tamarh Alzayat: Data curation; Investigation; Writing – review & editing.

Worood Qafisheh: Data curation; Investigation; Writing – review & editing.

Manal Badrasawi: Conceptualization; Project administration; Supervision; Writing – review & editing.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The dataset supporting the conclusions of this article is available upon request from the corresponding author.

Supplemental material

Supplemental material for this article is available online.

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