Natl. J. Physiol. Pharm. Pharmacol.(2025), Vol. 15(4): 258-266

Research Article

10.5455/NJPPP.2025.v15.i4.1

Stress, dietary patterns, and emotional eating: A crosssectional study among Indian High School students

Vedika Khurana^1* and Richa Verma²

¹Royal College of Surgeons in Ireland, Dublin, Ireland

²Government Medical College, Amritsar, India

*Corresponding Author: Vedika Khurana. Royal College of Surgeons in Ireland, Dublin, Ireland. Email: vedikakhurana1012 [at] gmail.com

Submitted: 31/12/2024 Accepted: 11/03/2025 Published: 30/04/2025

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Introduction

The intricate relationship between stress and dietary patterns is increasingly recognized as a significant factor influencing student well-being. Various internal and external factors, such as stress, emotions, habits, and individual attitudes toward food, play crucial roles in determining appetite and food consumption behaviors. Historically, stress has been understood to trigger physiological responses that can alter eating behaviors, leading to either an increase or decrease in appetite (Adam and Epel, 2007; Torres and Nowson, 2007). Emotional eating (EE), a behavior influenced by stress and emotional states, is not classified as a distinct eating disorder but significantly affects eating patterns (KidsHealth, 2022).

Students, particularly those transitioning from education to professional life, often experience high stress levels due to factors such as packed schedules, sleep deprivation, poor organizational habits, lack of downtime, and inadequate support (BNI Treatment, 2023). The prevalence of anxiety and stress among students is alarmingly high, with significant proportions experiencing moderate to extremely severe levels of stress. In India, a study highlighted that 17.8% of students suffer from severe anxiety, with 46.8% experiencing extremely severe anxiety, while stress levels were severe in 13.2% and extremely severe in 2.8% of students (Asif et al., 2020)

A cross-sectional study conducted at Punjab University, Chandigarh, revealed that the prevalence rates of depression, anxiety, and stress among students were 59.2%, 86.5%, and 52.7%, respectively. This study also indicated that these mental health issues were more prevalent among females and tended to decrease with age, underscoring the need for improved mental health awareness, reduced stigma, and better mental health services for students (Singh et al., 2014).

Current trends indicate that adolescents, who are highly vulnerable to the effects of incorrect nutrition, often develop poor dietary habits during periods of stress and opt for convenience foods high in fat and sugar (Hopkins Medicine). This stress-induced preference for high-calorie comfort foods is driven by hormonal changes, such as increased cortisol and ghrelin levels, which heighten appetite and cravings (Sharp Health News, 2024). The public health implications of these findings are profound, as stress-induced dietary changes can lead to increased rates of obesity, eating disorders, and other related health conditions among students (Torres and Nowson, 2007; Michels et al., 2015).

Noncommunicable diseases (NCDs) are significantly influenced by behavioral factors, such as tobacco use, physical inactivity, alcohol consumption, and diet imbalance. Behavioral aspects, including knowledge, attitudes, and practices related to health behaviors such as regular health checks, quitting smoking, physical activity, healthy eating, rest, and stress management, can indicate an individual’s risk of NCDs (Typeset, 2022a).

A study on emotional eating among students found that high stress levels were closely linked to emotional eating tendencies, indicating that stress management strategies could be crucial in addressing emotional eating issues. This study also revealed that emotional eating was more prevalent among students in nonhealth-related fields than among those in health-related fields, highlighting the impact of academic specialization on eating behaviors (Typeset, 2022b).

Therefore, developing effective intervention strategies to help students manage stress and maintain healthy eating habits is crucial (Nelson and Lytle, 2011; Conley et al., 2015). Furthermore, examining cross-cultural perspectives, particularly in the context of Indian students, can provide a broader understanding of how stress and dietary patterns vary globally (Kapur and Gupte).

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Materials and Method

Study setting: Two randomly selected schools on the periphery of the city (Amritsar) catering to students from both urban and rural areas.

Study period: 1 mo

Type of study: Descriptive cross-sectional study

Study population: Students of grades 9th, 10th, 11th, and 12th.

Exclusion Criteria:

Students who are not willing to participate.

Students absent on the day of data collection.

The questionnaire consisted of 42 questions.

Section one of the questionnaire consisted of demographic characteristics of the respondents such as age, body weight status, employment status, type of family, and location of the house.

The body mass index (BMI, kg/m²) was calculated using height and weight. BMI was divided into underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 23), overweight (23 ≤ BMI < 25), and obesity (BMI ≥ 25) according to the Asia–Pacific BMI classifications (World Health Organization and Regional Office for the Western Pacific, 2000).

Section two of the questionnaire consisted of two scales: Perceived stress scale (PSS) and emotional eater questionnaire (EEQ).

The stress score utilized the PSS created by Cohen et al. (1983) and modified by Lee et al. (2012). The test comprised 10 questions, each assessed on a 5-point Likert scale. The total score ranged from 0 to 40 points, with higher scores indicating greater perceived stress severity.

The level of emotional dietary behavior was assessed using the EEQ developed by Garaulet et al. (2012). The test consisted of ten questions, each rated on a 4-point Likert scale. For analysis, 0–5 points were classified as the nonemotional eater group, 6–10 points as the low emotional eater group, and over eleven points as the emotional eater group.

Section three of the questionnaire consisted of general practices related to diet like meal regularity, vegetable intake, fruit intake, protein intake, milk and dairy product intake, and sweet intake, along with questions about preparing the meal, food allergies, cholesterol problem, and diabetes. A few questions also inquired about the sleeping pattern to evaluate the lifestyle of the subjects.

Data analysis, including the generation of graphs and results, was conducted using R programming, allowing for detailed visualization of findings related to demographics, stress levels, emotional eating behaviors, and lifestyle practices.

Ethical Considerations:

1. Prior to data collection from students, informed consent was obtained.

2. The data and identity of the subjects were kept confidential. Information obtained from the study was not shared with any person who was not involved in the study.

3. No personal identifiers were used during the study.

Table 1. Distribution of respondents based on anthropometricand PSS and EEQ scores.

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Results

Table 1 presents the average values and standard deviations of the various characteristics of the female, male, and total participants. The study involved 475 participants (261 females and 214 males).

Regarding BMI, females had a higher average BMI of 21.77 kg/m² compared to males, who had an average of 19.63 kg/m². The mean total BMI was 20.70 kg/m² (±4.17).

Fig. 1. Distribution of participants based on sex.

Fig. 2. Age frequency distribution of participants.

Fig. 3. Distribution of sex in various age groups.

Fig. 4. Composition of participants based on their house location.

The PSS scores indicated that females experience higher stress levels, with an average score of 23.25 than males, with an average score of 19.95.

Finally, the EEQ scores showed that females had higher emotional eating tendencies with an average score of 11.57 (±5.20), compared to males who had an average score of 9.23 (±5.20).

Figure 1 represents the sex distribution in the sample population, which consists of a slightly higher percentage of female participants than male participants.

The bar chart in Figure 2 illustrates the frequency distribution of different ages in the dataset. Ages 14 and 15 had the highest frequencies, with both showing frequencies above 75. This suggests that the dataset contains a larger proportion of individuals aged 18 years.

Ages 17 and 18: These ages had much lower frequencies, with age 17 being slightly more than age 18. This indicates that individuals in these age groups were less represented in the dataset.

The chart in Figure 3 shows the distribution of stress levels across different age groups, with a color gradient representing BMI values. Here is a brief interpretation:

Age Groups: The age groups (14–18) are shown on the x-axis, but there is not much difference in stress levels based solely on age, as stress points seem similarly distributed across all ages.

Stress Levels: Stress levels, shown on the y-axis, vary widely within each age group, with values ranging from 0 to approximately 35. This spread suggests that stress levels are not strongly related to age in this dataset.

BMI: The points are shaded to indicate BMI, where darker shades represent lower BMI and lighter shades represent higher BMI. However, there is no clear trend between BMI and stress levels across age groups.

The following pie chart (Fig. 4) shows the distribution of participants according to the location of their houses. Students from urban areas participated significantly more than students from rural areas.

The data points were spread across a wide range of BMI values, with the highest BMI recorded at 40 kg/m² (Fig. 5).

Most participants fell within the midrange of both BMI and stress scores, indicating a concentration of individuals with moderate stress and BMI.

There are notable outliers in which participants with higher BMI tend to have higher stress scores, suggesting a possible correlation between increased BMI and stress levels.

Table 2 shows males and females and the total number of participants divided into underweight, normal weight, overweight, and obese categories based on BMI. Obesity is more prevalent in males than females. In addition, more females are underweight than males.

Stress scores were calculated using a Likert 5-point scale is also compared among students of different grades (Fig. 6).

Students in 12th grade had the highest average stress score. Students in the 9th grade have the lowest average stress score. This indicates that stress levels tend to increase as students progress to higher grades, with 12th graders experiencing the highest stress levels.

The plot in Figure 7 reveals a positive correlation between stress scores and EEQ scores, suggesting that higher levels of stress are associated with higher levels of emotional eating.

The data points are widely spread, indicating variability in both stress and emotional eating behaviors among the students. However, there is a noticeable trend where an increase in the stress score corresponds to an increase in the EEQ score.

There was a dense clustering of data points around the midrange of both stress and EEQ scores, suggesting that most students fell within this range.

Table 3 indicates a moderate positive correlation was found between stress levels and emotional eating scores ( r=0.3015), indicating that higher stress is associated with increased emotional eating tendencies. Additionally, a weak positive correlation was observed between BMI and stress ( r=0.0134) and a moderate correlation between BMI and EEQ scores ( r=0.2280).

Fig. 5. Correlation between BMI and stress.

Table 2. Distribution of respondents according to BMI values.

The t-test was used to compare the mean stress and EEQ scores. The results are as follows.

The t-value was 32.85, with a p-value less than 0.00001, indicating a significant difference between the stress and EEQ scores (p < 0.05).

BMI and Stress Score: The t-value was -3.24955, with a p-value of 0.000599, indicating a significant result (p < 0.05).

BMI and EEQ Score: The t-value was 32.42476, with a p-value less than 0.00001, indicating a significant result (p < 0.05).

The bar chart in Figure 8 indicates that there is no significant difference in the average EEQ scores between students from urban and rural areas, suggesting similar emotional eating behaviors regardless of the location of residence.

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Discussion

This study aimed to investigate the relationship between perceived stress, dietary patterns, and emotional eating among high school students in grades 9 through 12. Our findings highlight significant associations between stress levels and dietary behaviors, reflecting patterns observed in a broad population.

Emotional eating, which is characterized by the consumption of high-fat and sugar-rich energy-dense foods, is a common coping mechanism in response to stress. Studies have indicated that both positive and negative emotions significantly influence food choices, purchases, and consumption patterns. Emotional eating is not restricted to a particular age group or sex; it has been documented across various stages of life, affecting both men and women.

Fig. 6. Comparison of stress score in students of different grades.

Fig. 7. Correlation between stress and EEQ score of participants.

Table 3. Relationship between BMI EEQ and PSS scores.

Fig. 8. Average EEQ score of participants distributed based on the location of their house.

Several studies have highlighted the intricate relationship between emotional eating, psychological states such as depression and anxiety, and unhealthy dietary patterns. For instance, Carpioo-Arias et al. found that individuals experiencing perceived stress during the COVID-19 pandemic had a higher likelihood of engaging in emotional eating, potentially leading to weight gain. This study utilized questionnaires to assess emotional eating and perceived stress, revealing that stressed individuals are more prone to seek comfort in food (Carpio-Arias et al., 2022).

Similarly, Laura East Finch et al. explored the concept of comfort eating as a buffer against psychological stress in young adult women. The findings revealed that comfort eating could mitigate stress in individuals without high levels of depressive symptoms. However, the self-reported nature of the data and the exclusion of men from the sample limit the generalizability of these findings (Finch and Tomiyama, 2015).

The interplay between emotional dysregulation and emotional eating is also examined in various contexts. Guerrini-Usubini et al. demonstrated that emotional eating is not only linked to psychological distress and physical consequences, such as increased BMI. Their path model indicated that emotional eating contributes to a higher intake of energy-dense foods, which in turn affects weight status. However, the cross-sectional design and reliance on self-reported data necessitate further research to establish causal relationships (Guerrini-Usubini et al., 2023).

The physiological and psychological mechanisms through which stress influences eating behavior are complex. Stress can lead to dysregulation of bio-behavioral responses to food intake, increasing the consumption of high-fat, high-sugar foods as a coping mechanism. This is supported by Hill et al. who conducted a systematic review and meta-analysis and confirmed the global recognition of stress-induced alterations in food consumption patterns (Hill et al., 2022). Masih et al. (2017) also suggested that relaxation techniques could potentially counteract stress-induced eating by normalizing appetite through both physiological and psychological pathways.

Klatzkin et al. further showed that perceived life stress enhances the hyperphagic effects of stress-induced negative effects, particularly in women with high perceived stress. This finding underscores the need for targeted clinical interventions for individuals with chronic stress and related obesity concerns (Klatzkin et al., 2019).

The COVID-19 pandemic has brought additional dimensions to the understanding of stress and eating behaviors. Modrzejewska et al. reported that emotional overeating served as a coping mechanism during the quarantine, highlighting the influence of COVID-19-related stress on dietary habits. However, limitations such as cross-sectional design and self-reported data call for longitudinal studies to better understand these dynamics (Modrzejewska et al., 2021). Similarly, Ramalho et al. found that the psychosocial effects of the pandemic and associated psychological distress played a significant role in disturbed eating behaviors during the first lockdown in Portugal (Ramalho et al., 2022).

Large-scale population-based surveys, like the one conducted by Bemanian et al. in Norway, have shown a significant correlation between psychological distress and emotional eating during the pandemic. This study emphasized the increased intake of high-sugar foods and beverages among individuals experiencing distress, with a notable prevalence among women (Bemanian et al., 2020). Furthermore, Calderón-Asenjo et al. revealed that anxiety symptoms significantly predict negative emotional eating, underscoring the need for mental health interventions to address this issue (Calderón-Asenjo et al., 2022).

Overall, these studies collectively highlight the profound impact of stress on dietary patterns, emphasizing the need for comprehensive strategies to mitigate stress-induced eating behaviors. Future research should focus on longitudinal designs, diverse populations, and the development of interventions to promote healthy eating habits in the context of stress and emotional dysregulation.

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Conclusion

The findings of this study highlight a significant relationship between stress levels and emotional eating behaviors among high school students in Amritsar, India. The data indicate that students, particularly female students, experience higher levels of stress and are more prone to emotional eating. These behaviors are influenced by various factors, including academic pressure, which tends to increase as students advance to higher grades.

The positive correlation between stress and emotional eating underscores the need for targeted interventions for stress management. Implementing effective strategies such as stress reduction programs, mental health support, and promoting healthy coping mechanisms can help mitigate the impact of stress on dietary habits. Furthermore, educational initiatives to raise awareness of healthy eating and the effects of stress on eating behaviors can contribute to better physical and mental health outcomes for students.

Given the cultural context and unique challenges faced by this population, further research is essential to develop and assess the effectiveness of tailored interventions. Future studies should also consider longitudinal designs to examine the long-term effects of stress and emotional eating and explore the potential role of family, peers, and educational institutions in supporting students’ well-being.

In conclusion, addressing stress and emotional eating through comprehensive, culturally sensitive approaches can significantly improve high school students’ overall health and academic performance. The findings of this study provide a foundation for future research and intervention programs aimed at fostering healthier lifestyles and reducing the burden of stress-related eating disorders among adolescents.

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Acknowledgment

We would like to express our gratitude to the respected principals of the institutions as well as the directors of all the coaching institutions who graciously allowed us to collect the data. We are particularly grateful to all the students who diligently participated in this study.

Finally, we extend our heartfelt thanks to our friends and family for their encouragement and unwavering belief in us during this journey.

Conflict of interest

The authors declare no conflicts of interest regarding this study.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Authors’ contributions

Outline the role of each author in the research. A common format follows:

Conceptualization: Vedika Khurana

Methodology: Richa Verma

Data Collection and Analysis: Vedika Khurana

Manuscript Writing and Editing: Vedika Khurana and Richa verma

Data availability

The dataset used in this study is available from the corresponding author upon reasonable request.

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