Association of Food Habits on Adolescents’ Mental Distress and Quality of Life: an Observational Study From Higher Secondary Schools of Pakistan

Association of Food Habits on Adolescents’ Mental Distress and Quality of Life: an Observational Study From Higher Secondary Schools of Pakistan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of Food Habits on Adolescents’ Mental Distress and Quality of Life: an Observational Study From Higher Secondary Schools of Pakistan Khadija Muqadas, Shahbaz Ahmad Zakki, Ijaz ul Haq, Muhammad Ismail Qadri, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6242891/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Academic performance influence depression, anxiety, stress and overall quality of life of students. The purpose of this study is to investigate the eating habits of school adolescents, and its association with status of mental health and quality of life (QOL). Methods: A cross-sectional study was conducted among children and adolescents of all Government higher secondary schools in District Haripur, Khyber Pakhtunkhwa, Pakistan from March 2023 to May 2023. A 39-item Adolescent Food Habits Checklist, Depression, Anxiety, Stress Scale for youth (DASS-Y) 21 item questionnaire and 26 item WHOQOL-BREF questionnaire were used to collect the data. Data analyses were performed on SPSS Version 22.0 to measure significance between variables. Results : Study findings showed that stress, anxiety, and depression among students were 92.4%, 76.8%, and 86.6%, respectively. Analyses identified three groups: poor eating (36%), moderate eating (35%), and good eating habits (29%). Depression, anxiety and stress with eating behaviors have a substantial relationship (x 2 <137.7, p- value < 0.001), (x 2 <154.6, p- value < 0.001), (x 2 < 126.3, p- value < 0.001) respectively. Conclusion : Students showed high levels of psychological distress and low quality of life due to bad food habits. There is a need of interventions for dietary habits improvement and modification of school environment to reduce the risk of psychological distress and improve QOL. Food habits quality of life mental health schoolchildren adolescents WHOQOL-BREF DASS-Y KPK Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Children and adolescents confront ever-increasing social, emotional, and mental health challenges. Schools, as one of the primary systems in their life, are required to broaden their goals and help with addressing these challenges (Cefai et al., 2022 ). High academic attainment expectations have produced an extremely stressful situation that if not addressed, can be detrimental to their physical and mental health (Alharbi et al., 2019 ). Children and adolescents constitute of almost one third (2.2 billion individuals) of the world’s population however, mental health problems affect 10–20% of children and adolescents worldwide (López-Gil et al., 2023 ). According to a survey of adolescents in 17 nations, one in every 20 had a depressive episode on average. Psychological distress is the fourth largest contributor to the global disease burden and the leading cause of disability (Bedaso et al., 2018 ). Healthy lifestyles, mental health, and wellness are critical for children's physical, social, and emotional development. Unhealthy lifestyles and psychological issues at a young age can be difficult to overcome and can leave an effect on adulthood (Maximova et al., 2022 ). Prevalence of depression, anxiety, and stress (DAS) is increasing among children and adolescents. These mental health related problems are dangerous and may even prove to be suicidal and fatal. School adolescents do not consume a high-quality diet, therefore self-reported mental health issues within this group are on the rise. Food consumption is one of the environmental and psychological factors that lead to poor mental health (Regan et al., 2022 ). Adolescents’ eating habits have an important effect on their physical, emotional, and mental development. Their physical and academic progress will be influenced by the quality of their nourishment. Indeed, now is the time to build habits that will last a lifetime (Basiak-Rasała et al., 2022 ). Students in better health often study more effectively, accomplish higher academic goals and graduate at a higher rate, all of which offer long-term advantages (Kwok et al., 2021 ). QOL has become one of the ultimate goals of health services. According to the subjective definition of QOL with respect to the school context its varies, because its include the dimensions i.e. teacher-student relationship, climate and social relationship, commitment to school work, academic achievements, promotions, sense of responsibility, and physical environment of class room and school (Cruz et al., 2018 ). QOL is a complex and diverse notion that has been used to analyze several elements of people's lives, including physical and psychological well-being, financial independence, social interactions, personal views, and living situation (Sala et al., 2022 ). Depressive symptoms in early adulthood can have a negative influence on future employment and social relationships as well as QOL later in life. Successful management of depressive symptoms as well as stress may play a significant influence in enhancing the QOL (Seo et al., 2018 ). Ensuring the well-being of children and adolescents is a critical step toward healthy growth, healthy habits, and future accomplishments. Students mental health and QOL increase significantly when their eating habits are improved (Diamantis et al., 2023 ). Early detection is the key to healthy mental state for future generations (Sandal et al., 2017 ). The purpose of this study is to determine the prevalence and association between psychological distress (Depression, Anxiety, and Stress) and adolescent food intake patterns in school, as well as their influence on quality of life. It also focused on determining the correlation food habits can have as a potential driver for mental health and QOL in adolescents. The findings should help guide targeted programs to promote mental health and healthy eating habits among teenagers, addressing their overall well-being in school settings. Materials and Methods Study Design, Setting and Participants A cross-sectional study was conducted from March 2023 to May 2023 among school aged children and adolescents in grade nine, ten, eleven, twelve attending several Government higher secondary schools in District Haripur, Khyber Pakhtunkhwa Pakistan. Sampling Procedure and Sample Size Determination The sample size was estimated to be with the single population formula. Sample size was calculated using the prevalence from a previous research study, with a 95% confidence interval (CI) and a 5% margin of error. As a result, for the first objective, the prevalence of depression is computed as follows: n=(Zα/2) 2 x p (1 - p)/d2 = (1.96)2 x 0.523 x.477/d (0.05)2=383 (Nakie et al., 2022). As a result, we used multi-stage sampling with two stages, factoring in the stage and multiplying the sample size by the number of stages. Therefore, 425 × 2 equals 850. The total sample size was 850+43=893 after accounting for the 5% non-response rate. As a result, the minimal sample size for this study was 843. A stratified multi-stage sampling technique was used. There were several schools in the region, thus the overall sample size for the study was distributed proportionally between schools based on the number of students in each. Within each school, the sample size was again appropriately dispersed throughout the grades (grades nine, ten, eleven, and twelve) based on class size. Then, a suitable sampling procedure was utilized to choose each participant from each stratum (grade). Finally, the selected students from all grades were taken to one hall then the questionnaires were administered after orientation (Nakie et al., 2022). Inclusion and Exclusion Criteria The inclusion criteria were as follows: (i) being a student in grades 9 to 12 at Government Higher Secondary Schools in District Haripur, Khyber Pakhtunkhwa, Pakistan; (ii) being between the ages of 11 and 20; and (iii) include both females and boys. The following were exclusion criteria: (i) the presence of metabolic abnormalities; (ii) any known medical diseases influencing the participant's health and physical activity levels; and (iii) those with intellectual disabilities. Assessment Tools Depression, Anxiety, and Stress Scale for youth (DASS-Y) Data was gathered using a standardized, self-administered questionnaire consisting of four elements. Age, gender, grade, and other socio-demographic information were gathered using structured questionnaires. In the second section, depression, anxiety, and stress were measured using the (DASS-Y). The questionnaire's validity has been confirmed by African countries; the subscales assessing stress, anxiety, and depression have Cronbach's alpha values of 0.85, 0.80, and 0.85, respectively. Over the course of the preceding seven days, participants were asked to assess their symptoms in each domain on a scale from 0 (did not apply at all) to 3 (applied most of the time). Each dimension's scores were totaled. Using the DASS manual, the resultant score was divided by two and categorized as normal, mild, moderate, severe, or extremely severe (Lovibond & Lovibond, 1995). From 0 to 9, depression was classified as normal; from 10 to 13, as mild; from 14 to 20, as moderate; from 21 to 27 as severe; and from 28 and higher, as really serious. 0–7 was considered normal anxiety, 8–9 was considered mild, 10–14 was considered moderate, 15–19 was considered severe, and 20 and higher was considered extremely serious. A stress score of 0–14 was considered normal for those who experienced it, 15–18 mild, 19–25 moderate, 26–33 severe, and 34 and above extremely severe (Yihunie Akalu et al., 2021). Furthermore, the score can be divided into two categories: mild to highly severe disorders such as depression, anxiety, and stress, and otherwise not. Individuals who scored more than or equal to 8 on the depression subscale are considered worried, whereas those who scored more than or equal to 15 on the stress subscale were termed stressful (Lovibond & Lovibond, 1995). Food Behavior Checklist Is A 39-Item Questionnaire The third section of the adolescent’s food behavior checklist is a 39-item questionnaire with four-point Likert scales. Cronbach's alpha (a = 0.92) was used to examine the questionnaire's reliability and validity. This has both positive and negative items, the negative rating were as follows: Never/no=3, sometimes=2, most of the time=1, always=0. The positive ratings were as follows: never/never = 0, sometimes = 3, most of the time = 2, always = 3. All the participants’ scores were put together to generate a tertile group of good, medium, and bad. World Health Organization Quality of Life Assessment Instrument (WHOQOL-BREF) There are 26 items of (WHOQOL-BREF) used to measure QOL and each one has been given a four-point Likert-type score as follows: 1 denotes "bad," 2 "simple," 3 "good," and 4 "very good." The first two questions focus on health satisfaction and self-perception of quality of life. The remaining twenty-four elements are divided into four categories: environment (8 things), social relationships (3 items), psychological (6 items), and physical health (7 items). The four dimensions are converted into a point system ranging from 0 to 100. The QOL is higher when the total score approaches 100. In order to analyze the data, QOL indices were categorized as "high QOL" (tertile 3—58.69 to 100 points), "moderate QOL" (tertile 2—49.48 to 58.68 points), and "low QOL" (tertile 1—0 to 49.47 points) (Fleck et al., 2000). Ethical Consideration Declaration of Helsinki's guidelines was followed in this investigation. The University of Haripur's Research and Ethics Committee in Khyber Pakhtunkhwa, Pakistan granted ethical permission (Approval number: UOH/DASR/2023/1664). Statistical Analysis Statistical analyses were performed using the Statistical Package for Social Science (SPSS) version 22 to provide descriptive statistics such as means, standard deviation, frequency, and percentages. As the data were not normally distributed, non-parametric tests were applied such as Kruskal-Wallis, Chi-square, and correlation to examine the relationship between dependent variables and independent factors. Results Sociodemographic Characteristics of Participants: The total number of participants in the research was 898; 50.9% were females; the age range was usually 14-16 years (50.3%); 46.5% were 9th grade students; and 99.4% were single or unmarried. Table 1 shows most participants’ parents were educated: 33.7% had secondary education, 26.1% were graduates. Regarding father occupation, 47.8% participants were businessmen, 16.7% were private employees, 11.9% were government employees. 48.2% had a family monthly income of <25-50K, 36.0% had less than <25K, and 20.8% had a family medical history. Table 1. Sociodemographic Characteristics of Participants. The sociodemographic details of the study participants are shown in this table, which also shows the distribution of factors including father's occupation, parental education, age, class, marital status, gender, monthly family income, and family medical history. Variables Category n (%) Gender Male Female 441 (49.1) 457 (50.9) Age 11-13years 14-16years 17-20years 77 (8.6) 452 (50.3) 369 (41.1) Class 9 th 10 th 11 th 12 th 418 (46.5) 40 (4.5) 96 (10.7) 344 (38.3) Marital Status Married Single 5 (0.6) 893 (99.4) Father’s Education Primary Secondary Higher secondary Graduation 191 (21.3) 303 (33.7) 170 (18.9) 234 (26.1) Mother’s Education Primary Secondary Higher secondary Graduation 467 (52.0) 220 (24.5) 170 (18.9) 41 (4.6) Father’s Job Farmer Businessman Government employee Private employee Others 44 (4.9) 429 (47.8) 107 (11.9) 150 (16.7) 168 (18.7) Family Monthly Income (PKR) 51000K 323 (36.0) 433 (48.2) 142 (15.8) Family Medical History Yes No 187 (20.8) 711 (79.2) Source= primary data, N= frequency, %= Percentage Prevalence of Psychological Distress: The total prevalence of depression, anxiety, and stress was determined to be 86.6%, 92.4% and 76.8% respectively. Figure 1 shows 82 (9.1%) respondents were somewhat depressed, 251 (28.1%) were moderately depressed, 124 (13.8%) were severely depressed, and 321 (35.7%) were extremely depressed. Similarly, 46 (5.1%) of respondents reported light anxiety, 121 (13.5%) reported moderate anxiety, 164 (18.3%) reported severe anxiety, and 499 (55.6%) reported extremely severe anxiety. Furthermore, 108 (12%) of respondents had mild stress, 219 (24.4%) experienced moderate stress, 221 (24.6%) experienced severe stress, and 142 (15.8%) experienced extremely severe stress. Assessment of Food Habits in Adolescent School Children: Figure 2 shows the eating habits of teenagers. According to the data, 36% of the examined participants (equal to 321 persons) had "bad" eating habits. Another 35% of the participants (314 participants) were classified as having "medium" eating habits. On a more positive, 29% of the adolescents (263 in total) demonstrated "good" eating habits . Assessment of Overall QOL and General Health in Adolescents: Figure 3 shows 39% of school-aged teenagers had an excellent QOL, 30% had a very good quality of life, and 29% had a low QOL. Meanwhile, 42% of respondents reported having overall good general health, 29% reported having very good general health, and 29% reported having overall bad general health as shown in figure 3. Assessment of Qol Domains in School Adolescents: The data found that 39% of respondents were in poor physical health, 42% were in intermediate physical health, and 22% were in excellent physical health. However, 25% of respondents showed poor mental health, 39% showed moderate mental health, and 27% reported good mental health. Meanwhile, 52% of respondents indicated that they had a poor social relationship, 18% showed had a moderate social relationship and 35% reported had a good social relationship. However, 38% of respondents assessed a poor working environment, 38% an average working environment and 25% a good working environment as shown in figure 4. Food Habits as Potential Driver for Mental Health and QOL In Table 2 dietary choices may be a role in psychological discomfort, mental health, and QOL in schools, according to the research. There is a significant association between depression and eating habits (x 2 <137.7, p-value <0.001). Individuals with poor eating habits showed higher depression scores and lower QOL. Anxiety and stress were also shown to have significant correlations with eating behaviors (x 2 <154.6, p-value <0.001) and (x 2 <126.3, p-value <0.001), respectively. Poor eating habits in children resulting in higher levels of anxiety and stress. There is also a link between dietary habits and QOL in schoolchildren. Each domain such as, physical health, psychological health, social relationships, and environment had a strong correlation with dietary practices as shown in table 2 (x 2 < 35.3, p-value < 0.001), x 2 < 6.9, p-value < 0.031, x 2 < 25.8, p-value < 0.001 and x 2 < 16.7, p-value < 0.001). Table 2. Food Habits as Potential Driver for Mental Health and QOL. The table showed the mean rankings and statistical significance (p-value and 2) for each component across three levels of dietary habits (Bad, Medium, and Good). The p-values reflect the importance of the relationships, whereas *p < 0.05, **p < 0.01, ***p < 0.001. Factors Levels of food habits Mean Rank x 2 p -value Depression score Bad food habits Medium food habits Good food habits 526.8 501.7 292.8 137.7 < 0.001*** Anxiety score Bad food habits Medium food habits Good food habits 527.9 509.6 283.0 154.6 < 0.001*** Stress score Bad food habits Medium food habits Good food habits 521.1 502.2 299.1 126.3 < 0.001*** Physical health Bad food habits Medium food habits Good food habits 435.6 400.0 525.5 35.3 < 0.001*** Psychological health Bad food habits Medium food habits Good food habits 453.4 421.7 477.9 6.9 < 0.031* Social relationship Bad food habits Medium food habits Good food habits 493.7 457.1 368.4 25.8 < 0.001*** Environment Bad food habits Medium food habits Good food habits 489.0 449.8 400.7 16.7 < 0.001*** Kruskal Wallis Test, x 2 chi-square, Significance*p < 0.05, ***p < 0.001 Correlation between psychological distress, quality of life and food habits. The study showed substantial correlation with eating habits but a negative relationship (r value in the negative) between stress, anxiety, and depression. Physical health showed a positive correlation with significance association (r < 0.192, p < 0.001), psychological health showed a positive but week correlation with significance association (r < 0.071, p < 0.034), social relationships showed a negative week correlation with food habits but significance association (r <0.133, p < 0.001), and environment showed a negative week correlation with food habits but significance association (r <0.106, p < 0.001) as shown in table 3. Table 3. Correlation between psychological distress, QOL and food habits. The table showed an association (r) between dietary habits scores and important health variables such as depression, anxiety, stress, physical health, psychological health, social relationships, and environment. The importance of these correlations is determined by the p-values. Negative (r) values indicate an inverse relationship, in which greater dietary habits scores are associated with worse health factor results. Variables Food habits score Depression r= -0.316 p = <0.001*** Anxiety r= -0.337 p = < 0.001*** Stress r= -0.295 p = <0.001*** Physical Health r= 0.192 p = <0.001*** Psychological Health r= 0.071 p = 0.034* Social Relationship r= -0.133 p = <0.001*** Environment r= -0.106 p = <0.001*** Correlation & chi-square r= Pearson Correlation Significance*p < 0.05, ***p < 0.001 Association of Gender with QOL, Psychological Distress and Food Habits: The findings indicated a substantial correlation between social relations and gender (AOR=1.014, 95% CI: 1.000-1.027, p=0.046) and a strong link between environmental factors and gender (AOR=1.005, 95% CI: 0.988-1.023, p<0.001). Gender was also found to be strongly associated with indicators of psychological distress, specifically depression and stress. Food habits had a significant effect on gender (AOR=0.982, 95% CI: 0.961-1.003, p < 0.001). Other variables, such as physical health, psychological well-being, overall QOL, and general health, did not demonstrate any significant correlation with gender as shown in S1. Relationship Between Family Medical History and Dependent Variables: The study found no significant associations between physical health, psychological health, environment, overall general health, or family medical history. However, a substantial relationship was found between social relations and overall QOL with family medical history, but that relationship was only brief of statistical significance (AOR=1.007, 95% CI: 1.000-1.015, p=0.060). Depression, anxiety, and stress did not demonstrate any significant associations with family medical history, and eating habits had a minor, non-significant impact as shown in S2. Discussion The findings highlight the importance of addressing these issues and providing enough help and therapies to increase the well-being of individuals in this community. Depression, Stress and anxiety impair student’s emotional, cognitive, and social abilities and raise absenteeism from school, which has a negative impact on their academic performance. The outcome has a big impact on children’s emotional, mental, physical, and social health. According to the findings, a significant proportion of students experienced stress, anxiety, and depression. According to the results of the current study, eating habits have a statistically significant relationship with stress, anxiety, depression, and QOL. Depression was found to be very common in school children, which is consistent with previous findings (Sandal et al., 2017 ). There is a chance that a variety of school-related variables such a deficient supporting atmosphere in the classroom contribute to the greater rate of depression among students attending government schools, as reported in (Meng et al., 2013 ), (Raniti et al., 2022 ). Anxiety was significantly higher in this study among schoolchildren than depression, which is essentially identical to a research was done on Saudi female students and Malaysian high school students., probably due to variables such as traumatic events and psychosocial stressors (Awwas et al., 2023 ). Comprehensive techniques and interventions are required to effectively support individuals in managing and reducing their anxiety levels. However, the prevalence of anxiety in this study was greater than that observed among Saudi Arabian schoolboys in a 2014 study of adolescents from India and Iraqi high school students. The discrepancy could be attributed to differences in sociocultural, socioeconomic, study population type, and health facility availability between those nations and Ethiopia (Nakie et al., 2022 ). This is a contentious issue; several reports in favor have been published (Elsner et al., 2022 ). The current study's findings suggest more research to be conducted in this area for improved future outcomes. Environmental variables, lifestyle, mental health, food habits, and other relevant dimensions must be addressed in school-based health interventions. The outcomes of this study provide insights into adolescent food habits, revealing a variety of dietary trends. A significant proportion of the adolescents had "bad food habits," indicating a tendency toward less healthy eating choices, which is consistent with previous findings (Viljakainen et al., 2019 ), which means that some factors such as low socioeconomic status, peer pressure, education, and nutrition knowledge play a role. According to the WHO (2016), a balanced diet should consist of a high intake of fruits, vegetables, and whole grains, as well as limiting your consumption of saturated fats, sodium, and processed carbohydrates (Organização Mundial de Saúde, 2023 ). Given that many healthy behaviors are created and established throughout the adolescent to early adult transition, this period may be significant for health promotion interventions such as the promotion of good eating (Winpenny et al., 2018 ). It was found that the QOL has declined, which is consistent with earlier findings (Celebre et al., 2021 ) and might be attributed to several factors such as lifestyle characteristics, sleep patterns, dietary habits, and life events, which are also mentioned in (Shin et al., 2022 ). This research could help provide the groundwork for future interventional programs promoting healthy eating habits. A universal healthy eating policy should be established, potentially included, and practiced in all regions, including developing and developed nations, and should be blended with varied socio-cultural and psychological characteristics across different locations. Conclusion In conclusion, unhealthy eating habits significantly raise psychological distress levels and lower school-age children's and teenagers' QOL. Additional research should be conducted to find factors other than those already mentioned. Environmental variables, lifestyle, mental health, and other associated constructions must be addressed in school-based health treatments. Successful management of depressive symptoms and stress may have a major impact on improving students’ QOL. Improving the eating habits of low-income students through a school-based food distribution program results in significant benefits. Declarations Funding statement There is no funding support for this research. Informed Consent to Participate in Study Before participating in the study, informed consent was obtained from each participant after explaining objective and possible outcomes of the study. Assent was taken from parents or legal guardian for all participants under 18 years of age. Data Availability Statement: Data related to this study will be available on request to the corresponding author. Author Contribution Ismail Qadri, Azhar Mehmood, and Hammad Sha collected data andn interpreted data from various schools. Khadija Muqadas conceptualize the idea and wrote the whole manuscript. Muhammad Subhan Nazar, Ayesha Umar Chaudhary and Muhammad Junaid analyzed the data. Ijaz ul Haq and Shahbaz Ahmad Zakki reviewed the manuscript, made final changes, and approved the final version of manuscript. Acknowledgement We extend our sincere gratitude to the District Education Officer for their invaluable support in facilitating data collection for our research. 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(2022). The role of school connectedness in the prevention of youth depression and anxiety: a systematic review with youth consultation. BMC Public Health , 22 (1). https://doi.org/10.1186/S12889-022-14364-6 Regan, C., Walltott, H., Kjellenberg, K., Nyberg, G., & Helgadóttir, B. (2022). Investigation of the Associations between Diet Quality and Health-Related Quality of Life in a Sample of Swedish Adolescents. Nutrients , 14 (12), 2489. https://doi.org/10.3390/nu14122489 Sala, C. A., Ramón-Arbués, E., Echániz-Serrano, E., Martínez-Abadía, B., Antón-Solanas, I., Cobos-Rincón, A., Santolalla-Arnedo, I., Juárez-Vela, R., & Jerue, B. A. (2022). Predictors of the Quality of Life of University Students: A Cross-Sectional Study. Mdpi.ComE Ramón-Arbués, E Echániz-Serrano, B Martínez-Abadía, I Antón-Solanas, A Cobos-RincónInternational Journal of Environmental Research and Public Health, 2022•mdpi.Com , 19 , 12043. https://doi.org/10.3390/ijerph191912043 Sandal, R., Goel, N., Sharma, M., Bakshi, R., Singh, N., & Kumar, D. (2017). Prevalence of depression, anxiety and stress among school going adolescent in Chandigarh. Journal of Family Medicine and Primary Care , 6 (2), 405. https://doi.org/10.4103/2249-4863.219988 Seo, E. J., Ahn, J.-A., Hayman, L. L., & Kim, C.-J. (2018). The Association Between Perceived Stress and Quality of Life in University Students: The Parallel Mediating Role of Depressive Symptoms and Health-Promoting Behaviors. Asian Nursing Research , 12 (3), 190–196. https://doi.org/10.1016/j.anr.2018.08.001 Shin, H., Jeon, S., & Cho, I. (2022). Factors influencing health-related quality of life in adolescent girls: a path analysis using a multi-mediation model. Health and Quality of Life Outcomes , 20 (1). https://doi.org/10.1186/S12955-022-01954-6 Viljakainen, J., Augusta De Oliveira Figueiredo, R., Viljakainen, H., Roos, E., Weiderpass, E., & Rounge, T. B. (2019). Eating habits and weight status in Finnish adolescents. Cambridge.OrgJ Viljakainen, RA de Oliveira Figueiredo, H Viljakainen, E Roos, E Weiderpass, TB RoungePublic Health Nutrition, 2019•cambridge.Org , 14 , 2617–2624. https://doi.org/10.1017/S1368980019001447 Winpenny, E. M., van Sluijs, E. M. F., White, M., Klepp, K. I., Wold, B., & Lien, N. (2018). Changes in diet through adolescence and early adulthood: longitudinal trajectories and association with key life transitions. The International Journal of Behavioral Nutrition and Physical Activity , 15 (1), 86. https://doi.org/10.1186/S12966-018-0719-8 Yihunie Akalu, T., Alemu Gelaye, K., Addis Bishaw, M., Yitayih Tilahun, S., Yeshaw, Y., Azale, T., Tsegaye, T., Asmelash, D., & Akalu, Y. (2021). Depression, anxiety, and stress symptoms and its associated factors among residents of Gondar Town during the early stage of COVID-19 pandemic. Taylor & Francis , 14 , 1073–1083. https://doi.org/10.2147/RMHP.S296796 Additional Declarations No competing interests reported. Supplementary Files ESM1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6242891","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451478128,"identity":"c175a8f6-c11d-4a74-b165-bdfcb90ec13a","order_by":0,"name":"Khadija Muqadas","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Khadija","middleName":"","lastName":"Muqadas","suffix":""},{"id":451478132,"identity":"be646d96-8ea1-4760-b5aa-5b5b2c90b352","order_by":1,"name":"Shahbaz Ahmad Zakki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYJACxoYDEnIMDDxAJhsDhCZGizHJWhgSG4jWIt9+/OHHGWcs0jcc7z3A8KHsMIM5zwH8WgzOJCRLbrghkbvhzLkExhnnDjNY9jYQ0MKQcEDywQeglhs5Bsy8bYcZDM4Tclj/w+afQC3pBiAtf4nRwnAjmQ3ksASwFkaQlrOEHHbjGZvljDMShjPPnDE42HMuncey5wAhh6U/vtlzrE6e73iP4YMfZdZy5jwJhFyGBEDG8xiQoAHmVNK1jIJRMApGwTAHAHjvSg+9vHCpAAAAAElFTkSuQmCC","orcid":"","institution":"University of Haripur","correspondingAuthor":true,"prefix":"","firstName":"Shahbaz","middleName":"Ahmad","lastName":"Zakki","suffix":""},{"id":451478133,"identity":"a288a0b5-f3d4-4ba6-95fa-bdb48d367da9","order_by":2,"name":"Ijaz ul Haq","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Ijaz","middleName":"ul","lastName":"Haq","suffix":""},{"id":451478134,"identity":"e8ddef8d-6fdd-43a0-bcda-96601099ccc5","order_by":3,"name":"Muhammad Ismail Qadri","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Ismail","lastName":"Qadri","suffix":""},{"id":451478136,"identity":"889157d6-dd0a-450d-84eb-1d11cb1b1ecd","order_by":4,"name":"Azhar Mehmood","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Azhar","middleName":"","lastName":"Mehmood","suffix":""},{"id":451478139,"identity":"f292a3b3-7b50-483d-a78e-cd627f930558","order_by":5,"name":"Syed Hammad Abid","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Syed","middleName":"Hammad","lastName":"Abid","suffix":""},{"id":451478142,"identity":"3e0cb836-f23b-497c-8990-b138bac3b206","order_by":6,"name":"Muhammad Subhan Nazar","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Subhan","lastName":"Nazar","suffix":""},{"id":451478143,"identity":"30548e29-e139-4ec1-842d-13ed3efa9244","order_by":7,"name":"Muhammad Junaid","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Junaid","suffix":""},{"id":451478144,"identity":"ee382261-4d31-4baa-bf99-a23b50e8f694","order_by":8,"name":"Ayesha Umar Chaudhary","email":"","orcid":"","institution":"University of Haripur","correspondingAuthor":false,"prefix":"","firstName":"Ayesha","middleName":"Umar","lastName":"Chaudhary","suffix":""}],"badges":[],"createdAt":"2025-03-17 09:09:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6242891/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6242891/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82166724,"identity":"30290064-6752-4150-9db8-35e05769869f","added_by":"auto","created_at":"2025-05-07 09:15:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78995,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLevels of psychological distress in adolescent’s school children. \u003c/strong\u003eThe Prevalence and Severity of Depression, Anxiety, and Stress in the Study Population. This graph shows the overall prevalence of depression, anxiety, and stress, as well as the distribution of participants across various severity levels within each category. It emphasizes the considerable mental health issues experienced by those who participated in the study.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6242891/v1/30a3f903f258e903e72a0016.png"},{"id":82168611,"identity":"7b105c1b-d195-499b-82b3-0bb486af0d60","added_by":"auto","created_at":"2025-05-07 09:31:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65163,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLevels of food habits in adolescent school children. \u003c/strong\u003eIt depicts the categorization of eating habits among adolescent schoolchildren, highlighting the distribution of food habits throughout the sample population.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6242891/v1/49f9e331c37ab91e37706204.png"},{"id":82164633,"identity":"fe7933eb-0875-469a-a5a6-6d2b8407b397","added_by":"auto","created_at":"2025-05-07 09:07:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":204187,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLevels of overall QOL and general health. \u003c/strong\u003eIt depicts the assessment of overall QOL and general health among adolescents as well as the distribution of participants at various levels of QOL and general health status.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6242891/v1/0bd035e50810adab6017aa17.png"},{"id":82164626,"identity":"87e2506d-3bcb-445e-89cf-e50e4f440ef3","added_by":"auto","created_at":"2025-05-07 09:07:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":186209,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLevels of QOL domains\u003c/strong\u003e. The overall health and QOL of school-aged adolescents. The distribution of overall health and QOL scores is shown in the figure, illustrating the respondents' different levels of wellbeing.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6242891/v1/5ff47f87785353914dc00a78.png"},{"id":85639457,"identity":"5e848ab9-5b0a-442a-a2ee-72b8f6badfc9","added_by":"auto","created_at":"2025-06-30 07:02:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1685371,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6242891/v1/5cb17635-d0f0-42f4-a9e9-771f17d9a4dd.pdf"},{"id":82164624,"identity":"8857e1b5-2a2f-4eeb-9d34-06a5307238c0","added_by":"auto","created_at":"2025-05-07 09:07:07","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":20572,"visible":true,"origin":"","legend":"","description":"","filename":"ESM1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6242891/v1/380cfecb6699abe1690f7008.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAssociation of Food Habits on Adolescents’ Mental Distress and Quality of Life: an Observational Study From Higher Secondary Schools of Pakistan\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChildren and adolescents confront ever-increasing social, emotional, and mental health challenges. Schools, as one of the primary systems in their life, are required to broaden their goals and help with addressing these challenges (Cefai et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). High academic attainment expectations have produced an extremely stressful situation that if not addressed, can be detrimental to their physical and mental health (Alharbi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Children and adolescents constitute of almost one third (2.2\u0026nbsp;billion individuals) of the world\u0026rsquo;s population however, mental health problems affect 10\u0026ndash;20% of children and adolescents worldwide (L\u0026oacute;pez-Gil et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to a survey of adolescents in 17 nations, one in every 20 had a depressive episode on average. Psychological distress is the fourth largest contributor to the global disease burden and the leading cause of disability (Bedaso et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHealthy lifestyles, mental health, and wellness are critical for children's physical, social, and emotional development. Unhealthy lifestyles and psychological issues at a young age can be difficult to overcome and can leave an effect on adulthood (Maximova et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Prevalence of depression, anxiety, and stress (DAS) is increasing among children and adolescents. These mental health related problems are dangerous and may even prove to be suicidal and fatal. School adolescents do not consume a high-quality diet, therefore self-reported mental health issues within this group are on the rise. Food consumption is one of the environmental and psychological factors that lead to poor mental health (Regan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Adolescents\u0026rsquo; eating habits have an important effect on their physical, emotional, and mental development. Their physical and academic progress will be influenced by the quality of their nourishment. Indeed, now is the time to build habits that will last a lifetime (Basiak-Rasała et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Students in better health often study more effectively, accomplish higher academic goals and graduate at a higher rate, all of which offer long-term advantages (Kwok et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eQOL has become one of the ultimate goals of health services. According to the subjective definition of QOL with respect to the school context its varies, because its include the dimensions i.e. teacher-student relationship, climate and social relationship, commitment to school work, academic achievements, promotions, sense of responsibility, and physical environment of class room and school (Cruz et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). QOL is a complex and diverse notion that has been used to analyze several elements of people's lives, including physical and psychological well-being, financial independence, social interactions, personal views, and living situation (Sala et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDepressive symptoms in early adulthood can have a negative influence on future employment and social relationships as well as QOL later in life. Successful management of depressive symptoms as well as stress may play a significant influence in enhancing the QOL (Seo et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Ensuring the well-being of children and adolescents is a critical step toward healthy growth, healthy habits, and future accomplishments. Students mental health and QOL increase significantly when their eating habits are improved (Diamantis et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Early detection is the key to healthy mental state for future generations (Sandal et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The purpose of this study is to determine the prevalence and association between psychological distress (Depression, Anxiety, and Stress) and adolescent food intake patterns in school, as well as their influence on quality of life. It also focused on determining the correlation food habits can have as a potential driver for mental health and QOL in adolescents. The findings should help guide targeted programs to promote mental health and healthy eating habits among teenagers, addressing their overall well-being in school settings.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design, Setting and Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted from March 2023 to May 2023 among school aged children and adolescents in grade nine, ten, eleven, twelve attending several Government higher secondary schools in District Haripur, Khyber Pakhtunkhwa Pakistan.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling Procedure and Sample Size Determination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was estimated to be with the single population formula. Sample size was calculated using the prevalence from a previous research study, with a 95% confidence interval (CI) and a 5% margin of error. As a result, for the first objective, the prevalence of depression is computed as follows: n=(Z\u0026alpha;/2) 2 x p (1 - p)/d2 = (1.96)2 x 0.523 x.477/d (0.05)2=383 (Nakie et al., 2022). As a result, we used multi-stage sampling with two stages, factoring in the stage and multiplying the sample size by the number of stages. Therefore, 425 \u0026times; 2 equals 850.\u003c/p\u003e\n\u003cp\u003eThe total sample size was 850+43=893 after accounting for the 5% non-response rate. As a result, the minimal sample size for this study was 843. A stratified multi-stage sampling technique was used. There were several schools in the region, thus the overall sample size for the study was distributed proportionally between schools based on the number of students in each. Within each school, the sample size was again appropriately dispersed throughout the grades (grades nine, ten, eleven, and twelve) based on class size. Then, a suitable sampling procedure was utilized to choose each participant from each stratum (grade). Finally, the selected students from all grades were taken to one hall then the questionnaires were administered after orientation (Nakie et al., 2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and Exclusion Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria were as follows: (i) being a student in grades 9 to 12 at Government Higher Secondary Schools in District Haripur, Khyber Pakhtunkhwa, Pakistan; (ii) being between the ages of 11 and 20; and (iii) include both females and boys. The following were exclusion criteria: (i) the presence of metabolic abnormalities; (ii) any known medical diseases influencing the participant\u0026apos;s health and physical activity levels; and (iii) those with intellectual disabilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment Tools\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepression, Anxiety, and Stress Scale for youth (DASS-Y)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was gathered using a standardized, self-administered questionnaire consisting of four elements. Age, gender, grade, and other socio-demographic information were gathered using structured questionnaires. In the second section, depression, anxiety, and stress were measured using the (DASS-Y). The questionnaire\u0026apos;s validity has been confirmed by African countries; the subscales assessing stress, anxiety, and depression have Cronbach\u0026apos;s alpha values of 0.85, 0.80, and 0.85, respectively. Over the course of the preceding seven days, participants were asked to assess their symptoms in each domain on a scale from 0 (did not apply at all) to 3 (applied most of the time). Each dimension\u0026apos;s scores were totaled. Using the DASS manual, the resultant score was divided by two and categorized as normal, mild, moderate, severe, or extremely severe (Lovibond \u0026amp; Lovibond, 1995).\u003c/p\u003e\n\u003cp\u003eFrom 0 to 9, depression was classified as normal; from 10 to 13, as mild; from 14 to 20, as moderate; from 21 to 27 as severe; and from 28 and higher, as really serious. 0\u0026ndash;7 was considered normal anxiety, 8\u0026ndash;9 was considered mild, 10\u0026ndash;14 was considered moderate, 15\u0026ndash;19 was considered severe, and 20 and higher was considered extremely serious. A stress score of 0\u0026ndash;14 was considered normal for those who experienced it, 15\u0026ndash;18 mild, 19\u0026ndash;25 moderate, 26\u0026ndash;33 severe, and 34 and above extremely severe (Yihunie Akalu et al., 2021). Furthermore, the score can be divided into two categories: mild to highly severe disorders such as depression, anxiety, and stress, and otherwise not. Individuals who scored more than or equal to 8 on the depression subscale are considered worried, whereas those who scored more than or equal to 15 on the stress subscale were termed stressful (Lovibond \u0026amp; Lovibond, 1995).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFood Behavior Checklist Is A 39-Item Questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe third section of the adolescent\u0026rsquo;s food behavior checklist is a 39-item questionnaire with four-point Likert scales. Cronbach\u0026apos;s alpha (a = 0.92) was used to examine the questionnaire\u0026apos;s reliability and validity. This has both positive and negative items, the negative rating were as follows: Never/no=3, sometimes=2, most of the time=1, always=0. The positive ratings were as follows: never/never = 0, sometimes = 3, most of the time = 2, always = 3. All the participants\u0026rsquo; scores were put together to generate a tertile group of good, medium, and bad.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWorld Health Organization Quality of Life Assessment Instrument (WHOQOL-BREF)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are 26 items of (WHOQOL-BREF) used to measure QOL and each one has been given a four-point Likert-type score as follows: 1 denotes \u0026quot;bad,\u0026quot; 2 \u0026quot;simple,\u0026quot; 3 \u0026quot;good,\u0026quot; and 4 \u0026quot;very good.\u0026quot; The first two questions focus on health satisfaction and self-perception of quality of life. The remaining twenty-four elements are divided into four categories: environment (8 things), social relationships (3 items), psychological (6 items), and physical health (7 items). The four dimensions are converted into a point system ranging from 0 to 100. The QOL is higher when the total score approaches 100. In order to analyze the data, QOL indices were categorized as \u0026quot;high QOL\u0026quot; (tertile 3\u0026mdash;58.69 to 100 points), \u0026quot;moderate QOL\u0026quot; (tertile 2\u0026mdash;49.48 to 58.68 points), and \u0026quot;low QOL\u0026quot; (tertile 1\u0026mdash;0 to 49.47 points) (Fleck et al., 2000).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeclaration of Helsinki\u0026apos;s guidelines was followed in this investigation. The University of Haripur\u0026apos;s Research and Ethics Committee in Khyber Pakhtunkhwa, Pakistan granted ethical permission (Approval number: UOH/DASR/2023/1664).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using the Statistical Package for Social Science (SPSS) version 22 to provide descriptive statistics such as means, standard deviation, frequency, and percentages. As the data were not normally distributed, non-parametric tests were applied such as Kruskal-Wallis, Chi-square, and correlation to examine the relationship between dependent variables and independent factors.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSociodemographic Characteristics of Participants:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total number of participants in the research was 898; 50.9% were females; the age range was usually 14-16 years (50.3%); 46.5% were 9th grade students; and 99.4% were single or unmarried. Table 1 shows most participants\u0026rsquo; parents were educated: 33.7% had secondary education, 26.1% were graduates. Regarding father occupation, 47.8% participants were businessmen, 16.7% were private employees, 11.9% were government employees. 48.2% had a family monthly income of \u0026lt;25-50K, 36.0% had less than \u0026lt;25K, and 20.8% had a family medical history.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Sociodemographic Characteristics of Participants.\u0026nbsp;\u003c/strong\u003eThe sociodemographic details of the study participants are shown in this table, which also shows the distribution of factors including father\u0026apos;s occupation, parental education, age, class, marital status, gender, monthly family income, and family medical history.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eGender\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e441 (49.1)\u003c/p\u003e\n \u003cp\u003e457 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e11-13years\u003c/p\u003e\n \u003cp\u003e14-16years\u003c/p\u003e\n \u003cp\u003e17-20years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; 77 (8.6)\u003c/p\u003e\n \u003cp\u003e452 (50.3)\u003c/p\u003e\n \u003cp\u003e369 (41.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eClass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e9\u003csup\u003eth\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10\u003csup\u003eth\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11\u003csup\u003eth\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12\u003csup\u003eth\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e418 (46.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 40 (4.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 96 (10.7)\u003c/p\u003e\n \u003cp\u003e344 (38.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMarital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;5 (0.6)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;893 (99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFather\u0026rsquo;s Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003cp\u003eHigher secondary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eGraduation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;191 (21.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;303 (33.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;170 (18.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;234 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMother\u0026rsquo;s Education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003cp\u003eHigher secondary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eGraduation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;467 (52.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;220 (24.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;170 (18.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;41 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFather\u0026rsquo;s Job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFarmer\u003c/p\u003e\n \u003cp\u003eBusinessman\u003c/p\u003e\n \u003cp\u003eGovernment employee\u003c/p\u003e\n \u003cp\u003ePrivate employee\u003c/p\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;44 (4.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;429 (47.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;107 (11.9)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;150 (16.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;168 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFamily Monthly Income (PKR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;25000K\u003c/p\u003e\n \u003cp\u003e26000K-50000K\u003c/p\u003e\n \u003cp\u003e\u0026gt;51000K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;323 (36.0)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;433 (48.2)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;142 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFamily Medical History\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026nbsp;187 (20.8)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;711 (79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource= primary data, N= frequency, %= Percentage\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of Psychological Distress:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total prevalence of depression, anxiety, and stress was determined to be 86.6%, 92.4% and 76.8% respectively. Figure 1 shows 82 (9.1%) respondents were somewhat depressed, 251 (28.1%) were moderately depressed, 124 (13.8%) were severely depressed, and 321 (35.7%) were extremely depressed. Similarly, 46 (5.1%) of respondents reported light anxiety, 121 (13.5%) reported moderate anxiety, 164 (18.3%) reported severe anxiety, and 499 (55.6%) reported extremely severe anxiety. Furthermore, 108 (12%) of respondents had mild stress, 219 (24.4%) experienced moderate stress, 221 (24.6%) experienced severe stress, and 142 (15.8%) experienced extremely severe stress.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Food Habits in Adolescent School Children:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Figure 2 shows the eating habits of teenagers. According to the data, 36% of the examined participants (equal to 321 persons) had \u0026quot;bad\u0026quot; eating habits. Another 35% of the participants (314 participants) were classified as having \u0026quot;medium\u0026quot; eating habits. On a more positive, 29% of the adolescents (263 in total) demonstrated \u0026quot;good\u0026quot; eating habits\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Overall QOL and General Health in Adolescents:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 3 shows 39% of school-aged teenagers had an excellent QOL, 30% had a very good quality of life, and 29% had a low QOL. Meanwhile, 42% of respondents reported having overall good general health, 29% reported having very good general health, and 29% reported having overall bad general health as shown in figure 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Qol Domains in School Adolescents:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data found that 39% of respondents were in poor physical health, 42% were in intermediate physical health, and 22% were in excellent physical health. However, 25% of respondents showed poor mental health, 39% showed moderate mental health, and 27% reported good mental health. Meanwhile, 52% of respondents indicated that they had a poor social relationship, 18% showed had a moderate social relationship and 35% reported had a good social relationship. However, 38% of respondents assessed a poor working environment, 38% an average working environment and 25% a good working environment as shown in figure 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFood Habits as Potential Driver for Mental Health and QOL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Table 2 dietary choices may be a role in psychological discomfort, mental health, and QOL in schools, according to the research. There is a significant association between depression and eating habits (x\u003csup\u003e2\u003c/sup\u003e \u0026lt;137.7, p-value \u0026lt;0.001). Individuals with poor eating habits showed higher depression scores and lower QOL. Anxiety and stress were also shown to have significant correlations with eating behaviors (x\u003csup\u003e2\u003c/sup\u003e \u0026lt;154.6, p-value \u0026lt;0.001) and (x\u003csup\u003e2\u003c/sup\u003e \u0026lt;126.3, p-value \u0026lt;0.001), respectively. Poor eating habits in children resulting in higher levels of anxiety and stress. There is also a link between dietary habits and QOL in schoolchildren. Each domain such as, physical health, psychological health, social relationships, and environment had a strong correlation with dietary practices as shown in table 2 (x\u003csup\u003e2\u003c/sup\u003e \u0026lt; 35.3, p-value \u0026lt; 0.001), x\u003csup\u003e2\u003c/sup\u003e \u0026lt; 6.9, p-value \u0026lt; 0.031, x\u003csup\u003e2\u003c/sup\u003e \u0026lt; 25.8, p-value \u0026lt; 0.001 and x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e\u0026lt; 16.7, p-value \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Food Habits as Potential Driver for Mental Health and QOL.\u0026nbsp;\u003c/strong\u003eThe table showed the mean rankings and statistical significance (p-value and 2) for each component across three levels of dietary habits (Bad, Medium, and Good). The p-values reflect the importance of the relationships, whereas *p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e 0.05, **p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e 0.01, ***p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e 0.001.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevels of food habits\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ex\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003cem\u003e-value\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003eDepression score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBad food habits\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedium food habits\u003c/p\u003e\n \u003cp\u003eGood food habits\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e526.8\u003c/p\u003e\n \u003cp\u003e501.7\u003c/p\u003e\n \u003cp\u003e292.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e137.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003eAnxiety score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBad food habits\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedium food habits\u003c/p\u003e\n \u003cp\u003eGood food habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e527.9\u003c/p\u003e\n \u003cp\u003e509.6\u003c/p\u003e\n \u003cp\u003e283.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e154.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003eStress score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBad food habits\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedium food habits\u003c/p\u003e\n \u003cp\u003eGood food habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e521.1\u003c/p\u003e\n \u003cp\u003e502.2\u003c/p\u003e\n \u003cp\u003e299.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e126.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003ePhysical health\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBad food habits\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedium food habits\u003c/p\u003e\n \u003cp\u003eGood food habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e435.6\u003c/p\u003e\n \u003cp\u003e400.0\u003c/p\u003e\n \u003cp\u003e525.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003ePsychological health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBad food habits\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedium food habits\u003c/p\u003e\n \u003cp\u003eGood food habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e453.4\u003c/p\u003e\n \u003cp\u003e421.7\u003c/p\u003e\n \u003cp\u003e477.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.031*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003eSocial relationship\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBad food habits\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedium food habits\u003c/p\u003e\n \u003cp\u003eGood food habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e493.7\u003c/p\u003e\n \u003cp\u003e457.1\u003c/p\u003e\n \u003cp\u003e368.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 131px;\"\u003e\n \u003cp\u003eEnvironment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eBad food habits\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMedium food habits\u003c/p\u003e\n \u003cp\u003eGood food habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e489.0\u003c/p\u003e\n \u003cp\u003e449.8\u003c/p\u003e\n \u003cp\u003e400.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt; 0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eKruskal Wallis Test, \u003cem\u003ex\u003csup\u003e2\u003c/sup\u003e chi-square,\u003c/em\u003e Significance*p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e 0.05, ***p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e 0.001\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation between psychological distress, quality of life and food habits.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study showed substantial correlation with eating habits but a negative relationship (r value in the negative) between stress, anxiety, and depression. Physical health showed a positive correlation with significance association (r \u0026lt; 0.192, p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e0.001), psychological health showed a positive but week correlation with significance association (r \u0026lt; 0.071, p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e0.034), social relationships showed a negative week correlation with food habits but significance association (r \u0026lt;0.133, p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e0.001), and environment showed a negative week correlation with food habits but significance association (r \u0026lt;0.106, p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e0.001) as shown in table 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e \u003cstrong\u003eCorrelation between psychological distress, QOL and food habits.\u0026nbsp;\u003c/strong\u003eThe table showed an association (r) between dietary habits scores and important health variables such as depression, anxiety, stress, physical health, psychological health, social relationships, and environment. The importance of these correlations is determined by the p-values. Negative (r) values indicate an inverse relationship, in which greater dietary habits scores are associated with worse health factor results.\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFood habits score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cem\u003er= -0.316\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ep\u003cem\u003e= \u0026lt;0.001***\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eAnxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cem\u003er= -0.337\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ep\u003cem\u003e= \u0026lt; 0.001***\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eStress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cem\u003er= -0.295\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ep\u003cem\u003e= \u0026lt;0.001***\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003ePhysical Health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cem\u003er= 0.192\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ep\u003cem\u003e= \u0026lt;0.001***\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003ePsychological Health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cem\u003er= 0.071\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ep\u003cem\u003e= 0.034*\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eSocial Relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cem\u003er= -0.133\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ep\u003cem\u003e= \u0026lt;0.001***\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eEnvironment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u003cem\u003er= -0.106\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ep\u003cem\u003e= \u0026lt;0.001***\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCorrelation \u0026amp; chi-square r= Pearson Correlation Significance*p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e 0.05, ***p\u003cem\u003e\u0026nbsp;\u0026lt;\u003c/em\u003e 0.001\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation of Gender with QOL, Psychological Distress and Food Habits:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings indicated a substantial correlation between social relations and gender (AOR=1.014, 95% CI: 1.000-1.027, p=0.046) and a strong link between environmental factors and gender (AOR=1.005, 95% CI: 0.988-1.023, p\u0026lt;0.001). Gender was also found to be strongly associated with indicators of psychological distress, specifically depression and stress. Food habits had a significant effect on gender (AOR=0.982, 95% CI: 0.961-1.003, p \u0026lt; 0.001). Other variables, such as physical health, psychological well-being, overall QOL, and general health, did not demonstrate any significant correlation with gender as shown in S1. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship Between Family Medical History and Dependent Variables:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study found no significant associations between physical health, psychological health, environment, overall general health, or family medical history. However, a substantial relationship was found between social relations and overall QOL with family medical history, but that relationship was only brief of statistical significance (AOR=1.007, 95% CI: 1.000-1.015, p=0.060). Depression, anxiety, and stress did not demonstrate any significant associations with family medical history, and eating habits had a minor, non-significant impact as shown in S2.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings highlight the importance of addressing these issues and providing enough help and therapies to increase the well-being of individuals in this community. Depression, Stress and anxiety impair student\u0026rsquo;s emotional, cognitive, and social abilities and raise absenteeism from school, which has a negative impact on their academic performance. The outcome has a big impact on children\u0026rsquo;s emotional, mental, physical, and social health. According to the findings, a significant proportion of students experienced stress, anxiety, and depression. According to the results of the current study, eating habits have a statistically significant relationship with stress, anxiety, depression, and QOL. Depression was found to be very common in school children, which is consistent with previous findings (Sandal et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). There is a chance that a variety of school-related variables such a deficient supporting atmosphere in the classroom contribute to the greater rate of depression among students attending government schools, as reported in (Meng et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), (Raniti et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnxiety was significantly higher in this study among schoolchildren than depression, which is essentially identical to a research was done on Saudi female students and Malaysian high school students., probably due to variables such as traumatic events and psychosocial stressors (Awwas et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Comprehensive techniques and interventions are required to effectively support individuals in managing and reducing their anxiety levels. However, the prevalence of anxiety in this study was greater than that observed among Saudi Arabian schoolboys in a 2014 study of adolescents from India and Iraqi high school students. The discrepancy could be attributed to differences in sociocultural, socioeconomic, study population type, and health facility availability between those nations and Ethiopia (Nakie et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis is a contentious issue; several reports in favor have been published (Elsner et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The current study's findings suggest more research to be conducted in this area for improved future outcomes. Environmental variables, lifestyle, mental health, food habits, and other relevant dimensions must be addressed in school-based health interventions. The outcomes of this study provide insights into adolescent food habits, revealing a variety of dietary trends. A significant proportion of the adolescents had \"bad food habits,\" indicating a tendency toward less healthy eating choices, which is consistent with previous findings (Viljakainen et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which means that some factors such as low socioeconomic status, peer pressure, education, and nutrition knowledge play a role. According to the WHO (2016), a balanced diet should consist of a high intake of fruits, vegetables, and whole grains, as well as limiting your consumption of saturated fats, sodium, and processed carbohydrates (Organiza\u0026ccedil;\u0026atilde;o Mundial de Sa\u0026uacute;de, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Given that many healthy behaviors are created and established throughout the adolescent to early adult transition, this period may be significant for health promotion interventions such as the promotion of good eating (Winpenny et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt was found that the QOL has declined, which is consistent with earlier findings (Celebre et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and might be attributed to several factors such as lifestyle characteristics, sleep patterns, dietary habits, and life events, which are also mentioned in (Shin et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This research could help provide the groundwork for future interventional programs promoting healthy eating habits. A universal healthy eating policy should be established, potentially included, and practiced in all regions, including developing and developed nations, and should be blended with varied socio-cultural and psychological characteristics across different locations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, unhealthy eating habits significantly raise psychological distress levels and lower school-age children's and teenagers' QOL. Additional research should be conducted to find factors other than those already mentioned. Environmental variables, lifestyle, mental health, and other associated constructions must be addressed in school-based health treatments. Successful management of depressive symptoms and stress may have a major impact on improving students\u0026rsquo; QOL. Improving the eating habits of low-income students through a school-based food distribution program results in significant benefits.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding statement\u003c/h2\u003e\n\u003cp\u003eThere is no funding support for this research.\u003c/p\u003e\n\u003ch2\u003eInformed Consent to Participate in Study\u003c/h2\u003e\n\u003cp\u003eBefore participating in the study, informed consent was obtained from each participant after explaining objective and possible outcomes of the study. Assent was taken from parents or legal guardian for all participants under 18 years of age.\u003c/p\u003e\n\u003ch2\u003eData Availability Statement:\u003c/h2\u003e\n\u003cp\u003eData related to this study will be available on request to the corresponding author.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eIsmail Qadri, Azhar Mehmood, and Hammad Sha collected data andn interpreted data from various schools. Khadija Muqadas conceptualize the idea and wrote the whole manuscript. Muhammad Subhan Nazar, Ayesha Umar Chaudhary and Muhammad Junaid analyzed the data. Ijaz ul Haq and Shahbaz Ahmad Zakki reviewed the manuscript, made final changes, and approved the final version of manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe extend our sincere gratitude to the District Education Officer for their invaluable support in facilitating data collection for our research. Additionally, we express heartfelt appreciation to the heads or principals of participating schools. Their cooperation in facilitating data collection from students has been crucial to the project\u0026apos;s progress and quality. We acknowledge the efforts of all involved individuals, whose contributions have been integral to our research objectives.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlharbi, R., Alsuhaibani, K., Almarshad, A., \u0026amp; Alyahya, A. (2019). Depression and anxiety among high school student at Qassim Region. \u003cem\u003eJournal of Family Medicine and Primary Care\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(2), 504. https://doi.org/10.4103/jfmpc.jfmpc_383_18\u003c/li\u003e\n \u003cli\u003eAwwas, M. Y. Al, Alqasem, O. S., Alhussain, H. M., \u0026amp; Alqahtani, A. M. (2023). 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Eating habits and weight status in Finnish adolescents. \u003cem\u003eCambridge.OrgJ Viljakainen, RA de Oliveira Figueiredo, H Viljakainen, E Roos, E Weiderpass, TB RoungePublic Health Nutrition, 2019\u0026bull;cambridge.Org\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e, 2617\u0026ndash;2624. https://doi.org/10.1017/S1368980019001447\u003c/li\u003e\n \u003cli\u003eWinpenny, E. M., van Sluijs, E. M. F., White, M., Klepp, K. I., Wold, B., \u0026amp; Lien, N. (2018). Changes in diet through adolescence and early adulthood: longitudinal trajectories and association with key life transitions. \u003cem\u003eThe International Journal of Behavioral Nutrition and Physical Activity\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), 86. https://doi.org/10.1186/S12966-018-0719-8\u003c/li\u003e\n \u003cli\u003eYihunie Akalu, T., Alemu Gelaye, K., Addis Bishaw, M., Yitayih Tilahun, S., Yeshaw, Y., Azale, T., Tsegaye, T., Asmelash, D., \u0026amp; Akalu, Y. (2021). Depression, anxiety, and stress symptoms and its associated factors among residents of Gondar Town during the early stage of COVID-19 pandemic. \u003cem\u003eTaylor \u0026amp; Francis\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e, 1073\u0026ndash;1083. https://doi.org/10.2147/RMHP.S296796\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Food habits, quality of life, mental health, schoolchildren, adolescents, WHOQOL-BREF, DASS-Y, KPK","lastPublishedDoi":"10.21203/rs.3.rs-6242891/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6242891/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAcademic performance influence depression, anxiety, stress and overall quality of life of students. The purpose of this study is to investigate the eating habits of school adolescents, and its association with status of mental health and quality of life (QOL).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A cross-sectional study was conducted among children and adolescents of all Government higher secondary schools in District Haripur, Khyber Pakhtunkhwa, Pakistan from March 2023 to May 2023. A 39-item Adolescent Food Habits Checklist, Depression, Anxiety, Stress Scale for youth (DASS-Y) 21 item questionnaire and 26 item WHOQOL-BREF questionnaire were used to collect the data. Data analyses were performed on SPSS Version 22.0\u003cstrong\u003e to measure significance between variables.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Study findings showed that stress, anxiety, and depression among students were 92.4%, 76.8%, and 86.6%, respectively. Analyses identified three groups: poor eating (36%), moderate eating (35%), and good eating habits (29%). Depression, anxiety and stress with eating behaviors have a substantial relationship (x\u003csup\u003e2\u003c/sup\u003e \u0026lt;137.7, \u003cem\u003ep-\u003c/em\u003evalue \u0026lt; 0.001), (x\u003csup\u003e2\u003c/sup\u003e \u0026lt;154.6, \u003cem\u003ep-\u003c/em\u003evalue \u0026lt; 0.001), (x\u003csup\u003e2\u003c/sup\u003e \u0026lt; 126.3, \u003cem\u003ep-\u003c/em\u003evalue \u0026lt; 0.001) respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Students showed high levels of psychological distress and low quality of life due to bad food habits. There is a need of interventions for dietary habits improvement and modification of school environment to reduce the risk of psychological distress and improve QOL.\u003c/p\u003e","manuscriptTitle":"Association of Food Habits on Adolescents’ Mental Distress and Quality of Life: an Observational Study From Higher Secondary Schools of Pakistan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 09:07:03","doi":"10.21203/rs.3.rs-6242891/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ad5d05ae-6231-47ca-b734-d281ebcf5eae","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-30T06:54:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 09:07:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6242891","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6242891","identity":"rs-6242891","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}