Skip to main content
Download PDF
Download ePub

The association between lifelines diet score (LLDS) with depression and quality of life in Iranian adolescent girls

Nutrition Journal volume 23, Article number: 19 (2024) Cite this article

Abstract

Background

It has been proposed that a greater degree of adherence to a healthy dietary pattern is associated with a lower risk of depression and a poor quality of life (QoL). The Lifelines diet score (LLDS) is a new, evidence-base scoring system to define the quality of diet. We designed a cross-sectional study to investigate the association between LLDS with depression and QoL in Iranian adolescent girls.

Methods

A total of 733 female adolescents were recruited from Mashhad and Sabzevar cities, Iran. Depression and QoL were assessed utilizing the Beck Depression Inventory (BDI) and SF-12v2 questionnaires, respectively. The LLDS was defined by dividing intakes of 12 food groups with negative or positive health effects into quintiles ranging 12 to 60 points. To explore the association between LLDS with QoL and depression, logistic regression was used in crude and adjusted models.

Results

The prevalence of depression and poor QoL was 24% and 49%, respectively. After adjusting for confounding factors, adolescent girls in the highest quartile of LLDS compared with the participants in the lowest quartile had a 42% lower probability of reporting depressive symptoms (OR: 0.58; 95% CI: 0.35–0.97, P = 0.03). In addition, the participants in the highest quartile of LLDS had lower odds of poor QoL compared with the subjects in the lowest quartile (OR: 0.65; 95% CI: 0.42–0.92, P = 0.04).

Conclusions

There is an inverse relationship between LLDS with risk of depression and poor QoL. Prospective and interventional investigations are needed to reach a clear vision.

Peer Review reports

Introduction

Depression is a common mental disorder with two main symptoms: depressed mood and anhedonia [1]. The worldwide prevalence of depression is estimated to be between 11.1 and 14.6% [2], with greater prevalence among adolescents and females [3]. Its prevalence among Iranian children and adolescents is estimated to be 43.5% [3]. The increasing prevalence of depression and its consequences such as suicide ideation and suicide attempts have led to elevated socioeconomic costs in both developed and developing countries [4,5,6,7]. Oxidative stress and inflammation are associated with psychological disorders [7, 8]. Depression is associated with an increased risk of obesity, type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD), and infertility [9,10,11]. In addition, depression can lead to disrupted academic activities and motivation of students [12, 13]. The level of Quality of life (QoL), which is defined as “the perception of individuals about their position in life in the context of the culture and value systems which is related to their goals, expectations, standards and concerns” [14], decreases in patients of depression [15, 16].

Diet is a modifiable lifestyle factor that has been recognized as having an impact on mental wellbeing [17,18,19]. There is a relationship between a greater adherence to the western-style dietary patterns containing high amounts of red and processed meats, full-fat dairy products, saturated fatty acids (SFAs) and refined sugars with lower risk of mental disorders in adolescents [20, 21]. On the other hand, healthy dietary patterns rich in vegetables, fruits, sea foods, whole grains, legumes and nuts attenuate the risk of depression [22, 23].

Some studies reported the association between food groups and depression and quality of life. Results of the meta analysis study reported that fruit and vegetable consumption inversely associated with the risk of depression [24]. Another study has shown that vegetable and fruit intake are positively associated with health-related quality of life [25] Recently, the lifelines diet score (LLDS) was developed by Vinke et al. [26] to estimate the diet quality. This score is a food group-based diet quality assessment tool that reflects the latest international evidence on diet-disease associations. It has a high capacity to discriminate between people with widely different intakes. Moreover, it is flexible and widely applicable, as it uses a population-based quintile approach [26]. Other nutritional scores, such as the Healthy Eating Index and the Mediterranean Diet Score (MDS), are not entirely food-based and do not reflect the current scientific evidence [26]. Moreover, the MDS does not account for sugar-sweetened beverages, which have well-established detrimental effects on obesity and diabetes risk [27].

To the best of our knowledge, there is no study investigating the association between LLDS with depression and QoL. Accordingly, the present cross-sectional study was designed to determine the relationship between LLDS with depression and QoL in adolescent girls. We hypothesized that a higher adherence to the LLDS, demonstrating higher adherence to a healthy dietary pattern, may be associated with lower risk of depression and poor QoL.

Methods and materials

Study population

This cross-sectional study was performed in January 2015 in the cities of Mashhad and Sabzevar, Iran. The population of this study consisted of 733 female students aged 12–18 years recruited using a random cluster sampling method from different schools in these cities. Exclusion criteria included individuals with autoimmune disease, cancer, metabolic bone disease, hepatic or renal failure, cardiovascular disorders, malabsorption or thyroid, parathyroid, adrenal diseases, and anorexia nervosa or bulimia. Additionally, participants were excluded if they were taking any medication related to anti-inflammatory, anti-depressant, anti-diabetic, or anti-obesity drugs, vitamin D or calcium supplement use and hormone therapy within the previous 6 months [20]. The Ethics Committee of Mashhad University of Medical Sciences, Mashhad, Iran, approved the study and all participants and their parents provided informed written consent.

Calculation of LLDS

Dietary intakes were evaluated using a validated and reliable food frequency questionnaire (FFQ) containing data on 147 food items [23]. This FFQ has nine multiple-choice frequency response categories that varies from “never or < 1/mo” to “≥12/d. FFQs were completed during face-to-face interviews and reported dietary intakes were converted to grams and entered to the Nutritionist IV software. To calculate daily nutrient intake values for each participant, the US Department of Agriculture’s (USDA) national nutrient databank was used [24]. The LLDS was computed by considering 12 food groups which had positive or negative health effects [26]. Vegetables, fruits, whole grain products, legumes and nuts, fish, oils and soft margarines, unsweetened dairy, coffee, and tea were classified as nine positive food groups and red and processed meat, butter and hard margarines, and sugar-sweetened beverages were defined as three negative food groups. The intake of food groups were adjusted by 1000 kcal energy intake and then divided in to quintiles from 1 to 5. The individuals in highest quintile of each positive food group’s intake received 5 points, while one point was specified to lowest quintile. For food groups with negative health effects, point 1 representing the maximum and point 5 representing the minimum dietary intakes. The sum of points for intakes of 12 food groups consisted LLDS ranging from 12 to 60 points.

Assessment of depression

A Persian version of Beck Depression Inventory (BDI) was used to determine depression status in the current study. BDI is a self-administered questionnaire including 21 items with various options. The total score for the BDI ranges between 0 and 63 points. If the BDI score was < 13, the person was considered as not depressed, and if the subject’s score was > 13, they were categorized as depressed. The validity and reliability of BDI were assessed in previous studies (Cronbach’s α = 0.87 and acceptable test-retest reliability (r) = 0.74) [28].

Quality of life assessment

To assess health-related quality of life, the SF-12v2 questionnaire was used. This questionnaire is a short form of the SF-36 questionnaire and improved version of SF-12v1 (7). The validity and reliability of this questionnaire was previously confirmed in Iran (8). The questionnaire has 12 items evaluating 8 domains of health including physical functioning, role limitations because of physical problems, bodily pain, general health, vitality, social functioning, role limitations because of emotional problems, and mental health. The range of quality of life scores are between 0 (the worst quality of life) to 100 (the best quality of life). The median of the quality of life score is 43. The subjects were considered as subjects with poor quality of life, if their scores were lower than 43.

Covariate measurements

Weight and height were measured using standard protocols and the mean of two measurements was reported. Body mass index was calculated as weight (kg) divided by square of the height (m2). Mid-distance between the iliac crest and lowest rib was considered to measure waist circumference (WC). Hip circumference is measured at the largest circumference around the buttocks. Waist–hip ratio (WHR) is calculated as waist measurement divided by hip measurement. General Information including age, parental death or divorce was collected by face-to-face interview using a standard questionnaire. Physical activity was assessed through a validated modifiable activity questionnaire [22] and provided as metabolic equivalents (Mets) in hours per week.

Statistical analysis

The normality of data was assessed using the Kolmogorov–Smirnov test. The LLDS was categorized into quartiles. To compare continuous and categorical variables across quartiles of LLDS, One-way Anova and Chi-square test were used, respectively. Logistic regression was applied to evaluate the relationship between LLDS with poor quality of life and depression prevalence in crude and adjusted models. Model I was adjusted for age and energy intake. Further adjustment was for BMI percentile. Physical activity, parent’s death and parent’s divorce were additionally adjusted in the model III. P-values < 0.05 were considered statistically significant. To analyze the data, statistical Package for Social Sciences (SPSS) (version 23.0, SPSS Inc., Chicago, Illinois, USA) was used.

Results

General characteristics study participants

The mean age of the participants was 14.5 years. The prevalence of depression and poor QoL was 24% and 49%, respectively. General characteristics and anthropometric variables of the participants across quartiles of LLDS are presented in Table 1. Age, percentile of BMI, WC, WHR, physical activity, parent’s death and parent’s divorce were not different among quartiles of LLDS. General characteristics and anthropometric variables of the participants across categories of depression and QoL score are presented in Table 2. The depressed subjects had more parents who divorced than those not depressed subjects. General characteristics and anthropometric variables were not different among participants with well quality of life and poor quality of life.

Table 1 General characteristics of study participants by quartile of LLDS
Full size table
Table 2 General characteristics of study participants by categories of depression and Quality of life score
Full size table

Dietary intake study participants

Energy and dietary intakes of study participants by quartile of LLDS are shown in Table 3. Vitamin C (P < 0.01) and calcium (P = 0.01) intake were significantly higher among participants in the highest quartile of LLDS (per 1000 kcal) compared to the lowest quartile. The participants in the highest quartile of LLDS had higher intake of vegetables (p < 0.001), whole grain products (P = 0.04), fish (P < 0.01), oils and soft margarines (P = 0.02), tea (P < 0.01), coffee (P < 0.01) and unsweetened dairy (P = 0.04) compared to participants in the lowest quartile. Intake of cholesterol, saturated fatty acid, monounsaturated fatty acid, polyunsaturated fatty acid, iron, vitamin A, B6, B12 and folate were not significantly different between quartile of LLDS (per 1000 kcal). Food groups intake of study participants by across categories of depression and QoL score were presented in Table 4.

Table 3 Energy and dietary intakes of study participants by quartile of LLDS
Full size table
Table 4 Food groups intake of study participants by categories score of depression and quality of life
Full size table

The association between LLDS with depression and poor QoL.

Multi-variable adjusted odds ratios (ORs) for depression and poor QoL categories across quartiles of LLDS are represented in Table 5. Adolescent girls in the highest quartile of LLDS compared with the participants in the lowest quartile had a 41% lower probability of having depressive symptoms (OR: 0.59; 95% CI: 0.36–0.96, P = 0.03). This association remained significant after adjustment for age, energy intake, BMI percentile, physical activity, parent’s death and parent’s divorce (OR: 0.58; 95% CI: 0.35–0.97, P = 0.03). The participants in the highest quartile of LLDS had lower odds of poor QoL compared with the subjects in the lowest quartile (OR: 0.62; 95% CI: 0.41–0.94, P = 0.02) in crude model. This association remained significant after adjustment for age, energy intake, BMI percentile, physical activity, parent’s death and parent’s divorce (OR: 0.65; 95% CI: 0.42–0.92, P = 0.04).

Table 5 Multivariable-adjusted odds ratio of the associations between LLDS with poor quality of life and depression
Full size table

Discussion

The findings of our cross-sectional study showed that higher LLDS is associated with lower prevalence of depression in adolescent girls. An inverse correlation was found between LLDS and poor QoL. Depression can adversely affect academic attainment and acquisition of effective social skills, decrease motivation, and increase suicide ideation as well as suicide attempts in adolescents [6, 7, 12, 13]. Adherence to the healthy dietary patterns can decrease the risk of depression and poor QoL [29, 30]. The LLDS is a new, flexible and evidence-base score used to estimate adherence to a healthy diet [26]. A higher LLDS indicates higher consumption of positive food groups (vegetables, fruits, whole grain products, legumes and nuts, fish, oils and soft margarines, unsweetened dairy, coffee, and tea) and lower consumption of negative food groups (red and processed meat, butter and hard margarines, and sugars sweetened beverages), and vice versa [26]. To the best of our knowledge, this is the first study that examined the association of LLDS with depression and QoL in adolescent girls. We found that higher level of LLDS is associated with lower risk of depression and poor QoL.

Subjects with higher LLDS consumed higher amounts of plant foods. In general, plant foods and their biological compounds regulate dopaminergic pathways of brain, increase the levels of serotonin and dopamine in the hippocampus and prefrontal cortex, decrease the activity of monoamine oxidase (MAO) and subsequent improve depression [31,32,33,34]. In line with our findings, a cross-sectional study demonstrated that greater adherence to dietary approaches to stop hypertension (DASH), which is a healthy plant-based dietary pattern, is associated with lower odds of depression [30]. Likewise, it has been reported that risk of depression is lower in subjects with higher adherence to MDS (a plant-based diet) [22].

Oxidative stress and inflammation are two factors linked to the development of depression [8, 35]. Biological components of plant foods such as phytochemicals, which have antioxidant and anti-inflammatory properties, can modulate the production of fatty acids, improve mitochondrial dysfunction, increase the levels of antioxidant factors, decrease production of free radicals and pro-inflammatory cytokines [36,37,38,39]. The cross-sectional study of Holt et al. [40] demonstrated an inverse relationship between consumption of plant foods with levels of oxidative stress and inflammation. In addition, we demonstrated that participants in higher quartile of LLDS had higher intake of Vitamin C. Vitamin C through mechanisms such as inhibiting the activity of hydroxyl radical, tocopheroxyl radical, peroxyl radical, thiol radical and alkoxyl radicals by providing an electron for these damaging oxidizing radicals, decreasing macrophages-induced LDL oxidation, regulating nitric oxide-cyclic GMP (cGMP) pathways, inhibiting potassium channels, activating γ-aminobutyric acid (GABA) type A receptors and decreasing GABA type B receptors activation, decreasing levels of tumor necrosis alpha (TNF-α) and interleukins in the hippocampus and decreasing the activity of nuclear factor κ-B (NF-κB) and mitogen-activated protein kinase (MAPK) pathways exert its antidepressant-like effect [41,42,43,44,45,46,47]. A study confirmed that sub-optimal vitamin C status is associated with increased symptoms of depression [48].

As mentioned, we found an inverse association between LLDS and QoL. There is no other study investigating this relationship. However, some studies have demonstrated a direct association between adherences to the healthy diets with QoL. As shown, two cross-sectional studies have reported that adherence to the Mediterranean diet is directly associated with QoL [49, 50]. Moreover, diets with higher quality containing higher amounts of whole grains, fruits and vegetables as well as lower amounts refined foods and fast food are associated with better QoL [51,52,53]. Recent systematic review of Govindaraju et al. [54] revealed a direct association between adherence to the dietary patterns rich in whole grains, fruits and vegetables with QoL.

There are some strength points for our study. This study was conducted in a large sample and is one of the first studies to examine the relationship between LLDS and depression or QoL in adolescent girls. High quality of data collection by validated questionnaires was first strength point in the current study. In addition, to avoid misleading conclusions in analysis and interpretation of data, we conducted rigorous statistical analyses, including several adjustment models for confounding factors to depression and QoL. Nevertheless, our findings require to be interpreted by considering some potential limitations. Cross-sectional design should be considered as the major limitation of the present study; because, we do not confirm a causal relationship. FFQs are prone to measurement error and misclassification. Also, the current study was performed only on girls and not boys that this might be a limitation. Finally, like other observational studies, several unmeasured confounders were in this study, which we are unable to control them.

Conclusions

In summary, findings of the current study suggest that a greater adherence to LLDS was associated with lower odds of depression and poor QoL in adolescent girls. Children and their parents should be informed which higher dietary intakes of antioxidant and fiber sources and lower consumption of saturated fatty acids and sugar promote mental health. In addition, adolescent-centered nutritional interventions should be designed as a school snack with a greater emphasis on fruits, vegetables, nuts, legumes, whole grain and dairy products. These findings are needed to confirm with prospective studies and trials to clarify the causal association and determine the dose-response curve between diet quality and risk of depression or poor QoL.

Data availability

The data and materials of the current study is available from the corresponding author on reasonable request.

Abbreviations

ALT:

Alanine transaminase

AST:

Aspartate transaminase

BDI:

Beck depression inventory

BMI:

Body mass index

cGMP:

Cyclic GMP

FFQ:

Food frequency questionnaire

FPG:

Fasting plasma glucose

GABA:

γ-aminobutyric acid

GGT:

Gamma-glutamyl transpeptidase

HDL-c:

High density lipoprotein-cholesterol

LDL-c:

Low density lipoprotein-cholesterol

MAO:

Monoamine oxidase

MAPK:

Mitogen-activated protein kinase

MAQ:

Modifiable activity questionnaire

NF-κB:

Nuclear factor κ-B

OR:

Odds ratio

QoL:

Quality of life

SD:

Standard deviation

SPSS:

Statistical package for social science

TC:

Total cholesterol

TG:

Triglyceride

WC:

Waist circumference

References

  1. Prince M, Patel V, Saxena S, Maj M, Maselko J, Phillips MR, Rahman A. No health without mental health. The Lancet. 2007;370:859–77.

    Article  Google Scholar 

  2. Bromet E, Andrade LH, Hwang I, Sampson NA, Alonso J, De Girolamo G, De Graaf R, Demyttenaere K, Hu C, Iwata N. Cross-national epidemiology of DSM-IV major depressive episode. BMC Med. 2011;9:1–16.

    Article  Google Scholar 

  3. Sajjadi H, Kamal SHM, Rafiey H, Vameghi M, Forouzan AS, Rezaei M. A systematic review of the prevalence and risk factors of depression among Iranian adolescents. Global J Health Sci. 2013;5:16.

    Article  Google Scholar 

  4. Collins PY, Patel V, Joestl SS, March D, Insel TR, Daar AS, Bordin IA, Costello EJ, Durkin M, Fairburn C. Grand challenges in global mental health. Nature. 2011;475:27–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kessler RC, Angermeyer M, Anthony JC, De Graaf R, Demyttenaere K, Gasquet I, De Girolamo G, Gluzman S, Gureje O, Haro JM. Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization’s World Mental Health Survey Initiative. World Psychiatry. 2007;6:168.

    PubMed  PubMed Central  Google Scholar 

  6. Bilsen J. Suicide and youth: risk factors. Front Psychiatry. 2018;9:540.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Turecki G, Brent DA. Suicide and suicidal behaviour. The Lancet. 2016;387:1227–39.

    Article  Google Scholar 

  8. Tayefi M, Shafiee M, Kazemi-Bajestani SMR, Esmaeili H, Darroudi S, Khakpouri S, Mohammadi M, Ghaneifar Z, Azarpajouh MR, Moohebati M. Depression and anxiety both associate with serum level of hs-CRP: a gender-stratified analysis in a population-based study. Psychoneuroendocrinology. 2017;81:63–9.

    Article  CAS  PubMed  Google Scholar 

  9. Katon WJ. Epidemiology and treatment of depression in patients with chronic medical illness. Dialog Clin Neurosci. 2011;13:7.

    Article  Google Scholar 

  10. Anderson SE, Cohen P, Naumova EN, Jacques PF, Must A. Adolescent obesity and risk for subsequent major depressive disorder and anxiety disorder: prospective evidence. Psychosom Med. 2007;69:740–7.

    Article  PubMed  Google Scholar 

  11. Bergantin LB. The clinical link between depression and obesity: role of Ca2+/cAMP signalling. Psychiatry Res. 2020;291:113167.

    Article  CAS  PubMed  Google Scholar 

  12. Paik J, Song J. Special editions: depression in the college student. J Kyung Hee Univ Med Cent. 2009;25:1–6.

    Google Scholar 

  13. Lyubomirsky S, Kasri F, Zehm K. Dysphoric rumination impairs concentration on academic tasks. Cogn Therapy Res. 2003;27:309–30.

    Article  Google Scholar 

  14. Group W. The World Health Organization quality of life assessment (WHOQOL): position paper from the World Health Organization. Soc Sci Med. 1995;41:1403–9.

    Article  Google Scholar 

  15. Zhang H-H, Zhao Y-J, Wang C, Zhang Q, Yu H-Y, Cheung T, Hall BJ, An F-R, Xiang Y-T. Depression and its relationship with quality of life in frontline psychiatric clinicians during the COVID-19 pandemic in China: a national survey. Int J Biol Sci. 2021;17:683.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Gao K, Su M, Sweet J, Calabrese JR. Correlation between depression/anxiety symptom severity and quality of life in patients with major depressive disorder or bipolar disorder. J Affect Disord. 2019;244:9–15.

    Article  PubMed  Google Scholar 

  17. Wheless JW. History of the ketogenic diet. Epilepsia. 2008;49:3–5.

    Article  PubMed  Google Scholar 

  18. Park S-J, Kim M-S, Lee H-J. The association between dietary pattern and depression in middle-aged Korean adults. Nutr Res Pract. 2019;13:316–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Oddy WH, Allen KL, Trapp GS, Ambrosini GL, Black LJ, Huang R-C, Rzehak P, Runions KC, Pan F, Beilin LJ. Dietary patterns, body mass index and inflammation: pathways to depression and mental health problems in adolescents. Brain Behav Immun. 2018;69:428–39.

    Article  PubMed  Google Scholar 

  20. Hoare E, Skouteris H, Fuller-Tyszkiewicz M, Millar L, Allender S. Associations between obesogenic risk factors and depression among adolescents: a systematic review. Obes Rev. 2014;15:40–51.

    Article  CAS  PubMed  Google Scholar 

  21. Khalid S, Williams CM, Reynolds SA. Is there an association between diet and depression in children and adolescents? A systematic review. Br J Nutr. 2016;116:2097–108.

    Article  CAS  PubMed  Google Scholar 

  22. Adjibade M, Assmann KE, Andreeva VA, Lemogne C, Hercberg S, Galan P, Kesse-Guyot E. Prospective association between adherence to the Mediterranean diet and risk of depressive symptoms in the French SU. VI. MAX cohort. Eur J Nutr. 2018;57:1225–35.

    Article  PubMed  Google Scholar 

  23. O’neil A, Quirk SE, Housden S, Brennan SL, Williams LJ, Pasco JA, Berk M, Jacka FN. Relationship between diet and mental health in children and adolescents: a systematic review. Am J Public Health. 2014;104:e31–e42.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Liu X, Yan Y, Li F, Zhang D. Fruit and vegetable consumption and the risk of depression: a meta-analysis. Nutrition. 2016;32:296–302.

    Article  CAS  PubMed  Google Scholar 

  25. Gong X-H, Wang J-W, Li J, Chen X-F, Sun L, Yuan Z-P, Yu J-M. Physical exercise, vegetable and fruit intake and health-related quality of life in Chinese breast cancer survivors: a cross-sectional study. Qual Life Res. 2017;26:1541–50.

    Article  PubMed  Google Scholar 

  26. Vinke PC, Corpeleijn E, Dekker LH, Jacobs DR, Navis G, Kromhout D. Development of the food-based lifelines Diet score (LLDS) and its application in 129,369 lifelines participants. Eur J Clin Nutr. 2018;72:1111–9.

    Article  PubMed  Google Scholar 

  27. Malik VS, Pan A, Willett WC, Hu FB. Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. Am J Clin Nutr. 2013;98:1084–102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ghassemzadeh H, Mojtabai R, Karamghadiri N, Ebrahimkhani N. Psychometric properties of a persian-language version of the Beck Depression Inventory‐Second edition: BDI‐II‐PERSIAN. Depress Anxiety. 2005;21:185–92.

    Article  PubMed  Google Scholar 

  29. Michael SL, Lowry R, Merlo C, Cooper AC, Hyde ET, McKeon R. Physical activity, sedentary, and dietary behaviors associated with indicators of mental health and suicide risk. Prev Med Rep. 2020;19:101153.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Khayyatzadeh SS, Mehramiz M, Mirmousavi SJ, Mazidi M, Ziaee A, Kazemi-Bajestani SMR, Ferns GA, Moharreri F, Ghayour-Mobarhan M. Adherence to a dash-style diet in relation to depression and aggression in adolescent girls. Psychiatry Res. 2018;259:104–9.

    Article  PubMed  Google Scholar 

  31. Kulkarni SK, Bhutani MK, Bishnoi M. Antidepressant activity of curcumin: involvement of serotonin and dopamine system. Psychopharmacology. 2008;201:435–42.

    Article  CAS  PubMed  Google Scholar 

  32. Yu Y, Wang R, Chen C, Du X, Ruan L, Sun J, Li J, Zhang L, O’Donnell JM, Pan J. Antidepressant-like effect of trans-resveratrol in chronic stress model: behavioral and neurochemical evidences. J Psychiatr Res. 2013;47:315–22.

    Article  PubMed  Google Scholar 

  33. Melo FHC, Moura BA, de Sousa DP, de Vasconcelos SMM, Macedo DS, Fonteles MMdF, Viana GSdB, de Sousa FCF. Antidepressant-like effect of carvacrol (5‐Isopropyl‐2‐methylphenol) in mice: involvement of dopaminergic system. Fundam Clin Pharmacol. 2011;25:362–7.

    Article  CAS  PubMed  Google Scholar 

  34. Zotti M, Colaianna M, Morgese MG, Tucci P, Schiavone S, Avato P, Trabace L. Carvacrol: from ancient flavoring to neuromodulatory agent. Molecules. 2013;18:6161–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Shafiee M, Ahmadnezhad M, Tayefi M, Arekhi S, Vatanparast H, Esmaeili H, Moohebati M, Ferns GA, Mokhber N, Arefhosseini SR. Depression and anxiety symptoms are associated with prooxidant-antioxidant balance: a population-based study. J Affect Disord. 2018;238:491–8.

    Article  CAS  PubMed  Google Scholar 

  36. Zhu F, Du B, Xu B. Anti-inflammatory effects of phytochemicals from fruits, vegetables, and food legumes: a review. Crit Rev Food Sci Nutr. 2018;58:1260–70.

    Article  CAS  PubMed  Google Scholar 

  37. Pu P, Wang X-A, Salim M, Zhu L-H, Wang L, Xiao J-F, Deng W, Shi H-W, Jiang H, Li H-L. Baicalein, a natural product, selectively activating AMPKα2 and ameliorates metabolic disorder in diet-induced mice. Mol Cell Endocrinol. 2012;362:128–38.

    Article  CAS  PubMed  Google Scholar 

  38. Sangouni AA, Azar MRMH, Alizadeh M. Effects of garlic powder supplementation on insulin resistance, oxidative stress, and body composition in patients with non-alcoholic fatty liver disease: a randomized controlled clinical trial. Complement Ther Med. 2020;51:102428.

    Article  PubMed  Google Scholar 

  39. Khayyatzadeh SS, Omranzadeh A, Miri-Moghaddam MM, Arekhi S, Naseri A, Ziaee A, Khajavi L, Salehkhani FN, Ferns GA, Ghayour-Mobarhan M. Dietary antioxidants and fibre intake and depressive symptoms in Iranian adolescent girls. Public Health Nutr. 2021;24:5650–6.

    Article  PubMed  Google Scholar 

  40. Holt EM, Steffen LM, Moran A, Basu S, Steinberger J, Ross JA, Hong C-P, Sinaiko AR. Fruit and vegetable consumption and its relation to markers of inflammation and oxidative stress in adolescents. J Am Diet Assoc. 2009;109:414–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Moritz B, Schmitz AE, Rodrigues ALS, Dafre AL, Cunha MP. The role of vitamin C in stress-related disorders. J Nutr Biochem 2020:108459.

  42. Han Q-q, Shen T-t, Wang F, Wu P-f, Chen J-g. Preventive and therapeutic potential of vitamin C in mental disorders. Curr Med Sci. 2018;38:1–10.

    Article  PubMed  Google Scholar 

  43. Buettner GR. The pecking order of free radicals and antioxidants: lipid peroxidation, α-tocopherol, and ascorbate. Arch Biochem Biophys. 1993;300:535–43.

    Article  CAS  PubMed  Google Scholar 

  44. Sil S, Ghosh T, Gupta P, Ghosh R, Kabir SN, Roy A. Dual role of vitamin C on the neuroinflammation mediated neurodegeneration and memory impairments in colchicine induced rat model of Alzheimer disease. J Mol Neurosci. 2016;60:421–35.

    Article  CAS  PubMed  Google Scholar 

  45. Huang Y-N, Lai C-C, Chiu C-T, Lin J-J, Wang J-Y. L-ascorbate attenuates the endotoxin-induced production of inflammatory mediators by inhibiting MAPK activation and NF-κB translocation in cortical neurons/glia cocultures. PLoS ONE. 2014;9:e97276.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  46. Moretti M, de Freitas AE, Budni J, Fernandes SCP, de Oliveira Balen G, Rodrigues ALS. Involvement of nitric oxide–cGMP pathway in the antidepressant-like effect of ascorbic acid in the tail suspension test. Behav Brain Res. 2011;225:328–33.

    Article  CAS  PubMed  Google Scholar 

  47. Rosa PB, Neis VB, Ribeiro CM, Moretti M, Rodrigues ALS. Antidepressant-like effects of ascorbic acid and ketamine involve modulation of GABAA and GABAB receptors. Pharmacol Rep. 2016;68:996–1001.

    Article  CAS  PubMed  Google Scholar 

  48. Gariballa S. Poor vitamin C status is associated with increased depression symptoms following acute illness in older people. Int J Vitam Nutr Res. 2014;84:12–7.

    Article  PubMed  Google Scholar 

  49. Veronese N, Stubbs B, Noale M, Solmi M, Luchini C, Maggi S. Adherence to the Mediterranean diet is associated with better quality of life: data from the Osteoarthritis Initiative. Am J Clin Nutr. 2016;104:1403–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Alcubierre N, Martinez-Alonso M, Valls J, Rubinat E, Traveset A, Hernández M, Martínez-González MD, Granado-Casas M, Jurjo C, Vioque J. Relationship of the adherence to the Mediterranean diet with health-related quality of life and treatment satisfaction in patients with type 2 diabetes mellitus: a post-hoc analysis of a cross-sectional study. Health Qual Life Outcomes. 2016;14:1–6.

    Article  Google Scholar 

  51. Sanchez-Aguadero N, Alonso-Dominguez R, Garcia-Ortiz L, Agudo-Conde C, Rodriguez-Martin C, de Cabo-Laso A, Sanchez-Salgado B, Ramos R, Maderuelo-Fernandez JA, Gomez-Marcos MA. Diet and physical activity in people with intermediate cardiovascular risk and their relationship with the health-related quality of life: results from the MARK study. Health Qual Life Outcomes. 2016;14:1–10.

    Article  Google Scholar 

  52. Rifai L, Pisano C, Hayden J, Sulo S, Silver MA. Impact of the DASH diet on endothelial function, exercise capacity, and quality of life in patients with heart failure. In Baylor University Medical Center Proceedings. Taylor & Francis; 2015: 151–156.

  53. Milte CM, Thorpe MG, Crawford D, Ball K, McNaughton SA. Associations of diet quality with health-related quality of life in older Australian men and women. Exp Gerontol. 2015;64:8–16.

    Article  PubMed  Google Scholar 

  54. Govindaraju T, Sahle BW, McCaffrey TA, McNeil JJ, Owen AJ. Dietary patterns and quality of life in older adults: a systematic review. Nutrients. 2018;10:971.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We acknowledge the contribution of the participants and co-researchers.

Funding

Mashhad University of Medical Sciences supported this study.

Author information

Authors and Affiliations

  1. Research Center for Food Hygiene and Safety, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

    Zahra Darabi, Abbas Ali Sangouni & Sayyed Saeid Khayyatzadeh

  2. Department of Nutrition, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

    Zahra Darabi & Sayyed Saeid Khayyatzadeh

  3. Non-Communicable Diseases Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran

    Abbas Ali Sangouni

  4. International UNESCO center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran

    Majid Ghayour-Mobarhan

  5. Brighton & Sussex Medical School, Division of Medical Education, Falmer, Brighton, Sussex, BN1 9PH, UK

    Gordon A. Ferns

Authors
  1. Zahra Darabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abbas Ali Sangouni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Majid Ghayour-Mobarhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gordon A. Ferns
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sayyed Saeid Khayyatzadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.Kh, M.Gh-M and G.F: designed the study. S.Kh: conducted the study; A.S and Z.D: wrote the manuscript and involved in the analysis. S.Kh: critically revised the manuscript; S.Kh: supervised the study. The final version of the manuscript was approved by all authors.

Corresponding author

Correspondence to Sayyed Saeid Khayyatzadeh.

Ethics declarations

Ethics approval and consent to participate

The ethical committee of Mashhad University of Medical Sciences in Mashhad approved the written informed consent (code number: 931188). The written informed consent was signed by all participants before the beginning study.

Consent for publication

No individual detail is presented in this manuscript; therefore it is not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Darabi, Z., Sangouni, A.A., Ghayour-Mobarhan, M. et al. The association between lifelines diet score (LLDS) with depression and quality of life in Iranian adolescent girls. Nutr J 23, 19 (2024). https://doi.org/10.1186/s12937-024-00913-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12937-024-00913-9

Keywords

Nutrition Journal

ISSN: 1475-2891

Contact us