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Salehi Mobarakeh M, Eftekhari M H. The Association between Diet Quality and Anxiety among Young Couples in Shiraz: A Cross-sectional Study
. JNFS 2019; 4 (3) :176-185
URL: http://jnfs.ssu.ac.ir/article-1-180-en.html
URL: http://jnfs.ssu.ac.ir/article-1-180-en.html
Department of Clinical Nutrition, School of Nutrition and Food Sciences, Shiraz University of Medical Sciences, Shiraz, IR Iran
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The Association between Diet Quality and Anxiety among
Young Couples in Shiraz: A Cross-sectional Study
Mahoor Salehi Mobarakeh; MSc1 & Mohammad Hassan Eftekhari; PhD*1
1 Department of Clinical Nutrition, School of Nutrition and Food Science, Shiraz University of Medical Sciences, Shiraz, Iran.
Young Couples in Shiraz: A Cross-sectional Study
Mahoor Salehi Mobarakeh; MSc1 & Mohammad Hassan Eftekhari; PhD*1
1 Department of Clinical Nutrition, School of Nutrition and Food Science, Shiraz University of Medical Sciences, Shiraz, Iran.
| ARTICLE INFO | ABSTRACT | |
| ORIGINAL ARTICLE | Background: Mental disorders impose a significant health and economic burden on both developed and developing countries. The relationship between nutrition and mental disorders has become an important topic of interest in recent years. Therefore, identification of modifiable risk factors for anxiety is a serious and critical research imperative. Thus, this study aimed to evaluate the relationship between the “diet quality index international” (DQI-I) and anxiety as a major subject. Methods: This cross-sectional study was conducted on 194 men and women, who were randomly selected to perform the routine examinations before marriage. In this research, socio-demographic and anthropometric indicators, such a dietary intake1 and mental health were measured. To measure the former, a Food Frequency Questionnaire (FFQ) was applied and to determine the latter, a short version of the self-report depression, anxiety, and stress scale questionnaire (DASS-21) was used. Results: Univariate and multivariate linear regressions of anxiety and DQI score demonstrated significant association between DQI score and anxiety in all participants. A negative correlation was also seen between DQI score and anxiety in all participants. The anxiety scores reported for males and females did not introduce a significant difference. Adjustments for age, education, income, job, smoking, physical activity, and body mass index did not change the aforementioned associations. Conclusion: In this study, a significant association was observed between diet quality and the risk of mental disorders. The increase in DQI in participants caused a remarkable reduction in their level of anxiety. A healthy diet proved to be inversely associated with anxiety, while unhealthy dietary patterns were associated with increased risk of anxiety. Keywords: Mental disorders; Anxiety; Nutrient |
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| Article history: Received: 11 Jul 2018 Revised: 3 Sep 2018 Accepted: 26 Jan 2019 |
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| *Corresponding author: h_eftekhari@yahoo.com Department of Clinical Nutrition, School of Nutrition and Food Sciences, Shiraz, Iran. Postal code: 7153675541 Tel: +98- 7137251001 |
Introduction
Nowadays, mental disorders are known as a leading factor affecting health and economy in both developed and developing countries. The prevalence of mental disorders range from 3.3 to 21.4% (Mueller et al., 1999), so that the global burden of anxiety is known as a major public health concern (Kessler et al., 2005). Therefore, the identification of modifiable risk factors for anxiety is a serious and important research imperative (Ferrari et al., 2013). Recent studies have highlighted role of the modifiable lifestyle behaviors, such as physical inactivity, smoking, and other lifestyle factors in the development of common mental disorders (Bonnet et al., 2005). In addition, the relationship between nutrition and mental disorders was of great interest in recent years (Eyre et al., 2013, Lopresti et al., 2013). In both observational and clinical studies, the majority of previous studies focused on either the intake of individual nutrients or various food groups and their association with anxiety, or the effect of nutritional supplementation as a treatment strategy on depression. In this regard, studies identified the relationship of the intakes of dietary nutrients, such as zinc, magnesium-group vitamins, culinary fat (such as olive oil) and single food groups such as sea-food or fish consumption with respect to decreased risk of anxiety (Gómez-Pinilla, 2008, Tannenbaum et al., 1997). However, given the complex combinations and interactions among nutrients in an individual’s daily diet, considerable barriers exist to study individual nutrients and the diseases caused directly by dietary habits.
Nowadays, mental disorders are known as a leading factor affecting health and economy in both developed and developing countries. The prevalence of mental disorders range from 3.3 to 21.4% (Mueller et al., 1999), so that the global burden of anxiety is known as a major public health concern (Kessler et al., 2005). Therefore, the identification of modifiable risk factors for anxiety is a serious and important research imperative (Ferrari et al., 2013). Recent studies have highlighted role of the modifiable lifestyle behaviors, such as physical inactivity, smoking, and other lifestyle factors in the development of common mental disorders (Bonnet et al., 2005). In addition, the relationship between nutrition and mental disorders was of great interest in recent years (Eyre et al., 2013, Lopresti et al., 2013). In both observational and clinical studies, the majority of previous studies focused on either the intake of individual nutrients or various food groups and their association with anxiety, or the effect of nutritional supplementation as a treatment strategy on depression. In this regard, studies identified the relationship of the intakes of dietary nutrients, such as zinc, magnesium-group vitamins, culinary fat (such as olive oil) and single food groups such as sea-food or fish consumption with respect to decreased risk of anxiety (Gómez-Pinilla, 2008, Tannenbaum et al., 1997). However, given the complex combinations and interactions among nutrients in an individual’s daily diet, considerable barriers exist to study individual nutrients and the diseases caused directly by dietary habits.
Diets are multidimensional; therefore, attribution of differential disease prevalence or symptomatology to a single nutrient or food group is difficult. Moreover, nutrient intake is associated with particular dietary patterns, which may act as a confounder regarding the diet-disease associations. In this regard, dietary patterns have been examined as predictors of disease outcomes more than ever. For example, according to a study among middle-aged women participating in the Nurses’ Health Study, a prudent dietary pattern was found to be relevant to higher intakes of vegetables, fruits, legumes, fish, poultry, and whole grains. However, the western dietary pattern w:as char:acterized by higher intakes of red and processed meats, desserts, refined grains, and fried foods. These patterns were aligned with markers of systemic inflammation (Esmaillzadeh and Azadbakht, 2008, Schulze et al., 2005).
In a study conducted over a group of adolescents, the dietary pattern of foods rich in animal foods had a direct relationship with anxiety (Weng et al., 2012). In another study conducted on a group of adult women and men, a significant relationship was observed between dietary patterns including processed foods and anxiety (Bakhtiyari et al., 2013).
Noticeable characteristics of a diet may be captured using a composite measure of dietary intake or dietary quality scores derived from the recommended dietary guidelines.
The evaluation of a diet quality is defined according to the level of adherence to the dietary guidelines and Food Guide Pyramid. Nowadays, eating habits are studied instead of reporting food or micronutrients. So, it can be more useful to consider the entire diet of such patterns and diet quality indicators.
According to the literature, different criteria exist for assessing the quality of the diet, such as healthy eating index (HEI), diet quality index International Version (DQI-I), and the Mediterranean diet scale (MDS). Among these factors, the most comprehensive and prestigious one is DQI-I, because the regimes quality in different countries can be affected by various stages of transition nutrition surveys for the chronic diseases to study malnutrition.
Therefore, the aim of this study was to investigate the relationship between DQI-I and anxiety.
Materials and Methods
Participants’ characteristics: The ethics committee in Shiraz University of medical science approved this study. This cross-sectional study was carried out among the couples. They were asked to perform routine examinations before marriage in Shiraz city, Iran. All participants were required to sign the written informed consents.
Regarding anxiety, as one of the indicators examined in this study, the sample size was determined as 194 using the following formula (29).
Inclusion criteria: couples (men and women) who intended to get married and visited the reference laboratory for performing routine examination before the marriage.
Exclusion criteria involved:
1) People, who were under treatment with regard to each components of metabolic syndromes (drugs affecting the metabolism of glucose, lipids, and blood pressure, such as steroids, non-steroidal anti-inflammatory drugs, thyroid hormones of male and female hormones) or were consuming supplements and vitamins in the last three months.
2) People having a history of chronic diseases in heart, lung, liver, kidney, and thyroid.
Initially, participants completed a series of demographic questions related to the following indicators:
In a study conducted over a group of adolescents, the dietary pattern of foods rich in animal foods had a direct relationship with anxiety (Weng et al., 2012). In another study conducted on a group of adult women and men, a significant relationship was observed between dietary patterns including processed foods and anxiety (Bakhtiyari et al., 2013).
Noticeable characteristics of a diet may be captured using a composite measure of dietary intake or dietary quality scores derived from the recommended dietary guidelines.
The evaluation of a diet quality is defined according to the level of adherence to the dietary guidelines and Food Guide Pyramid. Nowadays, eating habits are studied instead of reporting food or micronutrients. So, it can be more useful to consider the entire diet of such patterns and diet quality indicators.
According to the literature, different criteria exist for assessing the quality of the diet, such as healthy eating index (HEI), diet quality index International Version (DQI-I), and the Mediterranean diet scale (MDS). Among these factors, the most comprehensive and prestigious one is DQI-I, because the regimes quality in different countries can be affected by various stages of transition nutrition surveys for the chronic diseases to study malnutrition.
Therefore, the aim of this study was to investigate the relationship between DQI-I and anxiety.
Materials and Methods
Participants’ characteristics: The ethics committee in Shiraz University of medical science approved this study. This cross-sectional study was carried out among the couples. They were asked to perform routine examinations before marriage in Shiraz city, Iran. All participants were required to sign the written informed consents.
Regarding anxiety, as one of the indicators examined in this study, the sample size was determined as 194 using the following formula (29).
Inclusion criteria: couples (men and women) who intended to get married and visited the reference laboratory for performing routine examination before the marriage.
Exclusion criteria involved:
1) People, who were under treatment with regard to each components of metabolic syndromes (drugs affecting the metabolism of glucose, lipids, and blood pressure, such as steroids, non-steroidal anti-inflammatory drugs, thyroid hormones of male and female hormones) or were consuming supplements and vitamins in the last three months.
2) People having a history of chronic diseases in heart, lung, liver, kidney, and thyroid.
Initially, participants completed a series of demographic questions related to the following indicators:
- Age
- Gender
- Occupation
- Marital status
- Education
- Smoking (smoking time, average number of cigarettes smoked per day, week, and month, the number of leaves, etc.)
- Using other drugs now and in the past
- Types and dosage of used medications or supplements
- Income level
- Person's medical history and family disease background
- Dietary changes
- Physical activities in the past two months
- Exposure to sunlight, consumption of alcoholic beverages (the amount and type) in the past year.
The participants' body weight and height were measured by a trained nutrition student using a regulated measuring station (Seca GmbH & Co. KG, Hamburg, Germany). The participants were wearing light clothes, but no shoes during the measurement. Body mass index (BMI) was calculated as weight/height2 (kg/m2). Physical activity was assessed using the short version of the International Physical Activity Questionnaire (IPAQ). The physical activity levels as well as continuous values of MET-minutes per week (MET = metabolic equivalent of task) were calculated according to the IPAQ scoring protocol.
The hip circumference was measured in standing position using muscle-bound meters over the most massive relief the hip in a horizontal plane. The blood pressure of the participants was measured by standard methods; 15 minutes after the participant was in a sitting position and leaning his/her arm on a hard surface. The blood pressure was measured twice within 15 minutes from the right hand (at the heart level) and the average of the two values was considered as the final blood pressure.
The participants were asked to avoid consuming tea, coffee, and decongestant drugs as well as smoking. Systolic blood pressure measurement was conducted based on auscultation of the first phase and diastolic blood pressure were auscultation of the second, phase five korotkoff.
Diet quality assessment: The dietary intakes were assessed by a self-administered optically readable food frequency questionnaire (FFQ), which its validity and reliability were tested, approved, and used in Iran. It was administered to obtain information about the usual food intake during the past year (Mirmiran et al., 2010).
This comprehensive questionnaire consisted of 169 items and included frequency alternatives (from once per month to several times per day), the number of food units taken, and the portion sizes. After using the estimated portion sizes, the intake of each food was converted into daily equivalents (metrics were based on grams per day) for statistical analysis.
The DQI-I deals with four aspects of a high-quality diet consisting of variety, adequacy, moderation, and overall balance. Specific diet components are classified under each category. These categories help the users to identify diverse aspects of their diet that might be needed for improvement. The score for each category is calculated as the sum of the scores for each component in that category. The total DQI-I score (ranging from 0 to 100 points) is the sum of the scores for the four categories (Table 1) (Kim et al., 2003).
The hip circumference was measured in standing position using muscle-bound meters over the most massive relief the hip in a horizontal plane. The blood pressure of the participants was measured by standard methods; 15 minutes after the participant was in a sitting position and leaning his/her arm on a hard surface. The blood pressure was measured twice within 15 minutes from the right hand (at the heart level) and the average of the two values was considered as the final blood pressure.
The participants were asked to avoid consuming tea, coffee, and decongestant drugs as well as smoking. Systolic blood pressure measurement was conducted based on auscultation of the first phase and diastolic blood pressure were auscultation of the second, phase five korotkoff.
Diet quality assessment: The dietary intakes were assessed by a self-administered optically readable food frequency questionnaire (FFQ), which its validity and reliability were tested, approved, and used in Iran. It was administered to obtain information about the usual food intake during the past year (Mirmiran et al., 2010).
This comprehensive questionnaire consisted of 169 items and included frequency alternatives (from once per month to several times per day), the number of food units taken, and the portion sizes. After using the estimated portion sizes, the intake of each food was converted into daily equivalents (metrics were based on grams per day) for statistical analysis.
The DQI-I deals with four aspects of a high-quality diet consisting of variety, adequacy, moderation, and overall balance. Specific diet components are classified under each category. These categories help the users to identify diverse aspects of their diet that might be needed for improvement. The score for each category is calculated as the sum of the scores for each component in that category. The total DQI-I score (ranging from 0 to 100 points) is the sum of the scores for the four categories (Table 1) (Kim et al., 2003).
- Variety
Variety was evaluated both as an overall variety and as a variety of protein sources. The maximum overall variety score can be achieved by intake of at least one meal from each of the food groups (meat, poultry, fish, egg, dairy, beans, grains, fruit, and vegetables). The score for the variety of protein sources (meat, poultry, fish, dairy, beans and eggs) was based on consuming more than half of the serving size per day by taking into account the data gathered by the FFQ.
- Adequacy.
This feature evaluates the intake adequacy of those dietary elements required to protect the body against under-nutrition and deficiency disorders. The adequacy of fruits, vegetables, grains, and fibers' intake is dependent on the energy intake. So,, for an energy intake of 7118 kJ (1700 kcal), 9211 kJ (2200 kcal), and 11 304 kJ (2700 kcal), the maximum score was assigned to a diet containing two, three, and four portions of fruit and three, four, or five portions of vegetables, respectively. The protein intake was considered adequate when the proportion of the total energy from protein was 10%.
- Moderation
This element evaluates the intake of foods and nutrients related to chronic diseases, which may need limited. To emphasize on the intensity of moderation in fat intake, total fat intake in the DQI-I was evaluated using more stringent cut-off values than those found in other dietary indexes. The ‘empty-calorie food’ component measures how much a person’s energy supply is dependent on low-nutrient density foods, which provide energy alone and supply deficient nutrients. The DQI-I states that table sugar, alcohol, oil, and similar foods are empty calorie foods (if the sum of nutrient densities considered across nutrients in a food is greater than one, the food is considered as an empty-calorie food).
- Overall balance
This category examines the overall balance of diet in terms of proportions of energy sources and fatty acid composition.
Anxiety assessment: Anxiety was assessed by a mental health questionnaire, that is a short version of the self-report depression, anxiety, and stress scale questionnaire. This is a 21-item self-administered questionnaire designed to measure the magnitude of three negative emotional states of depression, anxiety, and stress. The DASS-Depression focuses on reports of low mood, motivation, and self-esteem. DASS-anxiety deals with physiological arousal, perceived panic, and fear. DASS-stress assesses tension and irritability.
Data analysis: For quantitative variables, the Kolmogorov-Smirnov test was used to investigate the normal distribution and to compare different variables in different groups (gender, occupation, etc.). Afterwards, in the case that the data were normal, t-test and ANOVA were run and in case of significant results, a posteriori test was applied. In the case that data were not normal, some other tests were applied including the Kruskal-Wallis nonparametric test. Chi-square test was also used to determine the relationship between qualitative variables. Data were checked for normality using the Kolmogorov–Smirnov test. Multivariate linear regression was used to examine the association between scores of dietary patterns and DASS with adjustments for age, education, job, income, and smoking for model 1 and additionally for BMI and physical activity for model 2. The significance level was set at P-value < 0.05. All statistical analyses were conducted using Statistical Package for the Social Sciences (SPSS version 16 (SPSS Inc., Chicago, USA)). In addition, mental health was assessed using a short version of the self-report depression, anxiety, and stress scale (DASS-21) questionnaire (with seven items per subscale) (Lovibond, 1996), which was validated for Iranian population (Sahebi et al., 2005).
Results
Demographic characteristics, lifestyle information, and DASS scores of the study participants are presented in Table 2. The mean age of 180 studied participants was 27.1 years. The age means of 90 men and 90 women were 29.13 and 25.06 years, respectively. The mean BMI for the total participants was 23.82 (kg/m2). The results showed that 98% of participants had an academic degree. The mean anxiety score of participants was 4.9 and the anxiety score was not different between men and women participating in the study. Table 3 shows the score of the dietary quality index and its components for all participants. As shown in Table 3, no difference was observed between men and women with regard to the score of the DQI and its components.
Univariate and multivariate linear regressions of anxiety and DQI score showed a significant relation between DQI score and anxiety in all participants, including both males and females (Table 4). Diet quality index score had a negative association with anxiety in all participants. In addition, adjustments for age, education, income, job, smoking, physical activity, and BMI did not change the aforementioned associations.
.PNG)
Anxiety assessment: Anxiety was assessed by a mental health questionnaire, that is a short version of the self-report depression, anxiety, and stress scale questionnaire. This is a 21-item self-administered questionnaire designed to measure the magnitude of three negative emotional states of depression, anxiety, and stress. The DASS-Depression focuses on reports of low mood, motivation, and self-esteem. DASS-anxiety deals with physiological arousal, perceived panic, and fear. DASS-stress assesses tension and irritability.
Data analysis: For quantitative variables, the Kolmogorov-Smirnov test was used to investigate the normal distribution and to compare different variables in different groups (gender, occupation, etc.). Afterwards, in the case that the data were normal, t-test and ANOVA were run and in case of significant results, a posteriori test was applied. In the case that data were not normal, some other tests were applied including the Kruskal-Wallis nonparametric test. Chi-square test was also used to determine the relationship between qualitative variables. Data were checked for normality using the Kolmogorov–Smirnov test. Multivariate linear regression was used to examine the association between scores of dietary patterns and DASS with adjustments for age, education, job, income, and smoking for model 1 and additionally for BMI and physical activity for model 2. The significance level was set at P-value < 0.05. All statistical analyses were conducted using Statistical Package for the Social Sciences (SPSS version 16 (SPSS Inc., Chicago, USA)). In addition, mental health was assessed using a short version of the self-report depression, anxiety, and stress scale (DASS-21) questionnaire (with seven items per subscale) (Lovibond, 1996), which was validated for Iranian population (Sahebi et al., 2005).
Results
Demographic characteristics, lifestyle information, and DASS scores of the study participants are presented in Table 2. The mean age of 180 studied participants was 27.1 years. The age means of 90 men and 90 women were 29.13 and 25.06 years, respectively. The mean BMI for the total participants was 23.82 (kg/m2). The results showed that 98% of participants had an academic degree. The mean anxiety score of participants was 4.9 and the anxiety score was not different between men and women participating in the study. Table 3 shows the score of the dietary quality index and its components for all participants. As shown in Table 3, no difference was observed between men and women with regard to the score of the DQI and its components.
Univariate and multivariate linear regressions of anxiety and DQI score showed a significant relation between DQI score and anxiety in all participants, including both males and females (Table 4). Diet quality index score had a negative association with anxiety in all participants. In addition, adjustments for age, education, income, job, smoking, physical activity, and BMI did not change the aforementioned associations.
Discussion
The purpose of this study was to investigate the association between anxiety and DQI score. This research is the first study on the relationship between diet quality and mental disorders in Iran. With respect to the importance of the global burden of anxiety, as a known major public health concern with an increasing prevalence, this study was designed. The results showed that anxiety and DQI scores of 90 couples had significant association. The relationship remained significant after adjusting for the covariates. According to the literature, it seems that no study has ever investigated the relationship between DQI and anxiety status.
The other studies had discovered the correlation between diet quality and chronic diseases. In the Nurses' Health Study and the Health Professionals Follow-Up Study, the risk of chronic diseases, such as cardiovascular disease and cancer was 25% lesser in individuals, who were in the top quintile of diet quality scores over eight years of follow-up compared to the lowest quintile (Weng et al., 2012). Diet quality measured by dietary pattern analysis showed the risk of cardiovascular diseases in studies (Bakhtiyari et al., 2013, Mirmiran et al., 2010). Diet quality index was also inversely related to cancer mortality in participants (McCullough et al., 2002). Recent results from the INTERHEART study over 52 countries demonstrated that the risk for acute myocardial infarction was 30% higher in individuals with higher scores on a measure of dietary “risk” (Fung et al., 2001).
These results are largely concordant with previous studies revealing an inverse relationship between measures of diet quality indices and anxiety (Hu et al., 2000, Mai et al., 2005). Healthy diet was found to have an inverse association with anxiety, while the unhealthy and western dietary patterns increased the risk of anxiety. Higher scores of healthy diet (greater intake of fruits, vegetables, whole grains and low-fat meat) were associated with better mental health and lower anxiety (Mai et al., 2005). On the other hand, higher intake of processed foods, sweets, beverage, as well as red meat and its products were found to have a positive association with mental disorders (Jacka et al., 2010b). Previous studies reported that micronutrients, such as vitamins (vitamins B, vitamin C, vitamin D, and vitamin E), minerals (calcium, chromium, iron, magnesium, zinc and selenium), and other bioactive substances (phenolic compounds and plant sterols) could reduce the risk of mental diseases (Jacka et al., 2010a). These nutrients and substances are found in many food groups. For example, fruits and vegetables are good sources of B vitamins, vitamin C, vitamin E, iron, calcium, magnesium, and bioactive substances (Munoz et al., 2008), dairy products are good sources of calcium, zinc, vitamin B2, vitaminB12, selenium, and magnesium, and finally, legumes are known to contain vitamin B9, iron, zinc, and calcium (Bakhtiyari et al., 2013).
In a study, a sample of 1046 adult women were asked to consume a dietary pattern including vegetables, fruit, beef, lamb, fish, and whole-grains. Later, the results showed that this dietary pattern decreased the odds ratio of clinically diagnosed anxiety. However, a dietary pattern including processed and western diets was related to an increased odds ratio of psychological symptoms. Augmented a priori diet quality scores were also related to reduce psychological symptoms (Fung et al., 2001). In another study, a lesser adherence to consumption of foods including a healthy diet as well as an augmented intake of unhealthy foods were related to increased odds for anxiety in participants (Hu et al., 2000). These associations confirmed the dose-response patterns and remained significant after adjustment for a wide range of potential confounding factors. Emotional eating means the tendency to preferably consume energy-dense sweet and high-fat foods in response to stress. Several studies confirmed that the manifestation of anxiety symptoms was related to emotional eating (Kaur and Kapoor, 2001, Lampe, 1999, Messina, 1999), but evidence is lacked regarding the role of specific anxiety profiles on emotional eating. Parker and Crawford observed that craving for comfort foods, such as chocolate or cake, increased with increased number of atypical anxiety symptoms and identified rejection sensitivity as one important predictor of such craving (Konttinen et al., 2010, Ouwens et al., 2009, Parker and Crawford, 2007, Whitaker et al., 2014).
The level of income, education, age, and smoking affects the person's depression and anxiety status. In the literature, lower education levels and higher age had a direct relationship with anxiety in individuals. A direct relationship was also reported between smoking and anxiety disorders (Yousefi et al., 2010). In this study, after adjusting these factors, a positive relationship was found between dietary quality and anxiety, which suggests that DQI has an impact on the level of anxiety beyond the other factors.
Inflammatory procedures are thought to play an etiological role in the initiation and maintenance of mental disorders (Smith, 1991). They are also of central importance in the high-prevalence of chronic disease, such as coronary heart diseases and diabetes (Shah et al., 2008, Spranger et al., 2003). Inflammation may describe the relationship among medical illnesses, mental disorders, and mortality, in addition to its associations with diet. Adaptation of a Mediterranean diet, high in vegetables, fruits, legumes, whole grains, fish, olive oil, and low-fat dairy products, is associated with lower levels of inflammation (Chrysohoou et al., 2004). However, western diets and diets high in refined carbohydrates are related to higher levels of C-reactive protein, as a marker of low-grade inflammation (Liu et al., 2002). A western dietary pattern decreased brain-derived neurotrophic factor (BDNF) levels during a short period and this result was independent of obesity or nutritional deficits (Molteni et al., 2002). This factor protects neurons from oxidative stress and stimulates neurogenesis (Duman et al., 1997). It also plays a central role in depressive illness (Hashimoto et al., 2004, Mariscal-Arcas et al., 2007). Thus, by moderating the expression of BDNF, diet can influence mental disorders.
This study had a number of limitations. The first limitation was that the study was cross-sectional and cross-sectional studies cannot confirm the cause-and-effect relationship between variables. Mental disorders affect appetite and food intake. Therefore, prospective studies should be conducted to confirm this relationship. In addition to diet, several other risk factors also can increase the risk of mental illnesses, including smoking, alcohol consumption and reduced physical activity. In addition to these risk factors, socio-economic status should be monitored carefully because it also can affect dietary intake and the risk of mental disorders people. So, in future studies, these factors should be monitored carefully. Another limitation of this study was the small number of participants. Future studies should have a greater number of participants.
Conclusions
This study is the first study on the relationship between diet quality and mental disorders in Iran. In this study, a significant correlation was observed between diet quality and risk of mental disorders. The increase in the index of dietary quality in humans caused a significant reduction in their level of anxiety.
Acknowledgements
The authors would like to acknowledge the School of Nutrition and Food Science, Shiraz University of Medical Sciences for their support and contribution considering this study. Researchers also thank all participants who cooperated in this study. This manuscript was based on a data set used in an MSc thesis written by Mahoor Salehi and was registered at the Shiraz University of Medical Sciences (Grant Number 94-01-84-9499). The authors are grateful to Dr. Mohammad Frarouei for his comments and advice.
Authors’ Contributions
Study concept and design: Mahoor Salehi; Acquisition of data Mahoor Salehi; Analysis and interpretation of data: Mahoor Salehi; Drafting of the manuscript: Mahoor Salehi; Critical revision of the manuscript for important intellectual content: Mohammad Hassan Eftekhari, Statistical analysis: Mahoor Salehi; Administrative, technical, and material support: Mohammad Hassan Eftekhari, Study supervision: Mohammad Hassan Eftekhari.
Conflict of Interest
Authors have no conflict of interests.
The purpose of this study was to investigate the association between anxiety and DQI score. This research is the first study on the relationship between diet quality and mental disorders in Iran. With respect to the importance of the global burden of anxiety, as a known major public health concern with an increasing prevalence, this study was designed. The results showed that anxiety and DQI scores of 90 couples had significant association. The relationship remained significant after adjusting for the covariates. According to the literature, it seems that no study has ever investigated the relationship between DQI and anxiety status.
The other studies had discovered the correlation between diet quality and chronic diseases. In the Nurses' Health Study and the Health Professionals Follow-Up Study, the risk of chronic diseases, such as cardiovascular disease and cancer was 25% lesser in individuals, who were in the top quintile of diet quality scores over eight years of follow-up compared to the lowest quintile (Weng et al., 2012). Diet quality measured by dietary pattern analysis showed the risk of cardiovascular diseases in studies (Bakhtiyari et al., 2013, Mirmiran et al., 2010). Diet quality index was also inversely related to cancer mortality in participants (McCullough et al., 2002). Recent results from the INTERHEART study over 52 countries demonstrated that the risk for acute myocardial infarction was 30% higher in individuals with higher scores on a measure of dietary “risk” (Fung et al., 2001).
These results are largely concordant with previous studies revealing an inverse relationship between measures of diet quality indices and anxiety (Hu et al., 2000, Mai et al., 2005). Healthy diet was found to have an inverse association with anxiety, while the unhealthy and western dietary patterns increased the risk of anxiety. Higher scores of healthy diet (greater intake of fruits, vegetables, whole grains and low-fat meat) were associated with better mental health and lower anxiety (Mai et al., 2005). On the other hand, higher intake of processed foods, sweets, beverage, as well as red meat and its products were found to have a positive association with mental disorders (Jacka et al., 2010b). Previous studies reported that micronutrients, such as vitamins (vitamins B, vitamin C, vitamin D, and vitamin E), minerals (calcium, chromium, iron, magnesium, zinc and selenium), and other bioactive substances (phenolic compounds and plant sterols) could reduce the risk of mental diseases (Jacka et al., 2010a). These nutrients and substances are found in many food groups. For example, fruits and vegetables are good sources of B vitamins, vitamin C, vitamin E, iron, calcium, magnesium, and bioactive substances (Munoz et al., 2008), dairy products are good sources of calcium, zinc, vitamin B2, vitaminB12, selenium, and magnesium, and finally, legumes are known to contain vitamin B9, iron, zinc, and calcium (Bakhtiyari et al., 2013).
In a study, a sample of 1046 adult women were asked to consume a dietary pattern including vegetables, fruit, beef, lamb, fish, and whole-grains. Later, the results showed that this dietary pattern decreased the odds ratio of clinically diagnosed anxiety. However, a dietary pattern including processed and western diets was related to an increased odds ratio of psychological symptoms. Augmented a priori diet quality scores were also related to reduce psychological symptoms (Fung et al., 2001). In another study, a lesser adherence to consumption of foods including a healthy diet as well as an augmented intake of unhealthy foods were related to increased odds for anxiety in participants (Hu et al., 2000). These associations confirmed the dose-response patterns and remained significant after adjustment for a wide range of potential confounding factors. Emotional eating means the tendency to preferably consume energy-dense sweet and high-fat foods in response to stress. Several studies confirmed that the manifestation of anxiety symptoms was related to emotional eating (Kaur and Kapoor, 2001, Lampe, 1999, Messina, 1999), but evidence is lacked regarding the role of specific anxiety profiles on emotional eating. Parker and Crawford observed that craving for comfort foods, such as chocolate or cake, increased with increased number of atypical anxiety symptoms and identified rejection sensitivity as one important predictor of such craving (Konttinen et al., 2010, Ouwens et al., 2009, Parker and Crawford, 2007, Whitaker et al., 2014).
The level of income, education, age, and smoking affects the person's depression and anxiety status. In the literature, lower education levels and higher age had a direct relationship with anxiety in individuals. A direct relationship was also reported between smoking and anxiety disorders (Yousefi et al., 2010). In this study, after adjusting these factors, a positive relationship was found between dietary quality and anxiety, which suggests that DQI has an impact on the level of anxiety beyond the other factors.
Inflammatory procedures are thought to play an etiological role in the initiation and maintenance of mental disorders (Smith, 1991). They are also of central importance in the high-prevalence of chronic disease, such as coronary heart diseases and diabetes (Shah et al., 2008, Spranger et al., 2003). Inflammation may describe the relationship among medical illnesses, mental disorders, and mortality, in addition to its associations with diet. Adaptation of a Mediterranean diet, high in vegetables, fruits, legumes, whole grains, fish, olive oil, and low-fat dairy products, is associated with lower levels of inflammation (Chrysohoou et al., 2004). However, western diets and diets high in refined carbohydrates are related to higher levels of C-reactive protein, as a marker of low-grade inflammation (Liu et al., 2002). A western dietary pattern decreased brain-derived neurotrophic factor (BDNF) levels during a short period and this result was independent of obesity or nutritional deficits (Molteni et al., 2002). This factor protects neurons from oxidative stress and stimulates neurogenesis (Duman et al., 1997). It also plays a central role in depressive illness (Hashimoto et al., 2004, Mariscal-Arcas et al., 2007). Thus, by moderating the expression of BDNF, diet can influence mental disorders.
This study had a number of limitations. The first limitation was that the study was cross-sectional and cross-sectional studies cannot confirm the cause-and-effect relationship between variables. Mental disorders affect appetite and food intake. Therefore, prospective studies should be conducted to confirm this relationship. In addition to diet, several other risk factors also can increase the risk of mental illnesses, including smoking, alcohol consumption and reduced physical activity. In addition to these risk factors, socio-economic status should be monitored carefully because it also can affect dietary intake and the risk of mental disorders people. So, in future studies, these factors should be monitored carefully. Another limitation of this study was the small number of participants. Future studies should have a greater number of participants.
Conclusions
This study is the first study on the relationship between diet quality and mental disorders in Iran. In this study, a significant correlation was observed between diet quality and risk of mental disorders. The increase in the index of dietary quality in humans caused a significant reduction in their level of anxiety.
Acknowledgements
The authors would like to acknowledge the School of Nutrition and Food Science, Shiraz University of Medical Sciences for their support and contribution considering this study. Researchers also thank all participants who cooperated in this study. This manuscript was based on a data set used in an MSc thesis written by Mahoor Salehi and was registered at the Shiraz University of Medical Sciences (Grant Number 94-01-84-9499). The authors are grateful to Dr. Mohammad Frarouei for his comments and advice.
Authors’ Contributions
Study concept and design: Mahoor Salehi; Acquisition of data Mahoor Salehi; Analysis and interpretation of data: Mahoor Salehi; Drafting of the manuscript: Mahoor Salehi; Critical revision of the manuscript for important intellectual content: Mohammad Hassan Eftekhari, Statistical analysis: Mahoor Salehi; Administrative, technical, and material support: Mohammad Hassan Eftekhari, Study supervision: Mohammad Hassan Eftekhari.
Conflict of Interest
Authors have no conflict of interests.
References
Bakhtiyari M, et al. 2013. Anxiety as a consequence of modern dietary pattern in adults in Tehran—Iran. Eating Behaviors. 14 (2): 107-112.
Bonnet F, et al. 2005. Anxiety and depression are associated with unhealthy lifestyle in patients at risk of cardiovascular disease. Atherosclerosis. 178 (2): 339-344.
Chrysohoou C, Panagiotakos DB, Pitsavos C, Das UN & Stefanadis C 2004. Adherence to the Mediterranean diet attenuates inflammation and coagulation process in healthy adults: The ATTICA Study. ournal of the American College of Cardiology. 44 (1): 152-158.
Duman RS, Heninger GR & Nestler EJ 1997. A molecular and cellular theory of depression. Archives of General Psychiatry. 54 (7): 597-606.
Esmaillzadeh A & Azadbakht L 2008. Food intake patterns may explain the high prevalence of cardiovascular risk factors among Iranian women. Journal of Nutrition. 138 (8): 1469-1475.
Eyre HA, Papps E & Baune BT 2013. Treating depression and depression-like behavior with physical activity: an immune perspective. Frontiers in Psychiatry. 4: 3.
Ferrari AJ, et al. 2013. The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010. PloS one. 8 (7): e69637.
Fung TT, Willett WC, Stampfer MJ, Manson JE & Hu FB 2001. Dietary patterns and the risk of coronary heart disease in women. Archives of Internal Medicine. 161 (15): 1857-1862.
Gómez-Pinilla F 2008. Brain foods: the effects of nutrients on brain function. Nature Reviews. Neuroscience. 9 (7): 568.
Hashimoto K, Shimizu E & Iyo M 2004. Critical role of brain-derived neurotrophic factor in mood disorders. Brain Research. Brain Research Reviews. 45 (2): 104-114.
Hu FB, et al. 2000. Prospective study of major dietary patterns and risk of coronary heart disease in men. American Journal of Clinical Nutrition. 72 (4): 912-921.
Jacka FN, et al. 2010a. Associations between diet quality and depressed mood in adolescents: results from the Australian Healthy Neighbourhoods Study. Australian and New Zealand Jjournal of Psychiatry. 44 (5): 435-442.
Jacka FN, et al. 2010b. Association of Western and traditional diets with depression and anxiety in women. American Journal of Psychiatry. 167 (3): 305-311.
Kaur C & Kapoor HC 2001. Antioxidants in fruits and vegetables–the millennium’s health. International Journal of Food Science and Technology. 36 (7): 703-725.
Kessler RC, Chiu WT, Demler O & Walters EE 2005. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry. 62 (6): 617-627.
Kim S, Haines PS, Siega-Riz AM & Popkin BM 2003. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. Journal of Nutrition. 133 (11): 3476-3484.
Konttinen H, Männistö S, Sarlio-Lähteenkorva S, Silventoinen K & Haukkala A 2010. Emotional eating, depressive symptoms and self-reported food consumption. A population-based study. Appetite. 54 (3): 473-479.
Lampe JW 1999. Health effects of vegetables and fruit: assessing mechanisms of action in human experimental studies–. American Journal of Clinical Nutrition. 70 (3): 475s-490s.
Liu S, et al. 2002. Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. American Journal of Clinical Nutrition. 75 (3): 492-498.
Lopresti AL, Hood SD & Drummond PD 2013. A review of lifestyle factors that contribute to important pathways associated with major depression: diet, sleep and exercise. Journal of Affective Disorders. 148 (1): 12-27.
Mai V, et al. 2005. Diet quality and subsequent cancer incidence and mortality in a prospective cohort of women. International Journal of Epidemiology. 34 (1): 54-60.
Mariscal-Arcas M, et al. 2007. Diet quality of young people in southern Spain evaluated by a Mediterranean adaptation of the Diet Quality Index-International (DQI-I). British Journal of Nutrition. 98 (6): 1267-1273.
McCullough ML, et al. 2002. Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. American Journal of Clinical Nutrition. 76 (6): 1261-1271.
Messina MJ 1999. Legumes and soybeans: overview of their nutritional profiles and health effects. American Journal of Clinical Nutrition. 70 (3): 439s-450s.
Mirmiran P, Esfahani FH, Mehrabi Y, Hedayati M & Azizi F 2010. Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study. Public Health Nutrition. 13 (5): 654-662.
Molteni R, Barnard R, Ying Z, Roberts C & Gomez-Pinilla F 2002. A high-fat, refined sugar diet reduces hippocampal brain-derived neurotrophic factor, neuronal plasticity, and learning. Neuroscience. 112 (4): 803-814.
Mueller TI, et al. 1999. Recurrence after recovery from major depressive disorder during 15 years of observational follow-up. American Journal of Psychiatry. 156 (7): 1000-1006.
Munoz M-A, Fíto M, Marrugat J, Covas M-I & Schröder H 2008. Adherence to the Mediterranean diet is associated with better mental and physical health. British Journal of Nutrition. 101 (12): 1821-1827.
Ouwens MA, van Strien T & van Leeuwe JF 2009. Possible pathways between depression, emotional and external eating. A structural equation model. Appetite. 53 (2): 245-248.
Parker G & Crawford J 2007. Chocolate craving when depressed: a personality marker. British Journal of Psychiatry. 191 (4): 351-352.
Schulze MB, et al. 2005. Dietary pattern, inflammation, and incidence of type 2 diabetes in women. American Journal of Clinical Nutrition. 82 (3): 675-684.
Shah A, Mehta N & Reilly MP 2008. Adipose inflammation, insulin resistance, and cardiovascular disease. ournal of Parenteral and Enteral Nutrition. 32 (6): 638-644.
Smith RS 1991. The macrophage theory of depression. Medical Hypotheses. 35 (4): 298-306.
Spranger J, et al. 2003. Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Diabetes. 52 (3): 812-817.
Tannenbaum BM, et al. 1997. High-fat feeding alters both basal and stress-induced hypothalamic-pituitary-adrenal activity in the rat. American Journal of Physiology. 273 (6): E1168-E1177.
Weng T-T, et al. 2012. Is there any relationship between dietary patterns and depression and anxiety in Chinese adolescents? ublic Health Nutrition. 15 (4): 673-682.
Whitaker KM, Sharpe PA, Wilcox S & Hutto BE 2014. Depressive symptoms are associated with dietary intake but not physical activity among overweight and obese women from disadvantaged neighborhoods. Nutrition Research. 34 (4): 294-301.
Yousefi F, Redzuan Mr, Bte M, Juhari RB & Talib MA 2010. The effects of family income on test-anxiety and academic achievement among Iranian high school students. Acian Social Science. 6 (6): 89.
Bonnet F, et al. 2005. Anxiety and depression are associated with unhealthy lifestyle in patients at risk of cardiovascular disease. Atherosclerosis. 178 (2): 339-344.
Chrysohoou C, Panagiotakos DB, Pitsavos C, Das UN & Stefanadis C 2004. Adherence to the Mediterranean diet attenuates inflammation and coagulation process in healthy adults: The ATTICA Study. ournal of the American College of Cardiology. 44 (1): 152-158.
Duman RS, Heninger GR & Nestler EJ 1997. A molecular and cellular theory of depression. Archives of General Psychiatry. 54 (7): 597-606.
Esmaillzadeh A & Azadbakht L 2008. Food intake patterns may explain the high prevalence of cardiovascular risk factors among Iranian women. Journal of Nutrition. 138 (8): 1469-1475.
Eyre HA, Papps E & Baune BT 2013. Treating depression and depression-like behavior with physical activity: an immune perspective. Frontiers in Psychiatry. 4: 3.
Ferrari AJ, et al. 2013. The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010. PloS one. 8 (7): e69637.
Fung TT, Willett WC, Stampfer MJ, Manson JE & Hu FB 2001. Dietary patterns and the risk of coronary heart disease in women. Archives of Internal Medicine. 161 (15): 1857-1862.
Gómez-Pinilla F 2008. Brain foods: the effects of nutrients on brain function. Nature Reviews. Neuroscience. 9 (7): 568.
Hashimoto K, Shimizu E & Iyo M 2004. Critical role of brain-derived neurotrophic factor in mood disorders. Brain Research. Brain Research Reviews. 45 (2): 104-114.
Hu FB, et al. 2000. Prospective study of major dietary patterns and risk of coronary heart disease in men. American Journal of Clinical Nutrition. 72 (4): 912-921.
Jacka FN, et al. 2010a. Associations between diet quality and depressed mood in adolescents: results from the Australian Healthy Neighbourhoods Study. Australian and New Zealand Jjournal of Psychiatry. 44 (5): 435-442.
Jacka FN, et al. 2010b. Association of Western and traditional diets with depression and anxiety in women. American Journal of Psychiatry. 167 (3): 305-311.
Kaur C & Kapoor HC 2001. Antioxidants in fruits and vegetables–the millennium’s health. International Journal of Food Science and Technology. 36 (7): 703-725.
Kessler RC, Chiu WT, Demler O & Walters EE 2005. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry. 62 (6): 617-627.
Kim S, Haines PS, Siega-Riz AM & Popkin BM 2003. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. Journal of Nutrition. 133 (11): 3476-3484.
Konttinen H, Männistö S, Sarlio-Lähteenkorva S, Silventoinen K & Haukkala A 2010. Emotional eating, depressive symptoms and self-reported food consumption. A population-based study. Appetite. 54 (3): 473-479.
Lampe JW 1999. Health effects of vegetables and fruit: assessing mechanisms of action in human experimental studies–. American Journal of Clinical Nutrition. 70 (3): 475s-490s.
Liu S, et al. 2002. Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. American Journal of Clinical Nutrition. 75 (3): 492-498.
Lopresti AL, Hood SD & Drummond PD 2013. A review of lifestyle factors that contribute to important pathways associated with major depression: diet, sleep and exercise. Journal of Affective Disorders. 148 (1): 12-27.
Mai V, et al. 2005. Diet quality and subsequent cancer incidence and mortality in a prospective cohort of women. International Journal of Epidemiology. 34 (1): 54-60.
Mariscal-Arcas M, et al. 2007. Diet quality of young people in southern Spain evaluated by a Mediterranean adaptation of the Diet Quality Index-International (DQI-I). British Journal of Nutrition. 98 (6): 1267-1273.
McCullough ML, et al. 2002. Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. American Journal of Clinical Nutrition. 76 (6): 1261-1271.
Messina MJ 1999. Legumes and soybeans: overview of their nutritional profiles and health effects. American Journal of Clinical Nutrition. 70 (3): 439s-450s.
Mirmiran P, Esfahani FH, Mehrabi Y, Hedayati M & Azizi F 2010. Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study. Public Health Nutrition. 13 (5): 654-662.
Molteni R, Barnard R, Ying Z, Roberts C & Gomez-Pinilla F 2002. A high-fat, refined sugar diet reduces hippocampal brain-derived neurotrophic factor, neuronal plasticity, and learning. Neuroscience. 112 (4): 803-814.
Mueller TI, et al. 1999. Recurrence after recovery from major depressive disorder during 15 years of observational follow-up. American Journal of Psychiatry. 156 (7): 1000-1006.
Munoz M-A, Fíto M, Marrugat J, Covas M-I & Schröder H 2008. Adherence to the Mediterranean diet is associated with better mental and physical health. British Journal of Nutrition. 101 (12): 1821-1827.
Ouwens MA, van Strien T & van Leeuwe JF 2009. Possible pathways between depression, emotional and external eating. A structural equation model. Appetite. 53 (2): 245-248.
Parker G & Crawford J 2007. Chocolate craving when depressed: a personality marker. British Journal of Psychiatry. 191 (4): 351-352.
Schulze MB, et al. 2005. Dietary pattern, inflammation, and incidence of type 2 diabetes in women. American Journal of Clinical Nutrition. 82 (3): 675-684.
Shah A, Mehta N & Reilly MP 2008. Adipose inflammation, insulin resistance, and cardiovascular disease. ournal of Parenteral and Enteral Nutrition. 32 (6): 638-644.
Smith RS 1991. The macrophage theory of depression. Medical Hypotheses. 35 (4): 298-306.
Spranger J, et al. 2003. Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Diabetes. 52 (3): 812-817.
Tannenbaum BM, et al. 1997. High-fat feeding alters both basal and stress-induced hypothalamic-pituitary-adrenal activity in the rat. American Journal of Physiology. 273 (6): E1168-E1177.
Weng T-T, et al. 2012. Is there any relationship between dietary patterns and depression and anxiety in Chinese adolescents? ublic Health Nutrition. 15 (4): 673-682.
Whitaker KM, Sharpe PA, Wilcox S & Hutto BE 2014. Depressive symptoms are associated with dietary intake but not physical activity among overweight and obese women from disadvantaged neighborhoods. Nutrition Research. 34 (4): 294-301.
Yousefi F, Redzuan Mr, Bte M, Juhari RB & Talib MA 2010. The effects of family income on test-anxiety and academic achievement among Iranian high school students. Acian Social Science. 6 (6): 89.
Type of article: orginal article |
Subject:
public specific
Received: 2018/07/11 | Published: 2019/08/1 | ePublished: 2019/08/1
Received: 2018/07/11 | Published: 2019/08/1 | ePublished: 2019/08/1
References
1. Bakhtiyari M, et al. 2013. Anxiety as a consequence of modern dietary pattern in adults in Tehran—Iran. Eating Behaviors. 14 (2): 107-112.
2. Bonnet F, et al. 2005. Anxiety and depression are associated with unhealthy lifestyle in patients at risk of cardiovascular disease. Atherosclerosis. 178 (2): 339-344.
3. Chrysohoou C, Panagiotakos DB, Pitsavos C, Das UN & Stefanadis C 2004. Adherence to the Mediterranean diet attenuates inflammation and coagulation process in healthy adults: The ATTICA Study. ournal of the American College of Cardiology. 44 (1): 152-158.
4. Duman RS, Heninger GR & Nestler EJ 1997. A molecular and cellular theory of depression. Archives of General Psychiatry. 54 (7): 597-606.
5. Esmaillzadeh A & Azadbakht L 2008. Food intake patterns may explain the high prevalence of cardiovascular risk factors among Iranian women. Journal of Nutrition. 138 (8): 1469-1475.
6. Eyre HA, Papps E & Baune BT 2013. Treating depression and depression-like behavior with physical activity: an immune perspective. Frontiers in Psychiatry. 4: 3.
7. Ferrari AJ, et al. 2013. The epidemiological modelling of major depressive disorder: application for the Global Burden of Disease Study 2010. PloS one. 8 (7): e69637.
8. Fung TT, Willett WC, Stampfer MJ, Manson JE & Hu FB 2001. Dietary patterns and the risk of coronary heart disease in women. Archives of Internal Medicine. 161 (15): 1857-1862.
9. Gómez-Pinilla F 2008. Brain foods: the effects of nutrients on brain function. Nature Reviews. Neuroscience. 9 (7): 568.
10. Hashimoto K, Shimizu E & Iyo M 2004. Critical role of brain-derived neurotrophic factor in mood disorders. Brain Research. Brain Research Reviews. 45 (2): 104-114.
11. Hu FB, et al. 2000. Prospective study of major dietary patterns and risk of coronary heart disease in men. American Journal of Clinical Nutrition. 72 (4): 912-921.
12. Jacka FN, et al. 2010a. Associations between diet quality and depressed mood in adolescents: results from the Australian Healthy Neighbourhoods Study. Australian and New Zealand Jjournal of Psychiatry. 44 (5): 435-442.
13. Jacka FN, et al. 2010b. Association of Western and traditional diets with depression and anxiety in women. American Journal of Psychiatry. 167 (3): 305-311.
14. Kaur C & Kapoor HC 2001. Antioxidants in fruits and vegetables–the millennium’s health. International Journal of Food Science and Technology. 36 (7): 703-725.
15. Kessler RC, Chiu WT, Demler O & Walters EE 2005. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry. 62 (6): 617-627.
16. Kim S, Haines PS, Siega-Riz AM & Popkin BM 2003. The Diet Quality Index-International (DQI-I) provides an effective tool for cross-national comparison of diet quality as illustrated by China and the United States. Journal of Nutrition. 133 (11): 3476-3484.
17. Konttinen H, Männistö S, Sarlio-Lähteenkorva S, Silventoinen K & Haukkala A 2010. Emotional eating, depressive symptoms and self-reported food consumption. A population-based study. Appetite. 54 (3): 473-479.
18. Lampe JW 1999. Health effects of vegetables and fruit: assessing mechanisms of action in human experimental studies–. American Journal of Clinical Nutrition. 70 (3): 475s-490s.
19. Liu S, et al. 2002. Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. American Journal of Clinical Nutrition. 75 (3): 492-498.
20. Lopresti AL, Hood SD & Drummond PD 2013. A review of lifestyle factors that contribute to important pathways associated with major depression: diet, sleep and exercise. Journal of Affective Disorders. 148 (1): 12-27.
21. Mai V, et al. 2005. Diet quality and subsequent cancer incidence and mortality in a prospective cohort of women. International Journal of Epidemiology. 34 (1): 54-60.
22. Mariscal-Arcas M, et al. 2007. Diet quality of young people in southern Spain evaluated by a Mediterranean adaptation of the Diet Quality Index-International (DQI-I). British Journal of Nutrition. 98 (6): 1267-1273.
23. McCullough ML, et al. 2002. Diet quality and major chronic disease risk in men and women: moving toward improved dietary guidance. American Journal of Clinical Nutrition. 76 (6): 1261-1271.
24. Messina MJ 1999. Legumes and soybeans: overview of their nutritional profiles and health effects. American Journal of Clinical Nutrition. 70 (3): 439s-450s.
25. Mirmiran P, Esfahani FH, Mehrabi Y, Hedayati M & Azizi F 2010. Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study. Public Health Nutrition. 13 (5): 654-662.
26. Molteni R, Barnard R, Ying Z, Roberts C & Gomez-Pinilla F 2002. A high-fat, refined sugar diet reduces hippocampal brain-derived neurotrophic factor, neuronal plasticity, and learning. Neuroscience. 112 (4): 803-814.
27. Mueller TI, et al. 1999. Recurrence after recovery from major depressive disorder during 15 years of observational follow-up. American Journal of Psychiatry. 156 (7): 1000-1006.
28. Munoz M-A, Fíto M, Marrugat J, Covas M-I & Schröder H 2008. Adherence to the Mediterranean diet is associated with better mental and physical health. British Journal of Nutrition. 101 (12): 1821-1827.
29. Ouwens MA, van Strien T & van Leeuwe JF 2009. Possible pathways between depression, emotional and external eating. A structural equation model. Appetite. 53 (2): 245-248.
30. Parker G & Crawford J 2007. Chocolate craving when depressed: a personality marker. British Journal of Psychiatry. 191 (4): 351-352.
31. Schulze MB, et al. 2005. Dietary pattern, inflammation, and incidence of type 2 diabetes in women. American Journal of Clinical Nutrition. 82 (3): 675-684.
32. Shah A, Mehta N & Reilly MP 2008. Adipose inflammation, insulin resistance, and cardiovascular disease. ournal of Parenteral and Enteral Nutrition. 32 (6): 638-644.
33. Smith RS 1991. The macrophage theory of depression. Medical Hypotheses. 35 (4): 298-306.
34. Spranger J, et al. 2003. Inflammatory cytokines and the risk to develop type 2 diabetes: results of the prospective population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Diabetes. 52 (3): 812-817.
35. Tannenbaum BM, et al. 1997. High-fat feeding alters both basal and stress-induced hypothalamic-pituitary-adrenal activity in the rat. American Journal of Physiology. 273 (6): E1168-E1177.
36. Weng T-T, et al. 2012. Is there any relationship between dietary patterns and depression and anxiety in Chinese adolescents? ublic Health Nutrition. 15 (4): 673-682.
37. Whitaker KM, Sharpe PA, Wilcox S & Hutto BE 2014. Depressive symptoms are associated with dietary intake but not physical activity among overweight and obese women from disadvantaged neighborhoods. Nutrition Research. 34 (4): 294-301.
38. Yousefi F, Redzuan Mr, Bte M, Juhari RB & Talib MA 2010. The effects of family income on test-anxiety and academic achievement among Iranian high school students. Acian Social Science. 6 (6): 89.
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