Associations between Dietary Patterns and Sleep Problems in Adolescent Girls:
A Descriptive Cross-Sectional Study

Seyede Hamide Rajaie; MSc ^{1, 2}, Amin Salehi-Abargouei; PhD ^{1, 2}, Gordon A.Ferns; PhD ³,
Majid Ghayour-Mobarhan; PhD ⁴ & Sayyed Saeid Khayyatzadeh; PhD ^{*1, 2}

¹ Nutrition and Food Security Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

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

³ Brighton & Sussex Medical School, Division of Medical Education, Falmer, Brighton, Sussex BN1 9PH, UK.

⁴ Metabolic Syndrome Research Center, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

Introduction

Sleep-related disorders are prevalent problems in adolescents and are related to mood disorders, including depression, anxiety, suicidal thoughts and attempts, impaired academic performance, fatigue, pain, and overall reduced quality of life (Roberts et al., 2008). Sleep difficulties are one important risk factor for serious metabolic disorders, including obesity, metabolic syndrome, and type 2 diabetes (Matthews and Pantesco, 2016). Adolescence is a critical period, especially for girls, which may be accompanied by menstrual cycles abnormalities that result in a higher incidence of sleep problems and related psychological disturbances (Roberts et al., 2008). Insomnia has been defined as difficulty with the initiation, maintenance, duration, or quality of sleep which has a negative influence on the day time functioning (Manjavong et al., 2016). The prevalence of insomnia in adolescents is reported to be approximately 23.8% (Hysing et al., 2013), so it seems to be the most common sleep disorder in this age group (Donskoy and Loghmanee, 2018). In addition, excessive daytime sleepiness (EDS) is a public health challenge among the adolescents, with a prevalence ranging from 7.8% to 55.8% (Pereira et al., 2010).

Dietary factors appear to be a modifiable etiologic factor, which can intensify or improve sleep problems and act as a bridge between sleep-related disorders and poor health outcomes. Recently, the role of diet in the pathogenesis of sleep problems have received more attention and their results are inconsistent (Kurotani et al., 2015). While, some findings from epidemiological studies indicated that individuals with higher intakes of refined carbohydrates (Yoneyama et al., 2014) and saturated fatty acids (Grandner et al., 2010, Shi et al., 2008) experience more sleep problems; others suggested that calcium, fiber and B-vitamins may prevent poor sleep symptoms (Peuhkuri et al., 2012). Although, it was reported that the subjects with more difficulty maintaining sleep (DMS) consumed lower carbohydrates (Tanaka et al., 2013), some other studies affirmed that carbohydrate-rich meals increased levels of day-time sleepiness, and this may occur due to serotonin production (Dye et al., 2000, Linder, 1991, Lowden et al., 2004). Moreover, direct associations were reported between low and high protein intakes with insomnia symptoms among middle-aged Japanese workers (Tanaka et al., 2013).

Given that foods are consumed in combination, it is difficult to distinguish the specific effects of each food or nutrient. Recently, nutritional epidemiology attentions have focused on the dietary pattern approach, which mainly corrects some possible interactions between foods and nutrients (Kurotani et al., 2015, Yu et al., 2017).

Although there is increasing evidence showing the relationship between diet and insomnia (Kurotani et al., 2015, Yu et al., 2017), to the best of the authors’ knowledge, no previous study  has focused on the relationship between habitual dietary patterns and chronic insomnia in adolescents. In the present cross-sectional study, it was hypothesized that some major dietary patterns may be related to insomnia problems among Iranian female adolescents.

Materials and Methods

Study population and design: This cross-sectional study was conducted in cities of Mashhad and Sabzevar, northeastern Iran in 2015-2016. A total of 752 adolescent girls aged 12-18 years were participated using a random cluster sampling method from several schools. The participants with a history of chronic diseases (colitis, diabetes, cardiovascular diseases, cancer, and hepatitis) and current medication for the psychological disease were excluded. All of the participants and their parents were asked to complete the written informed consent before the beginning of the study. The study was approved by the ethics committee of Mashhad University of Medical Sciences.

Mesurements: General demographic information was obtained by face-to-face interviews, using a standard questionnaire. Physical activity was assessed through the validated modifiable activity questionnaire (Delshad et al., 2015) and was provided as metabolic equivalents (METs) in hours per day. To estimate energy intake, the reported portion size in FFQ was converted to grams using household measures and then were entered into the Nutritionist IV software. A trained technician using standard protocols measured body weight and height. Body Mass Index (BMI) was calculated as weight in kilograms divided by height in meters squared.

To assess the prevalence of insomnia, a validated Iranian version of the Insomnia Severity Index (ISI) questionnaire was used (Yazdi et al., 2012). The ISI questionnaire has seven questions. Each question has a score range between 0 and 4 stratified into four categories, including 0 (None), 1 (Mild), 2 (Moderate), 3 (Severe), and 4 (Very severe). The total score of ISI ranges from 0 to 28 points. If the ISI score is >7, an individual is considered to have Insomnia.

Daytime sleepiness was assessed through a validated Persian translation of the Epworth Sleepiness Scale (ESS) (Johns, 1991, Sadeghniiat Haghighi et al., 2013). This questionnaire explore the sleepiness rate by assessing eight daily situations, each situation has a score range between 0 and 3. The total score of ESS ranges from 0 (no daytime sleepiness) to 24 (the most excessive daytime sleepiness). EDS was defined as ESS ≥10 (Hayley et al., 2014).

Aggression score was assessed using a validated Persian translation of the Buss-Perry questionnaire (Zivari-Rahman et al., 2012). This questionnaire includes 29 questions with multiple-choice responses. A median cut-point for the definition of aggression was used; therefore, the individuals were categorized as aggressive if their score was >64.

A Persian version of the Beck Depression Inventory (BDI) was used to determine depression score (Bonnet et al., 2005, Ghassemzadeh et al., 2005, Norrby, 2002). BDI is a self-administered questionnaire, including 21 items with various options. The total score for the BDI ranges from 0 to 63 points. If the BDI score was < 13, the person was not considered as de­pressed, and if the subject’s score was > 13, they were categorized as depressed.

A valid and reliable semi-quantitative food frequency questionnaire (FFQ) contained 147 food items used to obtain the dietary intakes of the study participants (Hosseini Esfahani et al., 2010). Experienced dietitians asked participants to designate their consumption frequency for each food item consumed during the previous year on a daily, weekly, or monthly basis during face-to-face interviews. Portion sizes of the consumed foods that were reported in household measures were then converted to grams. The energy and nutrient content of foods were then calculated with the USDA food composition table included in the Nutritionist IV software (First Databank; Hearst, San Bruno, CA, USA). For some traditional Iranian food items that are not included in Nutritionist IV (e.g., traditional bread and some dairy products such as Kashk), Iranian food composition table was used. The dietary intakes of the participants were adjusted for energy intake. To identify dietary patterns, 40 predefined food groups were evaluated (Table 1). Certain food groups were created based on the similarity of nutrients and their association with insomnia.

Ethical cosiderations: This study was approved by the Ethics Committee of Mashhad University of Medical Sciences, Mashhad, Iran (Ethic code: 931188). All methods of the current study were performed in accordance with the Declaration of Helsinki, and all students and their parents completed the informed written consent.

Data analysis: The major dietary patterns were identified using principal component analysis (PCA) based on the 40 food groups, and factors were rotated by varimax rotation. Three factors with eigenvalues > 2 and interpretation of a scree plot were determined. Therefore, three major dietary patterns were identified and then labeled by the interpretation of previous reports. For all the participants, the factor scores of each derived pattern were obtained by summing the intakes of foods weighted by their factor loading. The individuals categorized according to quartiles of dietary pattern scores. To assess the differences in continuous variables across quartiles of three dietary pattern scores one-way analysis of variance was performed. Data analysis: For all statistical analyses, SPSS software version 15.0 (SPSS Inc, Chicago, IL, USA) was used. A chi-squared test was used to compare categorical variables across quartiles of dietary pattern. To explore the relationship between dietary patterns and insomnia, logistic regression was used in several models. In model I, age, energy intake, passive smoking, physical activity, and menstruation status were controlled. In model II, a further adjustment was used for BMI percentile. A P-value < 0.05 was considered statistical significant level.

Results

Three major dietary patterns were identified and are shown in Table 1. The first pattern w:as char:acterized by higher consumption of low and high-fat dairy, fish, eggs, yogurt drink,legumes, fruits, garlic, olives, mayonnaise, tomatoes, cruciferous, green leafy, and other vegetables, which was named as a healthy dietary pattern. The second pattern was labeled as the western dietary pattern, characterized by higher intakes of refined grains, red meats, poultry, processed meats, pizza, fruits, fruit juice, industrial juice and compote, mayonnaise, nuts, soft drinks, sweets, and desserts, coffee, and pickles. The third pattern was a traditional dietary pattern with the highest loading factors for potatoes, snacks, hydrogenated fats, vegetable oil, sugars, soft drinks, sweets and desserts, tea, and spices.

General and clinical characteristics of the study participants across quartiles of major dietary patterns are shown in Table 2. There were no significant differences in age and mensuration status between the quartiles of dietary pattern scores. However, BMI percentiles of the participants were significantly different across quartiles of traditional dietary patterns. In addition, individuals with higher healthy dietary pattern scores were more likely to be physically active compared to those in the lowest quartiles (P = 0.006). Moreover, the depression score was higher in the first quartile of the healthy dietary pattern than in the fourth quartile (P = 0.003). Additionally, the participants in the lowest quartile of the healthy pattern tended to be exposed to smoking compared to those in the highest quartile (P = 0.01).

Table 3 reveals that the participants with the greatest adherence to any of these dietary patterns had significantly higher intakes of total energy and vitamin C, but lower intake of dietary fiber. Also, dietary intakes of red meat, high-fat dairy, coffee, and calcium increased by increasing adherence to the healthy or western dietary pattern, but decreased by increasing scores of traditional dietary pattern. The intakes of whole grains and magnesium were higher among individuals in the first quartile of the traditional or western dietary pattern, but were lower among those in the first quartile of healthy dietary pattern. The intakes of refined grains, total carbohydrate, folic acid, and vitamin B3 decreased by increasing scores of healthy or traditional dietary pattern.

By an increasing western dietary pattern
score, dietary intake of processed meat and nuts increased, but the intakes of low-fat dairy,
legumes, monounsaturated fatty acid (MUFA), polyunsaturated fatty acid (PUFA), vitamin E, and caffeine decreased.

Moreover, individuals in the last quartile of traditional dietary pattern tended to consume higher amounts of vegetable oil, spices, total fat, MUFA, PUFA, vitamin E, and caffeine, but the intakes of processed meats, total protein, vitamin B6, B12, D, and A were higher among those in the first quartile.

The participants with the greatest adherence to healthy dietary pattern had significantly higher intakes of low-fat dairy products, fruits and legumes as well as protein, total fat, MUFA, vitamin A, B6, B12, and D. However, these individuals consumed lower amounts of spices and caffeine.

Multivariable-adjusted odds ratios for insomnia and daytime sleepiness across categories of dietary pattern are indicated in Tables 4, respectively. No significant associations were found between the healthy (OR: 1; 95% CI 0.62-1.59, P_trend = 0.75), western (OR: 1.3; 95% CI 0.8-2.10, P_trend = 0.16) or traditional (OR: 0.62; 95% CI 0.69-1.82,
P_trend = 0.64) dietary patterns and sleep insomnia. There were no relations between the healthy (OR: 0.85; 95% CI 0.54-1.69, P _trend = 0.84), western (OR: 0.81; 95% CI 0.49-1.32, P _trend = 0.55) or traditional (OR: 1.07; 95% CI 0.66-1.74, P_trend = 0.9) dietary patterns and daytime sleepiness. These findings remained non-significant after adjustment for confounding variables in different models.

Discussion

There is increasing evidence showing an association between dietary patterns and insomnia symptoms. In the current cross-sectional study, three major dietary patterns were explored, including healthy, western, and traditional dietary patterns. The healthy dietary pattern w:as char:acterized by a high intake of legumes, fish, eggs, low- and high-fat dairy products, yogurt drink, fruits, garlic, olives, mayonnaise, tomatoes, cruciferous, green leafy, and other vegetables. A western dietary pattern w:as char:acterized by a high intake of red meats, poultry, processed meats, refined grains, pizza, fruits, fruit juice, industrial juice and compote, nuts, mayonnaise, soft drinks, sweets and desserts, coffee, and pickles. The third pattern was the traditional dietary pattern with the highest loading factors for potatoes, sugars, soft drinks, hydrogenated fats, vegetable oil, snacks, sweets and desserts, tea, and spices. No significant association was found between adherence to any of these dietary patterns and insomnia or daytime sleepiness in crude or adjusted models.

The results of the current study were in line with a recent cross-sectional descriptive study (Gonzalez-Sanchez et al., 2019) showing no association between diet quality and presence of insomnia; however, some other studies indicated significant associations between dietary patterns and insomnia symptoms or day-time sleepiness (Campanini et al.,

2017, Castro-Diehl et al., 2018, Godos et al., 2019, Kurotani et al., 2015, Martins et al., 2019, Rostami et al., 2019, Yoneyama et al., 2014, Yu et al., 2017).

Yu et al. found that both traditional northern and modern dietary patterns are associated with a decreased prevalence of insomnia symptoms (Yu et al., 2017). However, this study suffer from some limitations; first, an invalid FFQ was applied to obtain dietary intakes; second; only 12 commonly consumed food groups in the Chinese diet were reported and other food groups that may be related to sleep problemswere not addressed. Moreover, this study was conducted in an adult population which is different from the study population.

Yu et al. found that both traditional northern and modern dietary patterns are associated with a decreased prevalence of insomnia symptoms (Yu et al., 2017). However, this study suffer from some limitations; first, an invalid FFQ was applied to obtain dietary intakes; second; only 12 commonly consumed food groups in the Chinese diet were reported and other food groups that may be related to sleep problemswere not addressed. Moreover, this study was conducted in an adult population which is different from the study population.

Similarly, Kurotani et al. observed that higher adherence to the healthy dietary pattern (characterized by high intakes of vegetables, potatoes, mushrooms, seaweeds, soy products, and eggs) was related to low prevalence of difficulty initiating sleep once or several times in a week (Kurotani et al., 2015). However, they found no significant association between healthy dietary pattern and difficulty initiating sleep at least three times a week. They suggested that diet might have an effect on only mild insomnia symptoms, but it does not affect more sever sleep disorders, which may be affected by factors other than diet. Moreover, they used a not validated and reliable sleep symptom questionnaire (Kurotani et al., 2015).

The mechanisms underlying this inverse association are unclear, but it was hypothesized that dietary protein intake might be inversely associated with insomnia (Zadeh et al., 2011), the mechanism of this association may be related to Tryptophan (TRP). Brain TRP is a precursor to serotonin and melatonin controling sleep cycle (España and Scammell, 2011). However, TRP enters the brain in competition to large-chain neutral amino acids (LCAANs), and the ratio of plasma TRP to LCAANs is a determining factor in this competition. Recently, it has been proposed that this ratio is affected by both dietary carbohydrates and proteins (Wurtman et al., 2003). In animal models, it was shown that high-carbohydrate low-protein diets elevate brain TRP concentration compared to high-protein diets (Fernstrom and Wurtman, 1972).

Moreover, vitamin B3 and B6 may enhance TRP availability for the serotonin and melatonin synthesis (Peuhkuri et al., 2012); in addition, vitamin B12 (Hashimoto et al., 1996) and Magnesium (Meoli et al., 2005) can enhance the melatonin secretion.

In the present study, the participants with the greatest adherence to healthy dietary pattern had significantly higher intakes of animal protein resources, such as dairy products and red meat, as well as total protein (% energy), vitamin B6 and B12, and magnesium. However, they tended to intake lower amount of total carbohydrate (% energy) and vitamin B3. The lower intake of carbohydrate may attenuate the higher animal protein intake effects, and consequently the ratio of plasma TRP to LCAANs. It may be an explanation for the null associations between this healthy dietary pattern and insomnia.

This study hadseveral strengths; first, to the best of the authors’ knowledge, this was the first study focusing on the relationship between habitual dietary patterns and chronic insomnia in adolescents. Second, the dietary intake of the participants was assessed using a validated and reliable FFQ. Third, the data were collected with a high degree of quality control.

This study also had some limitations. First, the PCA required a subjective choice in determining the number of factors, the rotation method of initial factors, and the name of dietary patterns. Second, the causality or the direction of the relation cannot result from the cross-sectional studies. Third, the study population might not be representative of the general population. To assess dietary intake, the FFQ was used, which is prone to measurement error and misclassification. Finally, like other observational studies, several unmeasured confounders were in this study, which could not be controlled.

The present study indicated no significant association between dietary patterns and insomnia or daytime sleepiness among adolescent girl participants. Furthermore, well-designed and longitudinal studies are required to clarify the role of dietary patterns on the management of sleep problems.

Conclusion

The results indicated no significant association between adherence to either the healthy, Western or Traditional dietary patterns and sleep problems among adolescent girl participants. Moreover, well-designed and longitudinal studies are required to clarify the role of dietary patterns on the management of sleep problems.

Acknowledgment

Thanks are owed  to Mashhad and Sabzevar Universities of Medical Sciences, and all students who participated in this study

Authors’ contributions

Ghayour-Mobarhan M and Khayyatzadeh SS designed the research; Khayyatzadeh SS, Salehi-Abargouei A, and Ghayour-Mobarhan M managed the whole project and contributed in all steps; Rajaie H performed statistical analysis and interpretation of the data; Rajaie H wrote the first draft of the manuscript; Salehi-Abargouei A and A.Ferns G facilitated the preparation of the manuscript and its finalization; Khayyatzadeh SS had primary responsibility for final content. All the authors read and approved the final manuscript.

Confilict of interests

The authors declare that there is no competing interest.

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