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Introduction
A regular sleep is one of the basic elements of a healthy life for both children and adults. Many somatic, cognitive and psychological processes are strongly influenced by good sleep, and good sleep contributes to improving health1. It has been shown in many meta-analysis that chronic insufficient sleep (<6 hours) has negative effects on metabolism and it increases the risk of type 2 diabetes, obesity, hypertension, cardiovascular disease and mortality2-7. Despite the fact that adolescents need 8 to 10 hours of sleep8, the National Sleep Foundation has reported that they tend to have irregular sleep patterns across the week and only the 15% of them have an optimal sleep duration9. Sleep has an important role in brain development, and inadequate amount of sleep in adolescence may affect hypothalamic mechanisms that regulate appetite and energy metabolism10.
Studies have reported that short sleep duration is associated with the risk of obesity11,12. Adequate sleep duration is critical for preventing obesity. Overweight and obesity in adolescents not only increase the risk of chronic diseases and psychosocial problems such as decreased self-esteem, poor body image, and social exclusion, but also neuropsychological dysfunctions such as depression13. Furthermore, short sleep duration may have an impact on food intake and appetite. Changes in lifestyle and unhealthy habits such as following a high-calorie diet are often associated with altered sleep patterns and sleep efficiency14. In addition to this, it has been generally demonstrated that the habit of snacking is related to the shortness of sleep duration; nevertheless, it is not clear whether this is due to frequent eating during the day or the high energy and low nutrient content of snacks. However, it is certain that there is a positive relationship between short and irregular sleep patterns and an unhealthy diet15.
Daily activities, individual factors, and environmental changes can have an impact on the sleep patterns of adolescents. Since sleep duration and quality are of great importance in adolescents, the aim of this study was to determine sleep quality and sleep patterns among 11-13 years old adolescents. The second aim of the present study was to find out whether there was an association between sleep quality, sleep patterns, dietary habits, food consumptions, and anthropometric measurements in an adolescent population.
Material and methods
Study design
This study conducted on adolescents between the ages of 11-13 from two public schools between September and December 2017. For this research, approval from Ethics Committee of İzmir Katip Çelebi University were obtained (Decision No. 22.06.2017-95). All participants gave their assent in writing and necessary permissions were obtained from their parents.
Participants and sample
There were 3484 students in the city center of Muğla. A cross-sectional study was carried out in a random sample of adolescents who were attending two public schools in Muğla. The participants were selected using a stratified proportional sampling method according to the number of sampling calculated by the known population with a 95% confidence interval. The sample group included 346 participants. Within this group, the 11-year age group consisted of 65 girls and 70 boys; the age group of 12 consisted of 51 girls, 53 boys; and the age group of 13 consisted of 56 girls and 53 boys.
Questionnaire form
Data was recorded with a questionnaire form applied via face-to face method. The questionnaire form included items on adolescents' characteristics (age, gender, disease diagnosed by physician), screen times (spending time in front of computer and television in leisure time) dietary habits (regular breakfast, skipping main meals), sleep patterns (sleep duration, sleep latency, habitual sleep efficiency), sleep quality, anthropometric measurements, and food consumptions.
Sleep quality
Pittsburgh sleep quality index (PSQI) was applied to determine the sleep quality. In the form consisting of 18 questions, each question is evaluated with a number from 0 to 3. The sum of the scores gives the total PSQI score. The sleep quality of those with less than 5 points in total is “good” whereas that of those 5 points or above is considered as “poor”16,17.
Anthropometric measurements
The body weight, height, waist circumference, and hip circumference were evaluated by previously standardized nutritionists who used conventional anthropometric techniques. In addition, their waist/hip and waist/height ratios were calculated. A portable scale was used to measure body weight. Height measurement was performed using a 2m long inflexible steel waist circumference was measured with a flexible tape18. The anthropometric measurements were assessed using the WHO Growth Reference for 5-19 Years-200719. Gender and age specific z-scores were calculated using the WHO AnthroPlus software20. The children were classified into five categories of BMI for age Z-score (BAZ): underweight, at risk of underweight, normal weight, overweight and obese, in accordance with the cut-off points of < (-2SD), (-2SD) to (-1SD), (-1SD) to (1SD), 1SD, 1SD to 2SD and ≥2SD Z-scores, respectively19.
Food consumptions
The dietary intake was evaluated based on 24-hour food recall. The 24-hour recall was undertaken in chronological order of consumption (from morning to night). Participants were asked to record all the foods and beverages during the previous day. The portion contents of the meals consumed were calculated by using the book called Standard Recipes for Institutions21. The number of grams of the foods specified in the records as a standard was calculated by using the book called “Foods and Meals Photo Catalog: Standards and Quantities”22. Daily food consumption was noted, and daily energy, micro and macronutrient intakes were identified by the Nutrition Information System Software (BEBİS)23.
Statistical analysis
All analyses were done using Statistical Package for the Social Sciences version 24.0 (SPSS Inc. Chicago, IL, USA)24. Frequency tables and descriptive statistics were used to interpret the results. Following the parametric methods, T test was used to compare the independent groups. Following the non-parametric methods, the Mann-Whitney U test was used to compare the two independent groups, and the Kruskal-Wallis H test was used to compare the three or more independent groups.
Results
Adolescent's characteristics
Of the 346 adolescents included in the study, 50.9% were boys, 49.1% were girls, and the mean age was 11.9±0.8 years. It was determined that 86.1% of the individuals did not have a disease diagnosed by the physician. The most common diseases diagnosed by the physician were respiratory system diseases (25.0%) and cardiovascular diseases (18.8%) (Table 1).
Table 1. Adolescent characteristics and sleep patterns (n=346).
| Age (year), mean (SD) | 11.9 (0.8) |
|---|---|
| Age group (year), n (%) | |
| 11 | 135 (39.0) |
| 12 | 104 (30.0) |
| 13 | 107 (30.9) |
| Gender, n (%) | |
| Female | 170 (49.1) |
| Male | 176 (50.9) |
| Disease diagnosed by physician, n (%) | |
| Yes | 48 (13.9) |
| No | 298 (86.1) |
| Diseases, n (%) | |
| Cardiovascular diseases | 9 (18.8) |
| Diabetes | 3 (6.3) |
| Mental health problems | 7 (14.6) |
| Respiratory diseases | 12 (25.0) |
| Muscular system problems | 3 (6.3) |
| Endocrine diseases | 7 (14.5) |
| Vitamin-mineral deficiencies | 7 (14.5) |
| Spending time in front of computer | |
| Never | 92 (26.7) |
| < 1 | 88 (25.4) |
| 1 | 63 (18.2) |
| 2-3 | 76 (21.9) |
| > 3 | 27 (7.8) |
| Spending time in front of television | |
| Never | 27 (7.8) |
| < 1 | 64 (18.5) |
| 1 | 97 (28.0) |
| 2-3 | 125 (36.1) |
| > 3 | 33 (9.6) |
| Skipping main meal | |
| Yes | 35 (10.1%) |
| No | 217 (62.8%) |
| Sometimes | 94 (27.1%) |
| Regular breakfast | |
| Yes | 203 (58.7%) |
| No | 31 (9.0%) |
| Sometimes | 112 (32.3%) |
| Sleep duration (hour), n (%) | |
| 3-5 | 11 (3.2) |
| 6-8 | 101 (29.2) |
| > 8 | 234 (67.6) |
| Sleep latency, n (%) | |
| 0-15 minimum | 186 (53.8) |
| 15-30 minimum | 107 (30.9) |
| 31-60 minimum | 35 (10.1) |
| > 60 minimum | 18 (5.2) |
| Habitual sleep efficiency, n (%)a | |
| ≥ 85% | 334 (96.5) |
| 75-84% | 6 (1.7) |
| 65-74% | 4 (1.2) |
| < 65% | 2 (0.6) |
| PSQI total score, n (%) | |
| Good (< 5) | 299 (86.4) |
| Poor (≥ 5) | 47 (13.6) |
SD: Standard deviation: a: (total of hours asleep)/(total of hours in bed) x100.
Screen times
Spending 2-3 hours in front of computer and television in leisure time was 21.9% and 36.1%, respectively (Table 1).
Dietary habits
More than half (58.7%) of the adolescents eat breakfast regularly and 27.1% of them declared that they sometimes skipped main meals (Table 1).
Sleep patterns and sleep quality
Sleep duration of >8 hours (67.6%), sleep latency of 15 minutes (53.8%) were the most commonly identified sleeping patterns. The mean PSQI score was 3.07±2.54. PSQI scores revealed poor sleep quality in 13.6% of participants. Habitual sleep efficiency was ≥85% in 96.5% of subjects (Table 1).
Anthropometric measurements
The mean of body weight, height, waist circumference, hip circumference, waist to hip and waist to height ratio of adolescents were 46.2±11.7kg, 153.8±8.5cm, 69.4±9.6cm, 84.0±9.4cm, 0.8±0.0, 0.4±0.0, respectively. In the evaluation of BAZ, the prevalence of overweight and obesity was found to be 10.4% and 8.4%, respectively (Table 2).
Table 2. Anthropometric measurements of adolescents.
| Boys (n=176) Mean±SD | Girls (n=170) Mean±SD | Total Mean±SD | |
|---|---|---|---|
| Body weight (kg) | 46.2±12.0 | 46.2±11.4 | 46.2±11.7 |
| Height (cm) | 153.4±8.9 | 154.2±8.0 | 153.8±8.5 |
| WC (cm) | 71.4±9.8 | 67.4±8.9 | 69.4±9.6 |
| HC (cm) | 83.1±9.2 | 84.9±9.4 | 84.0±9.4 |
| WC/HC | 0.8±0.0 | 0.7±0.0 | 0.8±0.0 |
| WC/height | 0.4±0.0 | 0.4±0.0 | 0.4±0.0 |
WC: Waist circumference; HC: Hip circumference; NC: Neck circumference.
Food consumptions
On average, adolescents consumed 1875.6 calories, with caloric intake comprised of 49.3% carbohydrates, 34.8% fat, and 15.8% protein. Intakes of energy, carbohydrate, protein, fat, vitamin A, riboflavin, niacin, vitamin B6, vitamin B12, sodium, zinc, and iron were higher in boys (p<0.05) (Table 3).
Table 3. Daily energy and nutrient intakes of adolescents.
| Boys (n=176) Mean±SD | Girls (n=170) Mean±SD | Total Mean±SD | p | |
|---|---|---|---|---|
| Energy (kcal/day) | 1956.8±228.6 | 1791.1±276.9 | 1875.6±266.3 | <0.001 |
| Carbohydrate (%) | 50.3±6.9 | 48.2±7.9 | 49.3±7.5 | 0.010 |
| Protein (%) | 16.6±4.0 | 15.0±3.3 | 15.8±3.8 | <0.001 |
| Fat (%) | 33.0±5.4 | 36.6±7.3 | 34.8±6.6 | <0.001 |
| SFA (g) | 25.9±8.0 | 27.5±10.1 | 26.7±9.1 | 0.362 |
| Fiber (g) | 19.9±6.6 | 20.6±7.4 | 20.3±7.0 | 0.414 |
| Vitamin A (µg) | 732.2±550.5 | 917.6±346.3 | 898.9±897.3 | <0.001 |
| Vitamin E (mg) | 13.1±5.6 | 10.20±2.9 | 13.2±5.7 | 0.977 |
| Vitamin C (mg) | 99.6±84.0 | 10.8±2.5 | 104.8±80.8 | 0.116 |
| Thiamine (mg) | 0.8±0.2 | 917.6±346.3 | 0.8±0.2 | 0.446 |
| Riboflavin (mg) | 1.5±0.5 | 1.2±2.9 | 1.4±0.4 | 0.011 |
| Niacin (mg) | 11.0±5.0 | 10.8±2.5 | 10.1±4.5 | <0.001 |
| Vitamin B6 (mg) | 1.2±0.3 | 1.1±0.3 | 1.2±0.3 | 0.010 |
| Folate (µg) | 114.7±33.6 | 115.1±34.4 | 114.9±34.0 | 0.903 |
| Vitamin B12 (µg) | 5.2±8.3 | 3.6±2.3 | 4.4±6.1 | 0.001 |
| Sodium (mg) | 4408.1±1070.2 | 3783.3±1589.0 | 4101.1±1384.1 | <0.001 |
| Potassium (mg) | 2305.0±588.0 | 2331.5±650.4 | 2318.0±618.7 | 0.558 |
| Magnesium (mg) | 253.1±58.0 | 249.9±65.2 | 251.6±61.6 | 0.428 |
| Calcium (mg) | 917.6±346.3 | 869.1±318.3 | 893.8±333.2 | 0.238 |
| Zinc (mg) | 10.2±2.9 | 8.9±2.7 | 9.5±2.9 | <0.001 |
| Iron (mg) | 10.8±2.5 | 10.3±2.8 | 10.6±2.7 | 0.049 |
SFA: Saturated fatty acid.
Factors Associated with Sleep Quality
Adolescent's characteristics: Individuals in the age group of 13 and 12 had poorer sleep quality compared to the age group of 11. Moreover, individuals in the age group of 13 had poorer sleep quality compared to the age group of 12. Individuals with a disease had poorer sleep quality than those without a disease (p<0.05).
Screen times: A statistically significant difference was found between those who spent 2-3 hours, those who spent 1 or less than 1 hour, and those who spent no time in front of a computer, in terms of PSQI score (p=0.001).
Dietary habits: Individuals who did not have regular breakfast had poorer sleep quality compared to those who regularly and sometimes had breakfast. Those who skipped meals had poorer sleep quality than those who did not. It was determined that individuals who slept 3-5 hours a day had poorer sleep quality compared to those who slept more than 6-8 and 8 hours (p<0.05) (Table 4).
Table 4. Comparison of some characteristics of individuals with PSQI score.
| n | Total PSQI | p | ||
|---|---|---|---|---|
| Mean±SD | Median | |||
| Gender | ||||
| Male | 176 | 2.88±2.3 | 2.0 | 0.267 |
| Female | 170 | 3.28±2.7 | 3.0 | |
| Age (year) | ||||
| 11(a) | 135 | 2.30±2.1 | 2.0 | <0.01 [a-b,c] [b-c] |
| 12(b) | 104 | 3.29±2.3 | 2.5 | |
| 13(c) | 107 | 3.84±2.9 | 3.0 | |
| BMI classification | ||||
| At risk of underweight | 45 | 3.09±2.6 | 2.0 | 0.765 |
| Normal weight | 236 | 3.17±2.6 | 3.0 | |
| Overweight | 36 | 2.81±2.4 | 2.0 | |
| Obese | 29 | 2.57±1.6 | 2.0 | |
| Disease diagnosed by physician | ||||
| Yes | 48 | 4.08±3.2 | 3.5 | 0.023 |
| No | 298 | 2.92±2.3 | 2.0 | |
| Skipping main meal | ||||
| Yes (a) | 35 | 4.86±3.6 | 4.0 | <0.01 [b-a,c] |
| No (b) | 217 | 2.39±1.9 | 2.0 | |
| Sometimes (c) | 94 | 4.01±2.5 | 4.0 | |
| Regular breakfast | ||||
| Yes (a) | 203 | 2.54±1.9 | 2.0 | <0.01 [b-a,c] |
| No (b) | 31 | 5.19±3.7 | 4.0 | |
| Sometimes (c) | 112 | 3.47±2.6 | 3.0 | |
| Spending time in front of computer in leisure time | ||||
| Never(a) | 92 | 2.72±2.5 | 2.0 | <0.01 [a,b,c-d] |
| < 1(b) | 88 | 2.45±1.8 | 2.0 | |
| 1(c) | 63 | 2.73±2.2 | 2.0 | |
| 2-3(d) | 76 | 4.22±2.9 | 4.0 | |
| > 3(e) | 27 | 3.89±2.8 | 3.0 | |
| Spending time in front of television in leisure time | ||||
| Never | 27 | 3.81±2.7 | 3.0 | 0.200 |
| < 1 | 64 | 2.94±2.7 | 2.0 | |
| 1 | 97 | 2.77±2.2 | 2.0 | |
| 2-3 | 125 | 3.09±2.6 | 2.0 | |
| > 3 | 33 | 3.55±2.5 | 3.0 | |
| Daily sleep duration (hour) | ||||
| 3-5(a) | 11 | 9.82±2.7 | 10.0 | <0.01 [a-b,c][b-c] |
| 6-8(b) | 101 | 4.32±2.6 | 4.0 | |
| > 8(c) | 234 | 2.22±1.6 | 2.0 | |
Mann-Whitney U test and Kruskal -Wallis H test were used.Multiple significant differences between groups were shown by using the a,b,c,d,e characters.
Anthropometric measurements: There was no statistically significant relationship between PSQI score and body weight, BMI classification, waist circumference, hip circumference, and waist/height ratio (p>0.05) (Table 5).
Table 5. Comparison of anthropometric measurements of individuals by gender in terms of PSQI score.
| Boys (n=176) | p | Girls (n=170) | p | |||
|---|---|---|---|---|---|---|
| Good PSQI (≤5) | Poor PSQI (>5) | Good PSQI (≤5) | Poor PSQI (>5) | |||
| Mean±SD | Mean±SD | Mean±SD | Mean±SD | |||
| Body weight (kg) | 46.4±12.3 | 44.6±9.7 | 0.582 | 45.6±11.3 | 49.4±11.7 | 0.089 |
| Height (cm) | 153.2±8.8 | 155.7±9.5 | 0.237 | 153.7±8.3 | 156.5±6.0 | 0.044 |
| WC (cm) | 71.7±10.1 | 69.1±7.1 | 0.330 | 67.1±8.9 | 68.6±8.8 | 0.328 |
| HC (cm) | 83.4±9.4 | 80.4±7.1 | 0.188 | 84.3±9.3 | 88.1±9.4 | 0.030 |
| WC/HC | 0.8±0.0 | 0.8±0.0 | 0.696 | 0.8±0.0 | 0.7±0.0 | 0.089 |
| WC/height | 0.4±0.0 | 0.4±0.0 | 0.097 | 0.4±0.0 | 0.4±0.0 | 0.664 |
WC: Waist circumference; HC: Hip circumference; NC: Neck circumference. Mann-Whitney U test and Student's T test were used.
There was a weak negative relationship between PSQI and the sleep duration (r=0.499; p=0.000), a weak positive relationship between PSQI and height (r=0.185; p=0.001), and a weak negative relationship between PSQI and waist/hip ratio (r=-0.164; p=0.002) (Table 6).
Table 6. Correlation of PSQI scores with some parameters.
| PSQI | ||
|---|---|---|
| r | p | |
| Sleep duration (hour) | -0.499 | 0.000 |
| Energy (kcal) | -0.008 | 0.887 |
| BMI for age Z score | 0.015 | 0.776 |
| Body weight (kg) | 0.099 | 0.065 |
| Height (cm) | 0.185 | 0.001 |
| WC (cm) | -0.003 | 0.957 |
| HC (cm) | 0.102 | 0.058 |
| WC/HC | -0.164 | 0.002 |
| WC/height | -0.086 | 0.109 |
WC: Waist circumference; HC: Hip circumference; NC: Neck circumference. *In cases where at least one of the two quantitative variables does not have distribution, Spearman correlation coefficient was used in evaluating the relationship between the variables.
Food consumptions: When the daily energy and nutrient intake values of individuals were compared to PSQI, only the amount of saturated fatty acid taken daily was statistically significantly lower (p=0.040) in individuals in the good PSQI class compared to those in the poor PSQI class (Table 7).
Table 7. Comparison of daily energy and nutrients in terms of PSQI classification.
| Good PSQI (≤ 5) | Poor PSQI (> 5) | p | |||
|---|---|---|---|---|---|
| Mean±SD | Median | Mean±SD | Median | ||
| Energy (kcal/day) | 1876.6±268.2 | 1904.0 | 1867.8±257.0 | 1879.0 | 0.594 |
| Carbohydrate (%) | 49.3±7.7 | 49.0 | 48.9±6.3 | 50.0 | 0.716 |
| Protein (%) | 15.8±3.8 | 15.0 | 16.2±3.7 | 15.0 | 0.506 |
| Fat (%) | 34.8±6.8 | 34.0 | 34.8±5.7 | 33.0 | 0.884 |
| SFA (g) | 26.3±9.1 | 24.9 | 29.0±8.9 | 27.5 | 0.040 |
| SFA (%) | 12.7±4.0 | 12.02 | 13.6±3.7 | 12.69 | 0.027 |
| Fiber (g) | 20.6±7.1 | 20.0 | 18.5±6.5 | 18.5 | 0.083 |
| Vitamin A (µg) | 909.9±889.4 | 691.4 | 829.4±953.0 | 631.7 | 0.533 |
| Vitamin E (mg) | 13.3±5.7 | 12.1 | 12.5±5.2 | 11.9 | 0.566 |
| Vitamin C (mg) | 106.8±80.6 | 81.7 | 92.5±82.0 | 56.2 | 0.135 |
| Thiamine (mg) | 0.8±0.2 | 0.8 | 0.7±0.1 | 0.8 | 0.271 |
| Riboflavin (mg) | 1.4±0.5 | 1.4 | 1.6±0.4 | 1.5 | 0.065 |
| Niacin (mg) | 10.2±4.6 | 9.6 | 9.5±3.8 | 8.3 | 0.309 |
| Vitamin B6 (mg) | 1.2±0.3 | 1.2 | 1.1±0.3 | 1.1 | 0.707 |
| Folate (µg) | 114.9±33.6 | 114.1 | 114.7±36.7 | 116.7 | 0.964 |
| Vitamin B12 (µg) | 4.4±6.5 | 3.6 | 4.42±2.1 | 4.6 | 0.147 |
| Sodium (mg) | 4057.1±1381. | 3918.9 | 4380.9±1384.7 | 4123.8 | 0.102 |
| Potassium (mg) | 2323.6±630.8 | 2271.1 | 2282.6±539.9 | 2221.8 | 0.771 |
| Magnesium (mg) | 252.5±63.5 | 241.3 | 245.9±47.3 | 240.3 | 0.754 |
| Zinc (mg) | 9.5±3.0 | 9.2 | 9.7±2.2 | 9.9 | 0.221 |
| Iron (mg) | 10.7±2.8 | 10.5 | 10.1±1.9 | 9.8 | 0.347 |
SFA: Saturated fatty acid; PUFA: Polyunsaturated fatty acid; MUFA: Monounsaturated fatty acid. Mann-Whitney U test and Student's T test were used.
Discussion
The need for sleep may vary depending on individual and environmental factors such as age, gender, disease history, and lifestyle habits25. In this study, 13.6% of adolescents had poor sleep quality. The poor sleep quality rate in adolescents was 20% in the Xu et al.'s study26 and 54.7% in Şenol et al.'s study27. Studies have reported that prolonged sleep latency and increased sleep problems in adolescents28,29. Sleep latency was >30 minutes in 15.3% of adolescents in our cohort, which seem lower than previously reported rates28,29. Habitual sleep efficiency was ≥85% in 96.5% of subjects in our cohort, which seems also higher than previously reported rates for ≥85% habitual sleep efficiency in Turkish adolescents27,28. The results are considered to be incompatible due to different measurement methods, different demographic, cultural characteristics and differences in the mean age. National Sleep Foundation states that adolescents should sleep 8-10 hours9. In our study, more than half of adolescents slept 8 hours or more. In our cohort, since the mean age of the students was 11.9±0.8 years, the daily sleep duration may be found to be 8 hours or more. The sleep duration detected was consistent with the recommendation of the National Sleep Foundation. However, it was determined in our cohort that there was a significant relationship between age and daily sleep duration, and that as the age increased, daily sleep duration decreased. Similarly, Felden et al. identified that the risk of poor sleep quality increased with age30. This association may be explained by the fact that, while there is a cumulative increase of academic and recreational activities, there is also a reduction of time of sleep throughout the years31. Besides, the delay in the biological process of melatonin secretion is related with the advancement of puberty and with the reduced sleep hours among adolescents32.
This study has found that age does but gender does not affect sleep quality. Results of various studies report contradictory findings about whether boys or girls obtain more sleep. For example, one study found that girls obtained less sleep than boys and reported greater sleep disturbances33. Another study showed that girls reported longer ideal sleep duration34.
In the current study, a negative relation was detected between the amount of time the adolescents spent in front of a computer and sleep quality. Similar to our results, Akçay et al. showed that as the adolescents spent more time with their media products, their sleep quality deteriorated35. The daily watch on the screen has increased significantly among adolescents. Excessive technology use may contribute to the adolescent insufficient sleep36. A correlation was found between sleep deprivation and spending more than 2 hours in front of a TV or computer37. Watching too much TV has been found to be associated with sleep disorders in adolescence, and the presence of a TV or a computer in the child's room has been shown to cause changes in sleep parameters38. It has been emphasized by experts that children over the age of two should be limited to a maximum of 2 hours in front of the screen39.
It has been identified that adolescents with good and bad sleep quality generally have high dietary fat and saturated fat intake, and low fiber intake in our study. However, no statistically significant difference was identified in terms of energy, macro and micronutrient intake, except for saturated fat intake. Studies have shown that short sleepers have higher energy intakes, notably from fat and snacks, than do normal sleepers40,41. Insufficient sleep duration has been found to increase the rate of preferring high energy foods42. A negative relationship was found between amount of sleep and unhealthy eating habits43. According to previous studies, the intake of fruits, vegetables and milk has a positive association, and the intake of sweets, snacks and fast food has negative association with sleep duration44-46. On the other hand, studies suggest that short sleep duration was related to increased fat intake47,48. Poor sleep quality was associated with a lower intake of fruits, vegetables and milk and higher intake of soda, soft drinks, fast food, instant noodle and confectionaries49. Similar to our result, in a study conducted on Iranian adolescents, there was no relationship between sleep quality and consumption of micronutrients and macronutrients. The mean intake of omega-3 fatty acids in subjects with good-quality sleep was higher than that in the subjects with low-quality sleep50.
In our study, it was observed that individuals who did not have regular breakfast had poorer sleep quality. However, not many studies have examined the association of sleep duration with skipping breakfast among adolescents51-53. Among a large sample of Greek children and adolescents, insufficient sleep duration was associated with unhealthy dietary habits including skipping breakfast51. One study showed that skipping breakfast were significantly higher in children who reported poor sleep52. Skipping breakfast was associated with total and abdominal obesity in adolescents independent of sleep duration54.
Prevalence of obesity has reached epidemic proportions across all gender, age and ethnic groups55. Research to date in young children and adults shows a strong, inverse relationship between sleep duration and risk for overweight and obesity. Fewer studies examining this relationship have been conducted in adolescents56. In this study, the prevalence of overweight and obesity was found to be 10.4% and 8.4%, respectively. Also, although statistical significance was not found, obese adolescents were shown to have less sleep duration averages than adolescents with normal body weight. In current study, BAZ of adolescents was also evaluated according to their sleep quality and no significant difference was found. It is thought that this result was obtained because more than half of the adolescents had normal body weight. In addition, a negative correlation was determined between the waist/hip ratio of students and the PSQI score. Sleep duration and quality have recently been described among obesity risk factors. Many epidemiological studies have shown that there is a relationship between less than 6-7 hours of sleep and obesity57. However, causation is difficult to determine because of the fact that most of the epidemiological studies are observational58. HELENA study results showed that European adolescents who slept 6 hours or less had a higher average BMI of 1.7kg/m2 and 3.4cm larger waist circumference than those who slept 10 hours or more59. In a study on adolescents who less than 8 hours had significantly higher body fat, waist and hip circumference, and BMI60. Similar to our results, the findings of the Babu et al.'s study showed a nonmonotonic relationship between sleep quality and anthropometric parameters61.
There are some strengths and limitations of this study. To date, very few studies have investigated the relationship between dietary habits, food consumption, screen times, anthropometric measurements, and sleep quality in adolescents. We considered sleep duration and sleep quality in explaining sleep status. We considered numerous variables to investigate the association.
This was designed as a pilot study and therefore the sample chosen is not representative and the conclusions cannot be generalized. A single 24-hour recall is not considered to be representative of habitual diet. Further investigations should consider the relationship between sleep and related factors by using objective sleep measures such as polysomnography.
Conclusions
It was determined that most of the adolescents had good sleep quality and sleep duration is consistent with the recommended need. Sleep quality is affected by many factors such as dietary habits, food consumption, screen times, and individual factors. This study results support the development of interventions to help adolescents improve sleep quality. Further studies are needed to clarify the multiple mechanisms involved between individual factors, dietary habits, food consumption, anthropometric measurements, screen times, and sleep patterns in adolescents.
