Introduction
Obesity is considered a global epidemic. The prevalence of overweight and obesity among children of all ages is increasing [1]. The World Health Organization [WHO] has included obesity as a worldwide epidemic needing coordinated preventive measures and a disease in its own right that requires treatment. Obesity is a significant cause of preventable morbidity and mortality primarily in the developed world and increasingly in the developing countries [2]. Childhood obesity is considered the leading cause of pediatric hypertension, associated with type 2 diabetes, increases the risk for coronary heart disease, increases stress on the weight-bearing joints, and affects relationships with peers [3].
The more weight children gain, the more likely they will develop metabolic syndrome. Almost 39% of moderately obese children and nearly 50% of severely obese are classified as having metabolic syndrome. The metabolic syndrome is far more common among children than previously reported, and its prevalence increases with the degree of obesity. Each element of the syndrome becomes worse with increasing obesity [4–6].
In 2013, Ram et al. described “the metabolic syndrome” as a link between insulin resistance, dyslipidemia, type 2 diabetes, hypertension with other metabolic abnormalities, and an increased risk of atherosclerotic cardiovascular disease.
• Cook’s definition for metabolic syndrome in children includes the presence of three of the following:
• Central obesity; waist circumference ≥ 90th percentile for age and sex,
• Fasting blood glucose ≥ 110 mg/dl,
• Blood pressure ≥ 90th percentile for age, sex, and height,
• Serum triglycerides ≥ 110 mg/dl,
• Serum HDL cholesterol ≤ 40 mg/dl [7].
Dysregulation of the hypothalamic-pituitary-adrenal axis is crucial for developing metabolic syndrome [8]. Dysregulation of the hypothalamic-pituitary-adrenal axis increases cortisol levels. Increased cortisol is associated with increased abdominal body fat accumulation, triglyceride storage in the adipose cells, insulin resistance, and hypertension [9]. In children, metabolic syndrome has been linked to chronic stress exposure and hypothalamic-pituitary-adrenal axis abnormalities leading to the assumption that subjects with metabolic syndrome may have a mild form of hypercortisolism [10]. Evidence supporting this hypothesis includes the findings that an increase in stress-related cortisol secretion is associated with features of the metabolic syndrome in both males and females, and males with metabolic syndrome have increased urinary cortisol metabolite secretion [11]. Because cortisol is a well-known counter-regulator of insulin action, it is proposed that the relationship between metabolic syndrome and cortisol is likely due to the increased insulin resistance seen in the relative hypercortisolemic state [10].
Cortisol circulates in the plasma primarily bound to cortisol binding globulin or albumin. Less than 5% of circulating cortisol is free cortisol. Since binding proteins are absent from saliva, salivary cortisol concentration is in equilibrium with plasma free cortisol [12].
Previous studies used either a crude marker of cortisol or measured serum cortisol, but salivary cortisol testing provides a more accurate reflection of the amount of cortisol delivered to receptors and subsequently a reflection of active hormone levels in the body [13]. Thus, the salivary cortisol test is a simple, reproducible, stress-free, non-invasive, and early predictor of metabolic syndrome [14].
Aim
The aim of our study was to evaluate the relationship between dietary habits, salivary cortisol levels and metabolic syndrome in children.
Material and methods
This study was designed as a case-controlled study carried on a sample consisting of 23 subjects in each patient group and control group in Ismailia city primary schools to determine the relationship between metabolic syndrome and circadian salivary cortisol levels.
Study population
The study was conducted in 46 subjects selected from primary schools in Ismailia city urban primary schools. The study subjects were divided into two age- and gender-matched groups: Group 1: Children with metabolic syndrome as a patient group. Group 2: Normal age- and sex-matched children as a control group.
Each case was matched with a control child within the same classroom with similar scholarly achievement and socioeconomic status.
Inclusion criteria
1. Children have metabolic syndrome with the presence of at least three of the following according to guidelines from the third National Health and Nutrition Examination Survey (NHANES III):
• Central obesity; waist circumference ≥ 90th percentile for age and sex,
• Fasting blood sugar ≥ 110 mg/dl,
• Blood pressure ≥ 90th percentile for age, sex, and height,
• Serum triglycerides ≥ 110 mg/dl,
• Serum HDL cholesterol ≤ 40 mg/dl [7].
2. Age between (5–10) years.
Exclusion criteria
• Children are known to have type 1 DM.
• Children are known to have syndromes, including obesity.
• Children are known to have cardiovascular diseases.
• Long-term use of drugs (e.g., glucocorticoids).
Sample design
The sample size was calculated and the minimum required number of people in each group was determined to be 23 in each group.
Methods
All children were subjected to:
1. History taking
a) Symptoms of obesity complications. (e.g., dyspnea, easy fatigability, insomnia, polyuria, arthralgia, headache).
b) Risk factors of childhood metabolic syndrome include:
• Dietary habits,
• Physical activity,
• Sedentary behavior,
• Age of onset of obesity.
c) Detailed family history of (obesity, diabetes mellitus, hypertension, and cardiovascular diseases).
Measurements
Blood pressure (BP)
Using the clinical learning guide for measuring blood pressure for pediatric subjects, the BP level was placed on percentile charts [15].
Weight
The weight was measured while the child was wearing light clothes. It was measured to the nearest 0.5 kg. Then the reading was recorded and plotted on the Egyptian percentile for weight [16].
>Height
After removing the shoes and socks, the child stands straight so that his heels, buttocks, and shoulders are in contact with a vertical wall, ensuring that the knee is fully extended. The head is put carefully in the neutral position with the lower margins of the orbit in the same horizontal plane as the external auditory meatus. The reading is recorded and plotted on the Egyptian percentile for height [16].
Body mass index
Obesity in children was defined as BMI above the 95th percentile on growth charts for age according to the Egyptian percentile curves for BMI, 2002; BMI = weight (kg)/height (m²).
The reading is recorded and plotted on Egyptian percentile curves for BMI to determine the degree of obesity according to the value of BMI.
Waist circumference
Waist circumference is the minimum circumference between the costal margin and iliac crest, measured horizontally, with the subject standing [17].
Laboratory investigations
The studied groups were subjected to the following investigations to determine the metabolic syndrome’s laboratory components.
Total lipid profile: triglycerides (TG), cholesterol (TC), high-density lipoprotein (HDL), and low-density lipoprotein (LDL)
For the biochemical measurements of TC, LDL, HDL, and TG, approximately 5 ml of blood was collected from each child, after an 8–12 h fast, in vacutainer tubes. After mixing well, it was allowed to stand for 10 min at room temperature, and the serum was separated from the red blood cells by centrifuging the samples at 4,000 rpm for 20 min at 4°C up to 2 h after the venipuncture. The sera were placed in Eppendorf tubes and stored at 2–8°C for 7 days or at freezing at –20°C for 3 months for subsequent lipid fraction measurement. The material was analyzed in a laboratory, and the serum levels of TC, TG, and HDL were determined using Spinreact reagent by a spectrophotometer measuring at 505 nm at 37°C.
TC was estimated using the formula in the model.
TG was estimated using the formula in the sample. LDL-c levels were estimated using Friedewald’s formula: LDL =TC –- HDL – (TG/5) [18].
Fasting blood sugar
A venous sample was drawn in the morning. Subjects fasted for 8–12 h before the blood test. Fasting blood sugar was analyzed using Spinreact reagent by colorimetric enzymatic reaction [19].
Circadian salivary cortisol (in the day and at night)
Salivary cortisol was measured by a competitive immunoassay kit using automated enzymatic assays. Saliva samples were obtained twice, first at 9:00 a.m., then at 21:00, and were collected using special saliva sampling devices (SALI-TUBES 100 SLV-4158). Subjects were requested to abstain from physical activity and food for one hour before they were sampled. Samples were stored at –20°C until assay, and each piece was frozen, thawed, and centrifuged at least once to separate the mucins by centrifugation. Upon the arrival of the samples in the laboratory, the models stayed in the deep freeze at least overnight. The following day the frozen samples were warmed up to room temperature and were mixed carefully. Samples were centrifuged for 5 to 10 min (at 2000–3000 rpm).
Salivary cortisol concentrations were measured using a competitive enzyme immunoassay at a wavelength of 450 ±10 nm. The detection limit range is 0.12–1.47 µg/dl or 1.2–14.7 ng/ml [20].
Data management and statistical analysis
Quantitative data were expressed as mean ± SD or adjusted mean ± SE; qualitative data were described as a number of subjects and percentages. Differences in clinical and biochemical characteristics were tested by Student’s t-test for continuous variables and by χ2 test for categorical data. A two-sided p-value < 0.05 was considered statistically significant. Data were analyzed by Microsoft Office XP (Excel) and SPSS version 20. Multivariate adjustments were performed using the generalized linear model or stepwise multiple linear regression. Significance was established for p < 0.05. Study results were described in tables and graphs.
Results
In our study all cases were sex-matched with controls of similar age, cognitive abilities and socioeconomic status.
Interestingly, while evaluating parents’ BMI, more than 21% of fathers, 26% of mothers, and 26% of both parents of the patient group were obese, while 74% of both parents of the control group were not obese. Parents’ obesity was statistically significantly higher in the patient group compared to the control group (p < 0.05) (Table I),
There was no statistically significant difference in consumption of starch, fried and fatty food, and regularity of time of breakfast in the patient group compared to the control group (p > 0.05). There was statistically significantly higher excess fried food, fats in lunch in the patient group compared to the control group (p < 0.05). There was statistically significantly higher consumption of fried food, fats, and eating dinner at varying times in the patient group compared to the control group (p < 0.05) (Table II).
On the other hand, 30.43% of the patient group eat sweets and fast food, and 21.74% eat fruits, while 4.35% of the control group eat sweets and fast food, and 47.8% of the control group eat fruits. There was statistically significantly higher consumption of sweets and fast foods in the patient group compared to the control group. There was statistically significantly lower consumption of fruits in the patient group compared to the control group (p < 0.05) (Table III).
There was a statistically significantly higher level of shortness of breath, easy fatigability and back pain in the patient group compared to the control group (p < 0.05).
There were statistically significantly higher levels of triglycerides, high-density lipoprotein, hypertension, waist circumference in the patient group compared to the control group (p < 0.002) (Table IV).
Statistically significantly higher blood pressure, weight, BMI, and waist circumference were observed in the patient group compared to the control group (p < 0.001) (Table V).
Statistically significantly lower HDL and higher triglycerides, cholesterol, and fasting blood sugar were observed in the patient group compared to the control group. In the patient group, the mean salivary cortisol level in the day and night was 3.95 ng/ml and 2.95 ng/ml, respectively. In contrast, in the control group, the mean salivary cortisol level in the day and night was 1.52 ng/ml and 1.32 ng/ml, respectively, with no statistically significant difference between the two groups (p > 0.05) (Table VI).
A statistically significant positive correlation between salivary cortisol level in the day and both systolic and diastolic blood pressure and waist circumference (r = 0.554, p = 0.006; r = 0.485, p = 0.019; and r = 0.500, p = 0.018) was observed in the patient group. On the other hand, there was no statistically significant correlation between salivary cortisol level in the day and triglycerides, LDL, HDL, FBS, BMI, waist circumference, and blood pressure in the control group. There was no statistically significant correlation between salivary cortisol level at night and triglycerides, LDL, HDL, FBS, BMI, waist circumference, and blood pressure in both control and patient groups (Table VII).
Discussion
Metabolic syndrome refers to cardiovascular risk factors, such as insulin resistance, obesity, atherogenic dyslipidemia, and hypertension [21]. High BMI is a risk factor for metabolic syndrome in children, but not all overweight children develop metabolic syndrome. Cortisol excess from chronic psychological stress has been proposed as an independent risk factor for metabolic syndrome in this at-risk population [22].
Serum cortisol was used previously in many studies, but salivary cortisol, which represents the active hormone level, is simple, non-invasive and reliable to predict metabolic syndrome in children [23].
In the current study, we found a significant relationship between parental obesity and metabolic syndrome in their children. Similarly, Ejtahed et al. [24] reported significant correlations between the BMI and waist circumference of parents and weight, height, BMI, and waist circumference, as well as systolic and diastolic BP, of their children (p < 0.05).
As parents have crucial roles in constructing their children’s health behaviors, their weight status could be an essential factor. Studies conducted in some Western countries showed that parental obesity is associated with childhood obesity. Fewer studies have investigated the relationships between parental weight status and metabolic complications in children. Whether children with obese parents are at higher risk for cardiometabolic impairment remains to be determined [25].
In the current study, there was a significant relationship between excess fried foods and fats in lunch and the occurrence of metabolic syndrome. On the other hand, excess fried foods and inconsistent dinner time were related to a higher rate of metabolic syndrome. In a similar study, it was reported that there was an association between eating habits at night and metabolic syndrome in females, but in males, it was unrelated. Night eating patterns were associated with dyslipidemia in both males and females [26].
Many researchers agree that eating irregularly is linked to a higher risk of metabolic syndrome [high blood pressure, type 2 diabetes, and obesity] [27, 28].
In the current study, the type of snacks was related to metabolic syndrome, especially fast food and sweets. Similarly, Rinaldi et al. [29] proved in multivariate analysis that students with sweet dietary patterns were at higher risk for abdominal obesity (OR = 1.29; 95% CI: 1.01–1.66), elevated blood pressure (OR = 1.35; 95% CI: 1.01–1.81) and metabolic syndrome (OR = 1.33; 95% CI: 1.02–1.74).
Similarly, Carroll and Dudfield [30] revealed that unprocessed food was considered a protective dietary factor for metabolic syndrome components, and processed food with a high percentage of sugar and saturated fat was a risk factor for metabolic syndrome components.
In the current study, a sedentary lifestyle seems to have no significant effect on the incidence of metabolic syndrome. It was found that sports practice and reaching school either by walking, cycling or by car and watching television have no significant effect on the incidence of metabolic syndrome either.
On the other hand, systematic review and meta-analysis evidence was presented indicating that supervised, long-term, moderate- to vigorous-intensity exercise training, in the absence of therapeutic weight loss, improves the dyslipidemic profile by raising high-density lipoprotein cholesterol and lowering triglycerides in overweight and obese children with characteristics of the metabolic syndrome [31].
Exercise could decrease weight and body mass index and help in improving metabolic syndrome, but it seems that practice itself had no role in the treatment of metabolic syndrome [32].
In this study, the metabolic syndrome children group had a higher incidence of shortness of breath, easy fatigability, excessive sweating, back pain, knee pain, polyuria, and sleeping disorders, such as insomnia, nightmares, or sleep choking.
Similarly, Mushaira et al. [33] reported that sleep disorders were common in metabolic syndrome patients. Symptoms such as insomnia and “unrefreshing” sleep were significant predictors of the development of the metabolic syndrome. Snoring doubled the chances of developing the metabolic syndrome and also predicted specific metabolic abnormalities (elevated blood glucose level and decreased high-density lipoprotein cholesterol).
The present study revealed that blood pressure, weight, and BMI were significantly higher in metabolic syndrome patients than in the control group. Similarly, a study done by Hirschler et al. [34] reported that obese children showed significantly higher values of waist circumference, waist-to-hip ratio, levels of systolic and diastolic BP, insulin, and LDL compared to their lean controls.
The current study showed that waist circumference was significantly higher in patients with metabolic syndrome than in the control group. Similarly, Aganovic and Dusek [35] reported that there was a univariate association (p < 0.01) between waist circumference, proinsulinemia, and components of the metabolic syndrome, including lipid profile and BP.
The present study showed that LDL, triglycerides, cholesterol, and fasting blood sugar levels were higher in patients with metabolic syndrome. In contrast, HDL was lower in patients than controls. This is the classic picture of metabolic syndrome that Weigensberg described [36]. He reported that the metabolic syndrome is a constellation of interrelated abnormalities (namely elevated BMI, dyslipidemia, elevated blood glucose levels, and high blood pressure) that increase the risk for cardiovascular disease and type 2 diabetes.
Our study showed that salivary cortisol level in the day was more strongly correlated with components of metabolic syndrome, especially waist circumference and blood pressure measurements in children with metabolic syndrome. Yoshida [25] reported significant differences in cortisol levels at different times of day among metabolic syndrome females that positively correlated with metabolic syndrome components. Cortisol night/morning ratios were associated with metabolic syndrome scores and metabolic syndrome components. On the other hand, Anagnostis et al. reported no differences in salivary cortisol level at different time points in underweight, normal, overweight, and obese patients [37].
Recent studies have shown that increased levels of cortisol have an important role in the development of metabolic disorders and hypertension later in life. Köchli et al. conducted a cross-sectional study on 324 black and 227 white school children where their salivary cortisol reactivity, body mass index, blood pressure and cardiorespiratory fitness were screened and concluded that lower physical fitness and higher blood pressure were associated with lower cortisol responses in young children, which may subsequently result in a higher probability of developing early cardiovascular diseases at much younger ages in adolescence or early adulthood. This was in general agreement with our results [38].
In addition, another recent study, by Dai et al., showed that fluctuating cortisol levels and circadian cues in children (sunlight, exercise, diet patterns) are associated with health outcomes, which matches our results. They conducted a cross-sectional and longitudinal study of cardiovascular risk profiles in public elementary school children, to assess associations of daily cortisol fluctuations (morning, night) with cardiovascular health outcomes, and concluded that circadian misalignment may be a factor contributing to high blood pressure [39].
Conclusions
Dietary habits, family history, and high salivary cortisol levels during the day were found to be correlated with central obesity and hypertension in children. There was no correlation between salivary cortisol levels at night and presence of dyslipidemia and central obesity in children. The salivary cortisol test is simple, non-invasive, and reliable in predicting metabolic syndrome in children, and circulating cortisol levels are a sensitive biomarker of metabolic syndrome during childhood. Furthermore, the study findings reflect the impact of dietary habits and cortisol levels on developing metabolic syndrome. Intervention programs should focus on improving exercise and following a healthy lifestyle to achieve the long-term goal of reducing the risks of metabolic syndrome. This was a pilot study done on a small group of children. Further studies, on a larger group of participants, are advised to be done to confirm our observations.
Funding
No external funding.
Ethical approval
Not applicable.
Conflict of interest
The authors declare no conflict of interest.
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