Childhood obesity is a worldwide epidemic.1 Obesity rates have increased among children in Korea over the past decades.2 Childhood obesity is associated with greater risk of adult obesity and increases the lifetime risk of developing chronic diseases such as cardiovascular disease (CVD).3 As with the increased prevalence of overweight and obesity among children, risk factors for metabolic syndrome (MetS) have also increased in this population.4
Metabolic syndrome is defined as a cluster of risk factors for CVD and type 2 diabetes, including central obesity, impaired fasting glucose, elevated blood pressure (BP), and dyslipidemia.5 Metabolic syndrome is closely associated with obesity, and central obesity is a key component in the definition of MetS.6 Researchers have reported that the prevalence of MetS in children was 1.0% to 10.8% in the general population, and the prevalence was 27.2% for overweight/obese children in Korea.4,7,8 These findings are similar to the prevalence in Western countries where, for example, 0.4% to 5.5% of children in the general population, and 3.6% to 31.5% of obese children had pediatric MetS in the United States.9 The presence of multiple cardiovascular risk factors has been associated with accelerated atherosclerotic processes in young adults. For example, postmortem studies indicated that multiple metabolic risk factors (obesity, high BP, and abnormal lipid profile) were associated with atheroma in coronary arteries in children and adolescents, whereas presence of these risk factors measured in childhood and adolescence prior to dying of external causes was associated with a marked increase in percentage of fibrous plaques in the aorta and coronary arteries of black and white young adults.3,10 This may indicate that childhood MetS poses a significant threat to the health of children as well as contributing to morbidity and mortality later in life.
It is reported that many factors including socioeconomic characteristics, physical activity, and diet were associated with MetS in adults,11–13 whereas a few studies were conducted to elucidate behavioral and socioeconomic risk factors of MetS in overweight/obese school-age children.14 The theoretical framework of this study was the Social Structure and Personality Research framework, which is concerned with the association between macrosocial structures and individual characteristics and behavior. This perspective posits that because social structure influences individual behavior, socioeconomic differences in morbidity and mortality are due in part to conditions that originate from an individual’s socioeconomic position.15,16
Based on the Social Structure and Personality Research framework, the purpose was to examine behavioral and socioeconomic factors that were associated with MetS and its biomarkers among overweight/obese school-age children. The research questions are as follows:
Research Question 1: What was the prevalence of MetS among overweight/obese school-age children?
Research Question 2: What were the socioeconomic factors associated with MetS among school-age children?
Research Question 3: What were the behavioral risk factors associated with individual biomarkers of MetS among overweight/obese school-age children?
A cross-sectional nonexperimental study was conducted. This study was approved by the institutional review board of the university medical center with which the author(s) are affiliated.
A convenience sample of 4 elementary schools in 1 metropolitan area in South Korea was recruited. Health screenings are conducted annually by school nurses/health teachers in Korea. Based on health screening results, school nurses sent newsletters to parents of overweight/obese children. Parental consent forms and letters explaining the purpose of the study were accompanied with newsletters. Eligibility criteria included children who were body mass index (BMI) for age at 85% or greater,17 were able to read and understand the Korean language, and enrolled in the third or upper grades in participating schools. Children who had chronic health problems were excluded from the study. A total of 2720 students were enrolled in the 4 schools. Grade 3 or higher comprised 72.0% (n = 1959), of whom 10.7% were overweight/obese. A total of 75 parents (35.8% of overweight/obese children) agreed that their children could participate in the study.
Among the 75 children who participated in our study, 12 children did not provide education levels of both or either parent(s). Thus, data on 63 children were included in the logistic regression analysis in explaining socioeconomic factors of MetS. A former study reported significant association between maternal education level and central obesity among young adults with an odds ratio (OR) of 6.14 (P = .001).18 Based on the previous study, power analysis was performed using G*Power 3.1.9 (Heinrich-Heine University, Dusseldorf, Germany). With an OR of 6.14 (binomial distribution and a Pr [Y = 1 | X = 1] H0 = 0.2), 59 children were required to produce 80% power (R2 = 0.20, α = .05).18 Therefore, inclusion of 75 children was sufficient for our study.
General Characteristics. General characteristics included age and gender of children. Socioeconomic status included education levels of parents, mother’s employment status, children’s perception of family income, and family structure (whether living with single or both parents).
Children’s Perception of Family Income. To measure children’s perception of family income, a single item was used by asking, “What do you think of your family’s level of wealth?” This question was developed by Eo for Korean children.19 Response categories ranged from 1 = very poor to 5 = very wealthy. Validity of this question was verified in a previous study.19
Anthropometric Measurements. Anthropometric measurements included height, weight, and waist circumference. Body mass index (in kilograms per meter squared) was calculated from the height (in meters) and weight (in kilograms) measured using an electronic scale (Dong Sahn Jenix [DS-103], 2010, Seoul, Korea), with children wearing light clothes and shoes off.20 Body mass index–for–age percentiles were determined according to an age- and gender-specific reference growth chart for Korean children.17 Waist circumference was measured using a tape measure to the nearest 0.1 cm at the high point of the iliac crest at minimal respiration in a standing position.20
Physiological Examinations. Physiological examinations included fasting blood sugar, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol and were analyzed using enzymatic methods. Blood pressure was measured twice at intervals of at least 1 minute using an electronic sphygmomanometer, and mean BP scores were used. Children were instructed to rest in the seated position at least 5 minutes before BP measurements and to not talk during the measurement procedure, and BP was measured with a cuff placed around the bare right upper arm.21
Diagnosis of Metabolic Syndrome. Metabolic syndrome is determined using the criteria provided by Yoshinaga et al22 for Japanese children. Children who met at least 3 of the following 5 criteria were diagnosed as having MetS: (1) BP 120/70 mm Hg or greater for children in the first to third grades (7–9 years) and 130/80 mm Hg or greater for children in the fourth to sixth grades (10–12 years), (2) HDL-C of less than 40 mg/dL, (3) serum triglycerides of greater than 120 mg/ dL, (4) fasting blood sugar of greater than 100 mg/dL, and, (5) 90th percentile values or greater for waist circumference.22
Eating Behavior. Eating behavior was measured with 4 items that were developed after a review of the literature. Items that were found to be associated with obesity were included.23–27 Items included eating 3 meals each day regularly, eating breakfast, frequency of fast-food consumption (hamburgers, pizza, and/or fried chicken, etc), and eating a late dinner after 8 PM during the past month. Eating behavior was scored on a 5-point Likert scale (from 1 = always to 5 = never). Reverse questions were recoded before the analysis, and lower scores indicate better eating habits. Cronbach’s α’s for eating behavior were .76 in the previous study25 and .71 in our study.
Lifestyle Behaviors. To measure exercise frequency, children were asked how many days a week they performed moderate (eg, baseball, table tennis, or badminton) and/or vigorous exercise (eg, basketball, jogging, swimming, or bicycling). Exercise frequencies were measured by asking the number of days that children had performed moderate and vigorous exercise for more than 60 minutes per day, respectively, excluding minutes spent in physical activity classes in schools. Based on the World Health Organization recommendation, those who answered that they engaged in moderate and/or vigorous exercise at least 5 days a week were categorized as regular exercisers.28 Sleep duration was determined using the question, “What was your average sleep duration per evening in the past month?” The level of stress was measured using a single item: “How much stress do you feel in your normal life?” The question was scored on a 4-point Likert-type scale (from 1 = very severe to 4 = never). These lifestyle questions (exercise frequency, sleep duration, and stress) were borrowed from the Korean National Health and Nutrition Survey.29 Screen time was determined with a single question, “How long did you view TV/video, use computers, and play video games per day during the past month?” and was scored on a nominal scale (1 = less than 1 hour, 2 = 1–2.9 hours, 3 = 3 hours or more). This question was developed and validity verified in previous studies.30,31
An assessment of content validity and age-matched appropriateness and readability of the study instruments was performed by 2 experts in the field of child health nursing. The instruments were modified for use in the current study based on the experts’ recommendations. Experts suggested to change some words suited for children’s age (eg, replacement of embarrassment to shame) and to utilize identical period for measuring multiple health behaviors (eg, sleep duration, screen time, and eating behavior).
Data collection was conducted after obtaining written consent from the parents and verbal assent from the participating children. Self-reported data collection was conducted targeting children, and anthropometric measurements were obtained by trained nurses. Blood samples were drawn by medical technicians dispatched from the Planned Population Federation of Korea and sent to a clinical laboratory within the Planned Population Federation of Korea for blood testing. Planned Population Federation of Korea is a nonprofit organization providing services for the health of families, youth, and the elderly. Data collection, anthropometric measurements, and blood sampling were done in the health clinics located within the participating schools.
Data were analyzed with the SPSS 20.0 for Windows (SPSS Inc, Chicago, Illinois). Descriptive statistics such as means, SDs, frequencies, and percentages was used to describe the general, socioeconomic, and behavioral characteristics of the children. A logistic regression analysis and analyses of covariance were performed to analyze factors associated with MetS and its biomarkers. Significance was determined at P < .05 level with 2-tailed tests.
General and Socioeconomic Characteristics of Children and Family
The mean age was 10.6 (SD, 1.09) years (range, 8–12 years), and boys constituted 56.0% of the participants. Fifty-five percent and 45.3% of fathers and mothers, respectively, had obtained education greater than high school level, whereas 41.9% answered that their family was wealthy or very wealthy (Table 1).
Behavioral Characteristics of the Children
Twenty-eight percent performed moderate or vigorous exercise at least 5 days a week. Thirty-three percent perceived very severe or severe stress. Mean eating behavior scores ranged from 1.78 to 2.49 (SD, 0.96–1.26) (range, 1–5), indicating that these children had moderate to fair levels of eating behavior (Table 2).
Prevalence of Metabolic Syndrome and Distribution of Biomarkers
Metabolic syndrome was diagnosed in 27.8% of the population. Fifty-two percent had waist circumference at the 90th percentile or greater, 50.0% had total cholesterol levels of 170 mg/dL or greater, 34.7% had triglyceride levels of greater than 120 mg/dL, 31.9% had HDL-C levels of less than 40 mg/dL, 23.9% had low-density lipoprotein cholesterol levels of 110 mg/dL or greater, 20.8% had serum glucose levels of greater than 100 mg/dL, and 28.0% had elevated BP (Table 3).
Differences in Biomarkers According to Behavioral Characteristics
Systolic BP (SBP) was significantly associated with stress (P = .040). School-age children who perceived severe or very severe stress were more likely to have increased waist circumference than their counterparts; however, the association was not significant (P = .051). Similarly, school-age children who slept at least 9 hours were more likely to have increased total cholesterol (P = .062), increased triglycerides (P = .076), and increased waist circumference (P = .070) than their counterpart (Table 4).
Socioeconomic Factors Associated With Metabolic Syndrome
Increased age was negatively associated with MetS (OR, 0.16; 95% confidence interval [CI], 0.05–0.52), as well as male gender (OR, 0.03; 95% CI, 0.01–0.35). Meanwhile, children’s perception of family income (OR, 4.57; 95% CI, 1.25–16.79) and the mother’s education level (high school or less) were positively associated with MetS (OR, 26.39; 95% CI, 1.47–474.50) among overweight/obese children (Table 5).
Our study found that 27.8% received a diagnosis of MetS. Among the socioeconomic variables, children’s perception of family income and lower education levels of mothers were positively associated with MetS among overweight/obese school-age children. Our study also found that elevated SBP was positively associated with stress. This study is unique because the current study reported the prevalence of MetS among overweight/obese school-age children in Korea and also analyzed socioeconomic and behavioral factors associated with MetS and its biomarkers.
Similar to our study, a previous study reported that 27.2% of the overweight/obese school-age children had MetS in Korea.7 Others also found that 24.3% to 37.5% of overweight/obese children had MetS among Chinese children aged between 10 and 14 years,33 and 38.7% to 49.7% had MetS among obese children between 4 and 20 years of age in the United States.34 However, compared with MetS prevalence among children in total (from 1.0% to 10.8%), overweight/obese children are exposed to excessive risk of MetS.4,8 Therefore, special attention should be given to these high-risk groups of school-age children.
A previous study identified that low education and low income were associated with an increased OR of MetS among adults.12 However, there had been no studies elucidating socioeconomic factors of family associated with MetS in school-age children. Psychosocial and socioeconomic environments wherein children grow is determined by parents, and parents should provide a healthy living environment and should show the children healthy living practices.35 Therefore, socioeconomic (children’s perception of family income and mothers’ education level) and psychosocial environments (stress) provided by the parents may have influenced the increased prevalence of MetS in our study.
Children’s subjective perception of family income was used as 1 of the socioeconomic variables in our study, instead of objective monetary family income. Subjective perception of family income incorporates overall assessment of family’s wealth or poverty status including income, assets, and expenses.36 Children’s perception of family income was positively correlated with children’s health status and health promotion behaviors.37 Others reported that subjective income better captures children’s health behavior than objective measure of income and contended that family income is not equally distributed among family members. This may have resulted in differing perception of family income among family members.38 Thus, use of subjective perception of family income may well represent the socioeconomic environments of the participating children and in turn be associated with diagnosis of MetS in our study.
Kelishadi39 argued a paradox of underweight and overweight conditions coexists among children in Asian countries and contended that economic growth in Asian regions during the last 3 decades has facilitated changes in lifestyles. However, these lifestyles are harmful to chronic diseases including obesity and MetS, especially in regard to excessive consumption of fat among children.39 Therefore, it is assumed that children from affluent families were more likely to have a higher prevalence of MetS because of lifestyle changes associated with economic growth and stability.
Similar to the previous study, age was negatively associated with MetS in our study.40 Physiologic and metabolic changes during pubertal transition may have been responsible for a decrease in MetS among children in upper grades of elementary schools. Xu et al41 found a slight reduction in waist circumference among children during pubertal transition, whereas others reported lower prevalence of abdominal obesity, hypertriglyceridemia, and hyperglycemia among children 12 to 14 years compared with those 10 to 11 years old.40 Therefore, this transition period could be a critical time to help children prevent MetS and decrease BMI.
Our study found that those with perceived (very) severe stress had an elevated SBP compared with their counterpart. Former studies reported inconsistent results and found that an association between stress and BP was not significant among school-age children in the United States and obese children in Korea.42,43 Stress is considered as a potential threat to the well-being and healthy development of children.44 A chronic increase in cortisol (stress-related hormone) is associated with negative health consequences, including blood cholesterol concentration, BP, and immune function.44 Similarly, a longitudinal study indicates that stressful life experiences are connected with the risk of hypertension.44 Childhood BP levels have been linked with BP in adulthood.42 Thus, association between stress and BP may pose significant health threats to children in the long term.43
Our study results indicated that perceived stress was associated with waist circumference, although it was not statistically significant (P = .051). Consistent with our study, former studies reported that perceived stress was positively associated with waist circumference in adolescents (boys and girls) and abdominal adiposity in adolescent girls in Europe.45,46 Psychological stress increases consumption of energy-dense, high-calorie food, which in turn stimulates weight gain. Similarly, elevated cortisol levels as a result of stress exposure were associated with visceral fat accumulation and lead to abdominal adiposity.45,46 Central obesity is a key component in the definition of MetS, and increased waist circumference is associated with CVD risk factors in children and adolescents.6 Therefore, efforts to decrease waist circumference among overweight/obese children are required, and stress management intervention would be 1 of the options for these children. In the development of stress management intervention, sources of stress should be considered, because children and adolescents may be exposed to multiple stressors.46
The Centers for Disease Control and Prevention recommends at least 10 hours of sleep a day for school-age children.47 However, our study found that school-age children who slept at least 9 hours were more likely to have increased total cholesterol, increased triglycerides, and increased waist circumference than their counterpart, although association between sleep hours and these MetS risk factors was not statistically significant (P = .062–.076). A former study found that longer sleep duration was associated with increased triglyceride and decreased HDL-C levels in obese adolescents.48 Others reported that longer sleep was associated with lower waist circumference in children and adolescents with all BMI groups.49 Researchers reported U-shaped association between sleep hours and risk of MetS in adults, and those who sleep 7 to 8 hours per night had lower risk of MetS than did their counterparts.50 They explained that short sleep duration is associated with changes in circulating levels of leptin and ghrelin, which in turn stimulates appetite and weight gain by increasing calorie intake and reducing energy expenditure.51 Mechanisms underlying association between longer sleep and risk of MetS are not fully understood.50 However, better total cholesterol and triglyceride levels and lower waist circumference among children who slept less than 9 hours in our study may indicate that optimal sleep duration may differ between normal-weight and overweight/obese children. Further research is needed to discern the relationship between sleep duration and risk factors of MetS in normal-weight and overweight/obese children, respectively, using large representative samples.
The limitations of the study include the use of a cross-sectional study design, which may limit the interpretation of the study results to associations, rather than causal conclusions. Because of the use of the convenience sampling method and the small sample size, generalizability of the study results might be limited. In addition, because behavioral characteristics were collected using a self-reported method, they are subject to recall bias.
Summary and Implications
Based on the Social Structure and Personality Research framework, our study found that both socioeconomic and behavioral factors were associated with MetS and its biomarkers among overweight/obese school-age children in Korea. The results indicated that 27.8% had MetS in our study. Among the biomarkers, stress was associated with SBP. Among the demographic and family characteristics, age, gender, children’s perception of family income, and mother’s education level were associated with diagnosis of MetS.
Nobili52 argued that derangement of lipid and sugar metabolism that is observed in MetS is often associated with the damage of several organs including the gut, liver, pancreas, and adipose tissue. Therefore, early diagnosis and management of MetS are crucial to avoid their progression to severe organ damage. As in our results, investigation of behavioral factors that were associated with biomarkers of MetS can provide information relevant to the development of tailored education for prevention and management of MetS. Nurses should help children modify adverse health behaviors that are associated with MetS and its biomarkers. Future research is recommended to investigate behavioral and socioeconomic risk factors associated with Mets and its biomarkers in school-age children by using large representative samples and using a longitudinal study design such as a cohort study.
What’s New and Important?
- Based on a Social Structure and Personality Research framework, the current study found that children’s perception of family income and mother’s education level were associated with diagnosis of metabolic syndrome among overweight/obese children.
- Among the biomarkers of metabolic syndrome, systolic blood pressure was significantly associated with severe stress.
- Perceived stress was positively associated with waist circumference, and longer sleep duration was associated with increased total cholesterol, increased triglyceride, and increased waist circumference; however, these associations were not statistically significant (P = .051–.076).
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