Home Medicine Effects of exercise combined with diet intervention on body composition and serum biochemical markers in adolescents with obesity: a systematic review and meta-analysis
Article Open Access

Effects of exercise combined with diet intervention on body composition and serum biochemical markers in adolescents with obesity: a systematic review and meta-analysis

  • , , EMAIL logo , , , ORCID logo and
Published/Copyright: September 21, 2022
Download Article (PDF)
Journal of Pediatric Endocrinology and Metabolism
From the journal Journal of Pediatric Endocrinology and Metabolism Volume 35 Issue 11

Abstract

Background

This systematic review aims to evaluate the effects of exercise combined with diet (ECWD), exercise alone, diet alone, and no intervention on body composition and serum biochemical markers in adolescents with obesity to provide reference for solving the metabolic disorders of adolescents caused by obesity.

Contents

Studies published before January 5, 2021 were retrieved from PubMed, Web of Science, Ovid, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang data, VIP database, and SinoMed. Randomized controlled trials with an age between 10 and 20 years, body mass index (BMI) ≥28 kg/m2 or ≥95th percentiles, no history of endocrine and metabolic diseases, heart disease, hematologic disease, and so on before the trial were included.

Summary

Fifteen of the 50,155 studies met the criteria. Meta-analysis showed that ECWD was more effective in reducing BMI (kg/m2) (−2.45 kg/m2, 95% CI: −3.06; −1.85) and fat thickness of back (−13.77 mm, 95% CI: −15.92; −11.62), abdomen (−11.56 mm, 95% CI: −14.04; −9.09), and upper arm (−14.81 mm, 95% CI: −16.74; −12.89) than other interventions; in reducing body fat (−7.03 kg, 95% CI: −9.77; −4.29) and thigh circumference (−4.05 cm, 95% CI: −5.58; −2.52), ECWD and diet alone were more effective than exercise alone; ECWD and exercise alone were more effective in reducing waist circumference (−6.05 cm, 95% CI: −8.37; −3.72), waist-to-hip ratio (WHR; −0.06, 95% CI: −0.11; −0.01), upper arm circumference (−2.57 cm, 95% CI: −3.70; −1.45), triglycerides (TG; −0.30 mmol/L, 95% CI: −0.45; −0.14), total cholesterol (TC; −0.30 mmol/L, 95% CI: −0.59; −0.01), and low density lipoprotein (LDL; −0.22 mmol/L, 95% CI: −0.40; −0.04) than diet alone. ECWD also had effects on tumor necrosis factor-α (TNF-α), interleukin-6, leptin, and so on.

Outlook

ECWD is more effective than exercise alone, diet alone, or no intervention in solving the problems of body shape and metabolic disorder of adolescents with obesity.

Keywords: adolescents with obesity; body composition; exercise combined with diet; serum biochemical markers

Introduction

Adolescents with obesity have become one of the serious public health challenges all over the world in the 21st century. According to statistics, the prevalence of adolescents with obesity has been increasing from 1975 to 2016 [1]. In 2016, more than 340 million children and adolescents aged 5–19 were overweight or obese [1]. The prevalence of adolescents with obesity is growing faster in countries of lower socioeconomic status than in developed countries, especially in parts of Asia [2]. In 2020, the proportion of children and adolescents with overweight and obesity aged 6–17 years was close to 20% in China, and the prevalence of obesity is still increasing [3]. Studies have found that obesity is an important cause of chronic noncommunicable diseases [4], [5], [6], and about 70% of adolescents with obesity suffer from at least one cardiovascular disease risk factor (such as high blood pressure, high cholesterol, etc.) [7]. As the risk of disease increases, so does mortality. An epidemiological survey shows that 5.4% of children and adolescents aged 10–17 were affected by metabolic syndrome in China [8]. Adolescents with obesity have an increased risk of diabetes, kidney disease, liver disease, oncology, respiratory disease, and cardiovascular diseases such as hypertension [7, 9]. At the same time, since the outbreak of COVID-19, it has been found that obesity is one of the risk factors of severe acute respiratory syndrome coronavirus 2 (SARS-cov-2) infection, hospitalization, death, and other viral and bacterial infectious diseases. Therefore, obesity also increases the risk of viral infectious diseases [10, 11].

A number of studies have shown that either exercise interventions alone or diet interventions alone are effective ways to tackle obesity in adolescent [12, 13]. Meta-analysis has shown that diet intervention alone can reduce BMI, TG, and low-density lipoprotein cholesterol (LDL-C) and increase high-density lipoprotein cholesterol (HDL-C) in adolescents with obesity [14]. The proportion of macronutrients and patterns of food choice can affect adolescents’ body composition and metabolism [15], [16], [17]. Adherence to a low-energy diet is a key factor for weight loss [17, 18], and reducing total energy intake can reduce weight and cardiometabolic risk factors in adolescents with obesity [17, 19, 20]. On the basis of low-energy diet studies, it was found that low-fat diet and modified carbohydrate diet can significantly improve body composition indicators such as weight, BMI, body fat percentage (%BF), waist circumference, and so on [21]. It has also been shown that low-carbohydrate diet is more effective than low-fat diet in reducing body weight and blood lipids levels in adolescents with obesity [17]. Hoare et al. found that very low-energy diet, low-carbohydrate diet, and intermittent energy restriction can improve cardiometabolic metabolism in adolescents with obesity [13]. In addition, studies have found that aerobic and high-intensity interval exercise can also reduce BMI, waist circumference, TC, TG, LDL-C, and atherosclerosis index (AI), increase HDL-C, and effectively improve body shape and blood lipids levels in adolescents with obesity [22], [23], [24]. At least 3 days of physical activity per week in adolescents with obesity can effectively reduce weight and cardiometabolic risk factor [25], and long-term exercise can increase energy expenditure by increasing resting metabolic rate [26, 27]. Aerobic exercise and aerobic combined with resistance exercise are the most common intervention modalities [28]. Aerobic exercise can induce the highest efficiency of fat oxidation and can significantly reduce BMI, %BF, TC, TG, LDL-C, atherosclerosis index (AI) and increase HDL-C in adolescents with obesity [29]. Aerobic exercise is a main exercise modality to reduce the high risk of cardiovascular diseases for adolescents with obesity with hyperlipidemia [30]. Bharath et al. found that combined aerobic and resistance exercise can improve blood pressure, insulin resistance, and arteriosclerosis, reduce obesity-related inflammatory markers, reduce central fat, and lower the risk of diabetes in adolescents with obesity in prehypertension [12, 22, 30], [31], [32], [33], [34]. It can be concluded that both diet intervention and exercise intervention can effectively improve body composition and serum biochemical indicators in adolescents with obesity [22, 34, 35]. Therefore, many scholars have studied the effects of ECWD intervention on adolescents with obesity.

It was found that aerobic exercise combined with dietary intervention can effectively improve body shape indicators (except height) and some serum biochemical indicators (insulin, fasting blood glucose [FBG], TC, TG, LDL, TNF-α, cytokine interleukin-6 [IL-6], etc.), but not the content of HDL-C in adolescents with obesity [36, 37]. Moderate- and low-intensity exercise combined with adequate protein and low-fat diet can significantly improve lipid metabolism and decrease fasting insulin (FINS) level [38]. It also can increase the sensitivity of tissue cells to insulin [39], decrease the serum levels of insulin-like growth factor binding protein 3 (IGFBP-3), increase the activity of insulin-like growth factor 1 (IGF-1) [36], relieve the degree of fatty liver, and improve the liver function in adolescents with obesity [39]. Further studies have found that ECWD intervention can significantly decrease the content of protein carbonyl and total thiol (Total-SH) and increase the activities of superoxide dismutase (SOD) and glutathion peroxidase (GPx), which can enhance the ability of antioxidant, eliminate the unnecessary free radicals, and reduce the harm of free radicals to the body [23]. Mandy et al. [14] found that ECWD intervention can significantly improve the levels of HDL-C, FBG, and FINS and can effectively reduce the metabolic risk in adolescents with obesity in a short term.

Although there have been some studies to investigate the effects of ECWD intervention on body composition and serum biochemical indicators in adolescents with obesity, there are still some limitations. Firstly, although there have been some studies comparing the effects of ECWD, exercise alone, and diet alone interventions on adolescents with obesity [40], [41], [42], a systematic review of these studies is lacking. Secondly, obesity may lead to the development of metabolic and cardiovascular diseases in adolescents, which can have a negative impact on their physical and mental health [43]. To address the problem of adolescents with obesity, it is important to assess more comprehensive and accurate obesity-related body metrics (e.g. BMI, waist circumference, TC, TG, FBG etc.). Therefore, the aim of this review is to systematically assess the effects of ECWD, exercise alone, diet alone, and no intervention on body composition and serum biochemical markers in adolescents with obesity.

Methods

Agreement registration

We conducted a systematic review and meta-analysis according to Cochrane Collaboration’s recommendations and guidelines and the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) [44]. The research has been registered in PROSPERO and will be continuously updated (Protocol number: CRD42021297237).

Inclusion and exclusion criteria

Studies were included if they (a) were measured BMI ≥28 kg/m2 (Asians) [45] or BMI ≥95th percentiles (non-Asians) [46]; (b) had subjects aged between 10 and 19 years [47]; (c) had no history of endocrine and metabolic diseases, heart disease, hematologic disease, cancer, neurasthenia, recent infection, or surgery and did not take any medication prior to the trial; (d) were subjected to randomized controlled trial with study duration of at least one month; and (e) were received face to face supervised in ECWD group, exercise alone group, and diet alone group.

Studies were excluded if they (a) were nonrandomized controlled trial; (b) were not received face-to-face supervision in intervention process; (c) were adolescents with nonobesity in control group participants; (d) were also received other interventions (such as psychological counseling, nutrition courses, etc.); and (e) had the history of heart disease, asthma, cancer, or recent infection or surgery.

Data sources and retrieval strategy

Two searchers (L. Y. Z and X. S. D) independently searched in eight databases: PubMed, Web of Science, Ovid, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang data, VIP database, and SinoMed. The types of studies included academic journals, dissertations, and conferences, covering the period from 1 January 1936 to 5 January 2021. Boolean operators were used between the search terms. There was no language restriction. The search strategy for this article is attached as Appendix A.

Study selection

Two researchers (L. Y. Z and X. S. D) extracted their searched articles and imported them into Endnote X9 to remove duplicate articles. First, studies were initially screened on the basis of title and abstract, and then screened again on the basis of body text. When there was disagreement on the inclusion of a study, a third researcher (YG) made the decision to include the article.

Data extraction

The third researcher (YG) extracted all the information of the included studies, including title, country, name of the first author, year of publication, sample size (number of participants in experimental and control groups), sample size, sex, type of intervention in experimental and control groups, and pre and postchange values (mean and standard deviation) of the study indicators. Body composition indexes included BMI, body fat rate, lean body weight, WHR, which can be measured directly, and subcutaneous fat (fat thickness of back, fat thickness of upper arm, and fat thickness of abdomen), which can be measured indirectly. Waist circumference, hip circumference, upper arm circumference, chest circumference, and thigh circumference had also been added. Serum biochemical markers included TG, TC, LDL, HDL, FBG, FINS, adiponectin, leptin, TNF-α, IL-6, C-reactive protein (CRP), chemokines, SOD, GPx, protein carbonyl, total thiol (Total-SH), etc.

Risk of bias assessment

According to the bias risk assessment tool in Cochrane Collaboration, two researchers used Review Manager 5.4.1 software to assess rigorously the seven aspects of “the method of random sequence generation,” “whether the person making the allocation strictly applied the outcome assignment of random numbers,” “whether participants and trial staff were blinded,” “whether outcome assessors were blinded,” “whether outcome data were complete,” “whether positive results were selectively reported in the study,” and “whether there were other factors that could cause bias.”

Statistical analysis

Review Manager 5.4.1 and Stata MP 17.0 were used for statistical analysis. Because the articles had the same continuous outcome variable and the same unit of measure, the mean difference (MD) or standardized mean difference (SMD) with 95% confidence interval (95% CI) was used to combine the effect sizes to calculate the weighted mean difference. When the mean and standard deviations of the studied indicators were not published, they were estimated from pre- and postintervention values according to the Cochrane Handbook for Systematic Reviews of Interventions [48]. Because of the different study designs and study populations, the Cochran’s Q test and I2 statistic were used to assess statistical heterogeneity. I2 represents the ratio of the true variance of the observed effects to the total variance. If I2 is close to zero, then most of the dispersion in the forest plot will disappear if we can somehow eliminate the sampling error. Conversely, if I2 is close to one, most of the observed dispersion will be retained [49]. If I2>50%, it indicated that the heterogeneity is significant, so chose the random effect model. The overall effect was significant when p<0.05 [50]. Because the aim of this study was to investigate the effect of intervention type on body composition and serum biochemical markers in adolescents with obesity, we conducted subgroup analysis and sensitivity analysis according to intervention types (ECWD, exercise alone, diet alone, and no intervention) to evaluate the more effective intervention type and explore the causes of heterogeneity. By making funnel plot and conducting Egger’s test, the possible publication bias was evaluated, and then a meta-regression of variables with publication bias was then run through Stata MP 17.0 to examine which variables had an effect on the bias. If the p>0.05, the variable was not considered to be the cause of heterogeneity.

Results

Study selection

A total of 50,155 articles were found by literature search according to search terms. Finally, 15 studies were included after duplicates and articles that did not meet the inclusion criteria were removed. Among them, 7 studies were in English [51], [52], [53], [54], [55], [56], [57] and 8 studies were in Chinese [23, 58], [59], [60], [61], [62], [63], [64]. Six studies [52, 57, 59], [60], [61], [62] compared ECWD with exercise alone, 8 studies [52, 55, 57], [58], [59], [60, 63, 64] compared ECWD with dietary alone, and 10 studies [23, 51], [52], [53], [54, 56, 58], [59], [60], [61] compared ECWD with no intervention (some articles included exercise alone, dietary alone, and/or no intervention as control groups). A flowchart of the study selection process is shown in Figure 1.

Figure 1: Flow diagram of study selection and identification.
Figure 1:

Flow diagram of study selection and identification.

Study characteristics

A total of 15 studies met the inclusion criteria. Descriptive information of the included articles is summarized in Tables 1 and 2. Eleven of the studies were in China [23, 53], [54], [55, 58], [59], [60], [61], [62], [63], [64], two in France [52, 57], one in Brazil [56], and one in Tunisia [51]. A total of 307 adolescents with obesity, aged 10–20 years, were enrolled in all the studies, and BMI criteria for inclusion were BMI ≥28 kg/m2 or BMI ≥95th percentiles. All the studies were randomized controlled trials. ECWD intervention was used in the experimental group, and exercise alone, dietary alone, or no intervention were used in the control group. In the dietary intervention, most of the studies (n=10) [23, 51], [52], [53], [54], [55, 57, 59, 61, 62] first calculated the actual total energy requirements of the subjects per day, specified the proportions of protein, fat, and carbohydrate intake (n=11) [23, 51], [52], [53], [54], [55], [56], [57], [58, 61, 62], and proposed the proportions of calories to be served at three meals per day (n=6) [23, 53, 54, 58, 61, 62]. In 3 of the studies [59, 60, 62], specific diets for each day were provided. Training supervision by a teacher or coach was explicitly mentioned in 9 of the studies [51], [52], [53], [54], [55, 57, 59], [60], [61]. Exercise intensity was limited according to target heart rate or maximal heart rate. The main types of exercise were aerobic exercise (n=9) [51], [52], [53, 55, 57, 58], [59], [60], [61] and aerobic plus resistance training (n=6) [23, 54, 56, 62], [63], [64]. All the studies included at least 3 h of exercise per week. The duration of the intervention was from 4 weeks to 1 year. All the studies were conducted under supervised conditions. Most of the studies showed that ECWD intervention had a better effect than other interventions on body composition and serum biochemical markers in adolescents with obesity.

Table 1:

Study characteristics of included trials, structured by year of publication.

Participants
Source (country/setting) Sample size (intervention/control) Age, years (sex) Selection criteria Intervention duration Outcomes indicators
Dong Guijun [61], (China) DE (21) ± E (16) ± B (10) 12.19 ± 0.4 BMI ＞28 kg/m2 6 months Weight, BMI, TC, TG, HDL, LDL
M. Elloumi et al. [57], (France) DE (7) ± D (7) ± E (7) 13.2 ± 0.9 (F + M) BMI ＞97th percentiles 2 months Body mass, BMI, fat mass, waist, hip, waist/hip ratio, insulin, HOMA-IR
Omar Ben Ounis et al. [51], (Tunisia) DE (14) ± B (14) 13.1 ± 0.8 (F + M) BMI ＞97th percentiles 2 months Weight, BMI, TNF-α, IL-6, leptin, CRP, IGF-1, IGFBP-3
Mohamed Elloumi et al. [52], (France) DE (7) ± B (8) 13.1 ± 1.0 (M) BMI ＞97th percentiles 2 months Weight, BMI, fat mass, fat free mass
Xing Liangmei et al. [59], (China) DE (12) ± B (12) 13–14 (F + M) BMI ≥28 kg/m2 6 months BMI, waist, thigh, biceps circumference, skinfold thickness (back, upper arm, abdomen), TC, TG, HDL, LDL
Li Mingwei et al. [58], (China) DE (24) ± B (17) 13.9 ± 0.4 (F + M) BMI: 27.73 ± 3.6 kg/m2 3 months BMI, TC, TG
Li Ting et al. [63], (China) DE (25) ± D (25) 16.5 ± 0.3 (F + M) BMI: 31.1 ± 2.4 kg/m2 8 weeks Weight, BMI, BFR, TC, TG, HDL-C, FPG
N. J. Brandão Albuquerque Filho [56], (Brazil) DE (15) ± B (12) 13.4 ± 1.3 (M) BMI ＞97th percentiles 8 weeks Weight, BMI, waist, BFR, GL, TC, TG, HDL-C, LDL-C, hs-CRP
12.9 ± 1.4 (F)
Ning Xinhui [60], (China) DE (14) ± B (14) 13.12 ± 1.32 (F + M) BMI: 30.63 ± 1.39 kg/m2 6 months BMI, waist, thigh, biceps circumference, thickness (back, upper arm, abdomen), TC, TG, HDL, LDL
Li Chunyan et al. [23], (China) DE (20) ± B (5) 15.50 ± 2.07 (M) BMI ≥28 kg/m2 4 weeks Weight, BMI, BFR, LBM, waist, hip, waist/hip ratio, thigh, calf, fat mass, biceps circumference, forearm circumference, torso and limbs fat, MDA, PC, SOD, GPx, T-SH
Jin Yuan [62], (China) DE (28) ± E (36) 19.06 ± 0.57 (F + M) BMI ≥28 kg/m2 6 weeks Weight, BMI, BFR, waist, hip, waist/hip ratio, chest circumference, GL, TC, TG, HDL, LDL
Chun Xie et al. [53], (China) DE (30) ± B (28) 15.07 ± 0.83 (F + M) BMI ＞28 kg/m2 4 weeks Weight, BMI
Min Liu, Lin, and Wang [55], (China) DE (30) ± D (20) 14.7 ± 0.8 (F) BMI: 33.5 ± 3.6 kg/m2 4 weeks Weight, BMI, waist, trunk fat, FPG, FINS, TC, TG, HDL, LDL, HOMA-IR, TNF-α, IL-6, leptin, CRP, adiponectin, chemerin
Yang Dongqi [64], (China) DE (34) ± D (34) 16.52 ± 0.14 (F + M) BMI: 29.25 ± 2.01 kg/m2 1 year BMI, waist/hip ratio
Xiang Mingqiang et al. [54], (China) DE (18) ± B (18) 12.50 ± 1.92 (F + M) BMI ≥95th percentile 6 weeks Weight, BMI

  1. BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); M, male; F, female; DE, diet and exercise; B, blank control group; TC, total cholesterol; TG, triglyceride; HDL, high-density lipoprotein; LDL, low-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; CRP, C-reactive protein; TNF-α, tumor necrosis factor-α; IL-6, interleukin-6; BFR, body fat rate; FPG, fasting plasma glucose; FINS, fasting insulin; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; hs-CRP, high sensitive c-reactive protein; GL, glucose; LBM, lean body mass; MDA, malondialdehyde; PC, polycarbonate; SOD, superoxide dismutase; GPx, glutathione peroxidase; T-SH, total sulfhydryl.

Table 2:

Interventions and differences in weight loss between groups.

Intervention
Source (country/setting) Exercise Diet Significance weight loss difference between groups
Dong Guijun [61], (China) Intensity: THR = MHR × (50–70%) 3–4 times/week, 70–90 min each time, exercise prescription was carried out under the guidance of the coach Mainly to crude fiber food, avoid high energy, high fat food, staple food control but not control, three meals a day according to 2/5, 2/5, 1/5 supply, two fruits in the middle of the meal, dinner from sleep more than 4 h Yes (D + E > E)
M Elloumi et al. [57], (France) 500 kcal/day below the initial dietary records, and comprised 15% proteins, 55% carbohydrates, and 30% lipids 4 days/week (90 min/day) and during 2 months at a heart rate (HR) corresponding to lipoxmax. Exercises were supervised by PE teachers and included a warm-up, running, jumping, and ball games Yes (D + E > D > E)
Omar Ben Ounis et al. [51], (Tunisia) All exercise training was supervised, occurred four times/week (90 min/day) for 8 weeks, and consisted of warming up, running, jumping, and playing with a balloon The diet program was set at −500 kcal/day below the initial dietary records. The foods were composed of 15% proteins, 55% carbohydrates, and 30% lipids. Carbohydrates were primarily in the form of high-fiber whole grains (65 servings/day), vegetables (64 servings/day), and fruits (63 servings/day). Protein was primarily derived from plant sources, with nonfat dairy (2 servings/day) and fish and fowl served in 100-g portions (4 days/week) and in soups or casseroles (2 days/week). The diet contained 100 mg of cholesterol, and caffeinated beverages were not allowed. Sodium intake was limited to 1,600 mg/day Yes (D + E > B)
Mohamed Elloumi et al. [52], (France) 90-min/week, during the 2-month period; the training was performed in a gymnasium and supervised by a teacher of physical education The diet was set at −500 kcal/day below the initial dietary records and comprised 15% proteins, 55% carbohydrates, and 30% lipids Yes (D + E > D > E > B)
Xing Liangmei et al. [59], (China) Aerobic exercise, maximum oxygen uptake 60–70%, 3 times/week, 15 min of uniform running, 35 min interval running; 3 sets of sit-ups and 3 sets of burpees each day, 30 sets of sit-ups and 10 sets of burpees. Training is arranged by teachers Breakfast: 1 egg, steamed bread or vegetable bag not more than 2, porridge 1 bowl, 1 vegetable; lunch: rice 1 bowl, fish (except squid and hairtail) or shrimp not more than 100 g, high fiber vegetables 1 portion, do not drink soup; dinner: steamed bread not more than 2, 1 bowl of porridge, 1 vegetable; 250 mL milk before bed. Drink no less than 2,000 mL of water a day, do not drink sugary drinks, do not eat dessert and fried food; girls may have spareribs once a week for lunch, not exceeding 150 g. All students eat at home Yes (D + E > D = E = B)
Li Mingwei et al. [58], (China) Do aerobic exercise 3–4 times/week for 1 h after class Protein, fat, and carbohydrates account for 25, 30, and 45% of total energy, respectively. After 4 weeks, protein, fat, and carbohydrate intake accounted for 20–25 percent, 25–30 percent, and 45–55 percent of total energy, respectively. The energy of breakfast, lunch, and dinner accounted for 25, 40, and 35% of the total energy, respectively Yes (D + E = D > B)
Li Ting et al. [63], (China) Moderate- to low-intensity aerobic exercise. Warm up with active stretching, starting with strength training for a minimum of 40 min, followed by aerobic exercise for 50 min of alternating running. The exercise forms and items were chosen by the subjects themselves Control the proportion of carbohydrate, fat, and protein supply, less oil and salt, less carbohydrate, and reduce the intake of high calorie foods Yes (D + E > D)
N. J. Brandão Albuquerque Filho [56], (Brazil) Endurance training and resistance training. The 10 min warm up with 23 min of endurance training and about 30 min of resistance exercise, the concurrent exercise was not lasting more than 65 min and less than 63 min The energetic distribution of macronutrients were 15–20% protein, 50–55% carbohydrates, and 30% fat and were individually adapted to reduce the energy consumption by approximately 250 kcal Yes (D + E > B)
Ning Xinhui [60], (China) Exercise 3 times/week, max oxygen uptake 60–70% HR max, 15 min jogging each time, 35 min interval running; do 30 × 3 sets of sit-ups and 10 × 3 sets of push-ups every day Breakfast: 2 steamed buns, 1 bowl of porridge, 1 portion of vegetable, 1 egg; lunch: 1 bowl of rice, 100 g of fish or shrimp or lean meat, 1 portion of vegetables; dinner: steamed bread up to 2, dilute rice 1, vegetable 1; 250 mL milk before bed; avoid sugary drinks and fried foods Yes (D + E > B)
Li Chunyan et al. [23], (China) Sports forms include badminton, basketball, table tennis, and so on; the movement intensity control was 60–70% HR max, the movement frequency was 3 times/day, 6 days/week, and the duration was 4 weeks Carbohydrate complexes account for 55–65%, lipids for 20–30%, and proteins for 10–15%. The ratio of heat for three meals a day is about 4:4:2 Yes (D + E > B)
Jin Yuan [62], (China) The main way of exercise is jogging and brisk walking. Exercise for 90 or 120 min three times a week, with 15 min of pre-workout and 15 min of post-workout stretching. The whole exercise process is guided by professors with rich teaching experience and supervised by medical staff Limit dietary calories, pay attention to nutrition collocation, drink more water, and the proportion of protein, fat, and carbohydrate food is 5:3:12. The ratio of calories for three meals a day is about 3:4:3 Yes (D + E > E)
Chun Xie et al. [53], (China) The exercise protocol comprised two sessions per day, 6 days/week for four consecutive weeks. Each session lasted 120 min and comprised three stages of (a) 18 min warm-up; (b) 84 min low- to moderate-intensity exercise with a target heart rate zone within 110–130 bpm; and (c) 18 min cool-down. A variety of exercise modes were provided (e.g., treadmill walking, swimming, badminton, and basketball). Two coaches oversee the process The percentage values for the intake of high quality proteins, fats, and carbohydrates set as 25–35%, 10–15%, and 55–65%, respectively. The breakfast, lunch, and dinner calorie ratio for the three daily meals was approximately 3:4:3. There are also health education classes Yes (D + E > B)
Min Liu, Lin, and Wang [55], (China) Aerobic exercise (such as brisk walking, swimming, jogging, table tennis, and badminton), lasting for 2 h with 5 min rest per 30 min, twice a day, 6 days/week. The exercise intensity was gradually increased from low (heart rate at the 1st week: 100–120 beats/min) to moderate (heart rate during the 2nd–4th weeks: 120–140 beats/min) level in accordance with the heart rates immediately postexercise in these females. The course is guided by a fitness instructor and a registered dietitian Three meals were provided with a total daily energy of 1,400 or 1,600 kcal (different in portion size, and carbohydrate, protein and fat accounting for 65, 15, and 20% of the total energy, respectively). The subjects of the dieting group were on a mild diet by eating the same three meals delivered to their home with no extra food intake Yes (D + E > D)
Yang Dongqi [64], (China) The training methods include strength training (20 min/time), flexibility training (10 parts per time, 1.5 min/part), basketball dribble ball return running (2 times/group, 5 times/time), and aerobic jogging (20 min/time). Exercise 3 times/week, once every other day, pay attention to warm up before exercise and pay attention to relax after training. A total of 48 training sessions were conducted for 16 weeks Control your dietary intake Yes (D + E > D)
Xiang Mingqiang et al. [54], (China) 5 h/day, 6 days/week for 6 weeks. The exercise primarily consisted of typical aerobic training, ball games, outdoor training, yoga, and resistance training. Resistance training was performed at 40–50% maximal strength for three to four sets of 12–15 maximal repetitions. The rest period between sets and training was 60–90 s. The energy expenditure of participants ranged from 1,500 to 2,500 kcal/day during the exercise program. All the exercise programs were supervised by qualified trainers Diet was nutritionally complete (20% protein, 20% fat, and 60% carbohydrate). Calorie intake ranged from 1,300 to 2,000 kcal/day based on body weight. Energy was distributed as approximately 30% at breakfast, 40% at lunch, and 30% at dinner Yes (D + E > B)

  1. D, diet only; E, exercise only; D + E, exercise combined with diet intervention; B, blank group; THR, target heart rate; MHR, maximal heart rate; D + E > D (or D + E > E or D + E > B) indicates that the exercise combined with diet intervention group had a greater reduction than the diet-only intervention group (or exercise-only intervention group or blank group) (p<0.05); D + E, D indicates that there was no significant difference in weight between the exercise combined with diet intervention group and the diet-only intervention group.

Risk of study bias

Bias risk assessment is shown in Figure 2. The overall quality of the included studies was average. The generation of the random sequence was not reported in most studies (n=13) [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62, 64]. The allocation was hidden as “high risk” in 2 studies [23, 53], and the dropout rate was not clearly reported in 6 studies [23, 51, 60, 61, 63, 64]. The presence of bias in blinding to trial staff and reviewers was not clearly reported in 7 [53, 54, 58, 61], [62], [63], [64] and 4 studies [58, 62], [63], [64], respectively. Almost all the studies (n=14) [23, 51, 52, 54], [55], [56], [57], [58], [59], [60], [61], [62], [63], [64] did not have sufficient information to judge whether there are other risks of bias.

Figure 2: Assessment of risk of bias. (A) Risk of bias graph; (B) risk of bias summary.
Figure 2:

Assessment of risk of bias.

(A) Risk of bias graph; (B) risk of bias summary.

Study results

Effect on body composition

Of the body composition indicators, BMI, body fat mass and subcutaneous fat (fat thickness of back, fat thickness of upper arm, and fat thickness of abdomen), as well as waist circumference, hip circumference, upper arm circumference, and thigh circumference were studied in two or more articles, so we focus on these indicators. Fourteen of the 15 studies [23, 51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61, 63, 64] showed that ECWD intervention reduced BMI more significantly than diet alone (I2=5%; p<0.00001), exercise alone (I2=0%; p<0.00001), and no intervention (I2=51%; p<0.00001) (Figure 3). The effects of different interventions on fat thickness of back, abdomen, and upper arm were similar to those of BMI. The effects of ECWD on body fat mass (I2=0%; p=0.005) (Figure 4) and thigh circumference (I2=0%; p<0.0001) were more significant than that of exercise alone, but not as significant as diet alone. The effects of ECWD on waist circumference (I2=0%; p=0.0005) (Figure 5), WHR (I2=0%; p<0.00001), and upper arm circumference (I2=0%; p<0.00001) were more significant than that of diet alone, but not as significant as that of exercise alone. Studies on hip circumference showed that ECWD, exercise alone, and diet alone could reduce hip circumference, but the effects of the three interventions were not significant. Two of the studies [23, 62] were aerobic combined resistance interventions and one was an aerobic training intervention [57], so the lack of effect may be related to the type of exercise.

Figure 3: Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in body mass index.
Figure 3:

Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in body mass index.

Figure 4: Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in body fat mass.
Figure 4:

Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in body fat mass.

Figure 5: Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in waistline.
Figure 5:

Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in waistline.

Effect on serum biochemical markers

The results showed that ECWD, exercise alone, and diet alone could reduce triglyceride, total cholesterol, and LDL in adolescents with obesity. In subgroup analysis, we found that ECWD and exercise alone had no significant effects on triglyceride (I2=36%; p=0.33) (Figure 6), total cholesterol (I2=0%; p=0.54), and LDL (I2=0%; p=0.82) in adolescents with obesity but were more significant than that of diet alone and no intervention. The changes of HDL (I2=0%; p=0.95) in ECWD, diet alone, exercise alone, and no intervention were not significant (Figure 7), indicating that the effects of exercise and/or dietary intervention on HDL were small. The effects of ECWD on fasting plasma glucose were not consistent. With the further study of adolescents with obesity, more indicators will be explored. Few studies had shown that ECWD can reduce plasma insulin, HOMA-IR, IGF-1, IGFBP-3, lipocalin, leptin, cytokines (TNF-α, IL-6, and IL-1β), apolipoprotein B (ApoB), inflammatory markers (C-reactive protein, hs-CRP, and chemokines), protein carbonyl, and Total-SH, increases apolipoprotein AI (ApoAI), and significantly enhances the activity of enzymes (SOD and GPx), but had no significant effect on high sensitive C-reactive protein (hs-CRP) and malondialdehyde (MDA).

Figure 6: Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in triglyceride.
Figure 6:

Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in triglyceride.

Figure 7: Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in high-density lipoprotein.
Figure 7:

Meta-analysis of comparing exercise combined with diet intervention with exercise intervention alone, diet intervention alone, and no intervention using change in high-density lipoprotein.

Sensitivity analysis

Meta-analysis showed that there was heterogeneity in lean body mass (I2=0%, p=0.83), hip circumference (I2=0%, p=0.59), and HDL (I2=0%, p=0.89), and sensitivity analysis was performed to produce funnel plots (Figure 8). Egger’s test showed that the p values for both lean body mass and hip circumference were greater than 0.05 and were not significant, indicating no publication bias, while p=0.006<0.05 for HDL, indicating publication bias. Meta-regression showed that the control group was not the cause of publication bias, which may be due to clinical heterogeneity or small number of included studies.

Figure 8: Funnel charts of exercise combined with diet intervention and other intervention methods in fat-free weight, hip circumference, and high-density lipoprotein.
Figure 8:

Funnel charts of exercise combined with diet intervention and other intervention methods in fat-free weight, hip circumference, and high-density lipoprotein.

Discussion

This study compared the effects of ECWD, exercise alone, diet alone and no intervention on body weight, body composition, and serum biochemical indices in adolescents with obesity. It was found that ECWD was most effective in reducing BMI, fat thickness, and other body components of adolescents with obesity and could promote the decrease of some serum biochemical indices such as IGF-1, TNF-α, and IL-6, decrease protein carbonyl and Total-SH, and increase the activities of SOD and GPx. Abnormally high TC, TG, and LDL and abnormally low HDL are important signs of metabolic disorders. ECWD and exercise intervention alone could reduce TC, TG, and LDL, and therefore, ECWD can improve metabolic disorders in adolescents with obesity.

With regard to body composition in adolescents with obesity, BMI is an effective index to measure overall obesity and predict lipid metabolism disorders and hypertension [65, 66]. The lowest mortality was found in BMI values between 22.5 and 25 kg/m2. Every 1 kg/m2 increase in BMI was associated with an increased risk of pulmonary embolism, coronary heart disease, peripheral artery disease, atrial fibrillation, hypertension, deep vein thrombosis, heart failure, and aortic stenosis, and with an increased risk of death from cardiovascular disease and coronary heart disease; every 5 kg/m2 increase in BMI was associated with an increased risk of coronary heart disease, peripheral artery disease, hypertension and heart failure, and the risk of developing cardiovascular disease increases from 10% for hemorrhagic stroke to 49% for hypertension [67]. Our subgroup analysis showed that ECWD was most effective in reducing BMI in adolescents with obesity. Both ECWD and exercise alone could reduce body fat in adolescents with obesity. Some studies have suggested that ECWD intervention could reduce lean body mass in adolescents with obesity [23], and aerobic combined with resistance training could increase lean body mass in adolescents with obesity [68]. However, this study found that none of the three intervention methods could effectively improve lean body mass in adolescents with obesity, which is inconsistent with previous studies. The interventions in the trial group in the two studies on lean body mass were aerobic and aerobic combined with resistance exercise, so this difference may be caused by the type of exercise. Waist circumference is not only an index to measure abdominal obesity but also an effective index to predict hypertension [66] and lipid metabolism disorders [65]. Stratified by BMI classification, the abdominal visceral fat content of adolescents with large waist circumference was 2∼3 times higher than that of adolescents with normal weight [69]. Adolescents with large waist circumference were at a significantly higher risk of hypertension, vascular morphologic changes, early myocardial and coronary artery lesions [70]. The mortality rate of central obesity with high WHR was 25–50% higher than that of normal persons [71]. WHR has positive effects on the early prevention and diagnosis of obesity, diabetes, and cardiovascular diseases [72, 73]. Our results showed that ECWD and exercise alone could effectively reduce WHR in adolescents with obesity, which is consistent with previous studies [74, 75].

As for the serum biochemical markers in adolescents with obesity, previous studies proposed that adolescents with obesity have different degrees of dyslipidemia, the main manifestations of which are TC, TG, and LDL-C increased, HDL-C decreased [76]. The increase of blood lipids such as total cholesterol, triglycerides, and LDL-C can affect the platelets and endothelial cells in vivo and increase blood viscosity and blood pressure [77]. HDL-C can remove excess cholesterol and LDL-C from the blood and cells and prevent atherosclerosis [22]. TG/HDL-C alone or TG/HDL-C combined with HOMA-IR may be a good predictor of metabolic syndrome (MS) and coronary heart disease [78, 79]. Previous studies have shown that exercise can reduce total cholesterol, triglycerides, and LDL-C and reduce cholesterol deposition in the blood vessel wall [22]. ECWD intervention can increase HDL content in adolescents with obesity, but it is still lower than that in adolescents with normal weight. In this meta-analysis, ECWD intervention can reduce total cholesterol, triglycerides, and LDL content in adolescents with obesity, but there is no significant difference between ECWD and exercise alone. In the subgroup analysis of HDL, ECWD, exercise alone, diet alone, and no intervention had no significant difference, which is inconsistent with previous studies, possibly due to clinical heterogeneity or small number of included studies. Therefore, further studies on the effect of ECWD on HDL content in adolescents with obesity are needed. Insulin is the only hormone in the body that lowers blood sugar. Insulin deficiency can cause fat metabolism disorders, over time will cause arteriosclerosis, and then lead to cardiovascular and cerebrovascular diseases. IGF-1 has the similar effect of lowering blood sugar and blood lipids as insulin. Current studies have found that the more disorders of glucose and lipids metabolism in obese subjects, the lower the level and activity of serum IGF-1 [80, 81]. Regular exercise can increase serum IGF-1 concentration [82]. But some studies have found that high intensity training or long-term endurance activities can cause a long-term decline in IGF-1 level [83, 84], that is, when the body’s energy expenditure exceeds energy intake, the free IGF-1 level will decline [85]. Exercise alone can effectively reduce blood sugar and insulin levels and reduce the risk of diabetes and cardiovascular disease [86]. In this meta-analysis, ECWD intervention can significantly reduce insulin, IGF-1, and IGFBP-3 levels, which is inconsistent with some previous studies, possibly due to insufficient exercise or insufficient time of intervention. Although only a few articles have studied serum biochemical markers such as TNF-α, IL-6, leptin, and adiponectin, these markers are closely related to obesity. The levels of TNF-α and IL-6 in adolescents with obesity and overweight are significantly higher than those in adolescents with normal weight. Some studies have shown that ECWD intervention can significantly reduce TNF-α and IL-6 levels [51, 55]. Adiponectin has anti-inflammatory, antidiabetic, antiatherosclerotic, and improved insulin resistance effects [87]. The serum adiponectin level in adolescents with obesity is lower than that in adolescents with normal weight. Adiponectin level is negatively correlated with BMI, WHR, TC, and LDL and positively correlated with HDL and insulin sensitivity [88], [89], [90], [91], [92]. Several meta-analyses show that exercise can increase serum adiponectin [93], [94], [95], [96], [97], but some studies have found that exercise has no significant effect on adiponectin, which may be that the magnitude of body fat reduction is insufficient to increase the level of adiponectin released by adipose tissue [32, 98, 99]. In this meta-analysis, ECWD intervention can increase adiponectin level, and the effect is better than diet alone. Combined with previous studies, ECWD intervention may be more effective than diet intervention or exercise intervention alone in improving adiponectin level in adolescents with obesity. In the future, we can further explore the effects of different intervention methods on adiponectin. In addition, adipocyte secretes leptin into the bloodstream to regulate body weight through feedback system. Its main function is to accelerate biological metabolism, suppress appetite, and control body weight [100]. In this meta-analysis, ECWD intervention and diet alone can decrease body leptin, but ECWD intervention has a better effect. Serum chemokines are positively correlated with changes of body fat, trunk fat, waist circumference, FPG, FINS, TNF-α, and IL-6. Early atherosclerotic changes and cardiac autonomic neuropathy in adolescents with type 1 diabetes may be related to high serum chemokines [101]. The decrease of chemokines caused by exercise is related to the changes of leptin and adiponectin/leptin ratio [55]. Only one of the included studies in this meta-analysis measured chemokines, and ECWD intervention can effectively decrease serum chemokines level in adolescents with obesity [55]. Serum C-reactive protein (CRP) and hs-CRP are significantly increased in acute inflammation, trauma, and infarction [102]. Hs-CRP is more sensitive than C-reactive protein. Most studies have shown that serum CRP is increased in adolescents with obesity [103, 104], and the risk of coronary heart disease increases by 29% for each unit increase of CRP [105]. However, some studies have shown that there is no significant difference in serum CRP between adolescents with obesity and normal controls [106]. Serum CRP and hs-CRP are positively correlated with anthropometric parameters BMI, body fat percentage, and waist circumference in adolescents with obesity [107, 108]. Low-intensity or high-intensity aerobic exercise for a long time can effectively decrease serum hs-CRP level in adolescents with obesity [86], which may be the result of the additive effect of exercise and weight loss. Previous studies have shown that exercise can increase the ability to mobilize and oxidize fat, decrease fat content, and thus decrease hs-CRP level, regardless of weight change [109]. This meta-analysis found that ECWD intervention can decrease serum CRP and hs-CRP level. However, because of the small number of studies, it is impossible to compare the differences of ECWD intervention, exercise alone, and diet alone. Further studies on CRP and hs-CRP should be conducted in the future. No studies included in this meta-analysis involved resistin, but some studies reported a significant association between resistin level, obesity, and insulin resistance [110]. It is hoped that more studies on resistin will be conducted in the future.

This paper has its limitations. First, this paper is limited to published literature, and publication bias cannot be excluded. Second, there are potential heterogeneity in the quantity and quality of dietary intake, exercise duration and intensity, and individual differences among participants. Moreover, the duration of intervention is short and inconsistent. Finally, the sample size of this study is small and most studies did not indicate follow-up. Despite these limitations, this meta-analysis and systematic review were more restrictive in terms of inclusion criteria, and subgroup analyses were conducted for all body composition and serum biochemical markers, and descriptive analyses were conducted for those unable to perform subgroup analyses. Finally, sensitivity analyses and meta-regressions were conducted for the markers with heterogeneity to provide a more comprehensive and accurate assessment.

Conclusions

ECWD intervention can effectively decrease body composition, reduce body weight and body fat, and enhance antioxidant capacity in adolescents with obesity. In serum biochemical markers, ECWD intervention has the same effect as exercise alone and is better than diet alone. Therefore, for adolescents with obesity, we should not only encourage them to exercise, but also limit and improve their diet.

Corresponding author: Yan Gao, Associate professor, School of Physical Education, Shandong University, Jingshi Road, Jinan, 250061, Shandong, P.R. China, Phone: +86 18663709793, E-mail:

Funding source: The National Social Science Foundation of China

Award Identifier / Grant number: 21BTY054

Funding source: Future Project for Youth Scholar of Shandong University

Award Identifier / Grant number: 2017WLJH17

Funding source: China Postdoctoral Science Foundation

Award Identifier / Grant number: 2017M62216

  1. Research funding: This research was funded by the National Social Science Foundation of China (grant number: 21BTY054), China Postdoctoral Science Foundation (grant number: 2017M622169), and Future Project for Youth Scholar of Shandong University (grant number: 2017WLJH17). The content of the paper is solely the responsibility of the authors and does not necessarily represent the official views of the funders.

  2. Author contributions: Liangyu Zhao and Xiaosheng Dong conducted literature search, research selection, and quality evaluation. Yan Gao carried out data extraction and data processing. Liangyu Zhao drafted the manuscript, and Yan Gao revised it. All authors participated in the interpretation of the data. All authors have read and agreed to the published version of the manuscript.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Not applicable.

  5. Ethical approval: The local Institutional Review Board deemed the study exempt from review.

References

1. World Health Organization. Obesity and overweight; 2020. Available from: https://www.who.int/zh/news-room/fact-sheets/detail/obesity-and-overweight.Search in Google Scholar

2. Ezzati, M, Bentham, J, Cisneros, J. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2,416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet;2017;390:2627–42.10.1016/S0140-6736(17)32129-3Search in Google Scholar

3. Report on nutrition and chronic diseases of Chinese residents (2020). Acta Nutr Sin 2020;42:521.Search in Google Scholar

4. Bjerregaard, LG, Jensen, BW, Ängquist, L, Osler, M, Sørensen, TIA, Baker, JL. Change in overweight from childhood to early adulthood and risk of type 2 diabetes. N Engl J Med 2018;378:1302–12. https://doi.org/10.1056/nejmoa1713231.Search in Google Scholar

5. Chung, ST, Onuzuruike, AU, Magge, SN. Cardiometabolic risk in obese children. Ann N Y Acad Sci 2018;1411:166–83. https://doi.org/10.1111/nyas.13602.Search in Google Scholar

6. Juonala, M, Magnussen, CG, Berenson, GS, Venn, A, Burns, TL, Sabin, MA. Childhood adiposity, adult adiposity, and cardiovascular risk factors. N Engl J Med 2011;365:1876–85. https://doi.org/10.1056/nejmoa1010112.Search in Google Scholar

7. Freedman, DS, Mei, Z, Srinivasan, SR, Berenson, GS, Dietz, WH. Cardiovascular risk factors and excess adiposity among overweight children and adolescents: the Bogalusa heart study. J Pediatr 2007;150:12–7. https://doi.org/10.1016/j.jpeds.2006.08.042.Search in Google Scholar

8. Fangfang, C, Peiyu, Y, Jie, M, Hong, C. Epidemiological characteristics of cardiovascular metabolic risk factors among children and adolescents aged 6–17 years in 7 cities of China from 2013 to 2015. Chin J Prev Med 2018;52:1130–5.Search in Google Scholar

9. Whitlock, G, Lewington, S, Sherliker, P, Clarke, R, Emberson, J, Halsey, J, et al.. Body-mass index and cause-specific mortality in 900,000 adults: collaborative analyses of 57 prospective studies. Lancet 2009;373:1083–96. https://doi.org/10.1016/s0140-6736(09)60318-4.Search in Google Scholar

10. Hendren, NS, de Lemos, JA, Ayers, C, Das, SR, Rao, A, Carter, S, et al.. Association of body mass index and age with morbidity and mortality in patients hospitalized with COVID-19 results from the American heart association COVID-19 cardiovascular disease registry. Circulation 2021;143:135–44. https://doi.org/10.1161/circulationaha.120.051936.Search in Google Scholar

11. Piroth, L, Cottenet, J, Mariet, AS, Bonniaud, P, Blot, M, Tubert-Bitter, P, et al.. Comparison of the characteristics, morbidity, and mortality of COVID-19 and seasonal influenza: a nationwide, population-based retrospective cohort study. Lancet Respir Med 2021;9:251–9. https://doi.org/10.1016/s2213-2600(20)30527-0.Search in Google Scholar

12. Bharath, LP, Choi, WW, Cho, J, Skobodzinski, AA, Wong, A, Sweeney, TE, et al.. Combined resistance and aerobic exercise training reduces insulin resistance and central adiposity in adolescent girls who are obese: randomized clinical trial. Eur J Appl Physiol 2018;118:1653–60.10.1007/s00421-018-3898-8Search in Google Scholar PubMed

13. Hoare, JK, Jebeile, H, Garnett, SP, Lister, NB. Novel dietary interventions for adolescents with obesity: a narrative review. Pediatr Obes 2021;16:e12798.10.1111/ijpo.12798Search in Google Scholar PubMed

14. Ho, M, Garnett, SP, Baur, LA, Burrows, T, Stewart, L, Neve, M, et al.. Impact of dietary and exercise interventions on weight change and metabolic outcomes in obese children and adolescents. JAMA Pediatr 2013;167:759–68. https://doi.org/10.1001/jamapediatrics.2013.1453.Search in Google Scholar PubMed

15. Nguo, K, Bonham, M, Truby, H, Barber, E, Brown, J, Huggins, C. Effect of macronutrient composition on appetite hormone responses in adolescents with obesity. Nutrients 2019;11:340. https://doi.org/10.3390/nu11020340.Search in Google Scholar PubMed PubMed Central

16. Nguo, K, Huggins, CE, Truby, H, Brown, J, Bonham, MP. Effect of macronutrient composition on meal-induced thermogenesis in adolescents with obesity. Eur J Nutr 2019;58:2327–33. https://doi.org/10.1007/s00394-018-1783-1.Search in Google Scholar PubMed

17. Gow, ML, Ho, M, Burrows, TL, Baur, LA, Stewart, L, Hutchesson, MJ, et al.. Impact of dietary macronutrient distribution on BMI and cardiometabolic outcomes in overweight and obese children and adolescents: a systematic review. Nutr Rev 2014;72:453–70. https://doi.org/10.1111/nure.12111.Search in Google Scholar PubMed

18. Ho, M, Garnett, SP, Baur, L, Burrows, T, Stewart, L, Neve, M, et al.. Effectiveness of lifestyle interventions in child obesity: systematic review with meta-analysis. Pediatrics 2012;130:e1647–71. https://doi.org/10.1542/peds.2012-1176.Search in Google Scholar PubMed

19. Schwartz, C, King, NA, Perreira, B, Blundell, JE, Thivel, D. A systematic review and meta-analysis of energy and macronutrient intake responses to physical activity interventions in children and adolescents with obesity. Pediatr Obes 2017;12:179–94. https://doi.org/10.1111/ijpo.12124.Search in Google Scholar PubMed

20. Mirza, NM, Palmer, MG, Sinclair, KB, McCarter, R, He, J, Ebbeling, CB, et al.. Effects of a low glycemic load or a low-fat dietary intervention on body weight in obese Hispanic American children and adolescents: a randomized controlled trial. Am J Clin Nutr 2013;97:276–85. https://doi.org/10.3945/ajcn.112.042630.Search in Google Scholar PubMed PubMed Central

21. Truby, H, Baxter, K, Ware, RS, Jensen, DE, Cardinal, JW, Warren, JM, et al.. A randomized controlled trial of two different macronutrient profiles on weight, body composition and metabolic parameters in obese adolescents seeking weight loss. PLoS One 2016;11:e151787. https://doi.org/10.1371/journal.pone.0151787.Search in Google Scholar PubMed PubMed Central

22. Zhijian, W, Zhuying, W, Yan, S, Qing, L. Meta-analysis of the effect of exercise on obesity adolescents in China. J Shenyang Sport Univ 2017;36:67–75+81.Search in Google Scholar

23. Chunyan, L, Feihu, F, Xiaoling, X, Rui, L, Sujie, Z. Changes of body shape, body composition and oxidative stress induced by exercise diet intervention in male obese adolescents. J Wuhan Inst Phys Educ 2016;5:90–5.Search in Google Scholar

24. Lijun, C, Xing, W, Ru, W. Experimental study on the effect of aerobic exercise prescription on physical health of obese adolescents in dopa plateau and plain respectively. China Sport Sci Technol 2013;6:89–93.Search in Google Scholar

25. Foschini, D, Araujo, RC, Bacurau, RFP, De Piano, A, De Almeida, SS, Carnier, J, et al.. Treatment of obese adolescents: the influence of periodization models and ACE genotype. Obesity 2010;18:766–72. https://doi.org/10.1038/oby.2009.247.Search in Google Scholar PubMed

26. Rocchini, AP, Katch, V, Schork, A, Kelch, RP. Insulin and blood pressure during weight loss in obese adolescents. Hypertension 1987;10:267–73. https://doi.org/10.1161/01.hyp.10.3.267.Search in Google Scholar PubMed

27. Rocchini, AP, Katch, VL, Grekin, R, Moorehead, C, Anderson, J. Role for aldosterone in blood pressure regulation of obese adolescent. Am J Cardiol 1986;57:613–8. https://doi.org/10.1016/0002-9149(86)90845-3.Search in Google Scholar

28. Sigal, RJ, Alberga, AS, Goldfield, GS, Prud’homme, D, Hadjiyannakis, S, Gougeon, R, et al.. Effects of aerobic training, resistance training, or both on percentage body fat and cardiometabolic risk markers in obese adolescents the healthy eating aerobic and resistance training in youth randomized clinical trial. JAMA Pediatr 2014;168:1006–14. https://doi.org/10.1001/jamapediatrics.2014.1392.Search in Google Scholar PubMed

29. Lei, F. Effects of four-week exercise combined with dietary intervention on weight loss and local fat changes of obese adolescents. Shanghai: Shanghai University of Sport; 2015, vol 1.Search in Google Scholar

30. Li, D, Chen, P. The effects of different exercise modalities in the treatment of cardiometabolic risk factors in obese adolescents with sedentary behavior—a systematic review and meta-analysis of randomized controlled trials. Children 2021;8:1062. https://doi.org/10.3390/children8111062.Search in Google Scholar PubMed PubMed Central

31. Campos, RMD, Masquio, DCL, Corgosinho, FC, Sanches, PD, de Piano, A, Carnier, J, et al.. Homeostasis model assessment-adiponectin: the role of different types of physical exercise in obese adolescents. J Sports Med Phys Fit 2017;57:831–8.10.23736/S0022-4707.16.06235-6Search in Google Scholar

32. Lopes, WA, Leite, N, da Silva, LR, Brunelli, DT, Gaspari, AF, Radominski, RB, et al.. Effects of 12 weeks of combined training without caloric restriction on inflammatory markers in overweight girls. J Sports Sci 2016;34:1902–12. https://doi.org/10.1080/02640414.2016.1142107.Search in Google Scholar PubMed

33. Son, W, Sung, K, Bharath, LP, Choi, K, Park, S. Combined exercise training reduces blood pressure, arterial stiffness, and insulin resistance in obese prehypertensive adolescent girls. Clin Exp Hypertens 2017;39:546–52. https://doi.org/10.1080/10641963.2017.1288742.Search in Google Scholar PubMed

34. Kelley, GA, Kelley, KS, Pate, RR. Exercise and BMI in overweight and obese children and adolescents: a systematic review and trial sequential meta-analysis. BioMed Res Int 2015;2015:1–17. https://doi.org/10.1155/2015/704539.Search in Google Scholar PubMed PubMed Central

35. Stoner, L, Rowlands, D, Morrison, A, Credeur, D, Hamlin, M, Gaffney, K, et al.. Efficacy of exercise intervention for weight loss in overweight and obese adolescents: meta-analysis and implications. Sports Med 2016;46:1737–51. https://doi.org/10.1007/s40279-016-0537-6.Search in Google Scholar PubMed

36. Hongfang, Y, Xiaojing, L, Xiaohui, W. Effects of 4-week aerobic exercise and diet control on serum IGF-1 and IGF-1 binding protein-3 levels in obese female adolescents. Chin J Appl Physiol 2018;1:78–82.Search in Google Scholar

37. Huimin, Z, Zheng, X. Effects of 6-week aerobic exercise combined with diet control on body shape and blood indexes of obese adolescents. Chin J Appl Physiol 2017;2:166–8.Search in Google Scholar

38. Hongfang, Y, Xiaojing, L, Xiaohui, W. Effects of aerobic exercise plus diet control on serum levels of total IGF-1 and IGF-1 binding protein-3 in female obese youths and adolescents. Chin J Appl Physiol 2018;34:78–82.Search in Google Scholar

39. Wangyu, X, Wenhe, C, Xunzhang, S. Effects of moderate and low intensity aerobic exercise combined with diet control on blood lipid and liver function of obese adolescents. Chin J Sports Med 2011;8:706–11.Search in Google Scholar

40. Said, MA, Abdelmoneem, M, Alibrahim, MC, Elsebee, MA, Kotb, AAH. Effects of diet versus diet plus aerobic and resistance exercise on metabolic syndrome in obese young men. J Exerc Sci Fit 2020;18:101–8. https://doi.org/10.1016/j.jesf.2020.03.002.Search in Google Scholar PubMed PubMed Central

41. Said, MA, Abdelmoneim, MA, Alibrahim, MS, Kotb, AAH. Aerobic training, resistance training, or their combination as a means to fight against excess weight and metabolic syndrome in obese students – which is the most effective modality? A randomized controlled trial. Appl Physiol Nutr Metabol 2021;46:952–63. https://doi.org/10.1139/apnm-2020-0972.Search in Google Scholar PubMed

42. Said, MA, Alibrahim, MS. Physical activity, sedentary behaviors, and breakfast eating as factors influencing BMI in Saudi students, aged 10–15 years. Ann Med 2022;54:1459–72. https://doi.org/10.1080/07853890.2022.2077429.Search in Google Scholar PubMed PubMed Central

43. Sepulveda, AR, Solano, S, Blanco, M, Lacruz, T, Graell, M. Prevalence of childhood mental disorders in overweight and obese Spanish children: identifying loss of control eating. Psychiatr Res 2018;267:175–81.10.1016/j.psychres.2018.06.019Search in Google Scholar

44. Page, MJ, McKenzie, JE, Bossuyt, PM, Boutron, I, Hoffmann, TC, Mulrow, CD, et al.. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. PLoS Med 2021;18:e1003583. https://doi.org/10.1371/journal.pmed.1003583.Search in Google Scholar

45. Barba, C, Cavalli-Sforza, T, Cutter, J, Darnton-Hill, I, Deurenberg, P, Deurenberg-Yap, M, et al.. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363:157–63.10.1016/S0140-6736(03)15268-3Search in Google Scholar

46. Cole, TJ. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320:1240. https://doi.org/10.1136/bmj.320.7244.1240.Search in Google Scholar PubMed PubMed Central

47. Plummer, ML, Baltag, V, Strong, K, Dick, B, Al, F. Global Accelerated Action for the Health of Adolescents (AA-HA!): guidance to support country implementation. Geneva: Licence: CC BY-NC-SA 3.0 IGO; 2017.Search in Google Scholar

48. Higgins, JPT, Thomas, J, Chandler, J, Cumpston, M, Li, T, Page, MJ, et al.. Cochrane handbook for systematic reviews of interventions, 2nd ed. Chichester (UK): John Wiley & Sons; 2019.10.1002/9781119536604Search in Google Scholar

49. Borenstein, M, Higgins, JPT, Hedges, LV, Rothstein, HR. Basics of meta-analysis: I2 is not an absolute measure of heterogeneity. Res Synth Methods 2017;8:5–18. https://doi.org/10.1002/jrsm.1230.Search in Google Scholar PubMed

50. Dan, W, Junxia, Z, Zhenyun, M, Hongxia, Z, Xiaodong, Z, Xueyi, W, et al.. Heterogeneity in meta-analysis and its treatment methods. Chin J Evidence-Based Med 2009;10:1115–8.Search in Google Scholar

51. Ben Ounis, O, Elloumi, M, Zouhal, H, Makni, E, Denguezli, M, Amri, M, et al.. Effect of individualized exercise training combined with diet restriction on inflammatory markers and IGF-1/IGFBP-3 in obese children. Ann Nutr Metab 2010;56:260–6. https://doi.org/10.1159/000275888.Search in Google Scholar PubMed

52. Elloumi, M, Makni, E, Ounis, OB, Moalla, W, Zbidi, A, Zaoueli, M, et al.. Six-minute walking test and the assessment of cardiorespiratory responses during weight-loss programmes in obese children. Physiother Res Int 2011;16:32–42. https://doi.org/10.1002/pri.470.Search in Google Scholar PubMed

53. Xie, C, Wang, X, Zhou, C, Xu, C, Chang, Y. Exercise and dietary program-induced weight reduction is associated with cognitive function among obese adolescents: a longitudinal study. PeerJ 2017;5:e3286. https://doi.org/10.7717/peerj.3286.Search in Google Scholar PubMed PubMed Central

54. Xiang, MQ, Liao, JW, Huang, JH, Deng, HL, Wang, D, Xu, ZB, et al.. Effect of a combined exercise and dietary intervention on self-control in obese adolescents. Front Psychol 2019;10:1385. https://doi.org/10.3389/fpsyg.2019.01385.Search in Google Scholar PubMed PubMed Central

55. Liu, M, Lin, X, Wang, X. Decrease in serum chemerin through aerobic exercise plus dieting and its association with mitigation of cardio-metabolic risk in obese female adolescents. J Pediatr Endocrinol Metab 2018;2:127–35. https://doi.org/10.1515/jpem-2017-0431.Search in Google Scholar

56. Brandao Albuquerque Filho, NJ, Bellaguarda, ERF, Reboucas, GM, Felipe, TR, Dantas, PMS, Knackfuss, MI, et al.. Concurrent exercise program plus diet intervention on body adiposity and lipid profile in obese adolescents. Gazz Med Ital Arch Sci Med 2015;174:259–66.Search in Google Scholar

57. Elloumi, M, Ben Ounis, O, Makni, E, Van Praagh, E, Tabka, Z, Lac, G. Effect of individualized weight-loss programmes on adiponectin, leptin and resistin levels in obese adolescent boys. Acta Paediatr 2009;98:1487–93. https://doi.org/10.1111/j.1651-2227.2009.01365.x.Search in Google Scholar

58. Mingwei, L, Jianfeng, G, Yingchun, W, Shaoyong, X. Effects of different nutritional support treatments on adolescent obesity with lipid metabolism disorder. Med J Chin Peoples Health 2015;4:104–5.Search in Google Scholar

59. Liangmei, X, Xiangtian, L, Wenjun, W, Chao, Z, Chengkai, S, Weijun, F, et al.. Effect evaluation of balanced diet and exercise intervention on simple obesity junior high school students. Chin J Sch Health 2015;1:51–3.Search in Google Scholar

60. Xinhui, N, Lijun, W. Evaluation on the effect of exercise and diet intervention for Uygur obese middle school students in Xinjiang. Chin J Sch Health 2016;4:589–91.Search in Google Scholar

61. Guijun, D. Study on the influence of combined weight loss methods on blood pressure and blood lipid of simple obesity teenagers. J Shandong Inst Phys Educ Sports 2009;12:42–5+48.Search in Google Scholar

62. Yuan, J. Empirical study on the effect of exercise-dietary intervention on fat reduction of obese college students. Nanjing: Nanjing Sport Institute; 2017, vol 8.Search in Google Scholar

63. Ting, L, Jin, L. Effect of moderate and low intensity aerobic exercise combined with diet control on weight loss and blood lipid of obese adolescents. Sport 2015;11:153–4.Search in Google Scholar

64. Dongqi, Y. Study on the changes of body shape and physical fitness of obese adolescents by regular physical exercise. Health Horizon 2018;15:20–1.Search in Google Scholar

65. Alberti, KGMM, Zimmet, PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. Provisional report of a WHO consultation. Diabet Med 1998;15:539–53. https://doi.org/10.1002/(sici)1096-9136(199807)15:7<539::aid-dia668>3.0.co;2-s.10.1002/(SICI)1096-9136(199807)15:7<539::AID-DIA668>3.0.CO;2-SSearch in Google Scholar

66. Ostchega, Y, Hughes, JP, Terry, A, Fakhouri, THI, Miller, I. Abdominal obesity, body mass index, and hypertension in US adults: NHANES 2007–2010. Am J Hypertens 2012;25:1271–8. https://doi.org/10.1038/ajh.2012.120.Search in Google Scholar

67. Kim, MS, Kim, WJ, Khera, AV, Kim, JY, Yon, DK, Lee, SW, et al.. Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. Eur Heart J 2021;42:3388. https://doi.org/10.1093/eurheartj/ehab454.Search in Google Scholar

68. Yi, D, Chuanming, X, Jinquan, W, Zunyu, K. Effects of aerobic exercise, resistance training and diet intervention on weight loss of young obese women. J Chengdu Sport Univ 2007;6:105–8.Search in Google Scholar

69. Huang, TTK, Johnson, MS, Figueroa-Colon, R, Dwyer, JH, Goran, MI. Growth of visceral fat, subcutaneous abdominal fat, and total body fat in children. Obesity 2001;9:283–9. https://doi.org/10.1038/oby.2001.35.Search in Google Scholar

70. Guansheng, M, Chengye, J, Jun, M, Jie, M, Yinzi, S, Feng, X, et al.. A study on waist boundaries of school-age children and adolescents aged 7–18 in China. Chin J Epidemiol 2010;6:609–15.Search in Google Scholar

71. Jayedi, A, Soltani, S, Zargar, MS, Khan, TA, Shab-Bidar, S. Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies. BMJ Br Med J (Clin Res Ed) 2020;370:m3324. https://doi.org/10.1136/bmj.m3324.Search in Google Scholar

72. Yoshizumi, T, Nakamura, T, Yamane, M, Islam, A, Menju, M, Yamasaki, K, et al.. Abdominal fat: standardized technique for measurement at CT1. Radiology 1999;211:283–6. https://doi.org/10.1148/radiology.211.1.r99ap15283.Search in Google Scholar

73. Jingjing, W, Han, H, Haifeng, Z. Effect of high intensity interval training on abdominal fat content of young obese women. Chin J Sports Med 2015;1:15–20.Search in Google Scholar

74. Wabitsch, M, Hauner, H, Heinze, E, Muche, R, Bockmann, A, Parthon, W, et al.. Body-fat distribution and changes in the atherogenic risk-factor profile in obese adolescent girls during weight reduction. Am J Clin Nutr 1994;60:54–60. https://doi.org/10.1093/ajcn/60.1.54.Search in Google Scholar

75. Karampatsou, SI, Genitsaridi, SM, Michos, A, Kourkouni, E, Kourlaba, G, Kassari, P, et al.. The effect of a life-style intervention program of diet and exercise on irisin and FGF-21 concentrations in children and adolescents with overweight and obesity. Nutrients 2021;13:1274. https://doi.org/10.3390/nu13041274.Search in Google Scholar

76. Chu, SY, Jung, JH, Park, MJ, Kim, SH. Risk assessment of metabolic syndrome in adolescents using the triglyceride/high-density lipoprotein cholesterol ratio and the total cholesterol/high-density lipoprotein cholesterol ratio. Ann Pediatr Endocrinol Metab 2019;24:41–8. https://doi.org/10.6065/apem.2019.24.1.41.Search in Google Scholar PubMed PubMed Central

77. Sesso, HD, Buring, JE, Chown, MJ, Ridker, PM, Gaziano, JM. A prospective study of plasma lipid levels and hypertension in women. Arch Intern Med 2005;165:2420–7. https://doi.org/10.1001/archinte.165.20.2420.Search in Google Scholar PubMed

78. Zhen, Z. High-density lipoprotein (HDL) and triglyceride are the therapeutic targets. Mol Cardiol China 2003;5:296–304.Search in Google Scholar

79. Chushan, W, Cong, Z, Haiyan, J, Rongxiu, Z. Significance of triglyceride and HDL-cholesterol ratio in predicting metabolic syndrome in children. J Tianjin Med Univ 2021;1:11–6.Search in Google Scholar

80. Lam, CSP, Chen, M, Lacey, SM, Yang, Q, Sullivan, LM, Xanthakis, V, et al.. Circulating insulin-like growth factor-1 and its binding protein-3. Arterioscler Thromb Vasc Biol 2010;30:1479–84. https://doi.org/10.1161/atvbaha.110.203943.Search in Google Scholar

81. Friedrich, N, Thuesen, B, Jørgensen, T, Juul, A, Spielhagen, C, Wallaschofksi, H, et al.. The association between IGF-I and insulin resistance. Diabetes Care 2012;35:768–73. https://doi.org/10.2337/dc11-1833.Search in Google Scholar PubMed PubMed Central

82. Koziris, LP, Hickson, RC, Chatterton, RJ, Groseth, RT, Christie, JM, Goldflies, DG, et al.. Serum levels of total and free IGF-I and IGFBP-3 are increased and maintained in long-term training. J Appl Physiol 1999;86:1436–42. https://doi.org/10.1152/jappl.1999.86.4.1436.Search in Google Scholar PubMed

83. Eliakim, A, Brasel, JA, Mohan, S, Wong, WL, Cooper, DM. Increased physical activity and the growth hormone-IGF-I axis in adolescent males. Am J Physiol 1998;275:R308–14. https://doi.org/10.1152/ajpregu.1998.275.1.r308.Search in Google Scholar PubMed

84. Filaire, E. Effects of 16 weeks of training prior to a major competition on hormonal and biochemical parameters in young elite gymnasts. J Pediatr Endocrinol Metab 2003;16:741–50. https://doi.org/10.1515/jpem.2003.16.5.741.Search in Google Scholar PubMed

85. Nemet, D, Connolly, P, Pontello-Pescatello, A, Rose-Gottron, C, Larson, J, Galassetti, P, et al.. Negative energy balance plays a major role in the IGF-I response to exercise training. J Appl Physiol 2004;96:276–82. https://doi.org/10.1152/japplphysiol.00654.2003.Search in Google Scholar PubMed

86. Xiaomei, Z, Shanshan, P, Wenhe, C. Effects of exercise intervention on body composition, blood lipid, insulin resistance and high-sensitivity protein in obese adolescents. J Shanghai Univ Sport 2012;6:62–6.Search in Google Scholar

87. Yanai, H, Yoshida, H. Beneficial effects of adiponectin on glucose and lipid metabolism and atherosclerotic progression: mechanisms and perspectives. Int J Mol Sci 2019;20:1190. https://doi.org/10.3390/ijms20051190.Search in Google Scholar PubMed PubMed Central

88. Gustafson, B. Adipose tissue, inflammation and atherosclerosis. J Atherosclerosis Thromb 2010;17:332–41. https://doi.org/10.5551/jat.3939.Search in Google Scholar PubMed

89. Guie, M, Ping, L, Hua, L. Study on the relationship between serum adiponectin, resistin and insulin resistance in overweight and obese women. Chin J Health Care Med 2010;6:449–51.Search in Google Scholar

90. Xiaohong, Y, Ping, Z, Xiaorong, H. Relationship between serum adiponectin and hypertension in overweight or obese adolescents. Labeled Immunoassay Clin Med 2009;6:344–436.Search in Google Scholar

91. Han, J, Hui, X, Tian, L, Hongyan, H. Plasma adiponectin level and its influencing factors in obese men. Med Philos (Clinical Decision Forum Edition) 2009;5:56–7.Search in Google Scholar

92. Yude, L. Correlation between plasma adiponectin and insulin level in children with obesity. Sichuan Med J 2009;11:1759–60.Search in Google Scholar

93. García-Hermoso, A, Ramírez-Vélez, R, Ramírez-Campillo, R, Peterson, MD, Martínez-Vizcaíno, V. Concurrent aerobic plus resistance exercise versus aerobic exercise alone to improve health outcomes in paediatric obesity: a systematic review and meta-analysis. Br J Sports Med 2018;52:161–6. https://doi.org/10.1136/bjsports-2016-096605.Search in Google Scholar PubMed

94. Sirico, F, Bianco, A, D’Alicandro, G, Castaldo, C, Montagnani, S, Spera, R, et al.. Effects of physical exercise on adiponectin, leptin, and inflammatory markers in childhood obesity: systematic review and meta-analysis. Child Obes 2018;4:207–17. https://doi.org/10.1089/chi.2017.0269.Search in Google Scholar PubMed PubMed Central

95. García-Hermoso, A, Ceballos-Ceballos, RJM, Poblete-Aro, CE, Hackney, AC, Mota, J, Ramírez-Vélez, R. Exercise, adipokines and pediatric obesity: a meta-analysis of randomized controlled trials. Int J Obes 2017;41:475–82. https://doi.org/10.1038/ijo.2016.230.Search in Google Scholar PubMed PubMed Central

96. Liang, S, Hu, Y, Liu, C, Qi, J, Li, G. Low insulin-like growth factor 1 is associated with low high-density lipoprotein cholesterol and metabolic syndrome in Chinese nondiabetic obese children and adolescents: a cross-sectional study. Lipids Health Dis 2016;15:1–7. https://doi.org/10.1186/s12944-016-0275-7.Search in Google Scholar PubMed PubMed Central

97. Yu, N, Ruan, Y, Gao, X, Sun, J. Systematic review and meta-analysis of randomized, controlled trials on the effect of exercise on serum leptin and adiponectin in overweight and obese individuals. Horm Metab Res 2017;49:164–73. https://doi.org/10.1055/s-0042-121605.Search in Google Scholar PubMed

98. Nascimento, H, Costa, E, Rocha, S, Lucena, C, Rocha-Pereira, P, Rego, C, et al.. Adiponectin and markers of metabolic syndrome in obese children and adolescents: impact of 8-mo regular physical exercise program. Pediatr Res 2014;76:159–65. https://doi.org/10.1038/pr.2014.73.Search in Google Scholar PubMed

99. Damaso, AR, Campos, RMD, Caranti, DA, de Piano, A, Fisberg, M, Foschini, D, et al.. Aerobic plus resistance training was more effective in improving the visceral adiposity, metabolic profile and inflammatory markers than aerobic training in obese adolescents. J Sports Sci 2014;32:1435–45.10.1080/02640414.2014.900692Search in Google Scholar PubMed

100. Zhang, F, Basinski, MB, Beals, JM, Briggs, SL, Churgay, LM, Clawson, DK, et al.. Crystal structure of the obese protein leptin-E100. Nature 1997;387:206–9.10.1038/387206a0Search in Google Scholar PubMed

101. El Dayem, SMA, Battah, AA, El Bohy, AEM, El Shehaby, A, El Ghaffar, EA. Relationship of plasma level of chemerin and vaspin to early atherosclerotic changes and cardiac autonomic neuropathy in adolescent type 1 diabetic patients. J Pediatr Endocrinol Metabol 2015;28:265–73. https://doi.org/10.1515/jpem-2014-0215.Search in Google Scholar PubMed

102. Kuo, H, Yen, C, Chen, J, Yu, Y, Bean, JF. Association of cardiorespiratory fitness and levels of C-reactive protein: data from the National health and nutrition examination survey 1999–2002. Int J Cardiol 2007;114:28–33. https://doi.org/10.1016/j.ijcard.2005.11.110.Search in Google Scholar PubMed

103. Guowei, L, Shuqin, W, Donghua, S, Xu, X, Yuan, Z, Fang, W, et al.. Changes and correlation analysis of serum adiponectin, leptin, free fatty acids and inflammatory factors in simple overweight and obese adolescents. J Med Res 2007;8:58–63.Search in Google Scholar

104. Wong, PCH, Chia, MYH, Tsou, IYY, Wansaicheong, GKL, Tan, B, Wang, JCK, et al.. Effects of a 12-week exercise training programme on aerobic fitness, body composition, blood lipids and C-reactive protein in adolescents with obesity. Ann Acad Med Singapore 2008;37:286–93.10.47102/annals-acadmedsg.V37N4p286Search in Google Scholar

105. Hung, J, Knuiman, MW, Divitini, ML, Langton, PE, Chapman, CL, Beilby, JP. C-reactive protein and interleukin-18 levels in relation to coronary heart disease: prospective cohort study from Busselton Western Australia. Heart Lung Circ 2008;17:90–5. https://doi.org/10.1016/j.hlc.2007.07.002.Search in Google Scholar PubMed

106. Xiaoqin, Z, Yong, S, Lili, Z. Comparative study on CRP and IL-6 levels in peripheral blood of normal-overweight-obese adolescents. J Practical Med Tech 2008;21:2739–41.Search in Google Scholar

107. Tomaszewski, M, Charchar, FJ, Przybycin, M, Crawford, L, Wallace, AM, Gosek, K, et al.. Strikingly low circulating CRP concentrations in ultramarathon runners independent of markers of adiposity. Arterioscler Thromb Vasc Biol 2003;23:1640–4. https://doi.org/10.1161/01.atv.0000087036.75849.0b.Search in Google Scholar

108. Timoteo, AT, Miranda, F, Feliciano, J, Ferreira, R. Influence of anthropometric variables in reactive protein. Acta Med Port 2011;24:419–26.Search in Google Scholar

109. Mattusch, F, Dufaux, B, Heine, O, Mertens, I, Rost, R. Reduction of the plasma concentration of C-reactive protein following nine months of endurance training. Int J Sports Med 2000;21:21–4. https://doi.org/10.1055/s-2000-8852.Search in Google Scholar PubMed

110. Silha, JV, Krsek, M, Skrha, JV, Sucharda, P, Nyomba, BL, Murphy, LJ. Plasma resistin, adiponectin and leptin levels in lean and obese subjects: correlations with insulin resistance. Eur J Endocrinol 2003;149:331–5. https://doi.org/10.1530/eje.0.1490331.Search in Google Scholar PubMed

Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/jpem-2022-0193).

Received: 2022-04-08
Accepted: 2022-08-30
Published Online: 2022-09-21
Published in Print: 2022-11-25

© 2022 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Review Article
  3. Effects of exercise combined with diet intervention on body composition and serum biochemical markers in adolescents with obesity: a systematic review and meta-analysis
  4. Mini Review
  5. Effect of stimulants on final adult height
  6. Original Articles
  7. Organic acidemias in the neonatal period: 30 years of experience in a referral center for inborn errors of metabolism
  8. The long-term growth, cost-effectiveness, and glycemic effects of growth hormone therapy on children born small for gestational age over 10 years: a retrospective cohort study
  9. Standard and high dose ergocalciferol regimens for treatment of hypovitaminosis D in epileptic children and adolescents
  10. Children and adolescents with type 1 diabetes mellitus in Nigeria: clinical characteristics and compliance with care
  11. Disordered eating and behaviors among young Egyptians with type 1 diabetes: risk factors and comorbidities
  12. Normal or elevated prolactin is a good indicator to show pituitary stalk interruption syndrome in patients with multiple pituitary hormone deficiency
  13. No pubertal growth spurt, rapid bone maturation, and menarche post GnRHa treatment in girls with precocious puberty
  14. Genetic analysis of failed male puberty using whole exome sequencing
  15. Gender diversity in adolescents with polycystic ovary syndrome
  16. Case Reports
  17. Management challenges of Rabson Mendenhall syndrome in a resource limited country: a case report
  18. Thyroid function tests of iodine deficiency goiter can mimic thyroid hormone resistance alpha
  19. Pseudohypoaldosteronism associated with hypertrophic cardiomyopathy, hypertension and thrombocytosis due to mutation in the ELAC2 gene: a case report
  20. Acromicric dysplasia due to a novel missense mutation in the fibrillin 1 gene in a three-generation family
  21. A case of severe systemic type 1 pseudohypoaldosteronism with 10 years of evolution
  22. Advantages of monitoring rT3 and dividing LT3 dose in the treatment of consumptive hypothyroidism associated with infantile hepatic hemangioma
https://doi.org/10.1515/jpem-2022-0193
Keywords for this article
adolescents with obesity; body composition; exercise combined with diet; serum biochemical markers
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Review Article
  3. Effects of exercise combined with diet intervention on body composition and serum biochemical markers in adolescents with obesity: a systematic review and meta-analysis
  4. Mini Review
  5. Effect of stimulants on final adult height
  6. Original Articles
  7. Organic acidemias in the neonatal period: 30 years of experience in a referral center for inborn errors of metabolism
  8. The long-term growth, cost-effectiveness, and glycemic effects of growth hormone therapy on children born small for gestational age over 10 years: a retrospective cohort study
  9. Standard and high dose ergocalciferol regimens for treatment of hypovitaminosis D in epileptic children and adolescents
  10. Children and adolescents with type 1 diabetes mellitus in Nigeria: clinical characteristics and compliance with care
  11. Disordered eating and behaviors among young Egyptians with type 1 diabetes: risk factors and comorbidities
  12. Normal or elevated prolactin is a good indicator to show pituitary stalk interruption syndrome in patients with multiple pituitary hormone deficiency
  13. No pubertal growth spurt, rapid bone maturation, and menarche post GnRHa treatment in girls with precocious puberty
  14. Genetic analysis of failed male puberty using whole exome sequencing
  15. Gender diversity in adolescents with polycystic ovary syndrome
  16. Case Reports
  17. Management challenges of Rabson Mendenhall syndrome in a resource limited country: a case report
  18. Thyroid function tests of iodine deficiency goiter can mimic thyroid hormone resistance alpha
  19. Pseudohypoaldosteronism associated with hypertrophic cardiomyopathy, hypertension and thrombocytosis due to mutation in the ELAC2 gene: a case report
  20. Acromicric dysplasia due to a novel missense mutation in the fibrillin 1 gene in a three-generation family
  21. A case of severe systemic type 1 pseudohypoaldosteronism with 10 years of evolution
  22. Advantages of monitoring rT3 and dividing LT3 dose in the treatment of consumptive hypothyroidism associated with infantile hepatic hemangioma
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Winner of the OpenAthens UX Award 2026
Winner of the OpenAthens UX Award 2026
Have an idea on how to improve our website?
Please write us.
© 2026 De Gruyter Brill
Downloaded on 19.3.2026 from https://www.degruyterbrill.com/document/doi/10.1515/jpem-2022-0193/html
Scroll to top button