With the increasing rate of overweight and obesity in children worldwide, adiposity rebound(AR)closely related to obesity has become the spotlight, and early AR phase has a broad impact on pubertal development in girls, but the specific mechanism of action isn't very clear.This paper is review of the prevalence of early AR at home and abroad, and its influencing factors, the impact of AR on the adolescent development of girls and related mechanisms, to identify high-risk individuals with early AR, early AR to identify early adolescent development, and take early intervention measures to promote children's health.
Female ; Adolescent ; Child ; Humans ; Adiposity ; Pediatric Obesity/epidemiology* ; Adolescent Development ; Body Mass Index ; Overweight/epidemiology*

OBJECTIVES: To investigate the prevalence rate of non-alcoholic fatty liver disease (NAFLD) in overweight/obese children who visit a hospital, and to explore the influencing factors of NAFLD, in order to provide a basis for the prevention of NAFLD in overweight/obese children. METHODS: Overweight/obese children who visited Hunan Children's Hospital from June 2019 to September 2021 were recruited. The prevalence rate of NAFLD was examined. Logistic regression analysis was used to explore the factors influencing the development of NAFLD [non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH)]. Receiver operating characteristic curve analysis was used to evaluate the predictive value of the influencing factors for NAFL and NASH. RESULTS: A total of 844 overweight/obese children aged 6-17 years were enrolled. The prevalence rate of NAFLD in overweight/obese children was 38.2% (322/844), among which the prevalence rates of NAFL and NASH were 28.8% (243/844) and 9.4% (79/844), respectively. Multivariate logistic regression analysis showed that the increase of waist-to-hip ratio (WHR) and low high-density lipoprotein cholesterol (HDL-C) were associated with the development of NAFL and NASH (P<0.05). The receiver operating characteristic curve analysis showed that the combined measurement of WHR and HDL-C had a predictive value for NAFL (area under the curve: 0.653, 95%CI: 0.613-0.694), and for NASH (area under the curve: 0.771, 95%CI: 0.723-0.819). CONCLUSIONS The prevalence rate of NAFLD in overweight/obese children who visit a hospital is high. WHR and HDL-C are associated with the development of NAFLD and the combined measurement of WHR and HDL-C has a certain value for predicating the development of NAFLD.
Child ; Humans ; Cholesterol, HDL ; Cross-Sectional Studies ; Non-alcoholic Fatty Liver Disease/complications* ; Overweight/complications* ; Pediatric Obesity/epidemiology* ; Prevalence ; Adolescent

OBJECTIVES: To investigate the physical growth and dietary characteristics of children with attention deficit hyperactivity disorder (ADHD), and to analyze their relationship with core symptoms of ADHD. METHODS: A total of 268 children who were newly diagnosed with ADHD in Children's Hospital of Nanjing Medical University from June to December 2020 were included in the ADHD group, and 102 healthy children who underwent physical examination during the same period were selected as the control group. Physical evaluations and dietary surveys were conducted for both groups. ADHD diagnosis and scoring were performed according to the Diagnostic and Statistical Manual of Mental Disorders (5th edition). Factor analysis, Spearman correlation analysis, and mediation analysis were used to study the relationship between core symptoms of ADHD, dietary patterns, and physical growth. RESULTS: The rate of overweight/obesity in the ADHD group was significantly higher than that in the control group (35.8% vs 21.6%, P<0.05). Three dietary patterns were extracted from the food frequency questionnaire: vegetarian dietary pattern, traditional dietary pattern, and snack/fast food pattern. The factor score for the snack/fast food pattern in the ADHD group was higher than that in the control group (P<0.05). There was a significant positive correlation between ADHD symptom scores, snack/fast food pattern factor scores, and body fat percentage (P<0.05). The mediation analysis showed that the snack/fast food pattern played a partial mediating role in the relationship between ADHD symptom scores and body fat percentage, with a mediation proportion of 26.66%. CONCLUSIONS The rate of overweight/obesity in children with ADHD is higher than that in non-ADHD children. Core symptoms of ADHD are related to dietary patterns and physical growth, with the snack/fast food pattern playing a partial mediating role in the relationship between core symptoms of ADHD and physical growth.
Humans ; Child ; Attention Deficit Disorder with Hyperactivity/epidemiology* ; Cross-Sectional Studies ; Overweight ; Pediatric Obesity ; Diet

Prevalence of childhood obesity is progressively increasing, reaching worldwide levels of 5.6% in girls and of 7.8% in boys. This also leads to a corresponding increase in the prevalence of obesity-associated morbidities particularly those involving obstructive sleep apnea（OSA）. Obesity is an independent risk factor and regulator of OSA in children. There is a bidirectional causal relationship between OSA and obesity in children. The factors involved in the association between OSA and obesity are systemic inflammation, oxidative stress, and gut microbiota etc. However, a causal link between obesity-related inflammatory state and OSA pathogenesis still needs to be properly confirmed. The present review aimed to investigate the links between childhood obesity and OSA.
Male ; Female ; Humans ; Child ; Pediatric Obesity/epidemiology* ; Sleep Apnea, Obstructive/epidemiology* ; Risk Factors ; Inflammation

OBJECTIVE: To analyze the association between outdoor artificial light-at-night (ALAN) exposure and overweight and obesity among children and adolescents aged 9 to 18 years in China. METHODS: Using follow-up data of 5 540 children and adolescents aged 9 to 18 years conducted from November 2019 to November 2020 in eight provinces of China, latitude and longitude were determined based on school addresses, and the mean monthly average nighttime irradiance at the location of 116 schools was extracted by the nearest neighbor method to obtain the mean outdoor ALAN exposure [unit: nW/(cm²·sr)] for each school. Four indicators of overweight and obesity outcomes were included: Baseline overweight and obesity, persistent overweight and obesity, overweight and obesity progression and overweight and obesity incidence. Mixed effects Logistic regression was used to explore the association between ALAN exposure levels (divided into quintiles Q1-Q5) and baseline overweight and obesity, persistent overweight and obesity, overweight and obesity progression and overweight and obesity incidence. In addition, a natural cubic spline function was used to explore the exposure response association between ALAN exposure (a continuous variable) and the outcomes. RESULTS: The prevalence of baseline overweight and obesity, persistent overweight and obesity, overweight and obesity progression and overweight and obesity incidence among the children and adolescents in this study were 21.6%, 16.3%, 2.9% and 12.8%, respectively. The OR value for the association between ALAN exposure and baseline overweight and obesity was statistically significant when ALAN exposure levels reached Q4 or Q5, 1.90 (95%CI: 1.26-2.86) and 1.77 (95%CI: 1.11-2.83), respectively, compared with the children and adolescents in the Q1 group of ALAN exposure. Similar to the results for baseline overweight and obesity, the OR values for the association with persistent overweight and obesity were 1.89 (95%CI: 1.20-2.99) and 1.82 (95%CI: 1.08-3.06) when ALAN exposure levels reached Q4 or Q5, respectively, but none of the OR values for the association between ALAN and overweight and obesity progression and overweight and obesity incidence were statistically significant. Fitting a natural cubic spline function showed a non-linear trend between ALAN exposure and persistent overweight and obesity. CONCLUSION There is a positive association between ALAN exposure and overweight and obesity in children and adolescents, and the promotion of overweight obesity in children and adolescents by ALAN tends to have a cumulative effect rather than an immediate effect. In the future, while focusing on the common risk factors for overweight and obesity in children and adolescents, there is a need to improve the overweight and obesity-causing nighttime light exposure environment.
Humans ; Adolescent ; Child ; Overweight/etiology* ; Pediatric Obesity/etiology* ; Light Pollution ; Risk Factors ; China/epidemiology*

From January 2019 to December 2021, overweight and obese children who visited in health outpatient Center of Hunan Children's Hospital were studied to explore and analyze the rate, related factors and patterns of multimorbidity of overweight and obesity-related diseases in children in Hunan Province. Univariate and multivariate logistic regression models were used to analyze the multimorbidity-related factors of overweight and obesity-related diseases in children. Association rules (apriori algorithm) were used to explore the multimorbidity patterns of overweight and obesity-related diseases in children. A total of 725 overweight and obese children were included in this study. The multimorbidity rate of overweight and obesity-related diseases in children was 46.07% (334/725). Age, waist circumference, the frequency of food consumption such as hamburgers and fries and adding meals before bedtime were multimorbidity-related factors of overweight and obesity-related diseases in children. The multimorbidity associated with nonalcoholic fatty liver disease (NAFLD) was relatively common. The patterns with the top three support degrees were "NAFLD+dyslipidemia","NAFLD+hypertension" and "NAFLD+hyperuricemia". The patterns with the top three confidence and elevation degrees were "Hypertension+dyslipidemia => NAFLD","Hyperuricemia => NAFLD" and "NAFLD+hypertension => dyslipidemia".
Child ; Humans ; Overweight/complications* ; Non-alcoholic Fatty Liver Disease ; Pediatric Obesity/epidemiology* ; Hyperuricemia ; Multimorbidity ; Hypertension/epidemiology* ; Dyslipidemias ; Body Mass Index ; Risk Factors

Objective: To examine risk factors of simple obesity and their interaction in preschool children in China. Methods: A total of 63 292 preschool children aged 3-7 years selected by cluster random sampling in 9 cities of China, including Beijing, Harbin, Xi'an, Shanghai, Nanjing, Wuhan, Guangzhou, Fuzhou and Kunming, were investigated from June to November in 2016. Based on the BMI-for-age cut off points of overweight and obesity for Chinese children aged 2-18 years, a total of 1 522 obese children (1 006 boys and 516 girls) were screened. By population-based matched case-control design, a normal weight child was randomly selected to match with an obese child by sex, age (difference ≤6 months) and body height (difference ≤5 cm) from the survey area. Conditional logistic regression model was used to analyze association of risk factors with obesity and the interaction of risk factors. Results: ① Univariate conditional logistic regression model showed that 17 risk factors of simple obesity had statistical significance (P<0.001), including high birth weight, cesarean section, gestational diabetes, gestational hypertension, formula feeding in the first 6 months after birth, strong appetite, fast or slow eating speed, low intensity of outdoor activities, daily outdoor activity time <1 hour, daily screen viewing time < 1 hour or ≥2 hours, daily night sleep time <9 hours, mother overweight, father overweight, mother's low educational level, father's low educational level, non-nuclear family structure, and parents not being the primary caregivers of children. ②Multivariate conditional logistic regression model showed that 12 risk factors had statistical significance, including high birth weight (OR=1.83, 95%CI:1.29-2.61, P<0.001), cesarean section (OR=1.22, 95%CI:1.07-1.39, P=0.003), gestational diabetes (OR=4.57, 95%CI:2.13-9.79, P<0.001), mother's low educational level (OR=1.52, 95%CI:1.11-2.07, P=0.008), single parent family (OR=4.79, 95%CI:1.44-15.88, P=0.010), mother overweight (OR=2.58, 95%CI:1.93-3.46, P<0.001), father overweight (OR=2.40, 95%CI:1.86-3.10, P<0.001), strong appetite (OR=7.78, 95%CI:5.38-11.27, P<0.001), fast eating speed (OR=6.59, 95%CI:4.86-8.94, P<0.001), daily outdoor activity time <1 hour (OR=1.42, 95%CI: 1.09-1.85, P=0.009), daily night sleep time <9 hours (OR=1.59, 95%CI: 1.13-2.23, P=0.007), daily screen viewing time ≥2 hours (OR=1.69, 95%CI:1.27-2.24, P<0.001). ③ Interaction of the four groups of risk factors had statistical significance, including interaction between mother overweight and father overweight (OR=5.53, 95%CI: 3.76-8.13, P<0.001), interaction between strong appetite and fast eating speed (OR=54.48, 95%CI: 32.95-90.06, P<0.001), interaction between low intensity of outdoor activity and daily outdoor activity time <1 hour (OR=2.12, 95%CI: 1.29-3.48, P=0.002), interaction between daily night sleep time <9 hours and daily screen viewing time ≥2 hours (OR=2.83, 95%CI: 1.71-4.68, P<0.001). Conclusions: This study identified 12 risk factors of childhood obesity, including high birth weight, cesarean section, gestational diabetes, mother's low educational level, single parent family, mother overweight, father overweight, strong appetite, fast eating speed, daily short outdoor activity time, daily short night sleep time, daily long screen viewing time, and interaction of the four groups of risk factors had statistical significance, including strong interaction between mother overweight and father overweight, interaction between strong appetite and fast eating speed, interaction between low intensity of outdoor activity and daily short outdoor activity time, interaction between daily short night sleep time and daily long screen viewing time.
Adolescent ; Body Mass Index ; Cesarean Section ; Child ; Child, Preschool ; China/epidemiology* ; Cities/epidemiology* ; Female ; Humans ; Male ; Overweight/epidemiology* ; Pediatric Obesity/epidemiology* ; Pregnancy ; Prevalence ; Risk Factors

Objective: To analyze the diversity differences of gut microbiota between school-aged obese children and normal-weight children and identify the characteristic flora in obese children to provide some evidence for the subsequent study of the following study-related mechanisms and the prevention and treatment of obesity in school-aged children. Methods: This study was based on a cohort established in a primary school in Jiading district, Shanghai, 2016. Sixty-three children, including 43 boys and 20 girls, who were obese during the three years from 2016 to 2018, were enrolled in the obesity group. Among children who were average weight for three years, a total of 63 were selected as the control group, with matching with the obese ones in a 1 to 1 way according to age, sex and class. The primary characteristics, diet status, breastfeeding, and other information of children were collected by questionnaire. Fecal samples of participants in both groups were collected, and 16S rDNA sequencing was performed. Operable taxon units clustering according to 97% similarity and species annotation were based on the quality-optimized sequences. The difference in the diversity and genius of gut microbiota among children in the obesity and control groups were analyzed. The α diversity indices, including Ace, Chao1, Shannon, and Simpson index, were calculated. The β diversity was presented based on unweighted Unifrac distance and weighted Unifrac space by principal coordinate analysis. The differences in β diversity between the two groups were compared by similarity analysis (ANOSIM).The differences in genus distribution between the two groups were selected by STAMP software. The association of obesity with the α diversity and genus with significant differences were analyzed by the generalized linear model (GLM). Results: The Ace and Chao1 index in the obesity group was significantly lower than those in the control group (The P values were 0.026 and 0.039, respectively). There was no significant difference in Shannon and Simpson index between the two groups (The P values were 0.879 and 0.922, respectively). The results of ANOSIM showed differences in gut microbiota between the two groups (R>0), but the group contribution was not significant (unweighted Unifrac distance: R=0.006, P=0.223; weighted Unifrac distance: R=0.010, P=0.134). Among the obese group, the relative abundance of Prevotella and Sarcina was highest in the endemic genus. The STAMP results showed that the relative lots of 15 genera were significantly different between the two groups (P<0.05). The results of GLM showed that, compared with the control group, the obesity group had a lower level of the relative abundance in Akkermansia muciniphila, while a higher level in Coprococcus_3, Ruminococcus, Agathobacter and Collinsella. After stratification by sex, the Chao1 index was also lower in the obese boys than that in the normal-weight boys. However, the obese girls only had a higher level in Coprococcus_3 than the ordinary weight girls. Conclusions: Compared with children with average weight, obese children had lower α diversity of gut microbiota and lower relative abundance of dominant probiotics but had a higher relative lot of genus associated with metabolic disorders, inflammation promotion, and metabolism rate reduction.
Child ; China/epidemiology* ; Cohort Studies ; Feces ; Female ; Gastrointestinal Microbiome/genetics* ; Humans ; Male ; Pediatric Obesity/epidemiology*

Objective: To examine the associations of childhood obesity, assessed by genetic variations of childhood body mass index (BMI), with the risk of adult ischemic heart disease (IHD) and major coronary event (MCE). Methods: More than 69 000 participants from the China Kadoorie Biobank were genotyped. After excluding those with coronary heart disease, stroke, or cancer at baseline, a total of 64 454 participants were included in this study. Based on genome-wide significant single nucleotide polymorphisms (SNPs), childhood BMI genetic risk score were constructed for every participant and divided into quintiles, with the lowest quintile as the low genetic risk group and the highest quintile as the high genetic risk group. Cox proportional hazards regression models were used to estimate the association between genetic predisposition to childhood obesity and the risk of ischemic heart disease. Results: During a median of 10.7 years of follow-up, 7 073 incident cases of IHD and 1 845 cases of MCE were documented. After adjusting for sex, age, region, and the first ten genetic principal components, the HRs (95%CIs) for IHD and MCE in the high genetic risk group were 1.10 (1.02-1.18) and 1.10 (0.95-1.27), compared with the low genetic risk group. IHD risk increased by 4% (2%-6%) for each one standard deviation increase in genetic risk score (trend P=0.001). After further adjustment for baseline BMI, the differences between genetic risk groups were not statistically significant, but there was still a linear trend between genetic risk score and IHD risk (trend P=0.019). Conclusions: IHD risk increased with genetic predisposition to childhood obesity, suggesting that childhood obesity is an important risk factor for the development of IHD in China. As an easily identifiable feature, changes of childhood BMI should be monitored regularly to realize early intervention of IHD in adults.
Adult ; Body Mass Index ; Child ; China/epidemiology* ; Genetic Predisposition to Disease ; Humans ; Myocardial Ischemia/genetics* ; Pediatric Obesity/genetics* ; Prospective Studies ; Risk Factors

OBJECTIVES: To investigate the prevalence of diabetes mellitus (DM) among Uygur children in Hotan Prefecture of Xinjiang, China, as well as the factors influencing the development of DM. METHODS: The cluster random sampling method was used to select 5 308 children, aged 4-18 years, from the middle and primary schools and kindergartens in Hotan Prefecture of Xinjiang. The survey methods included questionnaire survey and the measurement of height and weight. All subjects were tested for fasting fingertip blood glucose to investigate the prevalence of DM and impaired fasting glucose (IFG). RESULTS: A total of 5 184 valid questionnaires were collected. Fourteen children (0.27%) were found to have DM, among whom 8 had type 1 DM, 2 had type 2 DM, and 4 had unclassified DM. Twenty-nine children (0.56%) were found to have IFG. There was no significant difference in the prevalence rate of DM and IFG between boys and girls (P>0.05). The prevalence rate of DM was 0.18% in the 4-<10 years group, 0.47% in the 10-<15 years group, and 0.07% in the 15-18 years group (P=0.072).The prevalence rate of IFG in the above three age groups was 0.18%, 0.94%, and 0.42%, respectively, with a significant difference among groups (P=0.007). The proportion of family history of DM and the proportion of overweight/obesity in children with DM were significantly higher than those in children without DM (P<0.05), while the proportion of children with DM who preferred coarse grains was significantly lower than that in children without DM (P<0.05). CONCLUSIONS The prevalence of DM and IFG in Uyghur children in Hotan Prefecture of Xinjiang is relatively low. There is no significant difference in the prevalence of DM among children of different genders or age groups, but the prevalence of IFG in children of different age groups is different. A family history of DM, overweight or obesity, and low intake of coarse grains might be associated with the development of DM.
Adolescent ; Blood Glucose ; Child ; Child, Preschool ; China/epidemiology* ; Female ; Humans ; Male ; Pediatric Obesity ; Prediabetic State/epidemiology* ; Prevalence ; Risk Factors