[Analysis on the trend of overweight and obesity of children and adolescents in 9 provinces of China from 1991 to 2015]

Trends of overweight and obesity prevalence in school-aged children among Henan Province from 2000 to 2019

Objectives

Overweight and obesity are harmful to human health. However, the latest trends of Chinese childhood overweight and obesity prevalence are not available. The aim of this study was to examine the trends from 2000 to 2019 among students in China.

Methods

We analyzed data of 66,072 students in the Chinese National Survey on Students' Constitution and Health from 2000 to 2019. Overweight and obesity were defined based on the standard formulated by the International Obesity Task Force (IOTF standard), the World Health Organization (WHO standard), and the Working Group on Obesity in China (WGOC standard), respectively. The χ²-test was used to test the trends of overweight and obesity prevalence and logistic regression was conducted to evaluate the prevalence odds ratios of boys vs. girls and urban vs. rural areas.

Results

The prevalence of obesity/overweight and obesity combined was 6.03/23.58% (IOTF standard), 10.56/25.88% (WGOC standard) and 10.75/29.69% (WHO standard) in 2019. From 2000 to 2019, according to the WGOC standard, the prevalence increased from 2.51 to 10.56% for obesity and increased from 9.81 to 25.88% for overweight and obesity combined (P for trend < 0.001). Obesity/overweight and obesity were greater problems in boys than girls and urban than rural areas, but urban-rural differences decreased over time.

Conclusion

Overweight and obesity prevalence increased significantly in children and adolescents in China from 2000 to 2019. The prevalence of overweight and obesity in rural areas may contribute to a large percentage of children with overweight and obesity.

Association Between Trajectory Patterns of Body Mass Index Change Up to 10 Months and Early Gut Microbiota in Preterm Infants

Recent research suggests that gut microbiota plays an important role in the occurrence and development of excessive weight and obesity, and the early-life gut microbiota may be correlated with weight gain and later growth. However, the association between neonatal gut microbiota, particularly in preterm infants, and excessive weight and obesity remains unclear. To evaluate the relationship between gut microbiota and body mass index (BMI) growth trajectories in preterm infants, we examined microbial composition by performing 16S rDNA gene sequencing on the fecal samples from 75 preterm infants within 3 months after birth who were hospitalized in the neonatal intensive care unit of Hunan Children’s Hospital from August 1, 2018 to October 31, 2019. Then, we collected their physical growth information during 0–10 months. Latent growth mixture models were used to estimate growth trajectories of infantile BMI, and the relationship between the gut microbiota and the BMI growth trajectories was analyzed. The results demonstrated that there were 63,305 and 61 operational taxonomic units in the higher BMI group (n = 18), the lower BMI group (n = 51), and the BMI catch-up group (n = 6), respectively. There were significant differences in the abundance of the gut microbiota, but no significant differences in the diversity of it between the lower and the higher BMI group. The BMI growth trajectories could not be clearly distinguished because principal component analysis showed that gut microbiota composition among these three groups was similar. The three groups were dominated by Firmicutes and Proteobacteria in gut microbiota composition, and the abundance of Lactobacillus in the higher BMI group was significantly different from the lower BMI group. Further intervention experiments and dynamic monitoring are needed to determine the causal relationship between gut microbiota differences and the BMI change.

Exploration of the minimum necessary FVIII level at different physical activity levels in pediatric patients with hemophilia A

BACKGROUND

Physical activity can increase joint stability and reduce the risk of injury in hemophilia patients. There is limited clinical data on target trough FVIII levels during physical activity in hemophilia A patients. Hence, this study aimed to explore the target trough FVIII level required to avoid bleeding during different physical activities in hemophilia A patients.

METHODS

Patients with severe or moderate hemophilia A, who underwent pharmacokinetics (PK) tests at our center were enrolled in this study. Physical activities and clinical information such as bleeding were recorded. The FVIII level during physical activity was calculated by the WAPPS-Hemo.

RESULTS

A total of 105 patients were enrolled in this study. A total of 373 physical activities were recorded, of which 57.6% (215/373) was low-risk activities and the remaining 42.4% (158/373) was medium-risk activities. Most common physical activities were bicycling (59.0%), swimming (43.8%), running (48.6%), and jumping rope (41.0%). The FVIII trough level of low-risk physical activity was 3.8 IU/dl (AUC = 0.781, p = 0.002) and moderate-risk physical activity was 7.7 IU/dl (AUC = 0.809, p < 0.001). FVIII trough levels [low-risk activities: 6.1 (3.1, 13.2) IU/dl vs. 7.7 (2.3, 10.5) IU/dl, moderate-risk activities: 9.6 (5.8, 16.9) IU/dl vs. 10.2 (5.5, 11.0) IU/dl] were not statistically different between the mild arthropathy group and the moderate-severe arthropathy group. Multiple bleeding risk tended to increase with physical activities classified as moderate-risk (OR [95% CI]: 3.815 [1.766-8.238], p = 0.001).

CONCLUSION

The minimum necessary FVIII level increased with higher risk physical activity, irrespective of arthropathy.

Analysis of risk factors and construction of a prediction model for short stature in children

BACKGROUND

Short stature in children is an important global health issue. This study aimed to analyze the risk factors associated with short stature and to construct a clinical prediction model and risk classification system for short stature.

METHODS

This cross-sectional study included 12,504 children aged 6-14 years of age from 13 primary and secondary schools in Pingshan District, Shenzhen. A physical examination was performed to measure the height and weight of the children. Questionnaires were used to obtain information about children and their parents, including sex, age, family environment, social environment, maternal conditions during pregnancy, birth and feeding, and lifestyle. The age confounding variable was adjusted through a 1 : 1 propensity score matching (PSM) analysis and 1,076 children were selected for risk factor analysis.

RESULTS

The prevalence of short stature in children aged 6-14 years was 4.3% in the Pingshan District, Shenzhen. The multivariate logistic regression model showed that the influencing factors for short stature were father's height, mother's height, annual family income, father's level of education and parents' concern for their children's height in the future (P < 0.05). Based on the short stature multivariate logistic regression model, a short stature nomogram prediction model was constructed. The area under the ROC curve (AUC) was 0.748, indicating a good degree of discrimination of the nomogram. According to the calibration curve, the Hosmer-Lemesio test value was 0.917, and the model was considered to be accurate. Based on a risk classification system derived from the nomogram prediction model, the total score of the nomogram was 127.5, which is considered the cutoff point to divides all children into low-risk and high-risk groups.

CONCLUSION

This study analyzed the risk factors for short stature in children and constructed a nomogram prediction model and a risk classification system based on these risk factors, as well as providing short stature screening and assessment individually.

The Causes of Death and Their Influence in Life Expectancy of Children Aged 5-14 Years in Low- and Middle-Income Countries From 1990 to 2019

INTRODUCTION

Although child and adolescent health is the core of the global health agenda, the cause of death and its expected contribution to life expectancy (LE) among those aged 5-14 are under-researched across countries, especially in low- and middle-income countries (LMICs).

METHODS

Death rates per 10 years age group including a 5-14-year-old group were calculated by the formula, which used the population and the number of deaths segmented by the cause of death and gender from the 2019 Global Burden of Disease (GBD) study. LE and cause-eliminated LE in 10-year intervals were calculated by using life tables.

RESULTS

In 2019, the global mortality rate for children and adolescents aged 5-14 years was 0.522 (0.476-0.575) per 1,000, and its LF was 71.377 years. In different-income regions, considerable heterogeneity remains in the ranking of cause of death aged 5-14 years. The top three causes of death in low-income countries (LICs) are enteric infections [0.141 (0.098-0.201) per 1,000], other infectious diseases [0.103 (0.073-0.148) per 1,000], and neglected tropical diseases and malaria [0.102 (0.054-0.172) per 1,000]. Eliminating these mortality rates can increase the life expectancy of the 5-14 age group by 0.085, 0.062, and 0.061 years, respectively. The top three causes of death in upper-middle income countries (upper MICs) are unintentional injuries [0.066 (0.061-0.072) per 1,000], neoplasm [0.046 (0.041-0.050) per 1,000], and transport injuries [0.045 (0.041-0.049) per 1,000]. Eliminating these mortality rates can increase the life expectancy of the 5-14 age group by 0.045, 0.031, and 0.030 years, respectively.

CONCLUSION

The mortality rate for children and adolescents aged 5-14 years among LMICs remains high. Considerable heterogeneity was observed in the main causes of death among regions. According to the main causes of death at 5-14 years old in different regions and countries at different economic levels, governments should put their priority in tailoring their own strategies to decrease preventable mortality.

Visceral adiposity index performed better than traditional adiposity indicators in predicting unhealthy metabolic phenotype among Chinese children and adolescents

The relationship between visceral adiposity index (VAI) and unhealthy metabolic phenotype remained unclear in children and adolescents. This study aimed to investigate their association and compared the ability of VAI and traditional adiposity indicators (body mass index, waist circumference and waist-to-height ratio) to predict metabolically unhealthy phenotype among normal-weight, overweight and obese children and adolescents. In this cross-sectional study, 1722 children and adolescents aged 12-18 years were selected by cluster random sampling, underwent a questionnaire survey, physical examination and biochemical tests. Participants were divided into four phenotypes according to the combination of the weight status determined by body mass index (BMI) and metabolic syndrome components. Receiver operating characteristic (ROC) analysis and multivariate logistic regression were used to compare the predictive capacity between VAI and traditional adiposity indicators and their relationship with metabolically unhealthy phenotype. We found that VAI had better performance in predicting metabolically unhealthy phenotype than traditional adiposity indicators, the area under the receiver-operating characteristic curve (AUC) were 0.808 and 0.763 for boys and girls with normal-weight, 0.829 and 0.816 for boys and girls with overweight and obese (all P < 0.001). VAI was most strongly related to metabolically unhealthy phenotype whether or not to adjust the age, the adjusted OR and 95%CI was 6.15 (4.13-9.14) in boys with normal weight, and 5.90 (3.06-11.36), 4.95 (2.35-10.41) in boys and girls with overweight and obese, respectively (all P < 0.001). Our findings suggested VAI could be used as a comprehensive predictor to identify unhealthy metabolic phenotype in children and adolescents.

Association between parental socioeconomic status and offspring overweight/obesity from the China Family Panel Studies: a longitudinal survey

OBJECTIVE

To examine the association between parental socioeconomic status (SES) and the risk of offspring overweight/obesity and the changes of the association that occur as children grow older.

DESIGN

We used data from the nationally representative longitudinal survey of the China Family Panel Studies of 2010 and its three follow-up waves in 2012, 2014 and 2016.

PARTICIPANTS

A total of 6724 children aged 0-15 years old were included.

PRIMARY AND SECONDARY OUTCOME MEASURES

Average household income and paternal and maternal education levels were used as SES indicators. Logistic regression model for panel data was used to examine the associations between SES indicators and child overweight/obesity. A restricted cubic spline linear regression model was used to estimate body mass index (BMI) trajectories with child growth across parental SES levels.

RESULTS

Compared with the lowest education level (primary school or less), the ORs for fathers who had completed junior high school, senior high school and junior college or higher were 0.85 (95% CI 0.75 to 0.97), 0.77 (95% CI 0.64 to 0.92) and 0.72 (95% CI 0.55 to 0.93), respectively. The corresponding ORs for mothers were 0.76 (95% CI 0.67 to 0.86), 0.59 (95% CI 0.47 to 0.72) and 0.45 (95% CI 0.34 to 0.60), respectively. A negative association between parental education and offspring overweight/obesity was observed in the first 10 years but not in children 11-15 years old. BMI differences across parental education levels emerged from birth and widened before 6-7 years old, but decreased before adolescence. High average household income was related to a low risk of offspring overweight/obesity but not when parental education level was adjusted for.

CONCLUSION

High parental education levels were associated with a low risk of offspring overweight/obesity, especially before adolescence. Effective approaches need to be adopted in early childhood to reduce socioeconomic differences in overweight/obesity.