Background: Information tracking changes of birthweight is scarce in China. To examine trends of low birthweight (birthweight < 2500 g) and macrosomia (birthweight ≥ 4000 g) and potential risk factors in Beijing, hospital records from two major obstetrics and gynecology hospitals in urban districts in Beijing were analyzed. Methods: Hospital records from 1996 to 2010 were retrieved. Information of prenatal examination and birth outcomes was entered into a structured database. Live births were used for trend analysis. Information of live births in 2010 was used to identify potential risk factors. Results: A total of 63 661 live births were delivered during 1996–2010 in the study hospitals. The average birthweight increased from 3271 g in 1996 to 3 359 g in 2000 and slightly declined to 3 331 in 2010. The percentage of low birthweight fluctuated around 4.0%. No significant increase or decrease was observed. Preterm birth was the main cause of low birthweight, accounting for more than 73% of low birthweight. The average percentage of macrosomia was 7.6%. The percentages of macrosomia increased from 6.6% in 1996 to 9.5% in 2000 and declined to 7.0% in 2010. Excessive gestational weight gain and gestational diabetes were significantly associated with macrosomia. Conclusions: Continuously monitoring abnormal birthweight is needed and intervention should focus on appropriate gestational weight gain and reduction of preterm birth and gestational diabetes.

Inappropriate gestational weight gain (GWG) may be associated with postpartum depression,^1,2 cardiometabolic risk,³ and weight retention by the mother,^4-6 in addition to presenting untoward consequences with regard to birth outcomes,^7,8 including preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, small or large size with respect to gestational age at birth,⁹ and unfavorable long-term child health.^10-14 In 2009, the US National Academy of Medicine (NAM, formerly the Institute of Medicine) released revised GWG guidelines¹⁵ that have been widely adopted in many countries. Previous studies have shown that adherence to the NAM recommendations appears to achieve improved pregnancy outcomes¹⁶ and that GWG outside the NAM recommendations may be associated with adverse pregnancy outcomes and unhealthy children’s status.^17-21

The objective of this study is to explore the associations between obesity, body composition, and the self-reported risk of obstructive sleep apnea (OSA) and to examine whether the risk of OSA is related to metabolic abnormalities in children and adolescents aged 6–17 years. Utilizing data from the 2022 to 2023 Beijing Children and Adolescents Health Cohort baseline survey, 5000 school-aged participants were analyzed. OSA risk was assessed via the Pediatric Sleep Questionnaire, with anthropometric and body composition measurements taken. Metabolic markers included blood pressure, lipid levels, blood glucose, and uric acid. Associations were analyzed using logistic regression and generalized linear models. Results showed that 88.6% were low-risk and 11.4% were high-risk for OSA. Overweight (aOR 1.53, 95% CI 1.22–1.92), obesity (aOR 1.94, 95% CI 1.57–2.40), and abdominal obesity (aOR 1.59, 95% CI 1.31–1.93) significantly increased OSA risk. High fat mass was a critical factor, while muscle mass was not, especially in those who were overweight and obese. Associations of OSA risk with metabolic abnormalities were non-significant after adjusting for BMI. Our research highlights the significant associations of obesity and body composition with OSA risk, with child BMI influencing the relationship between OSA and metabolic abnormalities. Future research should explore causative relationships and the enduring impacts of OSA on metabolic health in children.

To assess the relationship between fat mass percentage (FMP) and glucose metabolism in children aged 0–18 years we performed a systematic review of the literature on Medline/PubMed, SinoMed, Embase and Cochrane Library using the PRISMA 2020 guidelines up to 12 October 2021 for observational studies that assessed the relationship of FMP and glucose metabolism. Twenty studies with 18,576 individuals were included in the meta-analysis. The results showed that FMP was significantly associated with fasting plasma glucose (FPG) (r = 0.08, 95% confidence interval (CI): 0.04–0.13, p < 0.001), fasting plasma insulin (INS) (r = 0.48, 95% CI: 0.37–0.57, p < 0.001), and homeostasis model assessment (HOMA)- insulin resistance (IR) (r = 0.44, 95% CI: 0.33–0.53, p < 0.001). The subgroup analysis according to country or overweight and obesity indicated that these associations remained significant between FMP and INS or HOMA-IR. Our results demonstrated that there is a positive relationship between FMP and FPG. Moreover, subgroup analysis according to country or overweight and obesity indicated that FMP is significantly associated with INS and HOMA-IR. This is the first known systematic review and meta-analysis to determine the associations of FMP with glucose metabolism in children and adolescents.

OBJECTIVE: To investigate the impact of factors in the first 1,000 days of life on metabolic phenotypes of obesity in preschool children in a cohort study.RESEARCH DESIGN AND METHODS: We recruited 3-year-old children for the study. Early life factors included maternal age at delivery, maternal education, prepregnancy BMI, gestational weight gain, gravidity, history of gestational diabetes mellitus, delivery mode, gestational age, family history of metabolic disorders, paternal education, annual family income, child sex, birth weight, and breastfeeding duration. According to BMI and metabolic status, children were classified as metabolically healthy (no metabolic risk factors) with normal weight (MHNW), metabolically unhealthy (one or more metabolic risk factors) with normal weight (MUNW), metabolically healthy with overweight or obesity (MHO), and metabolically unhealthy with overweight or obesity (MUO).RESULTS: We recruited 3,822 children for the study, with 3,015 analyzed. Accelerated BMI z score growth rate between 6 and 24 months was associated with MHO (β = 0.022; 95% CI 0.009, 0.036) and MUO (β = 0.037; 95% CI 0.018, 0.056). Maternal overweight (odds ratio [OR] 3.16; 95% CI 1.55, 6.42) and obesity (OR 8.14; 95% CI 3.73, 17.76) before pregnancy and macrosomia (OR 2.47; 95% CI 1.32, 4.59) were associated with MHO, and maternal obesity before pregnancy (OR 6.35; 95% CI 2.17, 18.52) increased the risk of MUO.CONCLUSIONS: Early life factors, such as maternal obesity and accelerated BMI growth rate between 6 and 24 months, were related not only to MHO but also to MUO. Children with these early life factors should be given interventions for weight control to prevent metabolic abnormalities.