Background: Skeletal muscle as an essential body composition component plays an important role in maintenance of normal growth and development as well as systemic glucose metabolism in children. No nationwide reference data for skeletal muscle mass for Chinese youths are available in China. We aimed to establish the sex‐specific and age‐specific percentile reference values of skeletal muscle mass for Chinese children and adolescents.Methods: This study consisted of 10 818 children and adolescents aged 3–17 years in Chinese urban area during 2013–15. Dual‐energy X‐ray absorptiometry scan was performed to measure whole body muscle mass and appendicular skeletal muscle mass. Lambda‐mu‐sigma method was used to obtain the sex‐specific and age‐specific percentile curves of muscle mass indices.Results: Overall, whole body muscle mass and appendicular skeletal muscle mass indices showed an increasing trend with age for both sexes, with boys vs. girls having higher values of all muscle mass indices. Whole body muscle mass index in boys increased slightly before age 9 years and then increased rapidly until 15 years and slowed down thereafter, while the mean values in girls increased slightly before age 8 years, increased rapidly until 14 years and remained stable thereafter. Appendicular skeletal muscle mass index increased rapidly until age 16 years and then increased slightly for boys; by contrast, for girls, the mean values increased consistently before age 14 years but showed a slightly decreasing trend after that.Conclusions: This study established sex‐specific and age‐specific percentile reference values for skeletal muscle mass for Chinese children and adolescents aged 3–17 years. These reference values can be used to evaluate the muscular development in Chinese children and adolescents.

Up to date, most of previous studies about Chinese prehypertension were conducted based on a small sample or in only one province, which could not represent the general population in China. Furthermore, no information on the ethnic difference in prevalence of prehypertension has been reported in China. The aim of this study is to examine the sex-specific, age-specific and ethnic-specific prevalence of prehypertension and associated risk factors in a large-scale multi-ethnic Chinese adult population. The subjects came from a large-scale population survey about Chinese physiological constants and health conditions conducted in six provinces. 47, 495 adults completed blood pressure measurement. Prehypertension was defined as not being on antihypertensive medications and having SBP of 120–139 mmHg and/or DBP of 80–89 mmHg. Odds ratio (OR) and its 95 % confidence interval (CI) from logistic models were used to reflect the prevalence of prehypertension. The mean age of all subjects was 43.9 ± 16.8 years. The prevalence of hypertension and prehypertension for all them was 29.5 and 36.4 %, respectively. The prevalence of hypertension and prehypertension for males (33.2 and 41.1 %, respectively) was higher than that for females (27.0 and 33.2 %, respectively), and P < 0.001. The mean age of the subjects was 54.8 ± 14.0 years for hypertensive, 44.0 ± 16.0 years for prehypertensive and 35.3 ± 14.5 years for normotensive. With aging, subjects had more odds of getting prehypertension. Multivariate logistic model indicated that males (OR = 2.076, 95 % CI: 1.952–2.208), laborers with mental work (OR = 1.084, 95 % CI: 1.020–1.152), Yi (OR = 1.347, 95 %CI: 1.210–1.500) and Hui subjects (OR = 1.133, 95 % CI: 1.024–1.253), alcohol drinkers (OR = 1.147, 95 % CI: 1.072–1.228), the generally obese (OR = 2.460, 95 % CI: 2.190–2.763), the overweight (OR = 1.667, 95 % CI: 1.563–1.788), the abdominally obese (OR = 1.371, 95 % CI: 1.280–1.467) and subjects with family history of cardiovascular diseases (OR = 1.132, 95 % CI: 1.045–1.226) had higher prevalence of prehypertension. Subjects with higher educational level (OR = 0.687, 95 % CI: 0.627–0.752 for university) and Miao (OR = 0.753, 95 % CI: 0.623–0.910), Tibetan (OR = 0.521, 95 % CI: 0.442–0.613), Tujia (OR = 0.779, 95 % CI: 0.677–0.898) subjects had lower prevalence. High prevalence rate of prehypertension was general in Chinese adults. Many sociodemographic characteristics were significantly associated with prehypertension. There were important clinical significance and public health significance about age-specific, gender-specific and ethnic-specific Chinese prehypertension conditions studies.

There are few studies on lead’s effect on bone mineral density (BMD) in childhood. In this study, we examined the association between lead exposure and BMD among 13,951 children and adolescents aged 8–19 years from NHANES 1999–2006 and 2011–2018. The whole blood lead levels (BLLs) were used as lead exposure biomarkers, and total BMD, subtotal BMD, lumbar spine BMD and limb BMD were used as outcome variables. The survey weighted multivariable generalized additive models (GAMs) with smoothing terms were used to explore the association between blood lead levels and BMDs, adjusted for age, sex, race/ethnicity, height, weight, family-income-to-poverty ratio and blood cadmium. Subgroup analyses stratified by sex and bony sites were further performed. We found an N-shaped curve association between BLLs and total BMD, subtotal BMD and limb BMD for males and females, whereas the association between BLLs and lumbar spine BMD was only significantly negative for females. The findings suggested that lead exposure had different effects on BMD of different bony sites (highly cortical or trabecular regions) in childhood and adolescence and had different effects on the same bone among different ages population and/or at different levels.

Chinese children are facing health challenges brought by chronic non-communicable diseases, such as physical problems and psychological related health problems. Childhood represents a critical life period when the long-term dietary and lifestyle behaviors are formed. It is necessary to survey the prevalence of suboptimal health status (SHS) among Chinese children and to research the relationship between SHS and lifestyles. This study aimed to examine the prevalence of SHS among Chinese children using a large-scale population survey sample covering school students and nonstudent children, and clarified the relationships between SHS and lifestyle factors using multi-level models controlled for the cluster effect of location and the confounding effect of demographics. Multi-level generalized estimating equation models were used to examine the relationships between SHS and lifestyle factors. Prevalence ratios (PR) and 95% confidence intervals (CI) were used to assess the strength of these relationships. Of the 29,560 children, 14,393 reported one or more SHS symptoms, giving a SHS prevalence of 48.69%. The prevalence of SHS for boys (46.07%) was lower than that for girls (51.05%). After controlling for the cluster effect of living areas and confounding effect of demographic characteristics, lifestyle factors associated with SHS were: less sleep duration, current smokers (PR = 1.085, 95%CI: 1.027–1.147), current drinkers (PR = 1.072, 95%CI: 1.016–1.131), children’ parents suffering from chronic diseases (PR = 1.294, 95%CI: 1.179–1.421), poor sleep quality (PR = 1.470, 95%CI: 1.394–1.550), stress (PR = 1.545, 95%CI: 1.398–1.707), negative life events (PR = 1.237, 95%CI: 1.088–1.406), hypertension (PR = 1.046, 95%CI: 1.009–1.084), unhealthy diet choice (PR = 1.091, 95%CI: 1.051–1.133) and irregular meal time (PR = 1.210, 95%CI: 1.163–1.259). Children who could exercise regularly (PR = 0.897, 95%CI: 0.868–0.927) and those with regular medical checkup (PR = 0.891, 95%CI: 0.854–0.929) were associated with lower prevalence probability of SHS. SHS has become a serious public health challenge for Chinese children. Unhealthy lifestyles were closely associated with SHS. Implementation of preventative strategies are needed to reduce the potential SHS burden associated with these widespread high-risk unhealthy lifestyle behaviors.

We explored the joint effects of different metabolic obesity phenotypes on all-cause and disease-specific mortality risk among the American population. Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. Mortality outcome data were from mortality files linked to National Death Index record and follow-up information was up to December 31, 2019. 50,013 participants were finally included. Four metabolic obesity phenotypes were defined based on obesity and metabolic status: metabolically healthy obese (MHO), metabolically unhealthy obese (MUO), metabolically healthy non-obese (MHNO), and metabolically unhealthy non-obese (MUNO). Population-weighted Cox proportional hazards models were used to explore the all-cause and disease-specific mortality risk of metabolic obesity phenotypes. The all-cause mortality risk of MUO and MUNO was significantly higher than MHNO. MUNO was associated with a significantly increased risk of death from heart disease (HR: 1.40, 95% CI 1.16–1.70), hypertension (HR: 1.68, 95% CI 1.34–2.12), diabetes (HR: 2.29, 95% CI 1.67–3.15), and malignant neoplasms (HR:1.29, 95% CI 1.09–1.53). Metabolic unhealth significantly increased the risk of all-cause mortality, regardless of obesity status. Among individuals with metabolic unhealthy status, obesity significantly reduced the risk of all-cause mortality (HR: 0.91, 95% CI 0.85–0.98). Our study highlights the importance of identifying and characterizing metabolic obesity phenotypes in obese and metabolically abnormal patients, as well as healthy adults. Comprehensive evaluation of obesity and metabolic status is necessary to adopt appropriate interventions and treatment measures and maximize patient benefit.

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.