Routine metabolic screening and simple body-composition measures should be embedded in paediatric obesity clinics, with screen-time reduction as a counselling priority.
Abstract
Childhood obesity-related metabolic complications are common in Northwest China, yet region-specific evidence and risk-stratification tools are lacking. In a single-visit cross-sectional study of 131 children (3–18 years) with overweight or obesity attending a Gansu maternal and child-care hospital, obesity-related metabolic complications (ORMC) were present in 31.3% (dyslipidaemia 16.0%, hyperuricaemia 9.2%, elevated blood pressure 7.6%). An interpretable model combining LASSO-selected adiposity measures (body mass index, neck circumference, body fat percentage) with penalised logistic regression achieved moderate, internally cross-validated discrimination (AUC 0.72, 95% CI 0.62-0.82) that awaits external validation, comparable to a random forest (0.73). Screen time was the strongest modifiable behavioural correlate. Routine metabolic screening and simple body-composition measures should be embedded in paediatric obesity clinics, with screen-time reduction as a counselling priority.
BACKGROUND
Lean metabolic dysfunction-associated steatotic liver disease (MASLD) can be overlooked in adults with a normal body mass index (BMI). We examined whether waist-to-height ratio (WHtR), a simple marker of central adiposity, was associated with prevalent lean MASLD and explored its relative contribution within...
Zi-Teng Wang, Wen-Tao Tan, Jing Luo et al.· Clinical Nutrition ESPEN· 0 citations
An explainable machine learning framework for MetS prediction based on non-invasive demographic, anthropometric, and behavioral variables provided moderate discrimination of prevalent MetS and may serve as candidate pre-laboratory risk-stratification tools.
Islam A. Berdaweel, S. Al-Azzam, Ghaith M. Al-Taani et al.· Diagnostics· 0 citations
Abstract Background Undiagnosed prediabetes and type 2 diabetes are major public health challenges. Machine learning tools utilizing anthropometrics effectively predict dysglycemia, but poor diet is a fundamental driver of metabolic dysfunction. This study investigates whether incorporating granular diet quality data i...
D. Yoo, T. Rebelo, VK Nguyen et al.· European Journal of Public H...· 0 citations
Childhood obesity is increasingly accompanied by metabolic dysfunction-associated steatotic liver disease (MASLD), creating a need for accessible screening strategies in routine clinical care. We aimed to develop and externally validate a machine learning (ML) model based on routinely available clinical data to i...
Wu Yan, Xiao-Yan Shi, Jin-Chao Hua et al.· BMC Medical Informatics and...· 0 citations
Background: Normal body mass index (BMI) does not necessarily indicate normal adiposity, and individuals with normal-weight obesity (NWO) may exhibit cardiometabolic abnormalities that remain undetected by BMI-based classification. We examined the cardiometabolic phenotype associated with NWO among adults with normal B...
P. J. Tárraga Marcos, Á. López-González, Emilio Martínez-Almoyna Rifá et al.· Academic Journal of Health S...· 0 citations
Abstract Metabolic syndrome (MetS) is a major risk factor for cardiovascular disease, and its prevalence continues to increase worldwide. In Japan, one of the most rapidly aging societies, approximately one in four individuals aged 40–74 years has MetS or is at high risk, making prevention an urgent public health pri...
A. Ozawa, T. Okawa, H. Arai et al.· European Journal of Public H...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
