Determinants of central obesity in children and adolescents and associated complications in South Africa: a systematic review
Bibliographic record
Abstract
Background: Central obesity in children is a global health concern associated with cardiovascular risk factors. In 2019 the World Obesity Federation predicted that in 2025, 206 million children and adolescents aged 5 to 19 will be obese, and the number is estimated to reach 254 million by 2030. There is limited literature on the factors that are associated with the development of central obesity in children. We report a systematic review, aimed to describe the current literature on determinants of central obesity and its associated health outcomes in children and adolescents in the South African population. Methods: We searched for peer-reviewed studies in Google Scholar, PubMed, and Science Direct search engines, and about seven studies were included. This systematic review has been registered with the International Prospective Register of Systematic Reviews (PROSPERO) (Registration number: CRD42023457012). This systematic review was conducted and reported according to an updated version of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. The quality of the included studies was assessed by following guidelines from the Newcastle-Ottawa Scale (NOS). The method considered three main domains: selection, comparability, and outcome across different study designs. Results: The prevalence of central obesity in children and adolescents by waist-to-height ratio (WHtR) ranged from 2.0 to 41.0%; waist-to-hip [WHR ranged from 10 to 25%; waist circumference (WC) ranged from 9 to 35%]. Central obesity was associated with age, physical inactivity, gender socio, and demographic profiles of the household. Central obesity in children was associated with cardiovascular diseases and mental health issues. Conclusion: Central obesity in children and adolescents was determined by gender, pubertal development, and age of the parents, households with high socioeconomic status, dietary practices, and overweight/obesity. Given the high prevalence of central obesity in children which can ultimately result in cardiometabolic diseases, cardiovascular risk factors, and mental health issues. This highlights the need for systems, jointly initiated by healthcare providers, policymakers, and the general society aimed at reducing the burden of central obesity such as introducing children and adolescents to health-promoting lifestyles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".