Abstract MP49: Socioeconomic Status and Metabolic Syndrome Components in Prepubescent Colombian Children
Bibliographic record
Abstract
The association between socioeconomic status (SES) and cardiometabolic risk has been extensively described in developed societies. However, this topic has received little attention in children from developing populations undergoing nutritional transition. Using data from a population-based cross-sectional study of 1,260 children, aged 6-10 y, in Bucaramanga (Colombia), we examined the association between SES and prevalence of metabolic syndrome components (MetS) components. SES was defined according to classification of neighborhood public service fees. High mean blood pressure (≥ 90 th %ile) was determined using sex-, age-, and height-adjusted cut points. For the remaining MetS components we defined internal age- and sex-specific cut points as follows: fasting triglycerides ≥ 90 th %ile; HDL ≤ 10 th %ile; insulin resistance (HOMA-IR) ≥ 90 th %ile; and waist circumference ≥ 90 th %ile. Odds ratios (ORs) and 95% confidence intervals (CIs) for each MetS component were calculated across SES before ( Model 1 ) and after adjustment for measures of early-life nutrition ( Model 2 ) and lifestyle factors ( Model 3 )( Table ). Colombian children from households in high-SES neighborhoods had higher odds of central obesity and insulin resistance, but lower odds of high triglycerides and low HDL cholesterol than their low-SES counterparts ( Table ). ORs for high blood pressure were null. These results suggest that, in low-SES children from nutritionally transitioning populations, blood lipids may emerge as early cardiometabolic risk factors in the absence of central obesity and insulin resistance. These findings highlight the importance of evaluating MetS components individually in prepubescent children. Research is needed to confirm these associations and to understand the cultural and lifestyle factors that may differentiate cardiometabolic risk across SES in children of developing countries.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".