Prevalence of the metabolic syndrome between 1999 and 2014 in the United States adult population and the impact of the 2007–2008 recession: an NHANES study
Bibliographic record
Abstract
To document changes in prevalence of the metabolic syndrome (MetS) in the United States adult population between 1999 and 2014 and to explore how variations in the dietary intakes explain changes in MetS prevalence and its components over time. A total of 38 541 individuals (aged 20–85 years; National Health and Nutrition Examination Survey 1999–2014) were studied. Outcome variables were MetS, waist circumference (WC), plasma high-density lipoprotein cholesterol (HDL-c), triglycerides, fasting glucose (FG) levels, resting systolic and diastolic blood pressure, dietary intakes (total daily energy, carbohydrates, proteins, fats, sodium, and alcohol intakes), the poverty income ratio (PIR) and sociodemographic data (age, sex, ethnicity). Overall, the prevalence of the MetS significantly increased between 1999 and 2014 (27.9% to 31.5%). High plasma FG levels and high WC increased between 1999 and 2014, while the prevalence of the other components of MetS decreased or remained stable. Interestingly, a significant peak in MetS prevalence was observed in 2007–2008 compared with 1999–2006 (34.4% vs 27.6%), accompanied by a concomitant increase in WC and plasma FG levels, as well as a decrease in plasma HDL-c. Finally, significant decreases were observed for the PIR, total daily energy intake, sodium, and all macronutrient intakes in 2007–2008 compared with 1999–2006 (all P < 0.01). Results showed that the MetS prevalence significantly increased between 1999 and 2014 in the United States adult population, with a peak in 2007–2008. Interestingly, the 2007–2008 peak in MetS prevalence was accompanied by decreases in the PIR, total daily energy, and macronutrients intakes, suggesting potential impact of the 2007–2008 recession.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".