Changes in the prevalence of chronic conditions associated with abdominal obesity between 1999 and 2014
Bibliographic record
Abstract
To examine the trends in chronic conditions after accounting for temporal differences in body mass index (BMI) and waist circumference (WC). Pooled cycles (1999-2014) of the U.S. National Health and Nutrition Examination Survey (NHANES) were analysed (n = 36 959). The models were adjusted for caloric intake, smoking, medications use and physical activity. The prevalence of diabetes increased in women with general or abdominal obesity (BMI*time; WC*time, P < .05), but there were no differences in men. For hypertension, independent of BMI, the prevalence was not different over time in both sexes (P > .05), whereas for a given WC, there was a decrease in the prevalence over time in women (WC*time, P = .05). For dyslipidemia, independent of BMI, the prevalence decreased in men, whereas for a given WC, there was a decrease in the prevalence in both sexes (P < .05). Over the same time frame, blood pressure, low-density lipoprotein and triglycerides decreased, while plasma glucose increased independent of general and abdominal obesity (P < .001). The relationship between obesity and chronic conditions has changed over time. There may be other changes that have altered how obesity is related with metabolic health markers over time. Further investigation is needed to better understand the current causes of chronic conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".