Trends in elevated waist-to-height ratio and waist circumference in U.S. adults and their associations with cardiometabolic diseases and cancer, 1999–2018
Bibliographic record
Abstract
Introduction: Although waist-to-height ratio (WHtR) has established association with cardiometabolic disease, the trend of changes in elevated WHtR among general population have not been examined adequately. Methods: This study examined the prevalence of elevated WHtR and waist circumference (WC) and their trends over time using Joinpoint regression models among adults who participated in the United States National Health and Nutrition Examination Survey (U.S. NHANES) 1999-2018. We performed weighted logistic regression to identify the association between central obesity subtypes and the prevalence of comorbidities, including diabetes, chronic kidney disease, hypertension, cardiovascular disease, and cancer. Results: The prevalence of elevated WHtR has increased from 74.8% in 1999-2000 to 82.7% in 2017-2018 while elevated WC also increased from 46.9% in 1999-2000 to 60.3% in 2017-2018. Men, older adults, former smokers, and people with lower education levels were more likely to have elevated WHtR. A total of 25.5% of American adults had normal WC but elevated WHtR, and they had a significantly higher chance of suffering from diabetes (odds ratio [OR] = 2.06 [1.66, 2.55]), hypertension (OR = 1.75 [1.58, 1.93]) and CVD (OR = 1.32 [1.11, 1.57]). Discussion: In conclusion, the burden of elevated WHtR and WC have been increasing among U.S. adults throughout the years, and the changes have been more significant across most subgroups. It is also notable that approximately a quarter of the population had normal WC but elevated WHtR, which had increased likelihood of having cardiometabolic diseases, especially diabetes. Future clinical practices should pay more attention to this subgroup of the population with overlooked health risks.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".