Distribution and related factors of cardiometabolic disease stage based on body mass index level in Chinese adults—The National Diabetes and Metabolic Disorders Survey
Bibliographic record
Abstract
Abstract Background It is important to characterize distribution of cardiometabolic disease (CMD) based on different body mass index (BMI) levels in a population. This information remains scarce in China, so we investigated the proportions and related factors of cardiometabolic disease stages based on different BMI levels in Chinese adults. Methods We included 45 093 participants aged ≥20 years from the National Diabetes and Metabolic Disorders Survey. Cardiometabolic disease (central obesity, elevated triglycerides, elevated blood pressure, elevated plasma glucose, reduced high‐density lipoprotein cholesterol, and cardiovascular disease) was classified as stage 0 (no CMD), stage 1 (mild‐to‐moderate CMD), or stage 2 (severe CMD). Overweight/obesity was defined as BMI ≥25 kg/m2. Results The standardized proportions of stage 0, stage 1, and stage 2 were 32.6%, 36.4%, and 30.9% in normal‐weight men, 29.9%, 42.5%, and 27.7% in normal‐weight women, 4.9%, 31.7%, and 63.4% in overweight/obese men, and 6.9%, 31.4%, and 61.7% in overweight/obese women, respectively. Multinomial regression showed that regardless of gender or region, the probability of severe cardiometabolic disease rapidly increased with increasing BMI. Severe cardiometabolic disease risk was positively associated with ageing, family history of diabetes, hypertension, or cardiovascular disease, but was inversely associated with higher levels of education and increased physical activity. Conclusions Of Chinese men and women with normal weight, more than one third had mild‐to‐moderate cardiometabolic disease, and less than one third had severe cardiometabolic disease, while of these with overweight or obesity, nearly one third had mild‐to‐moderate cardiometabolic disease, and nearly two thirds had severe cardiometabolic disease.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".