Lack of evidence for obesity paradox in patients with cardiovascular disease: A <scp>UK BioBank</scp> cohort study
Bibliographic record
Abstract
AIMS: The obesity paradox has been controversial and is mostly observed when body mass index (BMI) is used. We aimed to examine the presence of the obesity paradox using body fatness (body fat percentage, BF%) and central obesity (waist-to-hip ratio adjusted for BMI, WHRadjBMI). We also used Mendelian randomisation to explore causality for the associations of BMI, BF% and WHRadjBMI with cardiovascular disease (CVD) mortality. MATERIALS AND METHODS: A total of 85 926 participants with CVD from the UK Biobank were included. Prospective associations of BMI, BF% and WHRadjBMI with CVD mortality in these patients were examined. Polygenic risk scores (PRSs) for BMI, BF% and WHRadjBMI were used as instrumental variables in Mendelian randomisation analyses. RESULTS: A total of 5432 patients died of CVD causes during a median follow-up period of 13.6 years. BMI in the overweight and class-I obesity ranges was associated with reduced mortality, with class-II or more severe obesity associated with increased mortality; however, there was a linear trend toward increased mortality with increasing BF% and WHRadjBMI. There was no clear indication that increased obesity-PRSs were associated with reduced risk of CVD mortality among patients with known CVD. Sensitivity analyses by sex, age group and disease type, and by using a single variant from the FTO gene rs1558902 as an instrumental variable showed similar results. CONCLUSION: Increased obesity does not show a protective effect in patients with CVD. Previously reported obesity paradox in observational studies may be a result of confounding or other biases.
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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".