Associations of body fat and inflammation with non-communicable chronic diseases and mortality: A prospective cohort study
Bibliographic record
Abstract
Abstract Introduction Certain leading medical organizations are considering alternatives to the body mass index (BMI) as a predictor of the risk for non-communicable chronic disease (NCD) or death. Our objective was to evaluate the associations between various measures of body fat and the risk of incident NCDs or mortality, independent of inflammation. Methods This was a population-based prospective cohort study (the UK Biobank cohort) set in the United Kingdom. The participants (between 40 and 69 years) accrued between March 2006 and October 2010, and followed until December 2022. The exposures were BMI, waist:hip ratio (WHR), bioimpedance analysis-measured body fat (fat BIA ), C-reactive protein (CRP) and various other measures of body fat obtained by dual-energy X-ray absorptiometry (including visceral adipose tissue) and magnetic resonance imaging. The outcomes were all-cause death, cardiovascular disease (heart failure, hypertension, myocardial infarction, pulmonary embolism, and stroke), cancers (breast, colorectal, endometrial, esophageal, kidney, ovarian, pancreatic, and prostate), diabetes, asthma, gallbladder disease, chronic back pain, and osteoarthritis. Results There were 500,107 participants: the median age was 58 years (interquartile range 50-63) at baseline and 45.6% were male. The 5 th and 95 th %iles for measures of body fat were: BMI 20.5 (considered “healthy”) and 37.0 kg/m 2 (considered “unhealthy”), WHR 0.71 and 0.94, BIA 24.8 and 47.6% in females, and in males BMI 22.0 (considered “healthy”) and 35.4 kg/m 2 (considered “unhealthy”), WHR 0.83 and 1.05, BIA 15.5 and 34.7%. BMI was strongly correlated to fat BIA (0.85 in females, 0.80 in males) but less so with WHR (0.46 in females, 0.59 in males). All measures of body fat were positively associated with the incidence of NCDs but only WHR remained positively associated with death after full adjustment (HR 95 th %ile vs 5 th %ile [95%CI]: BMI 0.80 [0.76,0.84], WHR 1.21 [1.16,1.28], BIA 0.80 [0.76,0.84] in females; BMI 0.89 [0.85,0.93], WHR 1.19 [1.14,1.24], BIA 0.89 [0.85,0.92] in males). Simpler models that adjusted for age, sex, CRP, WHR and either BMI or fat BIA gave similar results. Associations between body fat and the incidence of NCDs after accounting for the competing risk of death were also similar. Conclusion BMI was strongly correlated with fat BIA , but WHR and VAT DXA were less so. All measures of body fat were associated with the incidence of NCDs but only WHR was independently associated with mortality. These findings support the hypothesis that body fat may be protective against death, and that the excess risk associated with higher WHR may be mediated by something other than body fat. Key Questions What is already known about this topic? Obesity as measured by body mass index is associated with chronic disease but less so with mortality. Less is known about alternative measures of body fat. What this study adds? Body mass index is strongly correlated with body fat as measured by bioimpedance analysis, but less so with the waist:hip ratio and visceral adipose tissue. All measures of body fat were associated with the incidence of chronic disease but only the waist:hip ratio was independently associated with mortality. How this study might affect research, practice or policy? These findings support the hypothesis that body fat may be protective against death, and that the excess risk associated with higher waist:hip ratio may be mediated by something other than body fat.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".