Validation of self-reported anthropometrics in the Adventist Health Study 2
Bibliographic record
Abstract
BACKGROUND: Relying on self-reported anthropometric data is often the only feasible way of studying large populations. In this context, there are no studies assessing the validity of anthropometrics in a mostly vegetarian population. The objective of this study was to evaluate the validity of self-reported anthropometrics in the Adventist Health Study 2 (AHS-2). METHODS: We selected a representative sample of 911 participants of AHS-2, a cohort of over 96,000 adult Adventists in the USA and Canada. Then we compared their measured weight and height with those self-reported at baseline. We calculated the validity of the anthropometrics as continuous variables, and as categorical variables for the definition of obesity. RESULTS: On average, participants underestimated their weight by 0.20 kg, and overestimated their height by 1.57 cm resulting in underestimation of body mass index (BMI) by 0.61 kg/m(2). The agreement between self-reported and measured BMI (as a continuous variable), as estimated by intraclass correlation coefficient, was 0.97. The sensitivity of self-reported BMI to detect obesity was 0.81, the specificity 0.97, the predictive positive value 0.93, the predictive negative value 0.92, and the Kappa index 0.81. The percentage of absolute agreement for each category of BMI (normoweight, overweight, and obese) was 83.4%. After multivariate analyses, predictors of differences between self-reported and measured BMI were obesity, soy consumption and the type of dietary pattern. CONCLUSIONS: Self-reported anthropometric data showed high validity in a representative subsample of the AHS-2 being valid enough to be used in epidemiological studies, although it can lead to some underestimation of obesity.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".