Body Mass Index Is Inversely Associated With Level of Response to Alcohol: Role of Total Body Water
Bibliographic record
Abstract
Objective: A low level of response (LR) to alcohol is a known risk factor for alcohol use disorder (AUD). Although higher total body water (TBW) is associated with lower blood alcohol concentrations and reduced responses following alcohol consumption, the relationship between morphometric measures such as body mass index (BMI) and LR is less clear. This study aimed to examine the relationship between BMI and LR to alcohol and the contribution of TBW to this relationship. Method: Participants (n = 1,086) enrolled in the National Institute on Alcohol Abuse and Alcoholism Natural History Protocol were assessed for LR to alcohol using the Self-Rating of the Effects of Alcohol (SRE) Questionnaire. BMI was estimated using height and weight, and TBW was based on height, weight, age, and sex. Participants were categorized based on BMI into three groups: normal weight (18.5–25.0 kg/m2; n = 430), overweight (25.0–30.0 kg/m2; n = 403), and obese (≥30.0 kg/m2; n = 253). Associations between the BMI group and SRE scores for the most recent 3-month period (SRE-Recent) and the effect of TBW were analyzed using analysis of variance. Linear regression analysis was conducted to estimate the proportion of variation in SRE-Recent, as explained by BMI and TBW. Results: BMI category was associated with LR, with the normal weight group showing higher responses (lower SRE-Recent scores) to alcohol than the overweight or obese groups. After controlling for TBW, the relationship became nonsignificant. Linear regression models confirmed these findings. Conclusions: Higher BMI is associated with lower LR to alcohol. However, TBW seems to account for this relationship, suggesting that concentrations achieved following alcohol consumption may be the primary determinant of BMI-related differences in LR. Future work should replicate these findings and examine these relationships throughout the life span and in individuals with AUD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".