Consumption of 100% Fruit Juice and Risk of Obesity and Metabolic Syndrome: Findings from the National Health and Nutrition Examination Survey 1999–2004
Bibliographic record
Abstract
OBJECTIVES: The health effects of added sugars have received much attention, but few studies have examined the association between foods that naturally contain sugar, such as 100% fruit juice, and risk of obesity and related conditions. Therefore, our purpose was to study the association between 100% fruit juice intake and risk of obesity and metabolic syndrome in a representative sample of the U.S. population. METHODS: Cross-sectional analysis of a multiethnic sample of U.S. adults from the National Health and Nutrition Examination Survey 1999-2004 was undertaken to examine the association between 100% fruit juice consumption and the odds of obesity (body mass index [BMI] ≥ 30 kg/m2) and metabolic syndrome (Adult Treatment Panel [ATP] III definition). We used logistic regression analysis to estimate the odds of obesity and metabolic syndrome per category of fruit juice consumption exposure, while adjusting for covariates that may be confounders of this association. RESULTS: Of 14,196 adults included in the sample, 3961 were consumers of fruit juice. Consumers of 100% fruit juice, relative to nonconsumers, had lower mean BMI, lower waist circumference, and lower homeostasis model assessment (HOMA) insulin resistance (p < 0.001). Level of intake (oz/d) had a linear inverse association with HOMA (p < 0.001), whereas the association with BMI and waist circumference was U-shaped (p < 0.001). Consumers relative to nonconsumers had 22% (95% confidence interval [CI] = 13%-30%) lower odds of obesity and 15% (95% CI = 10%-28%) lower odds of metabolic syndrome. After adjustment for demographics and lifestyle factors, the lower odds of obesity remained statistically significant, but a statistically significant reduction in odds of metabolic syndrome was no longer noted. CONCLUSIONS: Compared with nonconsumers, those who consumed 100% fruit juice were leaner, were more insulin sensitive, and had lower odds of obesity and metabolic syndrome. The association with metabolic syndrome was explained primarily by other lifestyle factors, while the association with obesity remained independent. Experimental studies are needed to determine whether any direct physiologic link exists between consumption of 100% fruit juice and lower risks for obesity and metabolic syndrome.
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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 | 0.002 |
| 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".