The impact of nutritional supplement intake on diet behavior and obesity outcomes
Bibliographic record
Abstract
After decades-old efforts to nudge consumers towards healthier lifestyles through dietary guidelines, diet-related diseases are on the rise. In addition, a growing share of U.S. consumers proactively chooses nutritional supplements as an alternative preventative way of maintaining good health, a $25.5 billion industry in the United States. This paper investigates possible linkages between the economics of consumer supplement choices and the relationship to important dietary and health outcomes. We use National Health and Nutrition Examination Survey (NHANES) data to estimate the impact of nutritional supplements intake on respondent's body weight outcomes, controlling for diet quality.: The focus of this article is to determine whether nutritional supplements takers differ from non-takers with regard to their health outcomes when controlling for differences in diet quality, based on individual Healthy Eating Index (HEI-2010) score. The analysis applies treatment effects estimators that account for the selection bias and endogeneity of self-reported behavior and diet-health outcomes. The analysis demonstrates a negative association between supplement intake and BMI but no significant effect on an individual's diet quality. Our findings suggest that individuals proactively invest into their health by taking nutritional supplements instead of improving diet quality through more nutritious food choices. Our results provide important contributions to the literature on a key food policy issue. Knowledge of the determinants of supplement demand in the context of strong diet-health trends should also be helpful to stakeholders in the U.S. produce sector in their competition over consumer market share.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".