Analysis of NHANES 2005–2016 Data Showed Significant Association Between Micro and Macronutrient Intake and Various Sleep Variables (P06-103-19)
Bibliographic record
Abstract
To understand the association between micro and macronutrient intake and sleep variables from the National Health and Nutrition Evaluation Survey (NHANES, 2005–2016). Data analysis was performed using SAS 9.4; regression analysis was used to assess the relationship (p < 0.05) of nutrient intake with sleep variables. All nutrients were individual usual intakes determined using the National Cancer Institute method from food plus supplements; covariates included age, gender, ethnicity, poverty income ration, current smoking status and physical activity level. Individuals 16+ years of age were included in the analysis; pregnant or lactating females and those with unreliable dietary recalls were excluded in the analysis. Seven (7) Sleep variables included in the analysis were short sleep hours (<7 hrs of sleep) and trouble sleeping (NHANES 2005–2016), sleep disorder (NHANES, 2005–2014) and poor sleep quality, insomnia, sleep latency, and use of sleeping pills >5 times in the last month (NHANES 2005–2008). In adults (males and females) 19+ years, 32.7% experienced short sleep; 47.3% poor sleep quality; 8.94% a sleep disorder; 37.9% sleep latency; 9.30% used sleeping pills; 15.1% exhibited insomnia; and 27.7% experienced sleep trouble. Within this population, short sleep was significantly (p < 0.05) associated with the greatest number of nutrients; showing an inverse association with magnesium, niacin, vitamin D, calcium, and dietary fiber intake. Across all seven sleep variables, however, magnesium, niacin and vitamin D demonstrated significant (p < 0.05) inverse association within this population. Inverse associations were also found for dietary fiber intake and short sleep and sleep disorder; phosphorus intake and poor sleep quality, sleep latency and sleep pill use; and vitamin K intake and poor sleep quality, sleep disorder, sleep latency and sleep pill use in the gender combined adults 19+ years. Within this population however, there were direct associations for the intakes of protein and vitamin B6 and short sleep, sleep disorder and sleep trouble; for the intakes of sodium and vitamin A and poor sleep quality, sleep latency and sleep pill use; for the intake of vitamin B12 and poor ADL and insomnia; and for the intake of zinc and sleep quality, sleep latency, sleep pill use, poor ADL and insomnia. Among female adults 19+ years, dietary fiber was the only nutrient that showed an inverse association with all seven sleep variables. These findings demonstrate the importance of micro and macronutrient intake on numerous sleep variables. This analysis was funded by Pharmavite, LLC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.004 | 0.001 |
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".