Analysis of NHANES 2005–2016 Data Showed Significant Association Between Micro and Macronutrient Intake and Various Sleep Variables (P06-103-19). (13th June 2019)

• Record Type: Journal Article
• Authors: Ikonte, Chioma; Reider, Carroll; Fulgoni, Victor; Mitmesser, Susan
• Is Part Of: Current developments in nutrition. Volume 3(2019)Supplement 1
• Publication Date: 2019-06-13
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzz031.P06-103-19
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: To understand the association between micro and macronutrient intake and sleep variables from the National Health and Nutrition Evaluation Survey (NHANES, 2005–2016). Methods: 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). Results: 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. Conclusions: These findings demonstrate the importance of micro and macronutrient intake on numerous sleep variables. Funding Sources: This analysis was funded by Pharmavite, LLC.