In a recent study published within the journal Nutrients, researchers in america analyze the connection between weight-reduction plan quality and various sleep outcomes within the Bogalusa Heart Study (BHS).

Study: Food plan Quality and Sleep Characteristics in Midlife: The Bogalusa Heart Study. Image Credit: Prostock-studio / Shutterstock.com

Background

Cardiovascular diseases (CVD) are the leading explanation for death in america, with one person dying from CVD every 34 seconds on this country. With about 122 million adults currently living with CVD within the U.S., it’s imperative to discover risk aspects related to the disease to cut back its occurrence.

Certain lifestyle-associated risk aspects, resembling weight-reduction plan and sleep, might be modified to lower CVD risks. Actually, a balanced weight-reduction plan has been shown to stop CVD development, whereas sleep apnea and insomnia have been repeatedly linked to an increased risk of CVD. Studies have largely focused on the association between these activities and health outcomes; subsequently, data on the interaction between nutrition and sleep are limited.

Short-term studies support the concept that weight-reduction plan and sleep are cyclical, as sleep affects next-day food intake, and weight-reduction plan impacts sleep through metabolic pathways. Actually, high-quality diets are reportedly related to improved outcomes of sleep.

Nonetheless, a lot of these studies included non-diverse groups resembling males or females only and Mediterranean weight-reduction plan followers only. One other common limitation of those studies is that many only evaluated one sleep parameter, resembling sleep duration, with a single measure to find out dietary quality.

Concerning the study

In the current cross-sectional study, researchers investigate the association between weight-reduction plan quality and different sleep outcomes, resembling sleep apnea, healthy sleep patterns, and insomnia, within the BHS study cohort of white and black adults of each sexes. The researchers also determined whether the impacts varied by socioeconomic status, race, and sex.

The study cohort consisted of people who participated within the BHS study between 2013 and 2016 and accomplished sleep questionnaires and weight-reduction plan assessments. The Lower Mississippi Delta Nutrition Intervention Research Initiative’s (Delta NIRI) Food Frequency Questionnaire (FFQ) was used to evaluate weight-reduction plan. Over a six-month period, the participants provided 4 one-day weight-reduction plan recalls.

The team matched Delta NIRI components to the U.S. Department of Agriculture (USDA) Food Patterns Equivalent Database (FPED) data published between 2015 and 2016. The Nutrient Database for Scientific Research was used to estimate nutrient intake. The Healthy Eating Index (HEI) 2015, Alternate Healthy Eating Index (AHEI) 2010, and Alternate Mediterranean Dietary Pattern (aMed) were used to construct weight-reduction plan patterns.

The Women’s Health Initiative Insomnia Rating Scale (WHIIRS) was used to evaluate insomnia, whereas the Berlin Questionnaire was used for snoring and sleep apnea, and the healthy sleep pattern scores for overall sleep health. The International Physical Activity Questionnaire (IPAQ) was used to evaluate physical activity, and the full metabolic equivalent of task (MET) minutes per week was determined. The Centres for Epidemiologic Studies Depression (CESD) scale assessed depressive symptoms.

Multivariate Poisson regression modeling was performed using generalized estimating equations (GEE) to estimate prevalence rate ratios (PRRs). Models were adjusted for covariates resembling age, sex, body mass index (BMI), race, physical exertion, level of education, status of employment status, caffeine consumption, depressive symptoms, having bed partners, and frequent usage of sleeping pills.

Data adjustments were also made for household size, census tract Index of Concentration on the Extremes (ICE), pediatric individuals in households, census tract Modified Retail Food Environment Index (mRFEI), smoking habits, alcohol consumption, and illicit use of medicine.

Study findings

Out of 1,298 individuals, 224 individuals with implausible calorie intake exceeding 4,800 kcal/day, 43 individuals with a previous history of stroke or heart attack, 123 worked in shifts, seven individuals with missing sleep or weight-reduction plan data, and 77 individuals with missing covariate data were excluded from the evaluation. Consequently, the ultimate sample cohort included 824 individuals.

The participants’ mean age was 48 years, 30% were black, 36% were men, about 30% had depression, and over 50% were obese. Among the many participants, 44% had an increased risk of insomnia and sleep apnea, whereas sleeping patterns were considered good amongst 23% of the participants.

A mean rating of 45 was obtained for AHEI-2010. Higher AHEI-2010 quintiles were more prone to be observed amongst older individuals, females, more educated individuals, never-smokers, alcohol drinkers, and individuals who weren’t depressed.

Higher food quality, as determined using AHEI 2010 scores, was related to a reduced sleep apnea risk rating post-adjustment. There was no significant relationship between HEI 2015, aMed, insomnia symptoms, or a great sleep rating.

AHEI-2010 and HEI-2015 were inversely related to a high risk of sleep apnea. Individuals in Q5 of the AHEI-2010 had a 41% lower likelihood of being at high risk for sleep apnea than those in Q1. Analyzing AHEI-2010 as a continuous variable showed that the correlation was significant, with a 12% reduced prevalence of high sleep apnea rating per 10-point rise in AHEI-2010.

A greater AHEI-2010 was related to being positive on the sleepiness component but not the snoring component. Within the unadjusted model, the researchers found a modest association between healthy sleep patterns and the AHEI-2010.

The connection between AHEI-2010 and sleep apnea risk was greater amongst women than men. Notably, this relationship was also stronger amongst those with the next level of education.

Fruits, long-chain omega-3 fatty acids, sugar-loaded beverages, red and processed meats, and alcohol had significant inverse associations when comparing Q5 to Q1. The sensitivity evaluation, which was performed by excluding BMI from the covariates, yielded similar results.

Conclusions

Higher food quality was related to reduced sleep apnea risk scores amongst semi-rural, lower-income populations within the southeastern U.S., where health disparities are common. These findings elucidate how weight-reduction plan quality affects sleep and, in consequence, support the incorporation of high-quality food products into health interventions that will improve the efficacy of sleep therapies while concurrently reducing the chance of developing CVD.