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Background: Changes in sleep patterns and body weight occur during pregnancy, yet it is unclear whether sleep patterns are related to gestational weight gain (GWG). This study examined the relationship between maternal sleep across pregnancy and excessive GWG. Methods: Participants from the Michigan Archive for Research on Child Health (MARCH) cohort study, who had singleton births and provided information on fall-asleep and wake-up times during early (first or second) and the third trimesters, were included (n = 372). Changes in sleep duration and sleep midpoints throughout pregnancy were calculated. Prepregnancy weight and the last maternal weight before delivery were used to calculate GWG, which was categorized into groups (inadequate, adequate, and excessive). Poisson regression models were used to examine associations between sleep changes and excessive GWG, adjusted for age, race, gestational age, prepregnancy body mass index, income, fetus gender, physical activity, added sugar, and fruit and vegetable intake. Results: Excessive GWG was observed in 46.5% of women, and was more common among those with prepregnancy obesity (p < 0.001). Women who delayed sleep midpoint by 1 hour (or more) from the early trimester assessment to the third trimester experienced higher risk of excessive GWG (Risk ratio: 1.3; 95% confidence interval: 1.1-1.7). Single time points of sleep duration and sleep midpoint or changes in sleep duration were not related to GWG. Conclusions: Delay in sleep midpoint from early-mid pregnancy to the third trimester was associated with excessive GWG. Health professionals should consider changes in sleep patterns during pregnancy to identify those prone to excessive GWG.

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BACKGROUND: Manganese (Mn) is an essential micronutrient, but inadequate or excess Mn intake can have a detrimental impact on human health. Despite the essentiality, little is known about the relationship between Mn and sleep. OBJECTIVE: This study aimed to examine the relationship between blood Mn concentrations and sleep outcomes in US adults. METHODS: This cross-sectional study used data on blood Mn and sleep from the 2017-2020 National Health and Nutrition Examination Survey (NHANES) (n = 8356, age ≥18 y). Multivariable logistic regression was used to examine associations between quintiles of blood Mn concentrations and subjective sleep outcomes (short sleep duration, late sleep midpoint, trouble sleeping, and obstructive sleep apnea [OSA] symptoms), adjusting for age, gender, body mass index, race/ethnicity, income, smoking, inflammation-adjusted serum ferritin concentration (iron status), caffeine, and alcohol intake. Gender-stratified models were used due to interactions with gender. RESULTS: The mean (SE) blood Mn concentration was 9.7 (0.1) µg/L in US adults. In males, a nonlinear association was noted in the relationship between blood Mn levels and short sleep duration on weekdays and weekends. The third Mn quintile (Q3) group had lower odds of short sleep duration (<7 h) on weekdays (odds ratio [OR]=0.6, 95% confidence interval [CI]: 0.4, 0.9) than the lowest Mn quintile (Q1, reference) after adjusting for covariates in males. The second Mn quintile (Q2) group had lower odds of late sleep midpoint on weekdays than Q1 (OR=0.6, 95% CI: 0.4, 0.8). In females, Q2 group had lower odds of OSA symptoms than Q1 (OR: 0.6, 95% CI: 0.4, 0.9). No relationship was noted between Mn and trouble sleeping. CONCLUSIONS: Gender differences exist in the association between Mn and sleep in adults. Q1 group had the poorest sleep outcomes, including higher odds of short sleep duration (in males), late sleep midpoint (in males), and OSA symptoms (in females).

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Introduction: Poor sleep health during pregnancy is related to adverse pregnancy outcomes. This study aims to identify sociodemographic characteristics associated with sleep health during pregnancy and to examine how they relate to changes in sleep during pregnancy. Materials and Methods: Participants (n = 458) were from the Michigan Archive for Research on Child Health, which is a prospective pregnancy cohort. Sociodemographic characteristics and self-reported sleep timing and quality were collected in phone interviews. This longitudinal study collected sleep parameters once during the early trimesters and once during the third trimester. Fall asleep and wake-up times were used to calculate sleep duration and sleep midpoint. Results: Compared to the third trimester, sleep duration was 12 minutes longer (p = 0.02), fall asleep time was 21 minutes earlier (p < 0.001), and the midpoint of sleep was 12 minutes earlier (p = 0.01) in early trimesters. Shorter sleep duration was noted in younger women. Sleep midpoint was later in those who were younger, overweight, or obese, racial minorities, unmarried, and with lower educational levels or socioeconomic status, and who smoked before pregnancy after adjusting for covariates. After controlling for confounders, women who were not working for pay had higher likelihood of reduced sleep duration, and women who were unmarried were more likely to have a delayed sleep midpoint in the third trimester compared to the early trimesters. Conclusions: This study suggests that sleep parameters changed during pregnancy and sleep health differed by sociodemographic characteristics. Understanding sleep disparities could help with early detection of at-risk populations during prenatal care.

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Current literature has identified relationships among sleep, nutrition, and diet-related chronic diseases; however, knowledge about how sleep influences diet-related diseases is lacking in dietetics practice. This narrative review briefly explains sleep physiology and outlines the relationships between sleep duration and quality and common nutrition-related diseases, including obesity, diabetes, cardiovascular disease, obstructive sleep apnea, and cancer. Additionally, the review discusses how sleep influences wound healing and pregnancy outcomes and why hospitalized patients are likely to experience sleep problems. Plausible mechanisms explaining the relationships between sleep and disease are presented. Finally, commonly used sleep assessment tools and interventions are reviewed. Given the importance of sleep to health, dietitians should not only be aware of the role sleep plays in disease development and prevention but also assess sleep when feasible and refer patients and clients who are at high risk for sleep problems to a sleep clinic or community program that can address sleep issues.Teaching points:Sleep duration and quality influence risk and outcomes of common nutrition-related diseases.Sleep health evaluation is a missing piece in dietetic practice.There are easy-to-use, validated tools that dietitians can use to screen for sleep problems in order to refer patients and clients to sleep experts.

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Media use has been linked to sleep disturbance, but the results are inconsistent. This study explores moderating conditions. A media diary study with 58 free-living adults measured the time spent with media before bed, the location of use, and multitasking. Electroencephalography (EEG) captured bedtime, total sleep time, and the percent of time spent in deep (Stage N3), and rapid eye movement (REM) sleep. Media use in the hour before sleep onset was associated with an earlier bedtime. If the before bed use did not involve multitasking and was conducted in bed, that use was also associated with more total sleep time. Media use duration was positively associated with (later) bedtime and negatively associated with total sleep time. Sleep quality, operationalised as the percent of total sleep time spent in N3 and REM sleep, was unaffected by media use before bed. Bedtime media use might not be as detrimental for sleep as some previous research has shown. Important contextual variables moderate the relationship, such as location, multitasking, and session length.

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There is a growing body of literature that links chronotype to certain undesirable eating behaviors. However, the relationship between chronotype and dietary intake is poorly characterized among adults in the United States (U.S.). This cross-sectional study examined the associations among chronotype, snacking habits, dietary intake and quality, and food cravings. One-hundred adults living in the U.S. completed the study. Based on the Horne-Östberg Morningness-Eveningness Questionnaire score, an individual was categorized as having either a morning (M)-type, intermediate (I)-type, or evening (E)-type chronotype. Snack intake was assessed using a previously published specialized food frequency questionnaire. Sugar-sweetened beverage (SSB) intake was assessed using the updated version of the Beverage Intake Questionnaire-15. Alcohol misuse was measured using the Alcohol Use Disorders Identification Test-Consumption. Diet quality was obtained using the Diet History Questionnaire III. The validated General Food Cravings Questionnaire-Trait measured participants' food cravings. E-type individuals reported consuming snacks more often over the course of a week than M-types (p = .002) but not I-types. In terms of timing of snacking, E-type individuals consumed more snacks after dinner than M-types (p < .001). E-type individuals consumed more energy-dense snacks (p = .005), especially candies (p = .005), than M-types. However, there were no significant differences in healthy snack frequency, diet quality, energy and macronutrient intake, SSB consumption, alcohol misuse, or food cravings among chronotypes (p > .05, for all). In conclusion, E-type individuals consumed snacks more frequently and later than M-types; however, chronotype was not associated with an individual's energy intake, diet quality, and food cravings, which suggests that chronotype is negligibly associated with weight gain-related behaviors in this population.

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As insufficient sleep and obesity become more widespread, finding strategies to overcome changes in appetite and food cravings after sleep reduction is imperative. This study examined the effects of a high-protein (HP) and high-carbohydrate (HC) breakfast on appetitive sensations, food cravings, and dietary intake after nights of habitual (HS) and curtailed sleep (CS). Twenty-seven non-obese, premenopausal women who reported routinely eating breakfast participated in this randomized crossover study. Participants completed 4 laboratory visits with different combinations of sleep and breakfast conditions. Sleep was reduced by 33% on curtailed nights. At each visit, appetitive sensations were measured before breakfast and every 30 min thereafter throughout the 4-hour visit; area under the curve (AUC) was calculated. Food cravings were assessed before and 3.5 h after breakfast. Intake of ad libitum lunch and daily dietary intake were measured. Regardless of the breakfast condition, CS increased hunger (p = 0.043) and desire to eat (p = 0.044) and decreased fullness (p = 0.035). The HP breakfast increased fullness AUC after HS (p = 0.022) but not CS. Regardless of the sleep condition, the changes in food cravings scores were significantly different based on breakfast condition (p = 0.009), with food cravings increased after the HC breakfast and decreased after the HP breakfast. However, breakfast condition did not influence hunger or desire to eat AUC after either sleep condition. Neither the breakfast condition nor the sleep condition influenced lunch and daily energy intake. In conclusion, it appears protein reduces food cravings regardless of sleep condition in this population but obtaining sufficient sleep is necessary to benefit from the effects of high protein intake on fullness.

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OBJECTIVE: This study aimed to determine the effects of concurrent and prior media use on dietary intake and dietary compensation over 3 days in a free-living population. METHODS: Participants recorded food intake and media use for a 3-day period. The US Department of Agriculture multiple-pass method was used to ensure completeness of food records. Energy, protein, fiber, carbohydrates, sugar, added sugar, fat, saturated fat, trans fat, and sodium intake were assessed. RESULTS: Meals consumed while participants used media included 149.3 more calories on average than meals consumed without media. Media meals were higher in protein, carbohydrates, fat, and saturated fat. There was no evidence of dietary compensation at the meal following the media meal. CONCLUSIONS: Energy and macronutrient intake increased during media-paired meals. Dietary compensation at the subsequent meal did not occur, suggesting that the effects of media-paired meals are additive over the short term.

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This study examined the effects of one night of sleep curtailment on hunger, food cravings, food reward, and portion size selection. Women who reported habitually sleeping 7⁻9 h per night, were aged 18⁻55, were not obese, and had no sleep disorders were recruited. Sleep conditions in this randomized crossover study consisted of a normal night (NN) and a curtailed night (CN) where time in bed was reduced by 33%. Hunger, tiredness, sleep quality, sleepiness, and food cravings were measured. A progressive ratio task using chocolates assessed the food reward. Participants selected portions of various foods that reflected how much they wanted to eat at that time. The sleep duration was measured using a single-channel electroencephalograph. Twenty-four participants completed the study. The total sleep time was shorter during the CN (p < 0.001). Participants reported increased hunger (p = 0.013), tiredness (p < 0.001), sleepiness (p < 0.001), and food cravings (p = 0.002) after the CN. More chocolate was consumed after the CN (p = 0.004). Larger portion sizes selected after the CN resulted in increased energy plated for lunch (p = 0.034). In conclusion, the present study observed increased hunger, food cravings, food reward, and portion sizes of food after a night of modest sleep curtailment. These maladaptive responses could lead to higher energy intake and, ultimately, weight gain.

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