Meal Timing and Sleeping Energy Metabolism

Impact of environmental and lifestyle factors on adolescent sleep health in urban and semiurban areas

OBJECTIVES

This study examines the impact of lifestyle factors on adolescent sleep health across urban and semiurban settings.

METHODS

A cross-sectional survey was conducted among 1459 adolescents aged 14-19years from Tabriz (urban) and Hadishahr (semiurban), two cities with contrasting environmental conditions. Sleep duration and sleep deprivation were assessed using self-reported data, alongside key sociodemographic, behavioral, and health-related factors.

RESULTS

The results showed that adolescents in urban area were significantly more likely to experience shorter sleep durations (OR=0.63, 95% CI [0.48, 0.83]) and sleep deprivation (OR=0.66, 95% CI [0.51, 0.85]) compared to those in semiurban environments. Age was positively associated with short sleep (OR=1.21, 95% CI [1.07, 1.38]), while smoking (OR=1.46, 95% CI [1.02, 2.08]) and chronic cough (OR=1.35, 95% CI [1.01, 1.80]) were also linked to reduced sleep duration. In contrast, semiurban residents slept an average of 20minutes longer than urban residents (β=0.34, 95% CI [0.17, 0.51]). Sleep deprivation was strongly associated with lower Parent's income (OR=0.78, 95% CI [0.61, 0.98]) and daytime fatigue (OR=1.58, 95% CI [1.26, 2.00]).

CONCLUSIONS

The study highlights the need for public health interventions that address environmental barriers to healthy sleep, particularly in urban settings, to mitigate the long-term health risks associated with sleep deprivation.

Association of Evening Eating with Sleep Quality and Insomnia among Adults in a Brazilian National Survey

Objective  To examine the association of evening eating clock time, its elapsed time to the midpoint of sleep (TEM), consumption of caffeine and sugary foods, and reporting dinner as the largest meal with sleep quality indicators and insomnia. Methods  Participants ( n  = 2,050;18-65y) were part of population-based research, with virtual data collection. Logistic regression models were fitted to assess differences in the ORs(95%CI) of sleep duration < 7 hours, sleep latency > 30 minutes, poor sleep quality, and insomnia (outcomes) with the evening diet-related variables. Linear regression analyses evaluated differences in sleep duration and latency associated with the same variables. Restricted cubic splines were used to study the shape of the association of eating event clock time and TEM with sleep duration and latency. Results  Each additional hour of evening eating clock time and of the TEM, respectively increased and decreased, the odds of sleep duration < 7/h [OR(95%CI):1.30(1.20,1.40); OR(95%CI):0.51(0.47,0.56)], sleep latency > 30min [OR(95%CI):1.14(1.07,1.22); 0.88(0.83,0.94)], poor sleep quality [OR(95%CI):1.21(1.13,1.30); 0.80(0.76,0.85)] and insomnia [OR(95%CI):1.12(1.04,1.20); 0.89(0.84,0.95)]. We found a dose-response association between evening eating (clock time and TEM) and sleep duration. The shortest latency was seen when evening eating was ∼20:00 and ∼7-8 hours before the midpoint of sleep. Participants who reported dinner as the largest meal and consumed caffeine and sugary foods/beverages after 18:00 presented higher odds of sleep duration < 7 hours, poor quality, and insomnia. Conclusions  Our findings indicate that an early-eating schedule has beneficial sleep effects and that it will be necessary to consider evening eating patterns and timing, along with the existing sleep and circadian hygiene, to improve sleep quality and circadian health.

Meal Timing and Sleep Health Among Midlife Mexican Women During the Early Stages of the COVID-19 Pandemic

BACKGROUND/OBJECTIVES

This study aimed to examine associations between meal timing habits and sleep health in midlife Mexican women.

METHODS

Data comprised 379 midlife Mexican women who participated in a phone survey conducted within the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) project during the early stages of the COVID-19 pandemic. Women answered questions related to meal habits and sleep duration, latency, and quality. We used linear regression to investigate the associations between meal timing, frequency of meals/snacks, eating window (duration between first and last eating occasion of the day), duration between last meal, bedtime, sleep duration, and logistic regression to examine the associations between meal timing, sleep latency, and sleep quality, adjusting for confounders.

RESULTS

Later timing of meals throughout the day, and a shorter interval between the last meal of the day and bedtime, were associated with prolonged sleep latency and worse sleep quality. Associations with sleep duration were mixed: a longer eating window and a later largest and last meal were each associated with shorter sleep duration, while a later first meal and a shorter interval between the last meal of the day and bedtime were associated with longer sleep duration.

CONCLUSIONS

Meal timing habits are associated with sleep duration, latency, and quality in midlife women.

Association Between Chrononutrition Patterns and Multidimensional Sleep Health

BACKGROUND/OBJECTIVES

Sleep health has been associated with diet quality, but the relationship between chrononutrition patterns and multidimensional sleep health is unclear. This study identifies chrononutrition patterns among U.S. adults and examines their associations with multidimensional sleep health.

METHODS

This cross-sectional analysis used data from the 2017-2020 National Health and Nutrition Examination Survey. Chrononutrition behaviors were assessed using two 24 h dietary recalls. Latent profile analysis was used to identify chrononutrition profiles. Multivariable survey regression models determined the associations between chrononutrition patterns and sleep health dimensions.

RESULTS

The sample included 5228 subjects with a median age of 49 years. Of the sample, 52% of the participants were female, and 65% were White. In adjusted models, each additional hour between wake time and first instance of eating was associated with a 19% increase in the odds of poor timing (sleep midpoint < 2:00 a.m. or >4:00 a.m.; 95% CI: 1.07-1.33) and a 21% increase in poor duration (<7 or >9 h/night; 95% CI: 1.09-1.33). Each additional hour between last eating and bedtime was associated with 9% higher odds of poor duration (95% CI: 1.03-1.16). A one-hour longer eating window was associated with 10% lower odds of poor timing (95% CI: 0.84-0.98). We identified five chrononutrition profiles: Typical Eating (reference), Early Finished Eating, Later Heavy Eating, Extended Window Eating, and Restricted Window Eating. The Later Heavy Eating profile exhibited 96% higher odds of poor timing (95% CI: 1.09-3.51) and the Restricted Window Eating profile had 94% higher odds of poor duration (95% CI: 1.10-3.43).

CONCLUSIONS

These findings highlight the importance of unique chrononutrition patterns in relation to multidimensional sleep health. We provide a framework for future studies to identify personalized chrononutrition interventions and their role in improving sleep health.

Chronobiological perspectives: Association between meal timing and sleep quality

BACKGROUND

Meal timing has been associated with metabolism and cardiovascular diseases; however, the relationship between meal timing and sleep quality remains inconclusive.

OBJECTIVE

This study aims to investigate the relationship between meal timing and sleep quality from a chronobiological perspective.

METHODS

This study utilized data from the NHANES for the years 2005-2008, including a cohort of 7,023 participants after applying exclusion criteria. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Meal timing was analyzed based on two 24-hour dietary recalls from each individual, considering the timing of the initial and final meals, meal duration, and frequency of meal occasions. Multiple linear regression models and hierarchical analyses were employed to examine the relationship between meal timing and PSQI scores, adjusting for various demographic and habitat covariates.

RESULTS

Statistical analysis revealed a positive correlation between delayed meal timings, increased meal occasions, and elevated PSQI scores, indicating that later meal timing are intricately linked with diminished sleep quality. Both later meal timings and more frequent meal occasions were significantly associated with poorer sleep quality. Compared to the first tertile, the β (95%CI) values of the third tertile were 0.545 (0.226, 0.864) for first meal timing, 0.586 (0.277, 0.896) for midpoint meal timing, 0.385 (0.090, 0.680) for last meal timing, and 0.332 (0.021, 0.642) for meal occasions in the adjusted models.

CONCLUSION

These findings suggest that late initial, midpoint, and final meal timing, as well as more frequent meal occasions, are chrono-nutrition patterns associated with poor sleep quality.

Gender differences in body composition, dietary patterns, and physical activity: insights from a cross-sectional study

Introduction

This study investigates the interplay between body composition, dietary patterns, and physical activity across genders, focusing on gender-specific differences in food preferences and eating behaviors. Understanding these interactions is crucial for developing targeted nutritional and lifestyle interventions.

Methods

A cross-sectional study was conducted with 1,333 participants (58.7% female, 41.3% male), aged 18-65 years. Participants were categorized into tertiles based on their fat mass to fat-free mass (FM-to-FFM) ratio. Data on dietary choices, eating behaviors, and physical activity were collected and analyzed to identify gender-specific trends.

Results

Significant gender-specific differences were observed in food preferences and eating behaviors. Males experienced greater hunger in the late afternoon, while females felt more hunger in the morning. Males showed a preference for processed and red meats, whereas females preferred cooked vegetables. Eating behaviors such as meal skipping, uncontrolled eating, nocturnal eating, and taste preferences (sweet or salty) varied distinctly between FM-to-FFM tertiles and genders. Higher FM-to-FFM ratios correlated with lower physical activity levels, particularly in strength training and general sports engagement.

Discussion

These findings highlight the complex interactions between body composition, dietary habits, and lifestyle factors, emphasizing gender-specific differences. The results suggest that body composition and BMI significantly impact health-related behaviors, necessitating tailored interventions to address these differences and promote healthier lifestyles.

Examining the evidence between screen time and night eating behaviour with dietary intake related to metabolic syndrome: A narrative review

Screen time (ST) on digital devices has increased in recent decades due to digital development. Furthermore, constant engagement with digital devices alters sleep patterns, leading to nocturnal eating behaviour among users. These phenomena are therefore of great concern, as digital device addiction and night eating are associated with unhealthy food intake, increasing the metabolic syndrome (MetS) risks. The purpose of this review was to examine the evidence of the influence of ST and night eating behaviour (NEB) on dietary intake and its association with MetS based on previous literature. Prolonged ST and NEB have an association with excessive intake of energy from overconsumption of high-sugar and high-fat foods. However, the relationship between digital content and its influence on food intake is inconsistent. A higher MetS risk was found in individuals with longer ST due to a sedentary lifestyle, while positive energy balance and a shift in circadian rhythm contributed to night eaters. ST and NEB presented with a significant influence on food intake in adults. Additionally, unhealthy food intake due to excessive consumption of empty-calorie foods such as sweet and fatty foods due to addiction to electronic devices and eating at night has a detrimental effect on metabolic function. Therefore, improving food intake by reducing ST and night binges is essential to reduce the risk of MetS.

Does early time-restricted eating reduce body weight and preserve fat-free mass in adults? A systematic review and meta-analysis of randomized controlled trials

BACKGROUND

This meta-analysis evaluated whether weight loss caused by early time-restricted eating could promote fat mass loss while preserving fat-free mass, thereby leading to improvements in inflammation and metabolic health.

METHODS

Relevant randomized controlled trials (RCTs) published up to March 28, 2023, were identified in six databases, including PubMed, Web of Science, and Embase.

RESULTS

We initially screened 1279 articles, thirteen RCTs with 859 patients were ultimately included. Compared with nontime-restricted eating, early time-restricted eating significantly reduced body weight (-1.84 kg [-2.28, -1.41]; I2 = 56 %; P < 0.00001), fat mass (-1.10 kg [-1.47, -0.74]; I2 = 42 %; P < 0.00001), waist circumstance (-3.21 cm [-3.90, -2.51]; I2 = 43 %; P < 0.00001), visceral fat area (-9.76 cm2 [-13.76, -5.75]; I2 = 2 %; P < 0.00001), and inflammation as measured by tumour necrosis factor-α (-1.36 pg/mL [-2.12, -0.60]; I2 = 42 %; P < 0.001). However, early time-restricted eating did not lead to a significant change in fat-free mass (-0.56 kg [-1.16, 0.03]; I2 = 59 %; P = 0.06). Subgroup analysis showed that the early time-restricted eating of the 16:08 (fasting-time versus eating-time) strategy had a superior effect on preserving fat-free mass (-0.25 kg [-0.68, 0.18]; I2 = 0 %; P = 0.25) while significantly reducing body weight (-1.60 kg [-2.09, -1.11]; I2 = 0 %; P < 0.001) and improving metabolic outcomes.

CONCLUSIONS

Early time-restricted eating, especially 16:08 strategy, appears to be an effective strategy to decrease body weight, fat mass, abdominal obesity and inflammation, but less likely to decrease fat-free mass.