Late, but Not Early, Night Sleep Loss Compromises Neuroendocrine Appetite Regulation and the Desire for Food

Neural and hormonal mechanisms of appetite regulation during eating

Numerous animal and clinical studies have demonstrated that the arcuate nucleus of the hypothalamus, a central regulator of appetite, plays a significant role in modulating feeding behavior. However, current research primarily focuses on long-term dietary changes and their effects on the body, with limited investigation into neuroendocrine dynamics during individual meals across diverse populations. In contrast to long-term dietary adjustments, directives for dietary behavior during a specific meal are more actionable, potentially enhancing patient adherence and achieving better outcomes in dietary behavior interventions. This review aimed to explore the neural pathways and endocrine changes activated by gastrointestinal expansion and variations in blood nutrient levels during a single meal, with the goal of informing dietary behavior guidance.

Relationship Among Macronutrients, Dietary Components, and Objective Sleep Variables Measured by Smartphone Apps: Real-World Cross-Sectional Study

BACKGROUND

Few studies have explored the relationship between macronutrient intake and sleep outcomes using daily data from mobile apps.

OBJECTIVE

This cross-sectional study aimed to examine the associations between macronutrients, dietary components, and sleep parameters, considering their interdependencies.

METHODS

We analyzed data from 4825 users of the Pokémon Sleep and Asken smartphone apps, each used for at least 7 days to record objective sleep parameters and dietary components, respectively. Multivariable regression explored the associations between quartiles of macronutrients (protein; carbohydrate; and total fat, including saturated, monounsaturated, and polyunsaturated fats), dietary components (sodium, potassium, dietary fiber, and sodium-to-potassium ratio), and sleep variables (total sleep time [TST], sleep latency [SL], and percentage of wakefulness after sleep onset [%WASO]). The lowest intake group was the reference. Compositional data analysis accounted for macronutrient interdependencies. Models were adjusted for age, sex, and BMI.

RESULTS

Greater protein intake was associated with longer TST in the third (+0.17, 95% CI 0.09-0.26 h) and fourth (+0.18, 95% CI 0.09-0.27 h) quartiles. In contrast, greater fat intake was linked to shorter TST in the third (-0.11, 95% CI -0.20 to -0.27 h) and fourth (-0.16, 95% CI -0.25 to -0.07 h) quartiles. Greater carbohydrate intake was associated with shorter %WASO in the third (-0.82%, 95% CI -1.37% to -0.26%) and fourth (-0.57%, 95% CI -1.13% to -0.01%) quartiles, while greater fat intake was linked to longer %WASO in the fourth quartile (+0.62%, 95% CI 0.06%-1.18%). Dietary fiber intake correlated with longer TST and shorter SL. A greater sodium-to-potassium ratio was associated with shorter TST in the third (-0.11, 95% CI -0.20 to -0.02 h) and fourth (-0.19, 95% CI -0.28 to -0.10 h) quartiles; longer SL in the second (+1.03, 95% CI 0.08-1.98 min) and fourth (+1.50, 95% CI 0.53-2.47 min) quartiles; and longer %WASO in the fourth quartile (0.71%, 95% CI 0.15%-1.28%). Compositional data analysis, involving 6% changes in macronutrient proportions, showed that greater protein intake was associated with an elevated TST (+0.27, 95% CI 0.18-0.35 h), while greater monounsaturated fat intake was associated with a longer SL (+4.6, 95% CI 1.93-7.34 min) and a larger %WASO (+2.2%, 95% CI 0.63%-3.78%). In contrast, greater polyunsaturated fat intake was associated with a reduced TST (-0.22, 95% CI -0.39 to -0.05 h), a shorter SL (-4.7, 95% CI to 6.58 to -2.86 min), and a shorter %WASO (+2.0%, 95% CI -3.08% to -0.92%).

CONCLUSIONS

Greater protein and fiber intake were associated with longer TST, while greater fat intake and sodium-to-potassium ratios were linked to shorter TST and longer WASO. Increasing protein intake in place of other nutrients was associated with longer TST, while higher polyunsaturated fat intake improved SL and reduced WASO.

Isolated and Combined Effects of Moderate Normobaric Hypoxia and Sleep Restriction on Energy Intake and Food Reward

Hypoxia (HY) and sleep deprivation have opposite effects on appetite. As HY may alter sleep, it may be informative to assess the accumulative effects of these two stressors on hunger, energy intake (EI), and food reward. Seventeen young, active, healthy males completed four 5-hr sessions in normoxia (NO) or normobaric HY (FIO2 = 13.6%, ∼3,500 m) after a night of habitual sleep (HS; total sleep time >6 hr) or sleep restriction (SR; total sleep time <3 hr). Subjective appetite was assessed regularly using visual analogic scales and EI during an ad libitum lunch after 3.5 hr of exposure. Food reward was assessed using the Leeds Food Preference Questionnaire just before the lunch. As expected, EI was lower for the HY-HS (4.32 ± 0.71 MJ; p = .048) and HY-SR (4.16 ± 0.68 MJ, p = .013) sessions than the NO-HS (4.90 ± 0.84 MJ) session without acute mountain sickness-related gastrointestinal symptoms. No significant effect of SR alone was observed (NO-SR: 4.40 ± 0.68 MJ). Subjective appetite was not affected. Explicit liking for high-fat foods was higher with SR than HS (main effect: p = .002) and implicit wanting for high-fat foods was higher for the NO-SR, HY-HS, and HY-SR sessions than the NO-HS session (p < .006). Thus, acute SR did not modify subjective appetite or EI despite the increasing food reward for high-fat foods and did not alter the HY-induced changes of appetite or food reward.

Latent profiles of multi-dimensional sleep characteristics and association with overweight/obesity in Chinese preschool children

OBJECTIVES

To examine the association between latent profiles of multi-dimensional sleep characteristics and overweight/obesity (OWO) in Chinese preschool children.

STUDY DESIGN

The cross-sectional analysis included 3204 preschool children recruited from 24 kindergartens in Shanghai. Parents reported children's demographics and sleep characteristics, including sleep duration, timing and disturbances. Latent profile analysis (LPA) was used to identify sleep subtypes. Logistic regression models were used to evaluate the associations between sleep characteristics/subtypes and OWO.

RESULTS

Short sleep duration, late bedtime, long social jetlag and sleep disturbances were significantly associated with increased OWO. However, when considering the interplay of sleep duration and timing, there was no significant association between sleep duration and OWO for children sleeping later than 22:00. Three sleep subtypes were identified based on children's sleep duration, timing and disturbances: "Average Sleepers" (n = 2107, 65.8 %), "Good Sleepers" (n = 481, 15.0 %), and "Poor Sleepers" (n = 616, 19.2 %). "Good Sleepers" had reduced odds of being OWO (AOR, 0.72; 95 % CI, 0.56-0.93) compared to "Average Sleepers", while "Poor Sleepers" showed an increased risk of OWO (AOR, 1.36; 95 % CI, 1.11-1.67).

CONCLUSIONS

These findings highlight that improving multiple sleep characteristics simultaneously is a promising option to prevent and intervene childhood obesity.

The impact of REM sleep loss on human brain connectivity

Brain function is vulnerable to the consequences of inadequate sleep, an adverse trend that is increasingly prevalent. The REM sleep phase has been implicated in coordinating various brain structures and is hypothesized to have potential links to brain variability. However, traditional imaging research have encountered challenges in attributing specific brain region activity to REM sleep, remained understudied at the whole-brain connectivity level. Through the spilt-night paradigm, distinct patterns of REM sleep phases were observed among the full-night sleep group (n = 36), the early-night deprivation group (n = 41), and the late-night deprivation group (n = 36). We employed connectome-based predictive modeling (CPM) to delineate the effects of REM sleep deprivation on the functional connectivity of the brain (REM connectome) during its resting state. The REM sleep-brain connectome was characterized by stronger connectivity within the default mode network (DMN) and between the DMN and visual networks, while fewer predictive edges were observed. Notably, connections such as those between the cingulo-opercular network (CON) and the auditory network, as well as between the subcortex and visual networks, also made significant contributions. These findings elucidate the neural signatures of REM sleep loss and reveal common connectivity patterns across individuals, validated at the group level.

Hypoglycemia Unawareness-A Review on Pathophysiology and Clinical Implications

Hypoglycemia is a particular problem in people with diabetes while it can also occur in other clinical circumstances. Hypoglycemia unawareness describes a condition in which autonomic and neuroglycopenic symptoms of hypoglycemia decrease and hence are hardly perceivable. A failure to recognize hypoglycemia in time can lead to unconsciousness, seizure, and even death. The risk factors include intensive glycemic control, prior episodes of severe hypoglycemia, long duration of diabetes, alcohol consumption, exercise, renal failure, and sepsis. The pathophysiological mechanisms are manifold, but mainly concern altered brain glucose sensing, cerebral adaptations, and an impaired hormonal counterregulation with an attenuated release of glucagon, epinephrine, growth hormone, and other hormones, as well as impaired autonomous and neuroglycopenic symptoms. Physiologically, this counterregulatory response causes blood glucose levels to rise. The impaired hormonal counterregulatory response to recurrent hypoglycemia can lead to a vicious cycle of frequent and poorly recognized hypoglycemic episodes. There is a shift in glycemic threshold to trigger hormonal counterregulation, resulting in hypoglycemia-associated autonomic failure and leading to the clinical syndrome of hypoglycemia unawareness. This clinical syndrome represents a particularly great challenge in diabetes treatment and, thus, prevention of hypoglycemia is crucial in diabetes management. This mini-review provides an overview of hypoglycemia and the associated severe complication of impaired hypoglycemia awareness and its symptoms, pathophysiology, risk factors, consequences, as well as therapeutic strategies.