Relationship between Seasonal Changes in Food Intake and Energy Metabolism, Physical Activity, and Body Composition in Young Japanese Women

Seasonal fluctuations of CGM metrics in individuals with type 1 diabetes using an intermittently scanned CGM device or sensor augmented pump

OBJECTIVE

To elucidate the fluctuations in glucose levels measured using CGM-metrics during the four distinct seasons of the year in individuals with type 1 diabetes mellitus (T1DM) using an intermittently scanned CGM (isCGM) device or sensor augmented pump (SAP).

RESEARCH DESIGN AND METHODS

This retrospective, single-center study enrolled 93 individuals with T1DM who were equipped with an isCGM device or SAP at Kobe University Hospital. The subjects had a median age of 47.0 years [interquartile range, 37.0-62.0 years], 25 individuals (26.9%) were male, median body mass index was 22.0 kg/m2 [20.8-23.8 kg/m2], and median hemoglobin A1c level was 7.4% [6.9-8.0%]. CGM data were reviewed from January to December 2019, and the mean sensor glucose (SG) value, time above range (TAR), time in range (TIR), time below range (TBR), and standard deviation (SD) of SG were calculated for each season (spring, March-May; summer, June-August; autumn, September-November; winter, December-February).

RESULTS

Seasonal fluctuations were detected for mean SG, TAR, TIR, and SD, with TIR being lower and mean SG, TAR, and SD being higher in cold seasons (spring or winter) than in warm seasons (summer or autumn).

CONCLUSION

Seasonal fluctuations in CGM metrics should be taken into account in future studies performed to evaluate the favorable impact of CGM on glycemic management in individuals with T1DM.

Multiple factor assessment for determining resting metabolic rate in young adults

Existing formulas cannot fully explain the variation of resting metabolic rate (RMR). This study aims to examine potential influencing factors beyond anthropometric measurements and develop more accurate equations using accessible parameters. 324 healthy adults (230 females; 18-32 years old) participated in the study. Height, fat-free mass (FFM), fat mass (FM) and RMR were measured. Menstrual cycle, stress levels, living habits, and frequency of consuming caffeinated foods were collected. Measured RMR were compared with predictive values of the new equations and previous 11 equations. Mean RMR for men and women was 1825.2 ± 248.8 and 1345.1 ± 178.7 kcal/day, respectively. RMR adjusted for FFM0.66FM0.066 was positively correlated with BMI. The multiple regression model showed that RMR can be predicted in this population with model 1 (with FFM, FM, age, sex and daily sun exposure duration) or model 2 (with weight and height replacing FFM and FM). The accuracy was 75.31% in the population for predictive model 1 and 70.68% for predictive model 2. The new equations had overall improved performance when compared with existing equations. The predictive formula that consider daily sun exposure duration improve RMR prediction in young adults. Additional investigation is required among individuals in the middle-aged and elderly demographic.

A 12-Week, Single-Centre, Randomised, Double-Blind, Placebo-Controlled, Parallel-Design Clinical Trial for the Evaluation of the Efficacy and Safety of Lactiplantibacillus plantarum SKO-001 in Reducing Body Fat

There is growing evidence linking gut microbiota to overall health, including obesity risk and associated diseases. Lactiplantibacillus plantarum SKO-001, a probiotic strain isolated from Angelica gigas, has been reported to reduce obesity by controlling the gut microbiome. In this double-blind, randomised clinical trial, we aimed to evaluate the efficacy and safety of SKO-001 in reducing body fat. We included 100 participants randomised into SKO-001 or placebo groups (1:1) for 12 weeks. Dual-energy X-ray absorptiometry was used to objectively evaluate body fat reduction. Body fat percentage (p = 0.016), body fat mass (p = 0.02), low-density lipoprotein-cholesterol levels (p = 0.025), and adiponectin levels (p = 0.023) were lower in the SKO-001 group than in the placebo group after 12 weeks of SKO-001 consumption. In the SKO-001 group, the subcutaneous fat area (p = 0.003), total cholesterol levels (p = 0.003), and leptin levels (p = 0.014) significantly decreased after 12 weeks of SKO-001 consumption compared with baseline values. Additionally, SKO-001 did not cause any severe adverse reactions. In conclusion, SKO-001 is safe and effective for reducing body fat and has the potential for further clinical testing in humans.

Mediating role of weight concerns in the relationship between seasonality and eating behavior among community-dwelling older adults: A path analysis

BACKGROUND

Weight concerns are common among older adults, and it is unclear how they may impact the relationship between seasonality and eating behaviors, which can contribute to various health-related issues.

AIM

This study investigated the mediating role of weight concerns in the relationship between seasonality and eating behavior among community-dwelling older adults.

METHOD

A descriptive correlational analytical design was used on 200 randomly chosen participants who completed the Personal Inventory for Depression and Seasonal Affective Disorder Self-Assessment Version, the Adult Eating Behavior Questionnaire, and the Weight Concern Subscale. A path analysis was conducted to test the hypothesized model.

RESULTS

The study findings indicated that most older adults reported moderate-to-severe seasonal variations, moderate enjoyment of food, emotional overeating, emotional undereating, and food fussiness. Weight concern partially mediated the relationship between seasonality and eating behavior.

CONCLUSION

By understanding the complex interplay between these factors, weight concerns may play an essential role in mediating the effects of seasonal changes on eating behavior, while seasonal winter symptoms may directly impact eating behavior. These results have potential implications for nurses' efforts to develop interventions to promote healthy eating behaviors and manage weight concerns during seasonal variations, especially in the winter.

Brain Dopamine-Clock Interactions Regulate Cardiometabolic Physiology: Mechanisms of the Observed Cardioprotective Effects of Circadian-Timed Bromocriptine-QR Therapy in Type 2 Diabetes Subjects

Despite enormous global efforts within clinical research and medical practice to reduce cardiovascular disease(s) (CVD), it still remains the leading cause of death worldwide. While genetic factors clearly contribute to CVD etiology, the preponderance of epidemiological data indicate that a major common denominator among diverse ethnic populations from around the world contributing to CVD is the composite of Western lifestyle cofactors, particularly Western diets (high saturated fat/simple sugar [particularly high fructose and sucrose and to a lesser extent glucose] diets), psychosocial stress, depression, and altered sleep/wake architecture. Such Western lifestyle cofactors are potent drivers for the increased risk of metabolic syndrome and its attendant downstream CVD. The central nervous system (CNS) evolved to respond to and anticipate changes in the external (and internal) environment to adapt survival mechanisms to perceived stresses (challenges to normal biological function), including the aforementioned Western lifestyle cofactors. Within the CNS of vertebrates in the wild, the biological clock circuitry surveils the environment and has evolved mechanisms for the induction of the obese, insulin-resistant state as a survival mechanism against an anticipated ensuing season of low/no food availability. The peripheral tissues utilize fat as an energy source under muscle insulin resistance, while increased hepatic insulin resistance more readily supplies glucose to the brain. This neural clock function also orchestrates the reversal of the obese, insulin-resistant condition when the low food availability season ends. The circadian neural network that produces these seasonal shifts in metabolism is also responsive to Western lifestyle stressors that drive the CNS clock into survival mode. A major component of this natural or Western lifestyle stressor-induced CNS clock neurophysiological shift potentiating the obese, insulin-resistant state is a diminution of the circadian peak of dopaminergic input activity to the pacemaker clock center, suprachiasmatic nucleus. Pharmacologically preventing this loss of circadian peak dopaminergic activity both prevents and reverses existing metabolic syndrome in a wide variety of animal models of the disorder, including high fat-fed animals. Clinically, across a variety of different study designs, circadian-timed bromocriptine-QR (quick release) (a unique formulation of micronized bromocriptine-a dopamine D2 receptor agonist) therapy of type 2 diabetes subjects improved hyperglycemia, hyperlipidemia, hypertension, immune sterile inflammation, and/or adverse cardiovascular event rate. The present review details the seminal circadian science investigations delineating important roles for CNS circadian peak dopaminergic activity in the regulation of peripheral fuel metabolism and cardiovascular biology and also summarizes the clinical study findings of bromocriptine-QR therapy on cardiometabolic outcomes in type 2 diabetes subjects.

Factors explaining seasonal variation in energy intake: a review

Maintaining a balance between energy intake and expenditure is crucial for overall health. There are seasonal variations in energy intake, with an increase during spring and winter as well as a decrease during summer. These variations are related to a combination of environmental factors, including changes in temperature and daylight hours; social factors, including events and holidays; and physiological factors, including changes in physical activity and emotions. Accordingly, this review aimed to summarize the environmental, social, and physiological factors that contribute to seasonal variations in energy intake. A review of the current literature revealed that changes in temperature and daylight hours may affect eating behavior by altering homeostatic responses and appetite-related hormones. Additionally, increased participation in events and frequency of eating out, especially during winter vacations, may contribute to increased energy intake. Notably, these findings may not be generalisable to all populations since environmental and social factors can vary significantly depending on the local climatic zones and cultural backgrounds. The findings of the present review indicate that seasonal climate, events, and associated hormonal changes should be taken into account in order to maintain adequate energy intake throughout the year.

Association of Eating Pattern, Chronotype, and Social Jetlag: A Cross-Sectional Study Using Data Accumulated in a Japanese Food-Logging Mobile Health Application

Chronotype (morningness-eveningness) and social jetlag (SJL; discrepancy in the sleep pattern between the weekday and weekend) are related to eating behavior and health. The association between sleep behavior and the daily macro- and micronutrient eating pattern of each meal (breakfast, lunch, and dinner) have not been discussed well and need more evidence. Here, meal pattern datasets of Japanese participants aged 20-59 years were obtained as averages over 1 month from the data stored in the food-logging app "Asken". We allocated three groups for each chronotype and SJL. Multiple regression analyses revealed that morning chronotype and small SJL were associated with higher total daily intake of potassium, fiber, magnesium, phosphorus, and vitamin K. Breakfast energy intake and consumption of nutrients, including protein, lipid, carbohydrate, and minerals, were higher in the morning chronotype or small SJL. Lunch intake of potassium, cholesterol, fiber, magnesium, and vitamin K was also higher in the morning chronotype or small SJL. Dinner energy intake and nutrient intake of proteins, lipids, carbohydrates, sodium, and saturated fatty acids were lower in the morning chronotype or small SJL. The current data would help to establish a detailed reference for dietary intake which considers eating patterns over a day.

A Preliminary Study on a Form of the 24-h Recall That Balances Survey Cost and Accuracy, Based on the NCI Method

The 24-h recall (24HR) is a short-term dietary assessment instrument that is widely used in large-scale nutrition surveys. The number of survey days is critical in the accuracy of estimates. The multiple, repeated collection of 24HRs can yield reliable dietary intakes, whereas that is not always feasible due to staffing, equipment, financial, and temporal constraints. The NCI (National Cancer Institute) method was developed to address this limitation by using only within-person variance to calculate usual dietary intake. However, the performance of different forms of 24HRs based on the NCI method remains unclear. The aim of this study was to explore a form of 24HR based on the NCI method that can balance accuracy and survey cost. A total of 595 subjects completed 7 consecutive 24HRs in each season, for a total of 28 24HRs. The averages of the 28 collection days were defined as the reference value to compare the performance of 24HRs for two consecutive days (C2), three consecutive days (C3), two non-consecutive days (NC2), and three non-consecutive days (NC3) for estimating the dietary intakes of Chinese adults. The equivalence test was used to evaluate whether the estimates of scenarios NC2 and NC3 were equivalent. Additionally, the accuracy of a scenario of NC2 which included a weekend was compared to that of a scenario of NC2 which included two weekdays. All results of the 24HRs in each scenario were corrected by the NCI method. Bias/relative bias and mean bias/mean relative bias were used as measures of precision and accuracy, respectively. The results showed that the precision was similar among the four scenarios, while the accuracy relationship varied among the different dietary components. In general, scenario NC3 was the most accurate, followed by scenario NC2, which was close to the former. The form using non-consecutive days was more accurate than that using consecutive days, and the main factor affecting the accuracy of the 24HRs was the continuity between multiple survey days rather than the number of days. The means and major percentiles of energy, nutrients, and frequently consumed food in scenarios NC2 and NC3 were functionally identical. The accuracy of the scenario of NC2 which included a weekend was higher than that of scenario NC2, which consisted of only weekdays. The above results indicated that the adoption of two, non-consecutive 24HRs consisting of a weekend and a weekday to collect dietary data prior to correction by the NCI method, is a feasible approach to balancing survey costs and accuracy in large-scale nutrition surveys.

Comparison of the 24 h Dietary Recall of Two Consecutive Days, Two Non-Consecutive Days, Three Consecutive Days, and Three Non-Consecutive Days for Estimating Dietary Intake of Chinese Adult

The specific forms of 24 h dietary recall used by national nutrition surveys differ, such as two non-consecutive days and three consecutive days. However, it is unclear which form of 24 h dietary recall is more accurate in the Chinese population. The purpose of this study was to compare the performance of 24 h recalls on two consecutive days (C2), three consecutive days (C3), two non-consecutive days (NC2), and three non-consecutive days (NC3) in estimating Chinese adult dietary intake. A total of 595 participants completed more than twenty-three 24 h recalls. The average of all completed 24 h recalls of each subject was defined as the individual’s true dietary intake. The dietary intake in the four scenarios of 24 h recalls was calculated using the within-person mean (WPM) method and National Cancer Institute (NCI) method and compared with the true values. Equivalent testing was used to evaluate whether scenarios NC2 and C3 were equivalent. Bias and mean bias were used as a measure of precision and accuracy, respectively. For the WPM method, the precision between the four scenarios was similar. For mean, the accuracy between the four scenarios was similar, yielding estimates that were close to the true intakes. However, for percentiles, the accuracy in descending order was scenario NC3, C3, NC2, and C2. Furthermore, the difference between two and three days was greater than that between consecutive and non-consecutive days. In most case, the distribution of dietary intakes calculated from scenarios NC2 and C3 was equivalent with equivalence margins of 5% (p < 0.05). Usually, the NCI method was significantly more accurate than the WPM method. We concluded that three non-consecutive 24 h recalls relative to three consecutive days increases accuracy. Two non-consecutive days can be substituted to some extent for three consecutive days. The new form of 24 h recall needs to be used with caution when applied practically in the China nutrition surveys. Furthermore, using the NCI method to calculate dietary intake from 24 h recall may be a way to reduce costs and increase accuracy.