Effects of follicle-stimulating hormone on energy balance and tissue metabolic health after loss of ovarian function.

Loss of ovarian function imparts increased susceptibility to obesity and metabolic disease. These effects are largely attributed to decreased estradiol (E2), but the role of increased follicle-stimulating hormone (FSH) in modulating energy balance has not been fully investigated. Previous work that blocked FSH binding to its receptor in mice suggested this hormone may play a part in modulating body weight and energy expenditure after ovariectomy (OVX). We used an alternate approach to isolate the individual and combined contributions of FSH and E2 in mediating energy imbalance and changes in tissue-level metabolic health. Female Wistar rats were ovariectomized and given the gonadotropin releasing hormone (GnRH) antagonist degarelix to suppress FSH production. E2 and FSH were then added back individually and in combination for a period of 3 wk. Energy balance, body mass composition, and transcriptomic profiles of individual tissues were obtained. In contrast to previous studies, suppression and replacement of FSH in our paradigm had no effect on body weight, body composition, food intake, or energy expenditure. We did, however, observe organ-specific effects of FSH that produced unique transcriptomic signatures of FSH in retroperitoneal white adipose tissue. These included reductions in biological processes related to lipogenesis and carbohydrate transport. In addition, rats administered FSH had reduced liver triglyceride concentration (P < 0.001), which correlated with FSH-induced changes at the transcriptomic level. Although not appearing to modulate energy balance after loss of ovarian function in rats, FSH may still impart tissue-specific effects in the liver and white adipose tissue that might affect the metabolic health of those organs.NEW & NOTEWORTHY We find no effect of follicle-stimulating hormone (FSH) on energy balance using a novel model in which rats are ovariectomized, subjected to gonadotropin-releasing hormone antagonism, and systematically given back FSH by osmotic pump. However, tissue-specific effects of FSH on adipose tissue and liver were observed in this study. These include unique transcriptomic signatures induced by the hormone and a stark reduction in hepatic triglyceride accumulation.

Preventing ovariectomy-induced weight gain decreases tumor burden in rodent models of obesity and postmenopausal breast cancer.

BACKGROUND: Obesity and adult weight gain are linked to increased breast cancer risk and poorer clinical outcomes in postmenopausal women, particularly for hormone-dependent tumors. Menopause is a time when significant weight gain occurs in many women, and clinical and preclinical studies have identified menopause (or ovariectomy) as a period of vulnerability for breast cancer development and promotion. METHODS: We hypothesized that preventing weight gain after ovariectomy (OVX) may be sufficient to prevent the formation of new tumors and decrease growth of existing mammary tumors. We tested this hypothesis in a rat model of obesity and carcinogen-induced postmenopausal mammary cancer and validated our findings in a murine xenograft model with implanted human tumors. RESULTS: In both models, preventing weight gain after OVX significantly decreased obesity-associated tumor development and growth. Importantly, we did not induce weight loss in these animals, but simply prevented weight gain. In both lean and obese rats, preventing weight gain reduced visceral fat accumulation and associated insulin resistance. Similarly, the intervention decreased circulating tumor-promoting growth factors and inflammatory cytokines (i.e., BDNF, TNFα, FGF-2), with greater effects in obese compared to lean rats. In obese rats, preventing weight gain decreased adipocyte size, adipose tissue macrophage infiltration, reduced expression of the tumor-promoting growth factor FGF-1 in mammary adipose, and reduced phosphorylated FGFR indicating reduced FGF signaling in tumors. CONCLUSIONS: Together, these findings suggest that the underlying mechanisms associated with the anti-tumor effects of weight maintenance are multi-factorial, and that weight maintenance during the peri-/postmenopausal period may be a viable strategy for reducing obesity-associated breast cancer risk and progression in women.

Energy intake estimation using a novel wearable sensor and food images in a laboratory (pseudo-free-living) meal setting: quantification and contribution of sources of error.

OBJECTIVES: Dietary assessment methods not relying on self-report are needed. The Automatic Ingestion Monitor 2 (AIM-2) combines a wearable camera that captures food images with sensors that detect food intake. We compared energy intake (EI) estimates of meals derived from AIM-2 chewing sensor signals, AIM-2 images, and an internet-based diet diary, with researcher conducted weighed food records (WFR) as the gold standard. SUBJECTS/METHODS: Thirty adults wore the AIM-2 for meals self-selected from a university food court on one day in mixed laboratory and free-living conditions. Daily EI was determined from a sensor regression model, manual image analysis, and a diet diary and compared with that from WFR. A posteriori analysis identified sources of error for image analysis and WFR differences. RESULTS: Sensor-derived EI from regression modeling (R2 = 0.331) showed the closest agreement with EI from WFR, followed by diet diary estimates. EI from image analysis differed significantly from that by WFR. Bland-Altman analysis showed wide limits of agreement for all three test methods with WFR, with the sensor method overestimating at lower and underestimating at higher EI. Nutritionist error in portion size estimation and irreconcilable differences in portion size between food and nutrient databases used for WFR and image analyses were the greatest contributors to image analysis and WFR differences (44.4% and 44.8% of WFR EI, respectively). CONCLUSIONS: Estimation of daily EI from meals using sensor-derived features offers a promising alternative to overcome limitations of self-report. Image analysis may benefit from computerized analytical procedures to reduce identified sources of error.

A Model of Adolescent Sleep Health and Risk for Type 2 Diabetes.

PURPOSE OF REVIEW: This paper presents a review of the current literature in support of a model explaining the relationships between sleep health and risk for type 2 diabetes in adolescents. RECENT FINDINGS: Short sleep duration is associated with risk of developing obesity in youth. Sleep restriction increases energy expenditure, but also increases hunger, appetite, and food intake, causing positive energy balance, impacting appetite-regulating hormones, and leading to increased eating late at night. Insufficient sleep may lead to reduced physical activity and greater sedentary behaviors. In addition, short sleep duration is associated with reduced insulin sensitivity. The cumulative negative consequences of insufficient sleep increase risk for type 2 diabetes. Applications to clinical care, public policy, and future research are discussed. Insufficient sleep in adolescence increases risk for type 2 diabetes directly through impact on insulin sensitivity and indirectly through increased dietary intake, sedentary activity, and weight gain.

Evaluation of the longitudinal change in health behavior profiles across treatment groups in the TODAY clinical trial.

BACKGROUND: Individual health behaviors (ie, eating habits and sedentary lifestyle) are associated with type 2 diabetes (T2D). Health behavior profiles specific to adolescents with T2D have not been described. OBJECTIVE: To identify health behavior profiles in adolescents with T2D and examine how these profiles change over time. METHODS: Diet (via food frequency questionnaire) and activity behaviors (via 3-day physical activity recall) examined at baseline, 6 months, and 24 months from participants in the the Treatment Options for T2D in Adolescents and Youth (TODAY) study were used for this analysis. Latent profile analysis identified profiles of health behaviors within three time points, and latent transition probabilities were estimated to examine the change from baseline to 6 months (n = 450) and baseline to 24 months (n = 415). Multinomial logistic regressions were used to examine if the assigned TODAY treatment group (Metformin [Met], Met + Rosiglitazone [Rosi], or Met + Lifestyle) predicted change in health behavior profiles. RESULTS: Three profiles emerged: "most sedentary," "healthy eaters," and "active and eat most." At 6 months, 50% of males and 29% of females in the Met + Lifestyle treatment group improved in their health behavior profile. Among males only, the Met + Lifestyle treatment group were more likely to improve their profiles from baseline to 6 months (P = .01). CONCLUSIONS: Three health behavior profiles emerged and shifted over time. A high quality, lifestyle intervention had little effect on improving health behavior profiles. Optimizing outcomes in youth with T2D might require more robust and multifaceted interventions beyond family-level lifestyle, including more extensive psychosocial intervention, novel medication regimen, or bariatric surgery.

Compensation for cold-induced thermogenesis during weight loss maintenance and regain.

Prevalence of obesity is exacerbated by low rates of successful long-term weight loss maintenance (WLM). In part, relapse from WLM to obesity is due to a reduction in energy expenditure (EE) that persists throughout WLM and relapse. Thus, interventions that increase EE might facilitate WLM. In obese mice that were calorically restricted to reduce body weight by ~20%, we manipulated EE throughout WLM and early relapse using intermittent cold exposure (ICE; 4°C, 90 min/day, 5 days/wk, within the last 3 h of the light cycle). EE, energy intake, and spontaneous physical activity were measured during the obese, WLM, and relapse phases. During WLM and relapse, the ICE group expended more energy during the light cycle because of cold exposure but expended less energy in the dark cycle, which led to no overall difference in total daily EE. The compensation in EE appeared to be mediated by activity, whereby the ICE group was more active during the light cycle because of cold exposure but less active during the dark cycle, which led to no overall effect on total daily activity during WLM and relapse. In brown adipose tissue of relapsing mice, the ICE group had greater mRNA expression of Dio2 and protein expression of UCP1 but lower mRNA expression of Prdm16. In summary, these findings indicate that despite robust increases in EE during cold exposures, ICE is unable to alter total daily EE during WLM or early relapse, likely due to compensatory behaviors in activity.

Regular exercise potentiates energetically expensive hepatic de novo lipogenesis during early weight regain.

Exercise is a potent facilitator of long-term weight loss maintenance (WLM), whereby it decreases appetite and increases energy expenditure beyond the cost of the exercise bout. We have previously shown that exercise may amplify energy expenditure through energetically expensive nutrient deposition. Therefore, we investigated the effect of exercise on hepatic de novo lipogenesis (DNL) during WLM and relapse to obesity. Obese rats were calorically restricted with (EX) or without (SED) treadmill exercise (1 h/day, 6 days/wk, 15 m/min) to induce and maintain weight loss. After 6 wk of WLM, subsets of WLM-SED and WLM-EX rats were allowed ad libitum access to food for 1 day to promote relapse (REL). An energy gap-matched group of sedentary, relapsing rats (REL-GM) were provided a diet matched to the positive energy imbalance of the REL-EX rats. During relapse, exercise increased enrichment of hepatic DN-derived lipids and induced hepatic molecular adaptations favoring DNL compared with the gap-matched controls. In the liver, compared with both REL-SED and REL-GM rats, REL-EX rats had lower hepatic expression of genes required for cholesterol biosynthesis; greater hepatic expression of genes that mediate very low-density lipoprotein synthesis and secretion; and greater mRNA expression of Cyp27a1, which encodes an enzyme involved in the biosynthesis of bile acids. Altogether, these data provide compelling evidence that the liver has an active role in exercise-mediated potentiation of energy expenditure during early relapse.

Impact of lifestyle behavior change on glycemic control in youth with type 2 diabetes.

BACKGROUND: Little is known about the feasibility and impact of lifestyle intervention, determined by change in diet and cardiovascular fitness (CRF), on glycemic control in youth who are overweight with type 2 diabetes. This was examined in the Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) clinical trial cohort from across 15 US centers. SUBJECTS: TODAY enrolled 699 youth aged 10 to 17 years with type 2 diabetes <2 years and body mass index ≥85th percentile at baseline. METHODS: Dietary data were collected by an interviewer-administered food frequency questionnaire; CRF was assessed using a submaximal cycle ergometer test. Change from baseline in these variables was analyzed using generalized linear mixed models for both continuous and categorical measures. Models were adjusted for age, baseline HbA1c, treatment group, and medication adherence. Data were collected at baseline, 6, and 24 months. Trial registration ClinicalTrials.gov NCT00081328. RESULTS: At 6 months, ~25% of females and ~33% of males improved CRF. In males, this was related to a decreased HbA1c (P = .001) and a lower percent experiencing glycemic failure (HbA1c ≥8%; P = .007). Females who decreased their saturated fat intake and/or increased their fiber intake had lower HbA1c at month 24 (P = .01 and P = .007, respectively). Males who increased their sweetened beverage intake at 6-month follow-up were at a 1.6-fold higher risk of experiencing glycemic failure (P = .04). CONCLUSIONS: Few youth improved fitness and/or diet over time, although those who did showed a beneficial impact on glycemic outcomes. Although lifestyle behaviors are difficult to change in youth with type 2 diabetes, interventions are needed that are feasible (in scope, complexity, and demands), sustainable, and clinically meaningful.

Impact of circadian misalignment on energy metabolism during simulated nightshift work.

Eating at a time when the internal circadian clock promotes sleep is a novel risk factor for weight gain and obesity, yet little is known about mechanisms by which circadian misalignment leads to metabolic dysregulation in humans. We studied 14 adults in a 6-d inpatient simulated shiftwork protocol and quantified changes in energy expenditure, macronutrient utilization, appetitive hormones, sleep, and circadian phase during day versus nightshift work. We found that total daily energy expenditure increased by ∼4% on the transition day to the first nightshift, which consisted of an afternoon nap and extended wakefulness, whereas total daily energy expenditure decreased by ∼3% on each of the second and third nightshift days, which consisted of daytime sleep followed by afternoon and nighttime wakefulness. Contrary to expectations, energy expenditure decreased by ∼12-16% during scheduled daytime sleep opportunities despite disturbed sleep. The thermic effect of feeding also decreased in response to a late dinner on the first nightshift. Total daily fat utilization increased on the first and second nightshift days, contrary to expectations, and carbohydrate and protein utilization were reduced on the second nightshift day. Ratings of hunger were decreased during nightshift days despite decreases in 24-h levels of the satiety hormones leptin and peptide-YY. Findings suggest that reduced total daily energy expenditure during nightshift schedules and reduced energy expenditure in response to dinner represent contributing mechanisms by which humans working and eating during the biological night, when the circadian clock is promoting sleep, may increase the risk of weight gain and obesity.

Impact of insufficient sleep on total daily energy expenditure, food intake, and weight gain.

Insufficient sleep is associated with obesity, yet little is known about how repeated nights of insufficient sleep influence energy expenditure and balance. We studied 16 adults in a 14- to 15-d-long inpatient study and quantified effects of 5 d of insufficient sleep, equivalent to a work week, on energy expenditure and energy intake compared with adequate sleep. We found that insufficient sleep increased total daily energy expenditure by ∼5%; however, energy intake--especially at night after dinner--was in excess of energy needed to maintain energy balance. Insufficient sleep led to 0.82 ± 0.47 kg (±SD) weight gain despite changes in hunger and satiety hormones ghrelin and leptin, and peptide YY, which signaled excess energy stores. Insufficient sleep delayed circadian melatonin phase and also led to an earlier circadian phase of wake time. Sex differences showed women, not men, maintained weight during adequate sleep, whereas insufficient sleep reduced dietary restraint and led to weight gain in women. Our findings suggest that increased food intake during insufficient sleep is a physiological adaptation to provide energy needed to sustain additional wakefulness; yet when food is easily accessible, intake surpasses that needed. We also found that transitioning from an insufficient to adequate/recovery sleep schedule decreased energy intake, especially of fats and carbohydrates, and led to -0.03 ± 0.50 kg weight loss. These findings provide evidence that sleep plays a key role in energy metabolism. Importantly, they demonstrate physiological and behavioral mechanisms by which insufficient sleep may contribute to overweight and obesity.

Energy intake estimation from counts of chews and swallows.

Current, validated methods for dietary assessment rely on self-report, which tends to be inaccurate, time-consuming, and burdensome. The objective of this work was to demonstrate the suitability of estimating energy intake using individually-calibrated models based on Counts of Chews and Swallows (CCS models). In a laboratory setting, subjects consumed three identical meals (training meals) and a fourth meal with different content (validation meal). Energy intake was estimated by four different methods: weighed food records (gold standard), diet diaries, photographic food records, and CCS models. Counts of chews and swallows were measured using wearable sensors and video analysis. Results for the training meals demonstrated that CCS models presented the lowest reporting bias and a lower error as compared to diet diaries. For the validation meal, CCS models showed reporting errors that were not different from the diary or the photographic method. The increase in error for the validation meal may be attributed to differences in the physical properties of foods consumed during training and validation meals. However, this may be potentially compensated for by including correction factors into the models. This study suggests that estimation of energy intake from CCS may offer a promising alternative to overcome limitations of self-report.

Resistant starch and energy balance: impact on weight loss and maintenance.

The obesity epidemic has prompted researchers to find effective weight-loss and maintenance tools. Weight loss and subsequent maintenance are reliant on energy balance--the net difference between energy intake and energy expenditure. Negative energy balance, lower intake than expenditure, results in weight loss whereas positive energy balance, greater intake than expenditure, results in weight gain. Resistant starch has many attributes, which could promote weight loss and/or maintenance including reduced postprandial insulinemia, increased release of gut satiety peptides, increased fat oxidation, lower fat storage in adipocytes, and preservation of lean body mass. Retention of lean body mass during weight loss or maintenance would prevent the decrease in basal metabolic rate and, therefore, the decrease in total energy expenditure, that occurs with weight loss. In addition, the fiber-like properties of resistant starch may increase the thermic effect of food, thereby increasing total energy expenditure. Due to its ability to increase fat oxidation and reduce fat storage in adipocytes, resistant starch has recently been promoted in the popular press as a "weight loss wonder food". This review focuses on data describing the effects of resistant starch on body weight, energy intake, energy expenditure, and body composition to determine if there is sufficient evidence to warrant these claims.

Integrated image and sensor-based food intake detection in free-living.

The first step in any dietary monitoring system is the automatic detection of eating episodes. To detect eating episodes, either sensor data or images can be used, and either method can result in false-positive detection. This study aims to reduce the number of false positives in the detection of eating episodes by a wearable sensor, Automatic Ingestion Monitor v2 (AIM-2). Thirty participants wore the AIM-2 for two days each (pseudo-free-living and free-living). The eating episodes were detected by three methods: (1) recognition of solid foods and beverages in images captured by AIM-2; (2) recognition of chewing from the AIM-2 accelerometer sensor; and (3) hierarchical classification to combine confidence scores from image and accelerometer classifiers. The integration of image- and sensor-based methods achieved 94.59% sensitivity, 70.47% precision, and 80.77% F1-score in the free-living environment, which is significantly better than either of the original methods (8% higher sensitivity). The proposed method successfully reduces the number of false positives in the detection of eating episodes.

Prediction of resting energy expenditure for adolescents with severe obesity: A multi-centre analysis.

BACKGROUND AND OBJECTIVES: Resting energy expenditure (REE) assessments can help inform clinical treatment decisions in adolescents with elevated body mass index (BMI), but current equations are suboptimal for severe obesity. We developed a predictive REE equation for youth with severe obesity and obesity-related comorbidities and compared results to previously published predictive equations. METHODS: Data from indirect calorimetry, clinical measures, and body composition per Dual x-ray absorptiometry (DXA) were collected from five sites. Data were randomly divided into development (N = 438) and validation (N = 118) cohorts. A predictive equation was developed using Elastic Net regression, using sex, race, ethnicity, weight, height, BMI percent of the 95th%ile (BMIp95), waist circumference, hip circumference, waist/hip ratio, age, Tanner stage, fat and fat-free mass. This equation was verified in the validation cohort and compared with 11 prior equations. RESULTS: Data from the total cohort (n = 556, age 15 ± 1.7 years, 77% female, BMIp95 3.3 ± 0.94) were utilized. The best fit equation was REE = -2048 + 18.17 × (Height in cm) - 2.57 × (Weight in kg) + 7.88 × (BMIp95) + 189 × (1 = male, 0 = female), R2 = 0.466, and mean bias of 23 kcal/day. CONCLUSION: This new equation provides an updated REE prediction that accounts for severe obesity and metabolic complications frequently observed in contemporary youth.

Distribution of dim light melatonin offset (DLMOff) and phase relationship to waketime in healthy adults and associations with chronotype.

OBJECTIVES: Dim light melatonin onset, or the rise in melatonin levels representing the beginning of the biological night, is the gold standard indicator of circadian phase. Considerably less is known about dim light melatonin offset, or the decrease in melatonin to low daytime levels representing the end of the biological night. In the context of insufficient sleep, morning circadian misalignment, or energy intake after waketime but before dim light melatonin offset, is linked to impaired insulin sensitivity, suggesting the need to characterize dim light melatonin offset and identify risk for morning circadian misalignment. METHODS: We examined the distributions of dim light melatonin offset clock hour and the phase relationship between dim light melatonin offset and waketime, and associations between dim light melatonin offset, phase relationship, and chronotype in healthy adults (N = 62) who completed baseline protocols measuring components of the circadian melatonin rhythm and chronotype. RESULTS: 74.4% demonstrated dim light melatonin offset after waketime, indicating most healthy adults wake up before the end of biological night. Later chronotype (morningness-eveningness, mid-sleep on free days corrected, and average mid-sleep) was associated with later dim light melatonin offset clock hour. Later chronotype was also associated with a larger, positive phase relationship between dim light melatonin offset and waketime, except for morningness-eveningness. CONCLUSIONS: These findings suggest morning circadian misalignment risk among healthy adults, which would not be detected if only dim light melatonin onset were assessed. Chronotype measured by sleep timing may better predict this risk in healthy adults keeping a consistent sleep schedule than morningness-eveningness preferences. Additional research is needed to develop circadian biomarkers to predict dim light melatonin offset and evaluate appropriate dim light melatonin offset timing to promote health.

Resistant starch: a promising dietary agent for the prevention/treatment of inflammatory bowel disease and bowel cancer.

PURPOSE OF REVIEW: Resistant starch represents a diverse range of indigestible starch-based dietary carbohydrates. Resistant starch has been investigated in the past for its effects on bowel health (pH, epithelial thickness, and apoptosis of colorectal cancer cells); reduction in postprandial glycemia; increased insulin sensitivity; and effects on the gut microbiome. This review highlights advances as resistant starch gains clinical relevance as a potential treatment/preventive tool for diseases such as colorectal cancer (CRC) and diabetes. RECENT FINDINGS: Recent articles have evaluated the comparative physiological effects of different types of resistant starch and investigated the effects of resistant starch on blood lipids, body weight, and defining resistant starch-induced changes to the micriobiome that may be important in health and disease. The most novel and relevant recent data describe a role for resistant starch in ameliorating inflammation; the use of resistant starch for optimal bowel health and prevention of CRC; and, further, that the systemic effects of resistant starch may be important for the treatment of other forms of cancer, such as breast cancer. SUMMARY: This review describes advances in resistant starch research highlighting the gastrointestinal effects that are now being linked to systemic, whole body effects with clinical relevance. These effects have important implications for overall health and the prevention or amelioration of various chronic diseases.

Long-Term Retention of Young Adult Study Participants with Youth-Onset Type 2 Diabetes: Results from the TODAY2 Study.

INTRODUCTION: The Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) trial examined the effects of three treatment arms in a group of racially and ethnically diverse adolescents and youth with type 2 diabetes mellitus. TODAY2 was an observational follow-up study reporting outcomes and complications in these participants after having diabetes for approximately 13 years. Participant retention was essential to fulfill this objective. This report describes the motivations and problems participants self-reported related to continuing in this study. METHODS: The TODAY2 retention survey was administered to participants with a mean age of 27 years, 36% non-Hispanic black, 18% non-Hispanic white, 39% Hispanic, 52% public, and 35% private healthcare coverage, who completed the last study visit (63.8% of original TODAY cohort). The survey listed potential benefits and barriers to staying in the trial. Participants indicated agreement or disagreement with each statement using a four-point Likert-type scale. RESULTS: More than 93% of survey responders agreed with the benefits listed for staying in TODAY2. The most cited reason for staying in the study was related to the strong relationship that participants had with study staff. The common barriers to attending trial visits were tending to other medical problems, fear of disappointing study staff, and school/work scheduling conflicts. Participants with public healthcare coverage were more likely to endorse benefits related to diabetes care (e.g., getting the latest test results, staying motivated to care for my diabetes) and monetary compensation, whereas participants with poor glycemic control cited that a barrier to attending study visits was "fear of disappointing" study staff. CONCLUSION: In a racially and ethnically diverse population of youth-onset type 2 diabetes, benefits and barriers associated with long-term retention are described. These findings can be used to help inform future retention strategies for young adults in clinical trials.

The spectrum of eating environments encountered in free living adults documented using a passive capture food intake wearable device.

Introduction: The aim of this feasibility and proof-of-concept study was to examine the use of a novel wearable device for automatic food intake detection to capture the full range of free-living eating environments of adults with overweight and obesity. In this paper, we document eating environments of individuals that have not been thoroughly described previously in nutrition software as current practices rely on participant self-report and methods with limited eating environment options. Methods: Data from 25 participants and 116 total days (7 men, 18 women, Mage = 44 ± 12 years, BMI 34.3 ± 5.2 kg/mm2), who wore the passive capture device for at least 7 consecutive days (≥12h waking hours/d) were analyzed. Data were analyzed at the participant level and stratified amongst meal type into breakfast, lunch, dinner, and snack categories. Out of 116 days, 68.1% included breakfast, 71.5% included lunch, 82.8% included dinner, and 86.2% included at least one snack. Results: The most prevalent eating environment among all eating occasions was at home and with one or more screens in use (breakfast: 48.1%, lunch: 42.2%, dinner: 50%, and snacks: 55%), eating alone (breakfast: 75.9%, lunch: 89.2%, dinner: 74.3%, snacks: 74.3%), in the dining room (breakfast: 36.7%, lunch: 30.1%, dinner: 45.8%) or living room (snacks: 28.0%), and in multiple locations (breakfast: 44.3%, lunch: 28.8%, dinner: 44.8%, snacks: 41.3%). Discussion: Results suggest a passive capture device can provide accurate detection of food intake in multiple eating environments. To our knowledge, this is the first study to classify eating occasions in multiple eating environments and may be a useful tool for future behavioral research studies to accurately codify eating environments.

I2N: image to nutrients, a sensor guided semi-automated tool for annotation of images for nutrition analysis of eating episodes.

Introduction: Dietary assessment is important for understanding nutritional status. Traditional methods of monitoring food intake through self-report such as diet diaries, 24-hour dietary recall, and food frequency questionnaires may be subject to errors and can be time-consuming for the user. Methods: This paper presents a semi-automatic dietary assessment tool we developed - a desktop application called Image to Nutrients (I2N) - to process sensor-detected eating events and images captured during these eating events by a wearable sensor. I2N has the capacity to offer multiple food and nutrient databases (e.g., USDA-SR, FNDDS, USDA Global Branded Food Products Database) for annotating eating episodes and food items. I2N estimates energy intake, nutritional content, and the amount consumed. The components of I2N are three-fold: 1) sensor-guided image review, 2) annotation of food images for nutritional analysis, and 3) access to multiple food databases. Two studies were used to evaluate the feasibility and usefulness of I2N: 1) a US-based study with 30 participants and a total of 60 days of data and 2) a Ghana-based study with 41 participants and a total of 41 days of data). Results: In both studies, a total of 314 eating episodes were annotated using at least three food databases. Using I2N's sensor-guided image review, the number of images that needed to be reviewed was reduced by 93% and 85% for the two studies, respectively, compared to reviewing all the images. Discussion: I2N is a unique tool that allows for simultaneous viewing of food images, sensor-guided image review, and access to multiple databases in one tool, making nutritional analysis of food images efficient. The tool is flexible, allowing for nutritional analysis of images if sensor signals aren't available.

Randomization to a Provided Higher-Complex-Carbohydrate Versus Conventional Diet in Gestational Diabetes Mellitus Results in Similar Newborn Adiposity.

OBJECTIVE: Nutrition therapy for gestational diabetes mellitus (GDM) has conventionally focused on carbohydrate restriction. In a randomized controlled trial (RCT), we tested the hypothesis that a diet (all meals provided) with liberalized complex carbohydrate (60%) and lower fat (25%) (CHOICE diet) could improve maternal insulin resistance and 24-h glycemia, resulting in reduced newborn adiposity (NB%fat; powered outcome) versus a conventional lower-carbohydrate (40%) and higher-fat (45%) (LC/CONV) diet. RESEARCH DESIGN AND METHODS: After diagnosis (at ∼28-30 weeks' gestation), 59 women with diet-controlled GDM (mean ± SEM; BMI 32 ± 1 kg/m2) were randomized to a provided LC/CONV or CHOICE diet (BMI-matched calories) through delivery. At 30-31 and 36-37 weeks of gestation, a 2-h, 75-g oral glucose tolerance test (OGTT) was performed and a continuous glucose monitor (CGM) was worn for 72 h. Cord blood samples were collected at delivery. NB%fat was measured by air displacement plethysmography (13.4 ± 0.4 days). RESULTS: There were 23 women per group (LC/CONV [214 g/day carbohydrate] and CHOICE [316 g/day carbohydrate]). For LC/CONV and CHOICE, respectively (mean ± SEM), NB%fat (10.1 ± 1 vs. 10.5 ± 1), birth weight (3,303 ± 98 vs. 3,293 ± 81 g), and cord C-peptide levels were not different. Weight gain, physical activity, and gestational age at delivery were similar. At 36-37 weeks of gestation, CGM fasting (86 ± 3 vs. 90 ± 3 mg/dL), 1-h postprandial (119 ± 3 vs. 117 ± 3 mg/dL), 2-h postprandial (106 ± 3 vs. 108 ± 3 mg/dL), percent time in range (%TIR; 92 ± 1 vs. 91 ± 1), and 24-h glucose area under the curve values were similar between diets. The %time >120 mg/dL was statistically higher (8%) in CHOICE, as was the nocturnal glucose AUC; however, nocturnal %TIR (63-100 mg/dL) was not different. There were no between-group differences in OGTT glucose and insulin levels at 36-37 weeks of gestation. CONCLUSIONS: A ∼100 g/day difference in carbohydrate intake did not result in between-group differences in NB%fat, cord C-peptide level, maternal 24-h glycemia, %TIR, or insulin resistance indices in diet-controlled GDM.