School Nutrition Personnel Perceptions of School Salad Bars before and after COVID-19.

Many schools have salad bars as a means to increase students' fruit and vegetable intake. School nutrition programs experienced drastic changes to the school food environment due to COVID-19. The aim of the current study was to understand cafeteria personnel's experiences related to salad bar implementation before the COVID-19 pandemic and in the current school environment to inform efforts to enhance salad bar sustainability. Seven elementary schools (N = 30 personnel) installed salad bars prior to COVID-19; three of these schools (n = 13 personnel) re-opened salad bars after COVID-19. Cafeteria personnel completed surveys assessing their experiences with salad bars at both time points. Satisfaction with salad bar implementation and training was high pre- and post-COVID-19. Most agreed that salad bars increased students' fruit and vegetable intake, yet had concerns about cleanliness and waste. Perceived job difficulty increased post-COVID-19 (p = 0.01), and satisfaction with student salad bar training decreased (p = 0.001). Additional staff support and greater student training were needed post-COVID-19. Overall, salad bars were viewed favorably; however, more challenges and lower satisfaction were reported following COVID-19. Increasing support for cafeteria personnel is needed for salad bar sustainability and improving the school food environment.

Dietary Supplement Use in Transmasculine People: Results of an Online Survey of Volunteer Adults.

INTRODUCTION: Health inequities and disparities in nutrition research exist among transmasculine people. A dearth of evidence on dietary supplement use and motivations exist, partially due to constrained collection of sex and gender identity in national surveys. OBJECTIVE: We sought to investigate common motivations and use of dietary supplements in a voluntary survey of transmasculine people. METHODS: A total of 48 participants completed an online survey detailing dietary supplement use, motivations, and demographic information. RESULTS: 64.5 and 90.0% of participants reported use of 1+ dietary supplement within the past 30-days and during some point in their lifetime, respectively. Top reported product types used included multivitamins (52%), melatonin (52%), vitamin D (46%), vitamin C (35%), fish oil (33%), B-vitamins or B-complex (31%), iron (29%), green tea (29%), biotin (25%), cranberry (23%), zinc (23%), protein powder (23%), probiotics (23%), and calcium (21%). There was no relationship between the number of supplements reported and participant age, BMI, income, or mastectomy status (p > 0.05). Participants reported top motivations being for "improving my overall health" (60.4%), "maintaining health" (54.2%), to "supplement my diet due to not getting enough from food"(41.7%), "mental health" (39.6%), and to "prevent colds, boost immune system" (33.3%). CONCLUSION: Transmasculine people in our study reported a high use of dietary supplements. Differences in the types of products and number of products used, as well as specific motivations for use likely exist within this subpopulation, however, future nationally-representative longitudinal studies are needed to fully elucidate these patterns and for informing evidence-based nutrition guidance.

Food sources of energy and nutrients among US college students: The Health Starts Here cohort study.

Objective: Identifying the food sources contributing most to total energy percentage, macronutrients, vitamin and mineral consumption among college freshmen, and whether sex played a role. Participants: First-year undergraduate students (N = 269). Methods: Diet was assessed using a DHQ-III and estimated with food source composition tables. Nutrient intakes were expressed as a percentage of total dietary intakes for each food category. Mann-Whitney U tests were used to determine the differences between the two sexes for each food category. Results: A significant proportion of energy and nutrients is contributed by certain food categories, such as grain products, meat, poultry, fish; however, other less desirable sources of energy and nutrient are also identified, including sugary and sports drinks. Among female students, a greater portion of nutritional intakes came from healthier choices. Conclusions: A majority of total energy intake comes from food categories that are energy-dense but also provide essential nutrients.

Design and rationale for evaluating the impact of salad bars on elementary school students' fruit, vegetable, and energy intake: a wait list control, cluster randomized controlled trial.

BACKGROUND: Most children do not consume the recommended amount of fruit and vegetable (FV) servings. Changing the school food environment can be a cost-efficient, effective approach to improving children's dietary quality. There is great popular support for school salad bars as a means to increase children's FV intake within the National School Lunch Program (NSLP), yet empirical research is limited. Further, although FV consumption can facilitate healthy weight management if these foods replace high calorie items, there is a need to enhance understanding of salad bars' influence on children's diet quality and energy intake within the NSLP. This is particularly important to investigate in schools in communities characterized by high poverty, as students they serve are particularly likely to rely on school meals. METHODS: This report describes the design and rationale of a federally-funded investigation that uses validated methods to evaluate school salad bars. This district plans to install salad bars into 141 elementary schools over 5-years, facilitating the conduct of a waitlist control, cluster randomized controlled trial. Specifically, 12 pairs of matched schools will be randomly selected: half receiving a salad bar (Intervention) and half serving pre-portioned FVs only, standard under the NSLP (Control). Thus, groups will have different FV presentation methods; however, all schools will operate under a policy requiring students to take at least one FV serving. Schools will be matched on Title I status and percent of racial/ethnic minoritized students. Intake will be objectively assessed at lunch in each school pair, prior to (baseline), and 4-6 weeks after salad bars are installed (post), yielding ~ 14,160 lunch observations throughout the study duration. Cafeteria sales and NSLP participation data will be obtained to determine how salad bars impact revenues. Finally, implementation factors and cafeteria personnel's perspectives will be assessed, to identify barriers and facilitators to salad bars use and inform sustainability efforts. Proposed methods and current status of this investigation due to COVID-19 are described. DISCUSSION: Results will have great potential to inform school nutrition policies and programs designed to improve dietary quality and reduce obesity. TRIAL REGISTRATION: Retrospectively registered (10/28/22) in clinicaltrials.gov (NCT05605483).

Loneliness is associated with unhealthful dietary behaviors and physical inactivity among US college students.

Objective: To evaluate dietary and physical activity behavior in relation to loneliness among college students. Participants: Three-hundred forty-six incoming first-year students in Fall 2019 at a large state University in the US. Methods: Students completed online surveys in Fall 2019. Multivariable regression analyses were used to model associations of health behaviors with loneliness, adjusting for gender and body mass index (BMI). Results: Two-hundred sixty-four students were included in this analysis. Students in loneliness score ranges of 4-6 and 7-9 have higher fat diet than students in score range of 10-12 (p = .007). Sedentary (19.2%) and low active (53.8%) behaviors were more frequent in students reporting high loneliness than those reporting low loneliness (13.8%, 36.7%, respectively) (p = .006). Conclusions: In this sample of college students, loneliness was related to altered diet quality and physical inactivity. Interventions to reduce loneliness may have a positive effect on health promotion in this population.

Why don't college freshmen meet the US dietary guidelines for added sugar, refined grains, sodium, and saturated fat?

OBJECTIVE: The objective of the study was to evaluate how well college students meet U.S. dietary guidelines by examining the mean intakes of nutrients to limit (sodium, sugar, refined grains, and saturated fat), and what factors lead to exceeding the dietary recommendations. PARTICIPANTS: Participants were first-year undergraduate students (N = 269). METHODS: Diet was assessed using a DHQ-III and estimated with food source composition tables. Multivariable logistic regression analysis was used to model variables associated with exceeding the recommendations. One-sample t-tests were performed to compare the cohort with national intakes. RESULTS: One-third met added sugar guidelines; only 4% met daily refined grains requirements, Fewer than half met saturated fat guidelines, and slightly over half met recommended sodium guidelines. Level of physical activity, race/ethnicity, and living on campus were the important predictors for exceeding recommended intakes. CONCLUSIONS: Most students do not adhere to the U.S. dietary guidelines for nutrients to limit.

Dietary Intake and Representativeness of a Diverse College-Attending Population Compared with an Age-Matched US Population.

Young adults typically gain more dietary autonomy as they start college, though this can also present nutritional challenges; however, research on the generalizability of their dietary intake data is scarce. To address this representativeness concern, we compared food and nutrient intakes reported by college freshmen attending a large, diverse university to an age-matched sample from the National Health and Nutrition Examination Survey (NHANES). We studied 269 students 18-24 years old recruited through the Mason: Health Start Here (HSH) study, a population-based cohort study of college students. Diet was assessed using a diet history questionnaire (DHQ-III) and estimated with food source composition tables. The NHANES sample of 835 adults was the reference dataset. Reported dietary intakes were weighted and compared with national intakes via t-tests. We observed comparable energy, carbohydrate, fat, and protein intakes in both groups; however, the HSH cohort reported a higher density intake of most micronutrients than the NHANES sample. Differences between these samples in intake, mode of dietary assessment administration, and reactivity may help explain the differences detected. These results demonstrate that when appropriately contextualized in terms of methodology and potential sources of bias, single college studies can be useful for understanding nutrition in young adults more broadly.

Protocol for the Mason: Health Starts Here prospective cohort study of young adult college students.

BACKGROUND: Young adulthood is a period of increasing independence for the 40% of young adults enrolled in U.S. colleges. Previous research indicates differences in how students' health behaviors develop and vary by gender, race, ethnicity, and socioeconomic status. George Mason University is a state institution that enrolls a highly diverse student population, making it an ideal setting to launch a longitudinal cohort study using multiple research methods to evaluate the effects of health behaviors on physical and psychological functioning, especially during the COVID-19 pandemic. RESULTS: Mason: Health Starts Here was developed as a longitudinal cohort study of successive waves of first year students that aims to improve understanding of the natural history and determinants of young adults' physical health, mental health, and their role in college completion. The study recruits first year students who are 18 to 24 years old and able to read and understand English. All incoming first year students are recruited through various methods to participate in a longitudinal cohort for 4 years. Data collection occurs in fall and spring semesters, with online surveys conducted in both semesters and in-person clinic visits conducted in the fall. Students receive physical examinations during clinic visits and provide biospecimens (blood and saliva). CONCLUSIONS: The study will produce new knowledge to help understand the development of health-related behaviors during young adulthood. A long-term goal of the cohort study is to support the design of effective, low-cost interventions to encourage young adults' consistent performance of healthful behaviors, improve their mental health, and improve academic performance.

Effect of Overeating Dietary Protein at Different Levels on Circulating Lipids and Liver Lipid: The PROOF Study.

BACKGROUND: During overeating, a low protein diet slowed the rate of weight gain and increased the energy cost of the added weight, suggesting that low protein diets reduced energy efficiency. The Protein Overfeeding (PROOF) study explored the metabolic changes to low and high protein diets, and this sub-study examined the changes in body composition and blood lipids when eating high and low protein diets during overeating. METHODS: Twenty-three healthy volunteers (M = 14; F = 9) participated in an 8-week, parallel arm study where they were overfed by ~40% with diets containing 5% (LPD = low protein diet), 15% (NPD = normal protein diet), or 25% (HPD = high protein diet) protein. Dual energy X-ray absorptiometry (DXA) and computer tomography (CT) were used to quantify whole body and abdominal fat and intrahepatic lipid, respectively. Metabolites were measured by standard methods. RESULTS: Protein intake and fat intake were inversely related since carbohydrate intake was fixed. Although overeating the LPD diet was associated with a significant increase in high density lipoprotein (HDL)-cholesterol (p < 0.001) and free fatty acids (p = 0.034), and a significant decrease in fat free mass (p < 0.0001) and liver density (p = 0.038), statistical models showed that dietary protein was the main contributor to changes in fat free mass (p = 0.0040), whereas dietary fat was the major predictor of changes in HDL-cholesterol (p = 0.014), free fatty acids (p = 0.0016), and liver fat (p = 0.0007). CONCLUSIONS: During 8 weeks of overeating, the level of dietary protein intake was positively related to the change in fat free mass, but not to the change in HDL-cholesterol, free fatty acids, and liver fat which were, in contrast, related to the intake of dietary fat.

Perfluoroalkyl substances and changes in bone mineral density: A prospective analysis in the POUNDS-LOST study.

BACKGROUND: Recent studies suggested an inverse association between exposures to perfluoroalkyl substances (PFASs) and bone mineral density (BMD). Whether exposures to PFASs are also associated with changes in BMD has not been examined. METHODS: Five major PFASs (perfluorooctanesulfonic acid, PFOS; perfluorooctanoic acid, PFOA; perfluorohexanesulfonic acid, PFHxS; perfluorononanoic acid, PFNA; perfluorodecanoic acid, PFDA) and BMD (g/cm2) at six bone sites (spine, total hip, femoral neck, hip intertrochanteric area, hip trochanter, and hip Ward's triangle area) were measured at baseline among 294 participants in the POUNDS-LOST study, a weight-loss trial, of whom a total of 175 participants had BMD measured at both baseline and year 2. Linear regression was used to model the differences or changes in BMD for each SD increment of PFAS concentrations. In a secondary analysis, interactions between PFASs and baseline body mass index (BMI), as well as a BMI-related genetic risk score (GRS) derived from 97 BMI-predicting SNPs were examined in relation to changes in BMD. RESULTS: At baseline, both PFOS and PFOA were significantly associated with lower BMD at several sites. For each SD increase of PFOS, the ßs (95% CIs) for BMD were -0.020(-0.037, -0.003) for spine, -0.013(-0.026, 0.001) for total hip, -0.014(-0.028, 0.000) for femoral neck, and -0.013(-0.026, 0.000) for hip trochanter. For PFOA, the corresponding figures were -0.021(-0.038, -0.004) for spine, -0.015(-0.029, -0.001) for total hip, and -0.015(-0.029, -0.002) for femoral neck. After adjusting for baseline covariates and 2-year weight change, higher baseline plasma concentrations of PFOS, PFNA, and PFDA were associated with greater reduction in BMD in the hip; the ßs (95% CIs) were -0.005(-0.009, -0.001), -0.006(-0.010, -0.001), and -0.005(-0.009, -0.001), respectively. Similar associations were found in hip intertrochanteric area for all PFASs except PFHxS, with ßs ranging from -0.006 for PFOA to -0.008 for PFOS and PFNA. Participants with a higher GRS tended to have less PFAS-related BMD decline in total hip (Pinteraction = 0.005) and the hip intertrochanteric area (Pinteraction = 0.021). There were similar PFAS-related BMD changes by baseline BMI levels, although the interactions did not achieve statistical significance. CONCLUSIONS: This study demonstrated that higher plasma PFAS concentrations were not only associated with a lower BMD at baseline, but also a faster BMD loss in a weight-loss trial setting. Genetic predisposition to larger body size may somewhat attenuate the deleterious effects of PFASs on BMD. Further exploration of the possible impact of PFAS exposures on bone density is warranted.

Plasma fatty acyl-carnitines during 8 weeks of overfeeding: relation to diet energy expenditure and body composition: the PROOF study.

OBJECTIVE: Overfeeding is a strategy for evaluating the effects of excess energy intake. In this secondary analysis we tested the possibility that different levels of dietary protein might differentially modify the response of fatty acyl-carnitines to overfeeding. METHODS: Twenty-three healthy adult men and women were overfed by 40% for 8 weeks while in-patients with diets containing 5% (LPD), 15% (NPD) or 25% (HPD) protein. Plasma fatty acyl-carnitines were measured by gas chromatography/mass spectrometry (GC/MS) at baseline and after 8 weeks of overfeeding. Measurements included: body composition by DXA, energy expenditure by ventilated hood and doubly-labeled water, fat cell size from subcutaneous fat biopsies, and fat distribution by CT scan. RESULTS: Analysis was done on 5 groups of fatty acyl-carnitines identified by principal components analysis and 6 individual short-chain fatty acyl carnitines. Higher protein intake was associated with significantly lower 8 week levels of medium chain fatty acids and C2, C4-OH and C 6:1, but higher values of C3 and C5:1 acyl-carnitines derived from essential amino acids. In contrast energy and fat intake were only weakly related to changes in fatty acyl-carnitines. A decease or smaller rise in 8 week medium chain acyl-carnitines was associated with an increase in sleeping energy expenditure (P = 0.0004), and fat free mass (P < 0.0001) and a decrease in free fatty acid concentrations (FFA) (P = 0.0067). In contrast changes in short-chain fatty acyl-carnitines were related to changes in resting energy expenditure (P = 0.0026), and fat free mass (P = 0.0007), and C4-OH was positively related to FFA (P = 0006). CONCLUSION: Protein intake was the major factor influencing changes in fatty acyl carnitines during overfeeding with higher values of most acyl-fatty acids on the low protein diet. The association of dietary protein and fat intake may explain the changes in energy expenditure and metabolic variables resulting in the observed patterns of fatty acyl carnitines.

Plasma Amino Acids During 8 Weeks of Overfeeding: Relation to Diet Body Composition and Fat Cell Size in the PROOF Study.

OBJECTIVE: Different amounts of dietary protein during overfeeding produced similar fat gain but different amounts of gain in fat-free body mass. Protein and energy intake may have differential effects on amino acids during overfeeding. METHODS: Twenty-three healthy adult men and women were overfed by 40% for 8 weeks with 5%, 15%, or 25% protein diets. Plasma amino acids were measured by gas chromatography and mass spectrometry at baseline and week 8. Body composition was measured by dual-energy x-ray absorptiometry, fat cell size (FCS) from subcutaneous fat biopsies, and insulin resistance by euglycemic-hyperinsulinemic clamp. RESULTS: The following three amino acid patterns were seen: increasing concentration of five essential and three nonessential amino acids with increasing protein intake, higher levels of six nonessential amino acids with the low-protein diet, and a pattern that was flat or "V" shaped. Dietary fat and protein were both correlated with changes in valine, leucine/isoleucine/norleucine, phenylalanine, and tyrosine, but energy intake was not. The change in fat mass and weight was related to the change in several amino acids. Baseline FCS and the interaction between glucose disposal and FCS were associated with changes in several amino acids during overfeeding. CONCLUSIONS: Overfeeding dietary protein affects the levels of both essential and nonessential amino acids.

Effect of Three Levels of Dietary Protein on Metabolic Phenotype of Healthy Individuals With 8 Weeks of Overfeeding.

CONTEXT: Obesity is associated with insulin resistance and other metabolic changes that might be modified by overfeeding diets with different protein levels. OBJECTIVE: The objective of the study was to determine the effect of overfeeding diets with 5%, 15%, or 25% energy from protein on insulin sensitivity and compartments of body fat in healthy men and women. METHODS: Fifteen men and five women were overfed by approximately 40% for 56 days with 5% (low protein), 15% (normal protein), or 25% (high protein) protein diets. Insulin sensitivity was measured using a two-step insulin clamp at baseline and at 8 weeks. Body composition and fat distribution were measured by dual-energy x-ray absorptiometry and multislice computed tomography scan and abdominal sc fat cell size was determined on osmium-fixed fat cells. SETTING: This was an in-patient metabolic ward study. MAIN OUTCOME MEASURES: Insulin sensitivity and free fatty acids during low and high levels of insulin infusion before and after 8 weeks after overfeeding and changes in body fat distribution from computed tomography were measured. RESULTS: Total body fat mass, fat-free mass (FFM), visceral adipose tissue (VAT), and deep sc fat all increased with overfeeding. FFM and intrahepatic lipid increased more on the high protein diet, whereas percentage BF and fasting free fatty acids (FFAs) increased more on the low protein diet. Baseline fat cell size predicted the increase in VAT and the magnitude of FFA suppression during the high-dose insulin clamp. Acute release of insulin at baseline predicted the increase in deep sc fat but not VAT. Fasting insulin and glucose increased with overfeeding, but glucose disposal as measured by the clamp was not changed. Suppression of FFAs was less complete during the high-dose insulin infusion after overfeeding. CONCLUSION: Eight weeks of overfeeding, which increased fat mass including expansion of visceral and deep sc tissues and intrahepatic lipid, increased fasting insulin and glucose, impaired the suppression of FFA but did not produce whole-body insulin resistance.

Effect of protein overfeeding on energy expenditure measured in a metabolic chamber.

BACKGROUND: Energy expenditure (EE) increases with overfeeding, but it is unclear how rapidly this is related to changes in body composition, increased body weight, or diet. OBJECTIVE: The objective was to quantify the effects of excess energy from fat or protein on energy expenditure of men and women living in a metabolic chamber. DESIGN: We conducted a randomized controlled trial in 25 participants who ate ∼40% excess energy for 56 d from 5%, 15%, or 25% protein diets. Twenty-four-hour EE (24EE) and sleeping EE (SleepEE) were measured on days 1, 14, and 56 of overfeeding and on day 57 while consuming the baseline diet (usually day 57). Metabolic and molecular markers of muscle metabolism were measured in skeletal muscle biopsy specimens. RESULTS: In the low-protein diet group whose excess energy was fat, the 24EE and SleepEE did not increase during the first day of overfeeding. When extra energy contained protein, both 24EE and SleepEE increased in relation to protein intake (r = 0.50, P = 0.02). The 24EE over 8 wk in all 3 groups was correlated with protein intake (r = 0.60, P = 0.004) but not energy intake (r = 0.16; P = 0.70). SleepEE was unchanged by overfeeding in the low-protein diet group, and baseline surface area predicted increased 24EE in this group. Protein and fat oxidation were reciprocally related during overfeeding. Observed 24EE was higher than predicted on days 1 (P ≤ 0.05), 14 (P = 0.0001), and 56 (P = 0.0007). There was no relation between change in fat mass and change in EE. CONCLUSIONS: Excess energy, as fat, does not acutely increase 24EE, which rises slowly as body weight increases. Excess energy as protein acutely stimulates 24EE and SleepEE. The strongest relation with change in 24EE was the change in energy expenditure in tissue other than muscle or fat-free mass.

Effects of weight gain induced by controlled overfeeding on physical activity.

It is unclear whether physical activity changes following long-term overfeeding and in response to different dietary protein intakes. Twenty-five (16 males, 9 females) healthy adults (18-35 yr) with BMI ranging from 19 to 30 kg/m(2) enrolled in this inpatient study. In a parallel group design, participants were fed 140% of energy needs, with 5, 15, or 25% of energy from protein, for 56 days. Participants wore an RT3 accelerometer for at least 59 days throughout baseline and during overfeeding and completed 24-h whole room metabolic chamber assessments at baseline and on days 1, 14, and 56 of overfeeding and on day 57, when the baseline energy intake was consumed, to measure percent of time active and spontaneous physical activity (SPA; kcal/day). Changes in activity were also assessed by doubly labeled water (DLW). From accelerometry, vector magnitude (VM), a weight-independent measure of activity, and activity energy expenditure (AEE) increased with weight gain during overfeeding. AEE remained increased after adjusting for changes in body composition. Activity-related energy expenditure (AREE) from DLW and percent activity and SPA in the metabolic chamber increased with overfeeding, but SPA was no longer significant after adjusting for change in body composition. Change in VM and AEE were positively correlated with weight gain; however, change in activity was not affected by protein intake. Overfeeding produces an increase in physical activity and in energy expended in physical activity after adjusting for changes in body composition, suggesting that increased activity in response to weight gain might be one mechanism to support adaptive thermogenesis.

Interaction between dietary fat and exercise on excess postexercise oxygen consumption.

The objective of this study was to determine the effect of increased physical activity on subsequent sleeping energy expenditure (SEE) measured in a whole room calorimeter under differing levels of dietary fat. We hypothesized that increased physical activity would increase SEE. Six healthy young men participated in a randomized, single-blind, crossover study. Subjects repeated an 8-day protocol under four conditions separated by at least 7 days. During each condition, subjects consumed an isoenergetic diet consisting of 37% fat, 15% protein, and 48% carbohydrate for the first 4 days, and for the following 4 days SEE and energy balance were measured in a respiration chamber. The first chamber day served as a baseline measurement, and for the remaining 3 days diet and activity were randomly assigned as high-fat/exercise, high-fat/sedentary, low-fat/exercise, or low-fat/sedentary. Energy balance was not different between conditions. When the dietary fat was increased to 50%, SEE increased by 7.4% during exercise (P < 0.05) relative to being sedentary (baseline day), but SEE did not increase with exercise when fat was lowered to 20%. SEE did not change when dietary fat was manipulated under sedentary conditions. Physical activity causes an increase in SEE when dietary fat is high (50%) but not when dietary fat is low (20%). Dietary fat content influences the impact of postexercise-induced increases in SEE. This finding may help explain the conflicting data regarding the effect of exercise on energy expenditure.

Neck circumference is a predictor of metabolic syndrome and obstructive sleep apnea in short-sleeping obese men and women.

BACKGROUND: The constellation of metabolic syndrome, although controversial with regard to its clinical usefulness, is epidemiologically related to increased diabetes risk and cardiovascular mortality. Our goal was to investigate the associations among neck circumference (NC), obstructive sleep apnea syndromes (OSAS), and metabolic syndrome in obese men and women sleeping less than 6.5 hr per night. METHODS: This was a cross-sectional study of obese men and premenopausal obese women sleeping less than 6.5 hr per night. We enrolled 120 individuals (92 women), age 40.5±6.9 years and body mass index (BMI) 38.6±6.5 kg/m(2). Metabolic syndrome severity was assessed by a score and OSAS was defined as a respiratory disturbance index (RDI) ≥5. Metabolic end endocrine parameters were measured, and sleep duration was determined by actigraphy and validated questionnaires. RESULTS: Metabolic syndrome was found in 41% and OSAS in 58% (28% had both). Subjects with metabolic syndrome were 3 years older and more often Caucasian; they had higher RDI scores, larger NC, more visceral fat, lower serum adiponectin, higher 24-hr urinary norepinephrine (NE) excretion, and lower growth hormone concentrations. A NC of ≥38 cm had a sensitivity of 54% and 58% and a specificity of 70% and 79% in predicting the presence of metabolic syndrome and OSAS, respectively. RDI, adiponectin, and NC accounted for approximately 30% of the variability in the metabolic syndrome score, as estimated by an age-, gender-, and race-corrected multivariate model (R(2)=0.376, P<0.001). CONCLUSION: Greater NC is associated with OSAS and metabolic syndrome in short-sleeping obese men and premenopausal obese women. Addition of NC to the definition of metabolic syndrome should be considered and needs to be validated in future studies.

Sleep extension improves neurocognitive functions in chronically sleep-deprived obese individuals.

BACKGROUND: Sleep deprivation and obesity, are associated with neurocognitive impairments. Effects of sleep deprivation and obesity on cognition are unknown, and the cognitive long-term effects of improvement of sleep have not been prospectively assessed in short sleeping, obese individuals. OBJECTIVE: To characterize neurocognitive functions and assess its reversibility. DESIGN: Prospective cohort study. SETTING: Tertiary Referral Research Clinical Center. PATIENTS: A cohort of 121 short-sleeping (<6.5 h/night) obese (BMI 30-55 kg/m(2)) men and pre-menopausal women. INTERVENTION: Sleep extension (468±88 days) with life-style modifications. MEASUREMENTS: Neurocognitive functions, sleep quality and sleep duration. RESULTS: At baseline, 44% of the individuals had an impaired global deficit score (t-score 0-39). Impaired global deficit score was associated with worse subjective sleep quality (p = 0.02), and lower urinary dopamine levels (p = 0.001). Memory was impaired in 33%; attention in 35%; motor skills in 42%; and executive function in 51% of individuals. At the final evaluation (N = 74), subjective sleep quality improved by 24% (p<0.001), self-reported sleep duration increased by 11% by questionnaires (p<0.001) and by 4% by diaries (p = 0.04), and daytime sleepiness tended to improve (p = 0.10). Global cognitive function and attention improved by 7% and 10%, respectively (both p = 0.001), and memory and executive functions tended to improve (p = 0.07 and p = 0.06). Serum cortisol increased by 17% (p = 0.02). In a multivariate mixed model, subjective sleep quality and sleep efficiency, urinary free cortisol and dopamine and plasma total ghrelin accounted for 1/5 of the variability in global cognitive function. LIMITATIONS: Drop-out rate. CONCLUSIONS: Chronically sleep-deprived obese individuals exhibit substantial neurocognitive deficits that are partially reversible upon improvement of sleep in a non-pharmacological way. These findings have clinical implications for large segments of the US population. TRAIL REGISTRATION: www.ClinicalTrials.gov NCT00261898. NIDDK protocol 06-DK-0036.

Variants in glucose- and circadian rhythm-related genes affect the response of energy expenditure to weight-loss diets: the POUNDS LOST Trial.

BACKGROUND: Circadian rhythm has been shown to be related to glucose metabolism and risk of diabetes, probably through effects on energy balance. Recent genome-wide association studies identified variants in circadian rhythm-related genes (CRY2 and MTNR1B) associated with glucose homeostasis. OBJECTIVE: We tested whether CRY2 and MTNR1B genotypes affected changes in measures of energy expenditure in response to a weight-loss diet intervention in a 2-y randomized clinical trial, the POUNDS (Preventing Overweight Using Novel Dietary Strategies) LOST Trial. DESIGN: The variants CRY2 rs11605924 (n = 721) and MTNR1B rs10830963 (n = 722) were genotyped in overweight or obese adults who were randomly assigned to 1 of 4 weight-loss diets that differed in their proportions of macronutrients. Respiratory quotient (RQ) and resting metabolic rate (RMR) were measured. RESULTS: By 2 y of diet intervention, the A allele of CRY2 rs11605924 was significantly associated with a greater reduction in RQ (P = 0.03) and a greater increase in RMR and RMR/kg (both P = 0.04). The G allele of MTNR1B rs10830963 was significantly associated with a greater increase in RQ (P = 0.01) but was not related to changes in RMR and RMR/kg. In addition, we found significant gene-diet fat interactions for both CRY2 (P-interaction = 0.02) and MTNR1B (P-interaction < 0.001) in relation to 2-y changes in RQ. CONCLUSIONS: Our data indicate that variants in the circadian-related genes CRY2 and MTNR1B may affect long-term changes in energy expenditure, and dietary fat intake may modify the genetic effects. This trial was registered at www.clinicaltrials.gov as NCT00072995.

Obstructive sleep apnea is a predictor of abnormal glucose metabolism in chronically sleep deprived obese adults.

CONTEXT: Sleep abnormalities, including obstructive sleep apnea (OSA), have been associated with insulin resistance. OBJECTIVE: To determine the relationship between sleep, including OSA, and glucose parameters in a prospectively assembled cohort of chronically sleep-deprived obese subjects. DESIGN: Cross-sectional evaluation of a prospective cohort study. SETTING: Tertiary Referral Research Clinical Center. MAIN OUTCOME MEASURES: Sleep duration and quality assessed by actigraphy, sleep diaries and questionnaires, OSA determined by a portable device; glucose metabolism assessed by oral glucose tolerance test (oGTT), and HbA1c concentrations in 96 obese individuals reporting sleeping less than 6.5 h on a regular basis. RESULTS: Sixty % of subjects had an abnormal respiratory disturbance index (RDI≥5) and 44% of these subjects had abnormal oGTT results. Severity of OSA as assessed by RDI score was associated with fasting glucose (R = 0.325, p = 0.001) and fasting insulin levels (ρ = 0.217, p = 0.033). Subjects with moderate to severe OSA (RDI>15) had higher glucose concentrations at 120 min than those without OSA (RDI<5) (p = 0.017). Subjects with OSA also had significantly higher concentrations of plasma ACTH (p = 0.009). Several pro-inflammatory cytokines were higher in subjects with OSA (p<0.050). CRP levels were elevated in this sample, suggesting increased cardiovascular risk. CONCLUSIONS: OSA is associated with impaired glucose metabolism in obese, sleep deprived individuals. Since sleep apnea is common and frequently undiagnosed, health care providers should be aware of its occurrence and associated risks. TRIAL REGISTRATION: This study was conducted under the NIDDK protocol 06-DK-0036 and is listed in ClinicalTrials.gov NCT00261898.