The Effects of a High-Carbohydrate versus a High-Fat Shake on Biomarkers of Metabolism and Glycemic Control When Used to Interrupt a 38-h Fast: A Randomized Crossover Study.

This study aimed to determine the impact of various fast-interrupting shakes on markers of glycemic control including glucose, ß-hydroxybutyrate (BHB), insulin, glucagon, GLP-1, and GIP. Twenty-seven sedentary adults (twelve female, fifteen male) with overweight or obesity completed this study. One condition consisted of a 38-h water-only fast, and the other two conditions repeated this, but the fasts were interrupted at 24 h by either a high carbohydrate/low fat (HC/LF) shake or an isovolumetric and isocaloric low carbohydrate/high fat (LC/HF) shake. The water-only fast resulted in 135.3% more BHB compared to the HC/LF condition (p < 0.01) and 69.6% more compared to the LC/HF condition (p < 0.01). The LC/HF condition exhibited a 38.8% higher BHB level than the HC/LF condition (p < 0.01). The area under the curve for glucose was 14.2% higher in the HC/LF condition than in the water condition (p < 0.01) and 6.9% higher compared to the LC/HF condition (p < 0.01), with the LC/HF condition yielding 7.8% more glucose than the water condition (p < 0.01). At the 25-h mark, insulin and glucose-dependent insulinotropic polypeptide (GIP) were significantly elevated in the HC/LF condition compared to the LC/HF condition (p < 0.01 and p = 0.02, respectively) and compared to the water condition (p < 0.01). Furthermore, insulin, GLP-1, and GIP were increased in the LC/HF condition compared to the water condition at 25 h (p < 0.01, p = 0.015, and p < 0.01, respectively). By the 38-h time point, no differences were observed among the conditions for any of the analyzed hormones. While a LC/HF shake does not mimic a fast completely, it does preserve some of the metabolic changes including elevated BHB and glucagon, and decreased glucose and insulin compared to a HC/LF shake, implying a potential for improved metabolic health.

Time Spent Jogging/Running and Biological Aging in 4458 U.S. Adults: An NHANES Investigation.

Telomere length is a good index of cellular aging. Longer telomeres are predictive of longer life, and healthy lifestyles are associated with longer telomeres. This study explored the relationship between time spent jogging or running each week and leukocyte telomere length (LTL) in 4458 randomly selected U.S. adults. The association was studied using data collected by the National Health and Nutrition Examination Survey (NHANES), and a cross-sectional design. Total weekly jog/run time was calculated from survey responses. From the minute totals, three categories were formed: <10 min/week, 10-74 min/week, and ≥75 min/week. Adults in the third category met the U.S. guidelines. Data were analyzed using one-way ANOVA. Partial correlation was used to adjust for differences in potential mediating factors, including demographic and lifestyle/medical factors. In the total sample, after adjusting for all the potential covariates, mean LTL significantly differed across the three jog/run categories (F = 4.1, p = 0.0272). Specifically, adults who met the guidelines via jogging and/or running had significantly longer telomeres than adults who performed no jogging/running. Adults in the middle category did not differ from the other two categories. A minimum of 75 min of jogging/running weekly is predictive of longer telomeres when compared to adults who do not jog or run regularly.

Weight Change over Ten Years Predicts Biological Aging in a Random Sample of 3070 U.S. Adults.

This investigation was designed to study the relationship between weight change over 10 years and leukocyte telomere length (LTL) in a large sample of 3070 randomly selected U.S. adults, 36-70 years old. The National Health and Nutrition Examination Survey (NHANES) data were used to examine the relationship between percent weight change and LTL. Potential mediating variables were controlled using partial correlation. After adjusting for age, race, year, and housing status, the association between percent weight change over 10 years and LTL was significant in women (F = 6.9, p = 0.0138). Adjusting for the demographic and several other covariates weakened the relationship slightly (F = 4.7, p = 0.0392). With all the covariates controlled, for each one percentage point increase in weight over the previous 10 years, telomeres were, on average, 3.48 base pairs (bp) shorter in women. Given that each one-year increase in age was associated with telomeres that were 15.0 bp shorter in women, the median weight change in U.S. women over the previous 10 years (an increase of 10.4%) was predictive of LTLs that were 36 bp shorter, on average, or an increase of 2.4 years of biological aging. Percent weight change over 10 years was not associated with LTL in U.S. men. Percent weight change over 10 years is a strong predictor of biological aging in U.S. women, but not in men.

Relationship between Sitting Time and Insulin Resistance in 6931 U.S. Adults: The Mediating Role of Abdominal Adiposity.

This cross-sectional investigation examined the relationship between sitting time and insulin resistance in 6931 U.S. adults. The mediating effects of several covariates were evaluated. Self-reported sitting time, measured in minutes per day, was the exposure variable. Insulin resistance (IR), indexed using the natural log of the homeostatic model assessment of insulin resistance (L-HOMA-IR), was the outcome variable. This study used data collected from the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Results showed a strong, positive, dose-response association between sitting time and insulin resistance after adjusting for age, sex, race, and year of assessment (F = 12.6, p < 0.0001). Across the sitting time tertiles (low, moderate, and high), the L-HOMA-IR means (±SE) each differed from each other (0.37 ± 0.008, 0.40 ± 0.012, and 0.43 ± 0.012). Further controlling for cigarette smoking and physical activity did not alter the significance of the relationship. Adding body mass index (BMI) to the demographic covariates weakened the relationship, but it remained significant. However, the association was no longer significant after adjusting for the demographic covariates and waist circumference (F = 1.1, p = 0.3349). None of the L-HOMA-IR means (±SE) differed from each other (0.40 ± 0.007, 0.41 ± 0.009, and 0.41 ± 0.008). Overall, waist circumference was a powerful mediating variable between sitting time and insulin resistance. Apparently, time spent sitting is a powerful predictor of IR. However, much of the association between sitting time and IR is a function of differences in waist size. As a strong measure of abdominal adiposity and a significant predictor of multiple metabolic diseases, managing waist size is a health practice to consider when insulin resistance is a concern.

The Effects of Exercise on Appetite-Regulating Hormone Concentrations over a 36-h Fast in Healthy Young Adults: A Randomized Crossover Study.

Hunger and satiety are controlled by several physiological mechanisms, including pancreatic and gastrointestinal hormones. While the influence of exercise and fasting have been described individually, in relation to these hormones, there is a paucity of work showing the effects of the two modalities (fasting and exercise) combined. Twenty healthy adults (11 males, 9 females) completed both conditions of this study, each consisting of a 36-h water-only fast. One of the fasts began with treadmill exercise, and the differences between the conditions on various appetite hormones were measured every 12 h. The difference in the area under the curve between conditions for ghrelin was 211.8 ± 73.1 pg/mL (F = 8.40, p < 0.0105), and, for GLP-1, it was -1867.9 ± 850.4 pg/mL (F = 4.82, p < 0.0422). No significant differences were noted for areas under the curve between conditions for leptin, PP, PYY, insulin, or GIP. Initiating a fast with exercise lowers ghrelin concentrations and elevates GLP-1 concentrations. Given that ghrelin elicits feelings of hunger and GLP-1 signals feelings of satiety, adding exercise to the beginning of a fast may reduce some of the biological drive of hunger, which could make fasting more tolerable, leading to better adherence and more significant health outcomes.

Legume Intake, Body Weight, and Abdominal Adiposity: 10-Year Weight Change and Cross-Sectional Results in 15,185 U.S. Adults.

There were three objectives: (1) evaluate the relationship between legume intake and weight change across the previous 10 years, (2) examine the cross-sectional associations between legume consumption, BMI, and abdominal adiposity, and (3) determine if the relationship between legume intake and the outcomes were influenced by multiple covariates, particularly fiber intake. The sample included 15,185 randomly selected adults representative of the U.S. population. Percent change in weight was used as the outcome measure for the 10-year analysis. BMI, and waist circumference, corrected for height, were employed as the outcomes for the cross-sectional analyses. Legume, fiber, and energy intakes were measured using the average of two 24-h dietary recalls. Legume intake was divided into three categories. Five demographic and five lifestyle covariates were controlled statistically. There was an inverse dose-response relationship between legume intake and percent weight change over the previous 10 years after adjusting for 9 of the covariates (F = 6.5, p = 0.0028). However, after controlling for fiber with the other covariates, there were no differences across the three legume intake groups (F = 1.9, p = 0.1626). The cross-sectional findings showed similar inverse dose-response results until fiber intake was controlled. Then the associations became non-significant. In conclusion, legume intake is a good predictor of percent weight change over the previous 10 years, and it is also a significant predictor of BMI and abdominal adiposity cross-sectionally. These relationships are strongly influenced by fiber consumption. Evidently, legumes have dietary advantages, especially high fiber levels, that seem to be valuable in the battle against weight gain and obesity.

Serum, Dietary, and Supplemental Vitamin D Levels and Insulin Resistance in 6294 Randomly Selected, Non-Diabetic U.S. Adults.

The primary aim of this study was to determine the associations between serum, dietary, and supplemental vitamin D levels and insulin resistance in 6294 non-diabetic U.S. adults. A total of 8 years of data from the 2011−2018 National Health and Nutrition Examination Survey (NHANES) and a cross-sectional design were utilized to answer the research questions. Serum vitamin D levels were quantified using high-performance liquid chromatography−tandem mass spectrometry. Dietary and supplemental vitamin D intakes were assessed using the average of two 24 h dietary recalls taken 3−10 days apart. The homeostatic model assessment (HOMA), based on fasting glucose and fasting insulin levels, was employed to index insulin resistance. Demographic covariates were age, sex, race, and year of assessment. Differences in physical activity, body mass index (BMI), cigarette smoking, body weight, season, and energy intake were also controlled statistically. Serum levels of vitamin D differed significantly, and in a dose−response order, across quartiles of HOMA-IR, after adjusting for year, age, sex, and race (F = 30.3, p < 0.0001) and with all the covariates controlled (F = 5.4, p = 0.0029). Dietary vitamin D levels differed similarly across HOMA-IR quartiles, but to a lesser extent, respectively (F = 8.1, p = 0.0001; F = 2.9, p = 0.0437). Likewise, supplemental vitamin D levels also differed across the HOMA-IR quartiles, respectively (F = 3.5, p = 0.0205; F = 3.3, p = 0.0272). With all the covariates controlled, the odds of having insulin resistance were significantly greater for those in the lowest quartile of serum and supplemental vitamin D intake compared to the other quartiles combined. In conclusion, in this nationally representative sample, serum, dietary, and supplemental vitamin D were each predictive of insulin resistance, especially in those with low serum levels and those with no supplemental intake of vitamin D.

10-Year Weight Gain in 13,802 US Adults: The Role of Age, Sex, and Race.

Purpose: The primary objective of the present investigation was to identify 10-year weight gain patterns in 13,802 US adults and also to determine the extent that differences in 10-year weight gains were associated with the key demographic variables: age, sex, and race. Methods: The study design was cross-sectional and included the years 2011-2018. Data for 2019-2020 were not available because of COVID. A multistage random sampling strategy was employed. Specifically, individual sample weights and randomly selected clusters and strata were used with each statistical model, allowing the results to be generalized to the US adult population. Results: Mean (±SE) 10-year weight gain was 4.2 ± 0.2 kg or 6.6 ± 0.2% of initial body weight. A total of 51% of the participants gained 5% or more body weight, 36% gained 10% or more, and 16% gained 20% or more across the 10-years. Age was linearly and inversely associated with 10-year weight gain, expressed in kg (F = 166.4, P < 0.0001) or percent weight gain (F = 246.9, P < 0.0001), after adjusting for sex and race. For each 1-year increase in age, 10-year weight gain decreased by 0.20 ± 0.02 kg and 0.28 ± 0.02 percent. After adjusting for age and race, 10-year weight gain (kg) was significantly greater (F = 73.6, P < 0.0001) in women (5.4 ± 0.3) than in men (2.6 ± 0.2). Weight gain also differed across races, kg (F = 27.7, P < 0.0001) and % (F = 28.5, P < 0.0001). Non-Hispanic Blacks gained more weight and NH Asians gained less weight than the other races. Conclusion: Without question, 10-year weight gain is a serious problem within the US adult population. Younger adults, women, and Non-Hispanic Blacks, particularly Black women, seem to experience the highest levels of 10-year weight gain. Consequently, obesity and weight gain prevention programs focusing on these at-risk individuals should be a public health priority.

Insulin Resistance and Biological Aging: The Role of Body Mass, Waist Circumference, and Inflammation.

The purpose of this investigation was to evaluate the association between insulin resistance and biological aging in a randomly selected sample of 2,596 U.S. women and men. Another key objective was to examine the extent to which the insulin resistance and biological aging association was influenced by differences in body mass, waist circumference, and systemic inflammation. Biological aging was indexed using the length of leukocyte telomeres. The homeostatic model assessment (HOMA) was employed to index insulin resistance. The body mass index (BMI) was used to represent body mass independent of height. Waist circumference was used to assess abdominal adiposity, and C-reactive protein (CRP) was measured to index body-wide inflammation. Insulin resistance and telomere length were both treated as continuous variables. Results revealed that insulin resistance was related significantly with cellular aging, after adjusting for several demographic covariates (F = 5.7, P = 0.0234). The association remained significant after controlling for multiple demographic and lifestyle covariates together (F = 4.6, P = 0.0410). However, after controlling for BMI, along with the other covariates, insulin resistance was no longer associated with biological aging (F = 2.1, P = 0.1573). After adjusting for differences in waist circumference, along with the demographic and lifestyle covariates, but not BMI, the relationship between insulin resistance and biological aging was negated further (F = 1.5, P = 0.2283). Adjusting for CRP with the demographic and lifestyle covariates, but not BMI or waist circumference, weakened the relationship (F = 4.0, P = 0.0552). Evidently, if all adults in the U.S. had the same BMI or waist circumference, there would not be a relationship between insulin resistance and telomere length. It appears that insulin resistance accounts for differences in biological aging mainly because of differences in BMI and waist circumference, especially the latter.

The effects of daily step goals of 10,000, 12,500, and 15,000 steps per day on neural activity to food cues: A 24-week dose-response randomized trial.

INTRODUCTION: The purpose of this study was to examine the effect of different levels of sustained physical activity on neural reflections of attention allocated toward food cues in first year college women. METHODS: Seventy-nine first-year college women (18.6 ± 0.5 years) were recruited to participate in the study. Women were randomly assigned to a daily step goal of 10,000, 12,500, or 15,000 for 24 weeks. Once during weeks 16-24, participants were shown pictures of plated meals or flowers with the neural response measured using the P300 and late positive potential (LPP) components of the scalp-recorded event-related potential. Diet was assessed using the automated 24-h recall. RESULTS: Both the P300 and LPP amplitudes were significantly more positive to food versus flower pictures (ps < .001). There was no interaction between step group and picture condition for the P300 and LPP. However, the 12,500-step group showed a significantly elevated LPP amplitude in comparison to the other groups for both food and flowers (F(2,74) = 8.84; p < .001). The effect size for the combined results (food and flowers) was 0.56 between 10,000 and 12,500-step groups, and 0.75 between the 12,500- and 15,000-step groups. In addition, the 12,500 group reduced caloric consumption over the course of the intervention (t(1,74) = 3.35, p = .001, dz  = 0.59). CONCLUSION: Habitual physical activity of 10,000, 12,500, or 15,000 steps per day does not preferentially alter neural reflections toward food cues compared to flowers. There may be a nonlinear response to pleasant visual cues, with 12,500 steps per day eliciting higher LPPs than either 10,000 or 15,000.

Macronutrient Intake and Insulin Resistance in 5665 Randomly Selected, Non-Diabetic U.S. Adults.

The main goal of this investigation was to evaluate the relationships between several macronutrients and insulin resistance in 5665 non-diabetic U.S. adults. A secondary objective was to determine the extent to which the associations were influenced by multiple potential confounding variables. A cross-sectional design and 8 years of data from the 2011-2018 National Health and Nutrition Examination Survey (NHANES) were used to answer the research questions. Ten macronutrients were evaluated: total carbohydrate, starch, simple carbohydrate, dietary fiber, total protein, total fat, saturated, polyunsaturated, monounsaturated, and total unsaturated fat. The homeostatic model assessment (HOMA), based on fasting glucose and fasting insulin levels, was used to index insulin resistance. Age, sex, race, year of assessment, physical activity, cigarette smoking, alcohol use, and waist circumference were used as covariates. The relationships between total carbohydrate intake (F = 6.7, p = 0.0121), simple carbohydrate (F = 4.7, p = 0.0344) and HOMA-IR were linear and direct. The associations between fiber intake (F = 9.1, p = 0.0037), total protein (F = 4.4, p = 0.0393), total fat (F = 5.5, p = 0.0225), monounsaturated fat (F = 5.5, p = 0.0224), and total unsaturated fat (F = 6.5, p = 0.0132) were linear and inversely related to HOMA-IR, with 62 degrees of freedom. Starch, polyunsaturated fat, and saturated fat intakes were not related to HOMA-IR. In conclusion, in this nationally representative sample, several macronutrients were significant predictors of insulin resistance in U.S. adults.

Milk-Fat Intake and Differences in Abdominal Adiposity and BMI: Evidence Based on 13,544 Randomly-Selected Adults.

The primary purpose of this investigation was to evaluate the relationship between milk-fat intake and obesity, particularly abdominal obesity, in 13,544 U.S. adults. A lesser objective was to measure the degree to which the association was influenced by multiple potential confounding variables. This cross-sectional study used data from the 2011-2016 National Health and Nutrition Examination Survey (NHANES). Quantity of milk-fat regularly consumed was the exposure variable. Sagittal abdominal diameter (SAD), a measure of abdominal obesity, and body mass index (BMI) were the outcome variables. Sagittal abdominal diameter is a strong predictor of visceral abdominal fat, when measured by computed tomography, and has been shown to predict cardiometabolic disorders better than BMI. After controlling for age, race, gender, physical activity, leisure computer use and gaming, alcohol habits, and cigarette use, significantly lower BMIs were associated with consistent non-fat and full-fat milk consumption (F = 4.1, p = 0.0063). A significantly lower SAD was associated only with regular consumption of non-fat milk (F = 5.0, p = 0.0019). No significant differences were detected between the other milk-fat groups or milk abstainers. In this nationally representative sample, only 19.6% of adults regularly consumed low-fat milk. In conclusion, consistent non-fat milk intake was predictive of lower levels of abdominal adiposity compared to consumption of higher levels of milk-fat.

Fruit and Vegetable Intake and Telomere Length in a Random Sample of 5448 U.S. Adults.

The relationship between fruit and vegetable intake and telomere length was examined using a cross-sectional design and an NHANES random sample of 5448 U.S. adults. Fruit and vegetable (F&V) consumption was assessed using a 24 h recall, and telomere length, an index of cellular aging, was measured using the quantitative polymerase chain reaction method. Telomere length was linearly related to F&V intake when combined (F = 22.7, p < 0.0001) and also when separated as fruit (F = 7.2, p < 0.0121) or vegetables (F = 15.4, p < 0.0005), after adjusting for covariates. Specifically, telomeres were 27.8 base pairs longer for each 100 g (3.5 ounces) of F&V consumed. Because each additional year of chronological age was associated with telomeres that were 14.9 base pairs shorter, when women and men were analyzed together, results indicated that a 100 g (3.5 oz) per day increment in F&V corresponded with 1.9 years less biological aging. When the 75th percentile of F&V intake was compared to the 25th, the difference was 4.4 years of cellular aging. When separated by sex, fruits and vegetables were both related to telomere length in women, but only vegetable intake was predictive of telomere length in men. In conclusion, evidence based on a random sample of U.S. adults indicates that the more the servings of F&V, the longer telomeres tend to be.

The Effects of Exercise on ß-Hydroxybutyrate Concentrations over a 36-h Fast: A Randomized Crossover Study.

PURPOSE: This study assessed ß-hydroxybutyrate (BHB) concentration during a short-term fast and the degree to which an initial bout of exercise influences the rate of ketogenesis. METHODS: Twenty subjects (11 male, 9 female) completed two 36-h fasts, with one protocol requiring the subject to complete a treadmill exercise session at the beginning of the fast. BHB levels were assessed via portable meter every 2 h, along with mood and hunger ratings. Venipuncture was performed every 12 h. RESULTS: The mean (SD) areas under the curve for BHB concentration were 19.19 (2.59) mmol·L-1 (nonexercised) and 27.49 (2.59) mmol·L-1 (exercised), yielding a difference of 8.30 mmol·L-1 between conditions (95% posterior probability interval (PPI), 1.94 to 14.82 mmol·L-1; posterior probability (PP) = 0.99). The mean (SD) times to BHB concentration of 0.5 mmol·L-1 were 21.07 (2.95) h (nonexercised) and 17.5 (1.69) h (exercised), a 3.57-h difference (95% PPI, -2.11 to 10.87 h; PP = 0.89). The differences in area under the curve between conditions were 5.07 µU·mL-1 (95% PPI, -21.64 to 36.18 µU·mL-1; PP = 0.67) for insulin, 97.13 pg·mL-1 (95% PPI, 34.08 to 354.21 pg·mL-1; PP = 0.98) for glucagon, and 20.83 (95% PPI, 4.70 to 24.22; PP = 0.99) for the insulin/glucagon ratio. CONCLUSIONS: Completing aerobic exercise at the beginning of a fast accelerates the production of BHB throughout the fast without altering subjective feelings of hunger, thirst, stomach discomfort, or mood. Insulin and the insulin/glucagon ratio experience a marked reduction within the first 12 h of fasting and was not altered with exercise. Thus, exercising at the beginning of a fast may improve the metabolic outcomes of fasting.

Acute after-school screen time in children decreases impulse control and activation toward high-calorie food stimuli in brain regions related to reward and attention.

The purpose of this study was to examine the effects of after-school sedentary screen time on children's brain activation in reward and cognitive control regions in response to pictures of high- and low-calorie foods. Thirty-two children participated in a randomized crossover study with counterbalanced treatment conditions. Conditions took place on separate days after school and included three hours of active or sedentary play. After each condition, neural activation was assessed using functional magnetic resonance imaging (fMRI) while participants completed a go/no-go task involving pictures of high- and low-calorie foods. General response inhibition was also measured using the Stroop task. Hunger was measured upon arrival to the testing facility and just prior to fMRI scans. Mixed effects models were used to evaluate main effects and interactions. Significant stimulus by condition interactions were found in the right superior parietal cortex, and left anterior cingulate cortex (Ps ≤ 0.05). High-calorie pictures elicited significantly more activation bilaterally in the orbitofrontal cortex compared to low-calorie pictures (Ps ≤ 0.05). Stroop task performance diminished significantly following the sedentary condition compared to the active (P ≤ 0.05). Subjective feelings of hunger were not different between conditions at any point. Sedentary screen time was associated with significantly decreased response inhibition and a reversed brain activation pattern to pictures of high- and low-calorie foods compared to active play, in areas of the brain important to the modulation of food intake. Decreased attention, and impulse control following sedentary screen time may contribute to disinhibited eating that can lead to overweight and obesity.

To play or not to play? The relationship between active video game play and electrophysiological indices of food-related inhibitory control in adolescents.

Sedentary behaviors, such as computer use and sedentary video games, are barriers to physical activity, contribute to overweight and obesity among adolescents, and can adversely affect eating behaviors. Active video games may increase daily physical activity levels among adolescents and improve food-related inhibitory control. We compared the effects of acute bouts of active and sedentary video gaming on event-related potential (ERP) indices of food-related inhibitory control, energy expenditure, and ad libitum eating. In a within-subjects design, 59 adolescent participants (49% female, Mage  = 13.29 ± 1.15) completed two separate counterbalanced, 60-min long video gaming sessions separated by seven days. Immediately after, participants completed two go/no-go tasks with high- and low-calorie images and N2 and P3 ERP amplitudes were measured. Participants also completed a Stroop task and were given high- and low-calorie snacks to consume ad libitum. Results indicated that active relative to sedentary video games significantly increased energy expenditure on multiple measures (e.g., METs, heart rate, kcals burned) and participants consumed more calories after the active compared to the sedentary video game session. N2 amplitudes were larger when participants inhibited to high- compared to low-calorie foods, suggesting that high-calorie foods necessitate increased the recruitment of inhibitory control resources; however, there were non-significant differences for the N2 or P3 amplitudes, accuracy or response times, and Stroop performance between active versus sedentary video game sessions. Overall, sixty minutes of active video gaming increased energy expenditure and food consumption but did not significantly alter neural or behavioral measures of inhibitory control to food stimuli.

Physical Activity and Insulin Resistance in 6,500 NHANES Adults: The Role of Abdominal Obesity.

This cross-sectional investigation studied differences in insulin resistance across levels of physical activity in 6,500 US adults who were randomly selected as part of the National Health and Nutrition Examination Survey (NHANES). Another important objective was to determine the influence of abdominal obesity on the physical activity and insulin resistance relationship. MET-minutes were utilized to quantify total activity based on participation in 48 different physical activities. Two strategies were employed to categorize levels of physical activity: one was based on relative MET-minutes (quartiles), and the other approach was based on the US physical activity guidelines. Insulin resistance was indexed using the homeostatic model assessment (HOMA). Abdominal obesity was indexed using waist circumference. Effect modification was tested by dividing waist circumferences into sex-specific quartiles and then evaluating the relationship between physical activity and HOMA-IR within each quartile separately. Results showed that relative physical activity level was associated with HOMA-IR after controlling for demographic and demographic and lifestyle covariates (F = 11.5, P < 0.0001 and F = 6.0, P=0.0012, respectively). Adjusting for demographic and demographic and lifestyle covariates also resulted in significant relationships between guideline-based activity and HOMA-IR (F = 8.0, P < 0.0001 and F = 4.9, P=0.0017, respectively). However, statistically controlling for differences in waist circumference with the other covariates nullified the relationship between total physical activity and HOMA-IR. Effect modification testing showed that when the sample was delimited to adults with abdominal obesity (Quartile 4), relative (F = 5.6, P=0.0019) and guideline-based physical activity (F = 3.7, P=0.0098) and HOMA-IR were significantly associated. Physical activity and HOMA-IR were not related within the other three quartiles. In conclusion, it appears that differences in physical activity may play a meaningful role in insulin resistance in those with abdominal obesity, but total activity does not seem to account for differences in insulin resistance among US adults with smaller waists.

Evaluating Relationships Between Sleep and Next-Day Physical Activity in Young Women.

BACKGROUND: To evaluate the relationship between sleep and next-day physical activity (PA) under free-living conditions in women. METHODS: Sleep and PA were measured objectively for 7 consecutive days by accelerometry in 330 young adult women (aged 17-25 y). A structural equation model was used to evaluate the relationship between the driving factor of sleep (total sleep or morning wake time) and the amount of nonsleep sedentary (SED) and moderate to vigorous physical activity (MVPA) each day. RESULTS: With sleep duration as the driving factor, the estimates of ßSED and ßMVPA were -0.415 and -0.093, respectively (P ≤ .05). For every hour slept, a 24.9-minute reduction in SED time and a 5.58-minute reduction in MVPA were observed. With wake time as the driving factor, the estimates of ßSED and ßMVPA were -0.636 and -0.149, respectively. For every wake time that was 1 hour later, a 38.2-minute decrease in SED and a 8.9-minute decrease in MVPA (P ≤ .05) were observed. CONCLUSIONS: Women who wake later or who sleep longer tend to get less MVPA throughout the day. Getting up earlier and going to bed earlier may support behaviors that improve PA and lifestyle.

Limited Agreement between Classifications of Diabetes and Prediabetes Resulting from the OGTT, Hemoglobin A1c, and Fasting Glucose Tests in 7412 U.S. Adults.

This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis.

Bean Consumption Accounts for Differences in Body Fat and Waist Circumference: A Cross-Sectional Study of 246 Women.

Beans and other legumes have multiple nutritional qualities that reduce the risk of many diseases. However, the link between legume intake and obesity remains unclear. Therefore, the present study was designed to examine the association between bean intake, body fat percentage (BF%), and waist circumference, in 246 women. BF% was measured using dual-energy X-ray absorptiometry (DXA). Bean intake was assessed using the Block Food Frequency Questionnaire and indexed using total cups of bean-based food items and also factor scores derived from a factor analysis showing adherence to a bean-based dietary pattern. Bean consumption was expressed as cups per 1000 kilocalories. R\egression results showed that the relationship between bean intake (total cups) and BF% was inverse and linear (F = 7.4, P=0.0069). Moreover, with bean consumption being divided into tertiles, there were mean differences across groups in BF% (F = 7.4, P=0.0008) and waist circumference (F = 4.2, P=0.0164). Specifically, women who consumed moderate or high amounts of beans had less body fat and smaller waists than those with low intakes. Similarly, using tertiles to categorize participants based on adherence to a bean-based dietary pattern, developed using factor analysis, those with low adherence had higher BF% (F = 7.9, P=0.0005) and larger waists (F = 4.5, P=0.0118) than their counterparts. The associations remained significant after adjusting for potential confounders. In conclusion, beans and other legumes seem to have dietary qualities that may be beneficial in the battle against obesity.