Identification of Changes in Sleep Across Pregnancy and the Impact on Cardiometabolic Health and Energy Intake in Women with Obesity

This prospective, observational study investigated changes in sleep and the effect on energy intake, gestational weight gain, and cardiometabolic health across pregnancy in 52 healthy pregnant women with obesity. Habitual sleep was assessed by wrist-worn actigraphy (time spent in bed; TIB, total sleep time; TST, and sleep efficiency) in early (13(0)-15(6) weeks) and late (35(0)-36(6)) pregnancy. A change to habitual sleep was defined as change of one-half of the standard deviation of TIB and TST across six consecutive nights from early pregnancy. Energy intake and changes in weight, fasting glucose, insulin, and lipids across pregnancy were compared between women who changed sleep. During early pregnancy, TIB was 9:24±0:08h and varied by 1:37±0:07h across the six nights. TST and sleep efficiency significantly declined from early to late pregnancy (7:03±0:08h to 6:28±0:09h, p<0.001) and (76±0.1% to 71±0.2%, p<0.001), respectively. For women who increased TIB (n=11), fasting glucose decreased (−11.6±4.3%, p<0.01) across pregnancy and they had a trend towards decreased insulin (−57.8±33.5%; p=0.09) and HOMA-IR (−72.4±37.3%; p=0.06) compared to women who decreased TIB (n=13). Women who increased TIB had a significantly lower daily energy intake across pregnancy (−540±163 kcal; p<0.01) and tended to have less gestational weight gain (−147±88 g/week; p=0.10). Changes in TST did not affect plasma markers, energy intake or weight gain. The positive relationship between sleep and cardiometabolic health during pregnancy is explained in part by lower energy intake. We hypothesize lower energy intake is due to a prolonged overnight fast and a decrease in the time available for eating

Skeletal muscle mitochondrial and lipid droplet content assessed with standardized grid sizes for stereology.

Skeletal muscle mitochondrial (Mito) and lipid droplet (Lipid) content are often measured in human translational studies. Stereological point counting allows computing Mito and Lipid volume density (Vd) from micrographs taken with transmission electron microscopes. Former studies are not specific as to the size of individual squares that make up the grids, making reproducibility difficult, particularly when different magnifications are used. Our objective was to determine which size grid would be best at predicting fractional volume efficiently without sacrificing reliability and to test a novel method to reduce sampling bias. Methods: ten subjects underwent vastus lateralis biopsies. Samples were fixed, embedded, and cut longitudinally in ultrathin sections of 60 nm. Twenty micrographs from the intramyofibrillar region were taken per subject at Ã-33,000 magnification. Different grid sizes were superimposed on each micrograph: 1,000 Ã- 1,000 nm, 500 Ã- 500 nm, and 250 Ã- 250 nm. Results: mean Mito and Lipid Vd were not statistically different across grids. Variability was greater when going from 1,000 Ã- 1,000 to 500 Ã- 500 nm grid than from 500 Ã- 500 to 250 Ã- 250 nm grid. Discussion: this study is the first to attempt to standardize grid size while keeping with the conventional stereology principles. This is all in hopes of producing replicable assessments that can be obtained universally across different studies looking at human skeletal muscle mitochondrial and lipid droplet content

Discrimination of wear and non-wear in infants using data from hip- and ankle-worn devices.

IntroductionA key component to analyzing wearable sensor data is identifying periods of non-wear. Traditionally, strings of consecutive zero counts (e.g. >60-minutes) are identified indicating periods of non-movement. The non-movement window length is then evaluated as wear or non-wear. Given that non-movement is not equivalent to non-wear, additional criteria should be evaluated to objectively identify periods of non-wear. Identifying non-wear is especially challenging in infants due to their sporadic movement, sleep frequency, and proportion of caregiver-generated movement.PurposeTo use hip- and ankle-worn ActiGraph wGT3X-BT (wGT3X-BT) data to identify non-wear in infants.MethodsFifteen infant participants [mean±SD; age, 8.7±1.7 weeks (range 5.4-11.3 weeks); 5.1±0.8 kg; 56.2±2.1 cm; n = 8 females] wore a wGT3X-BT on the hip and ankle. Criterion data were collected during two, 2-hour directly observed periods in the laboratory. Using raw 30 Hz acceleration data, a vector magnitude and the inclination angle of each individual axis were calculated before being averaged into 1-minute windows. Three decision tree models were developed using data from 1) hip only, 2) ankle only, and 3) hip and ankle combined.ResultsThe hip model classified 86.6% of all minutes (wear and non-wear) correctly (F1 = 75.5%) compared to the ankle model which classified 90.6% of all minutes correctly (F1 = 83.0%). The combined site model performed similarly to the ankle model and correctly classified 90.0% of all minutes (F1 = 80.8%).ConclusionThe similar performance between the ankle only model and the combined site model likely indicates that the features from the ankle device are more important for identifying non-wear in infants. Overall, this approach provides an advancement in the identification of device wear status using wearable sensor data in infants

The Panacea of Human Aging: Calorie Restriction Versus Exercise

Primary aging is the progressive decline in health and fitness and depends on metabolic rate and oxidative stress. Untoward changes in body composition and metabolic function characterize secondary aging. We hypothesize that both exercise and calorie restriction (CR) improve secondary aging, but only CR improves primary. However, CR followed with exercise is a superior strategy to maintain overall health and quality of life with age

Mitochondrial Phenotype as a Driver of the Racial Dichotomy in Obesity and Insulin Resistance

African Americans (AA) are disproportionately burdened by metabolic diseases. While largely unexplored between Caucasian (C) and AA, differences in mitochondrial bioenergetics may provide crucial insight to mechanisms for increased susceptibility to metabolic diseases. AA display lower total energy expenditure and resting metabolic rate compared to C, but paradoxically have a higher amount of skeletal muscle mass, suggestive of inherent energetic efficiency differences between these races. Such adaptations would increase the chances of overnutrition in AA; however, these disparities would not explain the racial difference in insulin resistance (IR) in healthy subjects. Hallmarks associated with insulin resistance (IR), such as reduced mitochondrial oxidative capacity and metabolic inflexibility are present even in healthy AA without a metabolic disease. These adaptations might be influential of mitochondrial “substrate preference” and could play a role in disproportionate IR rates among races. A higher glycolytic flux and provision of shuttles transferring electrons from cytosol to mitochondrial matrix could be a contributing factor in development of IR via heightened reactive oxygen species (ROS) production. This review highlights the above concepts and provides suggestions for future studies that could help delineate molecular premises behind potential impairments in insulin signaling and metabolic disease susceptibility in AA

Metabolic inflexibility in women with PCOS is similar to women with type 2 diabetes

Abstract Background An ability to switch between primarily oxidizing fat in the fasted state to carbohydrate in the fed state, termed metabolic flexibility, is associated with insulin sensitivity. Metabolic flexibility has been explored previously in women with polycystic ovary syndrome (PCOS), yet the independent or synergistic contributions of androgen excess and/or insulin resistance is not yet known. Therefore, the purpose of this article was to characterize metabolic flexibility in women with PCOS compared to women of normal BMI, obesity, or type 2 diabetes (T2DM). Methods Eighty-six weight-stable women; thirty with either PCOS (n = 30), or fifty-six with obesity (n = 12), T2DM (n = 27), or normal BMI (n = 17) underwent a hyperinsulinemic euglycemic clamp and indirect calorimetry to measure insulin sensitivity and substrate oxidation via indirect calorimetry, respectively. Results All analyses were adjusted for differences in age, ethnicity, and BMI between groups. Women with PCOS were less metabolically flexible compared to healthy women with obesity (p < 0.0001), normal BMI (p < 0.0001), but after controlling for glucose disposal rate, were similar to women with T2DM (p = 0.99). When dividing women with PCOS above and below the mean cutoff for insulin resistance, the insulin resistant women with PCOS had lower rates of non-oxidative glucose metabolism (p = 0.0001), higher levels of percent free testosterone (p = 0.04), a higher free androgen index (p = 0.006), more visceral adipose tissue (p = 0.02), and were less metabolically flexible (p = 0.007). Conclusions Women with T2DM were as metabolically inflexible as women with PCOS. When stratifying women with PCOS into those who are metabolically flexible and inflexible, the women who are inflexible display greater amounts of visceral fat and androgen excess. The inability to alter substrate use given the physiological stimulus may lead to subsequent increases in adiposity in women with PCOS thereby further worsening the insulin resistance. Trial registration number Clinical Trials.gov, NCT01482286. Registered 30 November 2011