Novel measures of inflammation and insulin resistance are related to obesity and fitness in a diverse sample of 11-14 year-olds:The HEALTHY Study

BACKGROUND: GlycA is a novel serum marker of systemic inflammation. There is no information on GlycA in pediatric populations, how it differs by gender or its association with body mass index (BMI) or fitness. LP-IR is a serum measure of insulin resistance which is related to changes in BMI group in adolescents, but its relationship with fitness is unknown. The current study examined the independent associations between fitness and BMI with GlycA and LP-IR among US adolescents. METHODS: Participants were 1664 US adolescents from the HEALTHY study with complete 6th and 8th grade BMI, fitness and blood data. GlycA and LP-IR were measured by NMR spectroscopy. Three BMI groups and three fitness groups were created. Linear mixed models examined associations between GlycA, LP-IR, fitness and BMI. RESULTS: LP-IR decreased between 6th and 8th grade. GlycA increased among girls but decreased among boys. At 8th grade, median GlycA values were 27 (7.6%) μmol/l higher (381 versus 354) for girls than boys. Median GlycA 6th grade values were 9% higher in obese girls than healthy weight girls. Overall there was strong evidence (P CONCLUSIONS: GlycA was associated with BMI and fitness among in US adolescents. These findings suggest that there are independent effects for BMI and fitness group with both GlycA and LP-IR. Future studies should validate the role of GlycA and LP-IR to evaluate the effects of interventions to modify obesity and fitness in order to improve systemic inflammation and insulin resistance.International Journal of Obesity accepted article preview online, 04 May 2016. doi:10.1038/ijo.2016.84

Long-term complications in youth-onset type 2 diabetes

BACKGROUND: The prevalence of type 2 diabetes in youth is increasing, but little is known regarding the occurrence of related complications as these youths transition to adulthood. METHODS: We previously conducted a multicenter clinical trial (from 2004 to 2011) to evaluate the effects of one of three treatments (metformin, metformin plus rosiglitazone, or metformin plus an intensive lifestyle intervention) on the time to loss of glycemic control in participants who had onset of type 2 diabetes in youth. After completion of the trial, participants were transitioned to metformin with or without insulin and were enrolled in an observational follow-up study (performed from 2011 to 2020), which was conducted in two phases; the results of this follow-up study are reported here. Assessments for diabetic kidney disease, hypertension, dyslipidemia, and nerve disease were performed annually, and assessments for retinal disease were performed twice. Complications related to diabetes identified outside the study were confirmed and adjudicated. RESULTS: At the end of the second phase of the follow-up study (January 2020), the mean (±SD) age of the 500 participants who were included in the analyses was 26.4±2.8 years, and the mean time since the diagnosis of diabetes was 13.3±1.8 years. The cumulative incidence of hypertension was 67.5%, the incidence of dyslipidemia was 51.6%, the incidence of diabetic kidney disease was 54.8%, and the incidence of nerve disease was 32.4%. The prevalence of retinal disease, including more advanced stages, was 13.7% in the period from 2010 to 2011 and 51.0% in the period from 2017 to 2018. At least one complication occurred in 60.1% of the participants, and at least two complications occurred in 28.4%. Risk factors for the development of complications included minority race or ethnic group, hyperglycemia, hypertension, and dyslipidemia. No adverse events were recorded during follow-up. CONCLUSIONS: Among participants who had onset of type 2 diabetes in youth, the risk of complications, including microvascular complications, increased steadily over time and affected most participants by the time of young adulthood. Complications were more common among participants of minority race and ethnic group and among those with hyperglycemia, hypertension, and dyslipidemia. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; ClinicalTrials.gov numbers, NCT01364350 and NCT02310724.)

HEALTHY Intervention: Fitness, Physical Activity, and Metabolic Syndrome Results

This study aimed to assess the effect of the HEALTHY intervention on the metabolic syndrome (Met-S), fitness, and physical activity levels of US middle-school students

BMI Change, Fitness Change and Cardiometabolic Risk Factors among 8 th Grade Youth

This paper examined whether a two-year change in fitness, body mass index (BMI) or the additive effect of change in fitness and BMI were associated with change in cardiometabolic risk factors among youth. Cardiometabolic risk factors, BMI group (normal weight, overweight or obese) were obtained from participants at the start of 6th grade and end of 8th grade. Shuttle run laps were assessed and categorized in quintiles at both time points. Regression models were used to examine whether changes in obesity, fitness or the additive effect of change in BMI and fitness were associated with change in risk factors. There was strong evidence (p < .001) that change in BMI was associated with change in cardiometabolic risk factors. There was weaker evidence of a fitness effect, with some evidence that change in fitness was associated with change in total cholesterol, HDL-C, LDL-C and clustered risk score among boys, as well as HDL-C among girls. Male HDL-C was the only model for which there was some evidence of a BMI, fitness and additive BMI*fitness effect. Changing body mass is central to the reduction of youth cardiometabolic risk. Fitness effects were negligible once change in body mass had been taken into account

Effect of Relative Weight Group Change on Nuclear Magnetic Resonance Spectroscopy Derived Lipoprotein Particle Size and Concentrations among Adolescents

To examine whether longitudinal changes in relative weight category (as indicated by change in BMI classification group) were associated with changes in nuclear magnetic resonance (NMR) derived lipoprotein particles among US youth

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

Student public commitment in a school-based diabetes prevention project: impact on physical health and health behavior

<p>Abstract</p> <p>Background</p> <p>As concern about youth obesity continues to mount, there is increasing consideration of widespread policy changes to support improved nutritional and enhanced physical activity offerings in schools. A critical element in the success of such programs may be to involve students as spokespeople for the program. Making such a public commitment to healthy lifestyle program targets (improved nutrition and enhanced physical activity) may potentiate healthy behavior changes among such students and provide a model for their peers. This paper examines whether student's "public commitment"--voluntary participation as a peer communicator or in student-generated media opportunities--in a school-based intervention to prevent diabetes and reduce obesity predicted improved study outcomes including reduced obesity and improved health behaviors.</p> <p>Methods</p> <p>Secondary analysis of data from a 3-year randomized controlled trial conducted in 42 middle schools examining the impact of a multi-component school-based program on body mass index (BMI) and student health behaviors. A total of 4603 students were assessed at the beginning of sixth grade and the end of eighth grade. Process evaluation data were collected throughout the course of the intervention. All analyses were adjusted for students' baseline values. For this paper, the students in the schools randomized to receive the intervention were further divided into two groups: those who participated in public commitment activities and those who did not. Students from comparable schools randomized to the assessment condition constituted the control group.</p> <p>Results</p> <p>We found a lower percentage of obesity (greater than or equal to the 95^thpercentile for BMI) at the end of the study among the group participating in public commitment activities compared to the control group (21.5% vs. 26.6%, p = 0.02). The difference in obesity rates at the end of the study was even greater among the subgroup of students who were overweight or obese at baseline; 44.6% for the "public commitment" group, versus 53.2% for the control group (p = 0.01). There was no difference in obesity rates between the group not participating in public commitment activities and the control group (26.4% vs. 26.6%).</p> <p>Conclusions</p> <p>Participating in public commitment activities during the HEALTHY study may have potentiated the changes promoted by the behavioral, nutrition, and physical activity intervention components.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov number, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00458029">NCT00458029</a></p

A review of software for analyzing molecular sequences

Background Over the past ten years, there has been an explosion of microbiome research. Many software packages for analyzing microbial sequences such as the 16S gene from 454 sequencers and Illumina platforms are available. But for a new researcher, it is difficult to know which package to choose. We present a systematic review of packages for the analysis of molecular sequences used to describe and compare microbial communities. This review gives students and researchers information to help choose the best analytic pipeline for their project. To the best of our knowledge, this is the first review of such software. Findings Seven software packages met our inclusion criteria of being cost free and publically available, offering analysis functions from platform sequencing to results presentation, and included documentation and data security. We installed and executed each of the software packages and describe the installation, documentation, features, and functions of each. Conclusions For the user, pipeline choices may be limited because some packages only run on select operating systems. Users should be aware of the availability of features and functions of each package. Of utmost importance is that the user must be aware of the default settings and underlying assumptions of each function. All packages are lacking sufficient methods for longitudinal analysis. Researchers can do well using any one of these seven packages. However, two packages are outstanding; mothur and QIIME, due not only to the comprehensive suite of functions and procedures incorporated into the pipelines but also because of the accompanying documentation