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The association of sleep disturbances with glycemia and obesity in youth at risk for or with recently diagnosed type 2 diabetes.

ABSTRACT: OBJECTIVE:Poor sleep may increase obesity and type 2 diabetes (T2D) risk in youth. We explored whether subjective sleep duration, sleep quality, or risk for obstructive sleep apnea (OSA) are associated with glycemia, body mass index (BMI), or blood pressure (BP) in overweight/obese youth. METHODS:Two-hundred and fourteen overweight/obese youth of 10 to 19?years of age at risk for or recently diagnosed with T2D who were screened for the Restoring Insulin Secretion (RISE) Study had a 2-hour oral glucose tolerance test (OGTT) and completed a Cleveland Adolescent Sleepiness questionnaire and a Sleep Disturbances Scale questionnaire. Independent associations between sleep variables and measures of glycemia, BMI, and BP were evaluated with regression models. RESULTS:The multiethnic cohort was 67% female, 14.1?±?2.1?years, and BMI 35.9?±?6.5 kg/m2 . Habitual sleep duration <8 hours was reported in 74%. Daytime sleepiness was reported in 51%, poor sleep quality in 26%, and 30% had high obstructive sleep apnea (OSA) risk. Daytime sleepiness was associated with higher HbA1c (0.2%, P = .02) and 2-hour glucose (13.6 mg/dL, P?

SUBMITTER: Mokhlesi B

PROVIDER: S-EPMC7199716 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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The association of sleep disturbances with glycemia and obesity in youth at risk for or with recently diagnosed type 2 diabetes.

Mokhlesi Babak B Temple Karla A KA Tjaden Ashley H AH Edelstein Sharon L SL Nadeau Kristen J KJ Hannon Tamara S TS Manchanda Shalini S Sam Susan S Barengolts Elena E Utzschneider Kristina M KM Ehrmann David A DA Van Cauter Eve E

Pediatric diabetes 20190915 8

<h4>Objective</h4>Poor sleep may increase obesity and type 2 diabetes (T2D) risk in youth. We explored whether subjective sleep duration, sleep quality, or risk for obstructive sleep apnea (OSA) are associated with glycemia, body mass index (BMI), or blood pressure (BP) in overweight/obese youth.<h4>Methods</h4>Two-hundred and fourteen overweight/obese youth of 10 to 19 years of age at risk for or recently diagnosed with T2D who were screened for the Restoring Insulin Secretion (RISE) Study had ...[more]

PMID: 31486162

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Project description:INTRODUCTION:Individuals with type 1 diabetes (T1D) present with diverse body weight status and degrees of glycemic control, which may warrant different treatment approaches. We sought to identify subgroups sharing phenotypes based on both weight and glycemia and compare characteristics across subgroups. RESEARCH DESIGN AND METHODS:Participants with T1D in the SEARCH study cohort (n=1817, 6.0-30.4 years) were seen at a follow-up visit >5 years after diagnosis. Hierarchical agglomerative clustering was used to group participants based on five measures summarizing the joint distribution of body mass index z-score (BMIz) and hemoglobin A1c (HbA1c) which were estimated by reinforcement learning tree predictions from 28 covariates. Interpretation of cluster weight status and glycemic control was based on mean BMIz and HbA1c, respectively. RESULTS:The sample was 49.5% female and 55.5% non-Hispanic white (NHW); mean±SD age=17.6±4.5 years, T1D duration=7.8±1.9 years, BMIz=0.61±0.94, and HbA1c=76±21?mmol/mol (9.1±1.9)%. Six weight-glycemia clusters were identified, including four normal weight, one overweight, and one subgroup with obesity. No cluster had a mean HbA1c <58?mmol/mol (7.5%). Cluster 1 (34.0%) was normal weight with the lowest HbA1c and comprised 85% NHW participants with the highest socioeconomic position, insulin pump use, dietary quality, and physical activity. Subgroups with very poor glycemic control (ie, ?108?mmol/mol (?12.0%); cluster 4, 4.4%, and cluster 5, 7.5%) and obesity (cluster 6, 15.4%) had a lower proportion of NHW youth, lower socioeconomic position, and reported decreased pump use and poorer health behaviors (overall p<0.01). The overweight subgroup with very poor glycemic control (cluster 5) showed the highest lipids and blood pressure (p<0.01). CONCLUSIONS:There are distinct subgroups of youth and young adults with T1D that share weight-glycemia phenotypes. Subgroups may benefit from tailored interventions addressing differences in clinical care, health behaviors, and underlying health inequity.

Project description:The aim of our study was to examine the associations between sedentary time (SED-time), time spent in moderate-to-vigorous-intensity physical activity (MVPA), total physical activity energy expenditure (PAEE) and cardiorespiratory fitness with metabolic risk among individuals with recently diagnosed type 2 diabetes.Individuals participating in the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care (ADDITION)-Plus trial underwent measurement of SED-time, MVPA and PAEE using a combined activity and movement sensor (n = 394), and evaluation of cardiorespiratory fitness (n = 291) and anthropometric and metabolic status. Clustered metabolic risk was calculated by summing standardised values for waist circumference, triacylglycerol, HbA1c, systolic blood pressure and the inverse of HDL-cholesterol. Multivariate linear regression analyses were used to quantify the associations between SED-time, MVPA, PAEE and cardiorespiratory fitness with individual metabolic risk factors and clustered metabolic risk.Each additional 1 h of SED-time was positively associated with clustered metabolic risk, independently of sleep duration and MVPA (? = 0.16 [95% CI 0.03, 0.29]). After accounting for SED-time, MVPA was associated with systolic blood pressure (? = -2.07 [-4.03, -0.11]) but not with clustered metabolic risk (? = 0.01 [-0.28, 0.30]). PAEE and cardiorespiratory fitness were significantly and independently inversely associated with clustered metabolic risk (? = -0.03 [-0.05, -0.02] and ? = -0.06 [-0.10, -0.03], respectively). Associations between SED-time and metabolic risk were generally stronger in the low compared with the high fitness group.PAEE was inversely associated with metabolic risk, whereas SED-time was positively associated with metabolic risk. MVPA was not associated with clustered metabolic risk after accounting for SED-time. Encouraging this high-risk group to decrease SED-time, particularly those with low cardiorespiratory fitness, and increase their overall physical activity may have beneficial effects on disease progression and reduction of cardiovascular risk.ISRCTN99175498.

Dataset Information

The association of sleep disturbances with glycemia and obesity in youth at risk for or with recently diagnosed type 2 diabetes.

Publications

The association of sleep disturbances with glycemia and obesity in youth at risk for or with recently diagnosed type 2 diabetes.

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