ESPE Abstracts (2018) 89 P-P2-139

ESPE2018 Poster Presentations Fat, Metabolism and Obesity P2 (58 abstracts)

The Associations Between Neck – and Upper Arm Circumference with Cardiometabolic Risk Over Traditional Risk Factors in Adolescents - Data from Five EUROPEAN Countries (PreSTART-Study)

Susann Weihrauch-Blüher a, , David Petroff a, , Emer M. Brady d , Laura J. Gray e , Rogério T. Ribeiro f , I. Vergara Mitxeltorena g , Diana A. Gerasimidi-Vazeou h & Melanie J. Davies i

aUniversity of Leipzig, Integrated Treatment- und Research Center (IFB) AdiposityDiseases, Leipzig, Germany; bUniversity of Halle, Dept. of Ped. I, Halle, Germany; cClinical Trial Centre, University of Leipzig, Leipzig, Germany; dUniversity Hospitals of Leicester NHS Trust- UK, Leicester Diabetes Centre, Leicester, UK; eUniversity of Leicester, Department of Health Sciences, Leicester, UK; fEducation and Research Centre/APDP-ERC, Lisbon, Portugal; gKronikgune, Bilbao, Spain; hP&A Kyriakou Chlidren’s Hospital, Athens, Greece; iUniversity of Leicester, Diabetes Research Centre, Leicester, UK

Background: Prevalence and severity of obesity and associated comorbidities are increasing in adolescents. Data on neck and upper arm (UA) circumference in addition to established anthropometric measures to define cardiometabolic risk are limited to date.

Methods: Data from Phase I of the EU-funded PreSTART-study (trial registration number NCT02545140) was applied. Demographic, clinical, biochemical and lifestyle data were collected in adolescents (12–14 years) from 5 European countries (UK, Portugal, Spain, Germany and Greece). All data were collected with the same standard operating procedures at each site, and fasting blood samples for measurement of HbA1c, glucose, cholesterol (Chol), triglycerides (TG), HDL-C and LDL-C were analysed using the same test kits. Anthropometric measures included weight, height and circumferences for waist, neck and UA. Correlation and linear models were used to establish associations.

Results: 584 adolescents (52% males) were included. Age and sex dependent BMI-z score correlated strongly with neck circumference (0.65 [95% CI 0.61, 0.70], P<0.001) and UA circumference (0.86 [95% CI 0.84, 0.88], P<0.001). TG was lower in boys (P=0.0011) and showed a strong site dependence (P<0.001) with non-UK centres having lower values. TG was associated with waist to height ratio (WHtR) (1.18-fold [95% CI 1.12–1.25] per 0.1 increase in WHtR, P<0.001), neck circumference (1.043-fold [95% CI 1.028–1.058 per 1 cm increase], P<0.001) and UA circumference (1.031-fold [95% CI 1.021–1.041) per 1 cm increase, P<0.001). Total Chol (n=539) was lower in boys (P<0.001) and associated with WHtR (0.10 mmol/L [95% CI 0.03–0.18] per 0.1 increase, P=0.007) as well as UA circumference (0.017 mmol/L [95% CI 0.004–0.031]) per cm increase, P=0.012). HDL-C (n=536) also showed a site dependence (P=0.032) and was strongly associated with WHtR (−0.11 mmol/L [95% CI −0.15 to −0.07] per 0.1 increase in WHtR, P<0.001), with neck circumference (−0.041 mmol/L [95% CI −0.051 to −0.030] per cm increase, P<0.001) and with UA circumference (−0.024 mmol/L [95% CI −0.032 to −0.016] per cm increase, P<0.001). HbA1c was not associated with anthropometric or lab parameters.

Discussion: Neck and UA circumference strongly correlate with BMI z-score and WHtR and are associated with cardiometabolic risk in a cohort of 12–14 year old adolescents from 5 European countries. Future studies need to assess to what extent subcutaneous fat depots from the upper body may provide additional predictive power above visceral fat.

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