Metabolically Healthy Obesity in Pediatric Population

NCT ID: NCT04694937

Last Updated: 2021-01-05

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 100 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-01-15
• Study Completion Date: 2022-01-30

Brief Summary

The global epidemic of childhood obesity, with the accompanying rise in the prevalence of endocrine, metabolic, and cardiovascular comorbidities in youth, represents one of the most important public health issues of the modern world. Nevertheless, a distinct subgroup of youth with obesity less prone to the development of metabolic disturbances, called "metabolically healthy obese" (MHO), has come into focus. Defining the MHO subpopulation within the youth with obesity is of high importance in order to elucidate the mechanisms protecting against the clustering of cardiometabolic risk factors, and for its clinical, preventive, and therapeutic decision-making implications. Little is known about the mechanisms of development of metabolic disturbance in pediatric obesity. Cardiac autonomic function, which can be measured non-invasively with heart rate variability (HRV), has been suggested as a potential mechanism underlying the development of metabolic syndrome and cardiovascular disease. The aims of the present study were to investigate clinical, anthropometric, and socio-demographic and lifestyle predictors of MHO in this group and to asses correlation between HRV and the metabolic syndrome progression or improvement , in order to reveal if HRV can serve as a predictor to metabolic disturbance in pediatric obesity population Materials and Methods The study will be performed in the Nutrition and Obesity Clinic of the Pediatric Gastroenterology Unit at "Dana Dwek" Children's Hospital. All children and adolescents that that will be admitted to our clinic between January 2021 to December 2022 will include in the study. sociodemographic parameters will be collected from the medical files.Blood will be drawn for complete metabolic assesment. MUO children will be defined according to the recent international definition. Resting HRV will be measured by Pulse Oximeter (BM2000A/Shanghai Berry Electronic Tech Co., Ltd.). The measurement will be performed twice - at two consecutive visits at the clinic, as part as the routine follow up of the patient every 3 months.

Detailed Description

Scientific background:

The global epidemic of childhood obesity, with the accompanying rise in the prevalence of endocrine, metabolic, and cardiovascular comorbidities in youth, represents one of the most important public health issues of the modern world (1-4). The earlier occurrence and increase in the prevalence of both pediatric obesity and metabolic syndrome (MS) leads to a potential decline in life expectancy, meaning that the youth of today could be the first generation to live shorter lives than their parents (2, 4-6).

In the context of the childhood obesity pandemic, a distinct subgroup of youth with obesity less prone to the development of metabolic disturbances, called "metabolically healthy obese" (MHO), has come into focus (7, 8). Despite having obesity, MHO individuals display a "favorable" metabolic profile, with preserved insulin sensitivity, normal blood pressure and glucose regulation, normal lipids and liver enzymes, as well as a normal hormonal, inflammation, and immune profile (9-13). Although MHO status might not necessarily translate into lower mortality, and can crossover to "metabolically unhealthy obese" (MUO) phenotype during puberty, defining the MHO subpopulation within the youth with obesity is of high importance in order to elucidate the mechanisms protecting against the clustering of cardiometabolic risk factors, and for its clinical, preventive, and therapeutic decision-making implications (4, 7, 13-15).

Few studies evaluated predictors and risk factors for MUO (14-15). However, these were based on variety of definitions and criteria used for defining MHO. moreover, little is known about the mechanisms of development of metabolic disturbance in pediatric obesity. More data is needed in order to identify the parameters which have the highest ability to predict clinically significant outcomes. Cardiac autonomic function, which can be measured non-invasively with heart rate variability, has been suggested as a potential mechanism underlying the development of metabolic syndrome and cardiovascular disease (16). Autonomic dysfunction characterized by reduced heart rate variability was found to predict coronary heart disease, type 2 diabetes mellitus and of all-cause and cardiac mortality (17-20) in adult population. However, the effect of reduced heart rate variability on metabolic syndrome in pediatric population and the influence of nutritional intervention with weight reduction on heart rate variability is not known. We aimed to investigate clinical, anthropometric, and socio-demographic and lifestyle predictors of MHO in this group, to describe HRV in children with obesity, and to find correlation to the metabolic syndrome or metabolic syndrome progression or improvement, in order to reveal if HRV can serve as a predictor to metabolic disturbance in pediatric obesity population.

Study design:

Study population and study design:

Study population The study will be performed in the Nutrition and Obesity Clinic of the Pediatric Gastroenterology Unit at "Dana Dwek" Children's Hospital.

All children and adolescents that that will be admitted to our clinic between December 2020 to December 2022 will include in the study.

Inclusion criteria: All children 10-18 with obesity, males and females, who attend the obesity clinic in the pediatric gastroenterology unit at "Dana-Dwek" children's hospital, Tel Aviv Sourasky Medical Center, will be included.

Exclusion criteria: Children with conditions that may affect HRV (e.g. congenital or acquired heart disease, other inflammatory conditions) will be excluded.

withdrawal criteria: children and parents that will refuse to participate in the telephone interview will withdrawl from the study.

Demographic data - age and gender, perinatal history, prior medication and hospitalization, sociodemographic parameters (area of living, parents' education, occupation and lifestyle) will be collected from the medical files. The obese children's perceptions of their motivation, health and social status will be ranked in 1-10 scale and documented upon admission to the clinic, and the parents' life style habits will also be documented during their first encounter. A parent will be defined as maintaining healthy lifestyle if he or she reported to maintain a healthy diet and regular exercise Clinical and metabolic evaluation Weight and height will be measured according to standardized protocols. Body mass index (BMI) percentiles are computed using age- and sex-specific BMI reference values from the World Health Organization . Body composition will be assessed using bioelectricalimpedence. Laboratory and radiologic parameters will include liver enzyme profile, lipid profile, glucose, insulin and HbA1C ,C rreactive protein (CRP) and abdominal ultrasound. MUO children and adolescent will be defined according to the recent international consensus-based definition (10). BMI Z score will be documented every 3-month and laboratory parameters will be repeated after 6 months of dietary intervention Nutritional assessment will be based on 3 days food report, including 2 week days and 1 weekend day, administered by a registered dietician at baseline visit and every 3 months.

Measurement of HRV Resting HRV will be measured by Pulse Oximeter BM2000A/Shanghai Berry Electronic Tech Co., Ltd. that is validated for this purpose and is approved by FDA. The measurement, at the patient's fingertip, takes 5 minutes. The measurement will be performed twice - at two consecutive visits at the clinic, as part as the routine follow up of the patient every 3 months.

HRV will be correlated to demographic and metabolic parameters between patients. In order to reveal whether HRV can serve as a predictor to metabolic disease progression or improvement HRV will be correlated to metabolic parameters in the same patient at two time-points.

Statistical analysis:

Epidemiologic data and patients' descriptive data available on continuous scales will be presented with medians, means and standard deviations. Categorical data will be presented as rates and percentages. Parametric tests will be applied when normality is satisfied. Regression analysis will be used to assess the impact of independent variables on the dependent variables. A p value of <0.05 will be considered significant.

Time line:

Study data analysis will be completed within 2 years.

Conditions

Obesity; Pediatric Obesity; Metabolic Syndrome

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

metabolic healthy obese

Demographic, clinical laboratory and heart rate variability assesment

heart rate variabilty measured by pulse oximetry

Intervention Type: DEVICE

Resting HRV will be measured by Pulse Oximeter BM2000A/Shanghai Berry Electronic Tech Co., Ltd. that is validated for this purpose and is approved by FDA. The measurement, at the patient's fingertip, takes 5 minutes. The measurement will be performed twice - at two consecutive visits at the clinic, as part as the routine follow up of the patient every 3 months.

HRV will be correlated to demographic and metabolic parameters between patients. In order to reveal whether HRV can serve as a predictor to metabolic disease progression or improvement, HRV will be correlated to metabolic parametrers in the same patient at two time-points.

metabolic unhealthy obese

Demographic, clinical laboratory and heart rate variability assesment

heart rate variabilty measured by pulse oximetry

Intervention Type: DEVICE

Resting HRV will be measured by Pulse Oximeter BM2000A/Shanghai Berry Electronic Tech Co., Ltd. that is validated for this purpose and is approved by FDA. The measurement, at the patient's fingertip, takes 5 minutes. The measurement will be performed twice - at two consecutive visits at the clinic, as part as the routine follow up of the patient every 3 months.

HRV will be correlated to demographic and metabolic parameters between patients. In order to reveal whether HRV can serve as a predictor to metabolic disease progression or improvement, HRV will be correlated to metabolic parametrers in the same patient at two time-points.

Interventions

heart rate variabilty measured by pulse oximetry

Resting HRV will be measured by Pulse Oximeter BM2000A/Shanghai Berry Electronic Tech Co., Ltd. that is validated for this purpose and is approved by FDA. The measurement, at the patient's fingertip, takes 5 minutes. The measurement will be performed twice - at two consecutive visits at the clinic, as part as the routine follow up of the patient every 3 months.

HRV will be correlated to demographic and metabolic parameters between patients. In order to reveal whether HRV can serve as a predictor to metabolic disease progression or improvement, HRV will be correlated to metabolic parametrers in the same patient at two time-points.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

All children 10-18 with obesity, males and females, who attend the obesity clinic in the pediatric gastroenterology unit at "Dana-Dwek" children's hospital, Tel Aviv Sourasky Medical Center, will be included

Exclusion Criteria

Children with conditions that may affect HRV (e.g. congenital or acquired heart disease, other inflammatory conditions) will be excluded.

withdrawal criteria: children and parents that will refuse to participate in the telephone interview will withdrawl from the study.

• Minimum Eligible Age: 10 Years
• Maximum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Tel-Aviv Sourasky Medical Center

OTHER_GOV

Sponsor Role: lead

Responsible Party

Eli Sprecher, MD

Director

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

shlomi cohen, md

Role: PRINCIPAL_INVESTIGATOR

pediatric gastroenterology

Central Contacts

hadar lev, md

Role: CONTACT

hadarlev6@gmail.com

00972527360713

References

1. Wang Y, Lobstein T. Worldwide trends in childhood overweight and obesity. Int J Pediatr Obes. (2006) 1:11-25. doi: 10.1080/1747 2. Zimmet P, Alberti KG, Kaufman F, Tajima N, Silink M, Arslanian S, et al. The metabolic syndrome in children and adolescents - an IDF consensus report. Pediatr Diabetes. (2007) 8:299-306. doi: 10.1111/j.1399-5448.2007. 00271.x 3. Bluher S, Schwarz P. Metabolically healthy obesity from childhood to adulthood - does weight status alone matter?Metabolism. (2014) 63:1084-92 4. Primeau V, Coderre L, Karelis AD, Brochu M, Lavoie ME, Messier V, et al. Characterizing the profile of obese patients who are metabolically healthy. Int J Obes. (2011) 35:971-81. doi: 10.1038/ijo.2010.216 5. Weiss R, Taksali SE, Dufour S, Yeckel CW, Papademetris X, Cline G, et al. The "obese insulin-sensitive" adolescent: importance of adiponectin and lipid partitioning. J Clin Endocrinol Metab. (2005) 90:3731-7. doi: 10.1210/jc.2004-2305 6. Karelis AD. Metabolically healthy but obese individuals. Lancet. 2008 372:1281-3. doi: 10.1016/S0140-6736(08)61531-7 7. Karelis AD, St-Pierre DH, Conus F, Rabasa-Lhoret R, Poehlman ET. Metabolic and body composition factors in subgroups of obesity: what do we know? J Clin Endocrinol Metab. (2004) 89:2569-75. 8. Sims EA. Are there persons who are obese, but metabolically healthy? Metabolism. (2001) 50:1499-504. 9. Bluher M. The distinction of metabolically 'healthy' from 'unhealthy' obese individuals. Curr Opin Lipidol. (2010) 21:38-43. 10. Damanhoury S, Newton AS, Rashid M, Hartling L, Byrne JLS, Ball GDC. Defining metabolically healthy obesity in children: a scoping review. Obes Rev. (2018) 19:1476-91 11. Vukovic R, Milenkovic T, Mitrovic K, Todorovic S, Plavsic L, Vukovic A, et al. Preserved insulin sensitivity predicts metabolically healthy obese phenotype in children and adolescents. Eur J Pediatr. (2015) 174:1649-55. 12. KiessW, PenkeM, Sergeyev E, NeefM, AdlerM, Gausche R, et al. Childhood obesity at the crossroads. J Pediatr Endocrinol Metab. (2015) 28:481-4. 13. Chen F, Liu J, Yan Y, Mi J, China Child and Adolescent Cardiovascular Health (CCACH) Study Group. Adolescent cardiovascular health study group. abnormal metabolic phenotypes among urban chinese children: epidemiology and the impact of DXA-measured body composition. Obesity. (2019) 27:837-44 14. Nasreddine L, Tamim H, Mailhac A, AlBuhairan FS. Prevalence and predictors of metabolically healthy obesity in adolescents: findings from the national "Jeeluna" study in Saudi-Arabia. BMC Pediatr. (2018) 18:281. 15. Roberge JB, Van Hulst A, Barnett TA, Drapeau V, Benedetti A, Tremblay A, et al. Lifestyle habits, dietary factors, and the metabolically unhealthy obese phenotype in youth. J Pediatr. (2019) 204:46-52. 16. Thayer JF, Yamamoto SS, Brosschot JF. The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors. Int J Cardiol 2010; 141(2): 122-131. 17.Liao D, Cai J, Rosamond WD, et al. Cardiac autonomic function and incident coronary heart disease: A populationbased case-cohort study. The ARIC study. Atherosclerosis risk in communities study. Am J Epidemiol 1997; 145(8): 696-706 18. Carnethon MR, Golden SH, Folsom AR, Haskell W, Liao D. Prospective investigation of autonomic nervous system function and the development of type 2 diabetes: The atherosclerosis risk in communities study, 1987-1998. Circulation 2003; 107(17): 2190-2195. 19. Carnethon MR, Prineas RJ, Temprosa M, et al. The association among autonomic nervous system function, incident diabetes, and intervention arm in the diabetes prevention program. Diabetes Care 2006; 29(4): 914-919 20.La Rovere MT, Bigger JT Jr, Marcus FI, Mortara A, Schwartz PJ. Baroreflex sensitivity and heart-rate variability in prediction of total cardiac mortality after myocardial infarction. ATRAMI (autonomic tone and reflexes after myocardial infarction) investigators. Lancet 1998; 351(9101): 478-484

Reference Type: BACKGROUND

Other Identifiers

0799-20

Identifier Type: -

Identifier Source: org_study_id