NCT05612282

Brief Summary

The aim of the research was to assess the impact of the distribution of abdominal fat (subcutaneous SAT and visceral VAT estimated at the height of the navel) on selected metabolic parameters and on specific parameters of cardiopulmonary fitness in terms of people with obesity.

Trial Health

100
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
91

participants targeted

Target at P50-P75 for all trials

Timeline
Completed

Started Nov 2016

Shorter than P25 for all trials

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

November 11, 2016

Completed
12 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

October 31, 2017

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

October 31, 2017

Completed
5 years until next milestone

First Submitted

Initial submission to the registry

October 26, 2022

Completed
15 days until next milestone

First Posted

Study publicly available on registry

November 10, 2022

Completed
Last Updated

November 10, 2022

Status Verified

October 1, 2022

Enrollment Period

12 months

First QC Date

October 26, 2022

Last Update Submit

November 4, 2022

Conditions

Keywords

Adipose tissueobesitymetabolic disorders

Outcome Measures

Primary Outcomes (5)

  • The impact of the body compositon parameters (BioScan 920-2) on the risk of metabolic complications of obesity with to use biochemical parameters.

    The body weight (kg) was measured using a scale with stadiometer. The height (cm) was measured using a scale with stadiometer. This measurment is needed to calculate BMI (Body Mass Index) and to do a body composition analysis. The body composition parameters was determined using the bioimpedance method with a BioScan 920-2 body composition analyzer (Maltron,UK): fat mass (kg), percentage of body fat (%), muscle mass (kg),total body water (kg), basal metabolic rate (kcal). Laboratory tests were performed to determine the following serum levels: fasting glucose, fasting insulin, total cholesterol, LDL cholesterol fraction, HDL cholesterol fraction, triglycerides, C-reactive protein (CRP), uric acid, creatinine, and aminotrasferases: alanine (ALT) and aspartate (AST). On the basis of fasting glucose and fasting insulin. The HOMA - IR insulin resistance index was calculated according to the formula: fasting insulin (microU/L) x fasting glucose (nmol/L)/22.5.

    1 week

  • The impact of the abdominal adipose tissue (VAT, SAT or VAT/SAT) on the risk of metabolic complications of obesity with to use biochemical parameters.

    Abdominal adipose tissue was determined using the bioimpedance method with a BioScan 920-2 body composition analyzer (Maltron,UK): visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and VAT/SAT. Laboratory tests were performed to determine the following serum levels: fasting glucose, fasting insulin, total cholesterol, LDL cholesterol fraction, HDL cholesterol fraction, triglycerides, C-reactive protein (CRP), uric acid, creatinine, and aminotrasferases: alanine (ALT) and aspartate (AST). On the basis of fasting glucose and fasting insulin. The HOMA - IR insulin resistance index was calculated according to the formula: fasting insulin (microU/L) x fasting glucose (nmol/L)/22.5.

    1 week

  • The impact of abdominal adipose tissue distribution (VAT and SAT) on the parameters of cardiopulmonary efficiency.

    Abdominal adipose tissue was determined using the bioimpedance method with a BioScan 920-2 body composition analyzer (Maltron,UK): visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and VAT/SAT. Cardiopulmonary fitness was assessed using the Modified Bruce protocol.

    1 week

  • Verification of the usefulness of selected anthropometric parameters in the assessment of the risk of developing metabolic disorders in obesity and their relationship with cardiovascular and respiratory efficiency.

    An assessment of the status of nutrition based on anthropometric measurements was carried out: body mass index (body weight-kg/weight m2), Waist circumference measurements have been made to the nearest 0.1 centimeter using a tape measure at the uppermost lateral border of the hip crest, Hip circumference was measured at the greater trochanters at the widest part of the hips, Relative fat mass was calculated by the equation: 64-(20 x (height/waist circumference) Laboratory tests were performed to determine the following serum levels: fasting glucose, fasting insulin, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, C-reactive protein (CRP), uric acid, creatinine, and aminotrasferases: alanine and aspartate. On the basis of fasting glucose and fasting insulin The HOMA - IR insulin resistance index was calculated according to the formula: fasting insulin (microU/L) x fasting glucose (nmol/L)/22.5 Cardiopulmonary fitness was assessed using the Modified Bruce protocol

    1 week

  • The impact of dietary habbits and typicaly diet on on the risk of metabolic complications of obesity with to use biochemical parameters.

    An interview questionnaire concerning the duration of obesity and past diseases was collected. Moreover, the diet and nutritional status were assessed. A 7-day nutrition interview was collected. The supply of energy, protein (including amino acids), fat (including fatty acids), carbohydrates, dietary fiber, vitamins and minerals in the usual diet was assessed. Laboratory tests were performed to determine the following serum levels: fasting glucose, fasting insulin, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, C-reactive protein (CRP), uric acid, creatinine, and aminotrasferases: alanine and aspartate. On the basis of fasting glucose and fasting insulin The HOMA - IR insulin resistance index was calculated according to the formula: fasting insulin (microU/L) x fasting glucose (nmol/L)/22.5

    1 week

Study Arms (6)

G1a - women

The G1a group consisted of women with obesity, in whom no additional components of the metabolic syndrome were found (n =16)

Diagnostic Test: body composition analysisOther: anthropometric measurementsOther: Interview questionnaireDiagnostic Test: biochemical parametersDiagnostic Test: cardiopulmonary fitness testOther: nutritional interview

G1b - men

The G1b group consisted of men with obesity, in whom no additional components of the metabolic syndrome were founds (n =6)

Diagnostic Test: body composition analysisOther: anthropometric measurementsOther: Interview questionnaireDiagnostic Test: biochemical parametersDiagnostic Test: cardiopulmonary fitness testOther: nutritional interview

G2a - women

The G2a group consisted of women with obesity, in whom only one additional component of the metabolic syndrome was found (e.g. triglycerides ≥ 150 mg/dl, HDL cholesterol in women \< 50 mg/dl, and in men \< 40 mg/dl, or glycaemia ≥ 100 mg/dl), but it was not a disease previously diagnosed and treated (n=19)

Diagnostic Test: body composition analysisOther: anthropometric measurementsOther: Interview questionnaireDiagnostic Test: biochemical parametersDiagnostic Test: cardiopulmonary fitness testOther: nutritional interview

G2b - men

The G2a group consisted of men with obesity, in whom only one additional component of the metabolic syndrome was found (e.g. triglycerides ≥ 150 mg/dl, HDL cholesterol in women \< 50 mg/dl, and in men \< 40 mg/dl, or glycaemia ≥ 100 mg/dl), but it was not a disease previously diagnosed and treated (n=11)

Diagnostic Test: body composition analysisOther: anthropometric measurementsOther: Interview questionnaireDiagnostic Test: biochemical parametersDiagnostic Test: cardiopulmonary fitness testOther: nutritional interview

G3a - women

Group G3a consisted of women who met the full criteria for diagnosing the metabolic syndrome (n=24)

Diagnostic Test: body composition analysisOther: anthropometric measurementsOther: Interview questionnaireDiagnostic Test: biochemical parametersDiagnostic Test: cardiopulmonary fitness testOther: nutritional interview

G3b - men

Group G3a consisted of men who met the full criteria for diagnosing the metabolic syndrome (n=15)

Diagnostic Test: body composition analysisOther: anthropometric measurementsOther: Interview questionnaireDiagnostic Test: biochemical parametersDiagnostic Test: cardiopulmonary fitness testOther: nutritional interview

Interventions

A body composition analysis was performed using the bioelectroimpedance method using the Maltron BioScan 920-2 analyzer

G1a - womenG1b - menG2a - womenG2b - menG3a - womenG3b - men

An assessment of the status of nutrition based on anthropometric measurements was carried out.

G1a - womenG1b - menG2a - womenG2b - menG3a - womenG3b - men

An interview questionnaire concerning the duration of obesity and past diseases was collected. Moreover, the diet and nutritional status were assessed.

G1a - womenG1b - menG2a - womenG2b - menG3a - womenG3b - men
biochemical parametersDIAGNOSTIC_TEST

The concentrations of the following parameters were determined from the blood serum: fasting glucose, fasting insulin, total cholesterol, LDL cholesterol fraction, HDL cholesterol fraction, triglycerides, C-reactive protein (CRP), uric acid, creatinine, and aminotrasferases: alanine (ALT) and aspartate (AST). On the basis of fasting glucose and fasting insulin, the HOMA - IR insulin resistance index was calculated.

G1a - womenG1b - menG2a - womenG2b - menG3a - womenG3b - men

Cardiopulmonary fitness was assessed using the Modified Bruce protocol

G1a - womenG1b - menG2a - womenG2b - menG3a - womenG3b - men

A 7-day nutrition interview was collected. The supply of energy, protein (including amino acids), fat (including fatty acids), carbohydrates, dietary fiber, vitamins and minerals in the usual diet was assessed.

G1a - womenG1b - menG2a - womenG2b - menG3a - womenG3b - men

Eligibility Criteria

Age20 Years - 65 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodProbability Sample
Study Population

The research included 91 obese people (59 women and 32 men) who met the criteria for being included in the study and who did not possess exclusion criteria.

You may qualify if:

  • primary obesity
  • BMI ≥ 30kg/m2 - ≤ 39,99 kg/m2
  • gender: women and men
  • age: 20-65 lat

You may not qualify if:

  • secondry obesity
  • BMI ≥ 40 kg/m2
  • diabetes type 2 or insulin resistance (occurance or treatment)
  • endocrine disorders
  • eating disorders
  • hormonal contraception/hormone replacement therapy
  • after steroid therapy
  • antiretroviral therapy
  • musculoskeletal dysfunctions
  • patients after surgery (min 3 months)
  • bariatric surgery
  • coronary artery disease
  • cardiac pacemaker
  • pregnancy
  • breast - feeding

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Related Publications (12)

  • Mongraw-Chaffin M, Foster MC, Anderson CAM, Burke GL, Haq N, Kalyani RR, Ouyang P, Sibley CT, Tracy R, Woodward M, Vaidya D. Metabolically Healthy Obesity, Transition to Metabolic Syndrome, and Cardiovascular Risk. J Am Coll Cardiol. 2018 May 1;71(17):1857-1865. doi: 10.1016/j.jacc.2018.02.055.

    PMID: 29699611BACKGROUND
  • Pimentel Ade C, Scorsatto M, de Oliveira GM, Rosa G, Luiz RR. Characterization of metabolically healthy obese Brazilians and cardiovascular risk prediction. Nutrition. 2015 Jun;31(6):827-33. doi: 10.1016/j.nut.2014.12.024. Epub 2015 Jan 10.

    PMID: 25933489BACKGROUND
  • Hoddy KK, Axelrod CL, Mey JT, Hari A, Beyl RA, Blair JB, Dantas WS, Kirwan JP. Insulin resistance persists despite a metabolically healthy obesity phenotype. Obesity (Silver Spring). 2022 Jan;30(1):39-44. doi: 10.1002/oby.23312. Epub 2021 Nov 24.

    PMID: 34816598BACKGROUND
  • Perreault M, Zulyniak MA, Badoud F, Stephenson S, Badawi A, Buchholz A, Mutch DM. A distinct fatty acid profile underlies the reduced inflammatory state of metabolically healthy obese individuals. PLoS One. 2014 Feb 10;9(2):e88539. doi: 10.1371/journal.pone.0088539. eCollection 2014.

    PMID: 24520395BACKGROUND
  • Kim H, Yoon E, Kim OY, Kim EM. Short-term Effects of Eating Behavior Modification on Metabolic Syndrome-Related Risks in Overweight and Obese Korean Adults. J Obes Metab Syndr. 2022 Mar 30;31(1):70-80. doi: 10.7570/jomes21074.

    PMID: 35296564BACKGROUND
  • Zhou YH, Guo Y, Wang F, Zhou CL, Tang CY, Tang HN, Yan DW, Zhou HD. Association of Sex Hormones and Fat Distribution in Men with Different Obese and Metabolic Statuses. Int J Gen Med. 2022 Feb 9;15:1225-1238. doi: 10.2147/IJGM.S351282. eCollection 2022.

    PMID: 35173463BACKGROUND
  • Numao S, So R, Matsuo T, Nakagaichi M, Tanaka K. A favorable metabolic profile in metabolically healthy obesity is associated with physical activity level rather than abdominal fat volume in Japanese males. J Phys Ther Sci. 2021 Feb;33(2):137-141. doi: 10.1589/jpts.33.137. Epub 2021 Feb 13.

    PMID: 33642688BACKGROUND
  • Matsha TE, Ismail S, Speelman A, Hon GM, Davids S, Erasmus RT, Kengne AP. Visceral and subcutaneous adipose tissue association with metabolic syndrome and its components in a South African population. Clin Nutr ESPEN. 2019 Aug;32:76-81. doi: 10.1016/j.clnesp.2019.04.010. Epub 2019 Jun 3.

    PMID: 31221294BACKGROUND
  • Osorio-Conles O, Vega-Beyhart A, Ibarzabal A, Balibrea JM, Vidal J, de Hollanda A. Biological Determinants of Metabolic Syndrome in Visceral and Subcutaneous Adipose Tissue from Severely Obese Women. Int J Mol Sci. 2022 Feb 21;23(4):2394. doi: 10.3390/ijms23042394.

    PMID: 35216509BACKGROUND
  • Schorr M, Dichtel LE, Gerweck AV, Valera RD, Torriani M, Miller KK, Bredella MA. Sex differences in body composition and association with cardiometabolic risk. Biol Sex Differ. 2018 Jun 27;9(1):28. doi: 10.1186/s13293-018-0189-3.

    PMID: 29950175BACKGROUND
  • Chashmniam S, Hashemi Madani N, Nobakht Mothlagh Ghoochani BF, Safari-Alighiarloo N, Khamseh ME. The metabolome profiling of obese and non-obese individuals: Metabolically healthy obese and unhealthy non-obese paradox. Iran J Basic Med Sci. 2020 Feb;23(2):186-194. doi: 10.22038/IJBMS.2019.37885.9004.

    PMID: 32405361BACKGROUND
  • Kaess BM, Pedley A, Massaro JM, Murabito J, Hoffmann U, Fox CS. The ratio of visceral to subcutaneous fat, a metric of body fat distribution, is a unique correlate of cardiometabolic risk. Diabetologia. 2012 Oct;55(10):2622-2630. doi: 10.1007/s00125-012-2639-5. Epub 2012 Aug 17.

    PMID: 22898763BACKGROUND

MeSH Terms

Conditions

Obesity, AbdominalObesityMetabolic Diseases

Condition Hierarchy (Ancestors)

OverweightOvernutritionNutrition DisordersNutritional and Metabolic DiseasesBody WeightSigns and SymptomsPathological Conditions, Signs and Symptoms

Study Officials

  • Katarzyna Witczak - Sawczuk, PhD

    Medical University of Bialystok

    STUDY DIRECTOR
  • Lucyna Ostrowska, Professor

    Medical University of Bialystok

    STUDY CHAIR

Study Design

Study Type
observational
Observational Model
CASE CROSSOVER
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

October 26, 2022

First Posted

November 10, 2022

Study Start

November 11, 2016

Primary Completion

October 31, 2017

Study Completion

October 31, 2017

Last Updated

November 10, 2022

Record last verified: 2022-10

Data Sharing

IPD Sharing
Will not share