The Impact of the Distribution of Adipose Tissue on the Occurrence of Metabolic Disorders and the Level of Cardiopulmonary Fitness
1 other identifier
observational
91
0 countries
N/A
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
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for all trials
Started Nov 2016
Shorter than P25 for all trials
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
November 11, 2016
CompletedPrimary Completion
Last participant's last visit for primary outcome
October 31, 2017
CompletedStudy Completion
Last participant's last visit for all outcomes
October 31, 2017
CompletedFirst Submitted
Initial submission to the registry
October 26, 2022
CompletedFirst Posted
Study publicly available on registry
November 10, 2022
CompletedNovember 10, 2022
October 1, 2022
12 months
October 26, 2022
November 4, 2022
Conditions
Keywords
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)
G1b - men
The G1b group consisted of men with obesity, in whom no additional components of the metabolic syndrome were founds (n =6)
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)
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)
G3a - women
Group G3a consisted of women who met the full criteria for diagnosing the metabolic syndrome (n=24)
G3b - men
Group G3a consisted of men who met the full criteria for diagnosing the metabolic syndrome (n=15)
Interventions
A body composition analysis was performed using the bioelectroimpedance method using the Maltron BioScan 920-2 analyzer
An assessment of the status of nutrition based on anthropometric measurements was carried out.
An interview questionnaire concerning the duration of obesity and past diseases was collected. Moreover, the diet and nutritional status were assessed.
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.
Cardiopulmonary fitness was assessed using the Modified Bruce protocol
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.
Eligibility Criteria
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: 29699611BACKGROUNDPimentel 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: 25933489BACKGROUNDHoddy 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: 34816598BACKGROUNDPerreault 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: 24520395BACKGROUNDKim 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: 35296564BACKGROUNDZhou 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: 35173463BACKGROUNDNumao 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: 33642688BACKGROUNDMatsha 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: 31221294BACKGROUNDOsorio-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: 35216509BACKGROUNDSchorr 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: 29950175BACKGROUNDChashmniam 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: 32405361BACKGROUNDKaess 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
Condition Hierarchy (Ancestors)
Study Officials
- STUDY DIRECTOR
Katarzyna Witczak - Sawczuk, PhD
Medical University of Bialystok
- STUDY CHAIR
Lucyna Ostrowska, Professor
Medical University of Bialystok
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