Dataset Information

Pericardial fat volume and coronary atherosclerotic markers among body mass index groups.

ABSTRACT: BACKGROUND:Increased pericardial fat volume (PFV) is associated with coronary atherosclerosis burden independent of body mass index (BMI) in many clinical studies. However, the association of PFV with markers of coronary atherosclerosis has not yet been assessed by dividing the patients according to BMI categories. HYPOTHESIS:To assess the association of PFV measured by multi-detector CT (MDCT) angiography with coronary atherosclerotic markers (coronary artery calcium score [CAC], plaque type, and luminal stenosis) among BMI categories. METHODS:A total of 496 patients with suspected coronary artery disease who underwent 64-slice MDCT angiography examination were enrolled. Patients divided into obese, overweight, and normal weight groups according to BMI degree. RESULTS:PFV showed a significant association with CAC, non-calcified coronary plaque, and significant coronary stenosis in obese group. After adjusting for cardiac risk factors, the association of PFV with the non-calcified coronary plaque and significant coronary stenosis persisted. There was a significant association between PFV with CAC and significant coronary stenosis in normal weight group. The association between PFV with CAC and significant coronary stenosis in normal weight was persisted afar adjusting for cardiac risk factors. No significant association was noted between PFV with coronary plaque type in normal weight group. There was no significant independent association between PFV with coronary atherosclerotic markers in overweight group. CONCLUSIONS:Increased PFV was associated with advanced stage atherosclerosis in normal weight group, while increased PFV was associated with non-calcified plaque in obese. These results highlight the differential relationship of PFV with coronary atherosclerotic markers among BMI categories.

SUBMITTER: Hassan MB

PROVIDER: S-EPMC7462198 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Pericardial fat volume and coronary atherosclerotic markers among body mass index groups.

Hassan Mohammed Bader MB Nafakhi Hussein H Al-Mosawi Abdulameer A AA

Clinical cardiology 20200603 9

<h4>Background</h4>Increased pericardial fat volume (PFV) is associated with coronary atherosclerosis burden independent of body mass index (BMI) in many clinical studies. However, the association of PFV with markers of coronary atherosclerosis has not yet been assessed by dividing the patients according to BMI categories.<h4>Hypothesis</h4>To assess the association of PFV measured by multi-detector CT (MDCT) angiography with coronary atherosclerotic markers (coronary artery calcium score [CAC], ...[more]

PMID: 32492245

Similar Datasets

Project description:BackgroundAccurate obesity classification is important so that appropriate intervention can be instituted to modify metabolic risk factors. Commonly utilized body mass index (BMI) and percentage body fat (PBF) are influenced by lean mass whereas fat mass index (FMI) measures only body fat. This study compares the prevalence of obesity and metabolic risk factors with FMI, BMI and PBF using DXA (dual-energy x-ray absorptiometry).Methods489 women randomly recruited from the electoral roll were stratified into 4 age groups; 40-49, 50-59, 60-69 and 70-79 years from 2000 to 2001. Clinical data and DXA body composition were obtained. Statistical analyses were performed using Medcalc v15 (Ostend, Belgium) with significance level at p = 0.05 (two-tailed).ResultsThere was higher prevalence of obesity using PBF compared to BMI and FMI (p<0.001). This difference was greater from age 50-59 (p<0.05) which may be explained by age-related lean mass loss. PBF over-classified obesity in over 35% of normal and 95% of overweight categories compared to FMI and BMI. BMI has a sensitivity of 78.9% and specificity of 98.3% for obesity using FMI as the standard. BMI under-classified obesity in the overweight category by 14.9% compared to FMI. There was no difference in diabetes, dyslipidemia, hypertension and metabolic syndrome prevalence within the BMI-obesity and FMI-obesity categories (p>0.05).ConclusionPBF classified more obesity than BMI and FMI because of its low pre-determined threshold. The greater difference with PBF compared to BMI and FMI from the 50-59 decade onwards can be attributed to age-related lean mass loss. BMI had the lowest sensitivity for obesity diagnosis. BMI under-classified obesity in the overweight category compared to FMI due to its inability to differentiate lean mass. However, there was no significant difference in the prevalence of metabolic risk factors between BMI and FMI-obesity categories indicating that fat location may influence metabolic dysregulation.

Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.

Dataset Information

Pericardial fat volume and coronary atherosclerotic markers among body mass index groups.

Publications

Pericardial fat volume and coronary atherosclerotic markers among body mass index groups.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets