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Body fat percentage is a better marker than body mass index for determining inflammation status in polycystic ovary syndrome.

ABSTRACT: Background:Polycystic ovary syndrome (PCOS) is an endocrinopathic disorder most commonly experienced by women of reproductive age, and it is characterized by a low-grade chronic inflammatory condition. Excessive fat deposit has been long considered as an etiological factor in the pathogenesis of this inflammatory condition. Currently, body mass index (BMI) or percentage of body fat is used as a marker to assess the body fat composition of a person. Objective:To determine whether BMI or body fat percentage (BFP) can be used as a better marker for measuring inflammation related to body fat accumulation in polycystic ovary syndrome patients. Materials and Methods:This study took place at the Center for Reproductive Medicine, Yasmin Clinic, Cipto Mangunkusumo Hospital from January to December 2015. In this cross-sectional study, 32 reproductive age women with PCOS according to the Rotterdam criteria (2003) participated. Women with hyperandrogenism caused by non-classic congenital adrenal hyperplasia, pregnant and lactating women, etc., were excluded. Some variables such as BMI, clinical hyperandrogenism sign, BFP, and inflammatory markers were assessed and statistically analyzed. Results:From a total of 32 subjects of the study, BFP had a significant positive correlation with procalcitonin levels (r=0.35; p=0.048), while BMI did not (r=0.27; p=0.131). Conclusion:BFP can be used as a better marker for measuring inflammation related to body fat accumulation in PCOS subjects.

SUBMITTER: Hestiantoro A

PROVIDER: S-EPMC6314644 | biostudies-other | 2018 Oct

REPOSITORIES: biostudies-other

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Body fat percentage is a better marker than body mass index for determining inflammation status in polycystic ovary syndrome.

Hestiantoro Andon A Kapnosa Hasani Rachmat Dediat RD Shadrina Amalia A Situmorang Herbert H Ilma Nurul N Muharam Raden R Sumapraja Kanadi K Wiweko Budi B

International journal of reproductive biomedicine 20181001 10

<h4>Background</h4>Polycystic ovary syndrome (PCOS) is an endocrinopathic disorder most commonly experienced by women of reproductive age, and it is characterized by a low-grade chronic inflammatory condition. Excessive fat deposit has been long considered as an etiological factor in the pathogenesis of this inflammatory condition. Currently, body mass index (BMI) or percentage of body fat is used as a marker to assess the body fat composition of a person.<h4>Objective</h4>To determine whether B ...[more]

PMID: 30643854

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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:Bioelectrical impedance analysis (BIA)-derived indexes [e.g., fat (FMI) and fat-free mass indexes (FFMI), visceral fat level (VFL)] are used to characterize obesity as a cardiovascular risk factor (CRF). The BIA-derived index that better predicts arterial variability is still discussed.AimsTo determine: (1) the association of classical [weight, height, body mass index (BMI), basal metabolic rate (BMR)] and BIA-derived indexes, with arterial properties deviations from expected values (arterial z-scores); (2) maximum arterial variations attributable to BIA-derived indexes; (3) whether the composition of total body, trunk and/or limbs is most closely associated with arterial variations.MethodsHemodynamic, structural, and functional parameters of different histological types of arteries were assessed (n = 538, 7-85 years). Classical and BIA-derived indexes [fat mass and percentage, FMI, VFL, muscle mass percentage (PMM), FFMI, and percentage] were measured (mono- and multi-segmental devices). Arterial z-scores were obtained using age-related equations derived from individuals not-exposed to CRFs (n = 1,688).ResultsFirst, regardless of the classical index considered, the associations with the arterial properties showed a specific hierarchy order: diameters and local stiffness > aortic and brachial blood pressure (BP) > regional stiffness. Second, all the associations of FMI and FFMI with z-scores were positive. Third, FFMI exceeded the association obtained with BMI and BMR, considering structural z-scores. In contrast, FMI did not exceed the association with z-scores achieved by BMI and BMR. Fourth, regardless of CRFs and classical indexes, arterial z-scores would be mainly explained by FFMI, VFL, and PMM. Fifth, regardless of the body-segment considered, the levels of association between FMI and z-scores did not exceed those found for classic and FFMI. Total fat mass and trunk indexes showed a greater strength of association with z-scores than the FMI of limbs. Sixth, compared to lower limb FFMI indexes, total and upper limbs FFMI showed higher levels of association with z-scores.ConclusionsFFMI (but not FMI) exceeded the strength of association seen between BMI or BMR and structural z-scores. Regardless of the body segment analyzed, the associations between FMI and z-scores did not exceed those found with classic and FFMI. Arterial z-scores could be independently explained by FFMI, VFL, and PMM.

Project description:BackgroundWomen with polycystic ovary syndrome (PCOS) are generally considered to be central obese and at higher risks of metabolic disturbances. Imaging methods are the golden standards for detecting body fat distribution. However, evidence based on magnetic resonance imaging (MRI) and computed tomography (CT) is conflicting. This study systematically reviewed the imaging-based body fat distribution in PCOS patients and quantitatively evaluated the difference in body fat distribution between PCOS and BMI-matched controls.MethodsPUBMED, EMBASE, and Web of Science were searched up to December 2019, and studies quantitatively compared body fat distribution by MRI, CT, ultrasound, or X-ray absorptiometry (DXA) between women with PCOS and their BMI-matched controls were included. Two researchers independently reviewed the articles, extract data and evaluated the study quality based on Newcastle-Ottawa Scale (NOS).Results47 studies were included in systematic review and 39 were eligible for meta-analysis. Compared to BMI-matched controls, higher accumulations of visceral fat (SMD 0.41; 95%CI: 0.23-0.59), abdominal subcutaneous fat (SMD 0.31; 95%CI: 0.20-0.41), total body fat (SMD 0.19; 95% CI: 0.06-0.32), trunk fat (SMD 0.47; 95% CI: 0.17-0.77), and android fat (SMD 0. 36; 95% CI: 0.06-0.66) were identified in PCOS group. However, no significant difference was identified in all the above outcomes in subgroups only including studies using golden standards MRI or CT to evaluate body fat distribution (SMD 0.19; 95%CI: -0.04-0.41 for visceral fat; SMD 0.15; 95%CI: -0.01-0.31 for abdominal subcutaneous fat). Moreover, meta-regression and subgroup analyses showed that young and non-obese patients were more likely to accumulate android fat.ConclusionsPCOS women seem to have abdominal fat accumulation when compared with BMI-matched controls. However, MRI- and CT- assessed fat distribution was similar between PCOS and controls, suggesting central obesity may be independent of PCOS. These findings will help us reappraise the relationship between PCOS and abnormal fat deposition and develop specialized lifestyle interventions for PCOS patients.Systematic review registrationPROSPERO, identifier CRD42018102983.

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Body fat percentage is a better marker than body mass index for determining inflammation status in polycystic ovary syndrome.

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Body fat percentage is a better marker than body mass index for determining inflammation status in polycystic ovary syndrome.

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