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Associations of Body Mass and Fat Indexes With Cardiometabolic Traits.

ABSTRACT: BACKGROUND:Body mass index (BMI) is criticized for not distinguishing fat from lean mass and ignoring fat distribution, leaving its ability to detect health effects unclear. OBJECTIVES:The aim of this study was to compare BMI with total and regional fat indexes from dual-energy x-ray absorptiometry in their associations with cardiometabolic traits. Duration of exposure to and change in each index across adolescence were examined in relation to detailed traits in young adulthood. METHODS:BMI was examined alongside total, trunk, arm, and leg fat indexes (each in kilograms per square meter) from dual-energy x-ray absorptiometry at ages 10 and 18 years in relation to 230 traits from targeted metabolomics at age 18 years in 2,840 offspring from the Avon Longitudinal Study of Parents and Children. RESULTS:Higher total fat mass index and BMI at age 10 years were similarly associated with cardiometabolic traits at age 18 years, including higher systolic and diastolic blood pressure, higher very low-density lipoprotein and low-density lipoprotein cholesterol, lower high-density lipoprotein cholesterol, higher triglycerides, and higher insulin and glycoprotein acetyls. Associations were stronger for both indexes measured at age 18 years and for gains in each index from age 10 to 18 years (e.g., 0.45 SDs [95% confidence interval: 0.38 to 0.53] in glycoprotein acetyls per SD unit gain in fat mass index vs. 0.38 SDs [95% confidence interval: 0.27 to 0.48] per SD unit gain in BMI). Associations resembled those for trunk fat index. Higher lean mass index was weakly associated with traits and was not protective against higher fat mass index. CONCLUSIONS:The results of this study support abdominal fatness as a primary driver of cardiometabolic dysfunction and BMI as a useful tool for detecting its effects.

SUBMITTER: Bell JA

PROVIDER: S-EPMC6290112 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Associations of Body Mass and Fat Indexes With Cardiometabolic Traits.

Bell Joshua A JA Carslake David D O'Keeffe Linda M LM Frysz Monika M Howe Laura D LD Hamer Mark M Wade Kaitlin H KH Timpson Nicholas J NJ Davey Smith George G

Journal of the American College of Cardiology 20181201 24

<h4>Background</h4>Body mass index (BMI) is criticized for not distinguishing fat from lean mass and ignoring fat distribution, leaving its ability to detect health effects unclear.<h4>Objectives</h4>The aim of this study was to compare BMI with total and regional fat indexes from dual-energy x-ray absorptiometry in their associations with cardiometabolic traits. Duration of exposure to and change in each index across adolescence were examined in relation to detailed traits in young adulthood.<h ...[more]

PMID: 30545453

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Project description:BackgroundAccelerated growth in early childhood is an established risk factor for later obesity and cardiometabolic disease, but the relative importance of fat mass (FM) and fat-free mass (FFM) accretion is not well understood. We aimed to study how FM and FFM at birth and their accretion during infancy were associated with body composition and cardiometabolic risk markers at 5 years.Methods and findingsHealthy children born at term were enrolled in the Infant Anthropometry and Body Composition (iABC) birth cohort between December 2008 and October 2012 at Jimma University Specialized Hospital in the city of Jimma, Ethiopia. FM and FFM were assessed using air displacement plethysmography a median of 6 times between birth and 6 months of age. In 507 children, we estimated individual FM and FFM at birth and their accretion over 0-3 and 3-6 months of age using linear-spline mixed-effects modelling. We analysed associations of FM and FFM at birth and their accretion in infancy with height, waist circumference, FM, FFM, and cardiometabolic risk markers at 5 years using multiple linear regression analysis. A total of 340 children were studied at the 5-year follow-up (mean age: 60.0 months; girls: 50.3%; mean wealth index: 45.5 out of 100; breastfeeding status at 4.5 to 6 months post-partum: 12.5% exclusive, 21.4% almost exclusive, 60.6% predominant, 5.5% partial/none). Higher FM accretion in infancy was associated with higher FM and waist circumference at 5 years. For instance, 100-g/month higher FM accretion in the periods 0-3 and 3-6 months was associated with 339 g (95% CI: 243-435 g, p < 0.001) and 367 g (95% CI: 250-484 g, p < 0.001) greater FM at 5 years, respectively. Higher FM at birth and FM accretion from 0 to 3 months were associated with higher FFM and cholesterol concentrations at 5 years. Associations for cholesterol were strongest for low-density lipoprotein (LDL)-cholesterol, and remained significant after adjusting for current FM. A 100-g higher FM at birth and 100-g/month higher FM accretion from 0 to 3 months were associated with 0.16 mmol/l (95% CI: 0.05-0.26 mmol/l, p = 0.005) and 0.06 mmol/l (95% CI: 0.01-0.12 mmol/l, p = 0.016) higher LDL-cholesterol at 5 years, respectively. Higher FFM at birth and FFM accretion in infancy were associated with higher FM, FFM, waist circumference, and height at 5 years. For instance, 100-g/month higher FFM accretion in the periods 0-3 and 3-6 months was associated with 1,002 g (95% CI: 815-1,189 g, p < 0.001) and 624 g (95% CI: 419-829 g, p < 0.001) greater FFM at 5 years, respectively. We found no associations of FM and FFM growth with any of the other studied cardiometabolic markers including glucose, HbA1c, insulin, C-peptide, HOMA-IR, triglycerides, and blood pressure. Non-attendance at the 5-year follow-up visit was the main limitation of this study, which may have introduced selection bias and limited the power of the regression analyses.ConclusionsFM accretion in early life was positively associated with markers of adiposity and lipid metabolism, but not with blood pressure and cardiometabolic markers related to glucose homeostasis. FFM accretion was primarily related to linear growth and FFM at 5 years.

Project description:ObjectiveThe worldwide prevalence of obesity mandates a widely accessible tool to categorize adiposity that can best predict associated health risks. The body adiposity index (BAI) was designed as a single equation to predict body adiposity in pooled analysis of both genders. We compared body adiposity index (BAI), body mass index (BMI), and other anthropometric measures, including percent body fat (PBF), in their correlations with cardiometabolic risk factors. We also compared BAI with BMI to determine which index is a better predictor of PBF.MethodsThe cohort consisted of 698 Mexican Americans. We calculated correlations of BAI, BMI, and other anthropometric measurements (PBF measured by dual energy X-ray absorptiometry, waist and hip circumference, height, weight) with glucose homeostasis indices (including insulin sensitivity and insulin clearance from euglycemic clamp), lipid parameters, cardiovascular traits (including carotid intima-media thickness), and biomarkers (C-reactive protein, plasminogen activator inhibitor-1 and adiponectin). Correlations between each anthropometric measure and cardiometabolic trait were compared in both sex-pooled and sex-stratified groups.ResultsBMI was associated with all but two measured traits (carotid intima-media thickness and fasting glucose in men), while BAI lacked association with several variables. BAI did not outperform BMI in its associations with any cardiometabolic trait. BAI was correlated more strongly than BMI with PBF in sex-pooled analyses (r?=?0.78 versus r?=?0.51), but not in sex-stratified analyses (men, r?=?0.63 versus r?=?0.79; women, r?=?0.69 versus r?=?0.77). Additionally, PBF showed fewer correlations with cardiometabolic risk factors than BMI. Weight was more strongly correlated than hip with many of the cardiometabolic risk factors examined.ConclusionsBAI is inferior to the widely used BMI as a correlate of the cardiometabolic risk factors studied. Additionally, BMI's relationship with total adiposity may not be the sole determinate of its association with cardiometabolic risk.

Project description:BackgroundIt is unknown how body fat distribution modulates the cardiometabolic risk of testicular cancer survivors after cisplatin-based chemotherapy.MethodsFor 455 patients enrolled in the Platinum Study at Memorial Sloan Kettering Cancer Center, visceral (VAT) and subcutaneous (SAT) adipose tissue was quantified on prechemotherapy computed tomography. The VAT-to-SAT ratio was calculated as a quantitative measure of central adiposity. Endpoints were incidence of new posthemotherapy cardiometabolic disease (new antihypertensive, lipid-lowering, or diabetes medication), and postchemotherapy Framingham risk scores. Cox models and linear regression with interaction terms were applied. Postchemotherapy body fat distribution was analyzed in 108 patients. All statistical tests were 2-sided.ResultsThe baseline median age was 31 years (interquartile range [IQR] = 26-39 years), body mass index (BMI) was 26 kg/m2 (IQR = 24-29 kg/m2), and the VAT-to-SAT ratio was 0.49 (IQR = 0.31-0.75). The median follow-up was 26 months (IQR = 16-59 months). Higher prechemotherapy VAT-to-SAT ratios inferred a higher likelihood of new cardiometabolic disease among patients with a BMI of 30 kg/m2 or greater (age-adjusted hazard ratio = 3.14, 95% confidence interval = 1.02 to 9.71, P = .047), but not other BMI groups. The prechemotherapy VAT-to-SAT ratio was associated with postchemotherapy Framingham risk scores in univariate regression analysis (exp(β)-estimate: 2.10, 95% confidence interval = 1.84 to 2.39, P < .001); in a multivariable model, this association was stronger in younger vs older individuals. BMI increased in most patients after chemotherapy and correlated with increases in the VAT-to-SAT ratio (Spearman r = 0.39, P < .001).ConclusionsIn testicular cancer survivors, central adiposity is associated with increased cardiometabolic risk after cisplatin-based chemotherapy, particularly in obese or young men. Weight gain after chemotherapy occurs preferentially in the visceral compartment, providing insight into the pathogenesis of cardiovascular disease in this population.

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.

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Dataset Information

Associations of Body Mass and Fat Indexes With Cardiometabolic Traits.

Publications

Associations of Body Mass and Fat Indexes With Cardiometabolic Traits.

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