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Waist, neck circumferences, waist-to-hip ratio: Which is the best cardiometabolic risk marker in women with severe obesity? The SOON cohort.

ABSTRACT: METHODS:Data from women (n = 305, aged 43 [34; 53] years-old, BMI 44.2 [40.8; 48.2] kg/m2) included in the Severe Obesity Outcome Network (SOON) cohort were analyzed (i) to evaluate collinearity between the different anthropometric markers, (ii) to compare the association of markers with hypertension, type 2 diabetes, obstructive sleep apnea syndrome (OSAS) and other cardiometabolic risks. RESULTS:Hip, waist and neck circumferences correlated with BMI with respectively less collinearity (r = 0.70, r = 0.59 and r = 0.37, respectively, p<0.001) whereas waist-to-hip ratio was not correlated (r = 0.11, p = 0.072). Waist and neck circumferences were significantly associated with hypertension, type 2 diabetes and OSAS in univariate logistic regressions, waist-to-hip ratio with hypertension and type 2 diabetes. Hip circumference was inversely correlated with type 2 diabetes (OR 0.970 (95CI: 0.948; 0.991) p = 0.006). BMI was only linked to OSAS (OR 1.092 (95CI: 1.043; 1.143) p<0.001). Neck circumference was the only marker significantly associated with all cardiometabolic risk markers (HOMA-IR, apnea-hypopnea index, Log Triglycerides/HDL-c, alanin-aminotransferase, aspartate-aminotransferase, gammaglutamyl transpeptidase). CONCLUSIONS:Neck circumference appears the most appropriate anthropometric marker to identify the fat distribution associated with high cardiometabolic risk in women with severe obesity.

SUBMITTER: Borel AL

PROVIDER: S-EPMC6224066 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Waist, neck circumferences, waist-to-hip ratio: Which is the best cardiometabolic risk marker in women with severe obesity? The SOON cohort.

Borel Anne-Laure AL Coumes Sandrine S Reche Fabian F Ruckly Stéphane S Pépin Jean-Louis JL Tamisier Renaud R Wion Nelly N Arvieux Catherine C

PloS one 20181108 11

<h4>Methods</h4>Data from women (n = 305, aged 43 [34; 53] years-old, BMI 44.2 [40.8; 48.2] kg/m2) included in the Severe Obesity Outcome Network (SOON) cohort were analyzed (i) to evaluate collinearity between the different anthropometric markers, (ii) to compare the association of markers with hypertension, type 2 diabetes, obstructive sleep apnea syndrome (OSAS) and other cardiometabolic risks.<h4>Results</h4>Hip, waist and neck circumferences correlated with BMI with respectively less collin ...[more]

PMID: 30408116

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Project description:Background Childhood overweight/obesity has been associated with an elevated risk of insulin resistance and cardiometabolic disorders. Waist-to-height ratio (WHtR) may be a simple screening tool to quickly identify children at elevated risk for cardiometabolic disorders. The primary objective of the present study was to create sex-specific tertile cut points of WHtR and assess its association with Insulin resistance and elevated liver enzyme concentrations in children, factors using cross-sectional data from the randomized, controlled Family Weight Management Study. Methods Baseline data from 360 children (7–12 years, mean Body Mass Index (BMI) ≥ 85th percentile for age and sex) were used to calculate WHtR tertiles by sex, male: ≤ 0.55 (T1), > 0.55- ≤ 0.59 (T2), > 0.59 (T3); female: ≤ 0.56 (T1), > 0.56- ≤ 0.6 (T2), > 0.6 (T3). The Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) was used to categorize participants as insulin-resistant (HOMA-IR ≥ 2.6) and insulin-sensitive (HOMA-IR < 2.6). Liver enzymes aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were categorized as normal vs. elevated (AST of < 36.0 µkat/L or ≥ 36.0 µkat/L; ALT of < 30.0 µkat/L or ≥ 30.0 µkat/L; ALT > 26 µkat/L males, > 22 µkat/L females). We examined differences in baseline cardiometabolic risk factors by WHtR tertiles and sex-specific multivariable logistic regression models to predict HOMA-IR and elevation of liver enzymes. Results Study participants had a mean WHtR of 0.59 ([SD: 0.06]). Irrespective of sex, children in WHtR T3 had higher BMIz scores, blood pressure, triglycerides, 2-h glucose, fasting 2-h insulin, and lower high-density lipoprotein cholesterol (HDL-C) concentrations than those in T2 and T1. After adjusting for covariates, the odds of elevated HOMA-IR (> 2.6) were over five-fold higher among males in T3 versus T1 [OR, 95%CI: 5.83, 2.34–14.52] and T2 [OR, 95%CI: 4.81, 1.94–11.92] and females in T3 [OR, 95%CI: 5.06, 2.10–12.20] versus T1. The odds of elevated ALT values (≥ 30) were 2.9 [95%CI: 1.01–8.41] fold higher among females in T3 compared to T1. Conclusion In public health settings, WHtR may be a practical screening tool in pediatric populations to identify children at risk of metabolic syndrome. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-023-16418-9.

Project description:ImportanceIn observational studies, abdominal adiposity has been associated with type 2 diabetes and coronary heart disease (CHD). Whether these associations represent causal relationships remains uncertain.ObjectiveTo test the association of a polygenic risk score for waist-to-hip ratio (WHR) adjusted for body mass index (BMI), a measure of abdominal adiposity, with type 2 diabetes and CHD through the potential intermediates of blood lipids, blood pressure, and glycemic phenotypes.Design, setting, and participantsA polygenic risk score for WHR adjusted for BMI, a measure of genetic predisposition to abdominal adiposity, was constructed with 48 single-nucleotide polymorphisms. The association of this score with cardiometabolic traits, type 2 diabetes, and CHD was tested in a mendelian randomization analysis that combined case-control and cross-sectional data sets. Estimates for cardiometabolic traits were based on a combined data set consisting of summary results from 4 genome-wide association studies conducted from 2007 to 2015, including up to 322 154 participants, as well as individual-level, cross-sectional data from the UK Biobank collected from 2007-2011, including 111 986 individuals. Estimates for type 2 diabetes and CHD were derived from summary statistics of 2 separate genome-wide association studies conducted from 2007 to 2015 and including 149 821 individuals and 184 305 individuals, respectively, combined with individual-level data from the UK Biobank.ExposuresGenetic predisposition to increased WHR adjusted for BMI.Main outcomes and measuresType 2 diabetes and CHD.ResultsAmong 111 986 individuals in the UK Biobank, the mean age was 57 (SD, 8) years, 58 845 participants (52.5%) were women, and mean WHR was 0.875. Analysis of summary-level genome-wide association study results and individual-level UK Biobank data demonstrated that a 1-SD increase in WHR adjusted for BMI mediated by the polygenic risk score was associated with 27-mg/dL higher triglyceride levels, 4.1-mg/dL higher 2-hour glucose levels, and 2.1-mm Hg higher systolic blood pressure (each P < .001). A 1-SD genetic increase in WHR adjusted for BMI was also associated with a higher risk of type 2 diabetes (odds ratio, 1.77 [95% CI, 1.57-2.00]; absolute risk increase per 1000 participant-years, 6.0 [95% CI, CI, 4.4-7.8]; number of participants with type 2 diabetes outcome, 40 530) and CHD (odds ratio, 1.46 [95% CI, 1.32-1.62]; absolute risk increase per 1000 participant-years, 1.8 [95% CI, 1.3-2.4]; number of participants with CHD outcome, 66 440).Conclusions and relevanceA genetic predisposition to higher waist-to-hip ratio adjusted for body mass index was associated with increased risk of type 2 diabetes and coronary heart disease. These results provide evidence supportive of a causal association between abdominal adiposity and these outcomes.

Project description:BackgroundWaist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) are all independent predictors of cardio-metabolic risk and therefore important in HIV/AIDS patients on antiretroviral therapy at risk of increased visceral adiposity. This study aimed to assess the extent of agreement between these parameters and the body mass index (BMI), as anthropometric parameters and in classifying cardio-metabolic risk in HIV/AIDS patients.MethodsA secondary analysis of data from a cross-sectional study involving 200 HIV/AIDS patients was done. Anthropometric parameters were measured from participants using standard guidelines and central obesity defined according to recommended criteria. Increased cardio-metabolic risk was defined according to the standard cut-off values for all four parameters. Data were analyzed using STATA version 14.1.ResultsThe prevalence of WC-defined central obesity, WHR-defined central obesity and WHtR > 0.50 were 33.5%, 44.5% and 36.5%, respectively. The prevalence of BMI-defined overweight and obesity was 40.5%. After adjusting for gender and HAART status, there was a significant linear association and correlation between WC and BMI (regression equation: WC (cm) = 37.184 + 1.756 BMI (Kg/m2) + 0.825 Male + 1.002 HAART, (p < 0.001, r = 0.65)), and between WHtR and BMI (regression equation: WHtR = 0.223 + 0.011 BMI (Kg/m2)- 0.0153 Male + 0.003 HAART, (p < 0.001, r = 0.65)), but not between WHR and BMI (p = 0.097, r = 0.13). There was no agreement between the WC, WHtR and BMI, and minimal agreement between the WHR and BMI, in identifying patients with an increased cardio-metabolic risk.ConclusionDespite the observed linear association and correlation between these anthropometric parameters, the routine use of WC, WHR and WHtR as better predictors of cardio-metabolic risk should be encouraged in these patients, due to their minimal agreement with BMI in identifying HIV/AIDS patients with increased cardio-metabolic risk. HAART status does not appear to significantly affect the association between these anthropometric parameters.

Project description:ObjectivesTo determine the prevalence of obesity indices (body mass index (BMI), waist circumference (WC), body fat per cent (BF%)) and cardiometabolic risk factors. To investigate the association between obesity indices and cardiometabolic risk factors in a Zanzibari population.DesignsCross-sectional study.SettingsParticipants randomly selected from 80 Shehias (wards) in Unguja, Zanzibar in 2013.ParticipantsA total of 470 participants between 5 and 95 years were examined. Data on socioeconomic status, area of residence, anthropometry and venous blood were collected. Associations between obesity indices and cardiometabolic risk factors were investigated using multilevel logistic regression analyses in two steps: first, each obesity indicator was tested independently; second, all indicators combined in one model were tested for their association with cardiometabolic risk factors.ResultsThe proportion of overweight/obese individuals was 26.4%, high WC (24.9%) and high BF% (31.1%). Cardiometabolic risk factors with highest prevalence of abnormal values included hypertension (24.5%), low high-density lipoprotein cholesterol (HDL-C) (29.4%), high low-density lipoprotein cholesterol (LDL-C) (21.3%) and high glycated haemoglobin (HbA1c) (19.1%). Obesity and hypertension increased with age, and were most prevalent in participants aged 45 years and above. Low HDL-C was most prevalent among participants aged ≥18 to <45 years, while high LDL-C was more prevalent in those above 45 years. High WC and high BF% were associated with high levels of LDL-C (OR=2.52 (95% CI 1.24 to 5.13), OR=1.91 (95% CI 1.02 to 3.58), respectively). Additionally, BMI and WC were associated with high levels of HbA1c (OR=2.08 (95% CI 1.15 to 3.79), OR=3.01 (95% CI 1.51 to 6.03), respectively). In the combined regression model, WC was associated with higher chances for hypertension (OR=2.62 (95% CI 1.14 to 6.06)) and for high levels of HbA1c (OR=2.62 (95% CI 1.12 to 6.15)).ConclusionHigh BMI, WC and BF% were strongly associated with hypertension, with individuals with high WC being twice more likely to have hypertension; this calls for early and effective screening strategies for this study population.

Project description:Background/objectiveThis observational study dissects the complex temporal associations between body-mass index (BMI), waist-hip ratio (WHR) and circulating metabolomics using a combination of longitudinal and cross-sectional population-based datasets and new systems epidemiology tools.Subjects/methodsFirstly, a data-driven subgrouping algorithm was employed to simplify high-dimensional metabolic profiling data into a single categorical variable: a self-organizing map (SOM) was created from 174 metabolic measures from cross-sectional surveys (FINRISK, n = 9708, ages 25-74) and a birth cohort (NFBC1966, n = 3117, age 31 at baseline, age 46 at follow-up) and an expert committee defined four subgroups of individuals based on visual inspection of the SOM. Secondly, the subgroups were compared regarding BMI and WHR trajectories in an independent longitudinal dataset: participants of the Young Finns Study (YFS, n = 1286, ages 24-39 at baseline, 10 years follow-up, three visits) were categorized into the four subgroups and subgroup-specific age-dependent trajectories of BMI, WHR and metabolic measures were modelled by linear regression.ResultsThe four subgroups were characterised at age 39 by high BMI, WHR and dyslipidemia (designated TG-rich); low BMI, WHR and favourable lipids (TG-poor); low lipids in general (Low lipid) and high low-density-lipoprotein cholesterol (High LDL-C). Trajectory modelling of the YFS dataset revealed a dynamic BMI divergence pattern: despite overlapping starting points at age 24, the subgroups diverged in BMI, fasting insulin (three-fold difference at age 49 between TG-rich and TG-poor) and insulin-associated measures such as triglyceride-cholesterol ratio. Trajectories also revealed a WHR progression pattern: despite different starting points at the age of 24 in WHR, LDL-C and cholesterol-associated measures, all subgroups exhibited similar rates of change in these measures, i.e. WHR progression was uniform regardless of the cross-sectional metabolic profile.ConclusionsAge-associated weight variation in adults between 24 and 49 manifests as temporal divergence in BMI and uniform progression of WHR across metabolic health strata.

Dataset Information

Waist, neck circumferences, waist-to-hip ratio: Which is the best cardiometabolic risk marker in women with severe obesity? The SOON cohort.

Publications

Waist, neck circumferences, waist-to-hip ratio: Which is the best cardiometabolic risk marker in women with severe obesity? The SOON cohort.

Similar Datasets

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