Universidad De Navarra-Body Adiposity Estimator Research Articles

Association of the CUN-BAE body adiposity estimator and other obesity indicators with cardiometabolic multimorbidity: a cross-sectional study

Cardiometabolic multimorbidity (CM), defined as the coexistence of two or three cardiometabolic disorders, is one of the most common and deleterious multimorbidities. This study aimed to investigate the association of Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) with the prevalence of CM. The data were obtained from the 2021 health checkup database for residents of the Electronic Health Management Center in Xinzheng, Henan Province, China. 81,532 participants aged ≥ 60 years were included in this study. Logistic regression models were used to estimate the odd ratios (ORs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in CM. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different anthropometric indicators for CM. The multivariable-adjusted ORs (95% CIs) (per 1 SD increase) of CM were 1.799 (1.710–1.893) for CUN-BAE, 1.329 (1.295–1.364) for BMI, 1.343 (1.308–1.378) for WC, and 1.314 (1.280–1.349) for WHtR, respectively. Compared with BMI, WC and WHtR, CUN-BAE had the highest AUC in both males and females (AUC: 0.642; 95% CI 0.630–0.653 for males, AUC: 0.614; 95% CI 0.630–0.653 for females). CUN-BAE may be a better measure of the adverse effect of adiposity on the prevalence of CM than BMI, WC, and WHtR.

Association of the Clínica Universidad de Navarra-Body Adiposity Estimator With Type 2 Diabetes: A Retrospective Cohort Study.

Objectives: Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) is considered to be a more accurate indicator of body fat estimation. We aimed to investigate the association of CUN-BAE with the risk of type 2 diabetes mellitus (T2DM) and to compare the strength of the association between CUN-BAE, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and T2DM. Methods: The data were obtained from the annual health checkup database of residents in Xinzheng, China. From January 2011 to December 2021, 80,555 subjects aged ≥45years met the inclusion criteria. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in T2DM. Results: During a mean follow-up of 6.26years, T2DM occurred in 12,967 subjects. The multivariable-adjusted HRs (95% CIs) of T2DM (highest vs. reference group) were 1.994 (1.811-2.196) for CUN-BAE, 1.751 (1.665-1.842) for WC, 1.715 (1.631-1.804) for WHtR, and 1.510 (1.436-1.588) for BMI, respectively. In addition, the risk of T2DM increased with baseline CUN-BAE (HR: 1.374; 95% CI: 1.328, 1.421), WC (HR: 1.236; 95% CI: 1.215, 1.256), WHtR (HR: 1.228; 95% CI: 1.208, 1.248), and BMI (HR: 1.175; 95% CI: 1.156, 1.195). Conclusion: Compared to BMI, WC or WHtR, CUN-BAE may more adequately reflect the adverse effects of adiposity on the risk of T2DM.

The relationship between the CUN-BAE body fatness index and incident diabetes: a longitudinal retrospective study

BackgroundThe Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index has been recommended as an ideal indicator of body fat and exhibited significant correlation with cardiometabolic risk factors. However, whether the CUN-BAE index correlates with incident diabetes in Asian populations is unknown. Therefore, this longitudinal study was designed to evaluate the association between baseline CUN-BAE index and type 2 diabetes mellitus (T2DM).MethodsThis retrospective longitudinal study involved 15,464 participants of 18–79 years of age in the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) study over the period of 2004–2015. Cox proportional hazards regression was performed to test the relationship between the baseline CUN-BAE index and diabetes incidence. Further stratification analysis was conducted to ensure that the results were robust. The diagnostic utility of the CUN-BAE index was tested by the receiver operating characteristic (ROC) curve.ResultsOver the course of an average follow-up of 5.4 years, 373 (2.41%) participants developed diabetes. A higher diabetes incidence was associated with higher CUN-BAE quartiles (P for trend< 0.001). Each 1 unit increase in CUN-BAE index was associated with a 1.08-fold and 1.14-fold increased risk of diabetes after adjustment for confounders in males and females, respectively (both P < 0.001). Stratification analysis demonstrated a consistent positive correlation between baseline CUN-BAE and diabetes incidence. Moreover, based on ROC analysis, CUN-BAE exhibited a better capacity for diabetes prediction than both body mass index (BMI) and waist circumference (WC) in both sexes.ConclusionsThe baseline CUN-BAE level was independently related to the incidence of diabetes. Increased adiposity determined by CUN-BAE could be used as a strong nonlaboratory predictor of incident diabetes in clinical practice.

Is There a Link between Obesity Indices and Skin Autofluorescence? A Response from the ILERVAS Project.

There is controversial information about the accumulation of advanced glycation end-products (AGEs) in obesity. We assessed the impact of total and abdominal adiposity on AGE levels via a cross-sectional investigation with 4254 middle-aged subjects from the ILERVAS project. Skin autofluorescence (SAF), a non-invasive assessment of subcutaneous AGEs, was measured. Total adiposity indices (BMI and Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE)) and abdominal adiposity (waist circumference and body roundness index (BRI)) were assessed. Lean mass was estimated using the Hume index. The area under the receiver operating characteristic (ROC) curve was evaluated for each index. Different cardiovascular risk factors (smoking, prediabetes, hypertension and dyslipidemia) were evaluated. In the study population, 26.2% showed elevated SAF values. No differences in total body fat, visceral adiposity and lean body mass were detected between patients with normal and high SAF values. SAF levels showed a very slight but positive correlation with total body fat percentage (estimated by the CUN-BAE formula) and abdominal adiposity (estimated by the BRI). However, none of them had sufficient power to identify patients with high SAF levels (area under the ROC curve &lt;0.52 in all cases). Finally, a progressive increase in SAF levels was observed in parallel with cardiovascular risk factors in the entire population and when patients with normal weight, overweight and obesity were evaluated separately. In conclusion, total obesity and visceral adiposity are not associated with a greater deposit of AGE. The elevation of AGE in obesity is related to the presence of cardiometabolic risk.

Body adiposity estimated with CUN-BAE predicts atrial fibrillation: the SUN cohort

Abstract Background Obesity is widely recognised as a strong risk factor for atrial fibrillation and recent interest has focused on epicardial fat. Although body mass index is commonly used in the clinical practice, it doesn't precisely estimate adiposity. The Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) is an equation developed for body fat calculation, that has been previously associated with cardiometabolic disease. Our objective was to assess the association between body fat, as captured by the CUN-BAE index, and the incidence of atrial fibrillation in a prospective cohort. Methods The SUN project is a dynamic, prospective cohort of Spanish university graduates. A total of 20.136 participants, free of atrial fibrillation at baseline, were followed-up for a median time of 12 years, with a retention proportion of 91%. CUN-BAE was calculated for each participant taking into account only sex, age and body mass index. Incident cases of atrial fibrillation were confirmed by a cardiologist according to a prespecified protocol. Multivariable Cox regression models were used to estimate hazard ratios (HR) of atrial fibrillation according to calculated body fat. Results During follow-up, we identified 128 incident cases of atrial fibrillation. There was a strong direct association between a higher CUN-BAE index at baseline and incident atrial fibrillation during follow-up. In comparison to participants with a lower body fat category (median 21.3%), those with a higher category of body fat (median 34.8%) exhibited a significant 118% higher relative risk of incident atrial fibrillation (adjusted HR=2.18; 95% CI: 1.22, 3.90). For each 2-unit increase in the CUN-BAE index, atrial fibrillation risk significantly increased by 10%. The risk of incident atrial fibrillation remained significantly associated with adiposity even after further adjustment for obesity (body mass index ≥30 kg/m2) and in repeated measures analysis of the CUN-BAE index every other year. Conclusions Increased body adiposity, as captured by CUN-BAE index, was strongly and independently associated with a higher risk of atrial fibrillation in a Spanish cohort. These findings support the hypothesis that adiposity is closely related with arrhythmogenic mechanisms that could lead to atrial fibrillation and may be predicted using an equation to estimate body fat. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Spanish Ministry of Health and European Regional Development Fund (FEDER)

Abstract 5940: Impact of obesity on sexual functioning in women with gynecologic cancer pre-and post-radiotherapy

Abstract Background: As the prevalence of obesity in women increases in the US, a better understanding of the effect of obesity on women with gynecologic cancer (GynCa) is imperative. However, whether obesity impacts sexual functioning (SF) in GynCa patients has been understudied. Limited studies have used body mass index (BMI) as the only obesity indicator, which may result in a misunderstanding of the effect of obesity on SF in GynCa patients with different body compositions. This study aimed to explore the role of obesity via two different measures in determining SF in GynCa patients pre-and post-radiotherapy (RT). Methods: In this secondary analysis, obesity was measured pre-RT by both BMI and body fat percentage (BFP). BFP was calculated by using the Clinica Universidad de Navarra-Body Adiposity Estimator. SF, physical and emotional well-being were assessed pre-RT by the Female Sexual Function Index and the Functional Assessment of Cancer Therapy-General. At 6 months post-RT, SF was reassessed. Generalized linear models (GLM) and generalized linear mixed models (GLMM) with a log-link were implemented to identify the effect of obesity (using BMI and BFP) on SF pre-and post-RT. Regression-based mediation analysis was used to identify mediating effects of physical and emotional well-being between obesity and SF. Results: Among 54 (24 cervical and 30 endometrial) patients, 48% were Black, 52% were married or in a domestic partnership, and 59% were treated with surgery and/or chemotherapy pre-RT (i.e. prior treatment). Less patients were classified as being obese when obesity was measured by BMI (48%) compared to BFP (61%). Patients with endometrial cancer and prior treatment history were more likely to be obese and reported better SF. Unadjusted GLM showed that patients with obesity had better SF than those without obesity pre-RT regardless of obesity measures (BMI p = .018; BFP p = .016). However, we found no association between obesity (both BMI-and BFP-based obesity) and SF pre-RT after adjusting for cancer type and prior treatment history. GLMM showed that BFP-based obesity had a negative effect on the improvement in SF from pre-RT to post-RT (p = .013) after adjusting for cancer type and prior treatment history. Patients without BFP-based obesity showed a significant improvement post-RT (p = .019), but those with obesity (per BFP) showed no changes in SF post-RT (p = .949) compared to pre-RT. BMI-based obesity did not affect the changes in SF post-RT. We found no mediation effects of physical and emotional well-being between obesity and SF. Conclusions: Obesity may play a negative role in SF improvement in GynCa patients post-RT. More rigorous research and clinical attention to obesity measurement are necessary to determine the association between obesity and SF in GynCa patients and thus lead to the discovery of new interventions for this long-neglected topic of SF in GynCa patients, particularly for those who are obese. Citation Format: Haerim Lee, Deborah W. Bruner, Yi-Juan Hu, Jinbing Bai, Tony Y. Eng, Joseph W. Shelton, Pretesh R. Patel, Namita Khanna, Isabelle Scott, Katherine A. Yeager. Impact of obesity on sexual functioning in women with gynecologic cancer pre-and post-radiotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5940.

Increased Adiposity Appraised with CUN-BAE Is Highly Predictive of Incident Hypertension. The SUN Project.

Overweight and obesity are growing worldwide and strongly associated with hypertension. The Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index is proposed as an optimal indicator of body fatness. We aimed to investigate the association of body fat as captured by the CUN-BAE index with incident hypertension in a Mediterranean population. We assessed 15,950 participants of the SUN (Seguimiento Universidad de Navarra) prospective cohort (63.7% women) initially free of hypertension. Participants completed follow-up questionnaires biennially. A validated 136-item food-frequency questionnaire was administered at baseline. We used Cox models adjusted for multiple confounders. Among 12.3 years of median follow-up (interquartile range: 8.3, 15.0 years), 2160 participants reported having received a diagnosis of hypertension. We observed a strong direct association between progressively higher the CUN-BAE index at baseline and incident hypertension during follow-up in multivariable-adjusted models for men and women, even after further adjustment for BMI ≥ 30 kg/m2, showing a significant association also in non-obese participants. For each 2-unit increase in the CUN-BAE index, hypertension risk increased by 27% and 29% in men and women, respectively. The results remained significant when considering longitudinal repeated measures of changes in body fat assessed with the CUN-BAE index among the different biennial follow-up questionnaires. Our results emphasize the importance of reducing and maintaining a low body fat to prevent hypertension.

Clinical Usefulness of Anthropometric Indices to Predict the Presence of Prediabetes. Data from the ILERVAS Cohort.

Prediabetes is closely related to excess body weight and adipose distribution. For this reason, we aimed to assess and compare the diagnostic usefulness of ten anthropometric adiposity indices to predict prediabetes. Cross-sectional study with 8188 overweight subjects free of type 2 diabetes from the ILERVAS project (NCT03228459). Prediabetes was diagnosed by levels of glycated hemoglobin (HbA1c). Total body adiposity indices [BMI, Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) and Deurenberg’s formula] and abdominal adiposity (waist and neck circumferences, conicity index, waist to height ratio, Bonora’s equation, A body shape index, and body roundness index) were calculated. The area under the receiver-operating characteristic (ROC) curve, the best cutoff and the prevalence of prediabetes around this value were calculated for every anthropometric index. All anthropometric indices other than the A body adiposity were higher in men and women with prediabetes compared with controls (p < 0.001 for all). In addition, a slightly positive correlation was found between indices and HbA1c in both sexes (r ≤ 0.182 and p ≤ 0.026 for all). None of the measures achieved acceptable levels of discrimination in ROC analysis (area under the ROC ≤ 0.63 for all). Assessing BMI, the prevalence of prediabetes among men increased from 20.4% to 36.2% around the cutoff of 28.2 kg/m2, with similar data among women (from 29.3 to 44.8% with a cutoff of 28.6 kg/m2). No lonely obesity index appears to be the perfect biomarker to use in clinical practice to detect individuals with prediabetes.

Anthropometric indices and cut-off points in the diagnosis of metabolic disorders.

Identifying metabolic disorders at the earliest phase of their development allows for an early intervention and the prevention of serious consequences of diseases. However, it is difficult to determine which of the anthropometric indices of obesity is the best tool for diagnosing metabolic disorders. The aims of this study were to evaluate the usefulness of selected anthropometric indices and to determine optimal cut-off points for the identification of single metabolic disorders that are components of metabolic syndrome (MetS). Cross-sectional study. We analyzed the data of 12,328 participants aged 55.7±5.4 years. All participants were of European descent. Four MetS components were included: high glucose concentration, high blood triglyceride concentration, low high-density lipoprotein cholesterol concentration, and elevated blood pressure. The following obesity indices were considered: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), body fat percentage (%BF), Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE), body roundness index (BRI), and a body shape index (ABSI). The following indices had the highest discriminatory power for the identification of at least one MetS component: CUN-BAE, BMI, and WC in men (AUC = 0.734, 0.728, and 0.728, respectively) and WHtR, CUN-BAE, and WC in women (AUC = 0.715, 0.714, and 0.712, respectively) (p<0.001 for all). The other indices were similarly useful, except for the ABSI. For the BMI, the optimal cut-off point for the identification of metabolic abnormalities was 27.2 kg/m2 for both sexes. For the WC, the optimal cut-off point was of 94 cm for men and 87 cm for women. Prospective studies are needed to identify those indices in which changes in value predict the occurrence of metabolic disorders best.

Dynamics of Anthropometric Indices in a Large Paired Cohort With 10 Years of Follow-Up: Paving the Way to Sarcopenic Obesity.

Introduction: Paired cohort investigations assessing the evolution of anthropometric indices are scarce. Here we assessed the 10-year evolution of BMI, total body fat, and lean body mass in 50,019 participants aged 18–90 years at the time of first assessment.Material and Methods: A retrospective cohort study using an electronic database that contains anonymized, longitudinal data from Primary Care medical records covering the 2007–2008 and 2017–2018 periods. Total body fat was estimated using the Clínica Universidad de Navarra-Body Adiposity Estimator formula, and the Hume formula was applied to estimate lean body mass.Results: The mean BMI of participants <60 years old in the 2007–2008 period increased significantly, from 27.5 to 28.3 kg/m2 (p < 0.001). However, the BMI of older subjects decreased during the next decade, from 28.9 to 28.3 kg/m2 (p < 0.001). The estimated total body fat showed a continuous progressive increase over all ages. Finally, lean body mass showed a progressive increase until the 40s, with a plateau between 40–45 years old and an uninterrupted decrease until older ages. Also, subjects who increased their BMI by 2 kg/m2 during the 10-year period were mainly women and younger at baseline, with a lower initial BMI and total body fat in comparison with those who experienced a BMI decrease of ≥2.0 kg/m2.Conclusion: The evolutions of BMI and the estimated body compositions reported here confirm that the adverse decrease in lean body mass begins in middle age. The proportion of older subjects is important when evaluating overweight and obesity prevalence in cross-sectional studies.

The Relation of CUN-BAE Index with Body Mass Index and Waist Circumference in Adults Aged 50 to 85 Years: The MCC-Spain Study.

Backgound: Traditional anthropometrics such as body mass index (BMI) or waist circumference (WC) do not fully capture the complex biology of body fat (BF) in the elderly. The Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index, based on BMI, is proposed as a better indicator of BF. However, its relation with BMI is not clear. The aim was to compare the agreement between CUN-BAE, BMI, and WC in those aged ≥50 years. Methods: A cross-sectional sample of 3153 Caucasian healthy adults was taken from the MCC-Spain study. The Pearson’s correlation and its 95% confidence interval (CI), adiposity distribution, and Kappa Index (95%CI) were calculated. Results: The correlation of CUN-BAE with WC is 0.18 (95%CI 0.14–0.21) and that with BMI is moderate (r 0.58; 95%CI 0.55–0.60), but both increased strongly by sex. Agreement (normal weight/overweight/obesity) of CUN-BAE with BMI is 7% and with WC is 18%. Conclusions: The correlation and the degree of agreement of CUN-BAE with BMI and WC are low in individuals aged over 50, but it is higher by sex. Thus, this different criterion of obesity may have clinical applications. More studies with a gold standard are needed to evaluate the CUN-BAE in elderly adults.

Is urinary sodium excretion related to anthropometric indicators of adiposity in adults?

Background:Although increasing salt intake is associated with greater odds of obesity, little is known about its relationship with body fat. We investigated the relation of urinary sodium (UNa) with obesity indices, including Clínica Universidad de Navarra–Body Adiposity Estimator (CUN-BAE), a body shape index (ABSI), body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR).Materials and Methods:A total of 508 free-living adults aged ≥ 19 years were selected through stratified multistage random method as a representative of general population from central parts of Iran and were included in this cross-sectional study. Dietary sodium intake was measured using 24-h UNa (24-UNa) excretion. Weight, height, and WC were measured using standard protocols and calibrated equipment and used to measure obesity indicators, including BMI, WHtR, ABSI, and CUN-BAE. Adjusted univariate multiple logistic regression was used to assess the risk of having greater obesity measures across the tertiles of 24-UNa.Results:Individuals in the top tertile of 24-UNa in comparison with those in the first tertile had greater body weight (72.02 ± 1.00 vs. 66.02 ± 0.89 kg; P < 0.0001), BMI (26.14 ± 0.33 vs. 24.82 ± 0.29 kg/m2; P = 0.007), and CUN-BAE (29.89 ± 0.42 vs. 28.38 ± 0.78; P = 0.036). There was a trend toward an increment in WC by increasing sodium intake (P = 0.073). After controlling for potential confounders, individuals with greater sodium consumption had greater chance for overweight (odds ratio [OR]: 1.004, 95% confidence interval [CI]: 1.001–1.007; P = 0.015), abdominal obesity (OR: 1.004, 95% CI: 1.00–1.008; P = 0.031), and more body fat (OR: 1.007, 95% CI: 1.003–1.01; P = 0.001). No significant association was found for sodium and WHtR and ABSI.Conclusion:Greater 24-UNa excretion was associated with greater means of body weight, BMI, WC, and CUN-BAE. Although changes in obesity indices per each additional 24-UNa excretion were small, our findings are relevant because of the rising obesity epidemic.

The Usefulness of Anthropometric Indices to Identify the Risk of Metabolic Syndrome.

Despite several papers having been published on the association between adiposity and the risk of metabolic syndrome (MetS), it is still difficult to determine unambiguously which of the indices of nutritional status is the best to identify MetS. The aim of this study was to analyze the ability of six anthropometric indices to identify MetS in the Polish population. The highest odds ratios for the occurrence of MetS, according to International Diabetes Federation (IDF), were noted for the following indices: waist-to-height ratio (WHtR, OR = 24.87) and Clínica Universidad de Navarra-body adiposity estimator (CUN-BAE, OR = 17.47) in men and WHtR (OR = 25.61) and body roundness index (BRI, OR = 16.44) in women. The highest odds ratios for the modified definition of MetS (without waist circumference) were found for the following indices: WHtR (OR = 7.32), BRI (OR = 6.57), and CUN-BAE (OR = 6.12) in women and CUN-BAE (OR = 5.83), WHtR (OR = 5.70), and body mass index (BMI, OR = 5.65) in men (p < 0.001 for all). According to the Receiver Operating Characteristic (ROC) analyses conducted for the identification of MetS, defined in accordance with IDF, the largest areas under the curve (AUCs) in men were observed for WHtR and CUN-BAE indices, whereas in women, they were observed for WHtR and BRI. In the analysis carried out for the identification of MetS (according to modified definition, without waist circumference), the AUCs were larger for WHtR and BRI in women, while in men, they were larger for CUN-BAE, BMI, and WHtR. BMI was also characterized by a relatively strong discriminatory power in identifying individuals with MetS. An optimal cut-off point for MetS, in accordance with the conventional definition, for both sexes was the value of BMI = 27.2 kg/m2. The weakest predictor of the syndrome was the ABSI (a body shape index) indicator. The most useful anthropometric indicator for the identification of MetS, both in men and in women in the Polish population, was WHtR. The optimal cut-off points for WHtR equaled 0.56 in men and 0.54 in women.

Blood pressure and body fat percent in women with NMOSD.

BackgroundHypertension is a prevalent and impactful comorbid condition among patients with multiple sclerosis (MS). High level of body mass index (BMI) is associated with the risk and poor outcomes of neuromyelitis optica spectrum disorder (NMOSD) in women. However, the clinical implication of blood pressure (BP) and body fat percent (BF%) based on the Clínica Universidad de Navarra‐Body Adiposity Estimator (CUN‐BAE) in NMOSD has not been investigated thus far.MethodsCase data were collected from 47 NMOSD and 28 MS patients at acute phase, 21 NMOSD and 25 MS patients at stable phase, and 68 age‐ and sex‐matched HCs. Four BP measures including systolic BP (SBP), diastolic BP (DBP), pulse pressure (PP), and mean arterial pressure (MAP); BMI; and BF% between NMOSD, MS, and healthy controls were determined.ResultsComparing NMOSD patients with MS patients, the former have significantly higher SBP (p < 0.001), DBP (p < 0.001), PP (p < 0.001), MAP (p < 0.001), BF% (p = 0.001), and BMI (p < 0.001) levels at acute phase after adjusting for age. Acute myelitis (OR 3.719, 95% CI 1.110–12.453) is more likely to occur in NMOSD patients with high BF% (≥30%) at acute phase. BF% was negatively correlated with 1/AQP4 titer in NMOSD at acute phase (r = −0.522, p = 0.004).ConclusionsWomen with NMOSD are probably more prone to have an increased BP and fat mass compared to MS.

Utility of the Z-score of log-transformed A Body Shape Index (LBSIZ) in the assessment for sarcopenic obesity and cardiovascular disease risk in the United States

Body mass index (BMI) has limited accuracy for predicting cardiovascular diseases (CVD) and is not capable of identifying sarcopenic obesity, the combination of sarcopenia (an age-associated decline in muscle mass and physical function) and obesity. To overcome this, the z-score of the log-transformed A Body Shape Index (LBSIZ) was recently introduced as a measure of obesity using waist circumference, height, and weight. We aimed to investigate the association of LBSIZ with sarcopenic obesity and CVD, and propose appropriate cut-off values using the National Health and Nutrition Examination Survey 1999–2016 data. Of 92,062 participants, 40,468 adults (≥20 years) were included. Overall area under curve (AUC) of LBSIZ was 0.735 (95% confidence interval [CI]: 0.716–0.754) for sarcopenic obesity, and 0.695 (95% CI: 0.687–0.703) for CVD. The subgroup analysis of ethnicity/race showed similar results. Waist circumference (WC), BMI, conicity index, body roundness index (BRI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), new BMI, and waist to height ratio (WHtR) showed a negative association with sarcopenic obesity, while LBSIZ and conicity index showed a positive association. The AUC of LBSIZ was significantly higher for sarcopenic obesity than that of conicity index (p < 0.001). The AUC of LBSIZ was significantly higher for CVD than those of parameters including WC, BMI, BRI, CUN-BAE, new BMI, and WHtR (p < 0.001). The AUC for conicity index alone was comparable to that of LBSIZ for CVD. Overall LBSIZ cut-off was 0.35 for both sarcopenic obesity (sensitivity, 65.3%; specificity, 71.5%) and CVD (sensitivity, 63.3%; specificity, 66.6%). These results may be useful not only to identify sarcopenic obesity, but also to conduct CVD risk assessment in the clinical setting.

Anthropometric Indicators of Adiposity Related to Body Weight and Body Shape as Cardiometabolic Risk Predictors in British Young Adults: Superiority of Waist-to-Height Ratio.

Frequently reported poor dietary habits of young adults increase their risk of metabolic syndrome (MetS). Excess adiposity is the most established predictor of MetS, and numerous anthropometric measures have been proposed as proxy indicators of adiposity. We aimed to assess prevalence of MetS in young adult population and to make comparison between weight- and shape-oriented measures of adiposity to identify the best index in association with measured body fat and as a risk predictor for MetS. Healthy males and females aged 18–25 years from the Northwest of England were recruited using convenience sampling (n=550). As part of the assessment of the overall health of young adults, the biochemical variables and adiposity measures BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), new BMI, Body Adiposity Index (BAI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), and A Body Shape Index (ABSI) were assessed. Linear regression analysis was used to investigate the association between the proxy indices of adiposity and measured percentage body fat. The odds ratio with 95% confidence interval was used to investigate the relationship between cardiometabolic (CM) risk factors and proxy measures of adiposity. The discriminatory power of these measures for diagnosis of MetS was investigated using area under the receiver operating characteristic curve. Body weight-related indicators of adiposity, particularly CUN-BAE, had stronger association with measured body fat compared with body shape-related indices. In relation with MetS, body shape-related indices, particularly elevated WC and WHtR, had stronger associations with CM risk compared with body weight-related measures. Amongst all indices, the best predictor for CM risk was WHtR, while ABSI had the weakest correlation with body fat, MetS, and CM risk. Indices directly associated with WC and specifically WHtR had greater diagnostic power in detection of CM risk in young adults.

Net contribution and predictive ability of the CUN-BAE body fatness index in relation to cardiometabolic conditions

BackgroundThe CUN-BAE (Clínica Universidad de Navarra-Body adiposity estimator) index is an anthropometric index based on age, sex and body mass index (BMI) for a refined prediction of body fatness in adults. CUN-BAE may help detect metabolically unhealthy individuals with otherwise normal weight according to BMI or waist circumference (WC). The aim of this study was to evaluate whether CUN-BAE, independent of its components (BMI, age and sex), was associated with cardiometabolic conditions including arterial hypertension, diabetes mellitus and metabolic syndrome (MetS).MethodsThe ENRICA study was based on a cross-sectional sample of non-institutionalized men and women representative of the adult Spanish population. Body weight, height, and WC were measured in all participants. The residual of CUN-BAE (rCUN-BAE), i.e. the part of the index not explained by its components, was calculated. The associations of CUN-BAE, rCUN-BAE, BMI and WC with hypertension, diabetes and MetS were analysed by multivariate logistic regression, and the Akaike information criterion (AIC) was calculated.ResultsThe sample included 12,122 individuals. rCUN-BAE was associated with hypertension (OR 1.14, 95% CI 1.07–1.21) and MetS (OR 1.48, 1.37–1.60), but not with diabetes (OR 1.05, 0.94–1.16). In subjects with a BMI < 25 kg/m2, CUN-BAE was significantly associated with all three outcome variables. CUN-BAE was more strongly associated with the cardiometabolic conditions than BMI and WC and fit similar AICs.ConclusionsThe CUN-BAE index for body fatness was positively associated with hypertension, diabetes and MetS in adults independent of BMI or WC. CUN-BAE may help to identify individuals with cardiometabolic conditions beyond BMI, but this needs to be confirmed in prospective settings.

Assessing Traditional and Novel Indices of Adiposity as Risk Predictors for Metabolic Syndrome in British Young Adults

Background: Frequently reported poor dietary habits of young adults increases their risk of metabolic syndrome (MetS). Excess adiposity is the most established predictor of MetS and numerous anthropometric measures have been proposed as proxy indicators of adiposity. We aimed to make a comparison between traditional and novel indices of adiposity to identify the best index in association with measured body fat and as Cardiometabolic (CM) risk predictor for MetS.Methods: 550 adults aged 18–25 years were recruited in a cross-sectional study. Biochemical variables and adiposity indices including BMI, waist circumference (WC), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), new BMI, Body Adiposity Index (BAI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) and A Body Shape Index (ABSI)) were measured. Regression analysis, the odds ratio and the area under the receiver operating characteristic curve were used to analyse the findings.Results: Novel indices of adiposity, particularly CUN-BAE, had stronger correlation with measured body fat compared with traditional indices. In relation with MetS, traditional indices, particularly elevated WC and WHtR, had stronger associations with CM risk compared with novel indices. Amongst novel indices, the best predictor for MetS was CUN-BAE, whereas the best predictor for at least one risk factor or at least two risk factors of CM conditions was new BMI. ABSI had the lowest correlation with body fat, MetS and CM risk.Conclusion: Despite higher correlation between CUN-BAE and body fat, WC and particularly WHtR had greater diagnostic power in detection of CM risk and MetS in young adults.

The relation of CUN-BAE index and BMI with body fat, cardiovascular events and diabetes during a 6-year follow-up: the Hordaland Health Study.

ObjectiveWe compared Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) and body mass index (BMI) as correlates of body fat percent (BF%) and the association with future risk of cardiovascular disease (CVD) and type 2 diabetes in a Caucasian population.MethodsWe used data from 6796 individuals (born 1925–27 and 1950–52) from the Hordaland Health Study, a prospective cohort study in Norway. The study was conducted in 1992–1993 and 1997–1999. Cross-sectional analyses were conducted with data from 1997/99, including BF% measured by dual-energy X-ray absorptiometry. Longitudinal analyses included BMI and CUN-BAE calculated in 1992/93, and self-reported information on CVD events and diabetes in 1997/99.ResultsThe correlation between CUN-BAE and BF% (r=0.88) was stronger than between BMI and BF% (r=0.56). In sex-stratified analyses, CUN-BAE and BMI correlated similarly with BF% in men (r=0.77 and r=0.76, respectively) and women (r=0.82 and r=0.81, respectively). In longitudinal analyses, the odds ratio (per 1 SD increase) of CVD and type 2 diabetes was higher for BMI (ORCVD =1.23 [95% CI: 1.11–1.36]; ORdiabetes =2.11 [1.82–2.45]) than for CUN-BAE (ORCVD =1.15 [1.04–1.27]; ORdiabetes =2.06 [1.72–2.47]) in the total population. In sex-stratified analyses, CUN-BAE showed higher CVD and diabetes risk than BMI: in men BMI ORCVD =1.22 (1.04–1.44), ORdiabetes =2.13 (1.64–2.83); CUN-BAE ORCVD =1.93 (1.54–2.43), ORdiabetes =4.33 (2.80–6.71); and in women BMI ORCVD =1.22 (1.07–1.39), ORdiabetes =2.11 (1.76–2.53); CUN-BAE ORCVD =2.06 (1.69–2.51), ORdiabetes =5.45 (3.87–7.67).ConclusionCUN-BAE is more strongly associated with future risk of type 2 diabetes and CVD compared with BMI in analysis stratified by sex. As a measure of adiposity in men and women separately, CUN-BAE has no advantage over BMI, except when the value of estimated BF% itself is of interest.

The influence of body composition on the N-terminal pro-B-type natriuretic peptide level and its prognostic performance in patients with acute coronary syndrome: a cohort study.

BackgroundWhether body composition is associated with the N-terminal pro-B-type natriuretic peptide (NT-proBNP) level and its prognostic performance in acute coronary syndrome (ACS) remains unknown. We aimed to investigate the influence of body composition on the NT-proBNP level and its prognostic performance among ACS patients.MethodsIn total, 1623 ACS patients with NT-proBNP data were enrolled. Percent body fat and lean mass index were estimated using the Clínica Universidad de Navarra—Body Adiposity Estimator equation. Patients were divided into three groups according to the tertiles of sex-specific body mass index, percent body fat, or lean mass index. The endpoints were death from any cause and cardiovascular death.ResultsBody mass index was inversely correlated with NT-proBNP levels (β = −0.036, P = 0.003). Lean mass index, but not percent body fat, was inversely associated with NT-proBNP levels (β of lean mass index = −0.692, P = 0.002). During a median follow-up of 23 months, 161 all-cause deaths occurred, and of these, 93 (57.8 %) were attributed to cardiovascular causes. Multivariate Cox analysis showed that the NT-proBNP level independently predicted all-cause mortality or cardiovascular death in the lower body mass index, lean mass index, and percent body fat groups. However, the prognostic performance of NT-proBNP was attenuated in patients with high body mass index, lean mass index, and percent body fat. In the subgroup of patients with diabetes, inverse associations between NT-proBNP levels and body mass index or body composition were not observed. In addition, the negative influence of high body mass index and body composition on the prognostic performance of the NT-proBNP level appeared to be attenuated.ConclusionsBody mass index and lean mass index, but not percent body fat, are inversely associated with NT-proBNP levels. The prognostic performance of this biomarker may be compromised in patients with high body mass index, percent body fat, or lean mass index. Additionally, the influence of body composition on the NT-proBNP level and its prognostic performance might be attenuated in diabetic patients with ACS.