Simple Anthropometric Parameters Research Articles

Feasibility of utilizing pectoral muscle thickness as a predictor for one repetition maximum bench press in trained men

ABSTRACT The aim of the present study was to develop prediction equations for the one repetition maximum (1RM) Bench Press (BP) in resistance-trained men based on muscle thickness and simple anthropometric parameters. 83 men (age: 26.2 ± 4.9y, height: 175.9 ± 6.3 cm, body mass: 82.9 ± 11.2 kg) participated in the present investigation and were assessed for anthropometric measurements and for muscle thickness of pectoral major (MTP). Then, the participants performed the 1RM BP test. A very large correlation was detected between MTP and 1RM BP (r = 0.83–0.88). A prediction equation based on MTP and body mass (EQ1) was developed: 1RM BP = –15.2460565 + (32.0751388 * MTP) + (0.6364405 * Body Weight) with R2 = 0.79. Another prediction equation was developed using MTP only (EQ2): 1RM BP = 20.36167 + (39.36532 * MTP) with R2 = 0.69. Bland-Altman analysis and paired sample t test provided insufficient evidence to support differences between the predicted and the measured 1RM BP in both the equations (p > 0.05). This study showed that both MTP based (EQ2) and MTP and body mass based (EQ1) methods can be used to predict 1RM BP and may represent important tools for the evaluation of maximal strength. These findings support the potential use of non-performance-based parameters to predict maximal dynamic strength in trained individuals.

Novel anthropometric parameters in the adult population with prediabetes.

Although it is assumed that novel-derived anthropometric indices can better reflect cardiometabolic risk than traditional ones, the results are conflicting. Previous studies have mainly focused on patients with type 2 diabetes mellitus. However, studies conducted on populations with prediabetes are scarce. The present study aimed to examine the potential relationship between prediabetes and novel anthropometric parameters [that is, cardiometabolic index (CMI), visceral adiposity index (VAI), lipid accumulation product index (LAP), body roundness index (BRI), and body adiposity index (BAI)] and traditional parameters [that is, waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR)] in adults with prediabetes. This case-control cross-sectional study included 177 patients with prediabetes and 609 control subjects. Biochemical and simple anthropometric parameters were measured (WC, HC, body weight, and height), whereas the other parameters were calculated. WC, CMI, VAI, and LAP independently correlated with prediabetes. Principal component analysis (PCA) was used to extract several factors that correlated with prediabetes. Significant predictive capability was demonstrated for non-traditional anthropometric/lipid-related factors and WHipR-related factors for prediabetes (OR=1.334 and OR=1.202, respectively). However, only non-traditional anthropometric/lipid-related factors (i.e., VAI, CMI, and LAP) demonstrated an independent significant positive relationship with prediabetes in multivariate binary regression analysis. CMI, VAI, and LAP could be superior to BAI, BRI, and conventional anthropometric parameters for discriminating patients with prediabetes in the adult population. Prospective trials are needed to confirm our results.

Effective and clinically relevant optimisation of cushioning stiffness to maximise the offloading capacity of diabetic footwear

IntroductionOptimising the cushioning stiffness of diabetic footwear/orthoses can significantly enhance their offloading capacity. This study explores whether optimum cushioning stiffness can be predicted using simple demographic and anthropometric parameters. MethodsSixty-nine adults with diabetes and loss of protective sensation in their feet were recruited for this cross-sectional observational study. In-shoe plantar pressure was measured using Pedar® for a neutral diabetic shoe (baseline) and after adding cushioning footbeds of varying stiffness. The cushioning stiffness that achieved maximum offloading was identified for each participant. The link between optimum cushioning stiffness and plantar loading or demographic/anthropometric parameters was assessed using multinomial regression. ResultsPeople with higher baseline plantar loading required stiffer cushioning materials for maximum offloading. Using sex, age, weight, height, and shoe-size as covariates correctly predicted the cushioning stiffness that minimised peak pressure across the entire foot, or specifically in the metatarsal heads, midfoot and heel regions in 70%, 72%, 83% and 66% of participants respectively. ConclusionsIncreased plantar loading is associated with the need for stiffer cushioning materials for maximum offloading. Patient-specific optimum cushioning stiffness can be predicted using five simple demographic/anthropometric parameters. These results open the way for methods to optimise cushioning stiffness as part of clinical practice.

Evaluation of the Applicability of Artificial Intelligence for the Prediction of Obstructive Sleep Apnoea

Background Due to the large number of undiagnosed obstructive sleep apnoea (OSA) patients, our aim was to investigate the applicability of artificial intelligence (AI) in preliminary screening, based on simple anthropometric, demographic and questionnaire parameters. Methods Based on the results of the polysomnography performed, the 100 patients in the study were grouped as follows: non-OSA, mild OSA and moderately severe–severe OSA. Anthropometric measurements were performed, and the Berlin and Epworth questionnaires were completed. Results OSA prediction based on body mass index (BMI), gender and age was accurate in 81% of cases. With the completion of the questionnaires, accuracy rose to 83%. The Epworth questionnaire alone yielded a correct OSA prediction in 75%, while the Berlin questionnaire was correct in 62% of all cases. The best results for categorization by severity were obtained by combining BMI, gender and age parameters, together with responses to the questionnaires (71%). Supplemented with neck circumference, this result improves slightly (73%). Conclusion Based on the results, it can be concluded that OSA can be effectively and easily categorized using AI by combining anthropometric and demographic parameters, as well as questionnaire data.

Visceral Adiposity Index in Type 2 Diabetes Mellitus and Its Risk for Cardiovascular Disease

Back ground: The Visceral Adiposity Index (VAI) is an empirical mathematical model, genderspecific, based on simple anthropometric (BMI and WC) and functional parameters (triglycerides (TG) and HDL cholesterol (HDL)), and indicative of fat distribution and function. Methods: This is a Cross sectional study. It was carried out in the department of Biochemistry, BSMMU from July 2015- June 2017. Type 2 Diabetes Mellitus patients attending in outpatient Department of Endocrinology and Metabolism, BSMMU were our study population. The cutoff value for VAI was considered as 3. Results: We enrolled 105 participants in this study. Among them 41 were male and 64 were female. There was significant difference between male and female in terms of height, weight and BMI. Male had greater height (p =0.01) and weight (p =0.01) than female. Female had greater BMI (p =0.01) than male. The majority of male and female scored above the cut off value of VAI which were 63.4% and 59.4% respectively. The mean value of biochemical parameters TG, FBG and HbA1c were significantly different on the basis of cutoff point of VAI (d”3 and > 3). There is increased TG, FBG and HbA1c and decreased HDL-C with the cut off value more than 3 in VAI. We found significant strong positive correlation with HbA1c with FRS (r= +.631, p=<0.001) and VAI (r= +.596, p=<0.001) Conclusion: High Visceral Adiposity Index is associated with Type 2 diabetes mellitus and increased cardiovascular risk J Dhaka Med Coll. 2021; 29(1): 68-75

Body fat estimated by equations based on anthropometric parameters correlates with bioelectrical impedance in patients undergoing bariatric surgery

Introduction: predictive equations to estimate body fat based on simple anthropometric parameters are easy to use in the clinical practice. Objective: to evaluate the relationship between predictive equations based on anthropometric parameters and bioelectrical impedance to estimate body fat in individuals undergoing bariatric surgery. Methods: a prospective and longitudinal study carried out with individuals undergoing bariatric surgery. Body weight, body mass index, waist circumference and body fat percentage estimated by anthropometric parameters and by impedance were evaluated at three moments, one month before, two and six months after surgery. Data were analyzed by one-way ANOVA for repeated measures with Holm-Sidak´s post hoc or Friedman test with Tukey´s post hoc, and Pearson or Spearman correlations, according to data distribution. Significance level adopted 5%. Results: twenty-five subjects composed the final sample. All anthropometric parameters reduced significantly over time (p<0.001). Except for Lean et al equation before surgery, the body fat percentage estimated by other formulas showed a strong correlation with impedance in all moments, with the highest correlation strength observed in Gómez-Ambrosi et al. equation. Conclusion: in the present study, the equations used showed a good correlation with bioelectrical impedance, and the Gómez-Ambrosi et al. equation as a better option to the use of bioimpedance to assess changes in body fat percentage of patients undergoing bariatric surgery for the treatment of severe obesity.

Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population.

ObjectiveNon-alcoholic fatty liver disease (NAFLD) is one of the leading causes of chronic liver disease. The controlled attenuation parameter (CAP) obtained by FibroScan reflects the level of liver steatosis in patients with obesity. Our study aimed to construct a simple equation to predict the CAP, to facilitate the screening and monitoring of patients at high risk for NAFLD.MethodsA total of 272 subjects were randomly divided into derivation and validation cohorts at a ratio of 1:2. The derivation set was used for constructing a multiple linear regression model; the validation set was used to verify the validity of the model.ResultsSeveral variables strongly correlated with the CAP were used to construct the following equation for predicting CAP values:CAP1 = 2.4 × BMI + 10.5 × TG+ 3.6 × NC + 10.3 × CP +31.0, where BMI is body mass index, TG is triglyceride, NC is neck circumference and CP is C-peptide. The CAP1 model had an R2 of 0.764 and adjusted R2 of 0.753. It was then simplified to derive CAP2 included only simple anthropometric parameters: CAP2 = 3.5 × BMI + 4.2 × NC + 20.3 (R2 = 0.696, adjusted R2 = 0.689). The data were well fitted by both models. In the verification group, the predicted (CAP1 and CAP2) values were compared to the actual CAP values. For the CAP1 equation, R2 = 0.653, adjusted R2 = 0.651. For the CAP2 equation, R2 = 0.625, adjusted R2 = 0.623. The intra-class correlation coefficient (ICC) values were 0.781 for CAP1 and 0.716 for CAP2 (p < 0.001). The actual CAP and the predicted CAP also showed good agreement in Bland-Altman plot.ConclusionThe equations for predicting the CAP value comprise easily accessible variables, and showed good stability and predictive power. Thus, they can be used as simple surrogate tools for early screening and follow-up of NAFLD in the Chinese population.

Blood Lead Level Is Associated with Visceral Adipose Dysfunction in Patients with Type 2 Diabetes.

We aimed to explore whether an elevated blood lead level (BLL) is associated with visceral adipose dysfunction in patients with type 2 diabetes mellitus (T2DM). Four thousand one hundred and fourteen diabetic participants were enrolled from seven communities in Shanghai in 2018 in the cross-sectional METAL study. BLL was measured by graphite furnace atomic absorption spectrometry. Visceral adiposity index (VAI) and lipid accumulation product (LAP)were calculated by simple anthropometric and biochemical parameters. We found that medians (IQR) of BLL were 26.0μg/L (18.0-37.0) for men and 25.0μg/L (18.0-35.0) for women, respectively. In men, each doubling of BLL was associated with a 2.0% higher VAI (95% CI, 0.6 to 3.5%) and 1.8% higher LAP (95% CI, 0.2 to 3.3%) after full adjustment. Using the lowest BLL quartile as the referent group, significant positive trends were observed for BLL with VAI and LAP. In women, each doubling of BLL was associated with a 1.9% higher LAP (95% CI, 0.6 to 3.1%). Additionally, there was a marginally significant positive association between BLL and VAI, either using log2-transformed concentrations as continuous variables or categorized in quartiles. In conclusion, lead exposure is associated with visceral adipose dysfunction in patients with T2DM. Further prospective studies are warranted to confirm our findings.

Factors Related to Metabolic Syndrome Development and Recovery in Chinese Adults: A Prospective Longitudinal Study

ObjectiveThis study was a prospective assessment of the epidemiological characteristics of metabolic syndrome (MetS) in cities in Northeast China. We explored the factors that affect the occurrence and outcome of MetS according to sex.Design and MethodsThis was a longitudinal survey assessing MetS status among 750 urban community residents in China. At baseline, the intra-abdominal fat area was measured by MRI, simple anthropometric parameters (body mass index (BMI), waist circumference (WC), etc.) were used to evaluate fat distribution; blood pressure and blood lipid profile were measured; an oral glucose tolerance test (OGTT) was used to detect blood glucose; questionnaires were used to investigate lifestyles. Follow-up was conducted after 1.5 years (follow-up rate was 66.93%) to analyze the incidence of MetS and the influencing factors of MetS outcomes according to sex.ResultsThe 1.5-year cumulative incidence of MetS in the survey area was 25.40%. Men with visceral obesity were more likely to develop MetS than those with subcutaneous obesity (OR=9.778, p<0.05). Increased BMI (OR=1.379) and blood uric acid (BUA)>416 mmol/L (OR=2.318) were associated with the occurrence of MetS in men (all p<0.05). At the initial visit, BUA>356.9 mmol/L (OR=3.538), increased BMI (OR=1.212), and increased HbA1c (OR=2.577) were associated with the occurrence of MetS in women (all p<0.05). After 1.5 years, 25.37% of MetS patients no longer had MetS. Elevated diastolic blood pressure (DBP) (OR=1.097) and increased visceral fat (OR=1.023) at the initial visit made men with MetS less likely to recover from MetS (all p<0.05). Higher High-density lipoprotein cholesterol (HDL-C) at the initial visit made women with MetS more likely to recover from MetS (β: -3.509, OR=0.003, p<0.05).ConclusionThere are different risk factors for MetS in different genders. Hyperuricemia is a risk factor for the onset of MetS in both men and women.

Positive association between body fat percentage and hyperuricemia in patients with hypertension: The China H-type hypertension registry study

Background and aimsThe relationship between the body fat percentage (BFP) and hyperuricemia is still unknown in different gender subjects. The purpose of this study was to determine the magnitude of the association between the BFP and the presence of hyperuricemia in the sex-specific group among hypertensive patients. Methods and resultsWe conducted a cross-sectional study enrolling 14,234 hypertensive participates from the Chinese Hypertension Registry Study. Body fat percentage (BFP) was calculated by simple anthropometric parameters. Hyperuricemia was defined as serum uric acid (SUA) level 420 umol/L in men and 360 umol/L in women. The mean BFP was 24.5% in men and 37.1% in women. Multiple logistic analyses showed that the relationship between BFP with the risk of hyperuricemia in a dose-dependent manner among both men (odds ratio [OR] 1.07, 95% CI 1.06, 1.09) and women (OR 1.08, 95% CI 1.06, 1.09) in the fully adjusted model. Subgroup analyses showed the positive association between BFP and the risk of hyperuricemia was consistent in all stratification subgroups (all P for interaction >0.05). ConclusionFor patients with hypertension, BFP was positively associated with an increased risk of hyperuricemia among both men and women.

Novel artificial neural network and linear regression based equation for estimating visceral adipose tissue volume.

There is a growing interest in fast and reliable assessment of abdominal visceral adipose tissue (VAT) volume for risk stratification of metabolic disorders. However, imaging based measurement of VAT is costly and limited by scanner availability. Therefore, we aimed to develop equations to estimate abdominal VAT volume from simple anthropometric parameters and to assess whether linear regression based equations differed in performance from artificial neural network (ANN) based equations. MRI-measured abdominal VAT volumes and anthropometric parameters of 5772 subjects (White ethnicity, age 45-76 years, 52.7% females) were obtained from the UK Biobank. Subjects were divided into the derivation sample (n=5195) and the validation sample (n=577). Basic models (age, sex, height, weight) and expanded models (basic model+waist circumference and hip circumference) were constructed from the derivation sample by linear regression and ANN respectively. Performance of the linear regression and ANN based equations in the validation sample were compared and estimating accuracies were evaluated by receiver-operating characteristic curves (ROC). The basic and expanded equations based on linear regression and ANN demonstrated the adjusted coefficient of determination (R2) ranging from 0.71 to 0.78, with bias ranging from less than 0.001L-0.07L in comparison with MRI-measured VAT. Both basic and expanded ANN based equations demonstrated slightly higher adjusted R2 and lower error measurements than linear regression equations. However, no statistical difference was found between linear regression equations and their ANN based counterparts in ROC analysis. Both linear regression and ANN based expanded equations presented higher estimating accuracies (76.9%-90.1%) than the basic equations (74.5%-87.5%) in ROC analysis. We present equations based on linear regression and artificial neural networks to estimate abdominal VAT volume by simple anthropometric parameters for middle-aged and elderly White population. These equations can be used to estimate VAT volume in general practice as well as population-based studies.

Visceral adipose accumulation increased the risk of hyperuricemia among middle-aged and elderly adults: a population-based study

BackgroundThe role of body fat distribution in uric acid metabolism is still ambiguity. We aimed to investigate the independent contribution of visceral adipose measured by visceral adiposity index and lipid accumulation product and liver fat assessed by fatty liver index to the risk of hyperuricemia.MethodsWe conducted a cross-sectional study involving 1284 participants aged ≥ 40 years old recruited from communities in Zhonglou district, Changzhou. Each participant completed a standard questionnaire, and provided blood samples for biochemical measurements. Visceral adiposity index, fatty liver index and lipid accumulation product were calculated by simple anthropometric and functional parameters. Hyperuricemia was defined as serum uric acid ≥ 420 μmol/l for males and ≥ 360 μmol/l for females.ResultsThe prevalence of hyperuricemia was 15.9% and gradually increased across tertiles of adiposity-based indices. The visceral adipose-based measurements (visceral adiposity index, fatty liver index, lipid accumulation product) had better power to discriminate hyperuricemia than body mass index (BMI), waist circumference and neck circumference, and visceral adiposity index exhibited the highest power, with the area under the receiver operating characteristics curve (AUROC) of 0.662 (0.636–0.688). Multivariate logistic regression found 1.49-fold, 2.21-fold and 2.12-fold increased risk of hyperuricemia with 1-unit increment of visceral adiposity index, fatty liver index, and lipid accumulation product, respectively. Compared to tertile 1, the odds ratios of hyperuricemia for the second tertile and the third tertile of visceral adiposity index were 1.57 (1.00–2.50) and 3.11 (1.96–4.94), those of fatty liver index were 1.64 (1.05–2.68) and 3.58 (1.94–6.01), and those of lipid accumulation product were 1.93 (1.19–3.15) and 3.53 (2.05–6.09), respectively. However, no significant associations of BMI, waist circumference and neck circumference with hyperuricemia were observed.ConclusionsVisceral adipose accumulation increased the risk of hyperuricemia, independently of BMI, waist circumference and neck circumference, among middle-aged and elderly Chinese adults.

The Comparison of Simple Anthropometric and Biochemical Parameters for Predicting Liver Steatosis in Obese Balinese Young Women.

BACKGROUND:The prevalence of non-alcoholic fatty liver disease (NAFLD) is increasing globally. Early identification of liver steatosis (LS) status is critical to prevent the development of NAFLD into non-alcoholic steatohepatitis (NASH) fibrosis.AIM:This study aimed at exploring the validity of simple anthropometric and biochemical parameters to predict LS in young obese women.MATERIALS AND METHODS:This is a cross-sectional study involving 132 young obese women. We collected the data of measured waist circumference (WC), body mass index (BMI), serum triglyceride (TG), and gamma-glutamyltransferase (GGT). The lipid accumulation product (LAP) was designed from TG and WC variables. Fatty liver index (FLI) was calculated from TG, BMI, WC, and GGT variables. LS status was measured using ultrasonography assay. Statistical significance was set at p < 0.05.RESULTS:A positive correlation was found between BMI, WC, TG, GGT, LAP, FLI, and LS (p = 0.001). We found that BMI is a better predictor for LS to WC. Our multiple linear regression analysis revealed that BMI, GGT, and TG could predict 41.4% of LS. The validity (specificity, sensitivity, and odds ratio) of simple body fat parameters in predicting LS were as follows: BMI ≥ 30 kg/m2 (69.6%, 74.4%, and 6.21), WC ≥ 90 cm (67.4%, 70.0%, and 4.28), TG ≥ 100 mg/dL (70.6%, 70.0%, and 5.62) and GGT ≥ 20 μg/L (69.6%, 77.5%, and 7.87), as well as LAP ≥ 30 (82.6%, 70.0%, and 11.1), and FLI ≥ 2.5 (79.3%, 72.5%, and 10.1), significantly.CONCLUSION:Simple anthropometric and biochemical parameters (BMI, WC, and TG, GGT), are appropriately predicting LS as well as LAP, and FLI among obese Balinese young women.

Visceral adiposity index is associated with increased urinary albumin excretion: A population-based study

The effects of visceral fat accumulation on the renal damage have drawn much attention. We aimed to investigate the possible relationship between visceral adiposity and albuminuria. We included information from a population-based study in 9473 subjects aged 40 years or older. As a novel and valid indicator for visceral adipose function, visceral adiposity index (VAI) was determined by gender-specific equations and calculated using simple anthropometric and functional parameters. Increased urinary albumin excretion was defined as albumin-to-creatinine ratio (ACR) 30mg/g or greater. The prevalence rate of increased urinary albumin excretion was 6.6% in this population and gradually increased across VAI quartiles. Participants with higher VAI had elevated age, blood pressure, cholesterol, fasting insulin and decreased high density lipoprotein cholesterol and estimated glomerular filtration rate (eGFR) level. In multivariate logistic regression analysis, the adjusted odds ratios (ORs) of increased urinary albumin excretion for increasing VAI quartiles were 1.00 (reference), 1.29 (95% confidence intervals [CI] 0.94-1.76), 1.46 (95% CI 1.08-1.97) and 1.79 (95% CI 1.33-2.41). In subgroup analysis and after multiple adjustments, significant relation between VAI level and prevalent increased urinary albumin excretion was detected in women, younger subjects, non-obesity subjects, those without diabetes and those with eGFR ≥60ml/min per 1.73m2. Visceral fat accumulation evaluating by VAI is independently associated with increased urinary albumin excretion in middle-aged and elderly Chinese.

Simple Anthropometric Indices are Useful for Predicting Non-alcoholic Fatty Liver Disease [NAFLD] in Asian Indians

With the rising prevalence of obesity and metabolic syndrome, nonalcoholic fatty liver disease (NAFLD) has become the most common liver disorder in both developed and developing nations. Several studies on NAFLD have described waist circumference, a surrogate marker of visceral fat accumulation and waist height ratio as a better screening tool for NAFLD and metabolic syndrome than body mass index (BMI). We conducted this study to assess simple abdominal obesity indices as a predictor of NAFLD and determine the appropriate cut-off levels with reference to NAFLD. 1000 subjects with NAFLD detected ultrasonographically and 360 controls attending a Gastroenterology Clinic at Cuttack, Odisha were included in the study and subjected to detailed anthropometric measurements. The abdominal anthropometric cut offs were determined using ROC analysis. Statistical analysis was performed by using SPSS software version 16. All receiver operating curve (ROC) curves of waist circumference, waist-height ratio and BMI were significantly above the diagonal line. There were no significant differences in the area under the curve values among these abdominal obesity indices in each gender. The appropriate cut-off point of waist circumference in screening for NAFLD was 89cm for men and 84cm for women and the optimal cut-off point of waist-height ratio was 0.53 for men and 0.57 for women and the cut-off point of waist to hip ratio was 0.94 for men and 0.87 for women with very good sensitivity and specificity. The simple anthropometric parameters, such as BMI, waist circumference, waist-hip ratio and waist-height ratio are useful for predicting NAFLD in Indian adults. The anthropometry cut offs would be very useful in setting target points of life style modification and weight reduction. Besides, our study also clearly demonstrated that a simple assessment of BMI is as efficacious as other anthropometry parameters in predicting NAFLD.

Neck Circumference and Leg Length as Surrogate Markers of Coronary Artery Disease - Simplifying Cardiac Risk Stratification.

Coronary angiography is the gold standard for quantification of coronary atherosclerosis. But, being invasive, it has inherent complications. Hence, we examined the accuracy of prediction of coronary angiography using simple anthropometric indices. To identify a patient friendly method to predict coronary artery disease using simple anthropometric parameters, by testing their correlation with coronary artery disease severity scoring system. We conducted a cross-sectional study on patients undergoing elective coronary angiography. A total of 48 patients were included in the study. Neck circumference and leg length of the patients were noted. The severity of coronary atherosclerosis was quantified using Jenkin's scoring system. Mean and standard deviation for each continuous variable was calculated. The correlation between Jenkins' score, neck circumference and leg length was tested. The data analysis was done using IBM-SPSS software. Mean leg length among the study population was 88.70 cm (±2.51 cm) among males, 79.04 cm (±4.32 cm) among females and 83.66 cm (±3.26 cm) overall. Mean neck circumference was 36.87 cm (±4.37 cm) among males, 36.04 cm (±3.65 cm) among females and 36.44 cm (±3.99 cm) when combined together. There was no correlation of Jenkin's scores with leg length. But, there was significant correlation between Jenkin's scores and neck circumference. Neck circumference can be used as a simple and effective tool and is better than leg length for risk stratification of patients with coronary heart disease.

Applicability of video-based training program on inter- and intra-observer variation in common anthropometric parameters measurement in adults

Background: Measurement of simple anthropometric parameters (e.g., weight, height) helps in estimation of degree of obesity in clinical and outdoor settings. However, inter- and intra-observer variation in measurement may contribute to bias in measured parameters. These should be minimized to get reliable data for patient management and researches. Aim: The aim of the study was to find out inter- and intra-observer variation in measurement of common anthropometric parameters by fitness trainer and to check the applicability of a video-based training program on change in variation. Materials and Methods: Two observers measured weight, height, waist circumference (WC), and hip circumference (HC) in 32 adult males on two occasions in forenoon. After a video based training, observers measured same parameters in same sample on two occasions. Inter- and intra-observer variations were expressed in terms of technical error of measurement (TEM), %TEM, and reliability by coefficient of reliability (R). Results: Interobserver variation was higher than intraobserver variation in all measurements expressed in %TEM. Before the training, measurement of waist-to-hip ratio (WHR) showed highest %TEM (2.437) followed by HC (1.716 %TEM). Weight measurement showed lowest %TEM (0.075). After the training, all measurements showed a decrease in %TEM. Waist-to-hip ratio showed highest error (1.598%TEM) followed by HC (1.396%TEM). All measurements showed reliability coefficient >0.98 both before and after the training. Conclusion: In measurement of weight, height, WC, and HC, interobserver variation is higher than intraobserver variation. Variation in circumference measurement is more than length measurement. Simple video-based training program helps in lowering both inter- and intra-observer variation.

Subclinical Cushing’s Syndrome in women with adrenal incidentalomas is associated with adipose tissue dysfunction

Introduction. The visceral adiposity index (VAI) is a mathematical formula based on simple anthropometric and biochemical parameters and reflects the distribution and function of the adipose tissue.Aim: to investigate the possible association between the presence of subclinical Cushing’s syndrome (SCS) and VAI in patients with adrenal incidentalomas.Patients and methods. We studied 258 patients with adrenal incidentalomas. The diagnosis of SCS was based on a post-LDDST cortisol level ≥1.8 mg/dl combined with an abnormal result of at least one other test of the HPA axis, in the absence of clinical signs. The VAI index was calculated as following: Women VAI= [WC/36.58+(1.89×BMI)] ×(TG/0.81)×(1.52/HDL), Men VAI= [WC/39.68+(1.88×BMI)] ×(TG/1.03)×(1.31/HDL).Results. 122 patients were excluded from the analysis due to overt metabolic problems (8 with BMI&gt;39, 82 with metabolic syndrome and 34 with type 2 diabetes). Among 136 patients who were included in the analysis (42M/94W, 56.9±9.7 y), SCS was diagnosed in 24 (17.6%). Patients with SCS presented with significantly higher levels of insulin (12.4±4.6 vs 9.9±3.2 μIU/ml, p=0.036) and triglycerides (114±36 vs 97±34 mg/dl, p=0.023), larger size of tumors (3.26±0.88 vs 2.28±1.06 cm, p&lt;0.001) and higher calculated VAI (1.77±0.83 vs 1.39±0.69, p=0.045). Regression analysis revealed that the presence of SCS was positively associated with VAI [OR (95% CI) 1.888 (1.051–3.394), p=0.034] but when gender subgroup analysis followed, this was shown only in women [OR (95% CI) 2.284 (1.135–4.595), p=0.021]. Another important prognostic factor for the probability of SCS was the mass size [OR (95% CI) 2.237 (1.441–3.472), p&lt;0.001].Conclusion. SCS in women with adrenal incidentalomas is associated with adipose tissue dysfunction.

Anthropometry in cardio-metabolic risk assessment

High prevalence of obesity, as a major public health problem, is connected with chronic cardiovascular and metabolic diseases. That is why some simple anthropometric parameters were developed to estimate overweight and obesity, and in the primary screening of risk groups. In this field, body mass index (BMI) is the most frequent parameter, both in epidemiological research and in everyday practice. It is a part of the algorithm used in the early detection of overweight and obese persons. However, BMI does not provide any data on body composition. This is why it is particularly insufficient in estimating body mass in physically active persons and in athletes who are often overweight, with a higher proportion of lean body mass but without any excess fat, as well as in those with normal weight but lower than normal lean body mass and/ or gentle skeleton. Over the last few decades, attention has been especially directed to different body fat distribution in relation to chronic cardio-vascular and metabolic diseases. Waist circumference (WC) is the best anthropometric predictor of cardiovascular risk. It is considered an indirect parameter of visceral fat. WC and waist-to-hip ratio are good parameters showing body fat distribution and cardio-metabolic risk. Waist-to-height ratio is suggested by some authors to be an even better parameter of cardio-vascular risk and metabolic syndrome. Hypertriglyceridemia combined with increased WC is considered a marker of atherogenic metabolic risk. The paper also deals with procedures of body composition analysis. Anthropometric assessment of body composition analysis belongs to a group of simple and inexpensive procedures. Development of generalised equations for body density prediction introduced anthropometric methods in the analysis of body composition in everyday practice.

Reliability of anthropometric parameters in the prediction of the visceral fat area among adult women

Visceral fat accumulation is a risk factor for cardiometabolic diseases. Magnetic resonance imaging (MRI) and computed tomography (CT) provided the most accurate techniques of abdominal fat assessment, but these methods are very expensive. The aim of this study was to examine and compare the predictive ability of simple anthropometric parameters for visceral fat area (VFA) among adult women in different age and obesity status groups. The sample consisted of 133 adult women (aged 18-76 years). All subjects underwent anthropometric measurements. Body composition and VFA were determined with a multi-frequency bioimpedance analyzer (BIA). 16.9% of the younger women (age < 45) were obese with a body-mass index (BMI) > or = 30.0 kg/m2, and 23.2% of the older individuals (age > 45) had BMI > or = 30 kg/m2. After age and BMI adjustment, the best correlation was observed between VFA and waist circumference (WC) in younger women (R = 0.347, p = 0.002). In the case of the older women, the best correlation efficient values were for SAD (R = 0.560, p < 0.001) and hip circumference (R = 0.550, p < 0.001). The partial correlation coefficients were consistently higher for younger subjects with excessive fat accumulation (overweight & obese subgroup; individuals with WC > 80 cm) compared to women without obesity. Results of the multiple linear stepwise regression analyses showed the significance of age and BMI in prediction of VFA. In addition, hip circumference (HC) was one of the methods that best reflected VFA in older women independently from obesity status. Using single anthropometric parameters is not usually sufficient for predicting with good accuracy the VFA, but the convenient combination of these parameters could be a suitable way for the reliable prediction in Hungarian women.