Simple Anthropometric Research Articles

Waist-to-height ratio and body roundness index: superior predictors of insulin resistance in Chinese adults and take gender and age into consideration

Background and objectivesMetabolic disease has become a global health concern, and insulin resistance (IR) is a crucial underlying mechanism in various metabolic diseases. This study aims to compare the ability of seven anthropometric indicators in predicting IR in the Chinese population, and to find more sensitive and simple anthropometric indicator for early identification of IR.MethodsThis prospective cross-sectional study obtained participants’ medical history, anthropometric indicators, and serum samples from three hospitals in China. Various anthropometric indicators were calculated, including body mass index (BMI), Waist-to-hip ratio (WHR), waist-to-height ratio (WtHR), conicity index (CI), A Body Shape Index (ABSI), body roundness index (BRI), abdominal volume index (AVI). The evaluation of IR is performed using the homeostasis model assessment-insulin resistance (HOMA-IR). Logistic regression analysis examined the relationship between indicators and HOMA-IR. The ability of the anthropometric indicators to predict IR was analyzed using the receiver operating characteristic (ROC) curve. Additionally, a stratified analysis was performed to evaluate the ability of the indicators in different age and gender groups.ResultsThe study included 1,592 adult subjects, with 531 in the non-IR group and 1,061 in the IR group. After adjusting for confounding factors, the anthropometric indicators showed a positive correlation with IR in the general population and across different genders and age groups (OR > 1, p < 0.05), except for ABSI. In the ROC curve analysis, WtHR and BRI had the highest AUC values of 0.711 for detecting IR. The optimal cut-off value for WtHR to diagnose IR was 0.53, while for BRI, it was 4.00. In the gender-stratified and age-stratified analysis, BMI, WtHR, BRI, and AVI all had AUC values >0.700 in females and individuals below 60.ConclusionWtHR and BRI demonstrated a better ability to predict IR in the overall study population, making them preferred indicators for screening IR, and gender and age are important considerations. In the stratified analysis of different genders or age, BMI, WtHR, BRI, and AVI are also suitable for detecting IR in women or individuals under 60 years old in this study.Clinical trial registrationwww.chictr.org.cn, ChiCTR2100054654.

The waist-to-height ratio is a good predictor for insulin resistance in women with polycystic ovary syndrome

ObjectiveThis study aimed to explore the role of the waist-to-height ratio (WHtR) in assessing insulin resistance (IR) in patients with polycystic ovary syndrome (PCOS).Materials and methodsWe enrolled 882 PCOS-afflicted women in a cross-sectional analysis to evaluate the association of the WHtR with IR. Their demographic characteristics, anthropometric parameters, and fasting blood samples were collected and measured. Moreover, IR was evaluated by homeostatic model assessment of insulin resistance (HOMA-IR). We estimated the relationship between the WHtR and IR and the cut-off thresholds of the WHtR for IR using multivariable linear regression and logistic regression models, respectively.Result(s)The prevalence rate of IR was 51.9%. The patients with PCOS and IR displayed significantly increased values for body mass index (BMI), waist circumference (WC), WHtR, systolic blood pressure (SBP), diastolic blood pressure (DBP), free androgen index (FAI), HOMA-IR, total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein B (ApoB). However, the patients with PCOS and IR showed a reduction in estradiol (E2), luteinizing hormone (LH), LH/FSH ratio, sex hormone binding globulin (SHBG), and high-density lipoprotein (HDL-C) values than those without IR. Moreover, BMI (log-transformed), WC, and HOMA-IR (log-transformed) were positively correlated with the WHtR. When adjusting for potential confounding variables, the WHtR was significantly associated with HOMA-IR (log-transformed), with a standardized regression coefficient of 0.271. Furthermore, the WHtR was significantly associated with an increased risk of IR, with the adjusted odds ratio (OR) of 3.15 (WHtR multiplied by 10). Additionally, the WHtR helped to identify IR in women with PCOS with an optimal cut-off point of 0.519 (Youden index = 0.433).Conclusion(s)The WHtR had a positive association with IR in women with PCOS. Hence, we suggest that the WHtR, as a simple, practical, and reliable anthropometric measure, can be used to predict the risk of IR in patients with PCOS.

Prediction models of basal energy expenditure in children and adolescents across the BMI spectrum based on room-calorimetry: a cross-sectional cohort study.

Existing equations for prediction of basal energy expenditure (BEE) may not be accurate in children with overweight or obesity (OW/OB). We aimed to develop BEE prediction equations applicable to children and adolescents across a wide BMI spectrum using gold standard room calorimetry. We measured weight, height, waist and hip circumferences, body composition (DXA), and BEE (whole room calorimetry) in a cross-sectional cohort of 1155 healthy children, 5-19 years of age. 67% of the males and 51% of the females were classified as OW/OB. We applied multiple linear regression analyses to develop BEE prediction models for each sex. Using relevant predictors, we developed models with fat-free mass (FFM); waist and hip circumference; weight and height only; and weight only. A representative sample of participants (83 males, 125 females) served as a validation dataset to test model performance. The models' performance in predicting BEE was compared to existing models in the literature. Model fits (R2) for the new BEE prediction models were = 0.84 (p<.0001). Our BEE prediction models performed equally in children with normal weight and OW/OB, with <1.5% difference between the measured versus predicted BEE in the validation dataset for both sexes. In Bland-Altman analysis, our BEE prediction models were superior to existing prediction models, especially for children with higher BEEs. New BEE prediction models developed and tested in cohorts representative of children with normal weight and OW/OB had superior performance compared with existing models. The BEE prediction equations based on simple anthropometrics or body composition provided improved accuracy and precision for children with NW or OW/OB, ages 5 to 19. More accurate estimates of BEE should allow for better estimates of energy requirements of children.

Waist-to-calf circumference ratio as a potential indicator of diabetes risk: results from the Longevity Check-Up (Lookup) 8+

Diabetes is a prevalent metabolic condition with substantial health and economic impacts. Therefore, effective and accessible indicators are essential for early detection and prevention. This study investigates the link between the waist-to-calf circumference ratio (WCR) and diabetes risk in a large cohort from the Longevity Check-Up (Lookup) 8+ Study. The present investigation is a retrospective cross-sectional study. Diabetes was defined either as self-reported diagnosis, or fasting plasma glucose equal to or greater than 126 mg/dL, or random plasma glucose equal to or greater than 200 mg/dL. The WCR was calculated by dividing waist circumference by calf circumference. A total population of 8900 participants (mean age 57.1 ± 14.8 years, 55% women) was included in the study. The prevalence of diabetes was 9.4%. Mean WCR displayed a significant trend (p for trend < 0.001), and the analysis of covariance (ANCOVA) revealed significant differences among the normal, pre-diabetes, diabetes groups. Unadjusted logistic regression showed a positive association between higher WCR and diabetes, which remained significant in the adjusted models. Receiver operating characteristic curve analysis indicated that WCR had a higher area under the curve compared to waist circumference alone, with cut-off values of 2.35 for men and 2.12 for women providing high sensitivity (91% for men, 92% for women) and specificity (74% for men, 75% for women). Our study introduces WCR as a novel, simple, and cost-effective anthropometric measure for identifying individuals at risk of diabetes, suitable for clinical use, especially in resource-limited settings.

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.

Validation of Fat Mass Metrics in Pediatric Obesity

Introduction: Hudda-Index is a prediction model for fat mass (FM) based on simple anthropometric measures. FM is a crucial factor in the development of comorbidities, i.e., type 2 diabetes. Hence, Hudda-Index is a promising tool to facilitate the identification of children at risk for metabolic comorbidities. It has been validated against deuterium dilution assessments; however, independent validation against the gold standard for body composition analysis, magnetic resonance imaging (MRI), is lacking. The aim of this study was to validate FM calculated by Hudda-Index against FM measured by MRI. The secondary aim was to compare Hudda-Index to other anthropometric measures including body mass index (BMI), BMI-standard deviation score (BMI-SDS), waist/hip-ratio, waist circumference (WC), and skinfold thickness. Methods: The study cohort consists of 115 individuals between the age of 9 and 15 years, recruited at Paracelsus Medical University Hospital in Salzburg (Austria) and Uppsala University Children’s Hospital (Sweden). Anthropometry, blood samples, and oral glucose tolerance tests followed standard procedures. MRI examinations were performed to determine visceral adipose tissue (VAT) and subcutaneous adipose tissue. Results: BMI and WC showed slightly stronger associations with the reference standard VAT (r = 0.72 and 0.70, p < 0.01, respectively) than Hudda-Index (r = 0.67, p < 0.01). There is an almost perfect linear association between BMI and Hudda-Index. Accordingly, BMI and Hudda-Index both showed an acceptable association with cardiometabolic parameters. VAT was strongly associated with markers of liver status (LFF r = 0.59, p < 0.01) and insulin resistance (HOMA-IR r = 0.71, p < 0.01) and predicted metabolic dysfunction-associated steatotic liver disease. Conclusion: BMI, although an imperfect measure, remains the most reliable tool and estimates cardiometabolic risk more reliably than other anthropometry-based measures.

Anthropometric predictors of hamstring graft size in anterior cruciate ligament reconstruction

Background: The anterior cruciate ligament (ACL) is commonly injured in the knee joint, necessitating surgical reconstruction where quadrupled hamstring tendon autografts are frequently utilized for their favourable outcomes. Predicting the appropriate dimensions of these grafts is essential for surgical success. This study aims to investigate whether simple anthropometric measurements-height, weight, body mass index (BMI), thigh length, and circumference-can predict the length and diameter of quadrupled hamstring tendons used in ACL reconstruction. Methods: This cross-sectional study included 45 patients undergoing ACL reconstruction with quadrupled hamstring autografts at department of orthopaedics, Renai Medicity Kerala, India. Preoperative anthropometric measurements were correlated with intraop graft dimensions using Pearson correlation and SPSS statistical software (version 22). Results: Taller patients exhibited a positive correlation with graft diameter (p=0.028). Height and thigh length correlated positively with both gracilis and semitendinosus tendon lengths (p&lt;0.001). Thigh circumference correlated positively with semitendinosus length (p=0.005), while weight, BMI, and other measures did not significantly correlate with graft dimensions. Conclusions: Anthropometric measurements, particularly height and thigh length, serve as valuable predictors for hamstring graft dimensions in ACL reconstruction. These findings may assist surgeons in selecting appropriate grafts and optimizing surgical outcomes.

Grip Strength, Anthropometric Indices, and Their Combination in Screening for Metabolic Syndrome in the Korean Population

Background: Metabolic syndrome (MS) is a cluster of cardiometabolic risk factors for future diabetes and cardiovascular diseases, and low grip strength (GS) is associated with an increased risk of MS. However, the index (among absolute GS, relative GS, and anthropometric indices) that is more strongly associated with MS has not been conclusively identified. Therefore, the objective of the present study was to simultaneously examine the associations of MS with relative and absolute GS and anthropometric indices in a Korean population. Methods: In this large-scale cross-sectional study, we used data from the Korean National Health and Nutrition Examination Survey (KNHANES). A total of 20,915 subjects were included in the statistical analyses. Complex sample binary logistic regression models were used to analyze the associations between MS and indices such as the waist-to-height ratio (WHtR), body mass index (BMI), and absolute and relative GS. Results: The prevalence of MS was 40.48% in men and 34.4% in women. The mean GS values in the healthy group and MS group were 38.06 ± 0.13 and 38.06 ± 0.15 years for men (p = 0.980) and 22.72 ± 0.07 and 21.19 ± 0.11 years for women (p &lt; 0.001), respectively. Among all the indices, the WHtR was the index most strongly associated with MS in men. Among the GS indices, the GS/weight index was closely associated with MS, and the magnitude of this association was stronger than that of the absolute GS index. In women, the WHtR was the most related index to MS among all the indices. Among the GS indices, the GS/weight and GS/BMI indices were strongly associated with MS, and the magnitudes of these associations were much greater than those of the absolute GS index. Conclusions: Although absolute and relative GS indices are strongly associated with MS in the Korean population, the strongest association was observed for the simple anthropometric index (WHtR).

Utility of mid-upper arm circumference in pediatric malnutrition: An Australasian Society of Parenteral and Enteral Nutrition consensus statement using the Delphi method.

Mid-upper arm circumference (MUAC) is a simple anthropometric tool used to screen for childhood undernutrition in humanitarian settings or low-income and middle-income countries. However, there is conflicting evidence and a lack of consensus with regard to its diagnostic use in clinical settings or population groups beyond this context. In 2023, a project officer was appointed by the Australasian Society of Parenteral and Enteral Nutrition (AuSPEN) to lead the development of a consensus review into the use of MUAC in the pediatric clinical setting. An AuSPEN appointed multidisciplinary group of informed clinicians used the Delphi method to critically appraise the evidence and develop a series of consensus statements. Delphi surveys were anonymous and distributed electronically. Members were asked to rate their level of agreement with each consensus statement using a 5-point Likert scale. A priori definition of consensus was established as ≥80% responses "agree" or "strongly agree." Three Delphi rounds were required to reach consensus. A total of 18 consensus statements, including rationale, were developed across the topics 'assessment and diagnosis', 'screening and monitoring' and 'clinical settings'. An evidence-based, region-specific consensus approach to the use of MUAC in pediatric malnutrition is a valuable tool for clinicians. MUAC is a straightforward, non-invasive and cost-effective tool, and may provide an advantage over traditional anthropometric tools in some clinical settings. There are limitations to the utility of MUAC and this consensus paper provides an empirical summary of advantages and limitations as they apply to the screening, assessment, diagnosis, and monitoring of pediatric malnutrition.

Predicting Sprint Performance From the Vertical and Horizontal Jumps in National Football League Combine Athletes.

Agar-Newman, DJ, MacRae, F, Tsai, M-C, and Klimstra, M. Predicting sprint performance from the vertical and horizontal jumps in National Football League Combine athletes. J Strength Cond Res 38(8): 1433-1439, 2024-Identifying fast athletes is an important part of the National Football League (NFL) Combine. However, not all athletes partake in the 36.58-m sprint, and relying on this single test may miss potentially fast athletes. Therefore, the purpose of this study was to determine whether sprinting times can be predicted using simple anthropometric and jumping measures. Data from the NFL Combine between the years 1999-2020 inclusive were used (n = 4,149). Subjects had a mean (±SD) height = 1.87 ± 0.07 m and body mass = 111.96 ± 20.78 kg. The cross-validation technique was used, partitioning the data into a training set (n = 2,071) to develop regression models to predict time over the 9.14-, 9.14- to 18.29-, 18.29- to 36.58-m, and 36.58-m segments using vertical jump, broad jump, height, and mass as the independent variables. The models were then evaluated against a test set (n = 2,070) for agreement. Statistically significant (p < 0.01) models were determined for 9.14-m time (adjusted R2 = 0.76, SEE = 0.05 seconds), 9.14- to 18.29-m time (adjusted R2 = 0.74, SEE = 0.04 seconds), 18.29- to 36.59-m time (adjusted R2 = 0.79, SEE = 0.07 seconds), and 36.58-m time (adjusted R2 = 0.84, SEE = 0.12 seconds). When evaluated against the test set, the models showed biases of -0.05, -0.04, -0.02, and -0.02 seconds and root-mean-square error of 0.07, 0.05, 0.07, and 0.12 seconds for the 9.14-, 9.14- to 18.29-, 18.29- to 36.58-m, and 36.58-m segments, respectively. However, 5-6% of the predictions lay outside of the limits of agreement. This study provides 4 formulae that can be used to predict sprint performance when the 36.58-m sprint test is not performed, and practitioners can use these equations to determine training areas of opportunity when working with athletes preparing for the NFL Combine.

Association between Neck Circumference and Asymptomatic Hyperuricemia in Nearly Healthy Adults: A Review of 2019-2020 Cross-Sectional Korean Nationwide Data.

Neck circumference (NC) measurement has been recently developed as a simple and time-saving anthropometric method for predicting cardiovascular risk. Asymptomatic hyperuricemia is known as one of the cardiovascular risk factors. This study investigated the association between NC and asymptomatic hyperuricemia among the general population of Korea. This cross-sectional study examined data from 7,629 participants in the 2019-2020 Korea National Health and Nutrition Examination Survey. Multivariable logistic regression analysis was used to identify the factors associated with hyperuricemia. Approximately 10% of participants corresponded to hyperuricemia group who were likely to be male, have more comorbidities, poorer habits, and larger NC. Multivariable regression analysis revealed that NC was significantly associated with hyperuricemia in women (OR 1.17; 95% CI 1.06-1.30), but not in men (OR 1.04; 95% CI 0.96-1.12). A large NC is independently correlated with hyperuricemia among Korean women.

Imaging-based body fat distribution and diabetic retinopathy in general US population with diabetes: an NHANES analysis (2003–2006 and 2011–2018)

BackgroundLimited studies have investigated the correlation between fat distribution and the risk of diabetic retinopathy (DR) in the general population with diabetes. The relationship between obesity and DR remains inconclusive, possibly due to using simple anthropometric measures to define obesity. This study investigates the relationships between the android-to-gynoid fat ratio (A/G ratio, measured using dual-energy X-ray absorptiometry) and DR within the US population with diabetes.MethodsThe study used a population-based, cross-sectional approach based on the 2003–2006 and 2011–2018 data of the National Health and Nutrition Examination Survey (NHANES). Multivariable logistic regression analyses were performed on participants with diabetes to evaluate the contribution of body mass index (BMI), waist-to-height ratio (WHtR), and A/G ratio to the prevalence of DR.ResultsThe prevalence of DR was 22.2, 21.2, and 17.6% among participants with A/G ratios <1.0, 1.0–1.2, and ≥1.2, respectively. After adjusting sex, age, ethnicity, diabetes duration, hemoglobin A1c level, blood pressure level, and non-high-density lipoprotein cholesterol level, a higher A/G ratio (≥1.2) was independently associated with decreased odds of DR (odds ratio [OR], 0.565; 95% CI: 0.372–0.858) compared with the A/G ratio of 1.0–1.2. Associations between a higher A/G ratio and DR remained statistically significant after adjusting for BMI (OR, 0.567; 95% CI: 0.373–0.861) and WHtR (OR, 0.586; 95% CI: 0.379–0.907). Moreover, these associations remained statistically significant in analyses using the ethnic-specific tertiles for the A/G ratio. In sex-stratified models, these correlations remained in males. There was a significant inverse association between the A/G ratio and diabetes duration in males, which persisted after multivariable adjustments (p < 0.05).ConclusionsA novel finding indicates that a higher A/G ratio is associated with a reduced likelihood of DR in males with diabetes. The results from NHANES underscore the importance of considering imaging-based fat distribution as a critical indicator in clinical practice.

LIVERSTAT for risk stratification for patients with metabolic dysfunction-associated fatty liver disease.

LIVERSTAT is an artificial intelligence-based noninvasive test devised to screen for and provide risk stratification for metabolic dysfunction-associated fatty liver disease (MAFLD) by using simple blood biomarkers and anthropometric measurements. We aimed to study LIVERSTAT in patients with MAFLD and to explore its role for the diagnosis of advanced fibrosis. This is a retrospective study of data from MAFLD patients who underwent a liver biopsy. Patients with type 2 diabetes who underwent transient elastography and had liver stiffness measurement (LSM)<5kPa were included as patients with no fibrosis. Among these patients, controlled attenuation parameter <248dB/m was considered as no steatosis. The LIVERSTAT results were generated based on a proprietary algorithm, blinded to the histological and LSM data. The data for 350 patients were analyzed (mean age 53years, 45% male, advanced fibrosis 22%). The sensitivity, specificity, positive predictive value, negative predictive value, and misclassification rate of LIVERSTAT to diagnose advanced fibrosis were 90%, 50%, 30%, 95%, and 42%, respectively. The corresponding rates for Fibrosis-4 score (FIB4) were 56%, 83%, 44%, 89%, and 22%, respectively. When LSM was used as a second test, the corresponding rates for LIVERSTAT were 60%, 97%, 76%, 94%, and 8%, respectively, while the corresponding rates for FIB4 were 38%, 99%, 83%, 89%, and 11%, respectively. LIVERSTAT had a higher negative predictive value compared with FIB4 and a lower misclassification rate compared with FIB4 when used in a two-step approach in combination with LSM for the diagnosis of advanced fibrosis.

Neck Circumference Cut-Off Points for Identifying Adiposity: Association with Chronic Metabolic Diseases in Older People.

The leading cause of death in older people is cardiovascular diseases. Several studies have found that neck circumference (NC) is a simple anthropometric marker associated with adiposity. The aim of this study is to estimate and validate NC cut-off points as adiposity markers and analyze their association with cardiovascular and chronic metabolic diseases in older people. A cross-sectional study in 358 non-disabled, community-dwelling older people (71.7 ± 3.9 years) living in Santiago de Chile and participating in the HTSMayor study was conducted. Measurements of body composition and cardiovascular risks were evaluated. Receiver operating characteristic (ROC) curves and multiple logistic regression models were used to evaluate the association of NC with cardiovascular and chronic metabolic diseases. NC cut-off points were obtained to predict obesity, abdominal obesity, and adiposity. The best performance values of neck circumference relative to obesity and adiposity were obtained with respect to abdominal obesity (40.6 cm in men and 34.2 cm in women). Higher NC values were associated with a higher area under the curve (AUC) for men and women (men: AUC = 0.84; women: AUC = 0.86). NC was significantly associated with a higher risk for diabetes mellitus (OR = 1.95), hypertension (OR = 2.42), acute myocardial infarction (OR = 4.36), and comorbidities (OR = 2.01), and a lower risk for sarcopenia (OR = 0.35). This study shows that NC is a useful tool for detecting abdominal obesity, obesity, and adiposity in older people and that a higher NC increases the risk of chronic diseases.

Correlation of anthropometric measurements with body mass index and estimation of the proportion of metabolic syndrome among overweight and obese children: a hospital-based cross-sectional study

BackgroundEarly identification of overweight and obesity with the help of simple anthropometric tests can prevent from development of metabolic complications in these children. Body mass index (BMI) is the most...

The relationship between body roundness index and depression: A cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) 2011–2018

BackgroundDepression is linked to obesity. The body roundness index (BRI) provides a more accurate assessment of body and visceral fat levels than the body mass index or waist circumference. However, the association between BRI and depression is unclear. Therefore, we investigated this relationship using the National Health and Nutrition Examination Survey (NHANES) database. MethodsIn this population-based cross-sectional study, data from 18,654 adults aged ≥20 years from the NHANES 2011–2018 were analyzed. Covariates, including age, gender, race/ethnicity, education level, marital status, poverty-income ratio, alcohol status, smoking status, hypertension, diabetes mellitus, cardiovascular disease, energy intake, physical activity, total cholesterol, and triglycerides were adjusted in multivariable logistic regression models. In addition, smooth curve fitting, subgroup analysis, and interaction testing were conducted. ResultsAfter adjusting for covariates, BRI was positively correlated with depression. For each one-unit increase in BRI, the prevalence of depression increased by 8 % (odds ratio = 1.08, 95 % confidence interval = 1.05–1.10, P < 0.001). LimitationsAs this was a cross-sectional study, we could not determine a causal relationship between BRI and depression. Patients with depression in this study were not clinically diagnosed with major depressive disorder. ConclusionBRI levels were positively related to an increased prevalence of depression in American adults. BRI may serve as a simple anthropometric index to predict depression.

Association between weight-adjusted-waist index and depression: a cross-sectional study.

Depression has become a multifaceted global health issue, with complex connections to obesity. Weight-adjusted-waist index (WWI) can effectively evaluate central obesity, but the relationship between WWI and depression has not been well studied. The study aims to investigate the potential correlation between these two health parameters. According to the data from National Health and Nutrition Examination Survey, this cross-sectional study used multiple regression analysis, subgroup analysis, and smooth curve fitting to explore the relationship between WWI and depression. The assessment ability of WWI was evaluated and compared to other obesity indicators using the receiver operating characteristic (ROC) curve. This study analyzed 38,154 participants. Higher WWI is associated with higher depression scores (β = 0.41; 95% CI, 0.36-0.47). After adjusting for various confounding factors, the positive correlation between WWI and depression remained significant (P for trend < 0.0001). Nonlinear positive correlation was detected with a breakpoint of 11.14. ROC analysis shows that compared to other obesity indicators (ROCWWI = 0.593; ROCBMI = 0.584; and ROCWC = 0.581), the correlation between WWI and depression has better discrimination and accuracy. DII mediated 4.93%, SII mediated 5.08%, and sedentary mediated 0.35% of the total association between WWI and depression. WWI levels were related to an increased likelihood of depression and showed a stronger relationship than BMI and waist circumference. Our findings indicated that WWI may serve as a simple anthropometric index to evaluate depression.

Neck circumference as an alternative marker of metabolic syndrome in Peruvian adults: A retrospective, cross-sectional study

Neck circumference is a low-cost and simple anthropometric measure that has been proven to accurately assess central obesity. However, evidence of its use and feasibility in low-resource settings is limited. We aimed to compare the utility of neck circumference with standard physical measures of obesity in northern Peru. This was a retrospective, cross-sectional study conducted among adults screened for metabolic syndrome. Body mass index, waist circumference, neck circumference, and additional measurements for metabolic syndrome were obtained. Assessments were performed following the WHO STEPS Surveillance Manual. Pearson correlation coefficients and multiple linear regression models were used to estimate the relationship of neck circumference to waist circumference and body mass index. Data from 250 participants showed a normal, homogeneous distribution in both men and women with respect to age and physical/biochemical measurements. The mean age was 53.6 years. A positive correlation of neck circumference with body mass index (r = 0.51 for women and 0.65 for men) and waist circumference (r = 0.6 for women and 0.74 for men) was observed. Multiple linear regression showed that a 1-cm increase in neck circumference increased body mass index by 0.72 kg/m2 (p < 0.001) in men and 0.94 kg/m2 (p < 0.001) in women, and waist circumference by 2.20 cm (p < 0.001) in men and 2.27 cm (p < 0.001) in women. Our findings suggest that neck circumference is a valid and reliable measure that will replace body mass index and waist circumference in Peruvian adults with central obesity; due to the strong correlation that exists between the NC and these anthropometric measurements, mainly because it is an easy, quick measurement and is less vulnerable to errors such as in the measurement of abdominal circumference or variabilities in weight.

Development and validation of age-specific predictive equations for total energy expenditure and physical activity levels for older adults

BackgroundPredicting energy requirements for older adults is compromised by the underpinning data being extrapolated from younger adults. ObjectivesTo generate and validate new total energy expenditure (TEE) predictive equations specifically for older adults using readily available measures (age, weight, height) and to generate and test new physical activity level (PAL) values derived from 1) reference method of indirect calorimetry and 2) predictive equations in adults aged ≥65 y. MethodsTEE derived from “gold standard” methods from n = 1657 (n = 1019 females, age range 65–90 y), was used to generate PAL values. PAL ranged 1.28–2.05 for males and 1.26–2.06 for females. Physical activity (PA) coefficients were also estimated and categorized (inactive to very active) from population means. Nonlinear regression was used to develop prediction equations for estimating TEE. Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split, and leave one out cross-validation were performed. Comparisons were made with existing equations. ResultsEquations predicting TEE using the Institute of Medicine method are as follows: For males, TEE = −5680.17 − 17.50 × age (years) + PA coefficient × (6.96 × weight [kilograms] + 44.21 × height [centimeters]) + 1.13 × resting metabolic rate (RMR) (kilojoule/day). For females, TEE = −5290.72 − 8.38 × age (years) + PA coefficient × (9.77 × weight [kilograms] + 41.51 × height [centimeters]) + 1.05 × RMR (kilojoule/day), where PA coefficient values range from 1 (inactive) to 1.51 (highly active) in males and 1 to 1.44 in females respectively. Predictive performance for TEE from anthropometric variables and population mean PA was moderate with limits of agreement approximately ±30%. This improved to ±20% if PA was adjusted for activity category (inactive, low active, active, and very active). Where RMR was included as a predictor variable, the performance improved further to ±10% with a median absolute prediction error of approximately 4%. ConclusionsThese new TEE prediction equations require only simple anthropometric data and are accurate and reproducible at a group level while performing better than existing equations. Substantial individual variability in PAL in older adults is the major source of variation when applied at an individual level.

Prediction Of Palmaris Longus Tendon Length And Thickness Through Simple Anthropometric Measurements.

This study aimed to test whether palmaris longus tendon (PLT) length and thickness can be predicted from simple anthropometric measurements. 120 healthy volunteers with bilateral PL muscles were enrolled in this prospective study. PLT length and thickness were measured by ultrasonographic examination. Anthropometric measurements included body height, weight, forearm length, and wrist circumference. Correlation, linear regression, and Bland-Altman plot were used for analysis. The mean PLT length and thickness were 10.8±1.4 cm and 4.0±0.9 mm, respectively. Body height and PLT length had a moderate positive correlation (r:0.407, p:0.001), and forearm length and PLT thickness had a weak positive correlation (r:0.229, p:0.001). The regression analysis showed that body height was the best predictor for PLT length, and forearm length was the best predictor for PLT thickness. The regression equations were as follows: PLT length=0.276+(0.062×height) (r2=0.165, p<0.001) and PLT thickness=1.373+(0.108×forearm length) (r2=0.052, p<0.001). The predicted PLT lengths and thicknesses were calculated using these regression formulas and compared with the actual thicknesses and lengths using the Bland-Altman plot. The upper and lower limits of agreement (95% CI) ranged from -2.54 cm to 2.51 cm for actual PLT length and predicted PLT length and from -1.76 mm to 1.74 mm for actual PLT thickness and predicted PLT thickness in the Bland-Altman plot with a weak agreement and proportional bias. These findings indicate that height and forearm length have limited accuracy in predicting PLT length and thickness. The preoperative ultrasonographic examination can provide valuable assistance, particularly in cases that require grafts with precise length and thickness requirements.