Mid-upper arm circumference as a simple tool for identifying central obesity and insulin resistance in type 2 diabetes

The relationship between mid-upper arm circumference and blood pressure in Walter Sisulu University community

Prevalence of hypertension is increasing to higher levels in South Africa. Anthropometric measures for obesity are well known to predict the development of hypertension. However, the relationship between mid-upper arm circumference (MUAC) and blood pressure (BP) is scant in South African communities such as universities. Therefore, this study was aimed at investigating the correlation between MUAC and BP among the community of Walter Sisulu University (WSU). A total of 230 participants from WSU (students and staff members), 113 females and 117 males aged ≥ 18 years participated in this cross-sectional study. MUAC, systolic BP (SBP) and diastolic BP (DBP) were measured using standard procedures. In a Pearson's correlation analysis, MUAC was positively correlated with SBP and DBP in both women (SBP; r = 0.53, P< 0.001; DBP; r = 0.45 P < 0.001) and men (SBP; r = 0.29 P = 0.001; DBP; r = 0.25 P = 0.007). Furthermore, in the multivariable-adjusted regression analysis, MUAC was positively associated with SBP in women only (adjusted R2 = 0.489, β = 0.29 (95% CI = 0.16; 2.08)), P =0.023) after adjusted for age, body fat percentage, waist-to-height ratio, smoking and alcohol. MUAC is positively correlated with BP in women, not in men of WSU community. MUAC, as a simple and low-cost quantifiable parameter, could be employed as a risk indicator in the early detection and prevention of cardiovascular diseases (CVDs) in women.

Mid-upper arm circumference predicts the risk of gestational diabetes in early pregnancy

BACKGROUND

The present work aimed to assess the value of mid-upper arm circumference (MUAC) at 8 to 12 weeks in predicting the occurrence of gestational diabetes mellitus (GDM).

METHODS

According to eligibility criteria, 328 women with singleton pregnancies who underwent routine antenatal check-ups at Qinhuangdao Maternal and Child Health Hospital from September 2017 to September 2020 were included. The patients were divided into the gestational diabetes mellitus (GDM) and non-GDM groups according to oral glucose tolerance test (OGTT) data from gestation weeks 24 to 28. Clinical data were compared between the two groups. Logistic regression analysis was performed to determine factors independently predicting GDM. Receiver operating characteristic (ROC) curve analysis was employed to analyze the value of MUAC in predicting the occurrence of GDM. The optimal cut-off points were calculated.

RESULTS

In logistic regression analysis, pre-pregnancy weight, waist circumference, MUAC, UA, TG, and HDL-C independently predicted the occurrence of GDM (P < 0.05). MUAC retained statistical significance upon adjustment for various confounders (OR = 8.851, 95%CI: 3.907-20.048; P < 0.001). ROC curve analysis revealed good diagnostic potential for MUAC in GDM (AUC = 0.742, 95%CI: 0.684-0.800, P < 0.001), with a cut-off of 28.5 cm, sensitivity and specificity were 61% and 77%, respectively.

CONCLUSION

Pregnant women with MUAC >28.5 cm are prone to develop GDM during pregnancy, indicating that MUAC as an important predictive factor of GDM in early pregnancy.

A cohort study on the predictive capability of body composition for diabetes mellitus using machine learning

Purpose

We applied machine learning to study associations between regional body fat distribution and diabetes mellitus in a population of community adults in order to investigate the predictive capability. We retrospectively analyzed a subset of data from the published Fasa cohort study using individual standard classifiers as well as ensemble learning algorithms.

Methods

We measured segmental body composition using the Tanita Analyzer BC-418 MA (Tanita Corp, Japan). The following features were input to our machine learning model: fat-free mass, fat percentage, basal metabolic rate, total body water, right arm fat-free mass, right leg fat-free mass, trunk fat-free mass, trunk fat percentage, sex, age, right leg fat percentage, and right arm fat percentage. We performed classification into diabetes vs. no diabetes classes using linear support vector machine, decision tree, stochastic gradient descent, logistic regression, Gaussian naïve Bayes, k-nearest neighbors (k = 3 and k = 4), and multi-layer perceptron, as well as ensemble learning using random forest, gradient boosting, adaptive boosting, XGBoost, and ensemble voting classifiers with Top3 and Top4 algorithms. 4661 subjects (mean age 47.64 ± 9.37 years, range 35 to 70 years; 2155 male, 2506 female) were analyzed and stratified into 571 and 4090 subjects with and without a self-declared history of diabetes, respectively.

Results

Age, fat mass, and fat percentages in the legs, arms, and trunk were positively associated with diabetes; fat-free mass in the legs, arms, and trunk, were negatively associated. Using XGBoost, our model attained the best excellent accuracy, precision, recall, and F1-score of 89.96%, 90.20%, 89.65%, and 89.91%, respectively.

Conclusions

Our machine learning model showed that regional body fat compositions were predictive of diabetes status.

Association between the arm circumference and non-alcoholic fatty liver disease in American children and adolescence: a population-based analysis

Background

The arm circumference (AC) has been used as an important tool to access the risk of non-alcoholic fatty liver disease (NAFLD) in adults. However, the association between AC and NAFLD in children and adolescence remains unclear. This study aims to explore the relationship between AC and NAFLD in American children and adolescence.

Methods

2017-2020 National Health and Nutrition Examination Survey (NHANES) was used to carry out the cross-sectional study. The association between AC and the risk of NAFLD, and liver steatosis was analyzed using weighted multivariable logistic regression and multivariate linear regression. Additionally, a two-part linear regression model was used to identify threshold effects in this study. Subgroup analysis, interaction tests and receiver operating characteristic (ROC) curve analysis were also carried out.

Results

A total of 1,559 children and adolescence aged 12-18 years old were included, and the prevalence of NAFLD was 27.3%. AC was positively correlated with the risk of NAFLD (OR = 1.25, 95% CI: 1.19, 1.32) and liver steatosis (β = 4.41, 95% CI: 3.72, 5.09). Subgroup analysis stratified by age and race showed a consistent positive correlation. A non-linear relationship and saturation effect between AC and NAFLD risk were identified, with an S shaped curve and an inflection point at 34.5 cm. Area under the ROC of AC to NAFLD was 0.812, with the sensitivity of 67.6%, the specificity of 83.8% and the cutoff value of 31.7 cm.

Conclusion

Our study shows that AC is independently correlated with an increased risk of NAFLD and the severity of liver steatosis in American children and adolescence.

Associations between Neck Circumference, Mid-Upper Arm Circumference, Wrist Circumference, and High Blood Pressure among Lithuanian Children and Adolescents: A Cross-Sectional Study

(1) Background: High blood pressure (HBP) and obesity are significant and growing public health issues worldwide. Our study aimed to evaluate the associations of neck circumference (NC), mid-upper arm circumference (MUAC), and wrist circumference (WrC) with HBP among Lithuanian children and adolescents aged 7-17 years. (2) Methods: In this cross-sectional study, data on BP and anthropometric measurements were analysed in 3688 children and adolescents aged 7-17 years. Multivariate logistic regression analysis was used to estimate the associations between anthropometric indices and HBP. (3) Results: Overall, the prevalence rates of elevated BP and hypertension were 13.7% and 12.9%, respectively. After adjustment for age, BMI, and WC, statistically significant elevated aORs were observed for associations between greater NC, MUAC, WrC, and HBP in boys (aORs: 2.13, 2.46, and 2.48, respectively) and in girls (aORs: 2.01, 2.36, and 2.09, respectively). Moreover, per-unit increase in NC, MUAC, and WrC was also associated with greater odds of HBP in boys (aORs: 1.20, 1.21, and 1.37, respectively) and in girls (aORs: 1.10, 1.10, and 1.21, respectively). The analysed anthropometric indices presented higher area under the curve values for predicting HBP in boys than in girls. (4) Conclusions: This study suggests that higher NC, MUAC, and WrC are associated with increased odds of HBP in Lithuanian children and adolescents.

Follow-up of a randomized trial optimizing neonatal nutrition in preterm very low birthweight infants: growth, serum adipokines, renal function and blood pressure

OBJECTIVE

The primary objectives were to compare body mass index (BMI) Z-score (Z), systolic blood pressure (SBP), serum leptin:adiponectin (L:A) ratio and estimated glomerular filtration rate (eGFR) at ~3 years adjusted age between two arms of a randomized controlled trial (RCT) comparing two modes of human milk fortification for very low-birthweight infants in the neonatal intensive care unit.

STUDY DESIGN

Follow-up of RCT at 33-48 months.

RESULTS

Follow-up data are available in 82/120 infants. Infants in the experimental arm have anthropometric data consistent with central obesity and higher serum L:A ratio (sensitivity analysis adjusting for sex and using all available data), but have similar eGFR and SBP at follow-up compared with controls. Serum L:A ratio is strongly correlated with anthropometric measurements suggesting central obesity.

CONCLUSIONS

Infants in the experimental arm have central obesity and higher serum L:A ratio compared with controls. Notably, serum L:A ratio is strongly correlated with weight gain.

TRIAL REGISTRATION

This randomized controlled trial was registered at ClinicalTrials.gov NCT02372136.

Performance of the Global Diet Quality Score (GDQS) App in Predicting Nutrient Adequacy and Metabolic Risk Factors among Thai Adults

BACKGROUND

The Global Diet Quality Score (GDQS) was developed for monitoring nutrient adequacy and diet-related noncommunicable disease risk in diverse populations. A software application (GDQS app) was recently developed for the standardized collection of GDQS data. The application involves a simplified 24-h dietary recall (24HR) where foods are matched to GDQS-food groups using an onboard database, portion sizes are estimated at the food group level using cubic models, and the GDQS is computed.

OBJECTIVES

The study aimed to estimate associations between GDQS scores collected using the GDQS app and nutrient adequacy and metabolic risks.

METHODS

In this cross-sectional study of 600 Thai males and nonpregnant/nonlactating females (40-60 y), we collected 2 d of GDQS app and paper-based 24HR, food-frequency questionnaires (FFQs), anthropometry, body composition, blood pressure, and biomarkers. Associations between application scores and outcomes were estimated using multiple regression, and application performance was compared with that of metrics scored using 24HR and FFQ data: GDQS, Minimum Dietary Diversity-Women, Alternative Healthy Eating Index-2010, and Global Dietary Recommendations score.

RESULTS

In covariate-adjusted models, application scores were significantly (P < 0.05) associated with higher energy-adjusted mean micronutrient adequacy computed using 24HR (range in estimated mean adequacy between score quintiles 1 and 5: 36.3%-44.5%) and FFQ (Q1-Q5: 40.6%-44.2%), and probability of protein adequacy from 24HR (Q1-Q5: 63%-72.5%). Application scores were inversely associated with BMI kg/m2 (Q1-Q5: 26.3-24.9), body fat percentage (Q1-Q5: 31.7%-29.1%), diastolic blood pressure (Q1-Q5: 84-81 mm Hg), and a locally-developed sodium intake score (Q1-Q5: 27.5-24.0 points out of 100); positively associated with high-density lipoprotein cholesterol (Q1-Q5: 49-53 mg/dL) and 24-h urinary potassium (Q1-Q5: 1385-1646 mg); and inversely associated with high midupper arm circumference (Q5/Q1 odds ratio: 0.52) and abdominal obesity (Q5/Q1 odds ratio: 0.51). Significant associations for the application outnumbered those for metrics computed using 24HR or FFQ.

CONCLUSIONS

The GDQS app effectively assesses nutrient adequacy and metabolic risk in population surveys.

The L-shaped association of mid-upper arm circumference with all-cause and cause-specific mortality in US adults: a population-based prospective cohort study

BACKGROUND

The arm circumference is a feasible and reliable indicator in evaluating the nutritional status of children. However, its application in general adults has yet to be thoroughly investigated.

OBJECTIVE

This study aimed to evaluate the association between mid-upper arm circumferences (MUACs) and mortality in general adults.

METHODS

The nationally representative cohort from the National Health and Nutrition Examination Survey (1999-2018) was analyzed with mortality information obtained through linkage to the National Death Index. The baseline MUACs were collected as exposure. Survey-weighted Cox proportional hazard regressions were performed to estimate the hazard ratios (HRs) and 95% confidential intervals (CIs) of mortality risk for individuals with different MUACs. Restricted cubic spline analyses were performed to examine the nonlinear association of MUAC with all-cause and cause-specific mortality.

RESULTS

A total of 52,159 participants were included in this study. During a median follow-up time of 117 months, 7157 deaths were documented, with leading causes of cardiovascular disease (CVD), cancer, and respiratory disease. Individuals in the first quartile (Q1) of MUAC tended to have higher all-cause mortality risk than the rest after full adjustment. Similarly, CVD mortality risk in Q1 was higher than that in the second quartile (Q2) and the third quartile (Q3); respiratory mortality risk in Q1 was higher than in Q2. MUAC was non-linearly associated with all-cause mortality and CVD mortality. Individuals in Q1 MUAC (≤ 29.3) tended to have higher all-cause mortality risk, with HRs (95% CIs) estimated to be 0.76 (0.67-0.87) for Q2 (29.4, 32.5), 0.69 (0.59-0.81) for Q3 (32.6, 36.0), and 0.59 (0.46-0.75) for Q4 (≥ 36.1) after adjustment of demographic, lifestyle, and comorbidity covariates. Similarly, compared with Q1, HRs (95% CIs) for CVD mortality were estimated to be 0.73 (0.58-0.93) for Q2 and 0.57 (0.43-0.47) for Q3; HRs (95% CIs) for respiratory mortality was estimated to be 0.57 (95% CI, 0.37-0.87) for Q2 with other differences not significant.

CONCLUSION

The MUAC was inversely associated with long-term mortality in general adults in the United States and may serve as a valuable measurement in adult health evaluations.

Arm Circumference, Arm-to-Waist Ratio in Relation to Cardiovascular and All-Cause Mortality among Patients with Diabetes Mellitus

Among patients with diabetes mellitus, limited studies have investigated the relationship between anthropometric parameters and cardiovascular disease (CVD), with all-cause mortality. We examined the associations of arm circumference (AC), arm-to-waist ratio (AC/WC), and CVD, with all-cause mortality among patients with diabetes. This is a cohort study of 5497 diabetic individuals aged 20 or over who were recruited in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014. Cox proportional hazards regression models were used to analyze the associations between AC, AC/WC, and CVD, with all-cause mortality. We also conducted stratified analyses and explored the possible non-linear relation by restricted cubic splines. During a median follow-up of 7.2 years, there were 271 and 1093 cases of CVD and all-cause death. The multivariable adjusted hazard ratios (HRs) with 95% confidence intervals (Cis) of CVD mortality in Q2, Q3, and Q4 groups compared with Q1 group were 0.37 (0.22, 0.62), 0.24 (0.12, 0.48), 0.18 (0.07, 0.46) for AC, and 0.18 (0.07, 0.46), 0.34 (0.20, 0.60), 0.28 (0.15, 0.53) for AC/WC. Similar results were observed in the analysis for all-cause mortality risk. AC and AC/WC were both inversely associated with CVD and all-cause mortality among individuals with diabetes. It is important to pay attention to these anthropometric parameters of diabetic patients.

Association of anthropometric parameters as a risk factor for development of diabetic retinopathy in patients with diabetes mellitus

OBJECTIVE

To study the relationship of body fat distribution in patients with diabetes mellitus (DM), and its long-term complications like diabetic retinopathy (DR), in Indian population.

METHODS

This was a prospective, cross-sectional observational study involving 1773 subjects diagnosed with DM and 1778 age and gender-matched individuals. The patients with DM were assessed for the presence and severity of DR. Severe non-proliferative DR and proliferative DR were categorised as sight threatening DR (STDR). Anthropometric parameters, i.e., neck circumference (NC); mid-upper arm circumference (MAC); waist circumference (WC); hip circumference (HC); mid-thigh circumference (MTC) and body mass index (BMI) were measured using standardised technique.

RESULTS

The mean age was 59.33 ± 9.32 for DM group, and 66.03 ± 11.04 for non-DM group. DM group showed significantly greater NC, WC, and MTC and significantly reduced MAC and weight. HC and BMI were comparable between the groups. There was a significant positive correlation of MAC and WC (with any level of DR) and MAC, WC, and weight (for STDR); and a significant negative correlation of HC and MTC (with any level of DR) and NC, HC, MTC, and BMI (for STDR). Multiple logistic regression analysis confirmed that WC was the single most important predictor for any level of DR and STDR.

CONCLUSIONS

Association of body fat distribution with DM and DR appears multifactorial. However, central obesity signified by waist circumference appears to be the significant risk related to the development of DR and STDR in Indian population.

Transitional Dynamics of Sarcopenia and Associations of Nutritional Indices with State Transitions in Chinese aged ≥ 50

OBJECTIVES

Sarcopenia's temporal profile can be regarded as a dynamic process with distinct states, in which malnutrition plays an important role. This study aimed to address two research gaps: sarcopenia's transitional dynamics and associations of nutritional indices with state transitions in community-dwelling Chinese adults aged 50 and older.

DESIGN

A prospective population-based cohort study.

SETTING

Community-based setting in western China.

PARTICIPANTS

The analytic sample included data from 1910 participants aged ≥ 50 in the West China Health and Aging Trend study between 2018-2022.

MEASUREMENTS

We defined three states: the initial normal state (normal muscle strength, physical performance and muscle mass), the worst sarcopenia state (low muscle mass plus low muscle strength and/or low physical performance) and the intermediate subclinical state (the other scenarios). The relevant measurement methods and cut-off points were based on the 2019 AWGS consensus. Using a continuous-time multistate Markov model, we calculated probabilities of transitions between different states over 1, 2 and 4 years; we also examined associations between nutritional indices and transitions, including body mass index (BMI), calf circumference (CC), mid-arm circumference (MAC), triceps skinfold thickness (TST), albumin (ALB), geriatric nutrition risk index (GNRI), vitamin D (VitD) and prealbumin (PA).

RESULTS

For individuals in the normal state, their probabilities of remaining stable versus progressing to a subclinical state were 53.4% versus 42.1% at 2 years, and 40.6% versus 49.0% at 4 years. In the subclinical population, their 2- and 4-year chances were 60.2% and 51.2% for maintaining this state, 11.8% and 16.2% for developing sarcopenia, 28.0% and 32.6% for reverting to normal. For sarcopenic individuals, the likelihood of staying stable versus retrogressing to the subclinical state were 67.0% versus 26.3% at 2 years, and 48.3% versus 36.3% at 4 years. Increased BMI, CC, MAC, TST, ALB, GNRI and PA correlated with reversion from the subclinical state, among which increased TST, ALB and PA were also paralleled with reversion from sarcopenia, while decreased BMI, CC, MAC, TST and GNRI were associated with progression to sarcopenia. VitD was not significantly associated with any transitions.

CONCLUSION

This study reveals how sarcopenia changes over time in a Chinese population. It also highlights the usefulness of simple and cost-effective nutritional status indices for indicating state transitions, which can help identify individuals at risk of sarcopenia and guide targeted interventions within the optimal time window.

Study of metabolic syndrome indicators in newly diagnosed diabetes mellitus type 2 patients in Pakistani population

BACKGROUND

Metabolic syndrome (MetS) being a biological abnormality confers the highest risk of type 2 diabetes mellitus (T2DM).

AIM

To assess MetS indicators in the newly diagnosed T2DM Pakistani population.

METHODS

A cross-sectional study (N = 123) with newly diagnosed T2DM patients (gender: both, MeanAge: 49.24 ± 6.84 years) was selected from Medical OPD, Pakistan Institute of Medical Sciences, Islamabad. Basic profile, family history, and physical activity were recorded through a predesigned questionnaire, dietary intake through seven days Food Diary and Food Frequency Questionnaire. Blood pressure and selected clinical signs and symptoms were recorded. Anthropometric measurements included mid-upper arm circumference (MUAC), body mass index (BMI), waist circumference (WC), waist-and-hip ratio (WHR), waist-to-height ratio (WHtR), and conicity index. Lab parameters included fasting blood glucose, HbA1c, insulin levels, and lipid profile. Homeostatic model assessment of insulin resistance (HOMA-IR) was computed to assess insulin resistance.

RESULTS

Almost all parameters related to MetS were higher than normal. The prevalence of MetS was 59.7%. BMI, MUAC, and WHtR were independently associated with HOMA-IR, but WC, WHR, and the conicity index had no relationship MetS indicators.

CONCLUSION

The prevalence rate of MetS was found to be 59.7% in newly diagnosed T2DM patients. MUAC was found to be a better parameter for the diagnosis of central obesity and insulin resistance in the selected population.

Data mining approaches for type 2 diabetes mellitus prediction using anthropometric measurements

BACKGROUND

The aim of this study was to evaluate the anthropometric measurements most associated with type 2 diabetes mellitus (T2DM) using machine learning approaches.

METHODS

A prospective study was designed for a total population of 9354 (43% men and 57% women) aged 35-65. Anthropometric measurements include weight, height, demispan, Hip Circumference (HC), Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), A Body Shape Index (ABSI), Body Mass Index (BMI), Waist-to-height Ratio (WHtR), and Waist-to-hip Ratio (WHR) were completed for all participants. The association was assessed using logistic regression (LR) and decision tree (DT) analysis. Receiver operating characteristic (ROC) curve was performed to evaluate the DT's accuracy, sensitivity, and specificity using R software.

RESULTS

Traditionally, 1461 women and 875 men with T2DM (T2DM group). According to the LR, in males, WC and BIA (p-value < 0.001) and in females, demispan and WC (p-value < 0.001) had the highest correlation with T2DM development risk. The DT indicated that WC has the most crucial effect on T2DM development risk, followed by HC, and BAI.

CONCLUSIONS

Our results showed that in both men and women, WC was the most important anthropometric factor to predict T2DM.

Mid-upper arm circumference as a substitute for body mass index in the assessment of nutritional status among adults in eastern Sudan

Background

Body mass index (BMI) remains the most used indicator of nutritional status despite the presence of a potentially credible alternative. Mid-upper arm circumference (MUAC) is an anthropometric measure that requires simple equipment and minimal training. The aim of this study was to compare MUAC with BMI and propose a MUAC cut-off point corresponding to a BMI of < 18.5 kg/m² (underweight) and ≥ 30.0 kg/m² (obesity) among Sudanese adults.

Methods

A cross-sectional study using multistage cluster sampling was conducted in New-Halfa, eastern Sudan. Participants’ age and sex were recorded and their MUAC, weight and height were measured using the standard procedures. The MUAC (cm) cut-offs corresponding to < 18.5 kg/m² and ≥ 30.0 kg/m² were calculated and determined using receiver operating characteristic (ROC) curve analysis

Results

Five hundreds and fifty-two adults were enrolled in the study. The median (interquartile range, IQR) of the participants age was 31.0 (24.0 – 40.0) years and 331 (60.0%) of them were females. The medians (IQR) of BMI and MUAC were 22.4 (19.1 – 26.3) kg/m² and 25.0 (23.0 – 28.0) cm, respectively.

There was a significant positive correlation between MUAC and BMI (r = 0.673, p < 0.001).

Of the 552 enrolled participants, 104 (18.8%), 282 (51.1%), 89 (16.1%) and 77 (13.9%) were normal weight, underweight, overweight and obese, respectively. Best statistically derived MUAC cut-off corresponding to a BMI < 18.5 kg/m² (underweight) was ≤ 25.5 cm in both males and females (Youden’s Index, YI = 0.51; sensitivity = 96.0%; specificity = 54.0%), with a good predictive value (AUROCC = 0.82). Best statistically derived MUAC cut-off corresponding to a BMI ≥ 30.0 kg/m² (obesity) was ≥ 29.5 cm in both males and females (YI = 0.62, sensitivity = 70.3%, specificity = 92.0%), with a good predictive value (AUROCC = 0.86, 95.0% CI = 0.76 – 0.95).

Conclusion

The results suggest that the cut-offs based on MUAC can be used for community-based screening of underweight and obesity

Mid upper arm circumference as screening tool of overweight or obesity among adult employees of Mizan Tepi University, Southwest Ethiopia

Background

Overweight or obesity is an excessive fat accumulation that impairs the health and wellbeing of the adult population throughout the world. Recently Mid upper arm circumference (MUAC) was suggested as a screening index for overweight or obesity among adolescents, but its utilization for the assessment of overweight or obesity in the adult population is not clear yet. In addition, little is known about the screening ability of MUAC for overweight or obesity in the adult population of Ethiopia. Therefore, this study aimed to evaluate the utility of MUAC for screening overweight or obesity among adult employees of Mizan Tepi University, Southwest Ethiopia.

Method

A Facility -based cross-sectional study was carried out from February 21 to March 20, 2020, at Mizan Tepi University. About 585 study participants were selected by gender-based stratified sampling technique. Anthropometric data like weight, height, and MUAC were collected. Pearson's correlation between MUAC, body mass index (BMI), and age was calculated to see a relationship between them. The Receiver operating characteristics (ROC) curve was calculated to identify the screening ability of MUAC for overweight or obesity. The appropriate MUAC cutoff point for both men and women established using the Youden index. Additionally, sensitivity, specificity, positive, and negative predictive values were calculated.

Result

The prevalence of overweight and obesity among the study participants was 18.1% and 4.8%, respectively. MUAC had a strong positive correlation with BMI, r = 0.65 (95% CI; 0.56-0.69). According to ROC analysis, MUAC is an excellent screening tool for male and female employees with excellent accuracy (AUC = 0.9 with 91.4% sensitivity and 76.4% specificity) and good accuracy (AUC = 0.83 with 67.2% sensitivity and 83.5% specificity), respectively. Based on the youden index, the cutoff point of MUAC to screen overweight or obesity among male and female employees was 26.91cm.

Conclusion

Mid-upper arm circumference (MUAC) has an equal ability with BMI to screen overweight or obesity among adults. Therefore, MUAC can be utilized as an alternative index to screen overweight and obesity in resource-limited setups.

Prognostic Value of Arm Circumference for Cardiac Damage and Major Adverse Cardiovascular Events: A Friend or a Foe? A 2-Year Follow-Up in the Northern Shanghai Study

Background

The high prevalence of cardiovascular diseases globally causes a great social burden and much individual suffering. The effective recognition of high-risk subjects is critical for primary prevention in the general population. In the elderly cohort, anthropometric measurements may have different prognostic values. Our study aimed to find convincing anthropometric measures to supplement conventional risk factors for major adverse cardiovascular events (MACEs) in the elderly cohort.

Materials and Methods

A total of 1,576 elderly participants (44.5% male, aged 72.0 ± 6.0 years) recruited into the Northern Shanghai Study (2014–2015) were followed up between 2016 and 2017. Following the standard guideline for cardiovascular risk evaluation, all conventional cardiovascular risk factors were assessed. The body measures were made up of body weight, body height, hip circumference, waist circumference, and middle-upper arm circumference (MUAC). Organ damage (OD) markers for cardiac, vascular, and renal diseases will be evaluated by the standardized methods.

Results

After the average 571 (±135) days of follow-up, a total of 90 MACEs (5.7%) occurred, i.e., 13 non-fatal myocardial infarction, 68 non-fatal stroke, and 9 cardiovascular deaths. Univariable COX survival analysis revealed that only MUAC could validly predict MACEs among anthropometric characters [adjusted hazard ratio (HR) 0.89; 95% confidence interval (CI) 0.82–0.96]. In Kaplan-Meier analysis, the group of high MUAC showed the lowest MACE risk (log-rank p = 0.01). Based on OD analysis, MUAC was independently linked to higher risk of left ventricular hypertrophy (LVH) in women and left ventricular diastolic dysfunction (LVDD) in both men and women. In adjusted COX analysis, only MUAC indicated statistical significance, but all other anthropometric parameters such as BMI, waist circumference, and waist-to-hip ratio (WHR) did not indicate significance. The higher level of MUAC remained a protective factor in fully adjusted models (HR: 0.73; 95% CI: 0.59–0.91), with p-values markedly significant in men (HR: 0.69; 95% CI: 0.49–0.97) and marginally significant in women (HR: 0.0.77; 95% CI: 0.59–1.01). After considering all factors (i.e., cardiovascular risk factors, MUAC, BMI, and WHR), the fully adjusted COX regression analysis demonstrated that the increased MUAC level was linked to decreased MACE risk in both men (HR: 0.57; 95% CI: 0.37–0.88) and women (aHR: 0.64; 95% CI: 0.46–0.93).

Conclusion

Despite being associated with a higher rate of cardiac damage, higher MUAC independently and significantly conferred protection against the MACE, in the elderly cohort.

Mid-upper arm circumference is associated with liver steatosis and fibrosis in patients with metabolic-associated fatty liver disease: A population based observational study

Metabolic-associated fatty liver disease (MAFLD) is a series of liver diseases based on liver steatosis and metabolic disorders. Steatosis, as the core factor in MAFLD diagnosis, and fibrosis, as the major determinant of adverse outcomes of MAFLD, need to be assessed simply and accurately. In this study, we explored the significance of mid-upper arm circumference (MUAC) in evaluating liver steatosis and fibrosis in patients with MAFLD. We included 2397 cases with MAFLD from the 2017-2018 National Health and Nutrition Examination Surveys (NHANES) database. Liver steatosis and fibrosis were measured by vibration controlled transient elastography. Anthropometric parameters and demographic and serological data were obtained from the NHANES database. The association between MUAC and liver steatosis and fibrosis were evaluated by a multivariable linear regression model, a weighted generalized additive model, and smooth curve fitting using R. MUAC was positively associated with liver steatosis in every multivariate linear regression model (model 1: β = 3.3513; 95% confidence interval [CI], 2.7722-3.9304; model 2: β = 3.8492; 95% CI, 3.2441-4.4542; model 3: β = 2.4987; 95% CI, 1.8371-3.1604), and this positive association was consistent in both men and women and among different race groups (Mexican American, other Hispanic, non-Hispanic White, Black, Asian, and other race). On the other hand, MUAC was positively associated with liver fibrosis in every multivariate linear regression model, and this positive association also was consistent in both men and women and among non-Hispanic White and Black populations. Increased MUAC was positively associated with liver steatosis and fibrosis in patients with MAFLD. This was particularly true for MUAC ≥ 42.0 cm. MUAC might be a simple and convenient evaluation tool for MAFLD.

Leg and arm adiposity is inversely associated with diastolic hypertension in young and middle-aged United States adults

BACKGROUND

We sought to determine the association between appendicular adiposity and hypertension, with the purpose of better understanding the role of body fat distribution on blood pressure (BP).

METHODS

We included 7411 adults aged 20 to 59 who were not taking antihypertensives and without cardiovascular disease from the 2011 to 2018 National Health and Nutrition Examination Surveys. Leg & arm adiposity, determined via dual-energy X-ray absorptiometry scans, was defined as percent of total body fat present in legs/arms (leg/total%, arm/total%). Measures were categorized into sex-specific tertiles. We estimated change in BP and odds ratios (ORs) of hypertension (BP ≥ 130/80) and hypertension subtypes using multivariable, survey design-adjusted linear & logistic regression, respectively.

RESULTS

Of the participants, 49% were female, the average (standard deviation) age was 37.4 (0.3) years, and 24% had hypertension. Those in the highest tertile (T3) of leg/total% had 30% decreased adjusted ORs (aOR) of hypertension compared to the lowest tertile (T1; aOR, 0.70; 95% confidence interval [95% CI], 0.55-0.89). This association was not significant for arm/total% (0.89, 0.68-1.17). T3 of leg/total% was associated with 49% lower, 41% lower, and unchanged relative odds of isolated diastolic hypertension (IDH), systolic-diastolic hypertension (SDH), and isolated systolic hypertension (ISH) compared to T1 (IDH: 0.51, 0.37-0.70; SDH: 0.59, 0.43-0.80; ISH: 1.06, 0.70-1.59). For every 10% increase in leg/total%, diastolic BP decreased by an adjusted mean 3.5 mmHg (95% CI, - 4.8 to - 2.2) in males and 1.8 mmHg (95% CI, - 2.8 to - 0.8) in females (P < 0.001 for both).

CONCLUSIONS

A greater proportional distribution of fat around the legs is inversely, independently associated with hypertension, and more specifically, diastolic hypertension (IDH and SDH).

Large mid-upper arm circumference is associated with reduced insulin resistance independent of BMI and waist circumference: A cross-sectional study in the Chinese population

BACKGROUND

Body mass index (BMI) is a common indicator in clinical practice, but it is not sufficient to predict insulin resistance (IR). Other anthropometric methods supplement BMI in the assessment of body composition, which can be predicted more accurately. This cross-sectional study aimed to evaluate the association between mid-upper arm circumference (MUAC), triceps skinfold (TSF) thickness, mid-arm muscle circumference (MAMC) and IR in Chinese adults.

METHODS

This cross-sectional study analyzed data from the 2009 China Health and Nutrition Survey database. The study population was divided into four groups according to the MUAC quartiles, and the homeostasis mode assessment was used to evaluate the degree of IR. Logistic regression analysis was performed to calculate odds ratios (ORs) with 95% confidence intervals (CIs), with adjustments for multiple covariates. Subgroup analyses stratified by age, sex, BMI, waist circumference (WC), smoking status, and alcohol consumption were performed.

RESULTS

In total, 8,070 participants were included in the analysis. As MUAC increased, BMI, TSF thickness, MAMC, and the proportion of IR tended to increase. However, we found that there was a significant negative association between MUAC and MAMC and IR in the logistic regression analysis, independent of BMI and WC, the ORs for the highest quartiles compared with the lowest quartiles were 0.662 (95%CI: 0.540-0.811) and 0.723 (95%CI: 0.609-0.860), respectively. There was no significant association was observed between the TSF thickness and IR (OR=1.035 [95%CI: 0.870-1.231]). The inverse associations were more pronounced among participants with lower BMI and WC. No significant age-specific differences were observed (P-heterogeneity > 0.05).

CONCLUSIONS

After adjusting for BMI and WC, MUAC was negatively associated with IR in Chinese adults, and the association between MUAC and IR was derived from arm muscle instead of subcutaneous fat. MUAC could be an additional predictor of IR besides BMI and WC in clinical practice.

Body composition of the upper limb associated with hypertension, hypercholesterolemia, and diabetes

The associations between segmental body composition and metabolic diseases remain equivocal. This study aimed to investigate this association using the example of U.S. adults. This cross-sectional study included 12,148 participants from the National Health and Nutrition Examination Survey (NHANES) (2011-2018). Multivariable logistic regression models were used to estimate associations between segmental body composition quartiles of hypertension, hypercholesterolemia, and diabetes. Among 12,148 participants, 3,569, 5,683, and 1,212 had hypertension, hypercholesterolemia, and diabetes, respectively. After adjusting for potential confounders, increased percent upper limb lean body mass was associated with a lower risk of hypertension (OR= 0.88, 95%CI: 0.84, 0.92, P _trend<0.001), hypercholesterolemia (OR= 0.93, 95%CI: 0.89, 0.96, P _trend<0.001), and diabetes (OR= 0.96, 95%CI: 0.95, 0.98, P _trend<0.001). Increased upper limb fat mass is associated with an increased risk of hypertension (OR= 1.11, 95%CI: 1.07, 1.15, P _trend<0.001), hypercholesterolemia (OR= 1.05, 95%CI: 1.01, 1.09, P _trend=0.07), and diabetes (OR= 1.03, 95%CI: 1.01, 1.05, P _trend=0.014). The same correlations were found in the torso and whole-body composition parameters. We observed that for women, lean body mass has a better protective effect on metabolic diseases [hypertension (OR= 0.88, 95%CI: 0.82, 0.93), hypercholesteremia (OR =0.86, 95%CI: 0.81, 0.92), diabetes (OR= 0.97, 95%CI: 0.85, 0.99)]; for men, increased body fat is associated with greater risk of metabolic disease[hypertension (OR= 1.24, 95%CI: 1.15, 1.33), hypercholesteremia (OR =1.09, 95%CI: 1.01, 1.18), diabetes (OR= 1.06, 95%CI: 1.01, 1.10)]. There were significant differences between different gender. These findings suggested that upper limb and torso adiposity should be considered when assessing chronic metabolic disease risk using body composition.

The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese

In order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529 cases were involved for analyzing the association between diabetes and BMI trajectories or MUAC trajectories. Growth mixture modeling was conducted among the prediabetic Chinese population to explore the trajectories of BMI and MUAC, and logistic regression was applied to evaluate the association between these trajectories and the risk of diabetes. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to assess the feasibility of prediction. BMI and MUAC were categorized into 4-class trajectories, respectively. Statistically significant associations were observed between diabetes in certain BMI and MUAC trajectories. The AUC for trajectories of BMI and MUAC to predict diabetes was 0.752 (95% CI: 0.690-0.814). A simple cross-validation using logistic regression indicated an acceptable efficiency of the prediction. Diabetes prevention programs should emphasize the significance of body weight control and maintaining skeletal muscle mass and resistance training should be recommended for prediabetes.