Comparative assessment of anthropometric and bioimpedence methods for determining adiposity

Bioelectrical impedance analysis predicts prehypertension and hypertension: A hospital-based cross-sectional study

Background

Hypertension prediction using anthropometry and bioimpedance offers practical advantages for screening. We aimed to analyze various anthropometric and bioelectrical impedance (BIA) estimates as predictive markers of prehypertension and hypertension.

Methods

This cross-sectional analysis included 432 adult participants recruited from the medicine outpatient department of a tertiary hospital. Blood pressure measurements; anthropometric measurements of weight, body mass index, waist circumference, and hip circumference; and BIA (Omron HBF 375) were performed for body fat%, resting metabolic rate, visceral fat level, and skeletal muscle percentage.

Results

Of the 432 participants comprising 220 males and 212 females, 36.8% were normotensive, 42% were prehypertensive, and 21% were hypertensive. Visceral fat (r 0.662, 95% CI: 0.60-0.72, P < 0.001) and resting metabolic rate (r 0.589, 95% CI: 0.52-0.65, P < 0.001) had the highest positive correlation, while skeletal muscle percentage (r -0.551, 95% CI: -0.62 to -0.48, P < 0.001) had a negative correlation with systolic blood pressure according to bivariate analysis. According to the receiver operating characteristic curve analysis for predicting hypertension, visceral fat volume had an area under curve (AUC) of 0.913, and resting metabolic rate had an AUC of 0.968, indicating the best predictive accuracy.

Conclusion

Multiple BIA estimates, including high visceral fat content, resting metabolic rate, and adipose marker levels combined with low skeletal muscle percentage, were strongly associated with hypertension. Our analysis suggested the superiority of bioimpedance predictors over anthropometry-based prediction modeling alone for screening for hypertension in clinical practice.

Association between ultraprocessed food consumption and excess adiposity in children and adolescents: A systematic review

Ultraprocessed foods (UPF) consumption is associated with excess adiposity in adults, but this linkage remains unclear among children and adolescents. The present systematic review sought to address this research gap. Publications up to November 2023 were retrieved from PubMed, Web of Science, and Scopus databases. Outcomes included overweight/obesity anthropometric and body composition indicators; the exposure was UPF consumption based on the NOVA classification system. The review included 23 studies (i.e., 8 cohort and 15 cross-sectional); approximately half were carried out in Brazil. Inconclusive and heterogeneous evidence exists as few cohort studies found positive/mixed associations between UPF consumption and excess adiposity in pediatric populations, whereas most cross-sectional studies reported null associations. Such inconsistencies may be attributed to underlying methodological issues, especially heterogeneity in the outcomes assessed and UPF consumption operationalization and/or categorization. Future studies should adopt longitudinal designs with sufficiently extended follow-up periods, account for relevant confounding factors, employ validated and standardized measurement tools to assess dietary exposure, ensure consistent operationalization of variables, and encompass diverse geographic contexts. Ultimately, strengthening the quality of existing research evidence may better inform current and forthcoming policy and practice interventions aimed at mitigating the increasing prevalence of overweight/obesity in childhood and across the life course.

Body composition is related to cognitive function among young adults in Ghana

BACKGROUND

A growing body of evidence suggests that obesity can affect cognitive function. However, it is unclear whether this effect is independent of obesity-related comorbidities. This study thus sought to determine the association between body composition and cognitive function of young adults in Ghana with less predisposition to obesity-related comorbidities.

METHODS

A cross-sectional study design was employed, involving 381 participants recruited by simple random sampling. After consenting, participants completed questionnaires that assessed sociodemographic characteristics, along with assessments for anthropometric measures and cognitive function. Analyses for associations were conducted by either Pearson's correlation test or chi-Square test of independence.

RESULTS

Over half (60%) of participants were females and 69.6% were in the first year with a mean age of 20.18 ± 2.52 years. Based on Pearson's correlation test, no significant association was found between Body Mass Index (BMI) and Waist to Hip Ratio (WHR), and Trail Making Test-A and B (TMT-A and TMT-B). Nonetheless, a chi-square test showed a significant association, between BMI and TMT-A (p = 0.01), and WHR and both TMT-A (p = 0.001) and TMT-B (p = 0.02). Weak direct correlations were found between body fat percentage and TMT-A (r = 0.120, p = 0.019) and TMT-B (r = 0.133, p = 0.009). Further, a weak inverse correlation was found between muscle mass and TMT-A (r = - 0.141, p = 0.006) and TMT-B (r = - 0.144, p = 0.005).

CONCLUSION

High body fat, low muscle mass and body fat distribution may have a significant association with cognitive functions and must be considered in obesity interventions. This study provided more insight on the association between BMI and cognitive function and would be helpful in designing new weight management interventions or modifying existing interventions to consider the influence of obesity on cognitive function.

Influences of sex chromosome aneuploidy on height, weight, and body mass index in human childhood and adolescence

Sex chromosome aneuploidies (SCAs) are collectively common conditions caused by carriage of a sex chromosome dosage other than XX for females and XY for males. Increases in sex chromosome dosage (SCD) have been shown to have an inverted-U association with height, but we lack combined studies of SCA effects on height and weight, and it is not known if any such effects vary with age. Here, we study norm-derived height and weight z-scores in 177 youth spanning 8 SCA karyotypes (XXX, XXY, XYY, XXXX, XXXY, XXYY, XXXXX, and XXXXY). We replicate a previously described inverted-U association between mounting SCD and height, and further show that there is also a muted version of this effect for weight: both phenotypes are elevated until SCD reaches 4 for females and 5 for males but decrease thereafter. We next use 266 longitudinal measures available from a subset of karyotypes (XXX, XXY, XYY, and XXYY) to show that mean height in these SCAs diverges further from norms with increasing age. As weight does not diverge from norms with increasing age, BMI decreases with increasing age. These findings extend our understanding of growth as an important clinical outcome in SCA, and as a key context for known effects of SCA on diverse organ systems that scale with body size.

Haematological Indices and Antioxidant Enzyme Activity in Ghanaian Stroke Patients

Background

Stroke is a cardiovascular disorder causing mortality globally and long-lasting harm worldwide. The disease occurs when the blood flow to the brain is either interrupted or blocked. This disruption leads to the increase in reactive oxygen species (ROS), especially superoxide free radicals, resulting in oxidative stress. The superoxide radicals are removed by superoxide dismutase (SOD), a key antioxidant enzyme. In this work, we investigated haematological indices and superoxide dismutase enzyme activity in Ghanaian patients with stroke and healthy control participants.

Materials and Methods

Thirty stroke patients attending a stroke clinic and thirty apparently healthy control participants were recruited into the study. Blood samples were collected to determine haematological indices and SOD enzyme activity in red blood cells.

Results

The stroke patients had significantly high blood parameters such as white blood cell (p < 0.001), neutrophil (p < 0.001), lymphocyte (p = 0.003), and eosinophil (p < 0.001) comparing with study participants without stroke, who were the control group in the study. Other blood parameters such as red blood cell, (p < 0.001), haemoglobin (p < 0.001), and haematocrit (p < 0.001) levels and mean cell haemoglobin concentration (p = 0.030), platelet (p = 0.010), and plateletcrit (p = 0.027) were high in stroke patients comparing with study control participants and statistically significant. Blood lymphocyte levels observed in stroke patients correlated negatively and significantly with SOD activity levels. SOD activity levels were significantly lower in stroke patients compared with the control group (p < 0.001). Low values of the antioxidant enzyme SOD activity levels, lymphocytes, and high values of plateletcrit were significant predictors of stroke.

Conclusion

Haematological parameters such as WBC, lymphocyte, platelet levels, and red cell indices were significantly different in the stroke patients being studied. There was negative correlation between lymphocyte significantly with SOD activity and high oxidative stress in stroke patients compared with the control group. Lymphocytes and plateletcrit levels were also good predictors of the occurrence of stroke.

Comparative Assessment of the Utility of Anthropometric and Bioelectrical Impedance Indices as Potential Predictors of Hypertension within a Ghanaian Adult Population: A Cross-Sectional Study

Background

Hypertension is an important public health concern that is claiming millions of lives worldwide. In sub-Saharan African countries, where some of the highest prevalence rates are being recorded, sufficient attention has not been given to its control.

Objective

The aim of this study was to determine the association and predictive potential of different anthropometric and bioelectrical impedance analysis (BIA) measures for hypertension.

Methods

A total of 812 individuals (204 men and 608 women) were enrolled, and their blood pressure measurement was determined. Direct anthropometric measures (weight, height, waist circumference (WC), and hip circumference) and derived anthropometric measures (body mass index, conicity index, abdominal volume index (AVI), and body adiposity index) were determined. BIA indices investigated included visceral fat level (VF), percentage body fat (%BF), resting metabolic rate (RMR), and skeletal muscle mass.

Results

A prevalence of 31.28% was observed for hypertension in the total study population, with males having a slightly higher prevalence than females. Except for the skeletal muscle mass, all the other indices measured showed an increasing trend from normotension to prehypertension and hypertension. Age and visceral fat level showed the highest correlation with systolic blood pressure for both genders. Receiver operator characteristic analysis showed that age was the best predictor of hypertension in both genders, whereas, in predicting prehypertension, RMR was the best predictor in males, and WC was the best predictor in females. VF, WC, and AVI were other good predictors of hypertension in this study population. However, BMI and % BF had a low predictive value for hypertension.

Conclusion

The result of this study shows that within this study population in addition to age, measures of central obesity rather than general obesity are the likely drivers of the hypertension epidemic; thus, measures aimed at controlling central obesity may offer some therapeutic and preventive advantage.

Evaluation of the Relationships between Simple Anthropometric Measures and Bioelectrical Impedance Assessment Variables with Multivariate Linear Regression Models to Estimate Body Composition and Fat Distribution in Adults: Preliminary Results

BACKGROUND

Overweight and obesity are conditions associated with sedentary lifestyle and accumulation of abdominal fat, determining increased mortality, favoring chronic diseases, and increasing cardiovascular risk. Although the evaluation of body composition and fat distribution are highly relevant, the high cost of the gold standard techniques limits their wide utilization. Therefore, the aim of this work was to explore the relationships between simple anthropometric measures and BIA variables using multivariate linear regression models to estimate body composition and fat distribution in adults.

METHODS

In this cross-sectional study, sixty-eight adult individuals (20 males and 48 females) were subjected to bioelectrical impedance analysis (BIA), anthropometric measurements (waist circumference (WC), neck circumference (NC), mid-arm circumference (MAC)), allowing the calculation of conicity index (C-index), fat mass/fat-free mass (FM/FFM) ratios, body mass index (BMI) and body shape index (ABSI). Statistical analyzes were performed with the R program. Nonparametric Statistical tests were applied to compare the characteristics of participants of the groups (normal weight, overweight and obese). For qualitative variables, the Fisher's exact test was applied, and for quantitative variables, the paired Wilcoxon signed-rank test. To evaluate the linear association between each pair of variables, the Pearson correlation coefficient was calculated, and Multivariate linear regression models were adjusted using the stepwise variable selection method, with Akaike Information Criterion (p ≤ 0.05).

RESULTS

BIA variables with the highest correlations with anthropometric measures were total body water (TBW), body fat percentage (BFP), FM, FFM and FM/FFM. The multiple linear regression analysis showed, in general, that the same variables can be estimated through simple anthropometric measures.

CONCLUSIONS

The assessment of fat distribution in the body is desirable for the diagnosis and definition of obesity severity. However, the high cost of the instruments (dual energy X-ray absorptiometry, hydrostatic weighing, air displacement plethysmography, computed tomography, magnetic resonance) to assess it, favors the use of BMI in the clinical practice. Nevertheless, BMI does not represent a real fat distribution and body fat percentage. This highlights the relevance of the findings of the current study, since simple anthropometric variables can be used to estimate important BIA variables that are related to fat distribution and body composition.