Measurement Of Body Fat Percentage Research Articles

The thin fat paradox: Understanding normal weight obesity and its clinical relevance

Obesity, defined by the World Health Organization (WHO) as an excess accumulation of body fat or body fat percentage (BFP) associated with clear health risks, presents a significant global challenge. While Body Mass Index (BMI) serves as a conventional metric for identifying obesity, it fails to account for body composition variations, such as distinguishing between fat-free mass and adipose tissue. Consequently, individuals with normal BMI may exhibit excessive body fat (BFP≥30%), termed Normal Weight Obesity (NWO). In contrast, others with normal BMI and normal body fat are termed Normal Weight Lean (NWL). NWO significantly elevates the risks of various metabolic disorders, including hyperglycemia, diabetes, hypertension, dyslipidemia, and reduced HDL levels. Moreover, NWO is associated with an increased risk of cardiovascular diseases (CVD), hypertension, low HDL, central obesity, and muscle weakness. Individuals with NWO face a heightened risk of developing cardiometabolic diseases, including atherosclerosis, coronary artery disease, stroke, and heart failure, due to the adverse effects of excess body fat on cardiovascular health. Furthermore, NWO is associated with insulin resistance, inflammation, and endothelial dysfunction, further exacerbating the risk of metabolic disorders and cardiovascular complications. Early identification of NWO is crucial for implementing preventive measures and lifestyle interventions to mitigate these health risks. Integrating body fat percentage measurements into nutritional screening protocols in healthcare facilities is essential for identifying individuals at risk of NWO and initiating appropriate interventions to prevent the onset of cardiometabolic diseases. This study aims to provide comprehensive insights into Normal-Weight Obesity (NWO) and its potential health implications.

More dietary advice may be needed to support healthy body composition for children with cerebral palsy in Aotearoa New Zealand

The available literature on the nutritional status of children with cerebral palsy (CP) worldwide has identified high rates of malnutrition, specifically undernutrition(1). However, there is a current lack of clear CP-specific dietary guidelines for children with CP across all functional levels. Standard reference tools such as estimated energy requirement (EER) and recommended dietary intake (RDI) may overestimate requirements in children with CP, especially those with reduced mobility and activity levels. Furthermore, for children with severe CP, body composition data indicates higher risks of obesity and obesity-related conditions(2). There can be a wide range of functional abilities, classifiable with tools such as the Gross Motor Function Classification System (GMFCS) and the Eating and Drinking Ability Classification System (EDACS). The majority of nutrition-related CP literature focuses on children requiring assistance for feeding (EDACS IV-V) with little information available for children with higher levels of functional independence. The aim of this study was to determine whether children with CP had received any prior dietary guidance for healthy body composition and to summarise the type of advice received. Children aged 5-12 years and their whānau were invited to participate in a study where a purpose-developed questionnaire captured their history of receiving tailored dietary recommendations for CP. Body composition was assessed via whole-body dual-energy X-ray absorptiometry scan. Nine participants (6 males, median age: 10y, n = 2 Māori), across GMFCS levels I-IV and EDACS levels I-III took part in the study. Out of 9 children, 5 (55%) indicated that their child had never received dietary advice, 3 of whom were classified as obese or overweight based on growth chart percentiles using their measures of body fat percentage, 1 was classified as underweight and 1 was within the healthy ranges. Of the 4 who had previously received advice, its nature was reported as in support of weight gain (n = 3), and weight loss (n = 1). All 4 received dietary advice from a dietitian and 1 reported some additional advice from a pediatrician and/or orthopedic doctor. Two of the children who had received dietary advice fell within a healthy body fat percentage based on the growth chart percentiles at the time of the study, while the other two were classified as overweight or obese. The results indicate the importance of developing clear dietary guidance for children with CP which may differ from that for typically developing children, particularly depending upon CP subtype diagnosis and functional level, in order to support healthy body composition.

Short-term impact of a healthy and typical Australian dietary pattern on cardiometabolic outcomes: insights from a randomised, cross-over feeding study

Immune Health Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, 2305 Australia.Cardiovascular disease (CVD) remains a major cause of global mortality. Poor diet quality, characterised by excessive consumption of energy-dense, nutrient-poor foods and insufficient intake of fruits, vegetables, and whole grains, is associated with an increased risk of CVD(1). This study compares the impact of two short-term dietary interventions, a Healthy Australian Diet adhering to national guidelines and a Typical Australian Diet representing current national consumption patterns, on several cardiometabolic outcomes. These outcomes include body weight, waist circumference (WC), body fat percentage (BFP), blood pressure (BP), fasting blood lipids and glucose concentrations. Data from an eight-week randomised, cross-over feeding study involving 34 adults (53% female, age 38.4 ± 18.1 years) were analysed, with participants randomly assigned to consume each diet for two weeks, separated by a two-week washout period. During each feeding phase, all food items were provided to ensure compliance. The Healthy Australian Diet adhered to the Australian Dietary Guidelines(2), including a balanced intake of the five food groups and meeting Acceptable Macronutrient Distribution Range targets(3), with saturated fat limited to ≤10% of energy. The Typical Australian Diet was formulated based on apparent consumption patterns in Australia(4), setting total fat intake at 40% of energy and total saturated fat at 15% of energy. Comprehensive data collection occurred at four key visits: week 0 (end of run-in; baseline 1), week 2 (post-feeding phase 1), week 4 (end of washout, baseline 2), and week 8 (post-feeding phase 2). Trained personnel measured WC using a tensible tape, while body weight and BFP measurements were obtained using bioimpedance analysis (Inbody 270; Biospace Co, Seoul, Korea). Blood pressure was recorded using the Uscom BP+ supra-systolic oscillometric central blood pressure device. Blood glucose and lipid (triglycerides, total-, low-density lipoprotein- [LDL] and high-density lipoprotein- [HDL] cholesterol) concentrations were measured after a 12-hour fast by an accredited pathology service. Differential changes in cardiometabolic variables between intervention groups were evaluated using linear mixed-effect models, adjusting for diet sequence, feeding phase, and subject ID as a random variable to account for potential autocorrelation. Post-hoc pairwise comparisons were conducted to assess the impact effects of each diet. There were no significant differences between the Healthy Australian Diet and the Typical Australian Diet with respect to weight, BFP, WC, blood triglycerides, systolic and diastolic BP. However, the Healthy Australian Diet led to a significantly greater decrease in total-, LDL-, HDL- and non-HDL cholesterol, and fasting blood glucose relative to the Typical Australian Diet (p<0.001). The results underscore the importance of promoting dietary intakes that align with Australian Dietary Guidelines for optimising the risk of CVD and impaired glucose tolerance. Conversely, the Typical Australian Dietary pattern demonstrated detrimental cardiometabolic effects over a short period of just two weeks.

Relationship of obesity assessed by Body Mass Index, waist circumference and body fat percentage measurement methods to epicardial fat thickness in non-diabetic young adults

Relationship of obesity assessed by Body Mass Index, waist circumference and body fat percentage measurement methods to epicardial fat thickness in non-diabetic young adults

Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics

PurposeExamine the association between obesity and clinical outcomes in early breast cancer and assess if patient, tumor, and treatment characteristics modify such associations in Malmö Diet and Cancer Study patients (MDCS).MethodsThe MDCS enrolled 17,035 Swedish women from 1991 to 1996. At enrollment, participants' body mass index (BMI), waist circumference and body fat percentage measures were collected. We identified all female MDCS participants with invasive breast cancer from 1991 to 2014. Follow-up began at breast cancer diagnosis and ended at breast cancer recurrence (BCR), death, emigration, or June 8, 2020. The World Health Organization guidelines were used to classify BMI, waist circumference, and body fat percentage into three categories of healthy weight, overweight, and obesity. We fit Cox regression models to compute adjusted hazard ratios (HRs) with 95% confidence intervals (CI) of BCR according to body composition. To evaluate effect measure modification, we stratified Cox models by patient, tumor, and treatment characteristics.ResultsIn total, 263 BCRs were diagnosed over 12,816 person-years among 1099 breast cancer patients with a median follow-up of 11.1 years. Obesity according to BMI (HR = 1.44 [95%CI 1.00–2.07]), waist circumference (HR = 1.31 [95%CI 0.98–1.77]), and body fat percentage (HR = 1.41 [95%CI 1.02–1.98]) was associated with increased risk of BCR compared with healthy weight. Obesity was stronger associated with BCR in patients with low socioeconomic position (HR = 2.55 [95%CI 1.08–6.02]), larger tumors > 20 mm (HR = 2.68 [95%CI 1.42–5.06]), estrogen-receptor-negative breast cancer (HR = 3.13 [95%CI 1.09–8.97]), and with adjuvant chemotherapy treatment (HR = 2.06 [95%CI 1.08–4.31]).ConclusionHigher pre-diagnostic BMI, waist circumference, and body fat percentage was associated with increased risk of BCR. The association between obesity and BCR appears dependent on patient, tumor, and treatment characteristics.

Using Bayesian Ridge Algorithm to Predict Effectiveness of Body Fat Measurement

Body fat is an important aspect in understanding and managing one's physical condition. Accurate measurement of body fat percentage is essential to help accurately plan future health plans. Currently, the method of measuring body fat is still traditional and quite difficult, so what is needed is a more effective method. The Bayesian Ridge Algorithm is a linear regression technique that uses Bayesian inference to estimate the parameters of the model. In this study, it was used to predict the effectiveness of measuring body fat, which is a method often used to evaluate a person's overall health and physical condition. This algorithm takes into account factors such as age, gender, and body mass index (BMI) to make predictions about a person's body fat percentage. The results from this study can be used to improve the accuracy of body fat measurement and help individuals better understand and manage their health. The results of this study indicate that the model has very high accuracy (more than 99%).

Overweight and obesity screening indicator using neck circumference

Background: Overweight and obesity can be assessed through anthropometric measurements using the body mass index (BMI). Some studies suggest that neck fat is positively correlated with visceral fat, insulin resistance, and metabolic syndrome. Neck circumference has been shown to be closely correlated with BMI and can be used as a practical screening tool for identifying overweight or obese individuals in both men and women. However, the correlation of neck circumference with measurements of body fat percentage in obesity has not been studied. Methods: This study is an analytical study that conducted sensitivity and specificity analyses of neck circumference to describe indicators of overweight and obesity in children. Data collected included neck circumference, weight, height (converted into BMI), and other characteristics of the children. Neck circumference measurements were taken using neck circumference tape. Results: The results showed that the body weight of school-age children had an average of 28.3 kg. Height had an average of 133.2 cm. Neck circumference measurements had an average of 30.3 cm. The correlation analysis using the Pearson product moment test showed a significant value of r=0.483 and p=0.00. Conclusions: There is a significant relationship between neck circumference and BMI. The greater the neck circumference, the greater the BMI, and the area under the curve (AUC) of the ROC curve indicates that neck circumference is a better diagnostic tool for identifying BMI. The results of the ROC curve showed a UAC value of 0.783, indicating that neck circumference can diagnose obesity with an accuracy of 78.3%.

Kadar Lemak Tubuh Pemain Bola Basket SMA Negeri 3 Kabupaten Ciamis (Berdasarkan Posisi Pemain)

This study aims to determine how much body fat percentage in male and female students of the Ciamis Regency Public High School 3 basketball team. To the objectives of the study above, the author uses survey methods using test and measurement techniques. The population of this study was male students and female students of SMA Negeri 3 Ciamis Regency totaling 30 people consisting of 15 boys and 15 girls. The research instrument used to collect the data was the measurement of fat percentage using a skinfold tool. Based on data analysis using SPSS series 22, the results of data processing are as follows: 1. The lowest description of fat measurement data in men was 16.50 and the highest description of fat measurement data was 37.90. The lowest fat measurement data description in the princess was 19.20 and the highest fat measurement data description was 35.60.2. The normality data for the female is 0.938 > 0.05 and the normality data for the male is 0.729 > 0.05 meaning that the data for the male and female are normally distributed, 3. The body fat percentage value for the girls was 26.55% while the body fat percentage value for the boys was 26.01%. The results showed that the measurement of body fat percentage in male and female students of SMA Negeri 3 Ciamis Regency was included in the excess category of the norm, namely 15-20% of the normal category for boys and the norm of 20-25% of the normal category for girls.

Agreement of body adiposity index (BAI), bioimpedance analysis and ultrasound scanning in determining body fat

BACKGROUND: The steadily increasing number of people with obesity requires the development of simple and accurate methodological approaches to assess the absolute and relative amount of body fat mass. The body adiposity index (BAI) is one of the indices proposed to assess the body fat percentage. However, the comparison analysis of common methods, i.e., of bio-electrical impedance analysis and ultrasound scanning, and BAI was not performed for the Russian population.AIM: Comparison analysis of the body fat percentage estimates by bio-electrical impedance analysis, ultrasound scanning, and body adiposity index in the group of adult male and females.MATERIALS AND METHODS: An examination of healthy males and females from Moscow was conducted. Height, weight, waist and hip circumferences were measured. The body fat percentage was obtained by bio-electrical impedance analysis — BIA (ABC-02 Medas), ultrasound scanning — US (BodyMetrixTM, IntelaMetrix), and body adiposity index.RESULTS: 263 females and 134 males aged 18 to 73 years participated in the study. Correlation coefficients between BAI values and the body fat percentage obtained by BIA and US were 0.749 and 0.763 (p<0.000), respectively. Comparison of body fat percentage measurements obtained by BAI, BIA and US showed the low agreement (ССС<0.90) between BAI and other methods in pooled sample as well as in the female and male groups. Comparison of the US and BAI methods revealed higher level of agreement (ССС=0.84 [0.80–0.86]) and no systematic bias. Lower level of agreement was obtained in the group of males.CONCLUSION: Conducted study allows to conclude that, at the individual level, BAI is not an appropriate method for estimating the body fat percentage relatively to other indirect methods. However, all three methods can be used in the group of pooled males and females when testing at the population level.

Influence of BMI, Body Fat Percent, Physical Activity, on Sports Fitness; Correlation Study on Students of SMP Negeri 3 Bandar Lampung

This study aims to determine the relationship between BMI, percent body fat, and physical activity on physical fitness of VIII grade students of SMP Negeri 3 Bandar Lampung. This type of research is quantitative with a correlational approach. The population in this study were VIII grade students of SMP Negeri 3 Bandar Lampung aged 13-14 years as many as 100 people, based on total sampling technique. The instruments used to measure BMI are scales and meters, measurement of body fat percentage is done in several parts, namely biceps, triceps subscapula, and suprailliaca, physical activity using questioner Physical Activity Level, Physical fitness is measured by the Physical Fitness Test (TKJI) age 13-15 years. Data analysis techniques using Pearson Correlation Product Moment analysis. The results showed that (1) There is a significant influence between BMI on physical fitness of VIII grade students of SMP Negeri 3 Bandar Lampung with r count 0.374. (2) There is a significant effect of body fat percent on the physical fitness of VIII grade students of SMP Negeri 3 Bandar Lampung with r count 0.439. (3) There is a significant influence between physical activity on physical fitness of VIII grade students of SMP Negeri 3 Bandar Lampung with r count. (4) There is a significant influence of BMI, body fat percent, and physical activity on the physical fitness of students in class VIII of SMP Negeri 3 Bandar Lampung with r count. (5) Physical activity has a greater influence on the physical fitness of VIII grade students of SMP Negeri 3 Bandar Lampung with r count. The coefficient of determination shows that physical activity has an influence of 40.96% on physical fitness.

Prediksi Persentase Body Fat Menggunakan Algoritma CART dan M5’

Body Fat Percentage (BFP) is a measurement of total body fat that is used as an accurate measurement for the diagnosis of obesity. BFP measurement is sometimes difficult and inconvenient to perform, even though the picture of BFP’s value is very important for someone to find out the chances of being obese. To overcome this, data mining techniques can be used to measure the predictions of BFP values in a more practical way. This study implements data mining techniques, namely the CART and M5’ algorithm to predict a person's BFP value based on his/her body measurement. The CART algorithm uses the sample average values at leaf nodes to make numerical predictions, while the M5' algorithm builds a regression model for each leaf node with a hybrid approach. Regression trees provide a simple way of explaining the relationship between features and numerical results, but more complex model trees also provide more accurate results. In this study, the results show that the M5' algorithm is superior to the BFP dataset with a correlation value of 0.86 and an MAE value of 3.86.

Proteomic indicators of health relate to Alzheimer’s and neurodegenerative disease biomarkers

AbstractBackgroundPrior studies suggest that peripheral health and comorbid disease can influence Alzheimer’s disease (AD) pathology and neurodegenerative processes. However, no studies to date have comprehensively examined how measures of peripheral health and risk for non‐neurological disease relate to biomarkers commonly used in AD research. The present study examined the association between 16 protein‐based health indicators and plasma biomarkers of brain amyloid‐β (Aβ) accumulation, phosphorylated tau, neurodegeneration, and reactive astrogliosis.MethodPlasma‐based biomarkers of AD pathology (Aβ42/40 ratio, pTau‐181), neurodegeneration (neurofilament light chain [NfL]), and reactive astrogliosis (glial fibrillary acidic protein [GFAP]) were measured in Baltimore Longitudinal Study of Aging participants using Quanterix SIMOA assays. Concurrently, the SomaScan proteomic platform was used to measure 7000 proteins, from which 16 proteomic signatures of health and disease risk were derived (i.e., SomaSignal Tests). A subset of participants also received PiB PET scans to assess cortical amyloid. We examined the relationship between health indicators and AD/neurodegeneration biomarkers using Pearson and Spearman correlations and linear regression analyses adjusted for age, sex, race, education, and APOEe4.ResultThe primary analysis included 720 participants (Table 1). Correlation analyses revealed several strong associations between measures of health/disease risk and plasma Aβ42/40 ratio, pTau‐181, NfL, and GFAP levels (Figure 1a). Notably, higher risk scores for heart failure, primary and secondary cardiovascular disease, and kidney disease were consistently positively associated with greater pTau‐181, NfL, and GFAP, and lower with Aβ42/40 ratio. Measures of body fat percentage, lean body mass, and visceral fat were associated with pTau‐181, NfL, and GFAP, whereas resting energy rate was only associated with NfL and GFAP. These relationships were maintained after adjusting for demographic factors and APOEe4 status (Figure 1b). Only heart failure and secondary cardiovascular disease risk scores were associated with elevated cortical amyloid (PiB+; Figure 2); these measures varied positively with cortical amyloid among participants who were PiB+, but not PiB‐ (Figure 3).ConclusionIndicators of peripheral health and disease risk demonstrate robust relationships with plasma AD, neurodegeneration, and reactive astrogliosis biomarkers. Peripheral health factors, particularly cardiovascular health, may play an important role in the pathophysiology of AD.

The Relationship between Body Fat Percentage with Vertical Jump and Sprint Performances of Football Players

Bu çalışma futbolcuların vücut yağ yüzdesi ile dikey sıçrama ve sürat performansları arasındaki ilişkinin incelenmesi amacı ile planlanmıştır. Kulüp düzeyinde futbol oynayan ortalama yaşları 25,45±4,25, ortalama boy uzunlukları 176,45±6,03 cm ve ortalama vücut ağırlıkları 74,62±6,05 kg olan, toplam 22 yetişkin futbolcu, basit rastgele örnekleme yöntemiyle araştırma için seçilmiş ve gönüllü olarak çalışmaya katılmıştır. Futbolculara antropometrik (boy uzunluğu, vücut ağırlığı, beden kitle indeksi-BKİ ve vücut yağ yüzdesi) ve performans (10-30 metre sprint ve dikey sıçrama) ölçümleri uygulanmıştır. Değişkenler arasındaki ilişkilerin tespit edilmesi için Pearson Korelasyon Katsayısı hesaplanmıştır. Futbolcularda sprint ve sıçrama performanslarının vücut yağ yüzdesi ile ilişkileri incelendiğinde, 10 metre sprint ile pozitif yönlü zayıf ilişki (r=0.474, p

Accuracy of fat fraction estimation using Dixon: experimental phantom study

Objective. Quantitative assessment of Dixon two-point and three-point technologies operation using phantom modeling in the range from 0 to 70%.Materials and methods. To simulate substances with different concentrations of the fat phase we chose direct oil-in-water emulsions. Tubes with ready-made emulsions were placed in a phantom. Emulsions based on vegetable oils were presented in the range from 0–70%. The phantom was scanned on an Optima MR450w MRI tomograph (GE, USA) in two Dixon modes: the accelerated two-point method “Lava-Flex” and the three-point method “IDEAL IQ”. A scan was performed on a GEM Flex LG Full RF coil. We calculated fat fraction (FF) using two formulas.Results. There is a linear relationship of the determined values when calculating the fat concentration in “IDEAL IQ” mode and using the formula based on Water and Fat. The accuracy of body fat percentage measurement in “IDEAL IQ” mode is higher than in “Lava-Flex” mode. According to the MR-sequence “Lava-Flex” draws attention to the overestimation of the measured values of the concentration of fat in relation to the specified values by an average of 57.6% over the entire range, with an average absolute difference of 17.2%.Conclusion. Using the “IDEAL IQ” sequence, the results of the quantitative determination of fractions by formulas were demonstrated, which are more consistent with the specified values in the phantom. In order to correctly quantify the fat fraction, it is preferable to calculate from the Water and Fat images using Equation 2. Calculations from the In-phase and Out-phase images provide ambiguous results. Phantom modeling with direct emulsions allowed us to detect the shift of the measured fat fraction.

Comparison Of A Novel Body Mass Index Equation To Body Composition Methods In Collegiate Athletes

INTRODUCTION: Accurate assessment of body composition in collegiate athletes is an effective tool to enhance training and nutrition protocols. The use of Body Mass Index (BMI) based equations for such purposes has been found to be relatively inaccurate in competitive athletes due to the inability to decipher between fat and fat-free mass. Recently, a BMI based equation developed by Nickerson et. al. (BMINICKERSON) that incorporates handgrip strength as a surrogate for lean mass was found to estimate body fat with low error in general population adults. The use of such a method in collegiate athletes may therefore be advantageous as a cost-effective and easily administered option for body composition assessment. PURPOSE: To compare the accuracy and effectiveness of BMINICKERSON with traditional body composition methods in estimating body fat percentage of Division II collegiate athletes. METHODS: Fifteen (n = 15) intercollegiate athletes (n = 9 male, 6 female) were assessed for percentage body fat using BMINICKERSON, bio-electrical impedance analysis (BIA) and seven site skinfold (SF). A One-Way repeated measures ANOVA was utilized to determine potential differences in body fat as estimated by each method. RESULTS: A significant difference in body fat percentage as assessed by the included methods was found for the sample (F = 16.78, p < 0.001). Further paired samples t-testing revealed a significantly greater body fat estimation by BMINICKERSON (20.84 % ± 6.73 %) in comparison to both BIA (t = 9.06, p < 0.001, 16.31 % ± 6.72 %) and skinfold (t = 4.57, p < 0.001, 16.34 % ± 8.34 %). Measurement of body fat percentage by BIA and skinfold did not significantly differ (t = 0.02, p = 0.98). CONCLUSION: Although use of BMINICKERSON in estimating body composition has been shown to provide relatively accurate results in the general population, the current study did not observe the same in collegiate athletes. The use of other cost-effective and easily administered methods, such as BIA and SF, may provide for more accurate estimation of body fat in the current population. Further research comparing BMINICKERSON to a gold standard measurement technique in collegiate athletes is warranted.

Tri-ponderal mass index and body mass index for estimating body fat in children in Surakarta, Indonesia

Background: The body mass index parameter is currently used to determine obesity (excess body fat) in children. Using this measure has limitations in predicting body fat, particularly in adolescents. An alternative parameter to predict body fat is the tri-ponderal mass index (TMI).Objective: The study aims to investigate the different patterns between body mass index and triponderal mass index in children and to determine the correlation of body mass index (BMI) or TMI as a predictor of body fat.Methods: This cross-sectional study of 351 subjects aged 6-18 in Surakarta (241 females; 110 males). All subjects underwent anthropometric measurements (height and weight) and body fat percentage measurements. We used equations for predicting the percent body fat in boys and girls based on their TMI and BMI.Results: TMI and BMI overall means were 13.3±2.9 vs 20.2±4.7. Among subjects less and more than 12 years, the TMI and BMI means were 13.3±2.1 vs 17.9±3.6. and 13.3±3.1 vs 20.7±4.8. The adjusted R2 of equations for predicting percent body fat based TMI and BMI were 0.76 vs 0.33 in boys and 0.89 vs 0.87 in girls).Conclusions: TMI showed greater stability with age than BMI. TMI was a better predictor for body fat percentage than BMI for both sexes, especially in boys. It is worth considering replacing body mass index with triponderal mass index to estimate body fat percentage in boys.

A Descriptive Study to Assess Relationship between Body Fat Percentage and Obesity at a Tertiary Level Health Facility

Introduction: The prevalence of obesity is increasing in Indian adults at alarming rate and causing high burden of chronic diseases due to relatively high Body Fat Percentage (BFP) compared to other ethnic groups. There is a dearth of studies on assessment of obesity by using BFP measurement. This study was undertaken to strengththe reliability of BFP in assessment of obesity. Objectives: To find out the relationship between body fat percentage and obesity among adults aged 18-59 years. Method: A total of 228 subjects were included in the study from the in-patients admitted to tertiary care hospitalby systematic random sampling method. In the interview, socio-personal characteristics were collected using pre-tested, semi-structured questionnaire. Anthropometric measurements were conducted to calculate BMI based on Asia-Pacific classification and waist circumference based on International Diabetes Federation guidelines along with body fat percentage was measured using standard guidelines. The t- test, ANOVA and correlation was used to determine the relationship between obesity and BFP. Results: A significant association between Body Fat Percentage (BFP) and obesity measured by Body Mass Index (BMI) and Waist Circumference (WC) was observed across the categories and sex. Positive correlation was observed between BMI and waist circumference (p&lt;0.001), BMI and body fat percentage (P&lt;0.001) and waist circumference and body fat percentage (P&lt;0.001). Conclusions: The study shown significant association and positive correlation between body fat percentage and obesity measured by BMI and waist circumference at lower cut-off among Indian adults indicating BFP is a reliable measure for assessment of obesity.

PERBANDINGAN STATUS GIZI MENURUT PENGUKURAN INDEKS MASSA TUBUH DAN PENGUKURAN PERSENTASE LEMAK TUBUH MENGGUNAKAN DXA SCAN DI RUMAH SAKIT X PEKANBARU

Background Obesity can occur due to the accumulation of excess fat in the body.Obesity has been declared as a global epidemic by the World Health Organization (WHO). In 2016, more than 1,9 billions adults were overweight. In 2018, it was found that 24,1% of adults in Riau Province were obese with an incidence higher in women than men. &#x0D; Research Objectives This research is an analytical study to determine the comparison of nutritional status based on the data that has been collected from body mass index (BMI) measurement and body fat percentage measurement by DXA Scan, which was carried out on 364 adults aged 19-65 years. &#x0D; Metodology The data that has been obtained from BMI measurement will be grouped to four categories and the data that has been obtained from body fat percentage will be grouped to five categories based on their gender. The bivariate analysis using paired T Test will be done to see the p value. &#x0D; Conclusion From this study, it was found that most of the subjects were obese. According to the BMI examination, about 50,27% of the subjects were categorized as obese. Meanwhile, according to the body fat percentage measurement using DXA Scan, about 89,56% of subjects were included in the obese category. Based on the p value of 0,001 that obtained from the paired t test, it can be concluded that there are significant differences between these two methods.&#x0D; &#x0D; Keywords : BMI, DXA Scan, nutritional status, obese

The Effect of Gelatinization Rice Storage on Body Fat Percentage and Short Chain Fatty Acids (Acetate) on Obesity

Background: Obesity is a problem in developed and developing countries that has a detrimental effect on health. Gelatinization rice that’s stored hot or cold can increase resistant starch and short-chain fatty acids (SCFA) especially acetate (C2). Resistant starch contributes to decreasing glycemic index (IG) of rice and blood glucose levels, while acetate contributes to GLP-1 and PYY secretion which is related to appetite and decreased body fat. Method: The experimental study design was a pre-post controlled group design with 39 obese respondents divided into three randomized treatment groups (Control, P1, and P2). The research instrument was a measurement of body fat percentage and SCFA (acetate) levels blood plasma and statistically analyze with Saphiro Wilk and Paired t-test or Wilcoxon. Results: The analysis results of gelatinized rice storage were significant for body fat percentage (p = 0.012 <0.005) and acetate (p = 0.000 <0.05) in cold storage treatment of 4 0C for 24 hours (P2). Conclusion: Gelatinized rice which is kept cold at 40C for 24 hours can reduce body fat percentage and increase acetate.

Analyzing The Impact Of Body Composition On Vertical Jump Performance In Collegiate Female Volleyball Players

The vertical jump (VJ) test is often used in sport and recreational performance sectors. Prior studies have examined the effects that anthropometric and body composition values have on VJ performance in no less than averagely fit populations. Yet, it appears that no study has evaluated the relationship between body fat percentage (BF), body mass index (BMI), lean leg mass (LLM), and trunk lean mass (TLM) on VJ performance using collegiate female volleyball players. PURPOSE: To assess the relationship between BF%, BMI, LLM, and TLM on VJ performance in collegiate female volleyball players. METHODS: After having descriptive data recorded, 12 female collegiate volleyball players had their BF%, BMI, LLM, and TLM assessed via dual-energy x-ray absorptiometry. Subjects had their reach height measured, participated in an 8 min dynamic warm-up, were then given a 4 min passive recovery (PR) period after the warmup, and then completed three familiarization jumps (ie. trials) using a VJ measurement device. After another 4 min PR period, subjects completed one series of six jumps with 30 secs of PR between each jump. Pearson Correlations were then performed between BF%, BMI, LLM, TLM, and VJ (ie. the highest of the six jumps) with significance differences determined at p < 0.05. RESULTS: A non-significant low negative correlation existed between BF% and VJ (r = -0.350, p = 0.132), yet a non-significant low correlation occurred between BMI and VJ (r = 0.371, p = 0.117), TLM and VJ (r = 0.265, p = 0.202), and LLM and VJ (r = 0.372, p = 0.117). CONCLUSIONS: BF% appears to have a low negative relationship with VJ performance in collegiate female volleyball players, while TLM, BMI, and LLM have a low relationship with VJ performance. Having a lower BF% may not necessarily predict higher jumping performance in collegiate female volleyball players. Further research may be required to determine if gender, fitness level, or a different type of body fat percentage measurement technique may play a factor when considering if BMI, BF%, LLM, and TLM have a relationship with VJ performance in athletes who specialize in sports with repetitive jumping movements.