Body fat percentage

Establishing a normative table for classifying body fat percentage in adolescents

Type of study:

Number of citations: 6

Year: 2022

Authors: Regiane De Paula Sena, Isabella Caroline Santos, Beatriz De Souza Cerqueira, Fabiano Mendes de Oliveira, Fábio Ricardo Acencio, Carina Bertoldi Franco, Braulio Henrique Magnani Branco

Journal: Journal of Human Growth and Development

Journal ranking: Q4

Key takeaways: This study established cut-off points for body fat percentage in male and female adolescents aged 16-19 years, improving clinical assessment and management of overweight and obese adolescents.

Abstract: Introduction: The prevalence of obesity in adolescents has increased worldwide, which is closely related to comorbidities in adulthood. Despite the severity of this pathology and its significant impacts on the health system, there is no international consensus on the cut-off point for the percentage of body fat for Brazilian children and adolescents, making it difficult to make an accurate and early diagnosis addition to assertive treatment. Objective: This study aimed to establish cut-off points for body fat percentage in male and female adolescents aged 16 to 19 years using bioelectrical impedance (InBody 570®). Methods: Gender-specific tables were proposed based on the percentiles 3, 5, 10, 15, 25, 50, 75, 85, 95, and 97. A total of 546 adolescents were included. Results: The body fat percentage cut-off points for the male group were: P3 = 6.0-7.0%; P5 = 7.1-8.9%; P10 = 9.0-9.8%; P15 = 9.9-11.7%; P25 = 11.8-15.5%; P50 = 15.6-21.9%; P75 = 22.0-27.8%; P85 = 27.9-36.0%; P95 = 36.1-38.0% and P97 ≥ 38.1%. For females, the cut-off points were: P3 = 9.5-10.0%; P5 = 10.1-11.0%; P10 = 11.1-11.8%; P15 = 11.9-14.0%; P25 = 14.1-19.0%; P50 = 19.1-27.1%; P75 = 27.2-29.0%; P85 = 29.1-39.9%; P95 = 40.0-51.0% and P97 ≥ 51.0%. Conclusion: The establishment of cut-off points for body fat percentage may improve the clinical assessment and management of overweight and obese adolescents.

Proposal of a normative table for body fat percentages of Brazilian young adults through bioimpedanciometry

Type of study: non-rct observational study

Number of citations: 28

Year: 2018

Authors: B. Branco, M. P. Bernuci, D. Marques, Isabelle Zanquetta Carvalho, Carlos Andrés Lopera Barrero, Fabiano Mendes de Oliveira, G. F. Ladeia, N. Junior

Journal: Journal of Exercise Rehabilitation

Journal ranking: Q2

Key takeaways: Brazilian young adults between 18 and 39 years of age can be classified into healthy and risky body fat levels using bioimpedanciometry.

Abstract: Identification of the body fat (BF) percentage allows health professionals to detect healthy or risky patterns in a population. However, no studies have elaborated BF cutoff points using the bioelectrical impedance method in young Brazilian adults. Thus, the objective of the present study was to elaborate normative tables for BF in Brazilian men and women (sedentary and physically active) between 18 and 39 years of age. A total of 3,111 adults (958 men and 2,153 women) were evaluated using bioimpedance measurements with the InBody 520 device. The data were distributed normally and divided into percentiles (P3, P10, P25, P50, P75, P90, and P97). The following values were observed: for men: P3=8.9%–12.5%; P10=12.6%–17.5%; P25=17.6%–25.3%; P50=25.4%–35.1%; P75=35.2%–43.0%; P90=43.1%–49.4% and P97=49.5%; for women: P3=18.7%–23.1%; P10=23.2%–28.7%; P25=28.8%–35.7%; P50=35.8%–42.9%; P75=43.0%–49.1%; P90=49.2%–52.1% and P97≥52.2%. These percentiles can be used to classify the adiposity of sedentary and physically active individuals evaluated by bioimpedanciometry.

Proposal of a Normative Table for Classification of Body Fat Percentage in Brazilian Jiu-Jitsu Athletes

Type of study:

Number of citations: 4

Year: 2022

Authors: Beatriz de Souza Cerqueira, Mateus Baú Cerqueira, W. Ferreira, Fabiano Mendes de-Oliveira, L. V. Andreato, Rubens Batista dos-Santos-Junior, P. Valdés-Badilla, B. Branco

Journal: International Journal of Morphology

Journal ranking: Q3

Key takeaways: A normative table for establishing body fat percentage cut-off points in Brazilian jiu-jitsu athletes has been proposed, with state-level athletes having higher fat percentages than national and international-level athletes.

Abstract: Proposal of a normative table for classification of body percentage in Brazilian jiu-jitsu athletes. SUMMARY: Previous evidence indicates that body fat can distinguish Brazilian jiu-jitsu (BJJ) athletes according to the competitive level. However, propositions of cut-off points for establishing classifications of body fat percentage for combat sports athletes and, specifically, for BJJ athletes are still incipient in the literature. In this sense, the main aim of the present study was to establish a normative table for the classification of body fat percentage in BJJ athletes. As a secondary aim, athletes were compared according to competitive level. Ninety male BJJ athletes (aged: 29.0 – 8.2 years; practice time: 6.0 – 2.1 years; body mass: 82.1 – 12.7 kg; height: 175.9 – 6.5 cm; fat mass: 16.0 – 8.9 kg; bone mineral content: 3.7 – 0.6 kg; muscle mass: 37.9 – 5.4 kg; body fat percentage: 17.3 – 6.8 %; basal metabolic rate: 1811.4 – 193.4 kcal) from different competitive levels: state (n= 42), national (n= 26) and international (n= 22) took part in this study. All athletes had their body composition measured via tetrapolar bioelectrical impedance. Percentiles p10, p25, p50, p75, and p90 were used to establish the classification. As a result, the following classification was obtained: <7.7 % (very low); ‡ 7.7–11.5 % (low); 11.6–17.0 % (medium); 17.1–24.0 % (high) and ‡ 24.1 % (very high). State-level athletes had a higher fat percentage than national and international-level athletes (p<0.05). The proposed cut-off points can help professionals responsible for sports training and nutritional prescription in monitoring the body fat of BJJ athletes.

Gender- and Gestational Age–Specific Body Fat Percentage at Birth

Type of study: non-rct observational study

Number of citations: 108

Year: 2011

Authors: C. Hawkes, J. Hourihane, L. Kenny, A. Irvine, M. Kiely, D. Murray

Journal: Pediatrics

Journal ranking: Q1

Key takeaways: Percentage body fat at birth is influenced by gestational age and gender, with accurate normative values generated from a large population-based cohort study.

Abstract: BACKGROUND: There is increasing evidence that in utero growth has both immediate and far-reaching influence on health. Birth weight and length are used as surrogate measures of in utero growth. However, these measures poorly reflect neonatal adiposity. Air-displacement plethysmography has been validated for the measurement of body fat in the neonatal population. OBJECTIVE: The goal of this study was to show the normal reference values of percentage body fat (%BF) in infants during the first 4 days of life. METHODS: As part of a large population-based birth cohort study, fat mass, fat-free mass, and %BF were measured within the first 4 days of life using air-displacement plethsymography. Infants were grouped into gestational age and gender categories. RESULTS: Of the 786 enrolled infants, fat mass, fat-free mass, and %BF were measured in 743 (94.5%) infants within the first 4 days of life. %BF increased significantly with gestational age. Mean (SD) %BF at 36 to 3767 weeks' gestation was 8.9% (3.5%); at 38 to 3967 weeks' gestation, 10.3% (4%); and at 40 to 4167 weeks' gestation, 11.2% (4.3%) (P < .001). Female infants had significantly increased mean (SD) %BF at 38 to 3967(11.1% [3.9%] vs 9.8% [3.9%]; P = .012) and at 40 to 4167 (12.5% [4.4%] vs 10% [3.9%]; P < .001) weeks' gestation compared with male infants. Gender- and gestational age–specific centiles were calculated, and a normative table was generated for reference. CONCLUSION: %BF at birth is influenced by gestational age and gender. We generated accurate %BF centiles from a large population-based cohort.

Evaluating lower limits of body fat percentage in athletes using DXA.

Type of study: non-rct observational study

Number of citations: 0

Year: 2025

Authors: Tamara D. Hew-Butler, Edward Kerr, Gloria Martinez Perez, J. Sabourin, Valerie Smith-Hale, Ruben Mendoza

Journal: Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry

Journal ranking: Q2

Key takeaways: The lower limits of whole-body fat mass in free-living competitive athletes is approximately 10% for males and 16% for females, with basketball players having the lowest and runners having the highest.

Relative fat mass (RFM) as a new estimator of whole-body fat percentage ─ A cross-sectional study in American adult individuals

Type of study: non-rct observational study

Number of citations: 242

Year: 2018

Authors: O. Woolcott, R. Bergman

Journal: Scientific Reports

Journal ranking: Q1

Key takeaways: Relative fat mass (RFM) is a more accurate estimator of whole-body fat percentage than BMI for both women and men, and reduces obesity misclassification among Mexican, European, and African-American adults.

Body fat and risk of all-cause mortality: a systematic review and dose-response meta-analysis of prospective cohort studies

Type of study: meta-analysis

Number of citations: 40

Year: 2022

Authors: Ahmad Jayedi, T. Khan, D. Aune, Alireza Emadi, Sakineh Shab-Bidar

Journal: International Journal of Obesity

Journal ranking: Q1

Key takeaways: Higher body fat content is associated with a higher risk of mortality in a J-shaped manner, with the lowest risk at 25% and 20 kg of fat mass.

Association between body fat percentage and depression: A cross-sectional study of NHANES.

Type of study: non-rct observational study

Number of citations: 7

Year: 2024

Authors: Wenjun Gu, Kunming Bao, Xiaoming Li, Shaohang Xiang, Junhao He, Jinning He, Lixin Ye, Zhidong Huang

Journal: Journal of affective disorders

Journal ranking: Q1

Key takeaways: Elevated body fat percentage is strongly associated with higher prevalence of depression, particularly in males or those in underweight and overweight groups.

Body fat percentage assessment by skinfold equation, bioimpedance and densitometry in older adults

Type of study: non-rct observational study

Number of citations: 28

Year: 2020

Authors: É. A. Silveira, Larissa Silva Barbosa, A. Rodrigues, M. Noll, C. D. de Oliveira

Journal: Archives of Public Health

Journal ranking: Q1

Key takeaways: The best agreement in estimating body fat percentage in older adults was observed between DXA and the anthropometric SF equation for men.

Abstract: Body fat estimation allows measuring changes over time attributed to interventions and treatments in different settings such as hospitals, clinical practice, nursing homes and research. However, only few studies have compared different body fat estimation methods in older adults with inconsistent results. We estimated body fat percentage (%BF) and the level of agreement among dual energy X-ray absorptiometry (DXA), bioelectrical impedance (BIA) and Durnin & Womersley's skinfold eq. (SF) in older Brazilian adults aged 60 years and older from the Elderly Project Goiânia, Brazil.The analytical sample comprised of 132 participants who had DXA data. The level of agreement for the %BF estimated by BIA, SF and DXA i.e. reference method, was examined using Bland and Altman's and Lin's plot.Overall, women had higher body mass index and %BF values measured by all three methods used. BIA and SF equation showed strong concordance to estimate body fat percentage in all participants (CCC = 0.857 and 0.861, respectively) and among women (CCC = 0.788 and 0.726, respectively) when compared to DXA. However, both methods underestimated body fat percentage in women and men with high body fat percentage. A strong level of agreement was observed between DXA and the anthropometric equation developed by Durnin & Womersley in men (CCC = 0.846), while BIA had a moderate concordance (CCC = 0.505) in this group.The examined methods indicated different body fat estimates. However, the best agreement was observed between DXA and the anthropometric SF equation for men. Future research in older adults should develop new SF equations considering different ethnic groups.

Body fat percentage is better than indicators of weight status to identify children and adolescents with unfavorable lipid profile.

Type of study: non-rct observational study

Number of citations: 27

Year: 2019

Authors: P. Oliosa, D. Zaniqueli, R. Alvim, M. Barbosa, J. Mill

Journal: Jornal de pediatria

Journal ranking: Q1

Key takeaways: Body fat percentage is better than weight status indicators like BMI and waist-to-height ratio to identify children and adolescents with unfavorable lipid profiles, especially among girls.

Predicting body fat percentage from anthropometric and laboratory measurements using artificial neural networks

Type of study: non-rct observational study

Number of citations: 29

Year: 2017

Authors: T. Ferenci, L. Kovács

Journal: Appl. Soft Comput.

Journal ranking: Q1

Key takeaways: Support vector machines slightly outperform feedforward neural networks and linear regression in predicting body fat percentage from easily measureable data, but all methods have an R2 of 44%.

Grading body fatness from limited anthropometric data.

Type of study: non-rct observational study

Number of citations: 431

Year: 1981

Authors: A. Roche, R. Sievogel, W. Chumlea, P. Webb

Journal: The American journal of clinical nutrition

Journal ranking: Q1

Key takeaways: Triceps skinfold is the best indicator of percentage body fat in children and women, while weight/stature is the best indicator of total body fat in girls and adults.

Abstract: Measurements relevant to body fatness are made commonly in clinical settings. However, associations between these measurements and body fatness are poorly known and procedures are needed to facilitate the interpretation of these measurements. Consequently, data from 405 white children and adults aged 6 to 49 yr were used to calculate the correlations between selected anthropometric measurements and estimates of percentage body fat and total body fat. Comparisons among these correlations, for children and adults of each sex, lead to conclusions that the triceps skinfold is the best single indicator of percentage body fat in children and women; weight/stature is the best single indicator of total body fat in girls and adults. In men weight/stature is the best indicator of percentage body fat and in boys the subscapular skinfold is the best indicator of total body fat. Weight/stature can be obtained using a calculator or the nomogram provided. It is recommended that these measures be obtained when there is interest in body fatness and the data compared with percentiles from a nationally representative sample.

What is the best predictor of body fat percentage for older brazilian women?

Type of study:

Number of citations: 0

Year: 2024

Authors: Vinicius De Oliveira Damasceno, Jeferson Macedo Vianna, Alexander Barreiros Cardoso Bomfim, Danilo EDSON DE SOUZA, Jakson Felix da Silva, Rubens Vinícius Letieri, André Dos Santos Costa, Jorge Perrout de Lima

Journal: Retos

Journal ranking: Q2

Key takeaways: Visser's equation 6 is the best predictor of body fat percentage in older Brazilian women, but its agreement with DXA is poor, and its specificity and sensitivity vary depending on the population in which it was developed.

Abstract: This study aimed to investigate the validity of several equations and predictive indices for estimating body fat percentage (%BF) in 152 older women, with an average age of 67.4 years and an average body mass index (BMI) of 28.65 kg/m². To this end, anthropometric measurements including height, body weight, circumferences (waist and hip), and a dual energy X-ray absorptiometry (DXA) scan were performed. All measurements were performed by trained researchers following specific protocols. The results were compared to the dual energy X-ray absorptiometry (DXA) technique, which is considered the reference method. The analyzed equations showed moderate to good correlation coefficients with DXA, with particular emphasis on Visser’s equation 6, which showed the best correlation (r = 0.752, p < 0.001). However, the agreement between the equations and DXA, as assessed by the Lin concordance coefficient, was classified as poor (ρc < 0.90). This indicates that although the equations have a positive correlation with body composition, they tend to deviate from the identity line when compared to the reference method. Additionally, the equations showed high sensitivity for detecting obesity when the cut-off point of 30% body fat was adopted, indicating a good ability to identify the presence of the condition. However, the equations, with the exception of equation 4, showed low specificity, meaning they had limited ability to detect normal individuals, resulting in a low negative predictive value. The results suggest that BF% equations and indices are dependent on the populations in which they were developed. The specificity and sensitivity of these equations may vary, and it is important to carefully select the most appropriate equation for estimating BF% in older Brazilian women. Keywords: Anthropometry; body composition; older adults.

Gender-based approach to estimate the human body fat percentage using Machine Learning

Type of study:

Number of citations: 7

Year: 2021

Authors: S. S. Alves, E. F. Ohata, N. M. Nascimento, J. M. O. D. Souza, G. Holanda, L. L. Loureiro, P. P. R. Filho

Journal: 2021 International Joint Conference on Neural Networks (IJCNN)

Journal ranking: brak

Key takeaways: Our gender-based approach using machine learning accurately estimates body fat percentage using anthropometric measures, with a MAE of 2.756 for males and 3.869 for females.

Abstract: Keeping a certain balance of body fat is essential for a healthy life, and proper nutrition is fundamental. One of the most worrying malnutrition problems is obesity, which plays a significant risk factor for chronic diseases like cardiovascular diseases, diabetes, and cancer. The Dual-energy X-ray absorp-tiometry (DXA) is the most accurate and automatic method that returns the body fat percentage; however, this method is expensive and not easily found at clinics. A lower-cost way of estimating the body fat percentage is through anthropometric measures. However, the literature has shown that estimating body fat percentage on women is challenging. In this work, we propose an approach specialized in gender to estimate body fat percentage using machine learning. Another contribution of this work is a dataset, BodyFat-163 (BF-163), containing the 12 anthropometric measures and the body fat percentage from DXA exams collected by a specialist. The dataset consists of 163 individuals (84 males and 79 females). Our experiments involved a variety of methods of regression, which includes Random Forest Regression, Extreme Gradient Boosting, Decision Tree, Support Vector Regression, Multilayer Perceptron Regression, and Least Square Support Vector Regression. The experiment results were evaluated with the metrics Mean Absolute Error (MAE), Root Mean Square Error, Mean Squared Logarithmic Error, and R2 score. Our gender-based approach successfully estimates the body fat percentage achieving a MAE = 2.756, and R2 = 0.68 on the male set and MAE = 3.869, and R2 = 0.69 on the female set.

Prediction Of Body Fat Percentage Based On Anthropometric Measurements Using Data Mining Approach

Type of study:

Number of citations: 1

Year: 2021

Authors: همسة عمرو, محمد عوض

Journal: مجلة الجامعة العربية الأمريكية للبحوث

Journal ranking: brak

Key takeaways: Artificial Neural Networks (ANNs) outperform other methods in predicting body fat percentage using anthropometric measurements, making them a valuable tool for health care data mining.

Abstract: In recent years, heart disease, diabetes, and some types of cancers have been reported as some main causes of death in most countries of the world, and obesity, which is often attributed to excess body fat, is one of the most common risk factors for these diseases. To make the vast amounts of data produced by health care information systems useful to the potential, the researchers applied knowledge discovery through predictive modeling. This study used anthropometric measurements as input data to different data mining techniques to predict body fat percentage. Fisher’s Method of Scoring was used to select the most effective features in the prediction process, which were represented by eight variables (abdomen, BMI, chest hip, neck, thigh, knee, and age). The selected features were used as input\output for data mining approaches like multiple regressions (MR), Support Vector Machine (SVM), and Artificial Neural Networks (ANNs). As a result, ANNs outperformed the other methods used to predict body fat percentage by correlation coefficient R²=0.77 with eight selected anthropometric parameters. This outperformance was attributed to ANNs high ability to predict and their understandable and implementable resulting knowledge. Therefore, the researchers concluded that ANNs could be used and applied to a dataset of the Palestinian population.

Association between Body Fat Percentage and Cardiometabolic Diseases in General Population.

Type of study: non-rct observational study

Number of citations: 1

Year: 2024

Authors: Jiayi Si, Lina Kang, Yihai Liu

Journal: Endocrine, metabolic & immune disorders drug targets

Journal ranking: Q3

Key takeaways: Higher body fat percentage levels are associated with a higher likelihood of cardiometabolic diseases, making it a powerful predictive factor.

Abstract: OBJECTIVES The body fat percentage is an indicator of overall body fat related to metabolism and inflammation. Our study aims to analyze the association between body fat percentage and the risk of cardiometabolic diseases in the general population. METHODS This was a retrospectively cross-sectional study. A total of 5084 participants enrolled from the National Health and Nutrition Examination Survey cycle of 1999-2004 were divided into quartiles according to their body fat percent levels. The body fat percentage was measured from bioelectrical impedance analysis. A history of cardiometabolic diseases, including cardiovascular disease, hypertension and diabetes mellitus, was ascertained from questionnaire, physical or laboratory examination. The association between body fat percentage and cardiometabolic diseases was investigated using multivariate logistic regression. RESULTS Compared with the lowest quartile of body fat percentage, the multivariate-adjusted odds ratio and 95% confidence interval of the highest quartile was 3.99 (1.58-10.88) for cardiovascular disease, 1.08 (1.04-1.13) for hypertension and 3.08 (1.89-5.11) for diabetes. Body fat percentage independently increased the risk of cardiometabolic diseases as a continuous variable. CONCLUSIONS Higher body fat percentage level was associated with a higher likelihood of cardiometabolic diseases, which could be a powerful predictive factor.

Determination of body fat percentage by electrocardiography signal with gender based artificial intelligence

Type of study:

Number of citations: 13

Year: 2021

Authors: M. K. Ucar, Z. Uçar, K. Uçar, M. Akman, M. R. Bozkurt

Journal: Biomed. Signal Process. Control.

Journal ranking: Q1

Key takeaways: ECG-based body fat percentage prediction models using gender-based electrocardiography signals and machine learning methods show promising performance for assessing body composition in practice.

Body Fat Prediction using Various Regression Techniques

Type of study:

Number of citations: 9

Year: 2023

Authors: Nikhil Mahesh, P. Pati, K. Deepa, Suresh Yanan

Journal: 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)

Journal ranking: brak

Key takeaways: Machine learning models, specifically Random Forest Regressor, can accurately predict body fat percentage with a lower RMSE of 0.276.

Abstract: Predicting body fat percentage is essential for addressing the obesity problem. This paper compares the performance of several machine learning models based on Regression, to predict the body fat percentage. Using a dataset of 252 participants with information on age, weight, height, and fat percentage, the models were assessed based on multiple performance criteria, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Squared Error(MSE). The results demonstrates that Random Forest Regressor surpass other models with a lower RMSE of 0.276. These findings suggest that machine learning models can be a valuable tool for precise BFP, the use of machine learning provides a faster and more precise method for predicting body fat percentage. Overall, the study’s results suggest that machine learning models can be valuable tool for accurate body fat percentage prediction.

Correlation between body fat percentage and aerobic capacity in various athletes

Type of study:

Number of citations: 0

Year: 2024

Authors: J. Rickta, Y. Arafat, Fatima Tus Johora Mukta, Rezaul Islam

Journal: Scientific Journal of Sport and Performance

Journal ranking: brak

Key takeaways: Higher body fat percentage is associated with lower aerobic capacity in athletes, while step pulse rate and fat percentage show a small positive correlation.

Abstract: Introduction: The Body Fat Percentage is an indicator of the Body's fitness level and its effects on VO2max and thus the cardiovascular status of the athletes. Physical exercise can help to improve a healthy life interestingly. Aims: This study aims to understand the relationship between Body Fat Percentage and Aerobic Capacity of different athletes. Methods: A total of 150 athletes were randomly selected as the subjects for the present study. In the present study VO2max was measured by Step test in millimeters of oxygen per kilogram of body weight per minute (ml.kg-1.min-1) and Fat percentage was measured by Skinfold Calliper in Millimeters (mm). The collected data were inferential statistics and an independent t-test was applied to check the level of significance. The significance level was set at p < .05. Descriptive and for the relationship appropriate multiple relation statistical tools will be used for the analysis of gathering data. Results: In between fat percentage and Step Test Pulse rate (b/min) coefficient of correlation (r = .441) and level of significance (p = .00) indicated statistical significance with a small positive correlation. At the time relationship between fat percentage and VO2max (ml/kg/min) (r = -.450) and level of significance (p = .00) indicated a statistically significant and medium negative correlation. Conclusion: The relationship between body fat percentage variables and VO2max was statistically significant and indicated a negative correlation but step pulse rate and fat percentage were statistically significant with a small positive correlation.

The Relationship of Fat Intake and Body Fat Percentage in Medical Students

Type of study:

Number of citations: 0

Year: 2024

Authors: Nurul Yuli Permata Sari, Ardesy Melizah Kurniati, Julius Anzar, Liniyanti D. Oswari, Sri Nita, Syarinta Adenina

Journal: Biomedical Journal of Indonesia

Journal ranking: brak

Key takeaways: Excessive fat intake is negatively associated with body fat percentage in medical students.

Abstract: Introduction. Obesity is an excessive fat accumulation in the body, now the prevalence is increasing in the group aged>18 years based on Body Mass Index (BMI). Nowadays body fat percentage has been declared to assess the risk factor of disease-related body weight better than BMI, people with proportioned weight had excessive body fat percentage evenly. Excessive fat intake is one of the important factors for obesity. The objective of this study was to analyze the association between fat intake with body fat percentage. Methods. This study was conducted with a cross-sectional design on 275 medical faculty students of Sriwijaya University, starting from August until December 2017 by collecting primary data through completing forms, food records, questionnaires, and physical examinations. Results. The results were analyzed statistically using chi-square. 67.3% of subjects had excessive body fat percentage and 50.2% with excessive fat intake. Results by the chi-square test indicate a negative association between fat intake with body fat percentage (p value=0.184). Conclusion. Fat intake with body fat percentage was negatively associated.

Relationship Among Body Fat Percentage, Body Mass Index, and All-Cause Mortality

Type of study: non-rct observational study

Number of citations: 200

Year: 2016

Authors: R. Padwal, W. Leslie, L. Lix, S. Majumdar

Journal: Annals of Internal Medicine

Journal ranking: Q1

Key takeaways: Greater body fat percentage, rather than greater BMI, is independently associated with increased all-cause mortality in middle-aged and older adults.

Abstract: Context A lower mortality rate among overweight and mildly to moderately obese adults (the obesity paradox) is unexplained. Studies documenting this paradox are limited because body mass index (BMI) is an imperfect and indirect measure of adiposity. Contribution In this population-based cohort study of middle-aged and older adults referred for bone mineral density testing, low BMI and high body fat percentage were independently associated with increased all-cause mortality among men and women. Caution Body fat percentage and BMI were measured only once at baseline. Implication The independent relationship between increased body fat percentage and mortality may help explain the obesity paradox. Many general population cohort studies over the past century have reported that excess adiposity (usually estimated with body mass index [BMI]) is associated with increased risk for all-cause death (13). However, not all of the published evidence agrees; a recent meta-analysis found that being overweight (BMI of 25.0 to 29.9 kg/m2) was associated with a decreased mortality risk and that mild obesity (BMI of 30.0 to 34.5 kg/m2) had a mortality risk similar to that of normal weight (BMI of 18.5 to 24.9 kg/m2) (4). Population-based cohort studies performed in middle-aged and older adults and more focused studies in persons with chronic diseases (such as heart failure and chronic kidney disease) have reported lower mortality rates in overweight and mildly or moderately obese persons than in those with normal weight (511). This unexpected finding has been termed the obesity paradox. These findings have generated considerable debate and discussion within and beyond the medical literature because they have obvious implications in terms of whether overweight and obese patients who are older or have chronic diseases should be counseled to lose weight to prolong their life (5, 9, 1215). Many explanations for the obesity paradox have been proposed. One commonly held view is that BMI, when used as a surrogate measure of body fat, confounds the relationship between excess adiposity and mortality risk (6, 16). Because it does not directly measure body fat, BMI is an imperfect measure of adiposity (6, 17, 18). Therefore, more sophisticated body fat measurements must be used in studies examining the relationship between adiposity and mortality so that this relationship can be more confidently and accurately assessed. The purpose of this study was to assess the relationship of BMI and body fat percentage (separately and together) with all-cause mortality in a general population cohort of middle-aged and older adults. We hypothesized that greater body fat percentage (rather than greater BMI) would be independently associated with increased mortality in sex-stratified models containing both parameters and adjusted for other potential confounders. If confirmed, this hypothesis would support the need to use direct fat measures instead of BMI when examining the relationship between adiposity and mortality risk. Methods Study Design We performed a population-based cohort study of all eligible residents of Manitoba, Canada, who were aged 40 years or older and who had initial dual-energy x-ray absorptiometry (DXA) of the spine and hip for bone mineral density (BMD) testing between 1999 and 2013. Participants were followed from the date of initial BMD testing until death or the end of the study. Only the initial BMD test was examined in each participant. Manitoba, which has a population of 1.25 million, provides government-funded universal health care to all residents, regardless of age or income. The Health Research Ethics Board of the University of Manitoba approved the study, and the Manitoba Health Information Privacy Committee approved data access. Data Sources Population Health Research Data Repository This registry contains multiple population-based, linked administrative health data sets provided by the provincial government and maintained by the Manitoba Centre for Health Policy of the University of Manitoba (1921). Data include sociodemographic variables, physician claims and hospital separations (including primary diagnosis and up to 25 secondary diagnoses), prescription drugs (drug name and date, dose, and quantity dispensed), and vital statistics (including mortality). The data sets are linked through a deidentified personal health information number that facilitates linkage to external data sources, including the provincial clinical BMD registry. These data are well-validated and have been used extensively in previous research (2023). Provincial Bone Mineral Density Registry This validated population-based registry contains data on all BMD tests performed for clinical purposes in Manitoba (2022). Uniform data collection standards are maintained, and data collection includes osteoporosis risk factors (including components of the World Health Organization [WHO] Fracture Risk Assessment [FRAX] risk calculator [24]), height and weight, testing indications, and reporting. The primary indication for testing is to assess bone density and fracture risk. All BMD test results have been captured since the program was established, with greater than 99% completeness and accuracy of registry data (2022). Lumbar spine and hip DXA are performed and scans analyzed in accordance with manufacturer recommendations using one of the Manitoba Bone Density Program's cross-calibrated DXA instruments (Prodigy in 98% and iDXA in 2% [GE Healthcare Lunar]). All densitometers and personnel are subject to province-wide quality assurance programs under the direction of a medical physicist, including daily evaluation of densitometer stability using anthropometric spine phantoms. Major Independent Variables: BMI and Body Fat Percentage Height was assessed with a wall-mounted stadiometer, and weight (without shoes) was assessed using a standard floor scale. Body mass index was calculated as weight (in kilograms) divided by height (in meters) squared. Persons with BMI at either extreme (<10 or >60 kg/m2) were excluded. Body fat percentages for the soft tissue regions included in the spine and hip scans were averaged to provide an index of total-body adiposity. A high correlation between body fat percentages from the regional DXA scan and the total-body DXA scan (the gold standard for total body fat measurement) was seen in a subgroup of participants with both measurements (r= 0.86 for 255 women and 0.87 for 46 men). Short-term precision errorcalculated as the root mean square for measurements of body fat percentage in 30 participants having repeated scans on the same day, with repositioning between the scanswas 1.8% for the spine scans and 1.7% for the hip scans (25). Body mass index and body fat percentage were divided into quintiles. In women, BMI quintiles were defined as follows: 22.52 kg/m2 or lower (quintile 1), 22.53 to 24.99 kg/m2 (quintile 2), 25.00 to 27.55 kg/m2 (quintile 3), 27.56 to 31.12 kg/m2 (quintile 4), and greater than 31.12 kg/m2 (quintile 5). To facilitate clinical interpretability, in a sensitivity analysis we also characterized BMI according to the WHO classification scheme as follows: less than 18.5 kg/m2 (underweight), 18.5 to 24.9 kg/m2 (normal weight), 25.0 to 29.9 kg/m2 (overweight), 30.0 to 34.9 kg/m2 (class I obesity), and 35.0 kg/m2 or greater (class II or III obesity). Body fat percentage quintiles in women were 25.57% or lower (quintile 1), 25.58% to 30.40% (quintile 2), 30.41% to 34.41% (quintile 3), 34.42% to 38.68% (quintile 4), and greater than 38.68% (quintile 5). In men, BMI quintiles were 23.85 kg/m2 or lower (quintile 1), 23.86 to 26.03 kg/m2 (quintile 2), 26.04 to 28.13 kg/m2 (quintile 3), 28.14 to 30.84 kg/m2 (quintile 4), and greater than 30.84 kg/m2 (quintile 5); the WHO BMI categories were the same as for women. Body fat percentage quintiles in men were 23.14% or lower (quintile 1), 23.15% to 27.98% (quintile 2), 27.99% to 31.72% (quintile 3), 31.73% to 36.14% (quintile 4), and greater than 36.14% (quintile 5). Outcomes The primary dependent variable of interest was all-cause mortality, ascertained from vital statistics data within the Population Health Research Data Repository. Potential Confounders Separate analyses were done a priori in men and women, with sequential adjustments. Potential confounders included age; Aggregated Diagnosis Groups (ADG) score; ethnicity (white vs. nonwhite); income quintile (lowest 2 vs. highest 3); residency (urban vs. nonurban); high alcohol use (yes vs. no); glucocorticoid use (yes vs. no); prior fracture; and presence of chronic obstructive pulmonary disease (COPD), diabetes, acute coronary syndrome, chronic kidney disease, or heart failure. The ADG score is an individualized comorbidity-based score consisting of 32 diagnostic clusters based on the Johns Hopkins Adjusted Clinical Groups Case-Mix System, version 10 (26). This score has been shown to accurately predict mortality in general ambulatory cohorts in Canada (27). Income data were at the neighborhood level and were sourced from the 2006 census. No data were missing for any of the covariates, but we lacked data on smoking status. However, we have previously shown that a COPD diagnosis in our population represents a valid measure of current smoking and can be substituted for smoking in risk stratification tools, such as FRAX (28, 29). Thirteen percent of Canadian women who are similar in age to those in our sample are smokers, and COPD was present in 8% of the women in our cohort; among men, both proportions were 18% (28, 29). Statistical Analysis Descriptive analyses were conducted according to BMI quintile using parametric or nonparametric tests as appropriate to test between-group differences. Spearman correlations between BMI and mean body fat percentage were calculated separately in men and women. Multivariable Cox proportional hazards models were then constructed sequentially as described earlier. Proportional hazards assump

Fat Tissue and Long Life

Type of study:

Number of citations: 39

Year: 2008

Authors: Matthias Blüher

Journal: Obesity Facts

Journal ranking: Q1

Key takeaways: Reduced fat mass and caloric restriction are associated with extended life span in various organisms, while obesity is associated with decreased life span in humans.

Abstract: Studies over the last several years have revealed important roles of the body fat content, caloric intake and nutrition, insulin/IGF-1 signaling systems, and pathways involved in oxidative stress and control of protein acetylation on life span. Although the discovery of longevity genes supports the concept that life span is genetically determined, adipose tissue seems to be a pivotal organ in the aging process and in the determination of life span. Leanness and caloric restriction have been shown to increase longevity in organisms ranging from yeast to mammals. Increased longevity in mice with a fat-specific disruption of the insulin receptor gene (FIRKO) suggests that reduced adiposity, even in the presence of normal or increased food intake, leads to an extended life span. Reduced fat mass has an impact on longevity in a number of other model organisms. In Drosophila, a specific reduction in the fat body through overexpression of forkhead type transcription factor (dFOXO) extends life span. Sirtuin 1 (SIRT1), the mammalian ortholog of the life-extending yeast gene silent information regulator 2 (SIR2), was proposed to be involved in the molecular mechanisms linking life span to adipose tissue. Moreover, in the control of human aging and longevity, one of the striking physiological characteristics identified in centenarians is their greatly increased insulin sensitivity even compared with younger individuals. On the other hand, overweight and obesity seem to be associated with decreased life span in humans. In addition, it was recently shown that modifiable risk factors during the later years of life, including smoking, obesity, and hypertension, are associated not only with lower life expectancy, but also with poor health and function during older age. There is growing evidence that the effect of reduced adipose tissue mass on life span could be due to the prevention of obesity-related metabolic disorders including type 2 diabetes and atherosclerosis.

Extended longevity and insulin signaling in adipose tissue

Type of study:

Number of citations: 88

Year: 2005

Authors: N. Klöting, M. Blüher

Journal: Experimental Gerontology

Journal ranking: Q1

Key takeaways: Reduced adiposity and insulin-signaling in adipose tissue play a key role in extending lifespan, potentially due to prevention of obesity-related metabolic disorders.

The Dual Role of the Pervasive “Fattish” Tissue Remodeling With Age

Type of study:

Number of citations: 47

Year: 2019

Authors: M. Conte, Morena Martucci, M. Sandri, C. Franceschi, S. Salvioli

Journal: Frontiers in Endocrinology

Journal ranking: Q1

Key takeaways: Aging leads to increased fat mass and changes in adipose tissue distribution, which can both positively and negatively impact human health and longevity.

Abstract: Human aging is characterized by dramatic changes in body mass composition that include a general increase of the total fat mass. Within the fat mass, a change in the proportions of adipose tissues also occurs with aging, affecting body metabolism, and playing a central role in many chronic diseases, including insulin resistance, obesity, cardiovascular diseases, and type II diabetes. In mammals, fat accumulates as white (WAT) and brown (BAT) adipose tissue, which differ both in morphology and function. While WAT is involved in lipid storage and immuno-endocrine responses, BAT is aimed at generating heat. With advancing age BAT declines, while WAT increases reaching the maximum peak by early old age and changes its distribution toward a higher proportion of visceral WAT. However, lipids tend to accumulate also within lipid droplets (LDs) in non-adipose tissues, including muscle, liver, and heart. The excess of such ectopic lipid deposition and the alteration of LD homeostasis contribute to the pathogenesis of the above-mentioned age-related diseases. It is not clear why age-associated tissue remodeling seems to lean toward lipid deposition as a “default program.” However, it can be noted that such remodeling is not inevitably detrimental. In fact, such a programmed redistribution of fat throughout life could be considered physiological and even protective, in particular at extreme old age. In this regard, it has to be considered that an excessive decrease of subcutaneous peripheral fat is associated with a pro-inflammatory status, and a decrease of LD is associated with lipotoxicity leading to an increased risk of insulin resistance, type II diabetes and cardiovascular diseases. At variance, a balanced rate of fat content and distribution has beneficial effects for health and metabolic homeostasis, positively affecting longevity. In this review, we will summarize the present knowledge on the mechanisms of the age-related changes in lipid distribution and we will discuss how fat mass negatively or positively impacts on human health and longevity.

Impact of visceral adipose tissue on longevity and metabolic health: a comparative study of gene expression in perirenal and epididymal fat of Ames dwarf mice.

Type of study: non-rct experimental

Number of citations: 1

Year: 2024

Authors: Agnieszka Zaczek, Andrzej Lewiński, M. Karbownik-Lewińska, Andrea Lehoczki, A. Gesing

Journal: GeroScience

Journal ranking: Q1

Key takeaways: Ames dwarf mice show increased expression of genes related to metabolic regulation, tumor suppression, mitochondrial biogenesis, and insulin pathways, potentially benefiting our understanding of longevity and aging.

Abstract: Emerging research underscores the pivotal role of adipose tissue in regulating systemic aging processes, particularly when viewed through the lens of the endocrine hypotheses of aging. This study delves into the unique adipose characteristics in an important animal model of aging — the long-lived Ames dwarf (df/df) mice. Characterized by a Prop1^df gene mutation, these mice exhibit a deficiency in growth hormone (GH), prolactin, and TSH, alongside extremely low circulating IGF-1 levels. Intriguingly, while surgical removal of visceral fat (VFR) enhances insulin sensitivity in normal mice, it paradoxically increases insulin resistance in Ames dwarfs. This suggests an altered profile of factors produced in visceral fat in the absence of GH, indicating a unique interplay between adipose tissue function and hormonal influences in these models. Our aim was to analyze the gene expression related to lipid and glucose metabolism, insulin pathways, inflammation, thermoregulation, mitochondrial biogenesis, and epigenetic regulation in the visceral (perirenal and epididymal) adipose tissue of Ames dwarf and normal mice. Our findings reveal an upregulation in the expression of key genes such as Lpl, Adrβ3, Rstn, Foxo1, Foxo3a, Irs1, Cfd, Aldh2, Il6, Tnfα, Pgc1α, Ucp2, and Ezh2 in perirenal and Akt1, Foxo3a, PI3k, Ir, Acly, Il6, Ring1a, and Ring 1b in epididymal fat in df/df mice. These results suggest that the longevity phenotype in Ames dwarfs, which is determined by peripubertal GH/IGF-1 levels, may also involve epigenetic reprogramming of adipose tissue influenced by hormonal changes. The increased expression of genes involved in metabolic regulation, tumor suppression, mitochondrial biogenesis, and insulin pathways in Ames dwarf mice highlights potentially beneficial aspects of this model, opening new avenues for understanding the molecular underpinnings of longevity and aging.

Determinants of body fat distribution in humans may provide insight about obesity-related health risks

Type of study:

Number of citations: 172

Year: 2018

Authors: Aaron P. Frank, R. De Souza Santos, B. Palmer, D. Clegg

Journal: Journal of Lipid Research

Journal ranking: Q1

Key takeaways: Body fat distribution, influenced by sex hormones, aging, and genetic variation, influences obesity-related health risks and can guide novel therapeutic approaches.

Abstract: Obesity increases the risks of developing cardiovascular and metabolic diseases and degrades quality of life, ultimately increasing the risk of death. However, not all forms of obesity are equally dangerous: some individuals, despite higher percentages of body fat, are at less risk for certain chronic obesity-related complications. Many open questions remain about why this occurs. Data suggest that the physical location of fat and the overall health of fat dramatically influence disease risk; for example, higher concentrations of visceral relative to subcutaneous adipose tissue are associated with greater metabolic risks. As such, understanding the determinants of the location and health of adipose tissue can provide insight about the pathological consequences of obesity and can begin to outline targets for novel therapeutic approaches to combat the obesity epidemic. Although age and sex hormones clearly play roles in fat distribution and location, much remains unknown about gene regulation at the level of adipose tissue or how genetic variants regulate fat distribution. In this review, we discuss what is known about the determinants of body fat distribution, and we highlight the important roles of sex hormones, aging, and genetic variation in the determination of body fat distribution and its contribution to obesity-related comorbidities.

Association of Body Fat With Health-Related Quality of Life and Depression in Nonagenarians: The Mugello Study.

Type of study: non-rct observational study

Number of citations: 40

Year: 2019

Authors: S. Giovannini, C. Macchi, R. Liperoti, A. Laudisio, D. Coraci, C. Loreti, F. Vannetti, G. Onder, L. Padua, G. Bonaccorsi, Roberta Boni, C. Castagnoli, F. Cecchi, F. Cesari, Francesco Epifani, R. Frandi, B. Giusti, M. Luisi, R. Marcucci, R. Molino-Lova, A. Paperini, L. Razzolini, F. Sofi, Nona Turcan, Debora Valecchi

Journal: Journal of the American Medical Directors Association

Journal ranking: Q1

Key takeaways: High body fat percentage is associated with poor health-related quality of life and increased depression in nonagenarians, with stronger effects observed in women.

Lipid metabolism and lipid signals in aging and longevity.

Type of study:

Number of citations: 167

Year: 2021

Authors: A. S. Mutlu, Jonathon Duffy, Meng C. Wang

Journal: Developmental cell

Journal ranking: Q1

Key takeaways: Lipid metabolism and lipid signaling play crucial roles in regulating aging and longevity, and interventions targeting these pathways may promote longevity.

Association of Percentage Body Fat and Metabolic Health in Offspring of Patients with Cardiovascular Diseases

Type of study: non-rct observational study

Number of citations: 4

Year: 2018

Authors: Yuan-Yuei Chen, W. Fang, Chung-Ching Wang, T. Kao, Yaw-Wen Chang, Hui-Fang Yang, Chen-Jung Wu, Yu-Shan Sun, Wei-liang Chen

Journal: Scientific Reports

Journal ranking: Q1

Key takeaways: Higher percentage body fat is associated with increased risk of cardiometabolic events, such as metabolic syndrome, type 2 diabetes, and hypertension.

The impact of dietary protein intake on longevity and metabolic health

Type of study:

Number of citations: 126

Year: 2019

Authors: Munehiro Kitada, Y. Ogura, I. Monno, D. Koya

Journal: EBioMedicine

Journal ranking: Q1

Key takeaways: A low-protein/high-carbohydrate diet, particularly low in red meat, may promote longevity and metabolic health, while excessive protein intake may promote age-related diseases.

Impact of body fat percentage change on future diabetes in subjects with normal glucose tolerance

Type of study: non-rct observational study

Number of citations: 12

Year: 2017

Authors: Tianxue Zhao, Ziwei Lin, Hui Zhu, Chen Wang, W. Jia

Journal: IUBMB Life

Journal ranking: Q1

Key takeaways: Maintaining normal body fat percentage is more important than BMI in preventing diabetes, with subjects from normal BF% at baseline to obese at follow-up having an increased risk of developing diabetes.

Abstract: The aim of the work was to determine the effect of body fat change on risk of diabetes in normal glucose tolerance (NGT) population. A total of 1,857 NGT subjects were included and followed up for an average period of 44.57 months. Body fat percentage (BF%) was measured by bioelectrical impedance analysis. Subjects were grouped based on the BF% and/or body mass index (BMI) state. Among all subjects, 28 developed diabetes after follow‐up. Compared with subjects with stable normal BF% (control), subjects who became obesity at follow‐up were defects in insulin secretion and had a higher risk of developing diabetes (7.102, 95% confidence intervals [CI] 1.740–28.993), while no difference in diabetic risk could be viewed between subjects with abnormal BF% at baseline but normal at the end of follow‐up and control subjects after adjustment of confounding factors. Moreover, compared with those keeping normal BF% and BMI both at baseline and follow‐up, subjects who had normal BMI at baseline and follow‐up, but abnormal BF% at baseline or/and follow‐up still had a higher risk to develop diabetes (4.790, 95% CI 1.061–21.621), while those with normal BF% at baseline and follow‐up, but abnormal BMI at baseline or/and follow‐up had not. Subjects from normal BF% at baseline to obese at follow‐up are associated with an increased risk of diabetes. Maintaining normal body fat is more relevant than BMI in preventing diabetes. © 2017 IUBMB Life, 69(12):947–955, 2017

The association between physical activity and body fat percentage with adjustment for body mass index among middle-aged adults: China health and nutrition survey in 2015

Type of study: non-rct observational study

Number of citations: 19

Year: 2020

Authors: Qinpei Zou, C. Su, W. Du, Y. Ouyang, Hui-jun Wang, Zhihong Wang, G. Ding, Bing Zhang

Journal: BMC Public Health

Journal ranking: Q1

Key takeaways: In middle-aged Chinese adults, the inverse association between physical activity and body fat% is stronger in certain subpopulations, particularly normal weight obese individuals.

Abstract: Abstract Background The inverse association between physical activity and body fat percentage (%) varies among different populations. We aim to examine whether the significant association between them was uniform across the subpopulations after taking into account body mass index (BMI). Methods Our study relied on data from China Health and Nutrition Surveys in 2015, including 5763 participants aged 40–64 years from 15 regions. Physical activity was calculated as metabolic equivalent task hours per day (MET·h/d). Body fat% was measured by bioelectrical impedance analysis. Body mass index &lt; 24 kg/m 2 was defined as normal weight and BMI ≥ 24 kg/m 2 was overweight/obese. The effects of physical activity on body fat% were estimated using the Kruskal-Wallis test among sex, age, BMI groups, education, income, region and urbanization. Quantile regression analyses were utilized to describe the relationship between physical activity and body fat% distribution. Results Older adults, overweight/obese, higher education, higher income, residents of central China and those living in areas of higher urbanization had the lower physical activity. Participants who engaged in the highest level of physical activity had 2.0 and 1.5% lower body fat% than the lowest level of physical activity group (23.4, 34.8%) for men and women, respectively. There were 10.4 and 8.8% of normal weight males and females called normal weight obese. Overall, 1 h extra 4.5 MET•h/d was significantly associated with 0.079 and 0.110% less total body fat% at the 75th and 90th percentiles in normal weight males, with 0.071% less at the 25th percentiles in overweight/obese males, with 0.046–0.098% less at the 25th to 90th percentiles in normal weight females, and with 0.035–0.037% less from the 50th to 90th percentiles in overweight/obese females. The inverse association between physical activity and total body fat% was stronger in normal weight obese participants than other subgroups. Conclusions In middle-aged Chinese adults, the inverse association between physical activity and body fat% was only in particular subpopulations rather than the entire population. We should pay much attention to normal weight obese and give a suitable physical activity guideline taking into account people with different body fat%.

Bothersome symptoms at midlife in relation to body fat percentage

Type of study: non-rct observational study

Number of citations: 1

Year: 2024

Authors: L. M. Gerber, B. W. Whitcomb, M. Verjee, L. L. Sievert

Journal: American Journal of Human Biology

Journal ranking: Q1

Key takeaways: Higher body fat percentage is associated with increased bothersomeness of symptoms at midlife.

Abstract: Increasing obesity has been associated with a higher frequency of symptoms at midlife. Bothersomeness represents an important measure of perceived symptom severity, but has received relatively little consideration, and relationships between symptom bothersomeness and obesity are not known. We evaluated the association between body fat percentage (%BF) and the bothersomeness of symptoms at midlife.

Is dietary fat a major determinant of body fat?

Type of study:

Number of citations: 433

Year: 1998

Authors: W. Willett

Journal: The American journal of clinical nutrition

Journal ranking: Q1

Key takeaways: Dietary fat is not the primary cause of excess body fat in society, and reducing fat intake alone will not solve the obesity problem.

Abstract: The percentage of energy from dietary fat is widely believed to be an important determinant of body fat, and several mechanisms have been proposed to account for such a relation. Comparisons of both diets and the prevalence of obesity between affluent and poor countries have been used to support a causal association, but these contrasts are seriously confounded by differences in physical activity and food availability. Within areas of similar economic development, regional intake of fat and prevalence of obesity have not been positively correlated. Randomized trials are the preferable method to evaluate the effect of dietary fat on adiposity, and are feasible because the number of subjects needed is not large. In short-term trials, a modest reduction in body weight is typically seen in individuals randomly assigned to diets with a lower percentage of energy from fat. However, compensatory mechanisms appear to operate because in trials lasting > or = 1 y, fat consumption within the range of 18-40% of energy appears to have little if any effect on body fatness. Moreover, within the United States, a substantial decline in the percentage of energy from fat consumed during the past two decades has corresponded with a massive increase in obesity. Diets high in fat do not appear to be the primary cause of the high prevalence of excess body fat in our society, and reductions in fat will not be a solution.

The Impact of Body Fat Percentage towards the Attention Aspect of the Cognitive Function in Pre-Clinical University Students of Atma Jaya

Type of study:

Number of citations: 1

Year: 2021

Authors: M. Santosa, Alvin Edwin Wiyono, Robi Irawan

Journal: Sriwijaya Journal of Medicine

Journal ranking: brak

Key takeaways: High body fat percentage negatively impacts the attention aspect of cognitive function in university students.

Abstract: In 2016, World Health Organization (WHO) predicts that 650 million adults aged 18 and more have obesity. Many research shows that obesity affects brain function and impairs the cognitive function of the brain. To understand whether body fat percentage has an impact on the attention aspect of the cognitive function in university students. This study is a cross-sectional study approach. The data was collected from August 2020 until March 2021 with a total of 72 respondents. The data was collected using the body fat percentage formula from the British Journal of Nutrition to assess body fat percentage and Stroop Test for attention. Kruskal-Wallis and spearman were used to assess the correlation between body fat percentage and attention. The result shows that body fat percentage affects the attention aspect of the cognitive function (p = 0.001, r = 0.71). In conclusion, based on 72 university students, it proves that body fat percentage has an impact on the attention aspect of the cognitive function. The impact that high body fat percentage does is lowering the attention aspect of the cognitive function.

The Impact of Physical Activity at School on Body Fat Content in School-Aged Children

Type of study: non-rct observational study

Number of citations: 11

Year: 2022

Authors: K. Ługowska, W. Kolanowski

Journal: International Journal of Environmental Research and Public Health

Journal ranking: Q2

Key takeaways: Increased physical activity at school reduces the risk of obesity in children aged 10-12 years.

Abstract: (1) Background: Excessive amounts of adipose tissue is a health risk. The aim of this study was to assess the impact of increased physical activity (PA) at school on body fat content in children aged 10 to 12 years over a 2-year follow-up. (2) Methods: Children born in 2007 (n = 245) in two groups, (1) standard PA and (2) increased PA at school, 4 and 10 h of physical education lessons per week, respectively. BIA measurements of body fat content were taken twice a year. Results were interpreted based on children’s fat content reference curves. (3) Results: During 2 years of observation, the percentage of children with excessive fat mass (overweight and obese) increased by one-third (from 28.11% to 39.67%) in the group of standard PA, while decreased by one-third in the increased PA one (from 28.92% to 21.00%); with normal fat content increased by one-quarter in the increased PA group (from 59.86% to 76.26%) and decreased by one-tenth in the standard PA one (from 61.61% to 56.29%). (4) Conclusions: An increase in PA at school has a positive impact on children’s body fat content. It is recommended to increase the number of physical education lessons at school, which has a positive effect on children’s health, reducing the risk of obesity.