scholarly journals Influence of adiposity and fatigue on the scapular muscle recruitment order

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7175
Author(s):  
Guillermo Mendez-Rebolledo ◽  
Eduardo Guzman-Muñoz ◽  
Rodrigo Ramírez-Campillo ◽  
Pablo Valdés-Badilla ◽  
Carlos Cruz-Montecinos ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Body Mass ◽  
Body Fat ◽  
Skinfold Thickness ◽  
The Body ◽  
Excess Body Weight ◽  
Onset Latency ◽  
Percentage Body Fat ◽  
Recruitment Order

Background Several authors have indicated that excess body weight can modify the electromyographic (EMG) amplitude due to the accumulation of subcutaneous fat. This accumulation of adipose tissue around the muscle would affect the metabolic capacity during functional activities. On the other hand, some authors have not observed differences in the myoelectric manifestations of fatigue between normal weight and obese people. Furthermore, these manifestations have not been investigated regarding EMG onset latency, which indicates a pattern of muscle activation between different muscles. The objective of this study was to determine whether an increase in body weight, skinfolds, and muscle fatigue modify the trapezius and serratus anterior (SA) onset latencies and to determine the scapular muscle recruitment order in fatigue and excess body weight conditions. Methods This cross-sectional study was carried out in a university laboratory. The participants were randomly assigned to the no-fatigue group (17 participants) or the fatigue (17 participants) group. The body mass index, skinfold thickness (axillary, pectoral, and subscapular), and percentage of body fat were measured. In addition, the onset latency of the scapular muscles [lower trapezius (LT), middle trapezius (MT), upper trapezius (UT), and SA] was assessed by surface EMG during the performance of a voluntary arm raise task. A multiple linear regression model was adjusted and analyzed for the additive combination of the variables, percentage body fat, skinfold thickness, and fatigue. The differences in onset latency between the scapular muscles were analyzed using a three-way repeated measure analysis of variance. In all the tests, an alpha level <0.05 was considered statistically significant. Results For the MT, LT, and SA onset latencies, the body mass index was associated with a delayed onset latency when it was adjusted for the additive combination of percentage of body fat, skinfold thickness, and fatigue. Of these adjustment factors, the subscapular skinfold thickness (R2 = 0.51; β = 10.7; p = 0.001) and fatigue (R2 = 0.86; β = 95.4; p = 0.001) primarily contributed to the increase in SA onset latency. A significant muscle ×body mass index ×fatigue interaction (F = 4.182; p = 0.008) was observed. In the fatigue/excess body weight condition, the UT was activated significantly earlier than the other three scapular muscles (p < 0.001) and SA activation was significantly delayed compared to LT (p < 0.001). Discussion Excess body weight, adjusted for skinfold thickness (axillary and subscapular) and fatigue, increases the onset latency of the MT, LT, and SA muscles and modifies the recruitment order of scapular muscles. In fact, the scapular stabilizing muscles (MT, LT, and SA) increase their onset latency in comparison to the UT muscle. These results were not observed when excess body weight was considered as an individual variable or when adjusted by the percentage body fat.

Prevalence of obesity using the body mass index and equivalent age- and sex-specific thresholds for percentage body fat mass

2013 ◽  
Vol 7 ◽  
pp. e93
Author(s):  
Julie A. Pasco ◽  
Haslinda Gould ◽  
Kara L. Holloway ◽  
Amelia G. Dobbins ◽  
Mark A. Kotowicz ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
The Body ◽  
Body Fat Mass ◽  
Percentage Body Fat ◽  
Equivalent Age ◽  
Prevalence Of Obesity ◽  
Age And Sex

scholarly journals The Relationship Between Body Mass Index with Body Fat Percentage of Participants EXPO 2021 Universitas Teuku Umar

2021 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Suci Eka Putri ◽  
Adelina Irmayani Lubis
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Nutritional Status ◽  
Body Mass ◽  
Body Fat ◽  
Body Height ◽  
The Body ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
The Relationship

Body mass index (BMI) is to monitor nutritional status adults, especially those related to deficiency and overweight. Body fat percentage can describe the risk of degenerative diseases.This study was conducted to measure the relationship between BMI and body fat percentage. Methods An analytical study was conducted to 41 male and 51 female participant from Universitas Teuku Umar. The body weight was measured using scales, whereas the body height was measured using microtoise. The body fat percentage was measured using Karada Scan. The BMI was calculated by dividing the body weight in kilogram divided by body height in meter square. Data was collected from 16-18th February 2021 and analyzed by Pearson’s correlation test. The results showed BMI underweight, normal, and overweight were 10,9, 57,6, and 31,5. High body fat percentage in men were 75,6% and in women were 35,5%. There is a relationship between the nutritional status of the women group and the body fat percentage with p-value is obtained = 0.021. Furthermore, for men, there is no relationship between nutritional status in the men group and the body fat percentage. There is a relationship between nutritional status and body fat percentage in women. Among this population, BMI can still be used to determine body fat percentage

Obesity in Auckland school children: a comparison of the body mass index and percentage body fat as the diagnostic criterion

2001 ◽  
Vol 25 (2) ◽  
pp. 164-169 ◽  
Author(s):  
VJ Tyrrell ◽  
GE Richards ◽  
P Hofman ◽  
GF Gillies ◽  
E Robinson ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
School Children ◽  
The Body ◽  
Percentage Body Fat ◽  
Diagnostic Criterion

scholarly journals Do Body Mass, Body Mass Index and Body Fat Ratio have an Effect on Proprioception?

2014 ◽  
Vol 2 (11_suppl3) ◽  
pp. 2325967114S0015
Author(s):  
Esra Ateş Numanoğlu ◽  
Filiz Can ◽  
Zafer Erden
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Knee Joint ◽  
Body Mass ◽  
Body Fat ◽  
The Body ◽  
Reflex Response ◽  
Load Bearing ◽  
Body Weights ◽  
Medium Strength

Objectives: Proprioceptive sense plays important role of the protective reflex response against the harmful forces on the joint takes part in protection against the injuries. The load on the musculoskeletal system increases with higher body weights and joints become prone to injuries due to this increased load. The goal of this study was to investigate the relationship between the proprioceptive sense of the knee joint, mostly affected by loading, and the body weight, body mass index, and body fat ratio. Methods: 25 healthy people aged between 21 and 36 years included in the study. Body weights, body mass indexes (BMI), and body fat ratios of the individuals were measured. Proprioceptive sense in the knee joint is evaluated through the active joint position sense (A-JPS) assessments. The A-JPS of 50 knees of 25 individuals are evaluated at supine and load bea squat with 30° and 90° of knee flexion. To measure A-JPS, targeted angle were shown using goniometer and digital photography has been taken. Then they return to the initial position and repeat the angle and the second image was captured. After three times repetitions, deviations from 30° and 90° were called mean angle errors. The angle error measurements were performed with specifically written programme MATLAB (Computer Aided Design software). Pearson and Spearman Correlation Analyses were used for statistics. Results: There was no correlation between the body weight and the proprioceptive error at supine and squat for 30° and 90° flexion angles (p>0.05). When the individuals has been grouped according to their BMI values thinnesses for (BMI = 15-20 kg/m²), normals for (BMI = 20-25 kg/m²), and overweights for (BMI = 25-30 kg/m²) and the correlation between the BMI and proprioceptive error has been evaluated, there was no correlation for thinnesses and normals, for overweights at 90° squat position a medium strength positive correlation is observed (r=0.644, p=0.01). For thinnesses and normals there is no correlation between the body fat ratio and the proprioceptive error. For the overweights for 30° and 90° flexions at squat there is medium strength, strong positive correlations (r1=0.540, p=0.04; r2=0.709, p=0.005). Conclusion: Consequently, especially for individuals with high BMI, at load bearing squat position for 90° flexion, the proprioceptive sense decreases. Increased body fat ratio negatively affects the proprioception at load bearing squat position for 30° and 90° flexion angles. According to these results being overweight can be considered as an disadvantage in terms of proprioceptive sense.

scholarly journals Body mass index: a measure of fatness or leanness?

1995 ◽  
Vol 73 (4) ◽  
pp. 507-516 ◽  
Author(s):  
Alan M. Nevill ◽  
Roger L. Holder
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Normal Range ◽  
Percentage Body Fat ◽  
Distributional Properties ◽  
Two Indices ◽  
The Relationship

The relationship between body fat and stature-adjusted weight indices was explored. Assuming the term height2 is a valid indicator of a subject's lean body mass, height2/weight was shown to be an accurate measure of percentage lean body mass and, as such, a better predictor of percentage body fat than the traditional body mass index (BMI; weight/height2). The name, lean body mass index (LBMI), is proposed for the index height2/weight. These assumptions were confirmed empirically using the results from the Allied Dunbar National Fitness Survey (ADNFS). Using simple allometric modelling, the term heightp explained 74% of the variance in lean body mass compared with less than 40% in body weight. For the majority of ADNFS subjects the fitted exponent from both analyses was approximately p = 2, the only exception being the female subjects aged 55 years and over, where the exponent was found to be significantly less than 2. Using estimates of percentage body fat as the dependent variable, regression analysis was able to confirm that LBMI was empirically, as well as theoretically, superior to the traditional BMI. Finally, when the distributional properties of the two indices were compared, BMI was positively skewed and hence deviated considerably from a normal distribution. In contrast, LBMI was found to be both symmetric and normally distributed. When height and weight are recorded in centimetres and kilograms respectively, the suggested working normal range for LBMI is 300–500 with the median at 400.

scholarly journals The relationship between body mass index and mental disorders in the adult population

2020 ◽  
Vol 64 (6) ◽  
pp. 336-342
Author(s):  
Andrei V. Golenkov ◽  
Igor V. Madyanov ◽  
Svetlana V. Shmeleva ◽  
Galina D. Petrova ◽  
Natalya N. Kamynina ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Body Mass ◽  
Adult Population ◽  
Statistical Processing ◽  
The Body ◽  
Excess Body Weight ◽  
Healthy Population ◽  
Demographic Indices ◽  
Icd 10

The purpose of the work is to study the features of the body mass index (BMI) in schizophrenia patients (SP) who live in Chuvashia. Material and methods. 607 SP were examined (307 men and 300 women) aged 18 to 82 (average - 44.51 ± 12.3 years). The diagnosis of schizophrenia met the criteria for ICD-10 (F20-29); disease duration ranged from 0 to 52 years (mean - 18.9 ± 10.7 years). BMI was taken into account according to the Ketle index. For each SP, a survey card with clinical, therapeutic, and socio-demographic indices was filled out. The comparison group included a sample of 3417 residents of Chuvashia. Mathematical and statistical processing was carried out using descriptive statistics and χ2 distribution. Results. 9.2% of SP had underweight, 54.2% - normal body weight, 36.6% - excess body weight and obesity. Among women there were significantly more persons with increased BMI and obesity, among men - with normal BMI. In SP, BMI did not depend on the group of taken antipsychotics (typical, atypical, mixed-use) and the disease’s duration. With patients’ age, BMI increased to excess BMI (25-29.9 kg/m2). Among SP, persons with underweight were much more common (among healthy people, 2% vs 9.2% in SP). From 40 years of age and older, among the healthy population, persons with an increased BMI and obesity begin to predominate significantly compared with the SP group. Observations of BMI during inpatient treatment from 1.5 to 22 months showed multidirectional dynamics, including increased body weight in 42.2% of SP, a decrease in 30.1%, without changes in BMI in 27.7%; it was not possible to retrospectively identify any patterns of BMI fluctuations. Conclusion. The revealed paradoxes of BMI for SP in Chuvashia, especially a high proportion of SP with underweight, require refinement considering ethnic, genetic, sex and age, hormon and metabolic factors.

L-Ascorbic Acid Addition to Chitosan Reduces Body Weight in Overweight Women

2014 ◽  
Vol 84 (1-2) ◽  
pp. 5-11 ◽  
Author(s):  
Eun Y. Jung ◽  
Sung C. Jun ◽  
Un J. Chang ◽  
Hyung J. Suh
Keyword(s):  
Ascorbic Acid ◽  
Body Weight ◽  
Fat Body ◽  
Body Weight Gain ◽  
Skinfold Thickness ◽  
The Body ◽  
Control Group ◽  
Percentage Body Fat ◽  
Overweight Women ◽  
Body Weights

Previously, we have found that the addition of L-ascorbic acid to chitosan enhanced the reduction in body weight gain in guinea pigs fed a high-fat diet. We hypothesized that the addition of L-ascorbic acid to chitosan would accelerate the reduction of body weight in humans, similar to the animal model. Overweight subjects administered chitosan with or without L-ascorbic acid for 8 weeks, were assigned to three groups: Control group (N = 26, placebo, vehicle only), Chito group (N = 27, 3 g/day chitosan), and Chito-vita group (N = 27, 3 g/day chitosan plus 2 g/day L-ascorbic acid). The body weights and body mass index (BMI) of the Chito and Chito-vita groups decreased significantly (p < 0.05) compared to the Control group. The BMI of the Chito-vita group decreased significantly compared to the Chito group (Chito: -1.0 kg/m2 vs. Chito-vita: -1.6 kg/m2, p < 0.05). The results showed that the chitosan enhanced reduction of body weight and BMI was accentuated by the addition of L-ascorbic acid. The fat mass, percentage body fat, body circumference, and skinfold thickness in the Chito and Chito-vita groups decreased more than the Control group; however, these parameters were not significantly different between the three groups. Chitosan combined with L-ascorbic acid may be useful for controlling body weight.

scholarly journals Effects of Triphala on Lipid and Glucose Profiles and Anthropometric Parameters: A Systematic Review

2021 ◽  
Vol 26 ◽  
pp. 2515690X2110110
Author(s):  
Wiraphol Phimarn ◽  
Bunleu Sungthong ◽  
Hiroyuki Itabe
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Blood Glucose ◽  
Waist Circumference ◽  
Lipid Profile ◽  
Body Mass ◽  
The Body ◽  
Current Evidence ◽  
Diabetic Patients ◽  
Anthropometric Parameters

Aim. The efficacy of triphala on lipid profile, blood glucose and anthropometric parameters and its safety were assessed. Methods. Databases such as PubMed, ScienceDirect, Web of Science, and Thai Library Integrated System (ThaiLIS) were systematically searched to review current evidence of randomized controlled trials (RCT) on triphala. RCTs investigating the safety and efficacy of triphala on lipid profile, blood glucose and anthropometric parameters were included. Study selection, data extraction, and quality assessment were performed independently by 2 authors. Results. Twelve studies on a total of 749 patients were included. The triphala-treated groups showed significantly reduced low-density lipoprotein-cholesterol, total cholesterol and triglyceride in 6 studies. Five RCTs demonstrated triphala-treated groups led to statistically significant decrease in body weight, body mass index and waist circumference of obese patients. Moreover, triphala significantly decreased fasting blood glucose level in diabetic patients but not in people without diabetes. No serious adverse event associated with triphala was reported during treatment. Conclusions. This review summarized a current evidence to show triphala might improve the lipid profile, blood glucose, the body weight, body mass index and waist circumference under certain conditions. However, large well-designed RCTs are required to confirm this conclusion.

scholarly journals Body mass index as a measure of body fatness: age- and sex-specific prediction formulas

1991 ◽  
Vol 65 (2) ◽  
pp. 105-114 ◽  
Author(s):  
Paul Deurenberg ◽  
Jan A. Weststrate ◽  
Jaap C. Seidell
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Prediction Error ◽  
Bioelectrical Impedance ◽  
Skinfold Thickness ◽  
Fat Percentage ◽  
Wide Range ◽  
The Relationship ◽  
Age And Sex

In 1229 subjects, 521 males and 708 females, with a wide range in body mass index (BMI; 13.9–40.9 kg/m2), and an age range of 7–83 years, body composition was determined by densitometry and anthropometry. The relationship between densitometrically-determined body fat percentage (BF%) and BMI, taking age and sex (males =1, females = 0) into account, was analysed. For children aged 15 years and younger, the relationship differed from that in adults, due to the height-related increase in BMI in children. In children the BF% could be predicted by the formula BF% = 1.51xBMI–0.70xage–3.6xsex+1.4 (R2 0.38, SE of estimate (see) 4.4% BF%). In adults the prediction formula was: BF% = 1.20xBMI+0.23xage−10.8xsex–5.4 (R2 0.79, see = 4.1% BF%). Internal and external cross-validation of the prediction formulas showed that they gave valid estimates of body fat in males and females at all ages. In obese subjects however, the prediction formulas slightly overestimated the BF%. The prediction error is comparable to the prediction error obtained with other methods of estimating BF%, such as skinfold thickness measurements or bioelectrical impedance.

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