(October 31, 2019) Monitoring energy gap using Muscle Fitness Indicators II (FROM KEEPING TAB WITH THE NEW Z SCORES)
(October 31, 2019) Monitoring energy gap using Muscle Fitness Indicators
KEEPING TAB WITH THE NEW Z SCORES:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345970/
Comparisons of different indices of low muscle mass in relationship with cardiometabolic disorder
Published online: January 24, 2019
Abstract: This study aimed to evaluate the most valid index among various indices of low muscle mass in assessing cardiometabolic risks in a Korean population. Appendicular lean mass index (ALMI, kg/m2), fat mass index (FMI, kg/m2), FMI-adjusted ALMI, ratio of ALM to weight index, ratio of ALM to body mass index and ratio of ALM to truncal fat index were measured by dual energy X-ray absorptiometry in 17,870 participants from 2008 to 2011. We adopted all the aforementioned indices of low muscle mass expressed as ***- and age-specific standard deviation scores (Z-scores). Low muscle mass for age was defined as Z-score <−1. The prevalence of low muscle mass was approximately 16% across all indices. The receiver operating characteristic curve in metabolic syndrome showed that the ALM to truncal fat index was 0.74 in male and 0.69 in female, indicating that ALM to truncal fat index was the best discrimination index for metabolic syndrome. This study showed that ALM to truncal fat index could be a useful indicator for screening cardiometabolic risk factors, particularly in normal or overweight Asian population.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356414/
Muscle Fitness to Visceral Fat Ratio, Metabolic Syndrome and Ideal Cardiovascular Health Metrics
Published online: December 22, 2018
Measuring Body Weight
Participants (a total of 1,467 young adults as college students) were instructed to wear light clothing (for example, a t-shirt and shorts) for the physical exam. Once the subjects were barefoot and in their underwear, their body weight (kg) was measured using an electric scale (Model Tanita BC-420-MA Tokyo, Japan) with a range of 0 to 200 kg and with an accuracy of within 100 g.
https://www.ncbi.nlm.nih.gov/pubmed/22370852
Effect of clothing weight on body weight.
Clothing weights across the year for Men:
Average within-person minimum = 0.9±0.2 kg
Average within-person maximum = 1.5±0.4 kg
My BIA (Bioelectric Impedance Analysis technology) body weight result, with 172 cm. standing height, in 2016: 58.7 kg using ‘Standard Mode’ of Hand-to-foot Tanita BC-545N Body Composition Monitor or equivalent, validated using ‘Athlete Mode’ of Hand-to-foot Tanita RD-545 Segmental Body Composition Monitor or equivalent
My Body Mass Index (BMI) at 28 years old: not actual clothing but for comparing data
Thus, at minimum for BIA: 58.7 kg (at 19.8 BMI) + 0.7 kg = 59.4 kg with clothes (at 20.1 BMI).
Also, 59.4 kg body weight was recorded on my 2016 Whole-body Hologic DXA (National Kidney and Transplant Institute).
Segmental Reading: Tanita BC-545N, Tanita RD-545
Measuring body fat % and muscle mass for whole body, each arm (left, right), each leg (left, right), trunk
Other features: weight, total body water, basal metabolic rate, metabolic age, visceral fat rating, physique rating, bone mass, body mass index; for Tanita RD-545: whole body muscle quality, limbs muscle quality, comparative muscle quality and its balance, plus standing heart rate option
Q1, Q2, Q3, & Q4 MVF ratio (Muscular fitness to visceral fat level ratio) + my profile as of 2016 BIA recording
Data: Values are presented as the mean (95% CI). The MVF ratio was divided into quartiles with the following (min–max) values: Q1: 0.015–0.136, Q2: 0.137–0.338, Q3: 0.339–0.498 and Q4: 0.499–0.904. To compare between groups, all dependent variables were analyzed by using ANCOVA with adjustment by age, gender, university and alcohol use as covariates. Categorical variables were analyzed by using the Chi-square test. WC, waist circumference; BMI, body mass index; NGS, normalized grip strength (Handgrip (kg)/body mass (kg)).
My Age (years) = 28
Q1 = 21.5 (21.2–21.8)
Q2 = 21.0 (20.8–21.4)
Q3 = 20.0 (19.7–20.3)
Q4 = 19.8 (19.6–20.1)
My Height (m) = 1.72 m
Q1 = 1.65 (1.65–1.66)
Q2 = 1.64 (1.64–1.65)
Q3 = 1.63 (1.63–1.64)
Q4 = 1.64 (1.64–1.65)
My BMI = 19.8 (without clothing); 20.1 (with minimum clothes weight)
Q1 = 28.1 (27.8–28.4)
Q2 = 23.8 (23.5–24.1)
Q3 = 20.9 (20.6–21.2)
Q4 = 20.3 (20.1–20.6)
Body Fat: Athlete Mode
https://journals.lww.com/acsm-msse/fulltext/2004/04000/Minimum_Weight_Prediction_Methods_Cross_Validated.13.aspx
(2004) Minimum Weight Prediction Methods Cross-Validated by the Four-Component Model: Using its wrestling sample, the ‘athlete mode’ provides an estimate of % Body Fat that averages 6% less than the standard mode.
My % Body Fat = 11.2% ‘Standard Mode’; ‘Athlete Mode’ recorded
Q1 = 30.8 (30.3–31.3)
Q2 = 23.3 (22.9–23.9)
Q3 = 17.4 (16.9–17.9)
Q4 = 16.2 (15.8–16.7)
Body Scan UK: Body Composition Calculators
https://www.bodyscanuk.com/body-composition-calculators.html
My Fat Mass Index = 2.3 at 11.2% ‘Standard Mode’
Q1 = 8.7 (8.6–9.0)
Q2 = 5.5 (5.4–5.8)
Q3 = 3.5 (3.4–3.8)
Q4 = 3.4 (3.3–3.6)
My Visceral Fat Level = ‘Standard Mode’ recorded; ‘Athlete Mode’ recorded
Q1 = 5.6 (5.4–5.8)
Q2 = 2.2 (2.1–2.4)
Q3 = 1.2 (1.1–1.4)
Q4 = 0.8 (0.7-1.0)
Reference: MVF ratio (Muscular fitness to visceral fat level ratio)
Q1 = 0.08 (0.07–0.09)
Q2 = 0.22 (0.21–0.22)
Q3 = 0.43 (0.42–0.44)
Q4 = 0.60 (0.59–0.61)
Outcomes: Metabolic Syndrome, Muscular Fitness
Diagnoses of Metabolic Syndrome:
Participants (a total of 1,467 young adults as college students) were considered to have a diagnosis of Metabolic Syndrome if they had three or more of the following: (1) abdominal obesity (Waist Circumference ≥ 80 cm in females and ≥90 cm in males); (2) hypertriglyceridemia (≥150 g/dL); (3) low high density lipoprotein cholesterol, HDL-c (<50 mg/dL in females and <40 mg/dL in males); (4) high blood pressure (systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg); (5) high fasting glucose (≥100 mg/dL). Metabolic Syndrome was defined in accordance with the updated harmonized criteria of the International Diabetes Foundation (IDF).
Prevalence of Metabolic Syndrome:
Q1 = 32.3%
Q2 = 5.0%
Q3 = 1.9%
Q4 = 2.2%
Muscular Fitness: Handgrip (kg), Normalized Grip Strength (Handgrip (kg)/body mass (kg))
Handgrip (kg)
Q1 = 30.9 (30.3–31.6)
Q2 = 30.8 (30.2–31.5)
Q3 = 27.7 (27.0–28.4)
Q4 = 32.3 (31.6–32.9)
Normalized Grip Strength (Handgrip (kg)/body mass (kg))
Q1 = 0.40 (0.39–0.41)
Q2 = 0.47 (0.46–0.48)
Q3 = 0.48 (0.47–0.49)
Q4 = 0.58 (0.58–0.59)
https://www.ncbi.nlm.nih.gov/pubmed/27134408/
(2016) Validity of muscle-to-fat ratio as a predictor of adult metabolic syndrome.
Abstract:
[Purpose] This study was aimed at determining the validity of the muscle-to-fat ratio as an indicator for the prevention and management of metabolic syndrome by establishing an optimal cutoff value. [Results] The receiver operating characteristic curve for the muscle-to-fat ratio, which represents the diagnostic power for predicting metabolic syndrome, was 0.713 in men and 0.721 in women. The optimal cutoff value for the prediction and diagnosis of metabolic syndrome was 3.09 kg/kg in men and 1.83 kg/kg in women. Intergroup differences based on the muscle-to-fat ratio indicated that the low-ratio group had higher values for all indicators of metabolic syndrome than the high-ratio group. [Conclusion] The muscle-to-fat ratio can be used as an indicator for the prediction and diagnosis of metabolic syndrome, and early prevention and management of metabolic syndrome can help in improving public health.
Body Scan UK: Body Composition Calculators
https://www.bodyscanuk.com/body-composition-calculators.html
2016 BIA ‘Standard Mode’ result: muscle-to-fat ratio may be derived
‘Athlete Mode’ taken on the same day for comparison, and may be validated by 2016 Whole-body DXA
Given 11.2% Body Fat, 19.8 BMI (without clothes weight)
My Fat Mass Index: approx. 2.3
My Lean Mass Index: approx. 17.5
Richard Benedict Baltazar
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