4 ms·
You have mostly lost water to be precise. As well as muscle. You need an expensive Dual-energy X-ray absorptiometry scan in order to precisely tell the body ma
by sdze 4y ago
You have mostly lost water to be precise.
As well as muscle.
You need an expensive Dual-energy X-ray absorptiometry scan in order to precisely tell the body mass composition.
- aenis 4y agoHow would you know, without the "expensive" densitometry scan? My anecdotal experience: I lost weight via alternate day fasting and did indeed shell out the 120 euro that two scans cost me. I lost mainly fat, my lean body mass after 6 months was down 4 pct, within error range I'd assume. I worked out normally through the entire period and even did things like a 200km bike trip during a 72hr fast. (I did a few of those to compensate for not fasting on holidays). Great experience, never felt better tbh. One thing I think I learned was the exact threshold of power that allowed me to keep burning fat. Its hard to describe the feeling but after doing this for months (over a year by now) I think I know exactly when I can still push and continue on fat, and when I need to slow down to prevent lbm loss. Doing sprints, short intervals etc. would likely cause me to break proteins in the body and indeed be counterproductive - but here more research is probably needed, and individuals will likely have different thresholds.
- hsn915 4y agoWhy would the body shed water instead of tapping into stored fat when there's no external energy coming it? This is delusional.
- orangepurple 4y agoIf you can't get a DEXA scan there is an equation published in December of 2021 which approximates it well: The new equation [%BFNew = 6.083 + (0.143 × SSnew) - (12.058 × sex) - (0.150 × age) - (0.233 × body mass index) + (0.256 × waist) + (0.162 × sex × age)] explained a significant proportion of variance in %BF5C (R2 = 0.775, SEE = 4.0%). Predictors included sum of skinfolds (SSnew, midaxillary, triceps, and thigh) and waist circumference. The new equation cross-validated well against %BF5C when compared with other existing equations, producing a large intraclass correlation coefficient (0.90), small mean bias and limits of agreement (0.4% ± 8.6%), and small measures of error (SEE = 2.5%). Generalized Equations for Predicting Percent Body Fat from Anthropometric Measures Using a Criterion Five-Compartment Model Zackary S Cicone, Brett S Nickerson 1, Youn-Jeng Choi 2, Clifton J Holmes 3, Bjoern Hornikel 4, Michael V Fedewa 4, Michael R Esco 4 Affiliations expand PMID: 34310492 PMCID: PMC8785250 (available on 2022-12-01) DOI: 10.1249/MSS.0000000000002754 https://pubmed.ncbi.nlm.nih.gov/34310492/ https://pubmed.ncbi.nlm.nih.gov/34310492/