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Case Studies | Male (42) Obesity
Manage episode 358716388 series 3460091
A tartalmat a Bodytrack biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Bodytrack vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
This podcast was about the downfalls of using predictive measures for weight loss, specifically with a client that had hit a plateau with his weight loss. More research is finding BMR prediction may only be accurate ∼40% of the time, regardless of gender and weight classification. Furthermore, individuals within the "overweight" classification often metabolise fats and/or carbohydrates very differently which means generic meal/exercise plans may not be appropriate. Listen on to find out what methods and technology can be utilised to help in individualising weight loss methods rather than predictive methods. https://www.sciencedirect.com/science/article/abs/pii/S1871403X15001118
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- this article found that BMR prediction was only accurate ∼40% of the time, regardless of gender and weight classification.
- This found that overweight individuals with metabolic syndrome or type 2 diabetes had lower capacity for fat metabolism
- Overweight individuals without metabolic conditions tended to utilize fat quite well
- Therefore utilisng generic exercise and diet guidelines may not be optimal for all overweight individuals
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