Energy balance
Mathematical models of body weight dynamics accurately predict average weight loss in compliant patients, but individual prediction precision is fundamentally limited by uncertainty in baseline energy requirements and physical activity changes.
Use dynamic weight loss models to set realistic expectations and track progress, but understand that individual results will vary. If you are adhering to a plan but not losing weight as predicted, it may be due to your unique baseline metabolism or activity changes, not just 'cheating'. Use the model's predicted range to discuss barriers with your clinician rather than assuming failure.
The model predictions were highly correlated with the individual weight loss data at the latest clinic visit (r = 0.9; P < 0.0001)... The mean 13.2 ± 8.9 kg weight loss observed in the patients was not significantly different from the model calculations (14.0 ± 9.1 kg; P = 0.14).
Why this rating
Observational study with a validated mathematical model; high correlation (r=0.9) but limited by small sample size (n=49) and lack of randomization.
Source
Dispatch from the field: Is mathematical modeling applicable to obesity treatment in the real world?
Ignatius Brady et al. · Obesity · 2014
DOI 10.1002/oby.20804
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