A scan is useful, but it is not a verdict. OptiSpan separates measured values, device estimates, and screening baselines so your plan never pretends the data is more precise than it is.
We normalize the report’s body weight, body-fat percentage, fat mass, and fat-free mass. Because BOD POD uses air-displacement plethysmography, we treat it as a direct report source—not something to reverse-engineer from a photo.
Starting composition, fat-to-lean balance, goal pacing, and same-method trend comparisons.
We capture weight, skeletal muscle mass, body-fat mass, percent body fat, segmental lean values, visceral-fat output, and body-water context when present.
Muscle distribution, composition targets, hydration-aware interpretation, and repeat testing under similar conditions.
Height and weight produce an adult BMI screening value. Age, sex used by the measurement model, activity, goals, and optional waist circumference add context. We do not present this as measured body-fat percentage.
Conservative calorie and training starting points, weight and waist trends, performance markers, and later recalibration.
Select the device or method and add the report date.
Enter body-fat percentage and lean mass from the report. This prevents an OCR mistake from silently becoming a plan input.
Convert units, check plausible ranges, record the method, and assign a confidence label.
Set training volume, nutrition targets, milestone pacing, and the most meaningful progress measures for that data quality.
InBody measurements can shift with food, exercise, body-water distribution, and testing time. Progress should be compared using the same method under similar conditions. BMI is useful as a screening measure but cannot distinguish fat, muscle, and bone.