Why Two Energy Estimates Can Both Look Plausible

Separate the equation from the activity choice

The Mifflin–St Jeor equation is a population-based starting estimate for resting energy expenditure. A maintenance estimate then applies an activity assumption. That second step is not a direct measurement of your individual day. Nutrinaut Tools deliberately shows a range instead of treating one multiplier as the truth.

For a fictional 30-year-old at 70 kg and 175 cm using the published male equation branch, the resting estimate is 10 × 70 + 6.25 × 175 − 5 × 30 + 5 = 1,648.75 kcal/day. The equation’s male/female constants are published model parameters, not a complete description of identity or physiology.

Change only the assumption

The resting equation has not changed between rows. The activity classification alone moves the estimate. That is why a watch, a calculator and a food log can disagree without any of them revealing an exact personal requirement. Do not choose the row that best matches a target weight; choose the band that best describes the period being estimated, then treat it as a starting hypothesis.

What a two-week log can and cannot settle

A consistent log of intake and comparable morning weights may help you decide whether a starting interval is useful. Compare averages of days 1–7 and 8–14 rather than one reading. Training changes, fluid shifts, illness, travel and incomplete logging can overwhelm a short signal. Two weeks are a practical review window, not validation of your true expenditure.

The tool never turns a short change into a supposedly precise calorie correction. It does not set weight-loss deadlines, minimum intakes or medical diets. People with a clinical diet, eating-disorder history, pregnancy or unusually high training volume need individual support.

Make the estimate accountable

1. Record the equation branch, units and activity band used.
2. Keep the first estimate and its range instead of repeatedly adjusting it to fit a desired outcome.
3. If tracking is appropriate, review a consistent period and note major changes.
4. When the evidence is noisy, say “uncertain” and collect better data rather than adding decimal places.

Recalculate with visible assumptions or read the full method guide.