Methodology

Sources & Methodology

Last Updated: August 30, 2026

This page explains how Rebalance calculates the numbers it shows you and where its nutrition data comes from. Every formula below is published, peer-reviewed, and widely used in clinical and sports nutrition.

Rebalance is not medical advice. The targets it produces are estimates for healthy adults. Talk to a doctor or registered dietitian before changing your diet if you are pregnant, under 18, have a medical condition, or take medication that affects appetite or weight.

1. Starting calorie target

Your first daily calorie target starts from an estimate of resting metabolic rate using the Mifflin-St Jeor equation, which a systematic review found to be the most accurate predictive equation for healthy adults [1]. That figure is multiplied by a standard activity factor (1.2 sedentary to 1.9 extra active) to estimate total daily energy expenditure [2].

If your goal weight is below your current weight, we subtract 400 kcal/day; if it is above, we add 250 kcal/day. These sizes correspond to roughly 0.5–1% and 0.25–0.5% of body weight per week, a range associated with better preservation of lean mass than faster rates [3].

2. Macro split

Protein is set at 1.6–1.8 g per kilogram of body weight, the range at which a meta-analysis of 49 trials found muscle gains plateau during resistance training [4]. The remaining calories are split roughly 60/40 between carbohydrate and fat. Calories are computed at 4 kcal/g for protein and carbohydrate and 9 kcal/g for fat.

3. Weekly check-in adjustments

Predictive equations are only a starting point; measured metabolic rate can differ from the estimate by several hundred kcal, and it changes as you lose or gain weight [5, 6]. So each week Rebalance re-estimates your actual energy expenditure from what you logged and how your weight trended, using the energy-balance method validated by Sanghvi et al. [7] and the body-weight dynamics described by Hall et al. [8, 9].

Adjustments are capped at ±300 kcal per week and skipped when logged intake is below 80% of your target, so a single unusual week cannot swing your plan. Weight trend uses a smoothed average of your weigh-ins rather than single readings, because daily scale weight fluctuates by 1–2% from water and food [10].

Longer explanations, written with a registered dietitian, are in How check-ins work and How rebalancing works.

4. Food nutrition data

  • Search. Foods found through search come from the FatSecret Platform API, whose database is compiled from manufacturer labels and government sources such as the USDA FoodData Central.
  • Barcode scan. Barcodes are looked up in Open Food Facts, an open, crowd-sourced product database. Values reflect the product label as submitted.
  • Photo scan and text estimate. Nutrition from a meal photo, or from the “Estimate” button on a food name in Manual entry, is an AI estimate of a typical portion. Treat it as an approximation and check the packaging when one is available.
  • Manual entry. Values you type in are stored as entered.

References

  1. Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc. 2005;105(5):775-789. jandonline.org
  2. FAO/WHO/UNU. Human energy requirements: Report of a Joint FAO/WHO/UNU Expert Consultation. Rome; 2004. Chapter 5, physical activity levels. fao.org
  3. Garthe I, Raastad T, Refsnes PE, Koivisto A, Sundgot-Borgen J. Effect of two different weight-loss rates on body composition and strength and power-related performance in elite athletes. Int J Sport Nutr Exerc Metab. 2011;21(2):97-104. pubmed
  4. Morton RW, Murphy KT, McKellar SR, et al. A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training-induced gains in muscle mass and strength in healthy adults. Br J Sports Med. 2018;52(6):376-384. bjsm.bmj.com
  5. Leibel RL, Rosenbaum M, Hirsch J. Changes in energy expenditure resulting from altered body weight. N Engl J Med. 1995;332(10):621-628. nejm.org
  6. Fothergill E, Guo J, Howard L, et al. Persistent metabolic adaptation 6 years after “The Biggest Loser” competition. Obesity. 2016;24(8):1612-1619. wiley
  7. Sanghvi A, Redman LM, Martin CK, Ravussin E, Hall KD. Validation of an inexpensive and accurate mathematical method to measure long-term changes in free-living energy intake. Am J Clin Nutr. 2015;102(2):353-358. pmc
  8. Hall KD, Sacks G, Chandramohan D, et al. Quantification of the effect of energy imbalance on bodyweight. Lancet. 2011;378(9793):826-837. pubmed
  9. Hall KD. The dynamics of human body weight change. PLoS Comput Biol. 2008;4(3):e1000045. pmc
  10. Walker J. The Hacker’s Diet, “Signal and Noise.” fourmilab.ch