Goal

Investigating TDEE and BMR overshoot in "Sedentary and Overweight" cohorts when online calculators are used.

Approach: We will employ a deterministic data analysis method to explore this phenomenon.

Why does it matter?

If someone who is overweight uses an online TDEE calculator that does not account for body fat percentage or lean mass, they may receive significantly inflated BMR and TDEE estimates.

Most users either skip entering body fat entirely or rely on visual estimates, which are often highly inaccurate, either overestimated or underestimated, leading to misleading TDEE and BMR. Our paper investigates and quantifies this exact issue.

Muscle burns more energy at rest than fat, meaning two individuals with the same height, weight, and BMI can have significantly different Basal Metabolic Rates (BMRs) depending on their body composition.

Skeletal muscle burns approximately 13 kcal/kg/day, while fat burns only about 4.5 kcal/kg/day. This inherent difference implies that a muscular person will have a notably higher BMR compared to someone with high fat mass, even if their BMI is identical. For instance, a 10 kg increase in lean mass can raise BMR by approximately 100 to 130 kcal/day. This relationship has been confirmed in studies such as Gallagher et al. (1998) in Am J Physiol and Muller et al. (2010) in Obesity Reviews.

Body Mass Index (BMI) does not account for individual body composition.

BMR and TDEE Definitions

Basal Metabolic Rate (BMR): BMR is the energy your body uses at rest, in a fasted state, solely to maintain vital physiological functions such as heartbeat, brain activity, and breathing.

Total Daily Energy Expenditure (TDEE): TDEE represents the total energy expended by your body over a full day. This includes BMR plus additional energy components like physical activity and the thermic effect of food.

Most online calculators typically estimate TDEE using a simplified approach:

TDEE = BMR × Activity Factor

A more rigorous TDEE calculation approach considers additional factors:

TDEE = (BMR + NEAT + EE) / (1 - TEF%)

Where:

• BMR is Basal Metabolic Rate
• NEAT is Non-Exercise Activity Thermogenesis, often estimated using a hybrid category plus steps approach
• EE is Exercise Energy Expenditure, calculated via selected METs
• TEF% is the Thermic Effect of Food. Different macronutrients have varying thermic effects, usually expressed as a percentage of consumed calories

If you want the practical version instead of the theory, use the TDEE Calculator.

Mifflin-St Jeor Equation

This is one of the most widely used equations for estimating BMR and does not require body fat percentage.

It was developed as an improvement over older equations like Harris-Benedict, which tended to overestimate BMR, particularly in overweight and obese individuals.

Many online discussions suggest it was validated in a sample that included overweight and obese subjects and tends to be more accurate than Harris-Benedict or FAO/WHO/UNU equations for modern populations with higher obesity prevalence.

• Men: BMR = 10 × weight(kg) + 6.25 × height(cm) - 5 × age(years) + 5
• Women: BMR = 10 × weight(kg) + 6.25 × height(cm) - 5 × age(years) - 161

This formula is commonly used in online calculators when body fat percentage is unknown.

Source: Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990 Feb;51(2):241-7.

Katch-McArdle Equation

This equation utilizes lean body mass (LBM) and is generally considered more accurate for trained or muscular individuals.

• Formula: BMR = 370 + (21.6 × LBM in kg)
• LBM = weight(kg) × (1 - body fat% as a decimal)
• Use when: You know or can reliably estimate body fat percentage

Source: Katch VL, McArdle WD. Nutrition, Weight Control, and Exercise. 1973.

Investigation Using Deterministic Data Analysis Approach

Our methodology involves using sample population data: age, weight, height, and gender, to first calculate BMR using the Mifflin-St Jeor Equation.

Crucial Assumption: We assume all individuals in the sample data are sedentary and do not engage in regular workouts.

Following the BMR calculation, we reverse-calculate Body Fat Percentage (BF%) and Fat-Free Mass Index (FFMI) using the Katch-McArdle Equation.

This approach reveals important insights into the accuracy of the Mifflin-St Jeor Equation when applied to individuals with higher body weight.

Results

Findings

Our analysis, primarily focused on a sedentary and overweight cohort (BMI >= 25) but including some normal-weight individuals (BMI 18.5 to 24.9) for comparative purposes, reveals that the Mifflin-St Jeor equation often overestimates Basal Metabolic Rate (BMR).

This overestimation leads to unrealistic body composition metrics when reverse-calculated using the Katch-McArdle equation, especially for a sedentary population. Key observations include:

• High FFMI Values in Overweight Individuals: For many sedentary, overweight individuals in our sample, the analysis reports Fat-Free Mass Index (FFMI) values above 22.5, such as FFMI 25.9 for a male age 46 with BMI 39.9, and FFMI 24.5 for a male age 66 with BMI 40.2.
• FFMI values exceeding 22.5 typically require years of dedicated strength training, and values of 24 to 25.9 are comparable to pre-steroid era Mr. America winners, average FFMI about 25, as noted in Kouri et al. (1995).
• These exceptionally high FFMI values are implausible for a sedentary cohort, strongly indicating BMR overestimation by the Mifflin-St Jeor equation for this group.
• Lower-Than-Expected Body Fat Percentages in Normal-Weight Individuals: While our primary focus is the overweight cohort, some normal-weight individuals also show lower-than-expected implied body fat percentages, such as 12.2% for a male age 25 with BMI 22.0, and 19.8% for a female age 22 with BMI 19.7.
• Given that sedentary individuals typically have higher fat mass, generally 20 to 30% for men and 25 to 35% for women, this suggests that Mifflin-St Jeor may also overestimate BMR even in this group, leading to an inflated estimation of lean body mass.
• Impact of BMI Filter: Filtering the dataset to exclude underweight individuals (BMI < 18.5) successfully eliminated unrealistic negative or 0% body fat percentages, thereby improving the reliability of our results.
• Including normal-weight individuals provides useful context, but the consistently high FFMI values observed in the overweight cohort (BMI >= 25) remain the most compelling evidence of BMR overshoot.

Source for FFMI claims: Kouri EM, Pope HG Jr, Katz DL, Oliva P. Fat-Free Mass Index in Users and Nonusers of Anabolic-Androgenic Steroids. Clin J Sport Med. 1995.

Conclusion

The Mifflin-St Jeor equation tends to overestimate BMR and, consequently, Total Daily Energy Expenditure (TDEE) for sedentary individuals, particularly those who are overweight (BMI >= 25). This is strongly evidenced by the unrealistically high FFMI values, up to 25.9, derived from our analysis.

Even in some normal-weight cases (BMI 18.5 to 24.9), the equation leads to lower-than-expected body fat percentages, which similarly imply an excessive lean body mass for a sedentary population. The overestimation likely stems from the equation's reliance on total body weight without adequately accounting for individual body composition differences.

While filtering out underweight individuals (BMI < 18.5) improved the analysis's robustness, the high FFMI values in the overweight cohort remain the most significant indicator of BMR overshoot.

This is also why we built pages like Actual TDEE and Adaptive TDEE instead of relying on one fixed equation plus a vague activity multiplier.

Also posted on Reddit: How we Built Most Accurate TDEE Calculator which finds ACTUAL TDEE