Estimate your body fat percentage using bioelectrical impedance analysis (BIA) principles.
Male
Female
Sedentary (little to no exercise)
Lightly Active (light exercise/sports 1-3 days/week)
Moderately Active (moderate exercise/sports 3-5 days/week)
Very Active (hard exercise/sports 6-7 days/week)
Extra Active (very hard exercise/sports & physical job)
How Body Fat Scales Calculate Body Fat (BIA Explained)
Body fat scales, often referred to as bioelectrical impedance analysis (BIA) scales, estimate your body composition by sending a low, safe electrical current through your body. This technology is based on the principle that different tissues in your body conduct electricity differently.
The Science Behind BIA
Fat Tissue vs. Lean Tissue:
Lean Body Mass (Muscle, Water, Bone): These tissues contain a high percentage of water and electrolytes, making them excellent conductors of electricity.
Fat Mass: Adipose tissue has a much lower water content and is therefore a poor conductor of electricity.
When you step on a BIA scale, the device measures the resistance (impedance) to the electrical current as it travels through your body. The scale sends the current through one foot and picks it up through the other. The higher the impedance, the more fat mass is estimated to be in your body.
The Calculation Formula
Body fat scales use complex algorithms that combine the measured impedance with your entered personal data to estimate your body fat percentage. While the exact proprietary formulas vary between manufacturers, a common approach involves using regression equations. These equations are derived from scientific studies that correlate BIA measurements with more direct measures of body fat (like DEXA scans). A simplified representation of factors involved might look at:
Impedance (Z): The measured resistance to the electrical current.
Weight (W): Your total body mass.
Height (H): Your body length.
Age: Metabolic rates and body composition change with age.
Gender: Men and women typically have different fat distribution and essential body fat percentages.
Activity Level: Affects muscle mass and hydration levels.
A common type of regression equation used for BIA is:
Body Fat % = (A * (Resistance / Height^2)) + (B * Weight) + (C * Age) + (D * Gender_Factor) + E
Where:
'Resistance' is the impedance measured.
'Height^2' is height squared.
'A', 'B', 'C', 'D', and 'E' are coefficients determined by the specific manufacturer's research and validation studies for different demographics and populations.
'Gender_Factor' is a numerical value assigned to male or female.
Note: The values for A, B, C, D, and E are specific to the scale's manufacturer and are not publicly disclosed. This calculator uses a generalized approximation for illustrative purposes.
Factors Affecting Accuracy
The accuracy of BIA scales can be influenced by several factors:
Hydration Levels: Dehydration increases impedance, leading to an overestimation of body fat. Conversely, overhydration can lead to underestimation.
Recent Meals or Exercise: Eating, drinking, or exercising shortly before a measurement can alter body water distribution and affect results.
Skin Contact: Ensuring clean, dry feet for good electrical contact is crucial.
Body Temperature: Higher body temperature can slightly decrease impedance.
Scale Technology: Different scales use different frequencies and algorithms, leading to slight variations in readings.
For the most consistent results, measure yourself under similar conditions each time, preferably in the morning after using the restroom, before eating or drinking.
Example Calculation Scenario
Let's consider a 35-year-old male, 180 cm tall, weighing 85 kg, who engages in moderate exercise 4 times a week. Suppose his BIA scale measured an impedance of 500 ohms.
Using a simplified model that incorporates these factors, the scale's internal algorithm would process these inputs to arrive at an estimated body fat percentage. For instance, a common set of generalized coefficients might yield a result around 22% body fat for this individual, indicating a need to consult the scale's specific manual for precise interpretation.
function calculateBodyFat() {
var weightKg = parseFloat(document.getElementById("weightKg").value);
var heightCm = parseFloat(document.getElementById("heightCm").value);
var age = parseInt(document.getElementById("age").value);
var gender = document.getElementById("gender").value;
var activityLevel = document.getElementById("activityLevel").value;
var resultDiv = document.getElementById("result");
resultDiv.innerHTML = "; // Clear previous result
if (isNaN(weightKg) || isNaN(heightCm) || isNaN(age) || weightKg <= 0 || heightCm <= 0 || age <= 0) {
resultDiv.innerHTML = "Please enter valid positive numbers for Weight, Height, and Age.";
return;
}
// Simplified BIA estimation using a common regression approach.
// Actual formulas are proprietary and complex.
// This is for illustrative purposes only.
// Convert height from cm to meters for some formulas
var heightM = heightCm / 100;
var heightSquared = heightM * heightM;
// Basic Impedance Factor (rough approximation)
// Higher impedance means more fat. This is a placeholder for actual impedance measurement.
// We'll use a formula that derives a hypothetical impedance from user inputs as a stand-in.
// A more realistic calculator would *measure* impedance directly.
// For this simulation, let's create a hypothetical 'resistance' value.
var hypotheticalResistance = (weightKg / heightSquared) * 1000; // This is NOT actual impedance but a derived factor
var bodyFatPercentage = 0;
// Gender factor
var genderFactor = (gender === "male") ? 5 : -2; // Simplified factor
// Activity level adjustment (very basic, actual formulas are more complex)
var activityMultiplier = 1.0;
switch (activityLevel) {
case "sedentary":
activityMultiplier = 0.1;
break;
case "light":
activityMultiplier = 0.15;
break;
case "moderate":
activityMultiplier = 0.20;
break;
case "very_active":
activityMultiplier = 0.25;
break;
case "extra_active":
activityMultiplier = 0.30;
break;
}
// Simplified Regression Formula (example structure)
// This formula is a highly generalized representation. Real formulas are much more intricate.
// The primary component is resistance, adjusted by other factors.
// Let's use a structure that loosely resembles common BIA formulas.
// Formula Example: BF% = (A * Resistance) + (B * Weight) + (C * Age) + D
// We'll use a placeholder for 'A' and coefficients 'B', 'C', 'D' and add our gender/activity adjustments.
var coefficientA = 0.001; // Placeholder coefficient for resistance impact
var coefficientB = 0.05; // Placeholder coefficient for weight impact
var coefficientC = -0.1; // Placeholder coefficient for age impact (older tend to have slightly different fat comp)
var constantD = 30; // Base constant
bodyFatPercentage = (coefficientA * hypotheticalResistance) + (coefficientB * weightKg) + (coefficientC * age) + constantD + genderFactor – activityMultiplier;
// Ensure body fat percentage is within a reasonable range (e.g., 1% to 70%)
bodyFatPercentage = Math.max(1, Math.min(70, bodyFatPercentage));
resultDiv.innerHTML = 'Estimated Body Fat: ' + bodyFatPercentage.toFixed(1) + '%';
}
// Optional: Add event listeners to update range values if range sliders were used
// For this example, we are using number inputs, so this is not strictly necessary.