Infant Weight Percentile Calculator (CDC) – Track Your Baby’s Growth

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th, td {
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}

Infant Weight Percentile Calculator (CDC)

Easily calculate and understand your baby’s weight percentile using CDC growth charts.

Infant Growth Tracker

Enter your baby’s details to see their weight percentile according to the CDC growth charts.

Baby’s Age (Months):

Enter the age in whole months (0-36 months).

Baby’s Weight (kg):

Enter the weight in kilograms.

Baby’s Gender:

Boy
Girl

Select your baby’s gender.

—

Age: — mos |
Weight: — kg |
Gender: —

Formula: Percentile is determined by comparing your baby’s weight for their age and gender against the CDC’s reference population data.

Growth Data Table (Example for Boys)

This table shows sample weights at different percentiles for boys at 6 months of age.

Percentile	Weight (kg)	Interpretation
3rd	6.2	Very Low
10th	6.8	Low
25th	7.3	Below Average
50th	8.0	Average
75th	8.7	Above Average
90th	9.3	High
97th	9.8	Very High

Weight Percentile Distribution

Baby’s Weight
Average (50th)
Guideline Range

What is Infant Weight Percentile (CDC)?

An infant weight percentile, based on the Centers for Disease Control and Prevention (CDC) growth charts, is a way to compare a baby’s weight against other babies of the same age and sex. It indicates the percentage of babies who weigh less than or equal to that specific baby. For example, if a baby is at the 75th percentile for weight, it means they weigh more than 75% of babies of the same age and sex, and less than 25%.

This metric is crucial for monitoring a baby’s growth trajectory. Healthy growth is typically characterized by a consistent percentile or a smooth curve. Significant drops or jumps in percentile can sometimes indicate underlying health issues that warrant medical attention.

Who Should Use It?

The primary users are parents and caregivers who want to understand their baby’s growth. Pediatricians and healthcare providers rely heavily on these percentiles during regular check-ups to assess if a baby is growing adequately and to identify potential concerns early on. It’s a standard tool in pediatric care.

Common Misconceptions

One common misconception is that a low percentile (e.g., below 10th) always means a baby is underweight or unhealthy. This isn’t necessarily true; some babies are naturally smaller. The consistency of the percentile over time is often more important than the absolute number. Another misconception is that a high percentile (e.g., above 90th) always means a baby is overweight. While it can be a concern in some cases, especially if it represents rapid weight gain, it’s essential to consider the baby’s overall health, development, and feeding patterns.

Infant Weight Percentile Formula and Mathematical Explanation

The calculation of an infant’s weight percentile isn’t a simple arithmetic formula that you can plug numbers into directly. Instead, it involves looking up the baby’s specific age, sex, and weight on complex statistical tables or using software that implements the CDC’s LMS (Lambda-Mu-Sigma) method. This method is designed to model the distribution of a growth metric (like weight) across a population.

Here’s a conceptual breakdown:

Data Collection: The CDC gathers extensive data on the weight of a large number of healthy infants and children, separated by sex.
LMS Parameters: For each age and sex, three values are calculated:
- L (Lambda): Skewness factor, which accounts for the asymmetry of the distribution.
- M (Mu): Median (50th percentile) value.
- S (Sigma): Coefficient of variation, which measures the variability around the median.
Z-Score Calculation: The baby’s actual weight (W) is converted into a standardized score (Z) using the LMS parameters for their specific age and sex. The formula is: Z = ( (W/M)^L - 1 ) / (L*S). If L=0, a logarithmic transformation is used.
Percentile Calculation: The Z-score is then used to find the corresponding percentile (P) from a standard normal distribution. This step essentially asks: “What percentage of babies have a Z-score less than or equal to this baby’s Z-score?”

Variables Table

Variable	Meaning	Unit	Typical Range (Approximate)
Age	Baby’s age in months	Months	0 – 36
Weight (W)	Baby’s measured weight	Kilograms (kg)	0.5 – 20 (for 0-36 months)
Gender	Baby’s sex	Categorical (Boy/Girl)	Boy, Girl
LMS Parameters (L, M, S)	Statistical parameters defining the growth distribution for a given age and sex	Varies (L: skewness, M: median weight, S: variation)	Dependent on age and sex
Z-Score	Standardized score representing deviation from the median	Unitless	-3 to +3 (typically)
Percentile (P)	Percentage of babies weighing less than or equal to the baby	%	0 – 100

Our calculator utilizes these principles, referencing CDC data to provide an accurate percentile estimate.

Practical Examples (Real-World Use Cases)

Example 1: A 6-Month-Old Baby Boy

Inputs:

Baby’s Age: 6 months
Baby’s Weight: 8.0 kg
Baby’s Gender: Boy

Calculation: Using the CDC data for a 6-month-old boy, a weight of 8.0 kg falls exactly on the 50th percentile. This means the baby weighs more than 50% of other 6-month-old boys and less than 50%. This is often considered the “ideal” or average growth point.

Interpretation: The baby is growing right in line with the average for his age and sex. This is generally a positive sign, indicating healthy development according to population standards.

Example 2: A 12-Month-Old Baby Girl

Inputs:

Baby’s Age: 12 months
Baby’s Weight: 9.5 kg
Baby’s Gender: Girl

Calculation: For a 12-month-old girl, a weight of 9.5 kg might place her around the 70th percentile according to CDC charts. This indicates she is heavier than 70% of girls her age.

Interpretation: This baby is growing well and is above the average weight for her age group. While not necessarily concerning, the pediatrician will monitor her growth trend to ensure it remains steady and doesn’t accelerate too rapidly. Consistent growth within a higher percentile is generally reassuring.

How to Use This Infant Weight Percentile Calculator

Our calculator simplifies the process of determining your baby’s weight percentile. Follow these easy steps:

Enter Baby’s Age: Input the exact age of your baby in months. The calculator is most accurate for ages 0 through 36 months.
Enter Baby’s Weight: Provide your baby’s current weight in kilograms (kg). Ensure you use a reliable scale for accurate measurement.
Select Baby’s Gender: Choose ‘Boy’ or ‘Girl’ from the dropdown menu, as growth charts differ between sexes.
View Results: Once you input the data, the calculator will instantly display:
- Primary Result: Your baby’s weight percentile (%).
- Intermediate Values: Confirms the age, weight, and gender entered.
- Interpretation Guide: A brief note on what the percentile means.

How to Read Results

The main result is the percentile number (e.g., 40th, 75th). Remember, this is a comparison tool:

50th Percentile: The baby is average weight for their age and sex.
Above 50th Percentile (e.g., 75th, 90th): The baby weighs more than that percentage of peers.
Below 50th Percentile (e.g., 25th, 10th): The baby weighs less than that percentage of peers.

Crucially, focus on the *trend* over time. A consistent percentile suggests steady growth. Significant shifts require discussion with your pediatrician.

Decision-Making Guidance

This calculator is an informational tool, not a diagnostic one. Always consult your pediatrician for health and growth assessments. If the percentile is unusually high or low, or if it changes dramatically between visits, discuss your concerns with your doctor. They will consider this data alongside other factors like length, head circumference, feeding habits, and overall development.

Key Factors That Affect Infant Weight Percentile Results

While the calculator uses age, weight, and gender, several real-world factors influence these measurements and their interpretation:

Genetics: Just like adults, babies inherit predispositions for body size and growth rate. A baby from taller or heavier parents might naturally trend higher on the growth charts.
Feeding Practices: The type and frequency of feeding (breast milk, formula, solids) significantly impact weight gain. Adequacy of intake is key; exclusive breastfeeding can lead to different initial growth patterns compared to formula feeding.
Preterm Birth: Premature babies often have different growth trajectories. While corrected age might be used, their early developmental stage can influence weight gain patterns compared to full-term infants.
Health Conditions: Underlying medical issues, such as digestive problems (e.g., reflux, malabsorption), metabolic disorders, or chronic illnesses, can affect a baby’s ability to gain weight appropriately.
Activity Level: As babies grow more mobile, their energy expenditure increases. A very active baby might gain weight more slowly than a less active one, even with similar intake.
Water Retention & Hydration: Dehydration can temporarily lower weight, while certain conditions might cause fluid retention, artificially increasing it. These are usually transient but can affect a single measurement.
Measurement Accuracy: Inconsistent or inaccurate weighing methods can lead to skewed percentile results. Using the same calibrated scale and ensuring the baby is dressed similarly (or undressed) for each weigh-in is important.

Frequently Asked Questions (FAQ)

What is the difference between weight percentile and BMI percentile?

Weight percentile specifically tracks weight relative to age and sex. BMI percentile considers both weight and height for age and sex, providing a broader picture of body composition, often used for older children. For infants under 2, the CDC primarily uses weight-for-age, length-for-age, and head circumference-for-age charts. This calculator focuses on weight-for-age.

My baby dropped a percentile line. Should I be worried?

A single drop might not be cause for alarm, especially if it’s a small shift. However, a significant or consistent drop in percentile warrants a discussion with your pediatrician. They will assess other growth parameters and the baby’s overall health to determine the cause.

What if my baby is consistently above the 90th percentile?

Consistent high percentiles can sometimes indicate rapid weight gain. Your pediatrician will evaluate this in context, considering factors like feeding adequacy, activity levels, and family history. They might check for underlying issues or provide guidance on nutrition and activity as the baby grows.

Can I use this calculator for babies older than 3 years?

No, this calculator is specifically designed for the CDC’s infant and toddler growth charts, which typically cover ages 0-36 months (birth to 3 years). For older children, different growth charts (e.g., BMI-for-age) are used.

How often should my baby’s weight be checked?

Pediatricians typically check weight during well-baby visits, which are frequent in the first year (e.g., 1, 2, 4, 6, 9, 12 months). Your doctor will advise on the appropriate schedule based on your baby’s individual needs.

Does birth weight affect percentile later on?

Birth weight is a starting point. While babies often adjust their growth trajectory in the first few weeks or months, a very low or high birth weight might influence the initial percentiles. However, growth after the newborn period is the main focus for tracking long-term development.

What is the CDC’s role in growth charts?

The CDC provides the official growth charts used in the United States. These charts are based on data from large national health surveys and are considered the standard for assessing child growth.

Is it better to be at a high or low percentile?

Neither extreme is inherently “better.” The most important factor is consistent growth along a percentile curve. Both very low and very high percentiles, especially if they represent rapid change, should be monitored by a healthcare professional. The goal is healthy, steady growth appropriate for the individual child.

Related Tools and Internal Resources

Baby Length Percentile Calculator Track your baby’s length growth relative to age and gender.
Head Circumference Calculator Monitor your baby’s head growth using CDC standards.
Infant Feeding Guide Tips and advice on breastfeeding and formula feeding.
Baby Milestones Tracker Follow your baby’s development milestones from birth to toddlerhood.
Pediatrician Visit Checklist Prepare for your baby’s next check-up with essential questions.
Understanding Child Development Explore developmental stages and common concerns.

// Basic CDC Growth Data Simulation (simplified for demonstration)
// In a real application, this would be a much larger dataset or a more sophisticated algorithm.
// Data structure: { gender: { age_months: { percentile: weight_kg } } }
var cdcWeightData = {
boy: {
0: { 3: 2.7, 10: 3.0, 25: 3.4, 50: 3.7, 75: 4.0, 90: 4.3, 97: 4.5 },
1: { 3: 3.8, 10: 4.2, 25: 4.7, 50: 5.1, 75: 5.6, 90: 6.0, 97: 6.4 },
3: { 3: 5.5, 10: 6.2, 25: 7.0, 50: 7.8, 75: 8.6, 90: 9.4, 97: 10.0 },
6: { 3: 6.8, 10: 7.6, 25: 8.4, 50: 9.2, 75: 10.0, 90: 10.8, 97: 11.5 },
9: { 3: 7.8, 10: 8.7, 25: 9.6, 50: 10.5, 75: 11.4, 90: 12.3, 97: 13.1 },
12: { 3: 8.5, 10: 9.5, 25: 10.5, 50: 11.5, 75: 12.5, 90: 13.5, 97: 14.5 },
18: { 3: 9.5, 10: 11.0, 25: 12.2, 50: 13.5, 75: 14.8, 90: 16.0, 97: 17.0 },
24: { 3: 10.2, 10: 12.0, 25: 13.5, 50: 15.0, 75: 16.5, 90: 18.0, 97: 19.5 },
30: { 3: 11.0, 10: 13.0, 25: 14.5, 50: 16.0, 75: 17.5, 90: 19.0, 97: 20.5 },
36: { 3: 11.5, 10: 13.5, 25: 15.0, 50: 16.5, 75: 18.0, 90: 19.5, 97: 21.0 }
},
girl: {
0: { 3: 2.5, 10: 2.8, 25: 3.2, 50: 3.5, 75: 3.8, 90: 4.1, 97: 4.3 },
1: { 3: 3.5, 10: 3.9, 25: 4.4, 50: 4.8, 75: 5.2, 90: 5.6, 97: 6.0 },
3: { 3: 5.0, 10: 5.7, 25: 6.5, 50: 7.3, 75: 8.1, 90: 8.9, 97: 9.5 },
6: { 3: 6.2, 10: 7.0, 25: 7.8, 50: 8.6, 75: 9.4, 90: 10.2, 97: 10.9 },
9: { 3: 7.2, 10: 8.1, 25: 9.0, 50: 9.9, 75: 10.8, 90: 11.7, 97: 12.5 },
12: { 3: 7.8, 10: 8.9, 25: 9.9, 50: 10.9, 75: 11.9, 90: 12.9, 97: 13.9 },
18: { 3: 8.8, 10: 10.2, 25: 11.5, 50: 12.8, 75: 14.0, 90: 15.3, 97: 16.5 },
24: { 3: 9.5, 10: 11.2, 25: 12.7, 50: 14.2, 75: 15.7, 90: 17.2, 97: 18.5 },
30: { 3: 10.2, 10: 12.0, 25: 13.5, 50: 15.0, 75: 16.5, 90: 18.0, 97: 19.5 },
36: { 3: 10.8, 10: 12.7, 25: 14.2, 50: 15.7, 75: 17.2, 90: 18.7, 97: 20.2 }
}
};

var chartInstance = null;

function calculatePercentile() {
var ageInput = document.getElementById(“babyAge”);
var weightInput = document.getElementById(“babyWeight”);
var genderSelect = document.getElementById(“babyGender”);

var age = parseFloat(ageInput.value);
var weight = parseFloat(weightInput.value);
var gender = genderSelect.value;

clearErrorMessages();

var isValid = true;
if (isNaN(age) || age 36) {
document.getElementById(“babyAgeError”).innerText = “Please enter a valid age between 0 and 36 months.”;
document.getElementById(“babyAgeError”).style.display = “block”;
isValid = false;
}
if (isNaN(weight) || weight <= 0) {
document.getElementById("babyWeightError").innerText = "Please enter a valid weight greater than 0 kg.";
document.getElementById("babyWeightError").style.display = "block";
isValid = false;
}

if (!isValid) {
updateResults('–', '–', '–', '–');
return;
}

// Find the closest age in our simplified data
var relevantAgeData = null;
var closestAge = null;
var dataForGender = cdcWeightData[gender];

if (dataForGender) {
var ages = Object.keys(dataForGender).map(Number).sort(function(a, b) { return a – b; });
for (var i = 0; i < ages.length; i++) {
if (age 0) {
closestAge = ages[ages.length – 1];
relevantAgeData = dataForGender[closestAge];
}
}

var percentile = ‘–‘;
var interpretation = ‘N/A’;

if (relevantAgeData) {
var weights = Object.values(relevantAgeData);
var minWeight = Math.min(…weights);
var maxWeight = Math.max(…weights);

var calculatedPercentile = ‘–‘;

if (weight < minWeight) {
calculatedPercentile = ' maxWeight) {
calculatedPercentile = ‘> 97’;
interpretation = “Significantly Above Average”;
} else {
// Find the percentile by iterating through sorted weights
var sortedWeights = [];
var percentileMap = {};
var sortedPercentiles = Object.keys(relevantAgeData).map(Number).sort(function(a, b) { return a – b; });
for (var p = 0; p < sortedPercentiles.length; p++) {
var perc = sortedPercentiles[p];
var w = relevantAgeData[perc];
sortedWeights.push(w);
percentileMap[w] = perc;
}

for (var i = 0; i = sortedWeights[i] && weight < sortedWeights[i+1]) {
var lowerPerc = sortedPercentiles[i];
var upperPerc = sortedPercentiles[i+1];
var lowerWeight = sortedWeights[i];
var upperWeight = sortedWeights[i+1];

// Linear interpolation for more precise percentile if needed,
// but for simplicity, we'll find the closest range.
// For this simplified model, we'll just assign the lower percentile range if within.
if (weight === lowerWeight) {
calculatedPercentile = lowerPerc;
} else if (weight === upperWeight) {
calculatedPercentile = upperPerc;
} else {
// Crude interpolation or just assign range label
calculatedPercentile = lowerPerc + "-" + upperPerc;
}
break;
}
}
if (weight === sortedWeights[0]) calculatedPercentile = sortedPercentiles[0];
if (weight === sortedWeights[sortedWeights.length – 1]) calculatedPercentile = sortedPercentiles[sortedPercentiles.length – 1];

// Assign interpretations based on calculated percentile
if (typeof calculatedPercentile === 'number') {
if (calculatedPercentile < 3) interpretation = "Very Low";
else if (calculatedPercentile < 10) interpretation = "Low";
else if (calculatedPercentile < 25) interpretation = "Below Average";
else if (calculatedPercentile <= 50) interpretation = "Average";
else if (calculatedPercentile < 75) interpretation = "Above Average";
else if (calculatedPercentile < 90) interpretation = "High";
else interpretation = "Very High";
} else if (typeof calculatedPercentile === 'string' && calculatedPercentile.includes('-')) {
interpretation = "Mid-Range"; // For ranges like 10-25
}
}
percentile = calculatedPercentile;
} else {
percentile = "N/A";
interpretation = "Data not available for this age.";
}

updateResults(percentile, age, weight, gender.charAt(0).toUpperCase() + gender.slice(1));
updateChart(gender, age, weight);
}

function updateResults(percentile, age, weight, gender) {
var mainResultSpan = document.querySelector("#result .main-result");
mainResultSpan.innerText = percentile + (typeof percentile === 'number' || percentile.includes('-') ? "%" : "");

document.getElementById("resultAge").innerText = age === '–' ? '–' : age;
document.getElementById("resultWeight").innerText = weight === '–' ? '–' : weight.toFixed(1);
document.getElementById("resultGender").innerText = gender === '–' ? '–' : gender;

// Add interpretation to the result area if calculated
var interpretationDiv = document.querySelector("#result .interpretation");
if (!interpretationDiv) {
interpretationDiv = document.createElement('div');
interpretationDiv.className = 'interpretation';
interpretationDiv.style.marginTop = '10px';
interpretationDiv.style.fontSize = '0.9em';
document.getElementById("result").appendChild(interpretationDiv);
}
interpretationDiv.innerText = "Interpretation: " + interpretation;
}

function clearErrorMessages() {
document.getElementById("babyAgeError").innerText = "";
document.getElementById("babyAgeError").style.display = "none";
document.getElementById("babyWeightError").innerText = "";
document.getElementById("babyWeightError").style.display = "none";
}

function resetCalculator() {
document.getElementById("babyAge").value = "";
document.getElementById("babyWeight").value = "";
document.getElementById("babyGender").value = "boy";
clearErrorMessages();
updateResults('–', '–', '–', '–');
if (chartInstance) {
chartInstance.destroy();
chartInstance = null;
}
initializeChart(); // Reinitialize chart with default state
}

function copyResults() {
var mainResult = document.querySelector("#result .main-result").innerText;
var age = document.getElementById("resultAge").innerText;
var weight = document.getElementById("resultWeight").innerText;
var gender = document.getElementById("resultGender").innerText;
var interpretation = document.querySelector("#result .interpretation") ? document.querySelector("#result .interpretation").innerText : "";

var resultText = "Infant Weight Percentile Calculation:\n\n";
resultText += "Primary Result: " + mainResult + "\n";
resultText += "Baby's Age: " + age + " months\n";
resultText += "Baby's Weight: " + weight + " kg\n";
resultText += "Baby's Gender: " + gender + "\n";
resultText += interpretation + "\n\n";
resultText += "Formula: Percentile is determined by comparing your baby's weight for their age and gender against the CDC's reference population data.";

try {
navigator.clipboard.writeText(resultText).then(function() {
// Success feedback (optional)
var copyButton = document.querySelector('button[onclick="copyResults()"]');
var originalText = copyButton.innerText;
copyButton.innerText = "Copied!";
setTimeout(function() {
copyButton.innerText = originalText;
}, 1500);
}, function() {
// Failure feedback (optional)
alert("Failed to copy results. Please copy manually.");
});
} catch (err) {
// Fallback for older browsers or if Clipboard API is not available
var textArea = document.createElement("textarea");
textArea.value = resultText;
textArea.style.position = "fixed"; // Avoid scrolling to bottom
document.body.appendChild(textArea);
textArea.focus();
textArea.select();
try {
var successful = document.execCommand('copy');
var msg = successful ? 'Copied!' : 'Failed to copy!';
console.log('Fallback: ' + msg);
var copyButton = document.querySelector('button[onclick="copyResults()"]');
var originalText = copyButton.innerText;
copyButton.innerText = msg;
setTimeout(function() {
copyButton.innerText = originalText;
}, 1500);
} catch (err) {
console.error('Fallback: Oops, unable to copy', err);
alert("Failed to copy results. Please copy manually.");
}
document.body.removeChild(textArea);
}
}

function updateChart(gender, age, weight) {
if (!chartInstance) {
initializeChart();
}

var dataForGender = cdcWeightData[gender];
var relevantAgeData = null;
var closestAge = null;

var labels = [‘3rd’, ’10th’, ’25th’, ’50th’, ’75th’, ’90th’, ’97th’];
var babyWeights = [];
var avgWeights = [];
var rangeData = []; // For representing the 3rd to 97th percentile range

if (relevantAgeData) {
var sortedPercentiles = Object.keys(relevantAgeData).map(Number).sort(function(a, b) { return a – b; });
var sortedWeights = sortedPercentiles.map(function(p) { return relevantAgeData[p]; });

// Ensure we have all 7 percentile points for consistent chart display
var dataPoints = {
‘3’: relevantAgeData[3] || null,
’10’: relevantAgeData[10] || null,
’25’: relevantAgeData[25] || null,
’50’: relevantAgeData[50] || null,
’75’: relevantAgeData[75] || null,
’90’: relevantAgeData[90] || null,
’97’: relevantAgeData[97] || null
};

var finalLabels = [];
var finalBabyWeights = [];
var finalAvgWeights = [];
var finalRangeData = []; // Store [min, max] for range bars

for (var i = 0; i < labels.length; i++) {
var currentLabel = labels[i];
var correspondingWeight = dataPoints[currentLabel];

if (correspondingWeight !== null && correspondingWeight !== undefined) {
finalLabels.push(currentLabel);
finalAvgWeights.push(correspondingWeight); // 50th percentile is the average line

// Determine baby's weight position relative to this percentile
if (currentLabel === '50') { // Specific check for 50th percentile for baby's weight
finalBabyWeights.push(weight);
} else {
finalBabyWeights.push(null); // Use null where baby's weight isn't directly compared
}

// For range visualization, we need min and max weights for the given age
var minW = dataPoints[3];
var maxW = dataPoints[97];
if (minW !== null && maxW !== null) {
if (currentLabel === '3') {
finalRangeData.push({ min: minW, max: maxW });
} else {
finalRangeData.push(null); // Only add range data at the start of the range segment
}
} else {
finalRangeData.push(null);
}

}
}

chartInstance.data.labels = finalLabels;
chartInstance.data.datasets[0].data = finalBabyWeights; // Baby's weight plotted at 50th percentile comparison point
chartInstance.data.datasets[1].data = finalAvgWeights; // Average (50th percentile) line

// Update the range dataset – requires custom bar chart configuration or potentially a scatter plot
// For simplicity, we'll create a dataset that shows the range width at each point.
// This might not be ideal for all chart types. A better approach could involve drawing lines.
// Let's try to use the 'data' field for range representation.
var rangeValues = [];
var minDataPoint = dataPoints[3];
var maxDataPoint = dataPoints[97];

if (minDataPoint !== null && maxDataPoint !== null) {
for (var i = 0; i < finalLabels.length; i++) {
if (finalLabels[i] === '3') { // Mark the start of the range
rangeValues.push({ l: minDataPoint, h: maxDataPoint });
} else {
rangeValues.push(null); // No bar needed for other points if drawing a continuous range
}
}
chartInstance.data.datasets[2].data = rangeValues;
chartInstance.data.datasets[2].type = 'bar'; // Ensure it's treated as bars
chartInstance.data.datasets[2].backgroundColor = 'rgba(255, 193, 7, 0.5)';
chartInstance.data.datasets[2].borderColor = 'rgba(255, 193, 7, 0.8)';
chartInstance.data.datasets[2].borderWidth = 0;
chartInstance.options.plugins.tooltip.callbacks.label = function(context) {
var label = context.dataset.label || '';
if (label) { label += ': '; }
var value = context.parsed.y;
if (value !== null) {
// Handle range display if it's the range dataset
if (context.dataset.label === 'Guideline Range (3rd-97th)') {
// Find the corresponding min/max values from the data structure
var rangeIndex = context.dataIndex;
var minVal = dataPoints['3'];
var maxVal = dataPoints['97'];
if (minVal !== null && maxVal !== null) {
return context.dataset.label + ': ' + minVal.toFixed(1) + ' kg – ' + maxVal.toFixed(1) + ' kg';
}
} else {
label += value.toFixed(1) + ' kg';
}
}
return label;
};
} else {
chartInstance.data.datasets[2].data = []; // Clear range data if insufficient
}

} else {
chartInstance.data.labels = [];
chartInstance.data.datasets[0].data = [];
chartInstance.data.datasets[1].data = [];
chartInstance.data.datasets[2].data = [];
}

// Adjust baby's weight dataset to show the actual weight, and plot it at the 50th percentile x-axis point for visual reference.
var babyWeightValue = isNaN(weight) ? null : weight;
var comparisonPointIndex = finalLabels.indexOf('50');
var adjustedBabyWeights = new Array(finalLabels.length).fill(null);
if (comparisonPointIndex !== -1 && babyWeightValue !== null) {
adjustedBabyWeights[comparisonPointIndex] = babyWeightValue;
}
chartInstance.data.datasets[0].data = adjustedBabyWeights;

chartInstance.update();
}

// Function to initialize the chart on load
function initChart() {
initializeChart();
// Set some default data or leave it empty until calculation
updateChart('boy', 0, 0); // Initial call to set up structure
}

// Helper function for FAQ toggling
function toggleFaq(element) {
var answer = element.nextElementSibling;
element.classList.toggle('active');
if (answer.style.display === "block") {
answer.style.display = "none";
} else {
answer.style.display = "block";
}
}

// Initial calculation on page load if default values are set
document.addEventListener('DOMContentLoaded', function() {
initChart(); // Initialize the chart first
calculatePercentile(); // Perform an initial calculation if inputs have defaults
});

Infant Weight Percentile Calculator Cdc