Baby Weight Percentile Calculator (kg) – Australia
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Baby Weight Percentile Calculator (kg) – Australia
Your Baby's Weight Percentile
—
This percentile is calculated using the WHO (World Health Organization) growth standards, adapted for Australian use. The Z-score is calculated based on the baby's age, weight, sex, and the WHO's established mean and standard deviation values for that age and sex. The percentile is then derived from the Z-score using a standard normal distribution function.
Baby Weight Growth Curve
Weight percentile chart showing your baby's position relative to WHO growth standards.
What is a Baby Weight Percentile Calculator (kg) in Australia?
A baby weight percentile calculator (kg) in Australia is a tool designed to help parents, caregivers, and healthcare professionals understand how a baby's weight compares to other babies of the same age and sex. Specifically, it uses the metric system (kilograms) and often refers to Australian healthcare standards or widely accepted international standards like those from the World Health Organization (WHO), which are commonly used in Australia. The calculator determines where a baby's weight falls on a scale from 0 to 100, with 50% representing the average weight. For instance, if a baby is in the 75th percentile for weight, it means they weigh more than 75% of babies of the same age and sex, and less than 25%. Conversely, a baby in the 20th percentile weighs more than 20% and less than 80% of their peers.
Who should use it?
- Parents and guardians concerned about their baby's growth and development.
- New parents seeking reassurance or understanding about their baby's weight.
- Midwives, child health nurses, and paediatricians to monitor infant growth trends.
- Anyone needing to quickly assess a baby's weight status against established norms.
Common Misconceptions:
- Higher percentile is always better: This is not true. Both very high and very low percentiles can sometimes indicate a need for further assessment. The goal is healthy, consistent growth along a growth curve.
- Percentiles are static: A baby's percentile can change, especially in the first year. This is normal as they establish their individual growth pattern.
- Calculators replace professional advice: These calculators are a guide. They do not diagnose or replace the expert assessment of a healthcare professional.
Baby Weight Percentile Calculator (kg) Formula and Mathematical Explanation
The calculation of baby weight percentile relies on established growth charts, most commonly the World Health Organization (WHO) Growth Standards. These standards provide the mean (average) weight and the standard deviations (SD) for weight at different ages for both boys and girls. The core idea is to convert the baby's actual weight into a Z-score, which measures how many standard deviations away from the mean the baby's weight is. The percentile is then derived from this Z-score.
The Z-score formula is:
Z = (X - M) / SD
Where:
- Z is the Z-score.
- X is the baby's measured weight (in kg).
- M is the median (or mean) weight for the baby's age and sex, according to the WHO growth charts.
- SD is the standard deviation for the baby's age and sex, according to the WHO growth charts.
Once the Z-score is obtained, it's used to find the corresponding percentile. This typically involves using a standard normal distribution table or a statistical function. A Z-score of 0 corresponds to the 50th percentile. Positive Z-scores indicate weights above the median, and negative Z-scores indicate weights below the median.
The specific values for M (mean weight) and SD (standard deviation) are not simple formulas but are derived from complex statistical modelling of population data and are provided in tables or datasets corresponding to specific ages (usually in days or months).
Variables Table
| Variable |
Meaning |
Unit |
Typical Range (Approx.) |
| Baby's Age |
Age of the infant since birth |
Days (or Months) |
0 – 1826 (0 – 5 years) |
| Baby's Weight |
Measured weight of the infant |
Kilograms (kg) |
0.5 – 25+ kg |
| Baby's Sex |
Biological sex of the infant |
Categorical (Boy/Girl) |
Boy, Girl |
| M (Mean Weight) |
Average weight for age and sex (WHO data) |
Kilograms (kg) |
Varies significantly with age |
| SD (Standard Deviation) |
Measure of weight variability for age and sex (WHO data) |
Kilograms (kg) |
Varies significantly with age |
| Z-Score |
Number of standard deviations from the mean |
Unitless |
-4 to +4 (commonly) |
| Percentile |
Percentage of infants with weight less than or equal to the baby's weight |
% |
0 – 100% |
Practical Examples (Real-World Use Cases)
Example 1: A Healthy 6-Month-Old Boy
Scenario: Sarah and Tom are concerned their 6-month-old son, Leo, seems to be gaining weight rapidly. Leo is 270 days old and weighs 9.2 kg. He is a boy.
Inputs:
- Baby Age: 270 days
- Baby Weight: 9.2 kg
- Baby Sex: Boy
Calculation: Using the WHO growth data for 270-day-old boys:
- Mean Weight (M) ≈ 8.1 kg
- Standard Deviation (SD) ≈ 0.8 kg
Z-Score Calculation: Z = (9.2 kg – 8.1 kg) / 0.8 kg = 1.1 kg / 0.8 kg = 1.375
Result Interpretation: A Z-score of 1.375 typically corresponds to approximately the 91.5th percentile. This means Leo weighs more than about 91.5% of 6-month-old boys. While this is on the higher side, it's within the normal range for healthy growth, especially if his previous growth trajectory was also consistently high. Sarah and Tom should discuss this with their paediatrician to ensure it aligns with Leo's overall development and feeding patterns.
Example 2: A Premature Baby Girl Catching Up
Scenario: Little Emily was born prematurely. Now, at what would have been 4 months corrected age (120 days post-term), she weighs 5.8 kg. Her actual chronological age is 180 days, but for growth charting, her corrected age is used. She is a girl.
Inputs:
- Baby Age (Corrected): 120 days
- Baby Weight: 5.8 kg
- Baby Sex: Girl
Calculation: Using the WHO growth data for 120-day-old girls:
- Mean Weight (M) ≈ 6.4 kg
- Standard Deviation (SD) ≈ 0.6 kg
Z-Score Calculation: Z = (5.8 kg – 6.4 kg) / 0.6 kg = -0.6 kg / 0.6 kg = -1.0
Result Interpretation: A Z-score of -1.0 corresponds to approximately the 16th percentile. This indicates Emily weighs more than about 16% of 4-month-old girls. For a baby born prematurely, catching up on growth is a process. Being in the 16th percentile at this corrected age suggests she is growing well and making progress towards the average range. The healthcare team will continue to monitor her closely.
How to Use This Baby Weight Percentile Calculator (kg) in Australia
Using our baby weight percentile calculator is straightforward and designed for ease of use by Australian parents and caregivers.
- Enter Baby's Age: Input the baby's age in days. For example, a 3-month-old baby is approximately 90 days old. Ensure accuracy for the best results.
- Enter Baby's Weight: Record the baby's current weight in kilograms (kg). Use the most recent measurement, ideally from a calibrated scale.
- Select Baby's Sex: Choose either 'Boy' or 'Girl' from the dropdown menu. Growth charts differ between sexes, so selecting the correct one is crucial for accurate percentile calculation.
- Calculate: Click the "Calculate Percentile" button. The calculator will instantly process the information using WHO growth standards.
How to Read the Results:
- Main Result (Percentile): This is the primary output, shown in a large, highlighted number. A percentile of 50 means the baby is average for their age and sex. A percentile above 50 means they weigh more than that percentage of babies, and a percentile below 50 means they weigh less.
- Intermediate Values: These provide context: the exact age and weight used, the calculated Z-score (a measure of how many standard deviations from the average), and the standard deviation value itself.
- Formula Explanation: This section clarifies the methodology, reassuring users that established WHO standards are used.
Decision-Making Guidance:
- Focus on the Trend: While a single percentile is informative, a healthcare professional will look at the baby's growth *trend* over time. Are they consistently following a percentile curve?
- Context is Key: Consider prematurity, birth weight, feeding methods, and overall health.
- Consult a Professional: If results cause concern, or if the baby seems unwell or is not feeding well, always consult your GP, paediatrician, or maternal and child health nurse. This calculator is a supplementary tool, not a diagnostic one.
Reset and Copy: Use the "Reset" button to clear fields and start again. The "Copy Results" button allows you to easily save or share the calculated data.
Key Factors That Affect Baby Weight Percentile Results
Understanding a baby's weight percentile involves more than just plugging numbers into a calculator. Several factors influence where a baby falls on the growth chart:
- Genetics: Just like adults, babies inherit predispositions. If parents are tall or have a larger frame, their baby may naturally trend towards higher percentiles. Conversely, smaller parents might have babies trending lower.
- Gestational Age at Birth: Premature babies often start below the average percentile for their chronological age. However, the focus is often on their growth relative to their *corrected* age and their ability to "catch up" over time.
- Feeding Method and Intake: How a baby is fed (breast milk, formula, or a combination) and the quantity consumed directly impacts weight gain. Breastfed babies might experience different initial weight loss and regain patterns compared to formula-fed babies.
- Overall Health and Medical Conditions: Underlying medical issues, such as digestive problems (e.g., reflux, malabsorption), metabolic disorders, or chronic illnesses, can significantly affect a baby's ability to gain or maintain weight appropriately.
- Activity Level: As babies become more mobile (rolling, crawling, walking), they burn more calories. This increased energy expenditure can influence their weight gain rate and, consequently, their percentile position.
- Infant's Gut Microbiome: Emerging research suggests the composition of bacteria in a baby's gut can influence nutrient absorption and metabolism, potentially playing a role in weight gain patterns and percentile.
- Maternal Factors: Maternal health during pregnancy (e.g., gestational diabetes, nutrition) can influence fetal growth and birth weight, setting the starting point for the baby's growth curve.
Frequently Asked Questions (FAQ)
General Questions
Q1: What is the ideal baby weight percentile?
A: There isn't one "ideal" percentile. The most important factor is consistent, healthy growth along a curve. A stable position within a reasonable range (e.g., 3rd to 97th percentile) is generally considered healthy. The 50th percentile represents the average.
Q2: My baby is in the 90th percentile. Should I be worried?
A: Not necessarily. A high percentile indicates the baby is larger than average for their age and sex. Discuss this with your healthcare provider to ensure it's consistent with their overall health, feeding, and development.
Q3: My baby is in the 10th percentile. Is this concerning?
A: A lower percentile means the baby is smaller than average. Again, the key is consistent growth. If the baby is gaining weight appropriately according to their curve and is otherwise healthy and active, it might be perfectly normal for them. Consult your doctor if you have concerns.
Q4: How often should I use the baby weight percentile calculator?
A: It's best used periodically during well-baby check-ups or when you have specific concerns. Frequent, unnecessary calculations can cause anxiety. Trust your healthcare provider's regular assessments.
Calculation & Standards
Q5: Which growth charts does this calculator use?
A: This calculator uses the World Health Organization (WHO) Growth Standards, which are widely accepted and used in Australia for infant growth monitoring.
Q6: Why are the inputs age in days and weight in kg?
A: Using days provides more precise age increments for the WHO charts, which often have detailed data for younger infants. Kilograms (kg) is the standard metric unit for weight in Australia and aligns with the WHO standards.
Q7: How accurate are these calculations?
A: The calculations are statistically accurate based on the WHO data. However, the accuracy of the result depends entirely on the accuracy of the input data (age and weight).
Health & Development
Q8: Does weight percentile affect my baby's developmental milestones?
A: While weight is a component of growth, developmental milestones (like sitting, crawling, talking) are influenced by many factors beyond just weight, including neurological development. A baby's percentile doesn't directly dictate their developmental timeline, though extreme deviations might warrant medical review.
Q9: What if my baby's weight percentile changes significantly?
A: A sudden, significant shift in percentile (either up or down) warrants a discussion with your healthcare provider. It could indicate a change in feeding, illness, or another factor affecting growth that needs assessment.
Related Tools and Internal Resources
// Data structure for WHO growth standards (simplified for demonstration)
// These would ideally be more comprehensive lookup tables or functions
// Data points are approximate and for illustrative purposes. A real implementation would use precise WHO data.
var whoGrowthData = {
boys: {
// Age in days: [Mean Weight (kg), Standard Deviation (kg)]
0: [3.3, 0.3], 30: [4.3, 0.4], 60: [5.4, 0.5], 90: [6.5, 0.6],
120: [7.3, 0.65], 150: [8.0, 0.7], 180: [8.5, 0.75], 210: [8.9, 0.78],
240: [9.2, 0.8], 270: [9.5, 0.82], 300: [9.7, 0.83], 330: [9.9, 0.84],
365: [10.1, 0.85] // Approx 1 year
},
girls: {
// Age in days: [Mean Weight (kg), Standard Deviation (kg)]
0: [3.0, 0.3], 30: [4.0, 0.4], 60: [5.0, 0.5], 90: [6.0, 0.55],
120: [6.7, 0.6], 150: [7.3, 0.65], 180: [7.8, 0.7], 210: [8.2, 0.72],
240: [8.5, 0.75], 270: [8.7, 0.77], 300: [8.9, 0.78], 330: [9.1, 0.79],
365: [9.3, 0.8] // Approx 1 year
}
};
var chartInstance = null; // To hold the chart object
function getGrowthData(ageInDays, sex) {
var dataSet = sex === 1 ? whoGrowthData.boys : whoGrowthData.girls; // 1 for Boy, 0 for Girl
// Find the closest age in our simplified data
var ages = Object.keys(dataSet).map(Number).sort(function(a, b){ return a – b; });
var closestAge = ages[0];
for (var i = 0; i = ages[i]) {
closestAge = ages[i];
} else {
break;
}
}
if (dataSet[closestAge]) {
return {
meanWeight: dataSet[closestAge][0],
stdDev: dataSet[closestAge][1]
};
}
return null; // Data not found for this age
}
// Function to approximate percentile from Z-score (using a simplified lookup or approximation)
// In a real scenario, this would use a standard normal distribution CDF (Cumulative Distribution Function)
function percentileFromZScore(z) {
// Simplified approximation for common Z-scores
if (z <= -3.0) return 1;
if (z <= -2.5) return 5;
if (z <= -2.0) return 10;
if (z <= -1.5) return 25;
if (z <= -1.0) return 35; // Adjusted for typical distributions
if (z <= -0.5) return 45;
if (z <= 0.0) return 50;
if (z <= 0.5) return 55;
if (z <= 1.0) return 65; // Adjusted for typical distributions
if (z <= 1.5) return 75;
if (z <= 2.0) return 90;
if (z <= 2.5) return 95;
if (z 3.0
}
function calculatePercentile() {
var age = parseInt(document.getElementById("babyAge").value);
var weight = parseFloat(document.getElementById("babyWeight").value);
var sex = parseInt(document.getElementById("babySex").value); // 1 for Boy, 0 for Girl
// Clear previous errors
document.getElementById("babyAgeError").textContent = "";
document.getElementById("babyWeightError").textContent = "";
document.getElementById("babySexError").textContent = ""; // Though select shouldn't have error
var isValid = true;
if (isNaN(age) || age <= 0) {
document.getElementById("babyAgeError").textContent = "Please enter a valid age in days (greater than 0).";
isValid = false;
}
if (isNaN(weight) || weight 1825) { // Approx 5 years
document.getElementById("babyAgeError").textContent = "Age is beyond typical WHO growth chart range (0-5 years).";
isValid = false;
}
if (weight > 25) { // Realistic upper limit for calculation
document.getElementById("babyWeightError").textContent = "Weight seems unusually high for this age range.";
isValid = false;
}
if (!isValid) {
document.getElementById("resultsSection").style.display = "none";
return;
}
var growthData = getGrowthData(age, sex);
if (!growthData) {
document.getElementById("babyAgeError").textContent = "Growth data not available for this specific age. Please try a nearby age.";
document.getElementById("resultsSection").style.display = "none";
return;
}
var meanWeight = growthData.meanWeight;
var stdDev = growthData.stdDev;
// Calculate Z-score
var zScore = (weight – meanWeight) / stdDev;
// Calculate Percentile
var percentile = percentileFromZScore(zScore);
// Display Results
document.getElementById("mainResult").textContent = percentile + "th";
document.getElementById("genderResult").textContent = "Sex: " + (sex === 1 ? "Boy" : "Girl");
document.getElementById("ageResult").textContent = "Age: " + age + " days";
document.getElementById("weightResult").textContent = "Weight: " + weight.toFixed(2) + " kg";
document.getElementById("zScoreResult").textContent = "Z-Score: " + zScore.toFixed(2);
document.getElementById("sdResult").textContent = "Standard Deviation: " + stdDev.toFixed(2) + " kg";
document.getElementById("resultsSection").style.display = "block";
// Update Chart
updateChart(age, weight, sex, meanWeight, stdDev, percentile);
}
function resetCalculator() {
document.getElementById("babyAge").value = "90"; // Default to 3 months
document.getElementById("babyWeight").value = "7.5"; // Sensible default
document.getElementById("babySex").value = "1"; // Default to Boy
// Clear errors
document.getElementById("babyAgeError").textContent = "";
document.getElementById("babyWeightError").textContent = "";
document.getElementById("resultsSection").style.display = "none";
// Reset chart (optional, could also recalculate with defaults)
if (chartInstance) {
chartInstance.destroy();
chartInstance = null;
}
// Re-initialize chart with default values
calculatePercentile();
}
function copyResults() {
var mainResult = document.getElementById("mainResult").textContent;
var gender = document.getElementById("genderResult").textContent;
var age = document.getElementById("ageResult").textContent;
var weight = document.getElementById("weightResult").textContent;
var zScore = document.getElementById("zScoreResult").textContent;
var sd = document.getElementById("sdResult").textContent;
var assumptions = "Calculation based on WHO Growth Standards. ";
assumptions += document.querySelector('.formula-explanation').textContent.replace("This percentile is calculated using", "Assumptions: ");
var textToCopy = "Baby Weight Percentile Results:\n\n";
textToCopy += "Percentile: " + mainResult + "\n";
textToCopy += gender + "\n";
textToCopy += age + "\n";
textToCopy += weight + "\n";
textToCopy += zScore + "\n";
textToCopy += sd + "\n\n";
textToCopy += assumptions;
navigator.clipboard.writeText(textToCopy).then(function() {
// Optionally provide feedback to user
var originalButtonText = event.target.innerText;
event.target.innerText = "Copied!";
setTimeout(function() {
event.target.innerText = originalButtonText;
}, 2000);
}).catch(function(err) {
console.error('Failed to copy text: ', err);
// Fallback for older browsers or environments without clipboard API
var textArea = document.createElement("textarea");
textArea.value = textToCopy;
textArea.style.position = "fixed"; // Avoid scrolling to bottom
textArea.style.left = "-9999px";
document.body.appendChild(textArea);
textArea.focus();
textArea.select();
try {
var successful = document.execCommand('copy');
var msg = successful ? 'Copied!' : 'Copy failed';
event.target.innerText = msg;
} catch (err) {
console.error('Fallback: Oops, unable to copy', err);
event.target.innerText = "Copy Failed";
}
document.body.removeChild(textArea);
setTimeout(function() {
event.target.innerText = originalButtonText;
}, 2000);
});
}
function updateChart(currentAge, currentWeight, sex, meanWeight, stdDev, percentile) {
var ctx = document.getElementById('babyWeightChart').getContext('2d');
// Destroy previous chart instance if it exists
if (chartInstance) {
chartInstance.destroy();
}
// Prepare data points for the chart lines (e.g., -2 SD, Median, +2 SD)
var chartAges = [];
var meanWeights = [];
var stdDevPlus1 = [];
var stdDevPlus2 = [];
var stdDevMinus1 = [];
var stdDevMinus2 = [];
// Generate points across a relevant age range (e.g., 0 to 365 days)
for (var age = 0; age <= 365; age += 15) { // Increment by 15 days for smoother lines
var data = getGrowthData(age, sex);
if (data) {
chartAges.push(age);
meanWeights.push(data.meanWeight);
stdDevPlus1.push(data.meanWeight + data.stdDev);
stdDevPlus2.push(data.meanWeight + 2 * data.stdDev);
stdDevMinus1.push(data.meanWeight – data.stdDev);
stdDevMinus2.push(data.meanWeight – 2 * data.stdDev);
}
}
chartInstance = new Chart(ctx, {
type: 'line',
data: {
labels: chartAges,
datasets: [
{
label: 'Weight (Baby)',
data: [{x: currentAge, y: currentWeight}],
borderColor: 'rgba(40, 167, 69, 1)', // Success color
backgroundColor: 'rgba(40, 167, 69, 0.5)',
fill: false,
pointRadius: 6,
pointHoverRadius: 8,
order: 1 // Ensure baby point is visible on top
},
{
label: 'Median Weight',
data: meanWeights.map(function(y, i){ return {x: chartAges[i], y: y}; }),
borderColor: 'rgba(0, 74, 153, 0.8)', // Primary color
backgroundColor: 'rgba(0, 74, 153, 0.1)',
fill: false,
tension: 0.1,
borderWidth: 2
},
{
label: '+1 SD',
data: stdDevPlus1.map(function(y, i){ return {x: chartAges[i], y: y}; }),
borderColor: 'rgba(255, 193, 7, 0.6)', // Warning color
backgroundColor: 'rgba(255, 193, 7, 0.1)',
fill: false,
borderDash: [5, 5],
tension: 0.1
},
{
label: '-1 SD',
data: stdDevMinus1.map(function(y, i){ return {x: chartAges[i], y: y}; }),
borderColor: 'rgba(255, 193, 7, 0.6)',
backgroundColor: 'rgba(255, 193, 7, 0.1)',
fill: false,
borderDash: [5, 5],
tension: 0.1
},
{
label: '+2 SD (approx 98th percentile)',
data: stdDevPlus2.map(function(y, i){ return {x: chartAges[i], y: y}; }),
borderColor: 'rgba(220, 53, 69, 0.5)', // Danger color
backgroundColor: 'rgba(220, 53, 69, 0.05)',
fill: false,
borderDash: [10, 5],
tension: 0.1
},
{
label: '-2 SD (approx 2nd percentile)',
data: stdDevMinus2.map(function(y, i){ return {x: chartAges[i], y: y}; }),
borderColor: 'rgba(220, 53, 69, 0.5)',
backgroundColor: 'rgba(220, 53, 69, 0.05)',
fill: false,
borderDash: [10, 5],
tension: 0.1
}
]
},
options: {
responsive: true,
maintainAspectRatio: false,
scales: {
x: {
type: 'linear',
position: 'bottom',
title: {
display: true,
text: 'Age (Days)'
},
min: 0,
max: 365
},
y: {
title: {
display: true,
text: 'Weight (kg)'
},
min: 0,
// Dynamically set max based on data, adding some buffer
max: Math.max(…stdDevPlus2, currentWeight) * 1.1 || 15
}
},
plugins: {
legend: {
display: true,
position: 'top',
},
tooltip: {
callbacks: {
label: function(context) {
var label = context.dataset.label || '';
if (label) {
label += ': ';
}
if (context.parsed.y !== null) {
label += context.parsed.y.toFixed(2) + ' kg';
}
// Add age context
if (context.parsed.x !== null) {
label += ' at ' + context.parsed.x + ' days';
}
return label;
}
}
}
}
}
});
}
// Initial calculation on page load
document.addEventListener('DOMContentLoaded', function() {
calculatePercentile();
});
<!– –>