Child Weight Percentile Calculator Canada

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Child Weight Percentile Calculator Canada

Understand your child's growth trajectory based on Canadian standards.

Child Weight Percentile Calculator

Enter age in full months (e.g., 18 for 1.5 years).
Enter weight in kilograms (e.g., 10.5).
Male Female Select the child's sex.

Weight-for-Age Percentile Chart (WHO Standards)

This chart visualizes WHO growth curves, showing the 3rd, 50th (median), and 97th percentiles for the selected sex. Your child's specific data point is plotted for comparison.

WHO Growth Standards Reference Data (Example Ranges)

Example Weight-for-Age Percentiles (kg)
Age (Months) Sex 3rd Percentile 50th Percentile 97th Percentile

What is a Child Weight Percentile Calculator Canada?

A Child Weight Percentile Calculator for Canada is a specialized tool designed to help parents, caregivers, and healthcare professionals in Canada assess a child's weight relative to the expected growth patterns for children of the same age and sex. In Canada, as internationally, the World Health Organization (WHO) growth standards are widely used for infants and young children up to age 5. This calculator takes your child's age and weight, along with their sex, and compares it against these established WHO growth curves. The output is a percentile number, indicating where your child's weight falls within the distribution of healthy children. For instance, a child at the 75th percentile for weight means that 75% of children of the same age and sex weigh less than them, and 25% weigh more. Understanding these percentiles is crucial for monitoring healthy child development and identifying potential growth concerns early. This child weight percentile calculator Canada focuses specifically on weight-for-age, a key indicator of nutritional status and growth progress.

Who Should Use It?

  • Parents and Guardians: To proactively monitor their child's growth and discuss any concerns with healthcare providers.
  • Pediatricians and Family Doctors: To quickly reference growth data during well-child check-ups.
  • Nurses and Dietitians: To assess nutritional status and provide tailored advice.
  • Childcare Providers: To gain a general understanding of age-appropriate growth.

Common Misconceptions

  • Myth: A low percentile is always bad. Reality: A consistently low percentile can be normal if the child is growing along their own curve and is healthy and active. Sudden drops or rapid rises are more concerning than a stable position.
  • Myth: The 50th percentile is the "ideal" weight. Reality: All percentiles between the 3rd and 97th are considered within the normal range for healthy growth. The goal is consistent growth along a curve, not necessarily hitting a specific number.
  • Myth: Percentiles are just for overweight or underweight concerns. Reality: Percentiles track overall growth patterns, including appropriate weight gain for growing bodies.
  • Myth: Canadian data is different from WHO data. Reality: Canada adopts WHO growth standards for young children, ensuring consistency in assessment.

Child Weight Percentile Calculator Canada Formula and Mathematical Explanation

The core of the Child Weight Percentile Calculator Canada relies on statistical interpolation and lookup against established WHO growth standards. While the exact calculation of a precise percentile value often involves complex statistical formulas and specialized software that utilizes smoothed data curves, the calculator approximates this by:

1. Identifying the child's specific age (in months) and sex.

2. Retrieving reference data points (weights corresponding to specific percentiles) for that exact age and sex from the WHO growth standards database.

3. Interpolating between known data points if the child's exact age isn't listed in the reference table.

4. Determining where the child's measured weight falls relative to these reference weights. A common simplified approach involves finding the z-score, which measures how many standard deviations a child's weight is from the mean (50th percentile), and then converting the z-score to a percentile rank.

Variable Explanations

The inputs required for this child weight percentile calculator Canada are straightforward:

Variables for Weight Percentile Calculation
Variable Meaning Unit Typical Range
Age The child's age in months. Crucial for comparing against age-specific growth curves. Months 0 – 60 months (up to 5 years)
Weight The child's measured weight. Kilograms (kg) 0.5 – 30 kg (approximate for the age range)
Sex Biological sex of the child, as growth patterns differ between males and females. Categorical (Male/Female) Male, Female

The primary output is the **Weight-for-Age Percentile**, representing the percentage of children of the same age and sex whose weight is below the child's measured weight. Intermediate values often include the nearest reference weights (e.g., 3rd, 50th, 97th percentile weights) for the child's age and sex, providing context.

Practical Examples (Real-World Use Cases)

Example 1: Monitoring a Growing Toddler

Scenario: Sarah is a 24-month-old (2 years) girl in Vancouver. Her parents weigh her at home, and the scale reads 12.5 kg. They want to see how she's doing.

Inputs:

  • Age: 24 months
  • Weight: 12.5 kg
  • Sex: Female

Calculator Output:

  • Main Result: Approximately 65th Percentile
  • Intermediate Values: Age: 24 months, Weight: 12.5 kg, Sex: Female
  • Formula Explanation: Based on WHO standards, 12.5 kg at 24 months for a female places the child above the median (50th percentile) but below the 97th percentile, indicating healthy growth within the expected range.

Interpretation: Sarah's weight is higher than approximately 65% of girls her age. This percentile is well within the healthy growth range (typically considered between the 3rd and 97th percentile). Her parents can feel reassured that she is growing appropriately, provided she is meeting developmental milestones and is generally healthy.

Example 2: Checking an Infant's Weight Gain

Scenario: Little Leo is 6 months old and weighs 7.8 kg. His parents are concerned about whether he's gaining enough weight. They use the calculator.

Inputs:

  • Age: 6 months
  • Weight: 7.8 kg
  • Sex: Male

Calculator Output:

  • Main Result: Approximately 40th Percentile
  • Intermediate Values: Age: 6 months, Weight: 7.8 kg, Sex: Male
  • Formula Explanation: Using WHO growth data, 7.8 kg for a 6-month-old male falls below the 50th percentile but significantly above the 3rd percentile, indicating consistent growth.

Interpretation: Leo's weight is around the 40th percentile for his age and sex. This means he is growing steadily and is within the healthy range. The key takeaway is his consistent progression along his growth curve, rather than the specific percentile number. If Leo were showing a significant drop in percentile or failing to gain weight, a consultation with a pediatrician would be recommended.

How to Use This Child Weight Percentile Calculator Canada

Using this Child Weight Percentile Calculator Canada is simple and intuitive. Follow these steps to get a clear picture of your child's growth:

Step-by-Step Instructions

  1. Measure Accurately: Ensure you have a recent and accurate measurement of your child's weight in kilograms (kg). If you only have pounds, use a reliable online converter. For age, count the child's age in full months.
  2. Enter Child's Age: Input the child's age in months into the "Child's Age (Months)" field.
  3. Enter Child's Weight: Input the child's weight in kilograms (kg) into the "Child's Weight (kg)" field.
  4. Select Child's Sex: Choose "Male" or "Female" from the dropdown menu for the "Child's Sex" field.
  5. Calculate: Click the "Calculate Percentile" button.
  6. View Results: The calculator will display the primary result (the weight percentile), along with key intermediate values and a brief explanation.
  7. Interpret the Chart and Table: Examine the generated chart and table. The chart visually places your child's data point against the WHO growth curves (3rd, 50th, 97th percentiles). The table provides reference weights for specific percentiles at different ages, offering further context.
  8. Reset (Optional): If you wish to calculate for another child or re-enter details, click the "Reset" button to clear the fields and start again.
  9. Copy Results (Optional): To save or share the calculated information, click "Copy Results". This will copy the main percentile, intermediate values, and key assumptions to your clipboard.

How to Read Results

  • Main Result (Percentile): A number between 0 and 100. A higher number means the child weighs more relative to other children of the same age and sex. For example, the 50th percentile means the child is at the midpoint. The 3rd percentile is the lower boundary of the typical range, and the 97th percentile is the upper boundary.
  • Intermediate Values: These confirm the inputs used for the calculation (Age, Weight, Sex).
  • Chart: Observe where your child's dot falls. Is it on or near a curve? Is it between curves? Is it above the 97th or below the 3rd?
  • Table: Use this to see what the actual weight would be at different percentiles for a specific age.

Decision-Making Guidance

  • Stable Growth: The most important factor is consistent growth along a particular percentile curve over time. A child consistently around the 25th percentile is growing normally if they stay there.
  • Sudden Changes: A sharp drop or rise in percentile warrants attention. This could indicate illness, changes in nutrition, or other health issues.
  • Outside the Range: Percentiles below the 3rd or above the 97th should be discussed with a healthcare professional. This doesn't automatically mean there's a problem, but it requires medical evaluation to rule out underlying conditions.
  • Consult Professionals: Always discuss your child's growth chart and any concerns with your pediatrician or healthcare provider. This calculator is a tool for information and discussion, not a substitute for professional medical advice.

Key Factors That Affect Child Weight Percentile Results

While the Child Weight Percentile Calculator Canada provides a clear number based on age and weight, several underlying factors influence a child's growth trajectory and, consequently, their percentile results. Understanding these can provide a more holistic view of your child's health:

  1. Genetics: Just like adults, children inherit genetic predispositions that influence their body frame, metabolism, and potential growth patterns. Some children are naturally leaner, while others are naturally more robust. This is a fundamental factor.
  2. Nutrition and Feeding Habits: This is perhaps the most significant modifiable factor. The quantity and quality of breast milk, formula, or solid foods directly impact weight gain. Adequate intake of calories, protein, fats, vitamins, and minerals is essential for healthy growth. Conversely, inadequate intake or feeding difficulties can lead to slower weight gain.
  3. Activity Level and Metabolism: A highly active child burns more calories, which can affect their weight gain rate. Similarly, individual metabolic rates vary. Some children naturally have a faster metabolism, requiring more energy intake to gain weight.
  4. Health Status and Illness: Acute illnesses (like stomach bugs) can cause temporary weight loss or slowed gain. Chronic conditions, such as digestive disorders, hormonal imbalances, or chronic infections, can persistently affect a child's ability to gain weight appropriately.
  5. Sleep Patterns: Sufficient and quality sleep is crucial for overall health and growth, as many growth hormones are released during sleep. Disruptions in sleep can indirectly impact growth.
  6. Socioeconomic Factors and Access to Healthcare: Factors like access to nutritious food, parental knowledge about nutrition, and regular access to healthcare services (for monitoring and early intervention) significantly influence a child's growth trajectory. In Canada, these factors play a role in ensuring children receive the necessary support.
  7. Prenatal and Birth History: A child's growth in utero and birth weight can set an initial trajectory. Premature birth or conditions like intrauterine growth restriction (IUGR) may mean a child starts on a different growth path.
  8. Parental Concerns and Observation: While not a direct biological factor, parental observation is key. A parent's intuition about their child's well-being and growth can prompt important discussions with healthcare providers, leading to timely interventions if needed.

Frequently Asked Questions (FAQ)

What is the difference between weight percentile and BMI percentile?

This calculator focuses specifically on weight-for-age percentile, which is standard for infants and young children (0-5 years) according to WHO guidelines. For older children (age 5 and above), BMI-for-age percentile becomes more relevant as it considers both height and weight, providing a better indication of body composition relative to peers.

Does my child need to be exactly on the 50th percentile?

No, the 50th percentile is simply the median – meaning half the children weigh less, and half weigh more. Any percentile between the 3rd and 97th is generally considered within the normal range for healthy growth, provided the child is growing consistently along their own curve.

When should I be concerned about my child's weight percentile?

Concerns typically arise if a child's growth curve shows significant deviations: a rapid drop to a much lower percentile, a sharp rise to a much higher percentile, or if the child consistently falls below the 3rd percentile or above the 97th percentile. It's always best to discuss growth charts with a pediatrician.

How often should my child's weight be monitored?

Regular monitoring is key. For infants, weight checks are frequent in the first year (often at well-baby visits every 1-3 months). For toddlers and preschoolers, annual check-ups are typical, but more frequent monitoring might be advised by a doctor based on individual circumstances.

Are these calculations specific to Canada?

While this calculator is tailored for use in Canada, the underlying data comes from the World Health Organization (WHO) growth standards, which are internationally recognized and used by Health Canada for children from birth to age 5. So, the data is globally standard for this age group.

Can this calculator predict future weight?

No, this calculator assesses the child's current weight percentile based on their current age and weight. It does not predict future growth, as growth is dynamic and influenced by many changing factors.

What if my child was born prematurely?

For premature infants, growth assessment often uses corrected age and specialized growth charts designed for preemies. This calculator uses chronological age. If your child was born prematurely, it's essential to use the growth charts provided by your healthcare team that account for prematurity.

What is the role of a pediatrician in interpreting percentiles?

A pediatrician integrates the percentile data with the child's overall health, feeding history, developmental milestones, family history, and physical examination. They can differentiate between normal variations in growth and potential health issues requiring intervention.

Related Tools and Internal Resources

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// WHO Growth Data (Simplified approximation for demonstration) // This data is a simplified representation. Real-world calculations often use complex curves or extensive lookup tables. // Units: Weight in kg, Age in months. var whoGrowthData = { male: { // Age in months: [3rd percentile weight, 50th percentile weight, 97th percentile weight] 0: [2.6, 3.6, 4.9], 1: [3.3, 4.5, 6.0], 2: [4.0, 5.2, 6.9], 3: [4.6, 5.8, 7.6], 4: [5.1, 6.3, 8.2, 9.0], 5: [5.5, 6.7, 8.6, 9.5], 6: [5.9, 7.1, 9.0, 10.0], 7: [6.2, 7.4, 9.3, 10.3], 8: [6.5, 7.7, 9.6, 10.6], 9: [6.8, 7.9, 9.8, 10.9], 10: [7.0, 8.1, 10.0, 11.1], 11: [7.2, 8.3, 10.2, 11.3], 12: [7.4, 8.4, 10.3, 11.5], 15: [7.9, 8.9, 10.8, 12.0], 18: [8.4, 9.4, 11.3, 12.6], 24: [9.3, 10.3, 12.2, 13.6], 30: [10.1, 11.2, 13.1, 14.6], 36: [10.9, 12.0, 13.9, 15.6], 48: [12.2, 13.5, 15.4, 17.3], 60: [13.4, 14.8, 16.8, 19.0] }, female: { // Age in months: [3rd percentile weight, 50th percentile weight, 97th percentile weight] 0: [2.4, 3.4, 4.7], 1: [3.1, 4.2, 5.7], 2: [3.7, 4.9, 6.5], 3: [4.2, 5.4, 7.2], 4: [4.7, 5.8, 7.7, 8.6], 5: [5.1, 6.2, 8.1, 9.0], 6: [5.4, 6.5, 8.4, 9.4], 7: [5.7, 6.8, 8.7, 9.6], 8: [5.9, 7.0, 8.9, 9.9], 9: [6.1, 7.2, 9.1, 10.1], 10: [6.3, 7.4, 9.3, 10.3], 11: [6.5, 7.5, 9.4, 10.5], 12: [6.6, 7.6, 9.5, 10.6], 15: [7.1, 8.1, 10.0, 11.2], 18: [7.6, 8.6, 10.5, 11.8], 24: [8.5, 9.5, 11.4, 12.7], 30: [9.2, 10.2, 12.1, 13.5], 36: [9.9, 10.9, 12.8, 14.4], 48: [11.0, 12.2, 13.9, 15.7], 60: [12.0, 13.3, 15.1, 17.0] } }; // Function to get closest age key from data function getClosestAgeKey(ageInMonths, data) { var ages = Object.keys(data).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; } } return closestAge; } // Function to interpolate weight for a given percentile and age function getInterpolatedWeight(ageInMonths, percentile, sex) { var dataForSex = whoGrowthData[sex]; var lowerAge = getClosestAgeKey(ageInMonths, dataForSex); var upperAge = lowerAge; var ages = Object.keys(dataForSex).map(Number).sort(function(a, b) { return a – b; }); for (var i = 0; i lowerAge) { upperAge = ages[i]; break; } } var lowerData = dataForSex[lowerAge]; var upperData = dataForSex[upperAge]; if (!lowerData) return null; // Should not happen with getClosestAgeKey var p3Lower = lowerData[0]; var p50Lower = lowerData[1]; var p97Lower = lowerData[2]; var p3Upper = upperData ? upperData[0] : p3Lower; var p50Upper = upperData ? upperData[1] : p50Lower; var p97Upper = upperData ? upperData[2] : p97Lower; var percentileWeightsLower = [p3Lower, p50Lower, p97Lower]; var percentileWeightsUpper = [p3Upper, p50Upper, p97Upper]; var targetPercentileIndex; if (percentile <= 3) targetPercentileIndex = 0; else if (percentile <= 50) targetPercentileIndex = 1; else targetPercentileIndex = 2; var weightAtLowerAge = percentileWeightsLower[targetPercentileIndex]; var weightAtUpperAge = percentileWeightsUpper[targetPercentileIndex]; if (lowerAge === upperAge) { return weightAtLowerAge; } // Linear interpolation between the two ages var ageRange = upperAge – lowerAge; var ageDiff = ageInMonths – lowerAge; var interpolationFactor = ageDiff / ageRange; var interpolatedWeight = weightAtLowerAge + (weightAtUpperAge – weightAtLowerAge) * interpolationFactor; return interpolatedWeight; } // Simplified percentile calculation (conceptual – precise calculation needs statistical libraries or Z-score tables) // This function approximates by finding the closest match or interpolating between known points. // Real-world accurate percentile calculation is complex and involves statistical methods (like LMS parameters). function calculateApproximatePercentile(ageInMonths, weightKg, sex) { var dataForSex = whoGrowthData[sex]; var ages = Object.keys(dataForSex).map(Number).sort(function(a, b) { return a – b; }); var lowerAge = getClosestAgeKey(ageInMonths, dataForSex); var upperAge = lowerAge; for (var i = 0; i lowerAge) { upperAge = ages[i]; break; } } var lowerData = dataForSex[lowerAge]; var upperData = dataForSex[upperAge]; if (!lowerData) return { percentile: null, p3: null, p50: null, p97: null }; // Error case var p3Lower = lowerData[0]; var p50Lower = lowerData[1]; var p97Lower = lowerData[2]; var p3Upper = upperData ? upperData[0] : p3Lower; var p50Upper = upperData ? upperData[1] : p50Lower; var p97Upper = upperData ? upperData[2] : p97Lower; // Interpolate the reference weights for the exact age var interpolatedP3, interpolatedP50, interpolatedP97; if (lowerAge === upperAge) { interpolatedP3 = p3Lower; interpolatedP50 = p50Lower; interpolatedP97 = p97Lower; } else { var ageRange = upperAge – lowerAge; var ageDiff = ageInMonths – lowerAge; var interpolationFactor = ageDiff / ageRange; interpolatedP3 = p3Lower + (p3Upper – p3Lower) * interpolationFactor; interpolatedP50 = p50Lower + (p50Upper – p50Lower) * interpolationFactor; interpolatedP97 = p97Lower + (p97Upper – p97Lower) * interpolationFactor; } // Determine percentile rank based on interpolated weights var percentile; if (weightKg < interpolatedP3) { // Simplified linear approximation for percentiles below 3rd percentile = (weightKg / interpolatedP3) * 3; } else if (weightKg < interpolatedP50) { // Between 3rd and 50th percentile = 3 + ((weightKg – interpolatedP3) / (interpolatedP50 – interpolatedP3)) * 47; } else if (weightKg < interpolatedP97) { // Between 50th and 97th percentile = 50 + ((weightKg – interpolatedP50) / (interpolatedP97 – interpolatedP50)) * 47; } else { // Above 97th percentile = 97 + ((weightKg – interpolatedP97) / (interpolatedP97 * 1.1)) * 3; // Rough extrapolation } // Ensure percentile is within reasonable bounds and rounded percentile = Math.max(0, Math.min(100, percentile)); return { percentile: parseFloat(percentile.toFixed(1)), p3: parseFloat(interpolatedP3.toFixed(2)), p50: parseFloat(interpolatedP50.toFixed(2)), p97: parseFloat(interpolatedP97.toFixed(2)) }; } function validateInput(id, minValue, maxValue, errorMessageElementId, isRequired = true) { var input = document.getElementById(id); var value = parseFloat(input.value); var errorElement = document.getElementById(errorMessageElementId); var isValid = true; errorElement.style.display = 'block'; // Show error space if (isRequired && (input.value.trim() === "" || isNaN(value))) { errorElement.textContent = "This field is required."; isValid = false; } else if (!isNaN(value)) { if (minValue !== undefined && value maxValue) { errorElement.textContent = "Value exceeds reasonable maximum."; isValid = false; } else { errorElement.textContent = ""; // Clear error errorElement.style.display = 'none'; // Hide error space if valid } } else { errorElement.textContent = ""; // Clear error if not required and empty errorElement.style.display = 'none'; } return isValid; } function calculatePercentile() { var ageInput = document.getElementById('childAge'); var weightInput = document.getElementById('childWeight'); var sexInput = document.getElementById('childSex'); var ageError = document.getElementById('childAgeError'); var weightError = document.getElementById('childWeightError'); var isValid = true; isValid &= validateInput('childAge', 0, 72, 'childAgeError'); // Max 6 years/72 months for WHO standards isValid &= validateInput('childWeight', 0, 30, 'childWeightError'); // Reasonable max weight for this age group if (!isValid) { document.getElementById('results-container').classList.add('hidden'); return; } var ageInMonths = parseFloat(ageInput.value); var weightKg = parseFloat(weightInput.value); var sex = sexInput.value; var calculationResult = calculateApproximatePercentile(ageInMonths, weightKg, sex); var resultsContainer = document.getElementById('results-container'); var mainResultDisplay = document.getElementById('mainResult'); var intermediateAgeDisplay = document.querySelectorAll('.intermediate-results div')[0].children[0]; var intermediateWeightDisplay = document.querySelectorAll('.intermediate-results div')[1].children[0]; var intermediateSexDisplay = document.querySelectorAll('.intermediate-results div')[2].children[0]; if (calculationResult.percentile !== null) { mainResultDisplay.textContent = calculationResult.percentile + "%"; intermediateAgeDisplay.textContent = ageInMonths; intermediateWeightDisplay.textContent = weightKg + " kg"; intermediateSexDisplay.textContent = sex.charAt(0).toUpperCase() + sex.slice(1); // Update intermediate results text in the UI var intermediates = resultsContainer.querySelectorAll('.intermediate-results span'); intermediates[0].textContent = ageInMonths; intermediates[1].textContent = weightKg.toFixed(1); intermediates[2].textContent = sex.charAt(0).toUpperCase() + sex.slice(1); resultsContainer.classList.remove('hidden'); updateChartAndTable(ageInMonths, sex, weightKg, calculationResult); } else { resultsContainer.classList.add('hidden'); mainResultDisplay.textContent = "Error"; } } function resetForm() { document.getElementById('childAge').value = 12; document.getElementById('childWeight').value = 10; document.getElementById('childSex').value = 'male'; document.getElementById('childAgeError').textContent = "; document.getElementById('childAgeError').style.display = 'none'; document.getElementById('childWeightError').textContent = "; document.getElementById('childWeightError').style.display = 'none'; document.getElementById('results-container').classList.add('hidden'); clearChart(); clearTable(); } function copyResults() { var resultsContainer = document.getElementById('results-container'); if (resultsContainer.classList.contains('hidden')) { alert("Calculate results first before copying."); return; } var mainResult = document.getElementById('mainResult').textContent; var intermediates = resultsContainer.querySelectorAll('.intermediate-results span'); var age = intermediates[0].textContent; var weight = intermediates[1].textContent; var sex = intermediates[2].textContent; var formula = document.querySelector('.formula-explanation').textContent; var textToCopy = "Child Weight Percentile Analysis:\n\n"; textToCopy += "Primary Result: " + mainResult + "\n"; textToCopy += "Age: " + age + " months\n"; textToCopy += "Weight: " + weight + "\n"; textToCopy += "Sex: " + sex + "\n\n"; textToCopy += "Formula/Explanation: " + formula; // Use a temporary textarea to copy var textArea = document.createElement("textarea"); textArea.value = textToCopy; textArea.style.position = "fixed"; // Avoid scrolling to bottom textArea.style.opacity = 0; document.body.appendChild(textArea); textArea.focus(); textArea.select(); try { var successful = document.execCommand('copy'); var msg = successful ? 'Results copied successfully!' : 'Failed to copy results.'; alert(msg); } catch (err) { alert('Oops, unable to copy. Please copy manually.'); } document.body.removeChild(textArea); } // Charting Logic var growthChart; var chartContext; function initializeChart() { chartContext = document.getElementById('growthChart').getContext('2d'); growthChart = new Chart(chartContext, { type: 'line', data: { labels: [], // Will be populated datasets: [{ label: '3rd Percentile', data: [], // Will be populated borderColor: 'rgba(255, 99, 132, 1)', // Red backgroundColor: 'rgba(255, 99, 132, 0.1)', fill: false, tension: 0.1 }, { label: '50th Percentile (Median)', data: [], // Will be populated borderColor: 'rgba(54, 162, 235, 1)', // Blue backgroundColor: 'rgba(54, 162, 235, 0.1)', fill: false, tension: 0.1 }, { label: '97th Percentile', data: [], // Will be populated borderColor: 'rgba(75, 192, 192, 1)', // Green backgroundColor: 'rgba(75, 192, 192, 0.1)', fill: false, tension: 0.1 }, { label: 'Child\'s Data Point', data: [], // Single point borderColor: 'rgba(255, 206, 86, 1)', // Yellow backgroundColor: 'rgba(255, 206, 86, 1)', fill: false, pointRadius: 6, pointHoverRadius: 8, type: 'scatter' // Use scatter for a single point }] }, options: { responsive: true, maintainAspectRatio: false, scales: { x: { title: { display: true, text: 'Age (Months)' } }, y: { title: { display: true, text: 'Weight (kg)' }, beginAtZero: true } }, plugins: { tooltip: { callbacks: { label: function(context) { var label = context.dataset.label || "; if (label) { label += ': '; } if (context.parsed.y !== null) { label += context.parsed.y + ' kg'; } return label; } } } } } }); } function updateChartAndTable(currentAge, sex, currentWeight, percentileData) { var ages = Object.keys(whoGrowthData[sex]).map(Number).sort(function(a, b) { return a – b; }); var dataForSex = whoGrowthData[sex]; var labels = []; var p3Data = []; var p50Data = []; var p97Data = []; // Generate data for relevant age range, including current age var minAge = Math.min(currentAge, ages[0]); var maxAge = Math.max(currentAge, ages[ages.length – 1]); var chartAgePoints = new Set(ages); chartAgePoints.add(currentAge); var sortedChartAges = Array.from(chartAgePoints).sort(function(a, b) { return a – b; }).filter(age => age >= 0 && age w !== null && !isNaN(w)); var maxY = Math.max(…allWeights); var minY = Math.min(…allWeights.filter(w => w > 0)) || 0; // Ensure minY is not negative if all weights are 0 or less growthChart.options.scales.y.min = Math.max(0, minY * 0.9); // Start slightly below min value, but not below 0 growthChart.options.scales.y.max = maxY * 1.1; // End slightly above max value growthChart.update(); // Update Table updateGrowthTable(ages, dataForSex); } function updateGrowthTable(ages, dataForSex) { var tableBody = document.getElementById('growthTableBody'); tableBody.innerHTML = "; // Clear existing rows var tableAges = [0, 6, 12, 18, 24, 36, 48, 60]; // Select key ages for the table tableAges.forEach(function(age) { var row = tableBody.insertRow(); var cellAge = row.insertCell(); var cellSex = row.insertCell(); var cellP3 = row.insertCell(); var cellP50 = row.insertCell(); var cellP97 = row.insertCell(); var interpolatedData = calculateApproximatePercentile(age, 0, dataForSex === whoGrowthData.male ? 'male' : 'female'); cellAge.textContent = age === 0 ? "Birth" : age; cellSex.textContent = dataForSex === whoGrowthData.male ? "Male" : "Female"; cellP3.textContent = interpolatedData.p3 !== null ? interpolatedData.p3.toFixed(2) : '-'; cellP50.textContent = interpolatedData.p50 !== null ? interpolatedData.p50.toFixed(2) : '-'; cellP97.textContent = interpolatedData.p97 !== null ? interpolatedData.p97.toFixed(2) : '-'; }); } function clearChart() { if (growthChart) { growthChart.data.labels = []; growthChart.data.datasets.forEach(function(dataset) { dataset.data = []; }); growthChart.update(); } } function clearTable() { var tableBody = document.getElementById('growthTableBody'); tableBody.innerHTML = "; } function toggleFaq(element) { var parent = element.parentElement; parent.classList.toggle('open'); } // Initial setup document.addEventListener('DOMContentLoaded', function() { initializeChart(); // Optionally calculate on page load with defaults // calculatePercentile(); });

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