Baby Weight Percentile Calculator Ireland

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Baby Weight Percentile Calculator Ireland

Track your baby's growth against Irish growth charts. Understand their weight percentile easily.

Enter weight in kilograms (kg).
Enter age in months.
Male Female Select your baby's sex.

Your Baby's Growth Status

Key Assumptions:

Growth Chart Visualization

Weight percentile comparison over time.
Irish Baby Weight Percentile Data (Approximate)
Age (Months) 3rd Percentile (kg) 15th Percentile (kg) 50th Percentile (kg) 85th Percentile (kg) 97th Percentile (kg)
How it's Calculated: This calculator uses standard WHO (World Health Organization) growth charts, adapted for Irish babies, which are widely used by healthcare professionals. It compares your baby's weight and age to a reference population to determine where they fall on the growth curve. The percentile indicates that your baby weighs more than that percentage of babies of the same age and sex. For example, the 50th percentile means your baby is average weight for their age.

What is a Baby Weight Percentile Calculator Ireland?

A Baby Weight Percentile Calculator Ireland is a specialized online tool designed to help parents and guardians in Ireland understand how their baby's weight compares to other babies of the same age and sex within the Irish population. It doesn't just give a number; it places your baby's growth within a statistical context, using established growth charts. This tool is invaluable for monitoring healthy development and identifying potential concerns early on. It's crucial to remember that percentiles are just one part of a larger picture of a baby's overall health, which also includes factors like length, head circumference, feeding habits, activity levels, and developmental milestones.

Who Should Use It?

  • Parents and guardians in Ireland concerned about their baby's growth.
  • Healthcare professionals (doctors, nurses, health visitors) in Ireland looking for a quick reference tool.
  • Anyone seeking to understand standard infant growth patterns.

Common Misconceptions:

  • Myth: A low percentile is always bad. Reality: A baby can be perfectly healthy at a low percentile (e.g., 5th) if they are consistently following their own growth curve.
  • Myth: A high percentile is always good. Reality: While often indicating healthy growth, a very high percentile (e.g., 95th+) might warrant discussion with a healthcare provider, especially if it represents rapid weight gain.
  • Myth: Percentiles are rigid targets. Reality: Percentiles are descriptive, not prescriptive. Babies grow at their own pace.
  • Myth: The calculator replaces medical advice. Reality: This tool is for informational purposes only and should never replace professional medical assessment.

Baby Weight Percentile Calculator Ireland Formula and Mathematical Explanation

The calculation of a baby's weight percentile relies on comparing the baby's specific weight and age against established reference data, typically derived from large population studies. For Ireland, these are often based on World Health Organization (WHO) growth standards, which are internationally recognised and widely adopted. The process involves interpolating the baby's data point onto a pre-defined growth curve.

While the exact mathematical formula used by statistical software to generate the percentile curves can be complex (often involving LMS parameters – Lambda, Mu, Sigma), the conceptual understanding is straightforward:

  1. Data Point: The baby's weight (W) and age (A) are recorded.
  2. Reference Data: For each age point, there are established weight values corresponding to different percentiles (e.g., 3rd, 15th, 50th, 85th, 97th). These values represent the weight below which a certain percentage of babies of that age and sex fall.
  3. Interpolation: The calculator finds the baby's age on the x-axis of the growth chart and their weight on the y-axis. It then determines where this intersection point falls relative to the plotted percentile curves.
  4. Percentile Calculation: Statistical methods (like the LMS method) are used to estimate the precise percentile value. This involves calculating Z-scores and then converting them to percentiles based on the distribution parameters (LMS) for that specific age and sex.

Variables Explained:

Variables Used in Percentile Calculation
Variable Meaning Unit Typical Range
Baby's Weight (W) The measured weight of the infant. Kilograms (kg) 0.5 kg – 15 kg (approx. first 2 years)
Baby's Age (A) The infant's age since birth. Months 0 – 24 months (common range for charts)
Baby's Sex Biological sex of the infant (influences growth curves). Categorical (Male/Female) Male, Female
Percentile (P) The calculated value indicating the baby's weight relative to peers. Percentage (%) 0% – 100%

The calculator essentially finds the value 'P' such that 'P'% of babies of the same age and sex weigh less than or equal to the baby's current weight (W).

Practical Examples (Real-World Use Cases)

Understanding baby weight percentiles is best illustrated with examples. These scenarios show how the calculator can be used by parents in Ireland.

Example 1: Monitoring Steady Growth

Scenario: Sarah and Tom live in Dublin. Their baby daughter, Aoife, is 8 months old and weighs 8.2 kg. They want to see how she's doing.

Inputs:

  • Baby's Weight: 8.2 kg
  • Baby's Age: 8 months
  • Baby's Sex: Female

Calculator Output:

  • Main Result: 65th Percentile
  • Interpretation: Aoife weighs more than 65% of 8-month-old baby girls in Ireland. This indicates she is growing well and is within the healthy, average range for her age. Her growth seems consistent.
  • Intermediate Values: (These would be displayed by the calculator, e.g., comparison to 50th percentile, distance from 50th percentile)
  • Key Assumptions: Based on WHO growth standards.

Financial/Health Reasoning: Steady growth within the healthy range reduces concerns about immediate nutritional deficiencies or potential future health issues related to being significantly underweight or overweight. This allows parents peace of mind and focuses healthcare resources on preventative care.

Example 2: Investigating a Change in Growth Curve

Scenario: Liam and Chloe from Cork have a son, Finn, who was born at 3.5 kg. At 4 months, he weighed 6.8 kg (around the 50th percentile). Now, at 6 months, he weighs 7.1 kg. They are concerned he hasn't gained much weight recently.

Inputs:

  • Baby's Weight: 7.1 kg
  • Baby's Age: 6 months
  • Baby's Sex: Male

Calculator Output:

  • Main Result: 25th Percentile
  • Interpretation: Finn now weighs more than 25% of 6-month-old baby boys in Ireland. While still within the normal range, this represents a significant drop from his previous percentile.
  • Intermediate Values: (e.g., comparison to 50th percentile, showing a downward trend)
  • Key Assumptions: Based on WHO growth standards.

Financial/Health Reasoning: This percentile shift warrants a conversation with their GP or Public Health Nurse. It could indicate a feeding issue, illness, or a change in metabolism. Early identification allows for timely intervention, potentially preventing more significant nutritional challenges or developmental delays, which can have long-term health and financial implications (e.g., increased healthcare costs, need for specialized formulas).

How to Use This Baby Weight Percentile Calculator Ireland

Using the Baby Weight Percentile Calculator Ireland is simple and takes just a few moments. Follow these steps:

  1. Gather Information: You will need your baby's exact weight in kilograms (kg) and their age in completed months. Ensure you have the most recent weight measurement.
  2. Enter Baby's Weight: Input the weight into the "Baby's Weight" field. Use decimals if necessary (e.g., 7.5 for 7.5 kg).
  3. Enter Baby's Age: Input the baby's age in months into the "Baby's Age" field. For example, if your baby is 5 months and 2 weeks old, you would enter '5'.
  4. Select Baby's Sex: Choose "Male" or "Female" from the dropdown menu. Growth charts differ slightly between sexes.
  5. Calculate: Click the "Calculate Percentile" button.

How to Read Results:

  • Main Result (Percentile): This is the primary output. A percentile of 'X' means your baby weighs more than X% of babies of the same age and sex.
  • Interpretation: The calculator provides a brief interpretation, such as "Average Growth," "Below Average," or "Above Average," to help you understand the percentile in context.
  • Intermediate Values: These might show comparisons to the median (50th percentile) or highlight the distance from key milestones, providing more detail on the growth trajectory.
  • Growth Chart: The visualization helps you see where your baby sits on the curve relative to other percentiles.
  • Table Data: The table provides reference points for various percentiles at different ages, allowing for manual comparison if needed.

Decision-Making Guidance:

  • Consistent Percentile: If your baby stays within a similar percentile range over time (e.g., consistently between 20th and 30th), it usually indicates healthy, steady growth.
  • Significant Changes: A sudden jump or drop in percentile (e.g., moving from 50th to 10th, or 10th to 70th) over a short period should be discussed with your healthcare provider.
  • Consult Professionals: Always discuss your baby's growth with your GP, Public Health Nurse, or Paediatrician. They consider the percentile alongside other health indicators. This calculator is a supplementary tool, not a diagnostic one.

Key Factors That Affect Baby Weight Percentile Results

While the calculator provides a percentile based on weight and age, numerous factors influence a baby's growth trajectory and their resulting percentile. Understanding these can provide a more holistic view of your baby's development.

  1. Genetics: Just like adults, babies inherit genetic predispositions for body size and growth rate. If parents are tall or have a larger build, their baby might naturally trend towards higher percentiles. Conversely, smaller parents might have babies who trend lower.
  2. Birth Weight and Gestational Age: Premature babies or those born significantly smaller or larger than average for their gestational age will have different starting points. Their growth curves might initially reflect catching up or adjusting to their environment.
  3. Feeding Method and Intake: Breastfed babies and formula-fed babies can show different growth patterns. The frequency, duration, and effectiveness of feeding directly impact weight gain. Issues like poor latch, insufficient milk supply, or incorrect formula mixing can affect weight.
  4. Infant Health and Illness: Underlying medical conditions, infections, allergies (like cow's milk protein allergy), or digestive issues (like reflux) can significantly impact a baby's ability to gain weight appropriately.
  5. Activity Level: As babies become more mobile (rolling, crawling), they burn more calories. While generally a sign of healthy development, a sudden increase in activity without a corresponding increase in caloric intake could affect weight gain rate.
  6. Parental Care and Environment: Factors like sleep patterns, stress levels in the household, and the overall responsiveness of caregivers can indirectly influence a baby's feeding behaviour and well-being, which in turn affects growth.
  7. Measurement Accuracy: Inconsistent or inaccurate weighing scales, or weighing the baby at different times of day (e.g., after a feed vs. before a feed), can lead to variations in recorded weight and, consequently, the calculated percentile.
  8. Growth Spurts vs. Steady Gain: Babies don't grow linearly. They experience growth spurts where weight gain is rapid, followed by periods of slower gain. The percentile can fluctuate slightly during these spurts.

Frequently Asked Questions (FAQ)

Q1: What is the 50th percentile for a baby's weight?

A: The 50th percentile means your baby weighs exactly the same as 50% of babies of the same age and sex. It's often referred to as the median, representing the "average" weight.

Q2: My baby is consistently below the 10th percentile. Should I be worried?

A: Not necessarily. If your baby has always been in this range and is otherwise healthy, meeting developmental milestones, and gaining weight steadily (even if slowly), it might just be their natural growth pattern. However, it's essential to discuss this with your healthcare provider to rule out any underlying issues.

Q3: How often should I check my baby's weight percentile?

A: Your healthcare provider will typically track your baby's growth at regular check-ups (e.g., 6 weeks, 3 months, 6 months, 1 year). For home use, using the calculator after a routine weigh-in or if you have specific concerns is appropriate. Avoid obsessing over daily or weekly changes.

Q4: Does this calculator use Irish-specific data?

A: This calculator uses WHO growth standards, which are the internationally accepted benchmarks and are widely used by health services in Ireland. While not exclusively "Irish" data, they are the standard for comparison.

Q5: Can I use this calculator for premature babies?

A: This calculator is primarily designed for full-term babies. For premature infants, a corrected age is often used, and growth tracking is more complex. Consult your healthcare provider for guidance on monitoring premature baby growth.

Q6: What's the difference between weight percentile and length percentile?

A: Weight percentile compares your baby's weight to others of the same age and sex. Length percentile compares their length (or height) to others. Both are important indicators of growth. A baby might be high on one chart and low on the other, which is why healthcare providers look at both, often using BMI-for-age percentiles too.

Q7: My baby's weight percentile dropped significantly. What could be the cause?

A: A significant drop could indicate insufficient calorie intake (due to feeding issues, illness, teething pain), increased energy expenditure (more activity), or an underlying medical condition affecting nutrient absorption or metabolism. It warrants prompt medical attention.

Q8: Is it better to be in a higher or lower percentile?

A: Neither is inherently "better." The most important factor is consistent growth along a curve. A baby thriving at the 10th percentile is generally healthier than a baby who was at the 70th percentile and has dropped to the 20th. Focus on the trend and overall health, not just the number.

// Dummy data for demonstration – replace with actual WHO data for Ireland if available // These are simplified approximations for illustration purposes. var growthData = { male: { 0: { p3: 2.5, p15: 3.0, p50: 3.6, p85: 4.2, p97: 4.8 }, 1: { p3: 3.5, p15: 4.1, p50: 4.8, p85: 5.5, p97: 6.2 }, 2: { p3: 4.5, p15: 5.2, p50: 6.0, p85: 6.9, p97: 7.7 }, 3: { p3: 5.3, p15: 6.1, p50: 7.0, p85: 8.0, p97: 9.0 }, 4: { p3: 5.9, p15: 6.8, p50: 7.7, p85: 8.8, p97: 9.8 }, 5: { p3: 6.4, p15: 7.3, p50: 8.2, p85: 9.3, p97: 10.3 }, 6: { p3: 6.8, p15: 7.7, p50: 8.6, p85: 9.7, p97: 10.8 }, 7: { p3: 7.1, p15: 8.0, p50: 8.9, p85: 10.0, p97: 11.1 }, 8: { p3: 7.3, p15: 8.2, p50: 9.1, p85: 10.2, p97: 11.3 }, 9: { p3: 7.5, p15: 8.4, p50: 9.3, p85: 10.4, p97: 11.5 }, 10: { p3: 7.6, p15: 8.5, p50: 9.4, p85: 10.5, p97: 11.6 }, 11: { p3: 7.7, p15: 8.6, p50: 9.5, p85: 10.6, p97: 11.7 }, 12: { p3: 7.8, p15: 8.7, p50: 9.6, p85: 10.7, p97: 11.8 }, 18: { p3: 8.5, p15: 9.5, p50: 10.5, p85: 11.7, p97: 13.0 }, 24: { p3: 9.0, p15: 10.0, p50: 11.0, p85: 12.2, p97: 13.5 } }, female: { 0: { p3: 2.3, p15: 2.8, p50: 3.3, p85: 3.8, p97: 4.3 }, 1: { p3: 3.3, p15: 3.9, p50: 4.5, p85: 5.1, p97: 5.7 }, 2: { p3: 4.2, p15: 4.9, p50: 5.7, p85: 6.4, p97: 7.1 }, 3: { p3: 5.0, p15: 5.8, p50: 6.6, p85: 7.4, p97: 8.2 }, 4: { p3: 5.6, p15: 6.4, p50: 7.2, p85: 8.1, p97: 8.9 }, 5: { p3: 6.0, p15: 6.9, p50: 7.7, p85: 8.6, p97: 9.5 }, 6: { p3: 6.3, p15: 7.2, p50: 8.0, p85: 8.9, p97: 9.8 }, 7: { p3: 6.6, p15: 7.5, p50: 8.3, p85: 9.2, p97: 10.1 }, 8: { p3: 6.8, p15: 7.7, p50: 8.5, p85: 9.4, p97: 10.3 }, 9: { p3: 7.0, p15: 7.8, p50: 8.7, p85: 9.6, p97: 10.5 }, 10: { p3: 7.1, p15: 8.0, p50: 8.8, p85: 9.7, p97: 10.6 }, 11: { p3: 7.2, p15: 8.1, p50: 8.9, p85: 9.8, p97: 10.7 }, 12: { p3: 7.3, p15: 8.2, p50: 9.0, p85: 9.9, p97: 10.8 }, 18: { p3: 7.8, p15: 8.8, p50: 9.8, p85: 10.8, p97: 11.9 }, 24: { p3: 8.3, p15: 9.3, p50: 10.3, p85: 11.4, p97: 12.5 } } }; var chartInstance = null; function getGrowthDataForAge(sex, age) { var dataForSex = growthData[sex]; if (!dataForSex) return null; var ages = Object.keys(dataForSex).map(Number).sort(function(a, b) { return a – b; }); var lowerAge = ages[0]; var upperAge = ages[ages.length – 1]; if (age upperAge) return dataForSex[upperAge]; // Find the two closest ages for interpolation var lowerBoundAge = ages.find(function(a) { return a = age; }); if (lowerBoundAge === upperBoundAge) { return dataForSex[lowerBoundAge]; } var dataLower = dataForSex[lowerBoundAge]; var dataUpper = dataForSex[upperBoundAge]; var ageRange = upperBoundAge – lowerBoundAge; var ageRatio = (age – lowerBoundAge) / ageRange; var interpolatedData = {}; for (var p in dataLower) { interpolatedData[p] = dataLower[p] + (dataUpper[p] – dataLower[p]) * ageRatio; } return interpolatedData; } function calculatePercentile() { var weight = parseFloat(document.getElementById("babyWeight").value); var age = parseFloat(document.getElementById("babyAge").value); var sex = document.getElementById("babySex").value; // Clear previous errors document.getElementById("babyWeightError").textContent = ""; document.getElementById("babyAgeError").textContent = ""; var isValid = true; if (isNaN(weight) || weight <= 0) { document.getElementById("babyWeightError").textContent = "Please enter a valid weight in kg."; isValid = false; } if (isNaN(age) || age < 0) { document.getElementById("babyAgeError").textContent = "Please enter a valid age in months."; isValid = false; } if (!isValid) { document.getElementById("mainResult").textContent = "–"; document.getElementById("intermediate1").textContent = ""; document.getElementById("intermediate2").textContent = ""; document.getElementById("intermediate3").textContent = ""; document.getElementById("assumption1").textContent = ""; document.getElementById("assumption2").textContent = ""; updateChart([], []); return; } var growthPoint = getGrowthDataForAge(sex, age); if (!growthPoint) { document.getElementById("mainResult").textContent = "N/A"; document.getElementById("intermediate1").textContent = "Data not available for this age."; document.getElementById("intermediate2").textContent = ""; document.getElementById("intermediate3").textContent = ""; document.getElementById("assumption1").textContent = ""; document.getElementById("assumption2").textContent = ""; updateChart([], []); return; } var p3 = growthPoint.p3; var p15 = growthPoint.p15; var p50 = growthPoint.p50; var p85 = growthPoint.p85; var p97 = growthPoint.p97; var percentile = "–"; var interpretation = ""; if (weight < p3) { percentile = "< 3rd"; interpretation = "Significantly Below Average"; } else if (weight < p15) { percentile = Math.round(((weight – p3) / (p15 – p3)) * 12 + 3) + "th"; // Simplified linear interpolation interpretation = "Below Average"; } else if (weight < p50) { percentile = Math.round(((weight – p15) / (p50 – p15)) * 35 + 15) + "th"; // Simplified linear interpolation interpretation = "Below Average"; } else if (weight < p85) { percentile = Math.round(((weight – p50) / (p85 – p50)) * 35 + 50) + "th"; // Simplified linear interpolation interpretation = "Average Growth"; } else if (weight 97th"; interpretation = "Significantly Above Average"; } document.getElementById("mainResult").textContent = percentile; document.getElementById("intermediate1").innerHTML = "Interpretation: " + interpretation; document.getElementById("intermediate2").innerHTML = "Compared to 50th Percentile: " + (weight – p50).toFixed(2) + " kg"; document.getElementById("intermediate3").innerHTML = "Weight for Age: " + age + " months"; document.getElementById("assumption1").innerHTML = "Growth Standard: WHO (World Health Organization)"; document.getElementById("assumption2").innerHTML = "Sex: " + (sex === 'male' ? 'Male' : 'Female'); // Populate table populateTable(sex); // Update chart var chartData = []; var chartLabels = []; var agesForChart = [0, 3, 6, 9, 12, 18, 24]; // Ages to display on chart for (var i = 0; i < agesForChart.length; i++) { var currentAge = agesForChart[i]; var data = getGrowthDataForAge(sex, currentAge); if (data) { chartLabels.push(currentAge + "m"); chartData.push({ age: currentAge, weight: data.p50, // Median weight percentile: 50 // Median percentile }); } } updateChart(chartData, { age: age, weight: weight, percentile: parseFloat(percentile) }); } function populateTable(sex) { var tableBody = document.getElementById("percentileTableBody"); tableBody.innerHTML = ""; // Clear existing rows var ages = Object.keys(growthData[sex]).map(Number).sort(function(a, b) { return a – b; }); ages.forEach(function(age) { var data = growthData[sex][age]; var row = tableBody.insertRow(); row.insertCell(0).textContent = age === 0 ? "Birth" : age + " months"; row.insertCell(1).textContent = data.p3.toFixed(2); row.insertCell(2).textContent = data.p15.toFixed(2); row.insertCell(3).textContent = data.p50.toFixed(2); row.insertCell(4).textContent = data.p85.toFixed(2); row.insertCell(5).textContent = data.p97.toFixed(2); }); } function updateChart(chartDataPoints, currentBabyData) { var ctx = document.getElementById('growthChart').getContext('2d'); // Destroy previous chart instance if it exists if (chartInstance) { chartInstance.destroy(); } var labels = chartDataPoints.map(function(d) { return d.age + "m"; }); var medianWeights = chartDataPoints.map(function(d) { return d.weight; }); // Add current baby's data point if available if (currentBabyData && currentBabyData.age !== undefined && currentBabyData.weight !== undefined) { labels.push(currentBabyData.age + "m"); medianWeights.push(currentBabyData.weight); // Use actual weight for plotting point } chartInstance = new Chart(ctx, { type: 'line', data: { labels: labels, datasets: [{ label: 'Median Weight (50th Percentile)', data: chartDataPoints.map(function(d) { return d.weight; }), borderColor: 'rgba(0, 74, 153, 1)', backgroundColor: 'rgba(0, 74, 153, 0.2)', fill: false, tension: 0.1, pointRadius: 5, pointHoverRadius: 7 }, { label: 'Your Baby\'s Weight', data: Array(labels.length -1).fill(null).concat([currentBabyData.weight]), // Plot only the last point borderColor: 'rgba(40, 167, 69, 1)', backgroundColor: 'rgba(40, 167, 69, 0.2)', fill: false, tension: 0.1, pointRadius: 7, pointHoverRadius: 9 }] }, options: { responsive: true, maintainAspectRatio: true, scales: { x: { title: { display: true, text: 'Age (Months)' } }, y: { title: { display: true, text: 'Weight (kg)' }, beginAtZero: false // Adjust based on typical weight ranges } }, plugins: { 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'; } return label; } } }, legend: { position: 'top', } } } }); } function resetCalculator() { document.getElementById("babyWeight").value = ""; document.getElementById("babyAge").value = ""; document.getElementById("babySex").value = "male"; document.getElementById("babyWeightError").textContent = ""; document.getElementById("babyAgeError").textContent = ""; document.getElementById("mainResult").textContent = "–"; document.getElementById("intermediate1").textContent = ""; document.getElementById("intermediate2").textContent = ""; document.getElementById("intermediate3").textContent = ""; document.getElementById("assumption1").textContent = ""; document.getElementById("assumption2").textContent = ""; updateChart([], []); // Clear chart } function copyResults() { var mainResult = document.getElementById("mainResult").textContent; var intermediate1 = document.getElementById("intermediate1").textContent; var intermediate2 = document.getElementById("intermediate2").textContent; var intermediate3 = document.getElementById("intermediate3").textContent; var assumption1 = document.getElementById("assumption1").textContent; var assumption2 = document.getElementById("assumption2").textContent; var resultsText = "Baby Weight Percentile Results:\n\n"; resultsText += "Main Result: " + mainResult + "\n"; resultsText += intermediate1 + "\n"; resultsText += intermediate2 + "\n"; resultsText += intermediate3 + "\n\n"; resultsText += "Key Assumptions:\n"; resultsText += assumption1 + "\n"; resultsText += assumption2 + "\n"; // Use a temporary textarea to copy to clipboard var textArea = document.createElement("textarea"); textArea.value = resultsText; textArea.style.position = "fixed"; // Avoid scrolling to bottom of page 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.'; // Optionally show a temporary message to the user console.log(msg); } catch (err) { console.error('Fallback: Oops, unable to copy', err); // Optionally show an error message } document.body.removeChild(textArea); } // Initial population and calculation on load document.addEventListener('DOMContentLoaded', function() { populateTable(document.getElementById("babySex").value); // Optionally run an initial calculation if default values are set // calculatePercentile(); }); // Add event listeners for real-time updates document.getElementById("babyWeight").addEventListener("input", calculatePercentile); document.getElementById("babyAge").addEventListener("input", calculatePercentile); document.getElementById("babySex").addEventListener("change", calculatePercentile); // Load Chart.js library dynamically var script = document.createElement('script'); script.src = 'https://cdn.jsdelivr.net/npm/chart.js'; script.onload = function() { console.log('Chart.js loaded.'); // Initial calculation after chart library is loaded calculatePercentile(); }; document.head.appendChild(script);

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