Calculate Child Weight Percentile

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Child Weight Percentile Calculator

Calculate Child Weight Percentile

Enter the child's age in completed months.
Enter the child's weight in kilograms.
Male Female Select the child's sex.

Your Results

Weight for Age Percentile:
Z-Score:
Growth Curve Position:

Key Assumptions:

Age: months
Weight: kg
Sex:
Formula Explanation: This calculator uses the World Health Organization (WHO) or Centers for Disease Control and Prevention (CDC) growth charts and formulas to determine the weight-for-age percentile. The percentile indicates the child's weight relative to other children of the same age and sex. A Z-score is also calculated, representing the number of standard deviations the child's weight is from the median.

Growth Data Table

Weight-for-Age Percentiles (Example Data)
Age (Months) Weight (kg) – 50th Percentile (Male) Weight (kg) – 50th Percentile (Female) Weight (kg) – 3rd Percentile (Male) Weight (kg) – 97th Percentile (Male)

What is Child Weight Percentile?

Child weight percentile is a way to measure a child's weight in relation to other children of the same age and sex. It's a crucial indicator of a child's growth and development. Instead of absolute numbers, percentiles provide a comparative context. For instance, if a child is at the 75th weight percentile for their age and sex, it means they weigh more than 75% of children in that same group and less than 25%. Understanding child weight percentile is vital for parents and healthcare providers to ensure healthy growth patterns.

Who should use it? Parents, pediatricians, healthcare providers, and anyone concerned about a child's growth and nutritional status should understand and utilize child weight percentile data. It's particularly important during infancy and early childhood when growth is rapid and critical.

Common Misconceptions:

  • Myth: Higher percentile is always better. Reality: While being in a healthy percentile range is good, extremely high percentiles can also indicate potential issues like obesity. The goal is a healthy, consistent growth trajectory within an appropriate range.
  • Myth: Percentiles are fixed. Reality: A child's percentile can fluctuate, especially in the first few years. What matters most is a consistent growth curve that follows a general trend, rather than specific percentile numbers at any given point.
  • Myth: Percentiles are a diagnosis. Reality: Percentiles are a screening tool. They indicate a potential area of concern that requires further evaluation by a healthcare professional, not a definitive diagnosis on their own.

Child Weight Percentile Formula and Mathematical Explanation

Calculating the exact weight percentile involves complex statistical models based on reference growth charts, typically provided by organizations like the World Health Organization (WHO) for children aged 0-2 years and the Centers for Disease Control and Prevention (CDC) for children aged 2-20 years. These charts are derived from extensive population data.

The core concept relies on finding the child's position on the smoothed percentile curves. While a direct, simple formula for every point isn't feasible without the underlying statistical models, the process generally involves:

  1. Identifying the Reference Data: Using age- and sex-specific growth charts (e.g., WHO or CDC).
  2. Locating the Child's Data Point: Plotting the child's age on the x-axis and their weight on the y-axis.
  3. Determining the Percentile Curve: Finding which percentile curve the plotted point falls closest to.
  4. Calculating the Z-Score: A more precise method involves calculating a Z-score, which measures how many standard deviations a child's measurement is from the median (50th percentile). The formula for Z-score is:
    Z = (Weight / M) ^ L - 1 / (L * S) Where:
    • Weight is the child's measured weight.
    • M is the median weight for the child's age and sex.
    • S is the coefficient of variation (related to standard deviation) for the child's age and sex.
    • L is the Box-Cox transformation parameter for the child's age and sex.
    These M, S, and L values are specific to each age and sex and are derived from the growth chart data.
  5. Converting Z-Score to Percentile: Once the Z-score is calculated, it can be converted into a percentile using standard statistical tables or functions (like the cumulative distribution function of the standard normal distribution).

Our calculator simplifies this by using pre-programmed algorithms that approximate these calculations based on the official WHO/CDC growth standards.

Variables Table

Variable Meaning Unit Typical Range
Age Child's age Months 0 – 240 (0-20 years)
Weight Child's measured weight Kilograms (kg) 0.5 – 100+ kg (highly variable)
Sex Child's biological sex Categorical Male, Female
Percentile Child's weight rank compared to peers % 0 – 100
Z-Score Number of standard deviations from the median Standard Deviations Approx. -3 to +3 (can extend beyond)
M (Median) Median weight for age/sex kg Varies by age/sex
S (CV) Coefficient of Variation for weight Unitless Varies by age/sex
L (Box-Cox) Box-Cox transformation parameter Unitless Varies by age/sex

Practical Examples (Real-World Use Cases)

Understanding child weight percentile is crucial for monitoring growth. Here are a couple of examples:

Example 1: Healthy Growth Monitoring

Scenario: A 12-month-old boy weighs 10.5 kg. His parents are concerned if he's growing adequately.

Inputs:

  • Age: 12 months
  • Weight: 10.5 kg
  • Sex: Male

Calculation Result (Hypothetical):

  • Weight Percentile: 50th
  • Z-Score: 0.0
  • Growth Curve Position: Median

Interpretation: This indicates the child is right at the median weight for his age and sex. This is considered excellent growth, showing he is tracking perfectly along the expected growth curve.

Example 2: Monitoring a Premature or Underweight Infant

Scenario: A 6-month-old girl weighs 6.2 kg. She was born prematurely and her parents want to ensure she's catching up.

Inputs:

  • Age: 6 months
  • Weight: 6.2 kg
  • Sex: Female

Calculation Result (Hypothetical):

  • Weight Percentile: 10th
  • Z-Score: -1.28
  • Growth Curve Position: Below Average

Interpretation: This places the child in the lower end of the healthy growth range. While not a cause for immediate alarm, it suggests the child is smaller than most peers. The pediatrician will likely monitor her closely, ensuring adequate nutrition and tracking her growth trajectory over time to see if she is consistently gaining weight and moving towards a higher percentile or maintaining a stable position. This data helps inform feeding strategies and potential interventions.

How to Use This Child Weight Percentile Calculator

Using our calculator is straightforward and designed to provide quick insights into your child's growth.

  1. Enter Child's Age: Input the child's age in completed months. For example, if your child is 1 year and 3 months old, enter '15'.
  2. Enter Child's Weight: Provide the child's most recent weight measurement in kilograms (kg). Ensure you use an accurate scale.
  3. Select Child's Sex: Choose 'Male' or 'Female' from the dropdown menu.
  4. Calculate: Click the "Calculate Percentile" button.

How to Read Results:

  • Primary Result (Weight Percentile): This is the main output, showing the percentage of children of the same age and sex that your child weighs less than. A result of '50th' means average weight. Results between the 3rd and 97th percentiles are generally considered within the normal growth range.
  • Z-Score: This provides a more precise statistical measure. A Z-score of 0 is the median. Positive scores mean heavier than average, negative scores mean lighter than average.
  • Growth Curve Position: A simplified interpretation of the percentile and Z-score (e.g., "Average," "Below Average," "Above Average").
  • Key Assumptions: This section confirms the inputs you used for the calculation.
  • Formula Explanation: Briefly describes the methodology used.

Decision-Making Guidance:

  • Consistent Growth: The most important factor is a consistent growth pattern over time. If your child's percentile remains stable, even if it's low or high, it often indicates healthy growth.
  • Sudden Changes: A sudden drop or jump in percentile can be a sign that needs medical attention.
  • Consult a Professional: This calculator is a tool, not a substitute for professional medical advice. Always discuss your child's growth with their pediatrician or healthcare provider. They can consider other factors like height, head circumference, and overall health.

Key Factors That Affect Child Weight Percentile Results

Several factors influence a child's weight percentile, and it's important to consider these when interpreting the results.

  • Genetics: Just like adults, children have genetic predispositions that influence their body size and growth rate. Some children are naturally leaner, while others are naturally more robust. This is a primary factor in determining where a child falls on the growth charts.
  • Nutrition and Diet: Adequate and appropriate nutrition is fundamental for healthy weight gain. This includes sufficient calories, protein, fats, vitamins, and minerals. Issues like picky eating, food allergies, digestive problems, or inadequate access to nutritious food can significantly impact weight.
  • Health Status and Illness: Chronic or acute illnesses can affect a child's appetite, nutrient absorption, and metabolism, leading to weight loss or failure to gain weight appropriately. Conditions like celiac disease, thyroid issues, or infections can play a role.
  • Physical Activity Levels: While important for overall health, very high levels of physical activity without sufficient caloric intake can sometimes lead to lower weight percentiles. Conversely, a sedentary lifestyle can contribute to higher weight percentiles.
  • Prematurity and Birth Weight: Premature babies often experience a "catch-up" growth phase after birth. Their percentile trajectory might initially be lower but should ideally move towards a more typical range over time. Birth weight itself also sets an initial baseline.
  • Socioeconomic Factors: Access to healthcare, quality nutrition, and safe environments can be influenced by socioeconomic status, indirectly affecting a child's growth and weight percentile.
  • Medications: Certain medications can have side effects that impact appetite or metabolism, potentially affecting weight gain.

Frequently Asked Questions (FAQ)

What is the difference between weight percentile and BMI percentile?
Weight percentile specifically looks at a child's weight relative to their age and sex. BMI percentile, on the other hand, considers both weight and height to assess body composition relative to age and sex. BMI percentile is often a better indicator of healthy weight status, as it accounts for a child's frame size.
At what age do weight percentiles become less important?
While weight percentile is crucial in infancy and early childhood, its importance shifts as a child gets older. From age 2 onwards, BMI percentile is generally preferred by healthcare providers as it better reflects body fatness and risk for weight-related health issues. However, weight-for-age is still monitored.
My child is consistently in the 90th percentile. Should I be worried?
A consistent percentile, even if high, often indicates healthy growth for your child's genetic makeup. However, a percentile above the 95th is typically considered overweight or obese and warrants a discussion with your pediatrician. They will assess other factors like height, activity level, and family history to provide guidance.
My child dropped from the 50th to the 10th percentile. What does this mean?
A significant drop in percentile (like from the 50th to the 10th) is a key indicator that requires medical attention. It could signal an underlying health issue, inadequate nutrition, or a change in growth pattern that needs investigation by a pediatrician.
Are the WHO and CDC growth charts the same?
No, they are different. The WHO growth charts are recommended for infants and children from birth up to 2 years old globally. The CDC growth charts are used for children aged 2 to 20 years in the United States. They use slightly different methodologies and data sets. Our calculator aims to align with these standards.
How accurate are online percentile calculators?
Reputable online calculators, like this one, use algorithms based on official WHO/CDC data and are generally quite accurate for providing an estimate. However, they are tools for information and screening, not a replacement for a professional assessment by a pediatrician who considers the child's full health picture.
What if my child's weight is outside the typical range shown on the chart?
Growth charts typically extend from the 3rd to the 97th percentile. If your child's measurement falls significantly below the 3rd or above the 97th percentile, it warrants close medical supervision. Pediatricians use specialized tools and clinical judgment to interpret these extreme values.
Does fluid intake affect weight percentile?
Temporary fluctuations in weight can occur due to hydration levels. However, for percentile calculations, a child's weight should be measured under consistent conditions (e.g., after using the restroom, before a meal). Persistent issues with fluid balance or dehydration should be discussed with a doctor.

Related Tools and Internal Resources

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// Dummy data for growth charts and tables – replace with actual data if available var growthData = { male: { // Age in months: [3rd percentile weight (kg), 50th percentile weight (kg), 97th percentile weight (kg)] 0: [2.5, 3.5, 4.5], 1: [3.5, 5.0, 6.5], 2: [4.5, 6.0, 7.5], 3: [5.2, 6.8, 8.2], 4: [5.8, 7.3, 8.8], 5: [6.3, 7.8, 9.3], 6: [6.7, 8.2, 9.7], 7: [7.0, 8.5, 10.0], 8: [7.3, 8.8, 10.3], 9: [7.5, 9.0, 10.5], 10: [7.7, 9.2, 10.7], 11: [7.9, 9.4, 10.9], 12: [8.0, 9.5, 11.0], 18: [9.0, 10.5, 12.5], 24: [10.0, 11.5, 13.5], 36: [11.5, 13.0, 15.5], 48: [13.0, 14.5, 17.5], 60: [14.5, 16.0, 19.5], 72: [16.0, 18.0, 22.0], 84: [17.5, 20.0, 24.5], 96: [19.0, 22.0, 27.0], 108: [20.5, 24.0, 29.5], 120: [22.0, 26.0, 32.0], 132: [23.5, 28.0, 34.5], 144: [25.0, 30.0, 37.0], 156: [26.5, 32.0, 39.5], 168: [28.0, 34.0, 42.0], 180: [29.5, 36.0, 44.5], 192: [31.0, 38.0, 47.0], 204: [32.5, 40.0, 49.5], 216: [34.0, 42.0, 52.0], 228: [35.5, 44.0, 54.5], 240: [37.0, 46.0, 57.0] }, female: { // Age in months: [3rd percentile weight (kg), 50th percentile weight (kg), 97th percentile weight (kg)] 0: [2.3, 3.3, 4.3], 1: [3.3, 4.8, 6.3], 2: [4.2, 5.8, 7.2], 3: [4.9, 6.5, 7.9], 4: [5.5, 7.0, 8.4], 5: [6.0, 7.5, 8.9], 6: [6.4, 7.9, 9.3], 7: [6.7, 8.2, 9.6], 8: [7.0, 8.4, 9.8], 9: [7.2, 8.6, 10.0], 10: [7.4, 8.8, 10.2], 11: [7.6, 9.0, 10.4], 12: [7.7, 9.1, 10.5], 18: [8.6, 10.1, 12.0], 24: [9.5, 11.0, 13.0], 36: [11.0, 12.5, 15.0], 48: [12.5, 14.0, 17.0], 60: [14.0, 15.5, 19.0], 72: [15.5, 17.5, 21.5], 84: [17.0, 19.5, 24.0], 96: [18.5, 21.5, 26.5], 108: [20.0, 23.5, 29.0], 120: [21.5, 25.5, 31.5], 132: [23.0, 27.5, 34.0], 144: [24.5, 29.5, 36.5], 156: [26.0, 31.5, 39.0], 168: [27.5, 33.5, 41.5], 180: [29.0, 35.5, 44.0], 192: [30.5, 37.5, 46.5], 204: [32.0, 39.5, 49.0], 216: [33.5, 41.5, 51.5], 228: [35.0, 43.5, 54.0], 240: [36.5, 45.5, 56.5] } }; // Function to get percentile data based on age and sex function getPercentileData(ageMonths, sex) { var sexData = growthData[sex]; if (!sexData) return null; var ages = Object.keys(sexData).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 sexData[closestAge]; } // Function to calculate Z-score (simplified approximation) // This is a placeholder. Real calculation requires complex LMS parameters. function calculateZScore(weightKg, ageMonths, sex) { var percentileData = getPercentileData(ageMonths, sex); if (!percentileData) return null; var p3 = percentileData[0]; var p50 = percentileData[1]; var p97 = percentileData[2]; // Very rough approximation using linear interpolation between percentiles // A proper implementation would use LMS parameters (L, M, S) from WHO/CDC var weightAtAge = p50; // Median weight var sdApprox = (p97 – p3) / (2 * 1.96); // Approximate SD from 3rd and 97th percentiles if (sdApprox === 0) return 0; // Avoid division by zero var z = (weightKg – weightAtAge) / sdApprox; return z; } // Function to convert Z-score to percentile (simplified approximation) function zScoreToPercentile(zScore) { if (zScore === null || isNaN(zScore)) return "–"; // Using a simplified approximation of the standard normal CDF // For accurate results, a proper statistical function or lookup table is needed. var erf = function(x) { var sign = x < 0 ? -1 : 1; x = Math.abs(x); var a1 = 0.254829592; var a2 = -0.284496736; var a3 = 1.421413741; var a4 = -1.453152027; var a5 = 1.061405429; var p = 0.3275911; var t = 1.0 / (1.0 + p * x); var y = 1.0 – (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * Math.exp(-x * x); return sign * y; }; var cdf = 0.5 * (1 + erf(zScore / Math.sqrt(2))); return (cdf * 100).toFixed(1); } function calculatePercentile() { var age = parseFloat(document.getElementById("childAge").value); var weight = parseFloat(document.getElementById("childWeight").value); var sex = document.getElementById("childSex").value; var errors = false; document.getElementById("childAgeError").style.display = "none"; document.getElementById("childWeightError").style.display = "none"; document.getElementById("childSexError").style.display = "none"; // Though select usually doesn't error if (isNaN(age) || age <= 0) { document.getElementById("childAgeError").innerText = "Please enter a valid age in months (greater than 0)."; document.getElementById("childAgeError").style.display = "block"; errors = true; } if (isNaN(weight) || weight <= 0) { document.getElementById("childWeightError").innerText = "Please enter a valid weight in kg (greater than 0)."; document.getElementById("childWeightError").style.display = "block"; errors = true; } if (errors) { document.getElementById("results-container").style.display = "none"; return; } var percentileData = getPercentileData(age, sex); if (!percentileData) { document.getElementById("results-container").style.display = "none"; alert("Data not available for this age. Please check inputs or consult growth charts."); return; } var p3 = percentileData[0]; var p50 = percentileData[1]; var p97 = percentileData[2]; var zScore = calculateZScore(weight, age, sex); var percentile = zScoreToPercentile(zScore); var growthCurvePosition = "Unknown"; if (percentile !== "–") { var p = parseFloat(percentile); if (p = 3 && p = 50 && p 97) growthCurvePosition = "Above 97th Percentile"; } document.getElementById("primaryResult").innerText = percentile + "%"; document.getElementById("weightPercentile").innerText = percentile + "%"; document.getElementById("zScore").innerText = zScore !== null ? zScore.toFixed(2) : "–"; document.getElementById("growthCurvePosition").innerText = growthCurvePosition; document.getElementById("assumedAge").innerText = age; document.getElementById("assumedWeight").innerText = weight.toFixed(2); document.getElementById("assumedSex").innerText = sex.charAt(0).toUpperCase() + sex.slice(1); document.getElementById("results-container").style.display = "flex"; updateChart(age, weight, sex); populateGrowthTable(age, sex); } function resetCalculator() { document.getElementById("childAge").value = "24"; document.getElementById("childWeight").value = "12.5"; document.getElementById("childSex").value = "male"; document.getElementById("childAgeError").style.display = "none"; document.getElementById("childWeightError").style.display = "none"; document.getElementById("results-container").style.display = "none"; // Clear chart and table if needed, or just reset to default calculation calculatePercentile(); } function copyResults() { var primaryResult = document.getElementById("primaryResult").innerText; var weightPercentile = document.getElementById("weightPercentile").innerText; var zScore = document.getElementById("zScore").innerText; var growthCurvePosition = document.getElementById("growthCurvePosition").innerText; var assumedAge = document.getElementById("assumedAge").innerText; var assumedWeight = document.getElementById("assumedWeight").innerText; var assumedSex = document.getElementById("assumedSex").innerText; var resultsText = "Child Weight Percentile Calculation Results:\n\n"; resultsText += "Primary Result: " + primaryResult + "\n"; resultsText += "Weight Percentile: " + weightPercentile + "\n"; resultsText += "Z-Score: " + zScore + "\n"; resultsText += "Growth Curve Position: " + growthCurvePosition + "\n\n"; resultsText += "Key Assumptions:\n"; resultsText += "Age: " + assumedAge + " months\n"; resultsText += "Weight: " + assumedWeight + " kg\n"; resultsText += "Sex: " + assumedSex + "\n"; try { navigator.clipboard.writeText(resultsText).then(function() { alert("Results copied to clipboard!"); }).catch(function(err) { console.error("Failed to copy results: ", err); prompt("Copy these results manually:", resultsText); }); } catch (e) { console.error("Clipboard API not available: ", e); prompt("Copy these results manually:", resultsText); } } function populateGrowthTable(currentAge, currentSex) { var tableBody = document.getElementById("growthTableBody"); tableBody.innerHTML = ""; // Clear previous rows var agesToShow = [0, 6, 12, 18, 24, 36, 48, 60, 72, 84, 96, 120, 180, 240]; // Example ages var maleData = growthData.male; var femaleData = growthData.female; agesToShow.forEach(function(age) { var row = tableBody.insertRow(); var cellAge = row.insertCell(0); cellAge.innerText = age === 0 ? "Birth" : age + " months"; var maleP3 = maleData[age] ? maleData[age][0] : "–"; var maleP50 = maleData[age] ? maleData[age][1] : "–"; var maleP97 = maleData[age] ? maleData[age][2] : "–"; var femaleP3 = femaleData[age] ? femaleData[age][0] : "–"; var femaleP50 = femaleData[age] ? femaleData[age][1] : "–"; var femaleP97 = femaleData[age] ? femaleData[age][2] : "–"; var cellMale50 = row.insertCell(1); cellMale50.innerText = maleP50 !== "–" ? maleP50.toFixed(2) + " kg" : "–"; var cellFemale50 = row.insertCell(2); cellFemale50.innerText = femaleP50 !== "–" ? femaleP50.toFixed(2) + " kg" : "–"; var cellMale3 = row.insertCell(3); cellMale3.innerText = maleP3 !== "–" ? maleP3.toFixed(2) + " kg" : "–"; var cellMale97 = row.insertCell(4); cellMale97.innerText = maleP97 !== "–" ? maleP97.toFixed(2) + " kg" : "–"; }); } function updateChart(currentAge, currentWeight, currentSex) { var ctx = document.getElementById('growthChart').getContext('2d'); if (window.growthChartInstance) { window.growthChartInstance.destroy(); // Destroy previous chart instance } var chartData = { labels: [], // Ages datasets: [ { label: 'Your Child\'s Weight', data: [], // Child's weight points borderColor: 'rgb(40, 167, 69)', // Success color backgroundColor: 'rgba(40, 167, 69, 0.5)', fill: false, tension: 0.1, pointRadius: 5, pointHoverRadius: 7 }, { label: '50th Percentile (' + (currentSex === 'male' ? 'Male' : 'Female') + ')', data: [], // Median percentile data borderColor: 'rgb(0, 74, 153)', // Primary color backgroundColor: 'rgba(0, 74, 153, 0.2)', fill: false, tension: 0.1, pointRadius: 0 }, { label: '3rd Percentile', data: [], borderColor: 'rgba(255, 99, 132, 0.7)', // Red for lower bound backgroundColor: 'rgba(255, 99, 132, 0.1)', fill: '-1′, // Fill to the previous dataset (50th percentile) tension: 0.1, pointRadius: 0 }, { label: '97th Percentile', data: [], borderColor: 'rgba(54, 162, 235, 0.7)', // Blue for upper bound backgroundColor: 'rgba(54, 162, 235, 0.1)', fill: '+1', // Fill to the next dataset (3rd percentile) tension: 0.1, pointRadius: 0 } ] }; var ages = Object.keys(growthData[currentSex]).map(Number).sort(function(a, b){ return a – b; }); var maxAgeForChart = Math.max(currentAge, 240); // Show up to 20 years or current age, whichever is greater ages.forEach(function(age) { if (age <= maxAgeForChart) { chartData.labels.push(age === 0 ? "Birth" : age + "m"); var dataPoints = growthData[currentSex][age]; chartData.datasets[1].data.push(dataPoints[1]); // 50th percentile chartData.datasets[2].data.push(dataPoints[0]); // 3rd percentile chartData.datasets[3].data.push(dataPoints[2]); // 97th percentile } }); // Add the child's data point chartData.labels.push(currentAge + "m (Current)"); chartData.datasets[0].data.push(currentWeight); // Add placeholder nulls for other datasets at the child's age point for alignment chartData.datasets[1].data.push(null); chartData.datasets[2].data.push(null); chartData.datasets[3].data.push(null); window.growthChartInstance = new Chart(ctx, { type: 'line', data: chartData, options: { responsive: true, maintainAspectRatio: false, scales: { x: { title: { display: true, text: 'Age (Months)' } }, y: { title: { display: true, text: 'Weight (kg)' }, beginAtZero: true } }, plugins: { title: { display: true, text: 'Child Weight Growth Chart' }, tooltip: { mode: 'index', intersect: false } }, hover: { mode: 'nearest', intersect: true } } }); } // Initialize FAQ toggles document.addEventListener('DOMContentLoaded', function() { var faqItems = document.querySelectorAll('.faq-item .faq-question'); faqItems.forEach(function(item) { item.addEventListener('click', function() { var parent = this.parentElement; parent.classList.toggle('open'); }); }); // Initial calculation and table population on load populateGrowthTable(); calculatePercentile(); });

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