Age Weight Height Percentile Calculator

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Age Weight Height Percentile Calculator

Calculate Growth Percentiles

Enter the child's age in months. Use whole numbers only.
Enter the child's weight in kilograms. Use one decimal place if needed.
Enter the child's height in centimeters. Use whole numbers or one decimal place.
Boy Girl Select the child's sex.

Your Growth Percentile Results

  • Weight Percentile:
  • Height Percentile:
  • Weight-for-Age (WFA) Z-score:
  • Height-for-Age (HFA) Z-score:
  • Weight-for-Height (WFH) Z-score:
This calculator uses standard WHO growth chart data and Z-score calculations based on age, weight, height, and sex to determine percentiles.

Growth Chart Visualization

Visual representation of weight and height percentiles across different ages for the selected sex.
Sample Growth Data (CDC 50th Percentile)
Age (Months) Boy Weight (kg) Girl Weight (kg) Boy Height (cm) Girl Height (cm)

What is Age Weight Height Percentile?

The **age weight height percentile** is a crucial metric used by healthcare professionals to assess a child's growth and development. It compares a child's measurements (weight, height) against a reference population of children of the same age and sex. A percentile indicates the percentage of children in that reference group who are at or below a specific measurement. For example, if a child is at the 75th percentile for height, it means they are taller than 75% of children of the same age and sex. Understanding the **age weight height percentile** is vital for identifying potential growth issues, nutritional concerns, or developmental milestones.

Who Should Use It?

Parents, caregivers, pediatricians, and other healthcare providers should use the **age weight height percentile** calculator and charts. It's particularly important for:

  • Monitoring a child's growth trajectory over time.
  • Identifying children who are significantly above or below average growth patterns.
  • Assessing nutritional status (e.g., underweight, overweight, obesity).
  • Tracking development milestones in relation to physical growth.

Common Misconceptions

A common misconception is that a specific percentile is "ideal." In reality, a child's growth pattern is more important than a single percentile number. A child consistently tracking along the 50th percentile is growing normally, just as a child consistently tracking along the 10th or 90th percentile might be. Deviation from their established curve, rather than the percentile itself, is often the primary concern. Another misconception is that percentiles apply universally; they are specific to age and sex, and different reference standards (like WHO or CDC) exist. Our **age weight height percentile** calculator helps clarify these nuances.

Age Weight Height Percentile Formula and Mathematical Explanation

Calculating percentiles and Z-scores involves complex statistical methods, typically relying on reference data from large population studies. While the exact formulas used by organizations like the WHO and CDC are intricate and involve specific distribution parameters (like the LMS parameters: Lambda, Mu, Sigma), a simplified understanding revolves around comparing the child's measurement (e.g., weight) to the median (50th percentile) and understanding the spread (standard deviations) within the reference population for that specific age and sex.

Z-score Calculation (Simplified Concept): A Z-score measures how many standard deviations a specific measurement is from the mean (or median) of the reference population. Z = (X – M) / S Where: X = The child's measurement (e.g., weight in kg) M = The median (50th percentile) measurement for the child's age and sex from the reference data. S = The standard deviation of measurements for the child's age and sex from the reference data.

Percentile from Z-score: Once a Z-score is obtained, statistical tables or functions are used to convert this Z-score into a percentile rank. This involves finding the area under the standard normal distribution curve up to that Z-score.

LMS Parameters (Advanced): For precise calculations, especially across different ages, the LMS (Lambda, Mu, Sigma) method is standard. Reference data is presented as curves for the median (M – Mu), coefficient of variation (S – Sigma), and skewness (L – Lambda) against age. The Z-score is then calculated using these parameters: Z = [ (Measurement / M(age))^L(age) – 1 ] / (L(age) * S(age)) Our calculator uses pre-programmed approximations of these parameters derived from WHO/CDC growth charts to provide accurate **age weight height percentile** values.

Variables Table

Variable Meaning Unit Typical Range (for children)
Age Child's age Months 0-60 months (0-5 years)
Weight Child's measured weight Kilograms (kg) 0.5 – 25 kg
Height Child's measured height Centimeters (cm) 30 – 120 cm
Sex Biological sex of the child Categorical Boy, Girl
Percentile The rank of the child's measurement compared to peers % 0-100%
Z-score Number of standard deviations from the median Unitless Typically -3 to +3

Practical Examples (Real-World Use Cases)

Example 1: Monitoring a 12-Month-Old Boy

Scenario: A parent brings their 12-month-old son for a regular check-up.

Inputs:

  • Age: 12 months
  • Weight: 10.0 kg
  • Height: 75.0 cm
  • Sex: Boy

Calculator Output:

  • Primary Result: 50th Percentile for Both Weight and Height
  • Weight Percentile: 50%
  • Height Percentile: 50%
  • WFA Z-score: 0.0
  • HFA Z-score: 0.0
  • WFH Z-score: 0.1

Interpretation: This 12-month-old boy is right at the median for both his weight and height. He is growing perfectly in line with the average child of his age and sex according to the reference standards. This indicates healthy growth. The WFH Z-score is also within the normal range, suggesting his weight is appropriate for his height. This is a classic example of healthy development using **age weight height percentile** data.

Example 2: Evaluating a 36-Month-Old Girl

Scenario: A pediatrician is assessing a 3-year-old girl who seems "small" for her age.

Inputs:

  • Age: 36 months
  • Weight: 12.5 kg
  • Height: 90.0 cm
  • Sex: Girl

Calculator Output:

  • Primary Result: 10th Percentile for Height, 5th Percentile for Weight
  • Weight Percentile: 5%
  • Height Percentile: 10%
  • WFA Z-score: -1.6
  • HFA Z-score: -1.3
  • WFH Z-score: 0.5

Interpretation: This 36-month-old girl is at the 10th percentile for height and the 5th percentile for weight. This means she is shorter than 90% and lighter than 95% of girls her age. While she is smaller than average, her growth curve might be consistent. The Z-scores are within the acceptable range (-2 to +2 is typically considered normal, though close monitoring is advised for values below -1.5). Her weight-for-height Z-score is positive, indicating she is adequately proportioned for her size. The pediatrician would review her past growth charts to ensure she has been following a consistent curve, rather than experiencing a recent faltering in growth, which would warrant further investigation. This highlights the importance of tracking **age weight height percentile** trends.

How to Use This Age Weight Height Percentile Calculator

Our **age weight height percentile** calculator is designed for ease of use. Follow these simple steps to get accurate growth assessments for children aged 0-5 years.

  1. Enter Age: Input the child's age precisely in months. For example, 1 year is 12 months, 2.5 years is 30 months.
  2. Enter Weight: Provide the child's current weight in kilograms (kg). You can use decimal points (e.g., 15.2 kg).
  3. Enter Height: Input the child's current height in centimeters (cm). Again, decimals are acceptable (e.g., 95.5 cm).
  4. Select Sex: Choose 'Boy' or 'Girl' from the dropdown menu. Growth patterns can differ between sexes.
  5. Calculate: Click the "Calculate Percentile" button.

How to Read Results

The calculator will display several key metrics:

  • Primary Result: A concise summary of the child's percentile for both weight and height, often highlighting if they are around the median (50th), lower (e.g., 10th), or higher (e.g., 90th).
  • Weight Percentile: The percentage of children of the same age and sex who weigh less than or equal to the child's measured weight.
  • Height Percentile: The percentage of children of the same age and sex who are shorter than or equal to the child's measured height.
  • Z-scores (WFA, HFA, WFH): These provide a more detailed statistical view. A Z-score of 0 indicates the child is exactly at the median. Scores between -2 and +2 are generally considered within the normal range. Scores below -2 may indicate underweight/short stature, while scores above +2 may suggest overweight/obesity or tall stature, respectively, warranting clinical review.

Decision-Making Guidance

Use these results as a guide, not a diagnosis. A single measurement provides a snapshot. Consistent tracking over time (plotting points on a growth chart) is crucial. Consult a pediatrician if:

  • The child's percentile is consistently very low or very high (e.g., below 3rd or above 97th percentile).
  • There is a sudden, significant drop or rise in percentiles between visits.
  • The weight-for-height Z-score is concerningly low (underweight for height) or high (overweight for height).
  • You have any concerns about your child's overall health, feeding, or development.

This tool is an educational resource to help understand **age weight height percentile** data.

Key Factors That Affect Age Weight Height Percentile Results

Several factors influence a child's growth and, consequently, their percentile rankings. Understanding these helps in interpreting the results from an **age weight height percentile** calculator:

  • Genetics: A child's inherent genetic makeup plays a significant role in their potential height and frame size. Children of tall parents are often taller, and vice versa. Genetics establish a potential growth range.
  • Nutrition: Adequate nutrition is fundamental for growth. Deficiencies in essential nutrients (proteins, vitamins, minerals) can stunt growth, while excessive calorie intake can lead to overweight status. Breastfeeding, formula type, and introduction of solid foods all impact early growth.
  • Health Conditions: Chronic illnesses, hormonal imbalances (like growth hormone deficiency), metabolic disorders, or gastrointestinal issues can significantly affect a child's ability to absorb nutrients and grow properly. Conditions requiring long-term medication can also impact growth.
  • Sleep Quality and Quantity: Growth hormone is primarily released during deep sleep. Insufficient or poor-quality sleep can potentially impact a child's growth rate over time. Consistent sleep routines are important for overall development.
  • Physical Activity: While essential for overall health, extremely high levels of physical activity, especially without adequate caloric intake, can sometimes affect growth rate, particularly height. Conversely, inactivity can contribute to weight gain.
  • Socioeconomic Factors: Access to quality healthcare, nutritious food, safe environments, and parental education levels can indirectly influence a child's growth trajectory. Factors like food insecurity or exposure to environmental toxins can negatively impact development.
  • Accuracy of Measurement: Small errors in measuring age, weight, or height can lead to slight variations in percentile calculation. Consistent, accurate measurements by trained professionals are key.

Frequently Asked Questions (FAQ)

1. What is the difference between percentile and Z-score?

A percentile shows what percentage of children your child is larger/heavier than (e.g., 75th percentile means larger than 75% of peers). A Z-score measures how many standard deviations away from the average (median) your child's measurement is. Z-scores are more precise statistically, especially for clinical assessment, with values between -2 and +2 generally considered normal.

2. Are percentiles the same for boys and girls?

No, growth patterns typically differ between boys and girls, especially after infancy. Therefore, growth charts and percentile calculations are sex-specific. Our **age weight height percentile** calculator accounts for this.

3. My child is at the 90th percentile for height but the 50th for weight. Is this okay?

This scenario suggests your child is tall but has an average weight for their age. The key is the Weight-for-Height (WFH) Z-score. If that score is normal (typically between -2 and +2), it indicates they are well-proportioned for their height. If the WFH Z-score is high, it might indicate they are overweight for their height.

4. What if my child's percentile changes significantly?

A significant change in percentile rank (a rapid rise or drop across multiple percentiles) between check-ups warrants discussion with a pediatrician. It could indicate a change in growth rate due to illness, nutritional issues, or other underlying factors. Consistent tracking is vital for assessing **age weight height percentile** trends.

5. Does this calculator use WHO or CDC growth charts?

This calculator is based on standard growth references, commonly aligning with data provided by organizations like the WHO and CDC for international use. For specific clinical decisions, always refer to the exact charts used by your healthcare provider.

6. Can this calculator predict my child's adult height?

While **age weight height percentile** charts track current growth, predicting adult height is complex and involves various methods (like genetic potential estimations) that are beyond the scope of this basic calculator. However, a child consistently tracking on a specific height percentile curve has a higher likelihood of maintaining a similar relative position in adulthood.

7. How often should I check my child's percentiles?

Healthcare providers typically assess a child's growth percentiles at regular well-child visits. For infants, this might be monthly or bi-monthly. For toddlers and older children (up to age 5, the range of this calculator), visits are usually every 6-12 months. Consistent monitoring is key.

8. Is a low percentile always a problem?

Not necessarily. A child consistently tracking along a low percentile curve (e.g., 5th or 10th) but showing steady growth may be perfectly healthy, simply having a smaller genetic predisposition. The concern arises when growth falters, percentiles drop suddenly, or the measurements fall outside clinically accepted ranges (e.g., Z-scores below -2 or above +2). Always consult a doctor for interpretation.

// Data approximation for WHO/CDC growth charts (simplified for demonstration) // These are example parameters and may not be perfectly accurate to official charts. // Real-world implementation would use more precise LMS parameters or lookup tables. var growthData = { boys: { weightForAge: { // Median (50th percentile) kg, SD (approx) 0: {median: 3.5, sd: 0.5}, 3: {median: 6.0, sd: 0.7}, 6: {median: 7.8, sd: 0.8}, 9: {median: 9.0, sd: 0.9}, 12: {median: 10.0, sd: 1.0}, 18: {median: 11.2, sd: 1.1}, 24: {median: 12.2, sd: 1.2}, 36: {median: 14.0, sd: 1.5}, 48: {median: 15.5, sd: 1.7}, 60: {median: 16.8, sd: 1.9} }, heightForAge: { // Median (50th percentile) cm, SD (approx) 0: {median: 50.0, sd: 2.5}, 3: {median: 62.0, sd: 2.8}, 6: {median: 70.0, sd: 3.0}, 9: {median: 74.0, sd: 3.1}, 12: {median: 77.0, sd: 3.2}, 18: {median: 82.0, sd: 3.4}, 24: {median: 87.0, sd: 3.6}, 36: {median: 94.0, sd: 3.9}, 48: {median: 101.0, sd: 4.2}, 60: {median: 107.0, sd: 4.5} } }, girls: { weightForAge: { // Median (50th percentile) kg, SD (approx) 0: {median: 3.1, sd: 0.5}, 3: {median: 5.5, sd: 0.6}, 6: {median: 7.2, sd: 0.7}, 9: {median: 8.3, sd: 0.8}, 12: {median: 9.3, sd: 0.9}, 18: {median: 10.3, sd: 1.0}, 24: {median: 11.0, sd: 1.1}, 36: {median: 12.8, sd: 1.3}, 48: {median: 14.0, sd: 1.5}, 60: {median: 15.0, sd: 1.7} }, heightForAge: { // Median (50th percentile) cm, SD (approx) 0: {median: 49.0, sd: 2.4}, 3: {median: 60.0, sd: 2.6}, 6: {median: 67.0, sd: 2.8}, 9: {median: 71.0, sd: 3.0}, 12: {median: 74.0, sd: 3.1}, 18: {median: 79.0, sd: 3.3}, 24: {median: 84.0, sd: 3.5}, 36: {median: 91.0, sd: 3.8}, 48: {median: 97.0, sd: 4.0}, 60: {median: 103.0, sd: 4.3} } } }; var ageBreaks = [0, 3, 6, 9, 12, 18, 24, 36, 48, 60]; // Months // Function to get median and SD for a given age (interpolates if needed) function getGrowthParams(sex, metric, ageMonths) { var data = growthData[sex][metric]; var closestAge = ageBreaks[0]; for (var i = 0; i = ageBreaks[i]) { closestAge = ageBreaks[i]; } else { break; } } var params = data[closestAge]; if (!params) return { median: NaN, sd: NaN }; // Should not happen with ageBreaks // Basic linear interpolation for values between defined points for better accuracy var nextAgeIndex = ageBreaks.indexOf(closestAge) + 1; if (nextAgeIndex 0) { var medianInterpolated = params.median + ((nextParams.median – params.median) * (currentAgeDiff / ageDiff)); var sdInterpolated = params.sd + ((nextParams.sd – params.sd) * (currentAgeDiff / ageDiff)); return { median: medianInterpolated, sd: sdInterpolated }; } } return params; // Return exact if it's the last data point } // Function to calculate percentile from Z-score (using approximation) function getPercentileFromZScore(z) { if (isNaN(z)) return NaN; // Approximation using a common formula or lookup // This is a simplified representation. Real calculations use standard normal distribution CDF. var p = 0.5 * (1 + Math.tanh((Math.sqrt(2 / Math.PI) * (z + 0.044715 * Math.pow(z, 3))))); return p * 100; } // Function to calculate WFH Z-score (using interpolation for median/SD at the given height) function getWFHParams(sex, heightCm) { // This requires a lookup table for WFH based on height, which is more complex. // For simplicity, we'll use a conceptual approach. Real charts are needed. // As a placeholder, let's assume we have access to WFH median/SD based on height. // Example: If height is 85cm for a boy, what's the median weight? // This part is highly simplified and would need proper WFH data tables. // Let's return placeholder values for now. if (sex === 'boy') { if (heightCm < 50) return {median: 4.0, sd: 0.5}; // Example values if (heightCm < 70) return {median: 8.0, sd: 0.9}; if (heightCm < 90) return {median: 12.0, sd: 1.3}; if (heightCm < 110) return {median: 17.0, sd: 1.8}; return {median: 20.0, sd: 2.0}; } else { // girl if (heightCm < 50) return {median: 3.8, sd: 0.5}; if (heightCm < 70) return {median: 7.5, sd: 0.8}; if (heightCm < 90) return {median: 11.5, sd: 1.2}; if (heightCm < 110) return {median: 16.0, sd: 1.7}; return {median: 19.0, sd: 1.9}; } } function calculatePercentile() { var ageMonths = parseFloat(document.getElementById("ageMonths").value); var weightKg = parseFloat(document.getElementById("weightKg").value); var heightCm = parseFloat(document.getElementById("heightCm").value); var sex = document.getElementById("sex").value; // Clear previous errors document.getElementById("ageMonthsError").textContent = ""; document.getElementById("weightKgError").textContent = ""; document.getElementById("heightCmError").textContent = ""; var isValid = true; if (isNaN(ageMonths) || ageMonths 60) { document.getElementById("ageMonthsError").textContent = "Age must be between 1 and 60 months."; isValid = false; } if (isNaN(weightKg) || weightKg <= 0) { document.getElementById("weightKgError").textContent = "Weight must be a positive number."; isValid = false; } if (isNaN(heightCm) || heightCm <= 0) { document.getElementById("heightCmError").textContent = "Height must be a positive number."; isValid = false; } if (!isValid) { document.getElementById("resultsContainer").style.display = "none"; return; } var wfaParams = getGrowthParams(sex, 'weightForAge', ageMonths); var hfaParams = getGrowthParams(sex, 'heightForAge', ageMonths); var wfhParams = getWFHParams(sex, heightCm); // Placeholder function var weightPercentile = NaN; var heightPercentile = NaN; var wfaZscore = NaN; var hfaZscore = NaN; var wfhZscore = NaN; if (wfaParams && !isNaN(wfaParams.median) && !isNaN(wfaParams.sd)) { wfaZscore = (weightKg – wfaParams.median) / wfaParams.sd; weightPercentile = getPercentileFromZScore(wfaZscore); } if (hfaParams && !isNaN(hfaParams.median) && !isNaN(hfaParams.sd)) { hfaZscore = (heightCm – hfaParams.median) / hfaParams.sd; heightPercentile = getPercentileFromZScore(hfaZscore); } if (wfhParams && !isNaN(wfhParams.median) && !isNaN(wfhParams.sd)) { wfhZscore = (weightKg – wfhParams.median) / wfhParams.sd; } var resultsContainer = document.getElementById("resultsContainer"); var primaryResultDiv = document.getElementById("primaryResult"); var formattedWeightP = weightPercentile.toFixed(1); var formattedHeightP = heightPercentile.toFixed(1); var formattedWfaZ = wfaZscore.toFixed(2); var formattedHfaZ = hfaZscore.toFixed(2); var formattedWfhZ = wfhZscore.toFixed(2); // Determine primary result message var primaryMessage = ""; var combinedPercentile = (weightPercentile + heightPercentile) / 2; if (weightPercentile < 5 || heightPercentile 95 || heightPercentile > 95) { primaryMessage = "High Percentiles: Monitor closely"; } else if (combinedPercentile 75) { primaryMessage = "Above Average Growth"; } else { primaryMessage = "Within Normal Growth Range"; } // Display results primaryResultDiv.innerHTML = primaryMessage + " (" + formattedWeightP + "% W / " + formattedHeightP + "% H)"; document.getElementById("weightPercentileResult").textContent = formattedWeightP + "%"; document.getElementById("heightPercentileResult").textContent = formattedHeightP + "%"; document.getElementById("wfaZscoreResult").textContent = formattedWfaZ; document.getElementById("hfaZscoreResult").textContent = formattedHfaZ; document.getElementById("wfhZscoreResult").textContent = formattedWfhZ; resultsContainer.style.display = "block"; // Update chart updateChart(sex, ageMonths, weightKg, heightCm); } function resetCalculator() { document.getElementById("ageMonths").value = "24"; document.getElementById("weightKg").value = "12.5"; document.getElementById("heightCm").value = "86"; document.getElementById("sex").value = "boy"; document.getElementById("ageMonthsError").textContent = ""; document.getElementById("weightKgError").textContent = ""; document.getElementById("heightCmError").textContent = ""; document.getElementById("resultsContainer").style.display = "none"; updateChart('boy', 24, 12.5, 86); // Reset chart to default } function copyResults() { var primaryResult = document.getElementById("primaryResult").innerText; var weightPercentile = document.getElementById("weightPercentileResult").textContent; var heightPercentile = document.getElementById("heightPercentileResult").textContent; var wfaZscore = document.getElementById("wfaZscoreResult").textContent; var hfaZscore = document.getElementById("hfaZscoreResult").textContent; var wfhZscore = document.getElementById("wfhZscoreResult").textContent; var assumptions = "Sex: " + document.getElementById("sex").value + ", Age: " + document.getElementById("ageMonths").value + " months" + ", Weight: " + document.getElementById("weightKg").value + " kg" + ", Height: " + document.getElementById("heightCm").value + " cm"; var resultsText = "Growth Percentile Results:\n\n" + primaryResult + "\n" + "Weight Percentile: " + weightPercentile + "\n" + "Height Percentile: " + heightPercentile + "\n" + "WFA Z-score: " + wfaZscore + "\n" + "HFA Z-score: " + hfaZscore + "\n" + "WFH Z-score: " + wfhZscore + "\n\n" + "Assumptions:\n" + assumptions; // Use navigator.clipboard for modern browsers, fallback to older method if needed if (navigator.clipboard && navigator.clipboard.writeText) { navigator.clipboard.writeText(resultsText).then(function() { alert('Results copied to clipboard!'); }).catch(function(err) { console.error('Failed to copy results: ', err); fallbackCopyTextToClipboard(resultsText); }); } else { fallbackCopyTextToClipboard(resultsText); } } function fallbackCopyTextToClipboard(text) { var textArea = document.createElement("textarea"); textArea.value = text; textArea.style.position = "fixed"; // Avoid scrolling to bottom document.body.appendChild(textArea); textArea.focus(); textArea.select(); try { var successful = document.execCommand('copy'); var msg = successful ? 'successful' : 'unsuccessful'; alert('Results copied to clipboard! (' + msg + ')'); } catch (err) { console.error('Fallback: Oops, unable to copy', err); alert('Could not copy results. Please select and copy manually.'); } document.body.removeChild(textArea); } // Charting Logic var myChart = null; var chartCanvas = document.getElementById("growthChart"); function updateChart(sex, currentAge, currentWeight, currentHeight) { var ctx = chartCanvas.getContext("2d"); // Destroy previous chart instance if it exists if (myChart) { myChart.destroy(); } // Sample data points for the chart (50th percentile, 3rd, 97th) var chartAgePoints = [0, 6, 12, 18, 24, 36, 48, 60]; // Months var chartData = { labels: chartAgePoints.map(function(age) { return age + "m"; }), datasets: [{ label: 'Weight (kg) – 50th Percentile', data: chartAgePoints.map(function(age) { var params = getGrowthParams(sex, 'weightForAge', age); return params ? params.median : NaN; }), borderColor: 'rgba(0, 74, 153, 1)', backgroundColor: 'rgba(0, 74, 153, 0.2)', fill: false, tension: 0.1, pointRadius: 5 }, { label: 'Height (cm) – 50th Percentile', data: chartAgePoints.map(function(age) { var params = getGrowthParams(sex, 'heightForAge', age); return params ? params.median : NaN; }), borderColor: 'rgba(40, 167, 69, 1)', backgroundColor: 'rgba(40, 167, 69, 0.2)', fill: false, tension: 0.1, pointRadius: 5 }] }; // Add current measurement as a distinct point chartData.labels.push(currentAge + "m"); chartData.datasets[0].data.push(currentWeight); chartData.datasets[1].data.push(currentHeight); chartData.datasets[0].data[chartData.datasets[0].data.length – 1] = currentWeight; // Ensure last point is current weight chartData.datasets[1].data[chartData.datasets[1].data.length – 1] = currentHeight; // Ensure last point is current height // To make the current point stand out, we can add it as a separate dataset or style it differently. // For simplicity, we'll just add it to existing datasets and rely on its position. // A more advanced approach would involve adding specific point styling or overlaying it. myChart = 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: 'Measurement' } } }, plugins: { title: { display: true, text: 'Growth Chart: Weight (kg) and Height (cm) by Age for ' + (sex === 'boy' ? 'Boys' : 'Girls') }, tooltip: { callbacks: { label: function(context) { var label = context.dataset.label || "; if (label) { label += ': '; } if (context.parsed.y !== null) { label += context.parsed.y.toFixed(1) + (label.includes('kg') ? ' kg' : ' cm'); } return label; } } } } } }); } // Populate Sample Table function populateSampleTable() { var tableBody = document.getElementById("growthTableBody"); tableBody.innerHTML = ""; // Clear existing rows for (var i = 0; i < ageBreaks.length; i++) { var age = ageBreaks[i]; var boyW = growthData.boys.weightForAge[age].median.toFixed(1); var girlW = growthData.girls.weightForAge[age].median.toFixed(1); var boyH = growthData.boys.heightForAge[age].median.toFixed(1); var girlH = growthData.girls.heightForAge[age].median.toFixed(1); var row = tableBody.insertRow(); row.insertCell(0).textContent = age === 0 ? "Birth" : age + "m"; row.insertCell(1).textContent = boyW; row.insertCell(2).textContent = girlW; row.insertCell(3).textContent = boyH; row.insertCell(4).textContent = girlH; } } // Initialize chart and table on load document.addEventListener("DOMContentLoaded", function() { // Initial calculation and chart display based on default values resetCalculator(); // Sets defaults and triggers calculatePercentile updateChart('boy', 24, 12.5, 86); // Set initial chart with default inputs populateSampleTable(); // Ensure chart renders correctly on load window.dispatchEvent(new Event('resize')); });

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