Cdc Weight Percentile Calculator Infant

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CDC Infant Weight Percentile Calculator

Determine your baby's weight percentile using CDC growth charts.

Infant Weight Percentile Calculator

Enter the baby's age in days (0 to 36 months or 1095 days).
Enter the baby's weight in kilograms (kg).
Boy Girl Select the baby's sex.
Weight Percentile
Z-Score: —
Median Weight (50th Percentile): —
3rd Percentile Weight: —
97th Percentile Weight: —
The percentile indicates the baby's weight relative to other babies of the same age and sex. A Z-score is a statistical measure of how many standard deviations a baby's weight is from the median weight for their age and sex. This calculator uses generalized WHO/CDC growth charts data points to estimate these values.

Growth Chart Visualization

This chart shows your baby's weight percentile relative to the CDC growth curve.

CDC Growth Chart Data Points (Example for Boys)
Age (Days) 3rd %ile (kg) 50th %ile (kg) 97th %ile (kg)

What is the CDC Infant Weight Percentile Calculator?

The CDC infant weight percentile calculator is a specialized tool designed to help parents, caregivers, and healthcare professionals assess a baby's weight in relation to established growth standards. It utilizes data from the Centers for Disease Control and Prevention (CDC) growth charts, which are the standard for monitoring child development in the United States. This calculator specifically focuses on the weight-for-age percentile for infants from birth up to 36 months (3 years) of age, differentiating between boys and girls due to inherent biological differences in growth patterns. The primary purpose is to provide a standardized measure of how a baby's weight compares to a reference population of healthy infants of the same age and sex.

Who should use it? Parents and guardians concerned about their baby's feeding, growth, or overall health are primary users. Pediatricians, nurses, and other healthcare providers use these percentiles routinely during well-child visits to track growth trajectories and identify potential concerns. It's also useful for researchers studying child development and nutrition.

Common misconceptions: A common misunderstanding is that a specific percentile (like 50th) is inherently "best." In reality, a healthy growth pattern can be represented by various percentiles, as long as the baby is consistently following a particular curve and gaining weight appropriately for their age. Another misconception is that a percentile is a diagnosis; it's merely a comparative measure that, when viewed alongside other health indicators, helps paint a picture of the baby's well-being.

CDC Infant Weight Percentile Calculator Formula and Mathematical Explanation

The CDC infant weight percentile calculator doesn't rely on a single, simple formula like a BMI calculation. Instead, it interpolates data from complex statistical models derived from extensive population studies. The core concept is to determine where a baby's specific weight falls on the **WHO/CDC weight-for-age growth charts** for their age and sex.

Key Concepts:

  • Weight-for-Age Percentiles: These represent the percentage of babies in the reference population who weigh the same or less than the baby being measured. For example, the 75th percentile means the baby weighs the same or less than 75% of babies of the same age and sex.
  • Median (50th Percentile): This is the midpoint – half of the babies weigh less, and half weigh more.
  • Z-Score: A more precise statistical measure. It indicates how many standard deviations a baby's weight is away from the median. A Z-score of 0 is the median. A positive Z-score means the baby is heavier than the median; a negative Z-score means they are lighter. Z-scores are particularly useful for tracking growth over time and comparing growth across different age ranges. The formula for a Z-score is: (Observed Value – Median Value) / Standard Deviation.

How the Calculator Works (Behind the Scenes):

The calculator typically uses lookup tables or algorithms that approximate the values from the official CDC growth charts. For a given age (in days) and sex, the calculator identifies the corresponding median weight, standard deviation, and potentially other percentile values (like 3rd and 97th) from its internal data. It then calculates the Z-score for the baby's actual weight.

Simplified Calculation Logic (Conceptual):

  1. Input: Baby's Age (days), Weight (kg), Sex.
  2. Data Lookup: Based on age and sex, find the corresponding reference data (Median Weight (M), Z-score for the 3rd percentile (Z3), Z-score for the 97th percentile (Z97), and potentially standard deviations (SD) or specific percentile weights). Note: Different chart versions might use slightly different parameters. The calculator likely has pre-defined sets of (M, SD) values for various ages, or directly provides percentile weights.
  3. Z-Score Calculation: If SD is available: Z = (Baby's Weight – M) / SD. If direct percentile weights are used, the calculator might interpolate to find the Z-score or directly calculate the percentile based on the position relative to these points.
  4. Percentile Determination: Using the calculated Z-score and a standard normal distribution table (or approximation), the calculator finds the corresponding percentile. For example, a Z-score of -1.645 corresponds to roughly the 5th percentile, 0 corresponds to the 50th, and +1.645 corresponds to the 95th. The calculator maps the input weight to one of the standard CDC percentiles (e.g., 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, 97th).
  5. Output: Display the calculated percentile, Z-score, and relevant reference weights (e.g., 3rd, 50th, 97th percentile weights for comparison).

Variables Table:

Variables Used in Percentile Calculation
Variable Meaning Unit Typical Range
Age (Days) Infant's age from birth. Days 0 – 1095 (0 to 36 months)
Weight (kg) Infant's measured weight. Kilograms (kg) 0.5 – 25.0 (approximate range for 0-36 months)
Sex Biological sex of the infant. Categorical (Boy/Girl) Boy, Girl
Median Weight (M) The weight at the 50th percentile for the given age and sex. Kilograms (kg) Varies with age and sex
Standard Deviation (SD) A measure of the spread or dispersion of weights around the median. Kilograms (kg) Varies with age and sex
Z-Score Number of standard deviations the infant's weight is from the median. Unitless -3 to +3 (typically)
Percentile The baby's weight rank compared to others of the same age and sex. Percentage (%) 0 – 100

Practical Examples (Real-World Use Cases)

Example 1: Tracking a Healthy Growth Trajectory

Scenario: Sarah is a 6-month-old baby girl who is exclusively breastfed. Her parents are keen to ensure she is growing well. During her 6-month check-up, the pediatrician measures her weight.

Inputs:

  • Baby's Age: 6 months = 6 * 30.44 days ≈ 183 days
  • Baby's Weight: 7.8 kg
  • Baby's Sex: Girl

Calculator Output (Illustrative):

  • Primary Result: 65th Percentile
  • Z-Score: 0.39
  • Median Weight (50th Percentile): 7.5 kg
  • 3rd Percentile Weight: 6.2 kg
  • 97th Percentile Weight: 9.1 kg

Interpretation: Sarah's weight of 7.8 kg places her at the 65th percentile for a 6-month-old girl. This means she weighs the same or less than 65% of 6-month-old girls in the reference population. Her Z-score of 0.39 indicates she is slightly above the median weight. The pediatrician notes that Sarah's growth has been consistent, following a curve around this percentile range since birth. This is considered a healthy growth pattern, indicating adequate nutrition and development. The pediatrician might reassure the parents that as long as Sarah is gaining weight consistently and meeting developmental milestones, this percentile is perfectly healthy.

Example 2: Assessing Potential Concerns for Lower Weight Gain

Scenario: David is a 9-month-old baby boy. His parents have noticed he seems smaller than other babies his age and is having trouble finishing his bottles. They use the calculator before their doctor's appointment.

Inputs:

  • Baby's Age: 9 months = 9 * 30.44 days ≈ 274 days
  • Baby's Weight: 7.2 kg
  • Baby's Sex: Boy

Calculator Output (Illustrative):

  • Primary Result: 10th Percentile
  • Z-Score: -1.28
  • Median Weight (50th Percentile): 8.8 kg
  • 3rd Percentile Weight: 6.8 kg
  • 97th Percentile Weight: 10.5 kg

Interpretation: David's weight of 7.2 kg puts him at the 10th percentile for a 9-month-old boy. This means 10% of 9-month-old boys weigh this much or less. His Z-score of -1.28 indicates his weight is more than one standard deviation below the median. While still within the "normal" range (typically considered between the 3rd and 97th percentiles), his position on the lower end and the parents' observations prompt a closer look. The pediatrician will investigate potential causes such as feeding issues, absorption problems, or underlying medical conditions. They will review his growth trend over previous months. If his weight gain has slowed significantly or dropped across percentiles, further medical evaluation would be recommended. This calculator result serves as an important data point for the clinical assessment, highlighting a need for closer monitoring and potential intervention.

How to Use This CDC Infant Weight Percentile Calculator

Using the CDC infant weight percentile calculator is straightforward and can provide valuable insights into your baby's growth. Follow these simple steps:

Step-by-Step Instructions:

  1. Gather Information: You will need your baby's exact age in days and their current weight in kilograms. Ensure the weight measurement is accurate and taken using calibrated scales.
  2. Enter Baby's Age: Input the number of days since your baby was born into the "Baby's Age (Days)" field. If you know the age in months, you can approximate (e.g., 6 months ≈ 183 days). For best accuracy, use the precise number of days.
  3. Enter Baby's Weight: Input your baby's weight in kilograms (kg) into the "Baby's Weight (Kilograms)" field.
  4. Select Baby's Sex: Choose "Boy" or "Girl" from the dropdown menu. This is crucial as growth charts differ significantly between sexes.
  5. Calculate: Click the "Calculate Percentile" button.
  6. View Results: The calculator will immediately display the primary result – your baby's weight percentile. It will also show the corresponding Z-score, the median weight (50th percentile), and the weights for the 3rd and 97th percentiles for comparison.
  7. Analyze the Chart and Table: Review the generated growth chart visualization and the data table. The chart provides a visual representation of your baby's position relative to the CDC growth curves. The table offers specific data points for reference.
  8. Reset (If Needed): If you want to perform a new calculation or correct an entry, click the "Reset Defaults" button to return the fields to their initial states.
  9. Copy Results: Use the "Copy Results" button to copy all calculated data to your clipboard, which can be useful for sharing with your pediatrician or for your personal records.

How to Read Results:

  • Percentile: This is the main indicator. A higher percentile means the baby weighs more relative to peers; a lower percentile means they weigh less. Remember, a consistent percentile is often more important than the absolute number.
  • Z-Score: This provides statistical context. A Z-score of 0 is average. Scores significantly above or below 0 (e.g., +/- 2 or 3) may warrant closer attention.
  • Median, 3rd, and 97th Percentiles: These values act as benchmarks. The 3rd and 97th percentiles represent the typical lower and upper bounds of healthy growth according to the CDC. Your baby's position relative to these markers is informative.

Decision-Making Guidance:

The calculator is a tool, not a diagnosis. Always discuss the results with your pediatrician. They will consider the percentile in the context of your baby's overall health, feeding patterns, developmental milestones, and growth *trend* over time. A single measurement is less important than the pattern observed across multiple visits. If your baby is consistently above the 97th percentile or below the 3rd percentile, or if their percentile is rapidly changing, consult your doctor.

Key Factors That Affect Infant Weight Percentile Results

While the calculator provides a precise percentile based on age, weight, and sex, several real-world factors influence these measurements and their interpretation:

  1. Accuracy of Measurement: This is paramount. Inaccurate scales or incorrect weighing procedures (e.g., not accounting for clothing weight) can lead to skewed results. Ensure weight is measured consistently, preferably by a healthcare professional.
  2. Feeding Practices: The type of milk (breast milk, formula), frequency of feeding, and volume consumed directly impact weight gain. Exclusively breastfed babies may follow slightly different growth curves initially compared to formula-fed babies, though the CDC charts are designed to encompass both.
  3. Prematurity: For babies born prematurely, growth is often assessed using specialized corrected age charts. Using a standard age calculator for a preemie without correction can lead to misleading percentile results. Consult your pediatrician about corrected age.
  4. Illness and Health Conditions: Acute illnesses (like gastroenteritis) can cause temporary weight loss or slowed gain, affecting the percentile. Chronic health conditions, genetic disorders, or metabolic issues can permanently influence growth patterns.
  5. Hydration Levels: Significant dehydration (e.g., from vomiting or diarrhea) can temporarily lower weight, impacting the percentile. Conversely, fluid retention could artificially inflate it.
  6. Genetics and Body Type: While CDC charts represent a population average, individual babies inherit genetic predispositions for body size and frame. Some babies are naturally larger or smaller than the "average" but still follow a healthy, consistent growth path within their genetic potential.
  7. Sleep Patterns and Activity Level: While less direct, factors influencing calorie intake and expenditure can subtly affect weight gain trends over longer periods.
  8. Medications: Certain medications can affect appetite or metabolism, potentially influencing weight gain and, consequently, the percentile.

Understanding these factors helps contextualize the percentile result provided by the calculator, emphasizing the need for professional medical interpretation.

Frequently Asked Questions (FAQ)

Q1: What does a 50th percentile weight mean for my infant?

A: It means your baby's weight is exactly average compared to other babies of the same age and sex. Half of the babies in the reference group weigh less, and half weigh more. This is a healthy position.

Q2: Is it bad if my baby is below the 10th percentile?

A: Not necessarily. Being below the 10th percentile simply means your baby weighs less than 90% of babies their age and sex. The key is whether they are following a consistent growth curve and meeting developmental milestones. A sudden drop in percentile or consistent failure to gain weight warrants a discussion with a pediatrician.

Q3: My baby is consistently above the 90th percentile. Should I be worried?

A: Similar to being on the lower end, consistency is key. If your baby has always been in the higher percentiles and is growing steadily, it might just be their natural growth pattern. However, rapid weight gain or consistently exceeding the 97th percentile may warrant a pediatrician's evaluation to rule out potential issues like overfeeding or underlying metabolic conditions.

Q4: How often should I use this calculator?

A: This calculator is best used periodically, especially around well-child visits, or if you have specific concerns about your baby's intake or weight gain. It's not meant for daily tracking. Your pediatrician will use official measurements during check-ups.

Q5: Does the calculator account for premature babies?

A: The standard CDC charts, and thus this calculator based on them, are primarily designed for full-term infants. For premature babies, it's crucial to use corrected age and potentially specialized growth charts recommended by your neonatologist or pediatrician.

Q6: What's the difference between weight percentile and BMI percentile for infants?

A: For infants under 2 years old, the CDC primarily uses weight-for-age, length-for-age, and head circumference-for-age charts. BMI-for-age charts become the standard from age 2 upwards. This calculator focuses on weight-for-age.

Q7: Can this calculator predict my baby's adult weight?

A: No, infant growth percentiles are not a reliable predictor of adult weight. Children's growth patterns can change significantly throughout development. Focusing on healthy, consistent growth during infancy is the primary goal.

Q8: My baby's weight seems off today, but I know they are probably just a bit dehydrated. Should I still use the calculator?

A: If you suspect temporary factors like dehydration are affecting the weight, it's best to wait until your baby is properly rehydrated for an accurate measurement. Using the calculator with skewed data can lead to unnecessary worry or misinterpretation.

© 2023 Your Website Name. All rights reserved. This calculator is for informational purposes only and does not constitute medical advice. Consult with a qualified healthcare provider for any health concerns.

var growthChartInstance = null; function getGrowthChartData(sex) { // Simplified representative data points (actual CDC data is much more granular) // These are illustrative values for demonstration. // For a real implementation, extensive data or an API lookup would be needed. if (sex === 0) { // Boy return [ { days: 0, median: 3.3, sd: 0.4, p3: 2.6, p97: 4.1 }, { days: 30, median: 4.5, sd: 0.5, p3: 3.6, p97: 5.5 }, { days: 60, median: 5.8, sd: 0.6, p3: 4.7, p97: 7.0 }, { days: 90, median: 6.8, sd: 0.7, p3: 5.5, p97: 8.2 }, { days: 120, median: 7.6, sd: 0.75, p3: 6.2, p97: 9.1 }, { days: 150, median: 8.3, sd: 0.8, p3: 6.7, p97: 9.9 }, { days: 180, median: 8.8, sd: 0.85, p3: 7.1, p97: 10.5 }, { days: 210, median: 9.2, sd: 0.9, p3: 7.4, p97: 11.0 }, { days: 240, median: 9.6, sd: 0.95, p3: 7.7, p97: 11.4 }, { days: 270, median: 9.9, sd: 1.0, p3: 7.9, p97: 11.8 }, { days: 300, median: 10.2, sd: 1.05, p3: 8.1, p97: 12.1 }, { days: 330, median: 10.4, sd: 1.1, p3: 8.3, p97: 12.3 }, { days: 365, median: 10.6, sd: 1.15, p3: 8.4, p97: 12.5 }, // Add more points up to ~1095 days { days: 730, median: 13.0, sd: 1.5, p3: 10.0, p97: 16.0 }, // ~2 years { days: 1095, median: 15.5, sd: 1.8, p3: 11.5, p97: 19.0 } // ~3 years ]; } else { // Girl return [ { days: 0, median: 3.1, sd: 0.4, p3: 2.4, p97: 4.0 }, { days: 30, median: 4.2, sd: 0.5, p3: 3.3, p97: 5.2 }, { days: 60, median: 5.4, sd: 0.55, p3: 4.3, p97: 6.6 }, { days: 90, median: 6.3, sd: 0.6, p3: 5.0, p97: 7.7 }, { days: 120, median: 7.1, sd: 0.65, p3: 5.7, p97: 8.5 }, { days: 150, median: 7.7, sd: 0.7, p3: 6.1, p97: 9.2 }, { days: 180, median: 8.2, sd: 0.75, p3: 6.5, p97: 9.8 }, { days: 210, median: 8.6, sd: 0.8, p3: 6.8, p97: 10.3 }, { days: 240, median: 9.0, sd: 0.85, p3: 7.1, p97: 10.7 }, { days: 270, median: 9.3, sd: 0.9, p3: 7.3, p97: 11.1 }, { days: 300, median: 9.5, sd: 0.95, p3: 7.5, p97: 11.3 }, { days: 330, median: 9.7, sd: 1.0, p3: 7.7, p97: 11.5 }, { days: 365, median: 9.9, sd: 1.05, p3: 7.8, p97: 11.7 }, // Add more points up to ~1095 days { days: 730, median: 12.2, sd: 1.4, p3: 9.0, p97: 15.0 }, // ~2 years { days: 1095, median: 14.5, sd: 1.7, p3: 10.5, p97: 17.5 } // ~3 years ]; } } function interpolate(ageDays, sexData, property) { // Find the two data points surrounding the ageDays var lowerData = null; var upperData = null; for (var i = 0; i < sexData.length; i++) { if (sexData[i].days <= ageDays) { lowerData = sexData[i]; } else { upperData = sexData[i]; break; } } if (!lowerData) return sexData[0][property]; // Age is before the first data point if (!upperData) return sexData[sexData.length – 1][property]; // Age is after the last data point // Linear interpolation var fraction = (ageDays – lowerData.days) / (upperData.days – lowerData.days); return lowerData[property] + fraction * (upperData[property] – lowerData[property]); } function calculatePercentile() { var ageDays = parseFloat(document.getElementById("infantAgeDays").value); var weightKg = parseFloat(document.getElementById("infantWeightKg").value); var sex = parseInt(document.getElementById("infantSex").value); // Clear previous errors document.getElementById("infantAgeDaysError").style.display = 'none'; document.getElementById("infantWeightKgError").style.display = 'none'; document.getElementById("results-container").style.display = 'none'; var isValid = true; if (isNaN(ageDays) || ageDays 1095) { document.getElementById("infantAgeDaysError").textContent = "Please enter a valid age between 0 and 1095 days."; document.getElementById("infantAgeDaysError").style.display = 'block'; isValid = false; } if (isNaN(weightKg) || weightKg 25) { // Max weight approx for 3 years document.getElementById("infantWeightKgError").textContent = "Please enter a valid weight between 0.1 and 25 kg."; document.getElementById("infantWeightKgError").style.display = 'block'; isValid = false; } if (!isValid) { return; } var sexData = getGrowthChartData(sex); var medianWeight = interpolate(ageDays, sexData, 'median'); var sdWeight = interpolate(ageDays, sexData, 'sd'); var p3Weight = interpolate(ageDays, sexData, 'p3'); var p97Weight = interpolate(ageDays, sexData, 'p97'); var zScore = (weightKg – medianWeight) / sdWeight; // Approximate percentile from Z-score (simplified) // Using a Z-score to percentile lookup table approximation var percentile; if (zScore < -3.0) percentile = 0.1; else if (zScore < -2.5) percentile = 0.6; else if (zScore < -2.0) percentile = 2.3; else if (zScore < -1.645) percentile = 5.0; else if (zScore < -1.28) percentile = 10.0; else if (zScore < -1.036) percentile = 15.0; else if (zScore < -0.841) percentile = 20.0; else if (zScore < -0.674) percentile = 25.0; else if (zScore < -0.524) percentile = 30.0; else if (zScore < -0.385) percentile = 35.0; else if (zScore < -0.253) percentile = 40.0; else if (zScore < -0.126) percentile = 45.0; else if (zScore < 0) percentile = 50.0; // Should ideally be calculated more precisely else if (zScore < 0.126) percentile = 55.0; else if (zScore < 0.253) percentile = 60.0; else if (zScore < 0.385) percentile = 65.0; else if (zScore < 0.524) percentile = 70.0; else if (zScore < 0.674) percentile = 75.0; else if (zScore < 0.841) percentile = 80.0; else if (zScore < 1.036) percentile = 85.0; else if (zScore < 1.28) percentile = 90.0; else if (zScore < 1.645) percentile = 95.0; else if (zScore < 2.0) percentile = 97.7; else if (zScore < 2.5) percentile = 99.4; else percentile = 99.9; document.getElementById("primary-result").textContent = Math.round(percentile) + "th"; document.getElementById("zScore").textContent = "Z-Score: " + zScore.toFixed(2); document.getElementById("weightForAgeMedian").textContent = "Median Weight (50th Percentile): " + medianWeight.toFixed(2) + " kg"; document.getElementById("weightForAge3rd").textContent = "3rd Percentile Weight: " + p3Weight.toFixed(2) + " kg"; document.getElementById("weightForAge97th").textContent = "97th Percentile Weight: " + p97Weight.toFixed(2) + " kg"; document.getElementById("results-container").style.display = 'block'; updateChart(ageDays, weightKg, sexData, medianWeight, p3Weight, p97Weight, sex); populateTable(sexData); } function populateTable(sexData) { var tableBody = document.getElementById("growthTableBody"); tableBody.innerHTML = ""; // Clear previous rows // Add a few representative rows to the table var rowsToShow = [0, 4, 8, 12, 16, 20, 24, 30, 36]; // Indices for ~ 0, 1mo, 2mo, … 3 yrs var maxIndex = sexData.length – 1; for (var i = 0; i = sexData.length) continue; var data = sexData[index]; var row = tableBody.insertRow(); var cellAge = row.insertCell(0); cellAge.textContent = data.days === 0 ? "0" : Math.round(data.days / 30.44) + " mo"; var cellP3 = row.insertCell(1); cellP3.textContent = data.p3.toFixed(2); var cellMedian = row.insertCell(2); cellMedian.textContent = data.median.toFixed(2); var cellP97 = row.insertCell(3); cellP97.textContent = data.p97.toFixed(2); } } function updateChart(currentAgeDays, currentWeightKg, sexData, medianWeight, p3Weight, p97Weight, sex) { var ctx = document.getElementById('growthChart').getContext('2d'); // Destroy previous chart instance if it exists if (growthChartInstance) { growthChartInstance.destroy(); } // Prepare data for chart var labels = []; var medianValues = []; var p3Values = []; var p97Values = []; var babyWeightValues = []; var dataPointsCount = Math.min(sexData.length, 15); // Limit points for clarity var step = Math.floor(sexData.length / dataPointsCount); for (var i = 0; i = sexData.length) index = sexData.length – 1; var dataPoint = sexData[index]; labels.push(dataPoint.days === 0 ? "0" : Math.round(dataPoint.days / 30.44) + " mo"); medianValues.push(dataPoint.median); p3Values.push(dataPoint.p3); p97Values.push(dataPoint.p97); // Add baby's weight point if age matches or is closest if (Math.abs(dataPoint.days – currentAgeDays) < (sexData[1].days – sexData[0].days)/2) { babyWeightValues.push(currentWeightKg); } else { babyWeightValues.push(null); // Use null for points where baby's weight isn't plotted } } // Ensure the current baby's point is plotted if it wasn't captured by the sampling if (!babyWeightValues.includes(currentWeightKg)) { labels.push(Math.round(currentAgeDays / 30.44) + " mo"); medianValues.push(medianWeight); p3Values.push(p3Weight); p97Values.push(p97Weight); babyWeightValues.push(currentWeightKg); } var sexLabel = sex === 0 ? "Boy" : "Girl"; var chartTitle = "Weight-for-Age Growth Chart (" + sexLabel + ")"; growthChartInstance = new Chart(ctx, { type: 'line', data: { labels: labels, datasets: [{ label: 'Median Weight (50th %ile)', data: medianValues, borderColor: 'rgb(75, 192, 192)', tension: 0.1, fill: false, pointRadius: 3, pointBackgroundColor: 'rgb(75, 192, 192)' }, { label: '3rd Percentile', data: p3Values, borderColor: 'rgb(255, 99, 132)', tension: 0.1, fill: false, pointRadius: 3, pointBackgroundColor: 'rgb(255, 99, 132)' }, { label: '97th Percentile', data: p97Values, borderColor: 'rgb(54, 162, 235)', tension: 0.1, fill: false, pointRadius: 3, pointBackgroundColor: 'rgb(54, 162, 235)' }, { label: 'Baby\'s Weight', data: babyWeightValues, borderColor: 'rgb(255, 159, 64)', backgroundColor: 'rgba(255, 159, 64, 0.5)', tension: 0.1, fill: false, pointRadius: 5, pointBackgroundColor: 'rgb(255, 159, 64)' }] }, options: { responsive: true, maintainAspectRatio: true, plugins: { title: { display: true, text: chartTitle, font: { size: 16 } }, legend: { position: 'top', } }, scales: { x: { title: { display: true, text: 'Age (Months)' } }, y: { title: { display: true, text: 'Weight (kg)' }, beginAtZero: false } } } }); } function copyResults() { var primaryResult = document.getElementById("primary-result").textContent; var zScore = document.getElementById("zScore").textContent; var medianWeight = document.getElementById("weightForAgeMedian").textContent; var p3Weight = document.getElementById("weightForAge3rd").textContent; var p97Weight = document.getElementById("weightForAge97th").textContent; var ageDaysInput = document.getElementById("infantAgeDays").value; var weightKgInput = document.getElementById("infantWeightKg").value; var sexInput = document.getElementById("infantSex").options[document.getElementById("infantSex").selectedIndex].text; var assumptions = "Key Assumptions:\n" + "- Baby's Age: " + ageDaysInput + " days (" + Math.round(ageDaysInput / 30.44) + " months)\n" + "- Baby's Weight: " + weightKgInput + " kg\n" + "- Baby's Sex: " + sexInput + "\n\n"; var resultsText = "CDC Infant Weight Percentile Results:\n" + "———————————-\n" + "Baby's Weight Percentile: " + primaryResult + "\n" + zScore + "\n" + medianWeight + "\n" + p3Weight + "\n" + p97Weight + "\n\n" + assumptions; // Use navigator.clipboard for modern browsers if (navigator.clipboard && navigator.clipboard.writeText) { navigator.clipboard.writeText(resultsText).then(function() { alert('Results copied to clipboard!'); }).catch(function(err) { console.error('Could not copy text: ', err); fallbackCopyTextToClipboard(resultsText); }); } else { fallbackCopyTextToClipboard(resultsText); } } function fallbackCopyTextToClipboard(text) { var textArea = document.createElement("textarea"); textArea.value = text; textArea.style.position = "fixed"; textArea.style.left = "-9999px"; textArea.style.top = "-9999px"; 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('Oops, unable to copy', err); alert('Failed to copy results. Please copy manually.'); } document.body.removeChild(textArea); } function resetCalculator() { document.getElementById("infantAgeDays").value = "180"; // Default to 6 months document.getElementById("infantWeightKg").value = "8.5"; // Default realistic weight document.getElementById("infantSex").value = "0"; // Default to Boy document.getElementById("results-container").style.display = 'none'; if (growthChartInstance) { growthChartInstance.destroy(); growthChartInstance = null; } // Optionally recalculate with defaults calculatePercentile(); } // Initial calculation on page load with default values document.addEventListener('DOMContentLoaded', function() { calculatePercentile(); // Ensure chart context is ready var canvas = document.getElementById('growthChart'); if (canvas) { var ctx = canvas.getContext('2d'); // Dummy chart to ensure canvas is initialized and responsive styles applied growthChartInstance = new Chart(ctx, { type: 'line', data: { labels: [], datasets: [] }, options: { responsive: true, maintainAspectRatio: true, scales: { y: { beginAtZero: false }} } }); growthChartInstance.destroy(); // Destroy the dummy chart } });

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