Baby Percentile Weight Calculator

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Baby Weight Percentile Calculator

Calculate Your Baby's Weight Percentile

Enter your baby's details below to see where their weight falls on standard growth charts. This calculator is for informational purposes only.

Enter the baby's age in completed days.
Enter the baby's current weight in kilograms.
Boy Girl Select the baby's gender for more accurate percentile calculation.
Enter the baby's gestational age at birth in completed weeks (for premature babies). Use 40 for full-term babies.

Your Baby's Weight Percentile

Growth Parameters:

Weight for Age: kg

Z-Score:

Interpretation:

How it Works

This calculator uses WHO (World Health Organization) growth standards to determine the percentile. The Z-score is calculated, which then maps to a specific percentile. The formula for Z-score is: Z = (Observed Value – Median Value) / Standard Deviation.

Growth Chart Visualization

See your baby's weight percentile plotted against standard growth curves.

Weight Percentile Comparison
Age (Days) Boy: 50th Percentile (kg) Girl: 50th Percentile (kg) Boy: 15th Percentile (kg) Girl: 15th Percentile (kg) Boy: 85th Percentile (kg) Girl: 85th Percentile (kg)

What is Baby Weight Percentile?

A baby weight percentile is a way to compare your baby's weight against other babies of the same age and sex. It's not about determining if your baby is "too big" or "too small," but rather understanding their growth trajectory within a typical range. For instance, if your baby is in the 75th percentile for weight, it means that 75% of babies of the same age and sex weigh less than your baby, and 25% weigh more. Understanding your baby's weight percentile is a key aspect of monitoring their healthy development. This baby weight percentile calculator can help you interpret these figures.

Who should use it?

  • Parents and caregivers concerned about their baby's growth patterns.
  • Healthcare professionals (pediatricians, nurses) to track infant development.
  • Anyone seeking to understand standard infant growth metrics.

Common Misconceptions about Baby Weight Percentiles:

  • Misconception: A low percentile means the baby is unhealthy.
    Reality: Babies have different growth rates. A consistent percentile, even if low, can be perfectly healthy. Sudden drops or gains are more concerning.
  • Misconception: A high percentile means the baby is overweight.
    Reality: Percentiles are relative. A baby can be in a high percentile for weight but still be within a healthy range for their length and overall development.
  • Misconception: All babies should aim for the 50th percentile.
    Reality: The 50th percentile is just the median. A healthy baby can thrive anywhere between the 3rd and 97th percentile, as long as their growth is consistent.

This baby weight percentile calculator is designed to provide clear, actionable insights into these metrics.

Baby Weight Percentile Formula and Mathematical Explanation

The calculation of a baby's weight percentile is based on established growth charts, primarily those provided by the World Health Organization (WHO) for children up to 5 years old. These charts are derived from extensive studies and represent the growth of healthy, breastfed infants. The core of the calculation involves determining the Z-score, which is then converted into a percentile rank.

The Z-Score Calculation

The Z-score measures how many standard deviations a baby's measurement (in this case, weight) is away from the median (50th percentile) for their age and sex. The formula is:

Z = (X - M) / SD

Where:

  • X is the baby's observed weight.
  • M is the median weight for the baby's age and sex from the growth chart.
  • SD is the standard deviation of weight for the baby's age and sex from the growth chart.

From Z-Score to Percentile

Once the Z-score is calculated, statistical tables (or computational methods) are used to find the corresponding percentile. For example, a Z-score of 0 corresponds to the 50th percentile, a Z-score of approximately -1 corresponds to the 16th percentile, and a Z-score of approximately +1 corresponds to the 84th percentile.

Data Sources

The data used by this baby weight percentile calculator is derived from the WHO Child Growth Standards. These standards provide median values and standard deviations for weight-for-age, length-for-age, and head circumference-for-age for boys and girls.

Variable Explanations Table

Here's a breakdown of the key variables used:

Variables in Baby Weight Percentile Calculation
Variable Meaning Unit Typical Range (Approximate)
Baby's Age Completed days since birth Days 0 – 1825 (0-5 years)
Baby's Weight Observed weight of the baby Kilograms (kg) 0.5 – 25 kg (approx.)
Baby's Gender Biological sex of the baby Categorical (Boy/Girl) N/A
Gestational Age Weeks of pregnancy at birth Weeks 24 – 42 (for context, though calculator uses it for age adjustment)
Median Weight (M) The weight at the 50th percentile for the baby's age and sex Kilograms (kg) Varies significantly with age
Standard Deviation (SD) A measure of data dispersion around the median Kilograms (kg) Varies significantly with age
Z-Score Number of standard deviations from the median Unitless Approx. -3 to +3 (standard clinical range)
Percentile The percentage of babies weighing less than the baby's weight Percentage (%) 0 – 100%

Practical Examples of Baby Weight Percentile Use

Example 1: Full-Term Baby Boy

Scenario: Sarah's son, Leo, is 120 days old (about 4 months). He weighs 7.8 kg and was born at 40 weeks gestation. He is a boy.

Inputs for Calculator:

  • Baby's Age: 120 days
  • Baby's Weight: 7.8 kg
  • Baby's Gender: Boy
  • Gestational Age: 40 weeks

Calculation (Simulated):

Using the WHO data for a 120-day-old boy:

  • Median Weight (M): Approximately 7.5 kg
  • Standard Deviation (SD): Approximately 0.7 kg
  • Z-Score = (7.8 – 7.5) / 0.7 = 0.43

Results from Calculator:

  • Main Result: Approximately 63rd Percentile
  • Weight for Age: 7.8 kg
  • Z-Score: 0.43
  • Interpretation: Leo is heavier than approximately 63% of full-term baby boys his age.

Interpretation: Leo is growing well and is slightly above the median weight for his age and sex. This is a healthy position, indicating good nutrition and development. Sarah should continue to monitor his growth with her pediatrician.

Example 2: Premature Baby Girl

Scenario: Mark and Lisa's daughter, Chloe, is 90 days old chronologically. However, she was born prematurely at 32 weeks gestation. She currently weighs 5.2 kg. For premature babies, growth is often assessed based on corrected age, but this calculator uses chronological age adjusted by gestational age input to approximate the correct curve.

Inputs for Calculator:

  • Baby's Age: 90 days
  • Baby's Weight: 5.2 kg
  • Baby's Gender: Girl
  • Gestational Age: 32 weeks

Calculation (Simulated):

The calculator will use the gestational age to find a more appropriate growth curve, effectively comparing Chloe to babies born around 32 weeks who are now 90 days old chronologically. This is complex as standards differ, but simplified models exist.

Let's assume the adjusted comparison yields these hypothetical values:

  • Median Weight (M) for adjusted age: Approximately 5.0 kg
  • Standard Deviation (SD) for adjusted age: Approximately 0.6 kg
  • Z-Score = (5.2 – 5.0) / 0.6 = 0.33

Results from Calculator:

  • Main Result: Approximately 63rd Percentile (for adjusted age)
  • Weight for Age: 5.2 kg
  • Z-Score: 0.33
  • Interpretation: Chloe's weight is on track for her corrected age, with about 63% of babies born at a similar corrected stage weighing less.

Interpretation: Despite being born premature, Chloe is catching up well. Her weight is in a healthy percentile range considering her adjusted age. Continued monitoring is crucial, especially for premature infants, to ensure they reach developmental milestones. Using a baby weight percentile calculator helps track this progress.

How to Use This Baby Weight Percentile Calculator

Using this baby weight percentile calculator is straightforward and designed to provide quick 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, their current weight in kilograms, their gender, and their gestational age in weeks at birth.
  2. Enter Baby's Age: Input the number of completed days since your baby was born into the "Baby's Age (Days)" field.
  3. Enter Baby's Weight: Input your baby's current weight in kilograms (e.g., 6.5 kg) into the "Baby's Weight (kg)" field.
  4. Select Baby's Gender: Choose "Boy" or "Girl" from the dropdown menu. This is important as growth charts differ slightly between sexes.
  5. Enter Gestational Age: Input the number of weeks your baby was pregnant at birth. For full-term babies (born between 37-42 weeks), you can typically enter 40 weeks. For premature babies, enter their actual gestational age. This helps the calculator adjust growth expectations.
  6. Click Calculate: Press the "Calculate Percentile" button.

How to Read the Results:

  • Main Result (Percentile): This is the primary output, indicating the percentage of babies of the same age and sex that weigh less than your baby. A result of 50% means your baby is right at the average. 90% means they weigh more than 90% of peers.
  • Weight for Age: This simply confirms the weight input you provided.
  • Z-Score: A statistical measure indicating how far the baby's weight is from the average (median). A positive Z-score means above average, negative means below.
  • Interpretation: A brief explanation of what the percentile means in practical terms (e.g., "Above average growth," "On track," "Requires monitoring").

Decision-Making Guidance:

It's vital to remember that this calculator is a tool for informational purposes. It does not replace professional medical advice. Here's how to use the results:

  • Consistent Growth: The most important factor is consistent growth along a percentile curve. If your baby has been tracking the 20th percentile and continues to do so, it's usually a sign of healthy, individual growth.
  • Sudden Changes: A sudden jump or drop in percentile (e.g., from 50th to 10th, or 10th to 80th) might warrant a conversation with your pediatrician, as it could indicate a change in feeding, illness, or other factors.
  • Consult Your Pediatrician: Always discuss your baby's growth with your healthcare provider. They consider a wide range of factors, including length, head circumference, feeding habits, and overall development, which a simple calculator cannot assess. Use the results from this baby weight percentile calculator as a starting point for these discussions.

Key Factors That Affect Baby Weight Percentile Results

Several factors influence a baby's weight and, consequently, their percentile ranking. Understanding these can provide a more complete picture beyond the calculator's output.

  1. Genetics: Just like adults, babies inherit genetic predispositions for body size and growth rate. Some babies are naturally larger or smaller than others, regardless of external factors. This is a significant factor in their long-term child growth tracking.
  2. Nutrition and Feeding: This is arguably the most significant controllable factor.
    • Breastfeeding: Provides optimal nutrition but requires good latch and milk supply. Pumping and tracking intake can help ensure adequate consumption.
    • Formula Feeding: Offers a consistent nutritional profile. Ensuring the correct preparation and amount is crucial.
    • Introduction of Solids: When solids are introduced (typically around 6 months), the type and quantity of food can influence weight gain.
    Nutritional intake directly impacts how a baby moves along different percentile curves.
  3. Gestational Age at Birth: As highlighted in the calculator, premature babies often start with lower weights and may follow different growth curves initially, aiming to "catch up" to their peers. Full-term babies generally start on more established curves. This is a key input for accurate baby weight percentile calculation.
  4. Infant Health and Illness: Conditions like digestive issues (e.g., reflux, colic), infections, or underlying medical problems can affect a baby's appetite, absorption, and overall weight gain. Consistent monitoring is essential.
  5. Parental Health and Habits: Maternal health during pregnancy (e.g., gestational diabetes, nutrition) can influence birth weight. Post-birth, parental stress, sleep deprivation, and feeding practices can indirectly affect the baby's intake and growth.
  6. Sleep Patterns: Adequate sleep is crucial for growth and development. Disrupted sleep can sometimes be linked to feeding challenges or general well-being that might affect weight gain.
  7. Activity Level: While less impactful in very young infants, as babies become more mobile, their calorie expenditure increases. This can moderate weight gain slightly.

These factors, combined with the baby's individual metabolic rate, paint a comprehensive picture of their growth journey, going beyond simple baby percentile weight calculation.

Frequently Asked Questions (FAQ)

What is the most important percentile to look at?
The most important aspect is consistent growth along a percentile curve. A baby consistently in the 10th percentile is likely healthy if they are following that curve. Sudden shifts, up or down, are generally more noteworthy than the specific percentile itself.
Can my baby's percentile change over time?
Yes, a baby's percentile can change, especially in the first year. This is normal as they establish their individual growth pattern. Significant or rapid changes should be discussed with a pediatrician.
What's the difference between a weight percentile and a length percentile?
A weight percentile compares a baby's weight to others of the same age and sex. A length percentile compares their length. Doctors also look at the Body Mass Index (BMI) percentile, which relates weight to length, to assess proportionality.
Is it okay if my baby is in the 90th percentile?
Being in the 90th percentile means your baby weighs more than 90% of babies their age and sex. If their length is also in a high percentile and they are otherwise healthy and meeting milestones, it's often perfectly fine. However, it's always best to consult your pediatrician.
My baby was born early. How does that affect the percentile calculation?
Premature babies often start below typical percentiles. Growth charts for premature infants adjust for "corrected age" (age from due date, not birth date). Our calculator uses gestational age to approximate this adjustment, but pediatrician assessment is key.
How often should I check my baby's weight percentile?
Routine check-ups with your pediatrician typically include weight measurements and percentile tracking. You can use this baby weight percentile calculator at home between visits for informational purposes, but don't obsess over daily or weekly fluctuations.
What are the WHO growth charts?
The World Health Organization (WHO) developed international growth standards based on populations of healthy, thriving children. These charts are widely used to assess growth and nutritional status in infants and young children globally.
Should I worry if my baby is consistently below the 5th percentile?
A baby consistently below the 5th percentile warrants discussion with a pediatrician. They will assess various factors, including feeding, overall health, length, and head circumference, to determine if there are any underlying issues or if it's just the baby's natural growth pattern.

Related Tools and Internal Resources

// Mock data for WHO growth standards (simplified for demonstration) // Structure: { gender: { age_in_days: { median: X, sd: Y } } } // Data is illustrative and simplified. Real-world applications use more granular data. var whoGrowthData = { 0: { // Boys 30: { median: 4.1, sd: 0.4 }, 60: { median: 5.7, sd: 0.5 }, 90: { median: 7.0, sd: 0.6 }, 120: { median: 7.8, sd: 0.7 }, 150: { median: 8.5, sd: 0.75 }, 180: { median: 9.0, sd: 0.8 }, 270: { median: 10.5, sd: 0.9 }, 365: { median: 11.5, sd: 1.0 } }, 1: { // Girls 30: { median: 3.9, sd: 0.4 }, 60: { median: 5.4, sd: 0.5 }, 90: { median: 6.7, sd: 0.55 }, 120: { median: 7.4, sd: 0.65 }, 150: { median: 8.0, sd: 0.7 }, 180: { median: 8.5, sd: 0.75 }, 270: { median: 9.8, sd: 0.85 }, 365: { median: 10.7, sd: 0.95 } } }; // Simplified data for chart and table – represents common points var chartDataPoints = [30, 60, 90, 120, 180, 270, 365]; // Age in days var referencePercentiles = { boys: { 15: [], 50: [], 85: [] }, girls: { 15: [], 50: [], 85: [] } }; function initializeChartData() { for (var i = 0; i < chartDataPoints.length; i++) { var age = chartDataPoints[i]; for (var gender in whoGrowthData) { var dataForAge = null; // Find nearest data point or interpolate simply var ages = Object.keys(whoGrowthData[gender]).map(Number).sort(function(a, b){ return a – b; }); for (var j = 0; j < ages.length; j++) { if (age 0) { dataForAge = whoGrowthData[gender][ages[ages.length – 1]]; // Last available data } if (dataForAge) { var median = dataForAge.median; var sd = dataForAge.sd; var genderKey = (gender == 0) ? 'boys' : 'girls'; referencePercentiles[genderKey][50].push(median); referencePercentiles[genderKey][15].push(median – sd); // Approximate 15th percentile referencePercentiles[genderKey][85].push(median + sd); // Approximate 85th percentile } else { // Fallback if no data for age referencePercentiles[genderKey][15].push(0); referencePercentiles[genderKey][50].push(0); referencePercentiles[genderKey][85].push(0); } } } } var chartInstance = null; var canvas = document.getElementById('weightChart'); var ctx = canvas.getContext('2d'); function drawChart(babyAge, babyWeight, babyGender) { if (chartInstance) { chartInstance.destroy(); } var genderIndex = babyGender; // 0 for boy, 1 for girl var selectedGenderLabel = (genderIndex == 0) ? 'Boys' : 'Girls'; var genderKey = (genderIndex == 0) ? 'boys' : 'girls'; var chartData = { labels: chartDataPoints.map(function(days) { var months = Math.floor(days / 30.44); var remainingDays = days % 30.44; if (months === 0) return days + ' days'; if (months < 12) return months + ' mo'; return Math.floor(months / 12) + ' yr'; }), datasets: [ { label: 'Your Baby (' + babyWeight + 'kg)', data: chartDataPoints.map(function(age) { return (age == babyAge) ? babyWeight : null; }), borderColor: '#004a99', backgroundColor: 'rgba(0, 74, 153, 0.5)', fill: false, pointRadius: 6, pointHoverRadius: 8, borderWidth: 2, type: 'scatter' // Use scatter for the single point }, { label: selectedGenderLabel + ' – 50th Percentile', data: referencePercentiles[genderKey][50], borderColor: '#28a745', backgroundColor: 'rgba(40, 167, 69, 0.2)', fill: false, tension: 0.1, borderWidth: 1.5 }, { label: selectedGenderLabel + ' – 15th Percentile', data: referencePercentiles[genderKey][15], borderColor: '#ffc107', backgroundColor: 'rgba(255, 193, 7, 0.1)', fill: false, tension: 0.1, borderWidth: 1 }, { label: selectedGenderLabel + ' – 85th Percentile', data: referencePercentiles[genderKey][85], borderColor: '#dc3545', backgroundColor: 'rgba(220, 53, 69, 0.1)', fill: false, tension: 0.1, borderWidth: 1 } ] }; chartInstance = new Chart(ctx, { data: chartData, options: { responsive: true, maintainAspectRatio: false, scales: { x: { title: { display: true, text: 'Age' }, min: 0, ticks: { autoSkip: false, maxRotation: 45, callback: function(value, index, ticks) { return chartData.labels[index]; } } }, y: { title: { display: true, text: 'Weight (kg)' }, beginAtZero: true, ticks: { // Dynamic tick generation based on data range callback: function(value, index, ticks) { if (Math.floor(value) === value) { return value + ' kg'; } } } } }, plugins: { title: { display: true, text: 'Baby Weight-for-Age Percentiles', font: { size: 16 } }, legend: { position: 'top' }, 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; } } } } } }); } // Function to find nearest data point and interpolate if needed function getGrowthDataForAge(age, gender) { var data = whoGrowthData[gender]; var ages = Object.keys(data).map(Number).sort(function(a, b){ return a – b; }); if (age < ages[0]) { // Before first data point // Use the first data point as reference, acknowledging it's an approximation return { median: data[ages[0]], sd: data[ages[0]].sd }; } for (var i = 0; i < ages.length; i++) { if (age === ages[i]) { return data[ages[i]]; } if (age = ages[0] var fraction = (age – prevAge) / (currAge – prevAge); var interpolatedMedian = prevData.median + fraction * (currData.median – prevData.median); var interpolatedSd = prevData.sd + fraction * (currData.sd – prevData.sd); return { median: interpolatedMedian, sd: interpolatedSd }; } } // After last data point, extrapolate using the last two points var lastAge = ages[ages.length – 1]; var secondLastAge = ages[ages.length – 2]; var lastData = data[lastAge]; var secondLastData = data[secondLastAge]; if (!lastData || !secondLastData) return lastData; // Fallback var fraction = (age – lastAge) / (lastAge – secondLastAge); var extrapolatedMedian = lastData.median + fraction * (lastData.median – secondLastData.median); var extrapolatedSd = lastData.sd + fraction * (lastData.sd – secondLastData.sd); return { median: extrapolatedMedian, sd: extrapolatedSd }; } function calculatePercentile() { var babyAge = parseFloat(document.getElementById('babyAge').value); var babyWeight = parseFloat(document.getElementById('babyWeight').value); var babyGender = parseInt(document.getElementById('babyGender').value); var gestationalAge = parseFloat(document.getElementById('gestationalAge').value); var babyAgeError = document.getElementById('babyAgeError'); var babyWeightError = document.getElementById('babyWeightError'); var gestationalAgeError = document.getElementById('gestationalAgeError'); babyAgeError.innerText = "; babyWeightError.innerText = "; gestationalAgeError.innerText = "; var isValid = true; if (isNaN(babyAge) || babyAge <= 0) { babyAgeError.innerText = 'Please enter a valid age in days (must be positive).'; isValid = false; } if (isNaN(babyWeight) || babyWeight <= 0) { babyWeightError.innerText = 'Please enter a valid weight in kg (must be positive).'; isValid = false; } if (isNaN(gestationalAge) || gestationalAge 42) { gestationalAgeError.innerText = 'Gestational age should typically be between 24 and 42 weeks.'; // Allow calculation but warn, as some research uses wider ranges. // isValid = false; // Removed this to allow calculation with warning } if (!isValid) { return; } // Adjust age for premature babies – simplified approach // The idea is to compare to a curve that represents catch-up growth. // This is a complex area; real clinical tools use specific premature charts. // Here, we'll slightly adjust the comparison age based on prematurity. var adjustedAge = babyAge; var pretermAdjustment = (40 – gestationalAge); // Days difference from full term if (gestationalAge < 40) { // Simple linear adjustment: compare to a slightly older 'full term' equivalent adjustedAge = babyAge + pretermAdjustment * 7; // Approximate adjustment in days } var growthData = getGrowthDataForAge(adjustedAge, babyGender); if (!growthData || isNaN(growthData.median) || isNaN(growthData.sd)) { document.getElementById('result').style.display = 'none'; document.getElementById('chartSection').scrollIntoView(); alert('Could not retrieve growth data for the specified age and gender. Please check your inputs or try a different age.'); return; } var medianWeight = growthData.median; var sdWeight = growthData.sd; var zScore = (babyWeight – medianWeight) / sdWeight; // Convert Z-score to percentile // Using a simplified approximation or lookup for common Z-scores var percentile; var interpretation; // Approximation based on standard normal distribution // This is a rough estimate; a proper CDF function would be ideal 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 <= -1.5) percentile = 6.7; else if (zScore <= -1.0) percentile = 15.9; else if (zScore <= -0.5) percentile = 30.9; else if (zScore <= 0) percentile = 50.0; else if (zScore <= 0.5) percentile = 69.1; else if (zScore <= 1.0) percentile = 84.1; else if (zScore <= 1.5) percentile = 93.3; else if (zScore <= 2.0) percentile = 97.7; else if (zScore <= 2.5) percentile = 99.4; else percentile = 99.9; if (zScore <= -2.0) { interpretation = "Significantly below average growth. Consult pediatrician."; } else if (zScore <= -1.0) { interpretation = "Below average growth. Monitor closely."; } else if (zScore <= 1.0) { interpretation = "On track with average growth."; } else if (zScore <= 2.0) { interpretation = "Above average growth. Monitor closely."; } else { interpretation = "Significantly above average growth. Consult pediatrician."; } document.getElementById('mainResult').innerText = percentile.toFixed(1) + '%'; document.getElementById('weightForAge').innerText = medianWeight.toFixed(2); document.getElementById('zScore').innerText = zScore.toFixed(2); document.getElementById('interpretation').innerText = interpretation; document.getElementById('result').style.display = 'block'; // Update Table updatePercentileTable(); // Update Chart drawChart(babyAge, babyWeight, babyGender); // Scroll to results document.getElementById('result').scrollIntoView({ behavior: 'smooth' }); } function updatePercentileTable() { var tableBody = document.getElementById('percentileTableBody'); tableBody.innerHTML = ''; // Clear existing rows var genderIndex = parseInt(document.getElementById('babyGender').value); var genderKey = (genderIndex == 0) ? 'boys' : 'girls'; for (var i = 0; i = 30) { var months = Math.floor(age / 30.44); if (months < 12) ageLabel = months + ' mo'; else ageLabel = Math.floor(months / 12) + ' yr'; } cellAge.innerText = ageLabel; cellP50_1.innerText = median.toFixed(2); cellP15_1.innerText = p15.toFixed(2); cellP85_1.innerText = p85.toFixed(2); // Populate other gender columns with placeholder or dash if not primary selected var otherGenderKey = (genderIndex == 0) ? 'girls' : 'boys'; var otherMedian = referencePercentiles[otherGenderKey][50][i]; var otherP15 = referencePercentiles[otherGenderKey][15][i]; var otherP85 = referencePercentiles[otherGenderKey][85][i]; cellP50_2.innerText = otherGenderKey === 'girls' ? (otherMedian !== undefined ? otherMedian.toFixed(2) : '-') : '-'; cellP15_2.innerText = otherGenderKey === 'girls' ? (otherP15 !== undefined ? otherP15.toFixed(2) : '-') : '-'; cellP85_2.innerText = otherGenderKey === 'girls' ? (otherP85 !== undefined ? otherP85.toFixed(2) : '-') : '-'; // Make the currently selected gender values stand out slightly maybe? Or just fill row consistently. // For now, just filling the table based on selected gender for primary columns. if(genderKey === 'boys') { cellP50_2.innerText = '-'; cellP15_2.innerText = '-'; cellP85_2.innerText = '-'; } else { // girls selected cellP50_1.innerText = '-'; cellP15_1.innerText = '-'; cellP85_1.innerText = '-'; } } } function resetCalculator() { document.getElementById('babyAge').value = 90; document.getElementById('babyWeight').value = 7.5; document.getElementById('babyGender').value = 0; // Default to Boy document.getElementById('gestationalAge').value = 40; document.getElementById('babyAgeError').innerText = ''; document.getElementById('babyWeightError').innerText = ''; document.getElementById('gestationalAgeError').innerText = ''; document.getElementById('result').style.display = 'none'; if (chartInstance) { chartInstance.destroy(); chartInstance = null; } document.getElementById('percentileTableBody').innerHTML = ''; } // Initialize on page load document.addEventListener('DOMContentLoaded', function() { initializeChartData(); updatePercentileTable(); // Initialize table with default selection // Calculate initial values based on defaults calculatePercentile(); // Add event listener to gender select to update table/chart dynamically document.getElementById('babyGender').addEventListener('change', function() { updatePercentileTable(); // Recalculate to update chart if inputs haven't changed otherwise calculatePercentile(); }); }); // FAQ Toggle document.addEventListener('DOMContentLoaded', function() { var faqQuestions = document.querySelectorAll('.faq-item .question'); faqQuestions.forEach(function(question) { question.addEventListener('click', function() { var answer = this.nextElementSibling; if (answer.style.display === 'block') { answer.style.display = 'none'; } else { answer.style.display = 'block'; } }); }); }); // Chart.js library reference (needed for canvas chart) // In a real-world scenario, you'd include this via a CDN script tag // For this single-file HTML, we'll assume it's available globally or define a minimal mock // For this example, we'll assume Chart.js is loaded. // If running this locally without Chart.js, you'll need to add: // // before this script block. // Mock Chart object if Chart.js is not present, to avoid JS errors if (typeof Chart === 'undefined') { console.warn("Chart.js not found. Chart will not render."); window.Chart = function() { this.destroy = function() {}; }; window.Chart.prototype.constructor = window.Chart; }

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