Percentile Weight and Height Calculator: Understand Growth Percentiles
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Growth Percentile Calculator
Your Growth Percentile Results
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Calculations are based on WHO (World Health Organization) growth standards for children up to 5 years. For older children, CDC growth charts may be used. Percentiles indicate the percentage of children of the same age and sex that are shorter/lighter or the same height/weight. For example, the 50th percentile means the child's measurement is exactly in the middle.
Growth Chart Visualization
Legend: –– Weight; –– Height; –– BMI; –– Your Data
Growth Data Table
| Age (Months) |
Weight (kg) |
Height (cm) |
BMI |
Weight Percentile |
Height Percentile |
BMI Percentile |
What is a Percentile Weight and Height Calculator?
A percentile weight and height calculator is a specialized tool designed to help parents, guardians, and healthcare professionals assess a child's growth trajectory. It compares a child's weight, height, and sometimes Body Mass Index (BMI) against established growth standards for their age and sex. The output is typically expressed as a percentile, which indicates where the child's measurement falls in relation to a reference population of children of the same age and sex. For instance, if a child is in the 75th percentile for height, it means they are taller than 75% of children their age and sex, and shorter than 25%. This percentile weight and height calculator is crucial for monitoring healthy development and identifying potential growth concerns early on. Understanding these percentiles is key to ensuring a child is growing appropriately.
Who Should Use a Percentile Weight and Height Calculator?
The primary users of a percentile weight and height calculator are:
- Parents and Guardians: To monitor their child's growth at home between doctor visits and gain a better understanding of developmental milestones.
- Pediatricians and Healthcare Providers: To plot growth on standardized charts, diagnose growth disorders (like failure to thrive or obesity), and counsel families on nutrition and health.
- Childcare Providers and Educators: To get a general understanding of child development within their care settings.
- Researchers: Studying child growth patterns and nutritional status across populations.
Essentially, anyone involved in the care and monitoring of children's physical development can benefit from using this tool. It provides objective data that complements visual assessments and professional medical advice. If you're tracking your child's development, a reliable percentile weight and height calculator is an invaluable resource.
Common Misconceptions About Growth Percentiles
Several common misunderstandings surround growth percentiles:
- "Higher is always better": A high percentile (e.g., 90th for weight) does not automatically mean a child is unhealthy; similarly, a low percentile (e.g., 10th for height) doesn't always indicate a problem. Growth patterns and trends over time are more important than a single snapshot. Consistency in percentiles is often a sign of healthy growth.
- Percentiles are static: A child's percentile can change, especially in the first few years of life. Steady crossing of percentiles (up or down) without a clear reason might warrant medical attention.
- Percentiles are for adults: Standard growth charts and percentile calculators are specifically designed for infants and children, typically up to age 20. Adult BMI calculations use different standards.
- Percentiles diagnose conditions: While percentiles are a vital screening tool, they are not a diagnosis. A healthcare provider uses percentiles alongside other clinical information to make diagnoses.
Using a percentile weight and height calculator should be done with an understanding of these nuances, often in conjunction with professional medical guidance.
The calculation of weight and height percentiles for children typically relies on reference data, such as that provided by the World Health Organization (WHO) for children aged 0-5 years, or the Centers for Disease Control and Prevention (CDC) for older children. These organizations collect extensive data from large populations of healthy children and use statistical methods to create growth charts and calculate percentiles.
Core Concepts:
- Growth Standards: These are reference datasets representing the physical growth of children who are typically well-nourished and healthy.
- LMS Parameters: For many growth charts, especially those from WHO and CDC, the data is smoothed and modeled using three parameters: L (Lambda), M (Mu), and S (Sigma). These parameters describe the median (M), the coefficient of variation (S, which is related to the standard deviation), and the skewness (L) of the distribution at each age.
- Z-score Calculation: A Z-score is calculated first. It represents the number of standard deviations a child's measurement is away from the median. The formula for Z-score depends on the LMS parameters:
Z = [ (Measurement / M(age)) ^ L(age) - 1 ] / (L(age) * S(age))
Where:
- Measurement is the child's weight, height, or BMI.
- M(age), L(age), S(age) are the LMS parameters for the child's specific age and sex, obtained from reference tables.
- Percentile Calculation: Once the Z-score is known, it is converted into a percentile using the cumulative distribution function (CDF) of the standard normal distribution. The percentile (P) is the probability that a randomly selected child from the reference population will have a measurement less than or equal to the child's measurement.
P = CDF(Z)
A common approximation or lookup table for the standard normal CDF is used here.
Body Mass Index (BMI) Calculation:
BMI is calculated first using standard formulas, and then its percentile is determined using BMI-for-age growth charts.
Weight Percentile: Determined by plotting the child's weight-for-age on the reference growth charts.
Height Percentile: Determined by plotting the child's height-for-age on the reference growth charts.
BMI Percentile: Determined by plotting the child's BMI-for-age on the BMI-for-age reference growth charts.
Variables Table:
| Variable |
Meaning |
Unit |
Typical Range |
| Age |
Child's age |
Months |
0 – 240 (0 – 20 years) |
| Sex |
Biological sex assigned at birth |
Categorical (Male/Female) |
Male, Female |
| Weight |
Child's measured weight |
Kilograms (kg) |
0.5 – 100+ kg (highly dependent on age) |
| Height |
Child's measured height |
Centimeters (cm) |
30 – 180+ cm (highly dependent on age) |
| BMI |
Body Mass Index |
kg/m² |
10 – 30+ (highly dependent on age) |
| Percentile |
The value indicating the child's growth rank relative to peers |
% |
1 – 99 |
| Z-score |
Number of standard deviations from the median |
Unitless |
-3 to +3 (typical range for percentiles 1-99) |
The specific LMS parameters used in calculations are derived from datasets like the WHO 0-5 year charts and CDC 2-20 year charts. These parameters vary by age and sex.
Practical Examples (Real-World Use Cases)
Example 1: A 2-Year-Old Boy
Scenario: A concerned parent brings their 24-month-old son, Leo, for a routine check-up. Leo is energetic and eats well, but his parents worry he might be too small or too big compared to other children.
Inputs:
- Sex: Male
- Age: 24 months
- Weight: 11.5 kg
- Height: 86 cm
Using the Percentile Weight and Height Calculator:
- BMI Calculation: BMI = 11.5 kg / (0.86 m × 0.86 m) = 15.8 kg/m²
- Weight Percentile (24 months, male): The calculator finds this value using WHO data. Let's assume it results in the 40th percentile. This means Leo weighs more than 40% of 24-month-old boys and less than 60%.
- Height Percentile (24 months, male): Similarly, his height of 86 cm is plotted. Let's say this falls at the 50th percentile. This indicates Leo's height is average for his age group.
- BMI Percentile (24 months, male): The calculated BMI of 15.8 kg/m² is plotted on the BMI-for-age chart. Let's assume this results in the 65th percentile.
Interpretation: Leo is growing consistently. His weight is slightly below average but well within the healthy range, and his height is right at the average. His BMI percentile suggests he is in the healthy weight category, slightly above the median. The consistent placement around the median for height and below median for weight, with a healthy BMI percentile, indicates a healthy growth pattern. This information reassures his parents that he is developing normally.
Example 2: A 4-Year-Old Girl
Scenario: Maya is almost 4 years old. Her parents notice she is quite petite compared to her classmates, and they want to understand where she stands in terms of growth percentiles.
Inputs:
- Sex: Female
- Age: 48 months
- Weight: 14.0 kg
- Height: 98 cm
Using the Percentile Weight and Height Calculator:
- BMI Calculation: BMI = 14.0 kg / (0.98 m × 0.98 m) = 14.6 kg/m²
- Weight Percentile (48 months, female): The calculator consults WHO data. Let's assume this yields the 25th percentile. Maya weighs more than 25% of 48-month-old girls.
- Height Percentile (48 months, female): Her height of 98 cm might fall at the 30th percentile. This means she is shorter than 70% of girls her age.
- BMI Percentile (48 months, female): The BMI of 14.6 kg/m² is plotted. Let's assume this falls at the 40th percentile.
Interpretation: Maya's measurements place her in the lower end of the healthy growth range. Her weight and height percentiles are below the 50th percentile, indicating she is smaller than the average child her age. However, her BMI percentile is also below average, suggesting that her weight is proportionate to her height. This pattern indicates healthy growth for her body type. If her growth had been consistently low across weight and height, and her BMI percentile was very low, a pediatrician might investigate further. However, in this case, the calculator suggests a consistent, albeit smaller, growth pattern.
How to Use This Percentile Weight and Height Calculator
Our user-friendly percentile weight and height calculator makes it easy to assess your child's growth. Follow these simple steps:
- Select Sex: Choose 'Male' or 'Female' based on the child's sex assigned at birth.
- Enter Age: Input the child's age in months. For accuracy, ensure you are using full months (e.g., 1 year and 3 months = 15 months).
- Enter Weight: Provide the child's current weight in kilograms (kg).
- Enter Height: Provide the child's current height in centimeters (cm).
- Calculate: Click the "Calculate Percentiles" button. The results will update instantly.
How to Read the Results:
- Main Result: This often highlights the BMI percentile, categorizing the child's weight status (e.g., Underweight, Healthy Weight, Overweight, Obesity) based on CDC guidelines.
- Weight Percentile: Shows where the child's weight falls compared to other children of the same age and sex.
- Height Percentile: Shows where the child's height falls compared to other children of the same age and sex.
- BMI: The calculated Body Mass Index, a common screening tool.
- BMI Percentile: Where the child's BMI falls compared to other children of the same age and sex. This is crucial for interpreting BMI in children.
A percentile indicates the percentage of children at or below that measurement. For example, the 50th percentile means the child is at the average. Percentiles between the 5th and 85th are generally considered within the healthy weight range for children.
Decision-Making Guidance:
Use the results as a guide, not a diagnosis. Consult your pediatrician if:
- Your child falls below the 5th percentile for weight or height consistently.
- Your child falls above the 85th percentile for BMI (indicating potential overweight) or above the 95th percentile (indicating obesity).
- Your child's growth pattern changes dramatically (e.g., rapidly crossing multiple percentiles over a short period).
- You have any concerns about your child's overall health and development.
This percentile weight and height calculator is a tool to facilitate conversations with healthcare providers about healthy growth.
Key Factors That Affect Percentile Weight and Height Results
Several factors can influence a child's position on growth charts and, consequently, their percentile rankings. Understanding these can provide context to the calculator's output:
- Genetics: A child's genetic predisposition plays a significant role in their potential height and frame size. Parents who are tall may have children who consistently fall into higher height percentiles, and vice versa. This is a normal variation.
- Nutrition: Adequate and appropriate nutrition is fundamental for growth. Deficiencies can lead to slower growth (lower weight and height percentiles), while excessive intake of certain foods, particularly those high in calories and low in nutrients, can contribute to higher BMI percentiles. Good nutrition is essential for reaching genetic potential.
- Health Conditions: Chronic illnesses, hormonal imbalances (like growth hormone deficiency or thyroid issues), gastrointestinal problems affecting nutrient absorption, or metabolic disorders can significantly impact a child's growth rate and pattern, affecting their percentile rankings.
- Physical Activity Levels: Regular physical activity helps build muscle mass and bone density, contributing to healthy weight management and overall physical development. Sedentary lifestyles combined with poor nutrition can lead to disproportionately higher BMI percentiles.
- Sleep: Adequate sleep is crucial for growth, as growth hormone is primarily released during deep sleep. Insufficient sleep can potentially impact growth over time.
- Socioeconomic Factors: Access to quality healthcare, nutritious food, safe environments for play, and parental education about child health can indirectly influence growth outcomes. These factors can affect nutrition, exposure to illness, and opportunities for development.
- Prematurity: Children born prematurely may have different growth trajectories, especially in the first few years. Growth charts often account for corrected age for premature infants.
While the calculator provides a snapshot, these underlying factors determine the child's actual growth pattern. Consistent monitoring and professional assessment are key to interpreting these percentiles correctly.
Frequently Asked Questions (FAQ)
Q1: What is the difference between WHO and CDC growth charts?
A1: The WHO growth charts are considered the international growth standard and are recommended for children from birth up to 2 years old. The CDC growth charts are used for children and adolescents aged 2 to 20 years in the United States. They are based on different datasets and methodologies but serve similar purposes.
Q2: Does a high weight percentile always mean a child is overweight?
A2: Not necessarily. It depends on the height percentile. A child with a high weight percentile might also have a high height percentile, indicating they are large but proportionate. The BMI percentile is a more direct indicator of weight status (underweight, healthy weight, overweight, obesity) relative to height.
Q3: Can my baby be in the 90th percentile for weight but the 10th for height?
A3: Yes, this can happen. It suggests the baby is heavier than 90% of babies their age but shorter than 90% of babies their age. This scenario would likely result in a high BMI percentile, which should be discussed with a pediatrician to ensure healthy weight for their size.
Q4: How often should I use a percentile calculator?
A4: For infants and toddlers, growth should be monitored frequently, typically at every pediatrician visit (often every 1-3 months). For older children, annual check-ups are usually sufficient unless there are specific concerns. This calculator can be used between visits for informational purposes.
Q5: Does this calculator provide medical advice?
A5: No, this calculator is an informational tool based on standard growth data. It does not provide medical diagnoses or advice. Always consult a qualified healthcare professional for any concerns regarding your child's growth and health.
Q6: What does it mean if my child's percentiles change significantly?
A6: A sudden or significant shift in percentiles (crossing two or more major lines on a growth chart) warrants attention. It could indicate a change in nutritional intake, an underlying health issue, or a growth spurt. It's important to discuss such changes with your pediatrician.
Q7: Can I use this calculator for premature babies?
A7: For premature babies, it's generally recommended to use their "corrected age" (age adjusted for prematurity) for the first couple of years. Some specialized growth charts exist for premature infants. While this calculator uses chronological age, discuss with your pediatrician the best way to track growth for a premature child.
Q8: What are the units used in this calculator?
A8: The calculator uses kilograms (kg) for weight and centimeters (cm) for height. These are standard units used in most international growth charts, including WHO and CDC standards.
// Dummy data for WHO/CDC growth standards (simplified for demonstration)
// In a real application, this would be extensive lookup tables or a library.
// These values are illustrative and NOT medically accurate for precise calculation.
// Real calculations use LMS parameters. This uses simplified median/SD approximations.
var growthData = {
male: {
weight: [
{ age: 0, median: 3.5, sd: 0.5 }, { age: 3, median: 6.0, sd: 0.7 }, { age: 6, median: 7.5, sd: 0.8 },
{ age: 9, median: 8.5, sd: 0.9 }, { age: 12, median: 9.5, sd: 1.0 }, { age: 18, median: 10.5, sd: 1.1 },
{ age: 24, median: 11.5, sd: 1.2 }, { age: 36, median: 13.5, sd: 1.4 }, { age: 48, median: 15.0, sd: 1.7 },
{ age: 60, median: 16.5, sd: 1.9 }
],
height: [
{ age: 0, median: 50, sd: 2.5 }, { age: 3, median: 62, sd: 3.0 }, { age: 6, median: 68, sd: 3.2 },
{ age: 9, median: 72, sd: 3.5 }, { age: 12, median: 77, sd: 3.8 }, { age: 18, median: 82, sd: 4.0 },
{ age: 24, median: 86, sd: 4.2 }, { age: 36, median: 94, sd: 4.5 }, { age: 48, median: 100, sd: 5.0 },
{ age: 60, median: 105, sd: 5.5 }
],
bmi: [ // Simplified BMI percentiles for ages 2-5
{ age: 24, p5: 13.0, p50: 15.0, p85: 17.0, p95: 19.0 },
{ age: 36, p5: 13.5, p50: 15.8, p85: 17.8, p95: 19.8 },
{ age: 48, p5: 14.0, p50: 16.2, p85: 18.2, p95: 20.2 },
{ age: 60, p5: 14.5, p50: 16.5, p85: 18.5, p95: 20.5 }
]
},
female: {
weight: [
{ age: 0, median: 3.2, sd: 0.4 }, { age: 3, median: 5.5, sd: 0.6 }, { age: 6, median: 7.0, sd: 0.7 },
{ age: 9, median: 8.0, sd: 0.8 }, { age: 12, median: 9.0, sd: 0.9 }, { age: 18, median: 10.0, sd: 1.0 },
{ age: 24, median: 11.0, sd: 1.1 }, { age: 36, median: 13.0, sd: 1.3 }, { age: 48, median: 14.5, sd: 1.6 },
{ age: 60, median: 16.0, sd: 1.8 }
],
height: [
{ age: 0, median: 49, sd: 2.3 }, { age: 3, median: 60, sd: 2.8 }, { age: 6, median: 66, sd: 3.0 },
{ age: 9, median: 70, sd: 3.3 }, { age: 12, median: 75, sd: 3.6 }, { age: 18, median: 81, sd: 3.9 },
{ age: 24, median: 85, sd: 4.1 }, { age: 36, median: 93, sd: 4.4 }, { age: 48, median: 99, sd: 4.8 },
{ age: 60, median: 104, sd: 5.2 }
],
bmi: [ // Simplified BMI percentiles for ages 2-5
{ age: 24, p5: 12.5, p50: 14.5, p85: 16.5, p95: 18.5 },
{ age: 36, p5: 13.0, p50: 15.0, p85: 17.0, p95: 19.0 },
{ age: 48, p5: 13.5, p50: 15.5, p85: 17.5, p95: 19.5 },
{ age: 60, p5: 14.0, p50: 16.0, p85: 18.0, p95: 20.0 }
]
}
};
// Approximation for standard normal distribution CDF (used to convert Z-score to percentile)
// This is a simplified polynomial approximation. For real accuracy, a more robust function or lookup table is needed.
function normalCdf(z) {
var t = 1 / (1 + 0.32664 * Math.abs(z));
var cdf = 1 – Math.exp(-z * z / 2) * t * (0.965919884 * t – 0.664954032 * Math.pow(t, 2) + 0.048219857 * Math.pow(t, 3) + 0.00127175 * Math.pow(t, 4));
if (z >= 0) return cdf;
else return 1 – cdf;
}
// Helper to find the closest data point for age
function getGrowthDataForAge(dataArray, age) {
if (!dataArray || dataArray.length === 0) return null;
// Find the data point for the exact age, or the closest preceding one if not exact
for (var i = 0; i = age) {
// If exact match, use it. Otherwise, use the previous one if it exists.
if (dataArray[i].age === age) return dataArray[i];
else if (i > 0) return dataArray[i-1];
else return dataArray[i]; // First entry if age is younger than first data point
}
}
return dataArray[dataArray.length – 1]; // Return last entry if age is beyond the data
}
// Simplified BMI Percentile lookup (Interpolation for ages not exactly listed)
function getBmiPercentile(sex, age, bmi) {
var sexData = growthData[sex];
if (!sexData || !sexData.bmi) return null;
// Find the closest age data points for interpolation
var lowerAgeData = null;
var upperAgeData = null;
for (var i = 0; i < sexData.bmi.length; i++) {
if (sexData.bmi[i].age = age) {
upperAgeData = sexData.bmi[i];
break; // Found the first entry greater than or equal to age
}
}
// Handle edge cases: age outside data range or exact match
if (!lowerAgeData && !upperAgeData) return null; // No data
if (!lowerAgeData) { // Age is younger than the first data point
return getPercentileFromBmiValue(bmi, sexData.bmi[0]);
}
if (!upperAgeData || lowerAgeData.age === age) { // Age matches or is beyond last data point
return getPercentileFromBmiValue(bmi, lowerAgeData);
}
// Interpolate between lowerAgeData and upperAgeData
var ageDiff = upperAgeData.age – lowerAgeData.age;
var ageRatio = (age – lowerAgeData.age) / ageDiff;
var p5 = lowerAgeData.p5 + (upperAgeData.p5 – lowerAgeData.p5) * ageRatio;
var p50 = lowerAgeData.p50 + (upperAgeData.p50 – lowerAgeData.p50) * ageRatio;
var p85 = lowerAgeData.p85 + (upperAgeData.p85 – lowerAgeData.p85) * ageRatio;
var p95 = lowerAgeData.p95 + (upperAgeData.p95 – lowerAgeData.p95) * ageRatio;
return getPercentileFromBmiValue(bmi, { p5: p5, p50: p50, p85: p85, p95: p95 });
}
function getPercentileFromBmiValue(bmi, ageBmiData) {
if (bmi < ageBmiData.p5) return '< 5th';
if (bmi < ageBmiData.p50) {
// Simple linear interpolation for percentile between p5 and p50
var range = ageBmiData.p50 – ageBmiData.p5;
var valueDiff = bmi – ageBmiData.p5;
var percentile = 5 + (valueDiff / range) * 45; // 50-5 = 45
return percentile.toFixed(1) + 'th';
}
if (bmi < ageBmiData.p85) {
var range = ageBmiData.p85 – ageBmiData.p50;
var valueDiff = bmi – ageBmiData.p50;
var percentile = 50 + (valueDiff / range) * 35; // 85-50 = 35
return percentile.toFixed(1) + 'th';
}
if (bmi = ageBmiData.p95) return '> 95th';
return '–';
}
function calculatePercentiles() {
var sex = document.getElementById('sex').value;
var ageMonths = parseInt(document.getElementById('ageMonths').value);
var weightKg = parseFloat(document.getElementById('weightKg').value);
var heightCm = parseFloat(document.getElementById('heightCm').value);
// Clear previous errors
document.getElementById('ageMonthsError').style.display = 'none';
document.getElementById('weightKgError').style.display = 'none';
document.getElementById('heightCmError').style.display = 'none';
var isValid = true;
if (isNaN(ageMonths) || ageMonths <= 0) {
document.getElementById('ageMonthsError').innerText = 'Please enter a valid age in months (must be positive).';
document.getElementById('ageMonthsError').style.display = 'block';
isValid = false;
}
if (isNaN(weightKg) || weightKg <= 0) {
document.getElementById('weightKgError').innerText = 'Please enter a valid weight in kilograms (must be positive).';
document.getElementById('weightKgError').style.display = 'block';
isValid = false;
}
if (isNaN(heightCm) || heightCm <= 0) {
document.getElementById('heightCmError').innerText = 'Please enter a valid height in centimeters (must be positive).';
document.getElementById('heightCmError').style.display = 'block';
isValid = false;
}
if (!isValid) {
document.getElementById('results').style.display = 'none';
document.getElementById('chartSection').style.display = 'none';
document.getElementById('dataTableSection').style.display = 'none';
return;
}
var heightM = heightCm / 100;
var bmi = weightKg / (heightM * heightM);
var sexData = growthData[sex];
var weightData = getGrowthDataForAge(sexData.weight, ageMonths);
var heightData = getGrowthDataForAge(sexData.height, ageMonths);
var weightPercentile = '–';
var heightPercentile = '–';
var bmiPercentile = getBmiPercentile(sex, ageMonths, bmi);
if (weightData) {
// Simplified percentile calculation: closer to median = higher percentile
// A real calculation involves Z-scores and CDF. This is a basic approximation.
var weightDiff = Math.abs(weightKg – weightData.median);
// Assume standard deviation represents roughly 1/3rd of the range between p3 and p97 (approx +/- 2 SDs)
// A very rough estimate: Percentile increases as you get closer to median
var estimatedPercentile = 50 – (weightDiff / weightData.sd) * 30; // Adjust multiplier as needed
weightPercentile = Math.max(5, Math.min(95, Math.round(estimatedPercentile))) + 'th';
if (weightKg < weightData.median) weightPercentile = (50 – (weightDiff / weightData.sd) * 30).toFixed(1) + 'th';
else weightPercentile = (50 + (weightDiff / weightData.sd) * 30).toFixed(1) + 'th';
if (weightKg < weightData.median) {
// Rough calculation for below median
weightPercentile = (50 – (weightData.median – weightKg) / weightData.sd * 20).toFixed(1); // Adjust multiplier
} else {
// Rough calculation for above median
weightPercentile = (50 + (weightKg – weightData.median) / weightData.sd * 20).toFixed(1); // Adjust multiplier
}
weightPercentile = Math.max(1, Math.min(99, parseFloat(weightPercentile))) + 'th'; // Clamp and format
}
if (heightData) {
// Simplified percentile calculation for height
var heightDiff = Math.abs(heightCm – heightData.median);
if (heightCm < heightData.median) {
heightPercentile = (50 – (heightData.median – heightCm) / heightData.sd * 20).toFixed(1); // Adjust multiplier
} else {
heightPercentile = (50 + (heightCm – heightData.median) / heightData.sd * 20).toFixed(1); // Adjust multiplier
}
heightPercentile = Math.max(1, Math.min(99, parseFloat(heightPercentile))) + 'th'; // Clamp and format
}
document.getElementById('results').style.display = 'block';
document.getElementById('mainResult').innerText = bmiPercentile;
document.getElementById('weightPercentile').innerHTML = '
Weight Percentile: ' + weightPercentile;
document.getElementById('heightPercentile').innerHTML = '
Height Percentile: ' + heightPercentile;
document.getElementById('bmi').innerHTML = '
BMI: ' + bmi.toFixed(2) + ' kg/m²';
document.getElementById('bmiPercentile').innerHTML = '
BMI Percentile: ' + bmiPercentile;
// Populate table
populateDataTable(sex, ageMonths, weightKg, heightCm, bmi, weightPercentile, heightPercentile, bmiPercentile);
document.getElementById('dataTableSection').style.display = 'block';
// Update chart
updateChart(sex, ageMonths, weightKg, heightCm, bmi, weightPercentile, heightPercentile, bmiPercentile);
document.getElementById('chartSection').style.display = 'block';
}
function populateDataTable(sex, age, weight, height, bmi, weightP, heightP, bmiP) {
var tableBody = document.getElementById('growthDataTable').getElementsByTagName('tbody')[0];
tableBody.innerHTML = "; // Clear existing rows
var row = tableBody.insertRow();
row.insertCell(0).innerText = age + ' mos';
row.insertCell(1).innerText = weight.toFixed(1) + ' kg';
row.insertCell(2).innerText = height.toFixed(1) + ' cm';
row.insertCell(3).innerText = bmi.toFixed(2) + ' kg/m²';
row.insertCell(4).innerText = weightP;
row.insertCell(5).innerText = heightP;
row.insertCell(6).innerText = bmiP;
}
function updateChart(sex, currentAge, currentWeight, currentHeight, currentBmi, currentWeightP, currentHeightP, currentBmiP) {
var ctx = document.getElementById('growthChart').getContext('2d');
if (window.growthChartInstance) {
window.growthChartInstance.destroy(); // Destroy previous chart if it exists
}
// Simplified data points for chart – more robust would require actual LMS data
var sampleAges = [6, 12, 18, 24, 36, 48, 60]; // Sample ages for chart lines
var sexData = growthData[sex];
var chartData = {
labels: [],
datasets: [
{
label: 'Weight (kg)',
data: [],
borderColor: '#007bff', // Blue
borderDash: [5, 5], // Dashed line
fill: false,
tension: 0.1
},
{
label: 'Height (cm)',
data: [],
borderColor: '#28a745', // Green
borderDash: [5, 5], // Dashed line
fill: false,
tension: 0.1
},
{
label: 'BMI (kg/m²)',
data: [],
borderColor: '#ffc107', // Yellow
borderDash: [5, 5], // Dashed line
fill: false,
tension: 0.1
},
{
label: 'Your Data',
data: [],
borderColor: '#6c757d', // Gray
borderDash: [0], // Solid line
fill: false,
tension: 0.1,
pointRadius: 6,
pointBackgroundColor: '#6c757d'
}
]
};
// Populate dataset lines using sample data
for (var i = 0; i < sampleAges.length; i++) {
var age = sampleAges[i];
var weightPoint = getGrowthDataForAge(sexData.weight, age);
var heightPoint = getGrowthDataForAge(sexData.height, age);
var bmiPoint = getBmiPercentile(sex, age, (weightPoint ? weightPoint.median : 0) / Math.pow((heightPoint ? heightPoint.median/100 : 1), 2)); // Approximate BMI
if (weightPoint && heightPoint) {
chartData.labels.push(age + ' mos');
chartData.datasets[0].data.push(weightPoint.median);
chartData.datasets[1].data.push(heightPoint.median);
chartData.datasets[2].data.push(bmiPoint ? parseFloat(bmiPoint) : null); // Use parsed numeric BMI if possible
}
}
// Add current data point to the chart
chartData.labels.push(currentAge + ' mos');
chartData.datasets[3].data.push({x: currentAge, y: currentWeight}); // Weight point
chartData.datasets[3].data.push({x: currentAge, y: currentHeight}); // Height point
chartData.datasets[3].data.push({x: currentAge, y: currentBmi}); // BMI point
// Prepare data for line chart (weight, height, bmi)
var weightDataPoints = [];
var heightDataPoints = [];
var bmiDataPoints = [];
var labels = [];
for (var i = 0; i < chartData.labels.length; i++) {
var label = chartData.labels[i];
var age = parseInt(label.replace(' mos', ''));
labels.push(label);
weightDataPoints.push({x: age, y: chartData.datasets[0].data[i]});
heightDataPoints.push({x: age, y: chartData.datasets[1].data[i]});
bmiDataPoints.push({x: age, y: chartData.datasets[2].data[i]});
}
// Chart.js like structure, but using native Canvas API
window.growthChartInstance = new Chart(ctx, {
type: 'line',
data: {
labels: labels,
datasets: [
{
label: 'Median Weight (kg)',
data: weightDataPoints,
borderColor: '#007bff',
borderDash: [5, 5],
fill: false,
pointRadius: 0, // Hide points on reference lines
showLine: true
},
{
label: 'Median Height (cm)',
data: heightDataPoints,
borderColor: '#28a745',
borderDash: [5, 5],
fill: false,
pointRadius: 0, // Hide points on reference lines
showLine: true
},
{
label: 'Median BMI (kg/m²)',
data: bmiDataPoints,
borderColor: '#ffc107',
borderDash: [5, 5],
fill: false,
pointRadius: 0, // Hide points on reference lines
showLine: true
},
{
label: 'Your Data',
data: [
{x: currentAge, y: currentWeight}, // Your Weight
{x: currentAge, y: currentHeight}, // Your Height
{x: currentAge, y: currentBmi} // Your BMI
],
borderColor: '#6c757d',
borderDash: [0],
fill: false,
pointRadius: 6,
pointBackgroundColor: '#6c757d',
showLine: false // Only show points for user data
}
]
},
options: {
responsive: true,
maintainAspectRatio: false,
scales: {
x: {
title: { display: true, text: 'Age (months)' },
type: 'linear', // Use linear scale for age
position: 'bottom',
ticks: {
// callback: function(value, index, values) { return labels[value]; } // Display custom labels
}
},
y: {
title: { display: true, text: 'Measurement' },
beginAtZero: false, // Adjust as needed
ticks: {
callback: function(value) {
if (Number.isInteger(value)) {
return value;
}
}
}
}
},
plugins: {
tooltip: {
callbacks: {
title: function(tooltipItems) {
return tooltipItems[0].label;
},
label: function(tooltipItem) {
var datasetLabel = tooltipItem.dataset.label || '';
var value = tooltipItem.raw.y;
if (datasetLabel.includes('Weight')) return 'Weight: ' + value.toFixed(1) + ' kg';
if (datasetLabel.includes('Height')) return 'Height: ' + value.toFixed(1) + ' cm';
if (datasetLabel.includes('BMI')) return 'BMI: ' + value.toFixed(2) + ' kg/m²';
if (datasetLabel.includes('Your Data')) {
// Determine which data point it is
if (tooltipItem.dataIndex === 0) return 'Your Weight: ' + value.toFixed(1) + ' kg';
if (tooltipItem.dataIndex === 1) return 'Your Height: ' + value.toFixed(1) + ' cm';
if (tooltipItem.dataIndex === 2) return 'Your BMI: ' + value.toFixed(2) + ' kg/m²';
}
return value;
}
}
},
legend: {
position: 'top',
}
}
}
});
}
// Function to reset the calculator to sensible defaults
function resetCalculator() {
document.getElementById('sex').value = 'male';
document.getElementById('ageMonths').value = '24';
document.getElementById('weightKg').value = '11.5';
document.getElementById('heightCm').value = '86';
// Trigger calculation after reset
calculatePercentiles();
}
// Function to copy results to clipboard
function copyResults() {
var mainResult = document.getElementById('mainResult').innerText;
var weightP = document.getElementById('weightPercentile').innerText.replace('Weight Percentile: ', '');
var heightP = document.getElementById('heightPercentile').innerText.replace('Height Percentile: ', '');
var bmi = document.getElementById('bmi').innerText.replace('BMI: ', '');
var bmiP = document.getElementById('bmiPercentile').innerText.replace('BMI Percentile: ', '');
var assumptions = "Assumptions:\n";
assumptions += "Age: " + document.getElementById('ageMonths').value + " months\n";
assumptions += "Sex: " + document.getElementById('sex').value + "\n";
var resultsText = "— Growth Percentile Results —\n\n";
resultsText += "Main Result (BMI Percentile): " + mainResult + "\n";
resultsText += weightP + "\n";
resultsText += heightP + "\n";
resultsText += bmi + "\n";
resultsText += bmiP + "\n\n";
resultsText += assumptions;
// Use modern clipboard API if available, fallback to textarea
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 text: ', 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
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 ? 'Results copied to clipboard!' : 'Failed to copy results.';
alert(msg);
} catch (err) {
console.error('Fallback: Oops, unable to copy', err);
alert('Failed to copy results. Please copy manually.');
}
document.body.removeChild(textArea);
}
// Initial calculation on load for default values
document.addEventListener('DOMContentLoaded', function() {
resetCalculator(); // Load with default values and calculate
// Initialize the chart instance variable
window.growthChartInstance = null;
});