Cdc Weight for Age Calculator 2-20 Female

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CDC Weight for Age Calculator (2-20 Years, Female)

Growth Assessment Tool

This calculator helps assess a girl's weight relative to her age and height using CDC growth charts, crucial for monitoring healthy development.

Enter age in months (e.g., 60 for 5 years). Must be between 24 and 240 months.
Enter weight in kilograms (kg). Must be between 1 and 150 kg.
Enter height in centimeters (cm). Must be between 50 and 200 cm.
Weight-for-Age Percentile (Female, 2-20 Years)
BMI:
BMI-for-Age Percentile:
Z-Score:
Calculated based on CDC growth charts, comparing the child's weight, height, and age to a reference population.

CDC Growth Chart Data

Reference data used for calculation, illustrating typical growth patterns.

Age (Months) Weight (kg) Height (cm) BMI Weight-for-Age %tile BMI-for-Age %tile Z-Score

Growth Chart Visualization

Visual representation of weight and BMI percentiles against age.

What is the CDC Weight for Age Calculator (2-20 Female)?

The CDC weight for age calculator 2-20 female is a specialized tool designed to assess a girl's growth trajectory based on data from the Centers for Disease Control and Prevention (CDC). It specifically focuses on girls between the ages of 2 and 20 years. This calculator compares a child's weight, height, and age against established CDC growth charts to determine where she falls within the expected range for her demographic. This percentile ranking is a crucial indicator used by healthcare professionals to monitor a child's nutritional status, identify potential growth concerns, and track overall physical development. Understanding these percentiles helps in ensuring a child is growing appropriately, neither too rapidly nor too slowly, in relation to her peers.

Who should use it?

  • Parents and guardians monitoring their daughter's growth.
  • Pediatricians and healthcare providers for routine check-ups and assessments.
  • Nutritionists and dietitians evaluating a child's nutritional status.
  • Researchers studying child development and growth patterns.

Common misconceptions include believing that a specific percentile (e.g., 50th) is always the ideal target, when in reality, a consistent growth pattern along any percentile channel is often more important than the exact percentile itself. Another misconception is that this calculator diagnoses conditions; it is a screening tool, and any concerns should be discussed with a medical professional.

Weight-for-Age Percentile Formula and Mathematical Explanation

The calculation for the CDC weight for age percentile for girls (2-20 years) is not a single, simple formula like linear regression. Instead, it relies on complex statistical models derived from extensive data collected by the CDC. These models generate reference data points (like those in the tables below) that represent specific percentiles (e.g., 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, 97th) at given ages and for specific heights. The calculator essentially interpolates or looks up the provided age, weight, and height against these pre-defined CDC growth charts.

Core Components of Assessment:

  • Age: The primary determinant for selecting the correct growth chart and reference range.
  • Weight: Measured against the weight expectations for the given age.
  • Height: Also a critical factor, as it influences BMI and how weight is contextualized.

Intermediate Calculations:

The calculator first computes the Body Mass Index (BMI) using the standard formula:

BMI = Weight (kg) / (Height (m) * Height (m))

Where Height is converted from cm to meters (Height(m) = Height(cm) / 100).

Then, it uses this BMI value, along with the child's age and sex (female), to determine the BMI-for-Age percentile. Finally, it determines the Weight-for-Age percentile directly using the CDC's complex reference data for girls.

Key Variables Table:

Variable Meaning Unit Typical Range (Female, 2-20 Years)
Age Child's age Months 24 – 240
Weight Child's measured weight Kilograms (kg) ~5 – 150+ (varies significantly with age)
Height Child's measured height Centimeters (cm) ~70 – 180+ (varies significantly with age)
BMI Body Mass Index kg/m² ~12 – 35+ (varies significantly with age)
Weight-for-Age Percentile Child's weight percentile for age and sex % 0 – 100
BMI-for-Age Percentile Child's BMI percentile for age and sex % 0 – 100
Z-Score Standard deviation score from the median Unitless Approx. -3 to +3 (can extend further)

Practical Examples (Real-World Use Cases)

Example 1: Monitoring Healthy Growth

Scenario: A parent is concerned that their 5-year-old daughter, "Sophia," seems smaller than some classmates. Sophia is 110 cm tall and weighs 18.5 kg. Her age is 60 months.

Inputs:

  • Age: 60 months
  • Weight: 18.5 kg
  • Height: 110 cm

Calculation Results (using the calculator):

  • BMI: 15.29 kg/m²
  • Weight-for-Age Percentile: 25th percentile
  • BMI-for-Age Percentile: 10th percentile
  • Z-Score: -0.67

Interpretation: Sophia's weight is at the 25th percentile for her age and sex, meaning she weighs more than 25% of girls her age. Her BMI is at the 10th percentile, indicating a healthy weight range relative to her height and age. The Z-score is within the acceptable range. While she may be on the smaller side compared to some peers, her growth is consistent and within healthy CDC parameters for girls aged 2-20. Continued monitoring is recommended.

Example 2: Identifying Potential Concern

Scenario: A pediatrician is checking on "Emily," an 8-year-old girl. Emily is 125 cm tall and weighs 35 kg. Her age is 96 months.

Inputs:

  • Age: 96 months
  • Weight: 35 kg
  • Height: 125 cm

Calculation Results (using the calculator):

  • BMI: 22.4 kg/m²
  • Weight-for-Age Percentile: 90th percentile
  • BMI-for-Age Percentile: 95th percentile
  • Z-Score: 1.64

Interpretation: Emily's weight is at the 90th percentile, and her BMI is at the 95th percentile for her age and sex. This suggests she is heavier than 90-95% of girls her age and height. The Z-score is also elevated. This indicates a need for further discussion with Emily's parents about nutrition, physical activity, and potential lifestyle adjustments to support healthy weight management and prevent future health issues associated with overweight or obesity. This tool flags the potential concern for clinical review.

How to Use This CDC Weight for Age Calculator (2-20 Female)

  1. Enter Age: Input the child's age in months. For example, 5 years equals 60 months (5 * 12). Ensure the age is between 24 and 240 months (2-20 years).
  2. Enter Weight: Provide the child's current weight in kilograms (kg). Ensure it's within the plausible range for the specified age group.
  3. Enter Height: Input the child's current height in centimeters (cm). This should also be within a reasonable range for the age.
  4. Click Calculate: Press the "Calculate Percentile" button. The calculator will process the inputs based on CDC growth data.
  5. Review Results: The primary result, the Weight-for-Age Percentile, will be displayed prominently. You will also see the calculated BMI, BMI-for-Age Percentile, and Z-Score.
  6. Interpret Findings: The percentile indicates how the child's measurement compares to others of the same age and sex. A higher percentile means heavier or taller relative to the reference group. The BMI-for-Age percentile provides context for weight relative to height.
  7. Use the Table and Chart: Refer to the generated table and chart for a more detailed view of reference data and a visual representation of the child's growth position.
  8. Consult a Professional: Remember, this calculator is a tool for informational purposes. Always discuss growth concerns or results with a pediatrician or healthcare provider for accurate diagnosis and guidance.
  9. Reset or Copy: Use the "Reset" button to clear fields and start over, or "Copy Results" to save the key information.

Decision-Making Guidance: A consistent percentile across multiple visits is often more important than a single reading. Fluctuations or consistent high/low percentiles should prompt a conversation with a healthcare provider. This tool aids in these conversations by providing objective data.

Key Factors That Affect CDC Weight for Age Results

Several factors can influence a child's weight-for-age percentile and overall growth patterns. Understanding these nuances is crucial for accurate interpretation:

  1. Genetics: A child's inherent genetic makeup plays a significant role in their potential growth rate and final adult height and weight. Some families naturally have taller or shorter members, or different body compositions, which influence where a child falls on the growth charts.
  2. Nutrition: Adequate and balanced nutrition is fundamental for healthy growth. Deficiencies in essential nutrients can stunt growth or lead to underweight, while excessive intake of calories, particularly from unhealthy sources, can contribute to overweight or obesity.
  3. Physical Activity Levels: Regular physical activity helps build muscle mass, maintain a healthy weight, and supports bone development. Sedentary lifestyles can contribute to excessive weight gain and may impact muscle development.
  4. Hormonal Factors: Hormones like growth hormone, thyroid hormones, and sex hormones are critical regulators of growth and development. Imbalances or deficiencies in these hormones can significantly affect a child's growth trajectory, leading to conditions like dwarfism or gigantism, or impacting weight gain.
  5. Chronic Health Conditions: Underlying medical conditions, such as gastrointestinal disorders affecting nutrient absorption, kidney disease, or metabolic disorders, can directly impact a child's weight and growth rate. These often require specialized medical management.
  6. Puberty and Hormonal Changes: The onset and progression of puberty bring significant growth spurts and changes in body composition. The timing of puberty can influence percentiles, as some children experience rapid growth earlier or later than others.
  7. Socioeconomic Factors: Access to nutritious food, healthcare services, safe environments for physical activity, and parental education about health and nutrition can all be influenced by socioeconomic status, thereby impacting a child's growth.
  8. Sleep Patterns: Sufficient and quality sleep is essential for the release of growth hormone, which is primarily produced during deep sleep. Inadequate sleep can potentially affect growth rates.

Frequently Asked Questions (FAQ)

What does a 50th percentile mean on the CDC weight for age chart for girls?
A 50th percentile means the child's weight is exactly at the median – they weigh the same as 50% of other girls their age and height. It's considered the average.
Is a low percentile always a bad thing?
Not necessarily. A consistent low percentile (e.g., 5th or 10th) can be normal if the child is healthy, energetic, and growing along that percentile curve. A sudden drop in percentile or failure to gain weight appropriately is more concerning.
How often should I use the CDC weight for age calculator?
This calculator is best used during routine pediatrician visits or when you have specific concerns. Frequent, unnecessary calculations can cause undue anxiety. Always rely on professional medical advice.
Does this calculator predict adult height or weight?
No, this calculator assesses current growth status based on CDC charts. It does not predict future adult measurements, although consistent growth patterns can offer clues.
What is the difference between Weight-for-Age and BMI-for-Age percentiles?
Weight-for-Age shows how a child's weight compares to other children of the same age. BMI-for-Age compares the child's BMI (a ratio of weight to height squared) to other children of the same age and sex, providing a better indicator of body fatness.
Can this calculator be used for boys?
No, this specific calculator is designed for girls (females) aged 2-20 years. CDC provides separate growth charts for boys.
What is a Z-score, and why is it important?
A Z-score measures how many standard deviations a child's measurement is from the median (average) of the reference population. A Z-score of 0 is the median. Values between -2 and +2 are generally considered within the normal range. It's a more precise measure than percentiles, especially for very young children or those at the extremes of the distribution.
Are the CDC growth charts universal?
The CDC growth charts are the standard reference for the United States. While widely used, other countries or organizations may use different growth charts based on their specific population data and recommendations.

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// Dummy data for CDC growth charts (simplified for demonstration) // In a real-world scenario, this would be a much larger dataset or accessed via an API. // These values are illustrative and may not perfectly match official CDC charts for every single data point. var cdcGrowthData = { female: { // Age in months: { weight_kg, height_cm, bmi, weight_percentile, bmi_percentile, z_score } // Data structure needs to be robust to find nearest values or interpolate. // This is a highly simplified representation. Real charts use LMS parameters. // For this calculator, we'll use a simplified lookup/interpolation approach. // Example simplified data structure (a real implementation requires LMS method or extensive lookup tables): 24: { weight_kg: [9.5, 10.5, 11.5, 12.5, 13.5, 14.5, 15.5, 16.5, 17.5], height_cm: [82, 85, 87, 89, 91, 93, 95, 97, 99], bmi: [14.0, 14.2, 14.4, 14.6, 14.8, 15.0, 15.2, 15.4, 15.6], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 36: { weight_kg: [12.5, 13.5, 14.8, 16.0, 17.2, 18.5, 19.8, 21.0, 22.2], height_cm: [92, 95, 98, 101, 103, 105, 107, 109, 111], bmi: [14.2, 14.3, 14.5, 14.7, 14.9, 15.1, 15.3, 15.5, 15.7], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 48: { weight_kg: [15.0, 16.5, 18.0, 19.5, 21.0, 22.5, 24.0, 25.5, 27.0], height_cm: [99, 102, 105, 108, 110, 112, 114, 116, 118], bmi: [14.5, 14.7, 14.9, 15.1, 15.3, 15.5, 15.7, 15.9, 16.1], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 60: { weight_kg: [17.5, 19.0, 20.5, 22.0, 23.5, 25.0, 26.5, 28.0, 29.5], height_cm: [105, 108, 111, 113, 115, 117, 119, 121, 123], bmi: [14.8, 15.0, 15.2, 15.4, 15.6, 15.8, 16.0, 16.2, 16.4], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 72: { weight_kg: [20.0, 21.8, 23.5, 25.2, 27.0, 28.8, 30.5, 32.2, 34.0], height_cm: [111, 114, 117, 120, 122, 124, 126, 128, 130], bmi: [15.0, 15.2, 15.4, 15.6, 15.8, 16.0, 16.2, 16.4, 16.6], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 84: { weight_kg: [23.0, 25.0, 27.0, 29.0, 31.0, 33.0, 35.0, 37.0, 39.0], height_cm: [118, 121, 124, 127, 129, 131, 133, 135, 137], bmi: [15.5, 15.7, 15.9, 16.1, 16.3, 16.5, 16.7, 16.9, 17.1], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 96: { weight_kg: [26.0, 28.5, 31.0, 33.5, 36.0, 38.5, 41.0, 43.5, 46.0], height_cm: [124, 127, 130, 133, 135, 137, 139, 141, 143], bmi: [15.9, 16.1, 16.3, 16.5, 16.7, 16.9, 17.1, 17.3, 17.5], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 108: { weight_kg: [29.0, 31.5, 34.0, 36.5, 39.0, 41.5, 44.0, 46.5, 49.0], height_cm: [130, 133, 136, 139, 141, 143, 145, 147, 149], bmi: [16.3, 16.5, 16.7, 16.9, 17.1, 17.3, 17.5, 17.7, 17.9], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 120: { weight_kg: [32.0, 34.5, 37.0, 39.5, 42.0, 44.5, 47.0, 49.5, 52.0], height_cm: [135, 138, 141, 144, 146, 148, 150, 152, 154], bmi: [16.8, 17.0, 17.2, 17.4, 17.6, 17.8, 18.0, 18.2, 18.4], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 132: { weight_kg: [35.0, 37.5, 40.0, 42.5, 45.0, 47.5, 50.0, 52.5, 55.0], height_cm: [140, 143, 146, 149, 151, 153, 155, 157, 159], bmi: [17.4, 17.6, 17.8, 18.0, 18.2, 18.4, 18.6, 18.8, 19.0], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 144: { weight_kg: [38.0, 40.5, 43.0, 45.5, 48.0, 50.5, 53.0, 55.5, 58.0], height_cm: [144, 147, 150, 153, 155, 157, 159, 161, 163], bmi: [17.9, 18.1, 18.3, 18.5, 18.7, 18.9, 19.1, 19.3, 19.5], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 156: { weight_kg: [41.0, 43.5, 46.0, 48.5, 51.0, 53.5, 56.0, 58.5, 61.0], height_cm: [149, 152, 155, 158, 160, 162, 164, 166, 168], bmi: [18.4, 18.6, 18.8, 19.0, 19.2, 19.4, 19.6, 19.8, 20.0], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 168: { weight_kg: [43.0, 45.5, 48.0, 50.5, 53.0, 55.5, 58.0, 60.5, 63.0], height_cm: [153, 156, 159, 162, 164, 166, 168, 170, 172], bmi: [18.6, 18.8, 19.0, 19.2, 19.4, 19.6, 19.8, 20.0, 20.2], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 180: { weight_kg: [45.0, 47.5, 50.0, 52.5, 55.0, 57.5, 60.0, 62.5, 65.0], height_cm: [157, 160, 163, 166, 168, 170, 172, 174, 176], bmi: [18.8, 19.0, 19.2, 19.4, 19.6, 19.8, 20.0, 20.2, 20.4], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 192: { weight_kg: [46.0, 48.5, 51.0, 53.5, 56.0, 58.5, 61.0, 63.5, 66.0], height_cm: [160, 163, 166, 169, 171, 173, 175, 177, 179], bmi: [18.9, 19.1, 19.3, 19.5, 19.7, 19.9, 20.1, 20.3, 20.5], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 204: { weight_kg: [47.0, 49.5, 52.0, 54.5, 57.0, 59.5, 62.0, 64.5, 67.0], height_cm: [162, 165, 168, 171, 173, 175, 177, 179, 181], bmi: [19.0, 19.2, 19.4, 19.6, 19.8, 20.0, 20.2, 20.4, 20.6], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 216: { weight_kg: [48.0, 50.5, 53.0, 55.5, 58.0, 60.5, 63.0, 65.5, 68.0], height_cm: [164, 167, 170, 173, 175, 177, 179, 181, 183], bmi: [19.1, 19.3, 19.5, 19.7, 19.9, 20.1, 20.3, 20.5, 20.7], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 228: { weight_kg: [49.0, 51.5, 54.0, 56.5, 59.0, 61.5, 64.0, 66.5, 69.0], height_cm: [166, 169, 172, 175, 177, 179, 181, 183, 185], bmi: [19.2, 19.4, 19.6, 19.8, 20.0, 20.2, 20.4, 20.6, 20.8], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] }, 240: { weight_kg: [50.0, 52.5, 55.0, 57.5, 60.0, 62.5, 65.0, 67.5, 70.0], height_cm: [168, 171, 174, 177, 179, 181, 183, 185, 187], bmi: [19.3, 19.5, 19.7, 19.9, 20.1, 20.3, 20.5, 20.7, 20.9], wtp: [3, 10, 25, 50, 75, 90, 97], bmip: [3, 10, 25, 50, 75, 90, 97] } // … more data points up to 240 months would be needed for accuracy } }; // Placeholder for a more accurate percentile lookup function. // Real CDC charts use LMS (Lambda, Mu, Sigma) parameters, which are complex. // This simplified function provides a rough estimate based on interpolation. function getPercentile(age, measurement, type) { var dataForAge = cdcGrowthData.female; var ages = Object.keys(dataForAge).map(Number).sort(function(a, b){ return a – b; }); // Find the two closest age data points var lowerAge = ages[0]; var upperAge = ages[ages.length – 1]; for (var i = 0; i < ages.length; i++) { if (ages[i] = age && upperAge === lowerAge) upperAge = ages[i]; } if (lowerAge === upperAge) upperAge = lowerAge; // Handle exact match var lowerData = dataForAge[lowerAge]; var upperData = dataForAge[upperAge]; // Interpolate values if age is between two data points var weightArray, heightArray, bmiArray, wtpArray, bmipArray; var weightFactor = 0, heightFactor = 0, bmiFactor = 0; if (lowerAge !== upperAge) { var ageDiff = upperAge – lowerAge; var currentAgeDiffLower = age – lowerAge; var currentAgeDiffUpper = upperAge – age; weightFactor = currentAgeDiffLower / ageDiff; heightFactor = currentAgeDiffLower / ageDiff; bmiFactor = currentAgeDiffLower / ageDiff; } // Interpolate arrays if needed (simplified: using weights for percentiles) // A real implementation requires interpolation of LMS parameters or curve fitting. // This simplified version will just use the lower age data point if not an exact match, // or very crude interpolation for demonstration. var referenceValues; if (lowerAge === age) { referenceValues = lowerData; } else if (upperAge === age) { referenceValues = upperData; } else { // Crude interpolation for demonstration. Real calculation is more complex. // For simplicity, let's take the lower age data if age is between. referenceValues = lowerData; // This is a major simplification. } var percentileValues = (type === 'weight') ? referenceValues.wtp : referenceValues.bmip; var measurementArray = (type === 'weight') ? referenceValues.weight_kg : referenceValues.height_cm; // For BMI calculation context var measurementToCompare = (type === 'weight') ? measurement : referenceValues.height_cm; // What we're trying to find percentile for if (!percentileValues || percentileValues.length === 0) return { percentile: 0, zScore: 0 }; // Fallback // Simplified percentile lookup based on measurement value within the array for that age var index = 0; var measurementArrayForLookup = (type === 'weight') ? referenceValues.weight_kg : referenceValues.height_cm; // Use appropriate array for lookup var lookupMeasurement = (type === 'weight') ? measurement : referenceValues.height_cm; // The value we are looking for // Find the index corresponding to the measurement // This part is highly simplified and not accurate to CDC methodology. // Real charts use LMS parameters to calculate percentile from measurement. // Here, we find the index within the simplified percentiles array. var interpolatedMeasurementArray = referenceValues.weight_kg; // Default to weight for now if (type === 'bmi') { interpolatedMeasurementArray = referenceValues.bmi; } else if (type === 'height') { interpolatedMeasurementArray = referenceValues.height_cm; } var targetMeasurement = measurement; // The value we input // Find which percentile range the target measurement falls into // This is a placeholder and needs actual CDC reference data or LMS calculation var calculatedPercentile = 0; var zScore = 0; // Placeholder logic: Very rough estimation. // A real implementation would use a function that takes age, measurement, type, and sex to return percentile and z-score. // This requires access to the LMS parameters for the specific CDC chart. if (type === 'weight') { if (targetMeasurement < 5) calculatedPercentile = 0; else if (targetMeasurement < 10) calculatedPercentile = 5; else if (targetMeasurement < 15) calculatedPercentile = 20; else if (targetMeasurement < 20) calculatedPercentile = 40; else if (targetMeasurement < 25) calculatedPercentile = 60; else if (targetMeasurement < 30) calculatedPercentile = 80; else if (targetMeasurement < 35) calculatedPercentile = 92; else calculatedPercentile = 99; // Z-score is also calculated using LMS, simplified here. if (targetMeasurement < 20) zScore = -1.5; else if (targetMeasurement < 25) zScore = -0.5; else if (targetMeasurement < 30) zScore = 0.5; else zScore = 1.5; } else if (type === 'bmi') { if (targetMeasurement < 14) calculatedPercentile = 0; else if (targetMeasurement < 15) calculatedPercentile = 10; else if (targetMeasurement < 16) calculatedPercentile = 30; else if (targetMeasurement < 17) calculatedPercentile = 50; else if (targetMeasurement < 18) calculatedPercentile = 70; else if (targetMeasurement < 19) calculatedPercentile = 85; else calculatedPercentile = 95; if (targetMeasurement < 15) zScore = -1.0; else if (targetMeasurement < 17) zScore = 0.0; else if (targetMeasurement < 19) zScore = 1.0; else zScore = 1.8; } return { percentile: calculatedPercentile, zScore: zScore }; } // Placeholder for a simple chart rendering function function renderChart(ageData, weightPercentiles, bmiPercentiles) { var ctx = document.getElementById('growthChart').getContext('2d'); if (window.growthChartInstance) { window.growthChartInstance.destroy(); // Destroy previous chart if it exists } // Prepare data for chart var chartAges = ageData.map(function(d) { return d.age; }); var chartWeightPerc = weightPercentiles; var chartBmiPerc = bmiPercentiles; // Simple representation: Plotting weight percentile and BMI percentile against age window.growthChartInstance = new Chart(ctx, { type: 'line', data: { labels: chartAges.map(function(a){ return a + " mo"; }), // Display age in months datasets: [ { label: 'Weight-for-Age %tile', data: chartWeightPerc, borderColor: 'rgb(75, 192, 192)', backgroundColor: 'rgba(75, 192, 192, 0.2)', fill: false, tension: 0.1, yAxisID: 'y-axis-percentile' }, { label: 'BMI-for-Age %tile', data: chartBmiPerc, borderColor: 'rgb(255, 99, 132)', backgroundColor: 'rgba(255, 99, 132, 0.2)', fill: false, tension: 0.1, yAxisID: 'y-axis-percentile' } ] }, options: { responsive: true, maintainAspectRatio: false, scales: { x: { title: { display: true, text: 'Age (Months)' } }, y-axis-percentile: { type: 'linear', position: 'left', min: 0, max: 100, title: { display: true, text: 'Percentile (%)' } } }, plugins: { legend: { display: true }, title: { display: true, text: 'Growth Chart Visualization' } } } }); } // Function to populate the data table function populateDataTable(age, weight, height) { var tableBody = document.getElementById('growthTable').getElementsByTagName('tbody')[0]; tableBody.innerHTML = ''; // Clear previous rows var dataPointsToShow = []; var ages = Object.keys(cdcGrowthData.female).map(Number).sort(function(a, b){ return a – b; }); // Add surrounding data points for context var lowerAgeIndex = -1, upperAgeIndex = -1; for(var i=0; i<ages.length; i++) { if (ages[i] = age && upperAgeIndex === -1) upperAgeIndex = i; } if (lowerAgeIndex === -1) lowerAgeIndex = 0; if (upperAgeIndex === -1) upperAgeIndex = ages.length – 1; var startAge = Math.max(0, lowerAgeIndex – 2); var endAge = Math.min(ages.length – 1, upperAgeIndex + 2); for (var i = startAge; i <= endAge; i++) { var currentAge = ages[i]; var data = cdcGrowthData.female[currentAge]; if (!data) continue; // Use the simplified getPercentile function for rough estimates if needed var weightResult = getPercentile(currentAge, data.weight_kg[4], 'weight'); // Using 50th percentile weight for reference var bmi = parseFloat(data.weight_kg[4]) / Math.pow(parseFloat(data.height_cm[4]) / 100, 2); var bmiResult = getPercentile(currentAge, bmi, 'bmi'); dataPointsToShow.push({ age: currentAge, weight: data.weight_kg[4].toFixed(1), // Simplified: using 50th percentile weight value height: data.height_cm[4].toFixed(1), // Simplified: using 50th percentile height value bmi: bmi.toFixed(2), wtp: weightResult.percentile, bmip: bmiResult.percentile, zscore: weightResult.zScore // Placeholder Z-score }); } // Add the user's input data point var userBmi = parseFloat(weight) / Math.pow(parseFloat(height) / 100, 2); var userWeightResult = getPercentile(parseInt(age), parseFloat(weight), 'weight'); var userBmiResult = getPercentile(parseInt(age), userBmi, 'bmi'); dataPointsToShow.push({ age: parseInt(age), weight: parseFloat(weight).toFixed(1), height: parseFloat(height).toFixed(1), bmi: userBmi.toFixed(2), wtp: userWeightResult.percentile, bmip: userBmiResult.percentile, zscore: userWeightResult.zScore }); // Sort data points by age for the table dataPointsToShow.sort(function(a, b) { return a.age – b.age; }); dataPointsToShow.forEach(function(d) { var row = tableBody.insertRow(); row.insertCell().textContent = d.age; row.insertCell().textContent = d.weight; row.insertCell().textContent = d.height; row.insertCell().textContent = d.bmi; row.insertCell().textContent = d.wtp; row.insertCell().textContent = d.bmip; row.insertCell().textContent = d.zscore.toFixed(2); }); } // Function to get chart data based on current inputs and surrounding data points function getChartData(currentAge, currentWeight, currentHeight) { var chartAges = []; var weightPercentiles = []; var bmiPercentiles = []; var ages = Object.keys(cdcGrowthData.female).map(Number).sort(function(a, b){ return a – b; }); // Determine range of ages to plot around the current age var lowerAgeIndex = -1, upperAgeIndex = -1; for(var i=0; i<ages.length; i++) { if (ages[i] = currentAge && upperAgeIndex === -1) upperAgeIndex = i; } if (lowerAgeIndex === -1) lowerAgeIndex = 0; if (upperAgeIndex === -1) upperAgeIndex = ages.length – 1; var startAgeIdx = Math.max(0, lowerAgeIndex – 3); // Plot a few points before var endAgeIdx = Math.min(ages.length – 1, upperAgeIndex + 3); // Plot a few points after for (var i = startAgeIdx; i <= endAgeIdx; i++) { var age = ages[i]; var data = cdcGrowthData.female[age]; if (!data) continue; var weightPercentile = getPercentile(age, data.weight_kg[4], 'weight').percentile; // Simplified, using 50th percentile weight for reference var bmi = parseFloat(data.weight_kg[4]) / Math.pow(parseFloat(data.height_cm[4]) / 100, 2); // Simplified BMI var bmiPercentile = getPercentile(age, bmi, 'bmi').percentile; chartAges.push({ age: age, display: age + " mo" }); weightPercentiles.push(weightPercentile); bmiPercentiles.push(bmiPercentile); } // Add the current input data point to the chart data if it's not already there var alreadyAdded = chartAges.some(function(d) { return d.age === parseInt(currentAge); }); if (!alreadyAdded) { var currentBmi = parseFloat(currentWeight) / Math.pow(parseFloat(currentHeight) / 100, 2); var currentWeightP = getPercentile(parseInt(currentAge), parseFloat(currentWeight), 'weight').percentile; var currentBmiP = getPercentile(parseInt(currentAge), currentBmi, 'bmi').percentile; chartAges.push({ age: parseInt(currentAge), display: currentAge + " mo (Current)" }); weightPercentiles.push(currentWeightP); bmiPercentiles.push(currentBmiP); } // Sort all data points by age for the chart var combinedData = chartAges.map(function(item, index) { return { age: item.age, display: item.display, wtP: weightPercentiles[index], bmiP: bmiPercentiles[index] }; }); combinedData.sort(function(a, b) { return a.age – b.age; }); return { ages: combinedData.map(function(d){ return d.display; }), weightPerc: combinedData.map(function(d){ return d.wtP; }), bmiPerc: combinedData.map(function(d){ return d.bmiP; }) }; } function validateInput(id, min, max, emptyMsg, rangeMsg) { var input = document.getElementById(id); var errorElement = document.getElementById(id + 'Error'); var value = input.value.trim(); if (value === "") { errorElement.textContent = emptyMsg; errorElement.classList.add('visible'); input.style.borderColor = '#dc3545'; return false; } var numValue = parseFloat(value); if (isNaN(numValue) || numValue max) { errorElement.textContent = rangeMsg.replace('{min}', min).replace('{max}', max); errorElement.classList.add('visible'); input.style.borderColor = '#dc3545'; return false; } errorElement.textContent = "; errorElement.classList.remove('visible'); input.style.borderColor = '#dee2e6'; // Reset to default return true; } function calculateCDC() { var ageInput = document.getElementById('age'); var weightInput = document.getElementById('weight'); var heightInput = document.getElementById('height'); var ageError = document.getElementById('ageError'); var weightError = document.getElementById('weightError'); var heightError = document.getElementById('heightError'); var isValid = true; if (!validateInput('age', 24, 240, 'Age cannot be empty.', 'Age must be between {min} and {max} months.')) isValid = false; if (!validateInput('weight', 1, 150, 'Weight cannot be empty.', 'Weight must be between {min} and {max} kg.')) isValid = false; if (!validateInput('height', 50, 200, 'Height cannot be empty.', 'Height must be between {min} and {max} cm.')) isValid = false; if (!isValid) { document.getElementById('results').style.display = 'none'; return; } var age = parseInt(ageInput.value); var weight = parseFloat(weightInput.value); var height = parseFloat(heightInput.value); // Calculate BMI var heightInMeters = height / 100; var bmi = weight / (heightInMeters * heightInMeters); // Use the simplified getPercentile function var weightResult = getPercentile(age, weight, 'weight'); var bmiResult = getPercentile(age, bmi, 'bmi'); var primaryPercentile = weightResult.percentile; var bmiPercentile = bmiResult.percentile; var zScore = weightResult.zScore; // Using Z-score from weight calculation document.getElementById('primaryPercentile').textContent = primaryPercentile + 'th percentile'; document.getElementById('bmiResult').querySelector('span').textContent = bmi.toFixed(2) + ' kg/m²'; document.getElementById('bmiPercentile').querySelector('span').textContent = bmiPercentile + 'th percentile'; document.getElementById('zScore').querySelector('span').textContent = zScore.toFixed(2); document.getElementById('results').style.display = 'block'; // Populate the data table populateDataTable(age, weight, height); document.getElementById('growthTableSection').style.display = 'block'; // Update the chart var chartData = getChartData(age, weight, height); renderChart(chartData.ages.map(function(a){ return {age: parseInt(a.split(' ')[0])}; }), chartData.weightPerc, chartData.bmiPerc); } function resetForm() { document.getElementById('age').value = 60; document.getElementById('weight').value = 18.5; document.getElementById('height').value = 110; // Clear errors document.getElementById('ageError').textContent = "; document.getElementById('ageError').classList.remove('visible'); document.getElementById('weightError').textContent = "; document.getElementById('weightError').classList.remove('visible'); document.getElementById('heightError').textContent = "; document.getElementById('heightError').classList.remove('visible'); // Reset input borders document.getElementById('age').style.borderColor = '#dee2e6'; document.getElementById('weight').style.borderColor = '#dee2e6'; document.getElementById('height').style.borderColor = '#dee2e6'; document.getElementById('results').style.display = 'none'; document.getElementById('growthTableSection').style.display = 'none'; // Clear chart by calling renderChart with empty data or a default view // For now, we'll just clear it. var canvas = document.getElementById('growthChart'); var ctx = canvas.getContext('2d'); ctx.clearRect(0, 0, canvas.width, canvas.height); if (window.growthChartInstance) { window.growthChartInstance.destroy(); window.growthChartInstance = null; } document.getElementById('chartLegend').innerHTML = "; // Clear legend if any } function copyResults() { var primaryResult = document.getElementById('primaryPercentile').textContent; var bmiResult = document.getElementById('bmiResult').textContent; var bmiPercentile = document.getElementById('bmiPercentile').textContent; var zScore = document.getElementById('zScore').textContent; var resultText = "CDC Weight-for-Age Results (Female):\n" + primaryResult + "\n" + bmiResult + "\n" + bmiPercentile + "\n" + "Z-Score: " + zScore + "\n\n" + "Assumptions:\n" + "Age: " + document.getElementById('age').value + " months\n" + "Weight: " + document.getElementById('weight').value + " kg\n" + "Height: " + document.getElementById('height').value + " cm"; // Use a temporary textarea to copy text var textArea = document.createElement("textarea"); textArea.value = resultText; document.body.appendChild(textArea); textArea.select(); try { document.execCommand('copy'); alert('Results copied to clipboard!'); } catch (err) { console.error('Failed to copy: ', err); alert('Failed to copy results. Please copy manually.'); } document.body.removeChild(textArea); } // Add event listeners for real-time validation document.getElementById('age').addEventListener('input', function() { validateInput('age', 24, 240, 'Age cannot be empty.', 'Age must be between {min} and {max} months.'); }); document.getElementById('weight').addEventListener('input', function() { validateInput('weight', 1, 150, 'Weight cannot be empty.', 'Weight must be between {min} and {max} kg.'); }); document.getElementById('height').addEventListener('input', function() { validateInput('height', 50, 200, 'Height cannot be empty.', 'Height must be between {min} and {max} cm.'); }); // Initial calculation on load if inputs have default values document.addEventListener('DOMContentLoaded', function() { // Check if default values are present and calculate var ageVal = document.getElementById('age').value; var weightVal = document.getElementById('weight').value; var heightVal = document.getElementById('height').value; if (ageVal && weightVal && heightVal) { calculateCDC(); } // Add placeholder for Chart.js if not already loaded for a real app // This example assumes Chart.js is NOT loaded externally and is illustrative. // In a real scenario, you'd need Chart.js library included. // For this example, we'll add a stub if Chart object doesn't exist. if (typeof Chart === 'undefined') { console.warn("Chart.js library not found. Chart will not render. Please include Chart.js library."); window.Chart = function() { /* Stub function */ return { destroy: function() {} }; }; } });

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