Health Insight and Age Estimation API

API ID 6826

The Health Insight and Age Estimation API analyzes input values to classify individuals as 'Adult' or 'Senior' and predicts their approximate age. Utilizing advanced Machine Learning techniques for both classification and regression tasks, this API offers valuable insights into age demographics. For further details about the underlying model, please reach out to us.

100% uptime 232 ms avg response

API Documentation

Endpoints

Request
EXAMPLE USE OF "/nutrition" endpoint for required input parameters:
Endpoint ID: 10317
GET https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10317/nutrition
INPUT PARAMETERS

Nutrition — Endpoint Features

Object Description
DIQ010 Required If the Respondent is diabetic
LBXGLT Required Respondent's Oral Microbiome Tests
LBXGLU Required Respondent's Blood Glucose after fasting
LBXIN Required Respondent's Blood Insulin Levels
PAQ605 Required If the respondent engages in moderate or vigorous-intensity sports, fitness, or recreational activities in the typical week (a 1 represents that the respondent takes part in weekly moderate or vigorous-intensity physical activity and a 2 represents that they do not)
RIAGENDR Required Respondent's Gender (a 1 represents Male and 2 represents Female)
BMXBMI Required Respondent's Body Mass Index

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

DIQ010
LBXGLT
LBXGLU
LBXIN
PAQ605
RIAGENDR
BMXBMI
API EXAMPLE RESPONSE
JSON
EXAMPLE CALL:
    
/nutrition?RIAGENDR=1&PAQ605=2&BMXBMI=38.9&LBXGLU=89&DIQ010=2&LBXGLT=113&LBXIN=17.47

    RES:
        {
          "Age Prediction": "34.516617",
          "Value Prediction": "Adult"
        }
Nutrition — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10317/nutrition?DIQ010=Required&LBXGLT=Required&LBXGLU=Required&LBXIN=Required&PAQ605=Required&RIAGENDR=Required&BMXBMI=Required' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request

List all vars and possible values.

Endpoint ID: 10318
GET https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10318/listallvars
INPUT PARAMETERS

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

This endpoint does not require any input parameters.

API EXAMPLE RESPONSE
JSON
{
  "BMXBMI": "Respondent's Body Mass Index",
  "DIQ010": "If the Respondent is diabetic",
  "LBXGLT": "Respondent's Oral Microbiome Tests",
  "LBXGLU": "Respondent's Blood Glucose after fasting",
  "LBXIN": "Respondent's Blood Insulin Levels",
  "PAQ605": "If the respondent engages in moderate or vigorous-intensity sports, fitness, or recreational activities in the typical week (a 1 represents that the respondent takes part in weekly moderate or vigorous-intensity physical activity and a 2 represents that they do not)",
  "RIAGENDR": "Respondent's Gender (a 1 represents Male and 2 represents Female)"
}
Listallvars — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10318/listallvars' --header 'Authorization: Bearer YOUR_API_KEY' 


    
Request

Info for this API ()

Endpoint ID: 10319
GET https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10319/info
INPUT PARAMETERS

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

This endpoint does not require any input parameters.

API EXAMPLE RESPONSE
JSON
{
  "API Info:": "This API requests per values provide class result ('Adult' or 'Senior'), and also a value for individual predicted Age. The AI algorithm consists of ML (Machine Learning) techniques either for Classification or Regression tasks. Please contact us for more information about the model. We acknowledge the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC) for providing this Dataset."
}
Info — CODE SNIPPETS

curl --location --request GET 'https://zylalabs.com/api/6826/health+insight+and+age+estimation+api/10319/info' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Health Insight and Age Estimation API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Overview

This API requests per values provide the class result ('Adult' or 'Senior'), and also a value for the individual predicted Age. The AI algorithm consists of ML (Machine Learning) techniques, either for Classification or Regression tasks. Please contact us for more information about the model. We acknowledge the National Center for Health Statistics (NCHS) at the Centers for Disease Control and Prevention (CDC) for providing this Dataset

Health Insight and Age Estimation API FAQs

The GET Nutrition endpoint returns an age prediction and a classification result ('Adult' or 'Senior') based on input health metrics. The GET listallvars endpoint provides a list of variables and their descriptions, while the GET info endpoint offers general information about the API's functionality and data sources.

The key fields in the GET Nutrition response include "Age Prediction," which indicates the estimated age, and "Value Prediction," which classifies the individual as either 'Adult' or 'Senior'. The listallvars endpoint returns variable names and descriptions.

The GET Nutrition endpoint accepts parameters such as RIAGENDR (gender), PAQ605 (physical activity level), BMXBMI (Body Mass Index), LBXGLU (blood glucose), DIQ010 (diabetes status), LBXGLT (oral microbiome tests), and LBXIN (blood insulin levels). Users can customize requests by providing specific values for these parameters.

The response data from the GET Nutrition endpoint is structured as a JSON object containing two main fields: "Age Prediction" (a numerical value) and "Value Prediction" (a string indicating 'Adult' or 'Senior'). This format allows for easy parsing and integration into applications.

The data utilized by the Health Insight and Age Estimation API is sourced from the National Center for Health Statistics (NCHS) at the CDC. This ensures that the dataset is reliable and representative of health demographics.

Typical use cases for this API include health assessments, demographic analysis, and personalized health recommendations. Researchers and developers can leverage the age classification and prediction to tailor health interventions or marketing strategies.

Users can utilize the returned data by integrating the age prediction and classification into health applications, enabling targeted health advice or interventions. For example, a fitness app could adjust workout plans based on the predicted age and activity level.

Data accuracy is maintained through the use of advanced Machine Learning techniques for classification and regression tasks. Continuous model training and validation against reliable datasets, such as those from the CDC, help ensure the predictions remain accurate and relevant.

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