HealthCorrelation# PRO

The HealthCorrelation class represents a group of health samples that are logically related. It provides an interface for accessing and creating correlation records that group multiple health data types together—such as combining dietary intake and blood pressure readings, or linking ovulation tests with menstrual flow records.

#Use Cases

• Grouping blood pressure systolic and diastolic values together
• Associating food intake with nutritional data
• Creating a composite record for cycle tracking events

#Properties

#Static Method

#HealthCorrelation.create(options): HealthCorrelation | null

Creates a new correlation with one or more health samples.

#Parameters

#Returns

• A new HealthCorrelation instance if the parameters are valid.
• Returns null if the type and samples are incompatible or validation fails.

#Examples

#Example 1: Create a blood pressure correlation

const systolic = HealthQuantitySample.create({
  type: "bloodPressureSystolic",
  startDate: new Date("2025-07-04T08:00:00"),
  endDate: new Date("2025-07-04T08:01:00"),
  value: 120,
  unit: HealthUnit.millimeterOfMercury()
})

const diastolic = HealthQuantitySample.create({
  type: "bloodPressureDiastolic",
  startDate: new Date("2025-07-04T08:00:00"),
  endDate: new Date("2025-07-04T08:01:00"),
  value: 80,
  unit: HealthUnit.millimeterOfMercury()
})

const correlation = HealthCorrelation.create({
  type: "bloodPressure",
  startDate: systolic.startDate,
  endDate: systolic.endDate,
  objects: [systolic, diastolic]
})

if (correlation) {
  // save correlation...
}

#Example 2: Query and inspect a correlation

for (const sample of correlation.quantitySamples) {
  const value = sample.quantityValue(HealthUnit.millimeterOfMercury())
  console.log(`${sample.quantityType}: ${value}`)
}

#Notes

• Samples in a correlation must match the expected types for the given HealthCorrelationType.
• Currently supported correlation types include "bloodPressure" and "food".
• This class allows grouping samples for higher-level reasoning or visualization of composite health events.