Health Data Sources

SuperAge integrates with Apple Health to access a wide variety of health metrics. This reference guide details every data type used, its importance for biological age calculation, and how to ensure optimal data quality.

Primary Data Categories

Heart Rate Data ❤️

Heart rate patterns are among the strongest predictors of biological age and cardiovascular health.

Resting Heart Rate

HealthKit Identifier: HKQuantityTypeIdentifierRestingHeartRate Importance: High - Primary cardiovascular health indicator Optimal Range:

Adults: 60-100 bpm (lower generally better for fitness)
Athletes: 40-60 bpm
Age-adjusted expectations

Data Sources:

Apple Watch (primary)
Compatible chest straps
Blood pressure monitors with HR
Manual entry possible

Quality Factors:

Consistency of measurement timing
Device calibration accuracy
Environmental factors (caffeine, stress, illness)

Heart Rate Variability (HRV)

HealthKit Identifier: HKQuantityTypeIdentifierHeartRateVariabilitySDNN Importance: Very High - Autonomic nervous system health Optimal Range: Highly individual, focus on personal trends

Typical adult range: 20-50ms SDNN
Higher variability often indicates better fitness

Data Sources:

Apple Watch Series 1+ (during sleep and breathe sessions)
Chest straps (more accurate for training)
Specialized HRV apps

Measurement Notes:

Best measured during consistent conditions
Sleep HRV most reliable
Affected by stress, alcohol, recovery status

Exercise Heart Rate

HealthKit Identifier: HKQuantityTypeIdentifierHeartRate (during workouts) Importance: High - Cardiovascular fitness assessment Key Metrics:

Maximum heart rate during exercise
Heart rate zones distribution
Recovery heart rate post-exercise

Analysis Factors:

Exercise type and intensity
Environmental conditions
Fitness level adaptations
Recovery patterns

Physical Activity Data 🏃‍♀️

Activity metrics provide insights into daily movement patterns and exercise habits.

Step Count

HealthKit Identifier: HKQuantityTypeIdentifierStepCount Importance: Medium-High - Basic activity level indicator Optimal Targets:

General health: 7,000-10,000+ steps/day
Active individuals: 12,000+ steps/day
Quality matters more than quantity

Data Sources:

iPhone motion sensors
Apple Watch (more accurate)
Third-party fitness trackers
Manual entry for specific activities

Considerations:

Step quality (pace, terrain, intentionality)
Distribution throughout day vs. concentrated
Seasonal and weather variations

Active Energy (Calories)

HealthKit Identifier: HKQuantityTypeIdentifierActiveEnergyBurned Importance: High - Metabolic activity assessment Calculation Basis:

Movement intensity and duration
Body weight and composition
Heart rate elevation
Environmental factors

Accuracy Factors:

Device calibration with personal metrics
Consistent wearing of devices
Activity type recognition
Individual metabolic variations

Exercise Minutes

HealthKit Identifier: HKQuantityTypeIdentifierAppleExerciseTime Importance: High - Structured activity assessment Definition: Minutes of activity ≥ brisk walk intensity Target: 150+ minutes/week moderate activity

Quality Indicators:

Consistency throughout week
Distribution of intensity levels
Recovery time between sessions
Progressive improvements

Flights Climbed

HealthKit Identifier: HKQuantityTypeIdentifierFlightsClimbed Importance: Medium - Functional fitness indicator Measurement: Approximately 10 feet of elevation gain Benefits: Indicates leg strength, cardiovascular capacity

Sleep Analysis Data 😴

Sleep quality significantly impacts biological age and recovery.

Sleep Duration

HealthKit Identifier: HKCategoryTypeIdentifierSleepAnalysis Importance: Very High - Recovery and health maintenance Optimal Ranges:

Adults (18-64): 7-9 hours
Older adults (65+): 7-8 hours
Individual variation ±1 hour

Quality Factors:

Consistency of sleep schedule
Sleep debt accumulation
Weekend vs. weekday patterns

Sleep Quality Metrics

Advanced Sleep Apps Provide:

Sleep efficiency (time asleep/time in bed)
Sleep stages (light, deep, REM)
Sleep latency (time to fall asleep)
Number of awakenings

Key Indicators:

Sleep efficiency >85% optimal
15-20% deep sleep ideal
REM sleep 20-25% of total
<30 minutes to fall asleep

Body Metrics Data ⚖️

Body composition trends provide metabolic health insights.

Body Weight

HealthKit Identifier: HKQuantityTypeIdentifierBodyMass Importance: Medium - Metabolic stability indicator Analysis Focus:

Trend stability over time
Rate of change (gradual vs. rapid)
Correlation with activity changes
Seasonal variations

Data Sources:

Smart scales (automatic sync)
Manual entry
Healthcare provider measurements
Fitness facility assessments

Body Mass Index (BMI)

HealthKit Identifier: HKQuantityTypeIdentifierBodyMassIndex Importance: Medium - Basic health risk assessment Categories:

Underweight: <18.5
Normal: 18.5-24.9
Overweight: 25-29.9
Obese: ≥30

Limitations:

Doesn’t account for muscle mass
Less accurate for athletes
Population-based, not individual optimal

Body Fat Percentage

HealthKit Identifier: HKQuantityTypeIdentifierBodyFatPercentage Importance: High when available - Body composition quality Healthy Ranges:

Men: 10-20% (athletes 6-13%)
Women: 16-24% (athletes 14-20%)

Measurement Methods:

Bioelectrical impedance scales
DEXA scans (most accurate)
Hydrostatic weighing
Bod Pod assessments

Advanced Data Sources

Respiratory Metrics 🫁

Breathing patterns provide insights into cardiovascular health and sleep quality.

Respiratory Rate

HealthKit Identifier: HKQuantityTypeIdentifierRespiratoryRate Importance: Medium - Health status indicator Normal Range: 12-20 breaths per minute at rest Measurement: Apple Watch during sleep (Series 3+)

Blood Oxygen Saturation

HealthKit Identifier: HKQuantityTypeIdentifierOxygenSaturation Importance: Medium-High when available Normal Range: 95-100% at sea level Device: Apple Watch Series 6+ (background and on-demand)

Environmental Data 🌡️

Environmental factors can influence health metrics and biological age.

Noise Exposure

HealthKit Identifier: HKQuantityTypeIdentifierEnvironmentalAudioExposure Importance: Low-Medium - Environmental health factor Safe Levels: <85 dB average daily exposure Source: Apple Watch Noise app

UV Exposure

Future Integration: Planned for enhanced environmental assessment Importance: Medium - Skin health and vitamin D factors

Nutrition and Hydration 🍎

When available, nutrition data enhances biological age accuracy.

Dietary Energy (Calories Consumed)

HealthKit Identifier: HKQuantityTypeIdentifierDietaryEnergyConsumed Importance: Medium - Energy balance assessment Sources: Food tracking apps (MyFitnessPal, Lose It!)

Water Intake

HealthKit Identifier: HKQuantityTypeIdentifierDietaryWater Importance: Low-Medium - Basic hydration tracking Target: ~8 glasses/day (varies by activity and climate)

Macronutrients

Available Types:

Dietary Protein, Carbohydrates, Fat
Individual amino acids and fatty acids
Vitamins and minerals

Usage: When comprehensive data available, used for metabolic health assessment

Data Quality Requirements

Minimum Data for Calculation

Essential (Required):

Heart rate data (7+ days)
Step count (7+ days)
Sleep duration (5+ nights)

Highly Recommended:

Apple Watch wearing 20+ hours daily
Exercise heart rate data
HRV measurements
Body weight trends

Optimal (Best Accuracy):

All essential + recommended data
30+ days of consistent collection
Advanced sleep stage data
Body composition metrics

Data Validation Process

Outlier Detection:

Statistical anomaly identification
Cross-metric consistency checks
Temporal pattern validation
Device-specific calibration

Missing Data Handling:

Interpolation for short gaps (<24 hours)
Reduced confidence scores for larger gaps
Alternative metric weighting when available
Historical pattern-based estimation

Data Source Priority

When Multiple Sources Available:

Apple Watch (highest priority for most metrics)
Connected smart devices (scales, blood pressure monitors)
iPhone sensors (steps, stairs when Watch unavailable)
Third-party apps (sleep, nutrition tracking)
Manual entry (backup for key metrics)

Privacy and Data Handling

Data Access Permissions

Read-Only Access:

SuperAge only reads health data
Never writes or modifies Apple Health data
Permissions can be revoked at any time

Granular Control:

Individual data type permissions
User can enable/disable specific categories
Partial access still provides biological age estimation

Local Processing

On-Device Analysis:

All calculations performed locally
No health data transmitted to servers
Model updates don’t include personal data

Data Retention:

SuperAge accesses historical Health data
No independent data storage
Uses Apple Health as single source of truth

Integration Guidelines

For Developers

HealthKit Integration:

Request minimum necessary permissions
Handle permission changes gracefully
Respect user privacy preferences
Follow Apple’s HealthKit guidelines

Data Quality Best Practices:

Validate data before processing
Handle missing data appropriately
Provide user feedback on data quality
Update algorithms based on available data

For technical questions about data integration or specific HealthKit implementations, contact our development team at developers@superage.app.