Blood Pressure (Diastolic)

Diastolic pressure is the lower number, reflecting arterial pressure between heart contractions. Blood pressure is normally written as systolic/diastolic, such as 120/80 mmHg. Interpret both numbers together: one component alone can miss an elevated reading in the other.

HealthKit supports separate quantity samples and a blood-pressure correlation that groups the components. A matching timestamp in an exported database does not prove membership in that correlation. See Blood Pressure for the pairing distinction.

The October 2025–September 2026 research window contained 39 diastolic samples on 17 reporting days, recorded in January and April. July–September contained none. This describes available records, not year-round monitoring or a clinical baseline.

The figure keeps systolic and diastolic distributions separate. Repeated timestamps are retained rather than silently deduplicated. A recording source describes the app that wrote the data; it does not establish the cuff, operator, posture or clinical setting.

There is no universal HealthKit schedule. A connected monitor may upload a reading after each cuff measurement, while an app or automation can log imported or manually entered values. In these records, the automation-source median positive start gap was approximately 24 hours, compared with 155 seconds in the tracking-app source. Both summaries include gaps between sessions, so neither is a recommended measurement interval.

Ten successive automation-source starts had zero timestamp gaps. The shortest positive tracking-app gap was one second, and the longest automation-source gap was about 79 days. Such patterns call for checking entry/import behavior before treating every row as a fresh cuff inflation.

Recording in the morning does not prove a standardized resting measurement. The saved observations do not supply all of the measurement conditions needed for a like-for-like comparison.

For comparable home readings, the American Heart Association recommends a validated monitor, correct cuff size, a quiet seated rest, supported positioning and repeated readings. Record the conditions consistently; exercise-adjacent measurements should not be pooled indiscriminately with rested home measurements.

Four of ten tracking-app diastolic rows exceeded that small source/context group’s 1.5-IQR fences; all were retained. No automation-source rows were flagged. Narrow distributions can make modest differences look statistically unusual. A statistical flag is not a diagnosis. Conversely, a value can need clinical review without being unusual within this small dataset. Recheck unexpected values against the original device, technique, units and symptoms.

These AHA categories use mmHg and should be assessed with repeated, properly obtained readings. They do not diagnose hypertension from an isolated HealthKit row; individual treatment targets may differ. Blood pressure above 180 systolic and/or 120 diastolic requires prompt reassessment and medical advice. With symptoms such as chest pain, shortness of breath or new neurological symptoms, seek emergency care.

Compare with Systolic Blood Pressure using verified paired measurements where available. Here, exact start/end/source matching produced 59 candidate combinations from 39 records per component, because some matching keys were duplicated. Assigning a unique pulse pressure or blood-pressure category to those combinations would invent pairing evidence.

Source-specific reporting-day medians allowed an exploratory systolic–diastolic comparison across 16 days in the automation source. That is a day-level relationship, not 16 confirmed cuff-reading pairs. Resting heart rate and body mass can provide broader context, but sparse overlapping days, app changes and inconsistent measurement conditions prevent causal conclusions.

Keep raw components, source revisions, units, timestamps and any actual correlation membership separate. Inspect duplicate keys before joining, use the same reporting calendar, and distinguish zero-duration observations from continuous monitoring. Compute visit or day summaries only after deciding how repeated measurements and imports should be handled. A source change or recording gap may explain a trend more readily than a physiological change.