Vively member data

How we get our numbers

Vively members share their blood test results, glucose readings and wearable data with us through the app. We combine those numbers, with nothing that identifies anyone, to show how results vary by age and sex and how everyday foods affect blood sugar. This page explains what goes into those charts, how we protect members’ privacy and what the numbers can’t tell you.

What we publish

Every chart on our site that says “Vively member data” comes from one of these sources.

How we protect members’ privacy

• We only ever take totals, medians and percentages out of our database. Individual records stay where they are.
• We show the middle of each group, never the highest or lowest single result.
• Staff and test accounts are left out.
• Members agree to this use of combined, de-identified data in our privacy policy.

How we calculate the numbers

Blood tests

We use each member’s first result for each marker between January 2024 and October 2026, tested at accredited Australian pathology labs. We group results by sex and age at the time of the test (18 to 29, 30 to 39, 40 to 49, 50 to 59 and 60 and over) and report the median, the middle 50% and, where groups are big enough, the 5th to 95th percentiles. Where we count how many people are above or below a level, we name the level, for example “LDL cholesterol of 3.5 mmol/L or higher”.

Glucose after meals

Members wearing a continuous glucose monitor log what they eat in the app. For each meal we take their average glucose over the 4 hours before eating as their baseline, and the highest reading in the 2 hours after as the peak. The rise is the peak minus the baseline, the same calculation members see in the app. We take each member’s typical response first, then the median across members, so people who log a lot count once. Members who told us they have type 2 diabetes are left out.

Wearables

Sleep, heart rate, heart rate variability and VO2 max come from devices members connect to the app. We average each member’s readings over the period first (for example at least 14 nights of sleep), then compare members by age and sex. Different devices measure some things differently: Apple Watch reports heart rate variability as SDNN while most other devices use RMSSD, so we never mix them in one chart.

What the numbers can’t tell you

• Members aren’t a cross-section of Australia. They chose to test their health with Vively, so they may be more health-conscious, or more worried about a symptom, than the average person.
• A comparison is not a diagnosis. Being higher or lower than other members doesn’t mean a result is healthy or unhealthy. The reference range on your own lab report, and your doctor, decide that.
• One test is a snapshot. Many markers change with the time of day, recent food, exercise, illness, the season or the menstrual cycle.
• Some details are self-reported. Menopause status, prediabetes and diabetes come from what members tell us in the app.
• Wearables estimate. Sleep stages, VO2 max and heart rate variability from a watch or ring are estimates, not lab measurements.
• Meals vary. Portion sizes and what else was eaten with a food aren’t standardised, so food results show typical responses, not a laboratory glycaemic index.

Data stories and tools

• Glucose spikes: 38 everyday foods tested on members’ CGMsLive
• How your blood test result compares with members your ageComing soon
• Is my after-meal glucose reading normal?Coming soon

For journalists and researchers

Last updated 14 October 2026. We refresh these numbers every 3 months.