Gary Wolf

May 29, 2018

At the 2018 Quantified Self Symposium, Azure Grant presented some of the discoveries from the QS Blood Testers project, showing data that suggests a single point measure may be inadequate for understanding cardiovascular risk. In the Blood Testers group, every participant crossed a CVD risk category by time of day in at least one lipid output. And 80% of participants crossed a risk category based on time of day when only fasting measurements were considered. Blood Testers data also showed that this lipid variability isn’t random, but is structured on the timescales of hours, days, and across the ovulatory cycle. These insights were gained using data from very high frequency measurement — sometimes as often as once per hour — and none of this could have happened without dedicated participants asking questions they cared about, with access to their own data.