Insights and takeaways
In the previously mentioned observational multivariate analysis3, we were able to find a clear difference in baseline, real-world levels of metabolic score and glycemic fitness in healthy and pre-diabetic Indians/SouthAsians. The question that remained was whether these metrics could be harnessed in an interventional mode for focussed fitness improvement regimes and whether tangible benefits could be derived in relatively short time intervals. Additionally, it was unclear how much real world engagement and adherence is found in a largely healthy demographic3,4. This latter feature is related to consistency and discipline that translates to
tangible results but is usually not used as a stratification tool in clinical or real-world data studies in the metabolic fitness domain5,6. We found that:
With the broadest inclusion criteria and design that allowed discontinuation at any time, we found a consistent decrease in average blood glucose across four weeks.
More than a third of the enrolled individuals did not engage, alluding the high barriers in daily life that inhibit commencing lifestyle changes. This supports the Ultrahuman approach of passive health monitoring and trying to minimise the effort required from the user. There is merit in examining adherence rates in larger cohorts and dissecting the factors driving drop-outs in such heterogeneous groups.
Among those who did complete three weeks or more of the bootcamps, it was a challenge to maintain and consistently prioritise healthy choices, which reflected in a flattened whole-group response over time.
Of those who did improve or showed higher engagement levels, there was far less variability of change in metabolic score and glucose values consistently, as indicated by the high statistical significance in the paired t-tests. This trend was also mirrored in the estimated HbA1c metric computed by the M1 platform based on the ADA formula7.
Since CGM provides a direct and dynamic insight into glucose levels, the effect is most pronounced in these metrics. User feedback did mention improved productivity and sleep patterns but the feedback received was for a small fraction of active participants.
In summary, this Ultra30 bootcamp did not focus on prescriptive food or exercise changes, but rather on improving awareness and user understanding of their own physiology and tools to measure it. Even in this mildly directive design, we found that for healthy Indians, significant improvements can be achieved in glucose metabolism (mean glucose, time in range, metabolic score, estimated HbA1c), provided there is a minimum of three to four weeks of engaged participation.
Future studies with improved sensors and data collection streams, coupled with multi-tiered analyses, is hoped to increase the amplitude of positive changes observed translating to benefits in larger populations.
