Fig. 1: Study design and data summary.
From: Insulin resistance prediction from wearables and routine blood biomarkers
a, Overview of physiological factors and associated lifestyle factors leading to IR, prediabetes and diabetes. b, Our proposed modelling pipeline for predicting HOMA-IR and interpreting the results with the insulin resistance literacy and understanding agent (IR agent). c, Correlation of blood biomarkers and lifestyle features (continuous values) with HOMA-IR. d–f, Distribution of the top three features of wearables that are highly correlated with HOMA-IR (RHR (d), daily step counts (e) and HRV (f)) for stratified insulin sensitivity groups (IS, impaired-IS and IR). RMSSD, root mean square of successive differences. g–i, Distribution of the top three highly correlated blood biomarkers (triglycerides (g), HDL cholesterol (h) and albumin/globulin ratio (i)) for stratified insulin sensitivity groups. In the box plots in d–i, the centre line indicates the median, the bounds of box represent the 25th and 75th percentiles and the whiskers extend to 1.5 times the interquartile range. j, Scatter plot of BMI and HOMA-IR values, showing the relationship between higher BMI values and IR (measured through HOMA-IR). k, Confusion matrix showing the number of participants in each combination of IR status and diabetes status.
