GLU: A software package for analysing continuously measured glucose levels in epidemiology

Louise A C Millard*, Nashita Patel, Kate M Tilling, Melanie Lewcock, Peter A Flach, Debbie A Lawlor

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

9 Citations (Scopus)
50 Downloads (Pure)


Continuous glucose monitors (CGM) record interstitial glucose levels ‘continuously’, producing a sequence of measurements for each participant (e.g. the average glucose level every 5 min over several days, both day and night). To analyse these data, researchers tend to derive summary variables such as the area under the curve (AUC), to then use in subsequent analyses. To date, a lack of consistency and transparency of precise definitions used for these summary variables has hindered interpretation, replication and comparison of results across studies. We present GLU, an open-source software package for deriving a consistent set of summary variables from CGM data. GLU performs quality control of each CGM sample (e.g. addressing missing data), derives a diverse set of summary variables (e.g. AUC and proportion of time spent in hypo-, normo- and hyper- glycaemic levels) covering six broad domains, and outputs these (with quality control information) to the user. GLU is implemented in R and is available on GitHub at Git tag v0.2 corresponds to the version presented here.
Original languageEnglish
Pages (from-to)744-757
Number of pages14
JournalInternational Journal of Epidemiology
Issue number3
Publication statusPublished - 13 Feb 2020


  • Glucose
  • continuous glucose monitoring
  • CGM
  • BMI
  • pregnancy


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