Gloria Aguayo is MD at the Catholic University of Chile, MSc in Nutrition (University of Chile), MSc in Clinical Epidemiology (Erasmus University Rotterdam) and PhD in Public Health at the University of Liège.
In the past, she has been a researcher in the emotional disorders lab participating in innovative virtual reality projects on agoraphobia and body image disruption in patients with severe obesity.
Now, Gloria Aguayo works on the epidemiology of ageing process and type 2 diabetes. In recent years, she has conducted a comprehensive analysis of frailty scores, their reliability and their predictive ability. She has also worked on frailty trajectories and biomarkers of diabetes and showed a longitudinal association of diabetes and its biomarkers with accelerated frailty trajectories on time. A major interest is to use advanced statistical methods in longitudinal cohort studies such as trajectory analysis, time-dependent variables, and multiple imputation to deal with missing data. In addition, she is interested in machine learning techniques applied to epidemiology.
Currently, she works as a scientific manager of CoLIVE Diabetes an international digital cohort dedicated to the health of people with diabetes.
Her activities in CoLIVE Diabetes are the following: establishing the publication strategy, the preparation of a crowdsourcing approach to identify innovative research ideas that matter to people with diabetes and procedures of how to integrate public and people with diabetes in modern epidemiological research, and building the international CoLIVE Diabetes scientific committee (patients associations, researchers, institutions). In addition, she is involved in the supervision of digital health master students focused on the use of digital health in older people or people with disabilities.
She is also working on the ORISLEEP, a project aiming at analysing the association between sleep patterns measured with accelerometers and diabetes biomarkers. This study is a secondary analysis of the ORISCAV-Lux Luxembourgish cohort in the general population.
• NEUROPRED - “Neurodegenerative diseases predictor biomarkers in general population: A machine learning approach”
• NCER-PD - Epidemiologist of "National Centre for Excellence in Research in Parkinson’s Disease" (NCER-PD). Project leader: Prof Rejko Krüger.
• Intricate relationships between frailty and diabetes: where do we go from here?
Aguayo GA, Fagherazzi G.
The Lancet Healthy Longevity. 2020. In Press.
• Identifying hotspots of cardiometabolic outcomes based on a Bayesian approach: The example of Chile.
June 22, 2020
2020 Jun. PLoS One.15(6):e0235009.
By: Aguayo GA Schritz A Ruiz-Castell M Villarroel L Valdivia G Fagherazzi G Witte DR Lawson A.
• Multi-scale multivariate models for small area health survey data: A chilean example.
March 05, 2020
2020 Mar. Int J Environ Res Public Health.17(5).
By: Lawson A, Schritz A, Villarroel L, Aguayo GA.
• Prospective association among diabetes diagnosis, HbA1c, glycemia and frailty trajectories in an elderly population.
October 01, 2019
2019 Oct. Diabetes Care.42(10):1903-1911. Epub 2019 Aug 26.
By:Aguayo GA, Hulman A, Vaillant MT, Donneau AF, Schritz A, Stranges S, Malisoux L, Huiart L, Guillaume M, Sabia S, Witte DR.
• Challenges and benefits of integrating diverse sampling strategies in the observation of cardiovascular risk factors (ORISCAV-LUX 2) study.
February 04, 2019
2019 Feb. BMC Med Res Methodol.19(1):27.
By:Alkerwi A, Pastore J, Sauvageot N, Coroller GL, Bocquet V, d'Incau M, Aguayo G, Appenzeller B, Bejko D, Bohn T, Malisoux L, Couffignal S, Noppe S, Delagardelle C, Beissel J, Chioti A, Stranges S, Schmit JC.
"In an ageing population, it is particularly important
that diabetes is diagnosed as early as possible to
prevent frailty. In addition, the population could be
made more aware of better lifestyles with a healthier
diet and more exercise through increased preventive
measures, thus rising their chances of healthy ageing",
says Gloria Aguayo, MD, PhD,
Scientist Manager of CoLive Diabetes.
1 A-B, rue Thomas Edison
Phone : +352 26 970 770