TY - JOUR
T1 - A Biological Age Model Designed for Health Promotion Interventions
T2 - Protocol for an Interdisciplinary Study for Model Development
AU - Husted, Karina Louise Skov
AU - Fogelstrøm, Mathilde
AU - Hulst, Pernille
AU - Brink-Kjær, Andreas
AU - Henneberg, Kaj-Åge
AU - Sorensen, Helge Bjarup Dissing
AU - Dela, Flemming
AU - Helge, Jørn Wulff
N1 - ©Karina Louise Skov Husted, Mathilde Fogelstrøm, Pernille Hulst, Andreas Brink-Kjær, Kaj-Åge Henneberg, Helge Bjarup Dissing Sørensen, Flemming Dela, Jørn Wulff Helge. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 26.10.2020.
PY - 2020/10/26
Y1 - 2020/10/26
N2 - BACKGROUND: Actions to improve healthy aging and delay morbidity are crucial, given the global aging population. We believe that biological age estimation can help promote the health of the general population. Biological age reflects the heterogeneity in functional status and vulnerability to disease that chronological age cannot. Thus, biological age assessment is a tool that provides an intuitively meaningful outcome for the general population, and as such, facilitates our understanding of the extent to which lifestyle can increase health span.OBJECTIVE: This interdisciplinary study intends to develop a biological age model and explore its usefulness.METHODS: The model development comprised three consecutive phases: (1) conducting a cross-sectional study to gather candidate biomarkers from 100 individuals representing normal healthy aging people (the derivation cohort); (2) estimating the biological age using principal component analysis; and (3) testing the clinical use of the model in a validation cohort of overweight adults attending a lifestyle intervention course.RESULTS: We completed the data collection and analysis of the cross-sectional study, and the initial results of the principal component analysis are ready. Interpretation and refinement of the model is ongoing. Recruitment to the validation cohort is forthcoming. We expect the results to be published by December 2021.CONCLUSIONS: We expect the biological age model to be a useful indicator of disease risk and metabolic risk, and further research should focus on validating the model on a larger scale.
AB - BACKGROUND: Actions to improve healthy aging and delay morbidity are crucial, given the global aging population. We believe that biological age estimation can help promote the health of the general population. Biological age reflects the heterogeneity in functional status and vulnerability to disease that chronological age cannot. Thus, biological age assessment is a tool that provides an intuitively meaningful outcome for the general population, and as such, facilitates our understanding of the extent to which lifestyle can increase health span.OBJECTIVE: This interdisciplinary study intends to develop a biological age model and explore its usefulness.METHODS: The model development comprised three consecutive phases: (1) conducting a cross-sectional study to gather candidate biomarkers from 100 individuals representing normal healthy aging people (the derivation cohort); (2) estimating the biological age using principal component analysis; and (3) testing the clinical use of the model in a validation cohort of overweight adults attending a lifestyle intervention course.RESULTS: We completed the data collection and analysis of the cross-sectional study, and the initial results of the principal component analysis are ready. Interpretation and refinement of the model is ongoing. Recruitment to the validation cohort is forthcoming. We expect the results to be published by December 2021.CONCLUSIONS: We expect the biological age model to be a useful indicator of disease risk and metabolic risk, and further research should focus on validating the model on a larger scale.
U2 - 10.2196/19209
DO - 10.2196/19209
M3 - Journal article
C2 - 33104001
SN - 1929-0748
VL - 9
JO - J M I R Research Protocols
JF - J M I R Research Protocols
IS - 10
M1 - e19209
ER -