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 - Fogelstrom, Mathilde

AU - Hulst, Pernille

AU - Brink-Kjaer, Andreas

AU - Henneberg, Kaj-Age

AU - Sorensen, Helge Bjarup Dissing

AU - Dela, Flemming

AU - Helge, Jorn Wulff

PY - 2020

Y1 - 2020

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.

KW - biological age

KW - health promotion

KW - protocol

KW - healthy aging

KW - principal component analysis

KW - LOWER-EXTREMITY FUNCTION

KW - LIFE-STYLE INTERVENTION

KW - BODY-MASS INDEX

KW - SKIN AUTOFLUORESCENCE

KW - METABOLIC SYNDROME

KW - CARDIOVASCULAR-RESPONSES

KW - CLINICAL BIOMARKERS

KW - WAIST CIRCUMFERENCE

KW - INSULIN-RESISTANCE

KW - PHYSICAL-ACTIVITY

U2 - 10.2196/19209

DO - 10.2196/19209

M3 - Journal article

C2 - 33104001

VL - 9

JO - J M I R Research Protocols

JF - J M I R Research Protocols

SN - 1929-0748

IS - 10

M1 - 19209

ER -