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University of Cambridge

Inclusive and adaptive assessment of cardiorespiratory fitness for population health research

Abstract

dc:description.abstract

This thesis addresses the challenge of measuring cardiorespiratory fitness (i.e., fitness) in large population studies, overcoming logistical constraints and safety considerations associated with exercise testing that often lead to selection bias and distorted health associations. It presents the development, validation, and application of a comprehensive suite of fitness assessment methods that are applicable in diverse population groups, enabling more inclusive, adaptive, and robust research. In the UK Biobank study, I develop and validate a novel approach to estimate fitness in approximately 80,000 adults who performed a risk-stratified cycle ergometer test. I then apply this method to examine associations with mortality, cardiovascular disease, type 2 diabetes, and cancer. In the Fenland study, I validate and apply a ramped treadmill test for estimating fitness in approximately 10,000 adults, revealing the importance of physical activity and body size on population variation in fitness. I validate the use of heart rate response during a self-paced walk test for estimating fitness and habitual physical activity. I investigate the use of resting heart rate as a biomarker of fitness, applying this approach in half a million UK Biobank study participants to explore its relationship with cardiovascular disease. Finally, I harmonise these methods into a generalised fitness estimation framework that can be adapted to various exercise testing scenarios, enhancing the field's ability to assess fitness in population research. Overall, this work not only advances our understanding of fitness's impact on health outcomes in population research but also lays the groundwork for global health surveillance, employing inclusive methodologies that reinforce the role of fitness in mitigating chronic disease outcomes.

Degree

thesis:*
Name dc:type.qualificationname
Doctor of Philosophy (PhD)
Level dc:type.qualificationlevel
Doctoral
Grantor dc:publisher.institution
University of Cambridge
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gonzales, Tomas
Advisor dc:contributor.advisor
  • Brage, Soren

Subjects

dc:subject × 6

Rights

dc:rights
Language dc:language
eng

Identifiers

dc:identifier.*
Author Identifier
0000-0003-0085-8771
OAI identifier oai:identifier
oai:www.repository.cam.ac.uk:1810/370307

Chain of custody

source
Harvested from
Cambridge University
Base URL
api.repository.cam.ac.uk/server/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Gonzales, Tomas. Inclusive and adaptive assessment of cardiorespiratory fitness for population health research. Doctoral thesis, University of Cambridge, 2024. https://doi.org/10.17863/CAM.109762