{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/370307"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/370307","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Inclusive and adaptive assessment of cardiorespiratory fitness for population health research","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Gonzales, Tomas"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Brage, Soren"],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-03-13","date_published":"2024-03-13","updated_at":"2026-07-22T22:23:54Z","subjects":["cardiorespiratory fitness","cardiovascular disease","epidemiology","exercise testing","physical activity","resting heart rate"],"languages":["eng"],"rights":[],"rights_urls":["https://www.repository.cam.ac.uk/bitstreams/8c82ec40-6154-4aaa-a36e-37d7e1237af5/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"identifier_entries":[{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000300858771"],"render_values":[{"text":"0000-0003-0085-8771","href":"https://orcid.org/0000-0003-0085-8771","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.109762","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Brage, Soren"]},{"key":"dc:creator","label":"Author","values":["Gonzales, Tomas"]},{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000300858771"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2024-03-13"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/370307"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["cardiorespiratory fitness","cardiovascular disease","epidemiology","exercise testing","physical activity","resting heart rate"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://www.repository.cam.ac.uk/bitstreams/8c82ec40-6154-4aaa-a36e-37d7e1237af5/download","https://www.rioxx.net/licenses/all-rights-reserved/"]},{"key":"dc:rights.embargodate","label":"Dc Rights Embargodate","values":["2026-07-04"]},{"key":"dc:rights.embargotype","label":"Dc Rights Embargotype","values":["embargo"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.17863/CAM.109762"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://www.repository.cam.ac.uk/bitstreams/a859191e-0e61-482a-a403-dad6656b2542/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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. 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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. 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