{"id":{"repo_id":"exeter","oai_identifier":"oai:figshare.com:article/32537166"},"canonical_url":"https://search.dev.ndltd.org/etd/exeter/oai:figshare.com:article/32537166","repository":{"repo_id":"exeter","name":"University of Exeter","base_url":"https://api.figshare.com/v2/oai"},"display":{"title":"Moving for life: Understanding healthy ageing through daily movement","abstract":"Physical activity (PA) is widely recognised as an important determinant for physical function (PF) in later life. However, little is known about how indoor and outdoor PA are independently associated with both objective and perceived PF. This thesis aimed to (1) develop and validate a method for classifying indoor and outdoor PA using wearable sensor data, and (2) examine whether indoor and outdoor PA volumes are associated with PF in community-dwelling older adults. Chapter 2 describes the development and validation of a machine learning predictive model integrating acceleration, light, and temperature data from a wrist-worn accelerometer to classify indoor and outdoor PA environments. Model performance was compared with that of a simpler model based on a light threshold of 1000-lux. Under controlled conditions, both methods demonstrated comparably high classification accuracy. However, given its computational efficiency and scalability, the 1000-lux threshold was identified as the more pragmatic approach for application in large epidemiological datasets. Chapter 3 applied the 1000-lux threshold method to the REACT dataset, a large, community-based cohort of older adults recruited via primary care. Indoor and outdoor PA volumes were estimated and examined in relation to objective PF, assessed using the Short Physical Performance Battery, and perceived PF, measured via the 36-Item Short Form Health Survey PF subscale. The cross-sectional analyses indicated that greater volumes of both indoor and outdoor PA were independently associated with higher SPPB scores and better perceived functional ability. These associations were observed across both objective and perceived dimensions of PF, suggesting that PA is linked to these aspects of PF in older adults, irrespective of environmental context. Collectively, this thesis advances understanding of the relationships between indoor and outdoor PA and PF in older adults. The findings underscore the importance of facilitating opportunities for engagement in PA across both indoor and outdoor environments in ageing populations. Furthermore, this work provides a foundation for longitudinal and experimental studies to clarify causal pathways between indoor and outdoor PA with PF outcomes.<p></p>","abstract_html":"Physical activity (PA) is widely recognised as an important determinant for physical function (PF) in later life. However, little is known about how indoor and outdoor PA are independently associated with both objective and perceived PF. This thesis aimed to (1) develop and validate a method for classifying indoor and outdoor PA using wearable sensor data, and (2) examine whether indoor and outdoor PA volumes are associated with PF in community-dwelling older adults. Chapter 2 describes the development and validation of a machine learning predictive model integrating acceleration, light, and temperature data from a wrist-worn accelerometer to classify indoor and outdoor PA environments. Model performance was compared with that of a simpler model based on a light threshold of 1000-lux. Under controlled conditions, both methods demonstrated comparably high classification accuracy. However, given its computational efficiency and scalability, the 1000-lux threshold was identified as the more pragmatic approach for application in large epidemiological datasets. Chapter 3 applied the 1000-lux threshold method to the REACT dataset, a large, community-based cohort of older adults recruited via primary care. Indoor and outdoor PA volumes were estimated and examined in relation to objective PF, assessed using the Short Physical Performance Battery, and perceived PF, measured via the 36-Item Short Form Health Survey PF subscale. The cross-sectional analyses indicated that greater volumes of both indoor and outdoor PA were independently associated with higher SPPB scores and better perceived functional ability. These associations were observed across both objective and perceived dimensions of PF, suggesting that PA is linked to these aspects of PF in older adults, irrespective of environmental context. Collectively, this thesis advances understanding of the relationships between indoor and outdoor PA and PF in older adults. The findings underscore the importance of facilitating opportunities for engagement in PA across both indoor and outdoor environments in ageing populations. Furthermore, this work provides a foundation for longitudinal and experimental studies to clarify causal pathways between indoor and outdoor PA with PF outcomes.&lt;p&gt;&lt;/p&gt;","abstract_has_math":false,"creators":["Sam Evans (21047888)"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-05-28T00:00:00Z","date_published":"2026-05-28T00:00:00Z","updated_at":"2026-07-27T19:32:51Z","subjects":["Physical activity","Physical function","Healthy ageing"],"languages":[],"rights":["All rights reserved"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["10779/exe.32537166.v1"],"render_values":[{"text":"10779/exe.32537166.v1","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Sam Evans (21047888)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2026-05-28T00:00:00Z"]},{"key":"dc:relation","label":"Dc Relation","values":["https://figshare.com/articles/thesis/Moving_for_life_Understanding_healthy_ageing_through_daily_movement/32537166"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Physical activity","Physical function","Healthy ageing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["All rights reserved"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["10779/exe.32537166.v1"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Physical activity (PA) is widely recognised as an important determinant for physical function (PF) in later life. However, little is known about how indoor and outdoor PA are independently associated with both objective and perceived PF. This thesis aimed to (1) develop and validate a method for classifying indoor and outdoor PA using wearable sensor data, and (2) examine whether indoor and outdoor PA volumes are associated with PF in community-dwelling older adults. Chapter 2 describes the development and validation of a machine learning predictive model integrating acceleration, light, and temperature data from a wrist-worn accelerometer to classify indoor and outdoor PA environments. Model performance was compared with that of a simpler model based on a light threshold of 1000-lux. Under controlled conditions, both methods demonstrated comparably high classification accuracy. However, given its computational efficiency and scalability, the 1000-lux threshold was identified as the more pragmatic approach for application in large epidemiological datasets. Chapter 3 applied the 1000-lux threshold method to the REACT dataset, a large, community-based cohort of older adults recruited via primary care. Indoor and outdoor PA volumes were estimated and examined in relation to objective PF, assessed using the Short Physical Performance Battery, and perceived PF, measured via the 36-Item Short Form Health Survey PF subscale. The cross-sectional analyses indicated that greater volumes of both indoor and outdoor PA were independently associated with higher SPPB scores and better perceived functional ability. These associations were observed across both objective and perceived dimensions of PF, suggesting that PA is linked to these aspects of PF in older adults, irrespective of environmental context. Collectively, this thesis advances understanding of the relationships between indoor and outdoor PA and PF in older adults. The findings underscore the importance of facilitating opportunities for engagement in PA across both indoor and outdoor environments in ageing populations. Furthermore, this work provides a foundation for longitudinal and experimental studies to clarify causal pathways between indoor and outdoor PA with PF outcomes.<p></p>"]},{"key":"dc:title","label":"Title","values":["Moving for life: Understanding healthy ageing through daily movement"]}]}],"canonical_facts":{"dc:creator":["Sam Evans (21047888)"],"dc:date":["2026-05-28T00:00:00Z"],"dc:description":["Physical activity (PA) is widely recognised as an important determinant for physical function (PF) in later life. However, little is known about how indoor and outdoor PA are independently associated with both objective and perceived PF. This thesis aimed to (1) develop and validate a method for classifying indoor and outdoor PA using wearable sensor data, and (2) examine whether indoor and outdoor PA volumes are associated with PF in community-dwelling older adults. Chapter 2 describes the development and validation of a machine learning predictive model integrating acceleration, light, and temperature data from a wrist-worn accelerometer to classify indoor and outdoor PA environments. Model performance was compared with that of a simpler model based on a light threshold of 1000-lux. Under controlled conditions, both methods demonstrated comparably high classification accuracy. However, given its computational efficiency and scalability, the 1000-lux threshold was identified as the more pragmatic approach for application in large epidemiological datasets. Chapter 3 applied the 1000-lux threshold method to the REACT dataset, a large, community-based cohort of older adults recruited via primary care. Indoor and outdoor PA volumes were estimated and examined in relation to objective PF, assessed using the Short Physical Performance Battery, and perceived PF, measured via the 36-Item Short Form Health Survey PF subscale. The cross-sectional analyses indicated that greater volumes of both indoor and outdoor PA were independently associated with higher SPPB scores and better perceived functional ability. These associations were observed across both objective and perceived dimensions of PF, suggesting that PA is linked to these aspects of PF in older adults, irrespective of environmental context. Collectively, this thesis advances understanding of the relationships between indoor and outdoor PA and PF in older adults. The findings underscore the importance of facilitating opportunities for engagement in PA across both indoor and outdoor environments in ageing populations. Furthermore, this work provides a foundation for longitudinal and experimental studies to clarify causal pathways between indoor and outdoor PA with PF outcomes.<p></p>"],"dc:identifier":["10779/exe.32537166.v1"],"dc:relation":["https://figshare.com/articles/thesis/Moving_for_life_Understanding_healthy_ageing_through_daily_movement/32537166"],"dc:rights":["All rights reserved"],"dc:subject":["Physical activity","Physical function","Healthy ageing"],"dc:title":["Moving for life: Understanding healthy ageing through daily movement"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:32:51Z"}