{"id":{"repo_id":"uic","oai_identifier":"oai:figshare.com:article/32995319"},"canonical_url":"https://search.dev.ndltd.org/etd/uic/oai:figshare.com:article/32995319","repository":{"repo_id":"uic","name":"University of Illinois - Chicago","base_url":"https://api.figshare.com/v2/oai"},"display":{"title":"Physical Activity, Heart Rate Variability, Sleep Parameters, and Glycemic Variability in T1D","abstract":"Background: In individuals with type 1 diabetes (T1D), glycemic variability (GV), beyond mean glucose levels, is a critical determinant of cardiovascular risk and long-term complications. Although physical activity and sleep are key behavioral factors influencing glycemic control, prior research has largely examined these behaviors in isolation and has rarely accounted for underlying physiological regulation or the constrained nature of time within a 24-hour day. In particular, limited evidence exists on how autonomic nervous system (ANS) function, as measured by heart rate variability (HRV), interacts with daily movement behaviors to influence glycemic stability. Objective: This study aimed to examine (1) whether daily movement behaviors modify the association between HRV and glycemic outcomes and (2) how reallocating time across sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) affects glycemic variability in adults with T1D. Methods: This study integrated multi-sensor wearable data collected under free-living conditions in adults with T1D. Continuous glucose monitoring (CGM) was used to assess glycemic variability, accelerometry (ActiGraph) was used to quantify physical activity and sedentary time, a home-based EEG device (Zmachine) was used to measure sleep duration, and the Empatica E4 wearable device was used to derive HRV indices. Two complementary analytic approaches were applied. First, linear mixed-effects models with repeated daily measures were used to evaluate interactions between HRV indices and movement behaviors. Second, isotemporal substitution modeling (ISM) was used to estimate the effects of reallocating 30-minute time segments among behaviors while holding total daily time constant. Results: A higher LF/HF ratio, reflecting sympathetic predominance, was associated with greater glycemic instability, as indicated by increased large amplitude of glycemic excursions (LAGE). Significant interaction effects demonstrated that the relationship between HRV and glycemic outcomes was context-dependent. Notably, higher SDNN in combination with greater MVPA was associated with reduced time in range (TIR), suggesting that autonomic flexibility may amplify glucose fluctuations during higher-intensity activity. ISM analyses further revealed that reallocating 30 minutes of sleep to any other behavior was associated with reduced TIR despite concurrent reductions in the coefficient of variation (CV), indicating a pattern consistent with maladaptive glycemic compression. In contrast, replacing sedentary time with LPA was associated with lower LAGE, suggesting fewer extreme glucose excursions. Conclusions: Optimizing glycemic stability in T1D requires an integrated approach that considers both physiological regulation and the behavioral composition of the 24-hour day. These findings highlight the importance of preserving sleep, reducing sedentary time, and tailoring physical activity recommendations according to individual autonomic profiles. Incorporating HRV-informed, time-aware strategies may enhance personalized diabetes management and contribute to the prevention of long-term cardiovascular complications.","abstract_html":"Background: In individuals with type 1 diabetes (T1D), glycemic variability (GV), beyond mean glucose levels, is a critical determinant of cardiovascular risk and long-term complications. Although physical activity and sleep are key behavioral factors influencing glycemic control, prior research has largely examined these behaviors in isolation and has rarely accounted for underlying physiological regulation or the constrained nature of time within a 24-hour day. In particular, limited evidence exists on how autonomic nervous system (ANS) function, as measured by heart rate variability (HRV), interacts with daily movement behaviors to influence glycemic stability. Objective: This study aimed to examine (1) whether daily movement behaviors modify the association between HRV and glycemic outcomes and (2) how reallocating time across sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) affects glycemic variability in adults with T1D. Methods: This study integrated multi-sensor wearable data collected under free-living conditions in adults with T1D. Continuous glucose monitoring (CGM) was used to assess glycemic variability, accelerometry (ActiGraph) was used to quantify physical activity and sedentary time, a home-based EEG device (Zmachine) was used to measure sleep duration, and the Empatica E4 wearable device was used to derive HRV indices. Two complementary analytic approaches were applied. First, linear mixed-effects models with repeated daily measures were used to evaluate interactions between HRV indices and movement behaviors. Second, isotemporal substitution modeling (ISM) was used to estimate the effects of reallocating 30-minute time segments among behaviors while holding total daily time constant. Results: A higher LF/HF ratio, reflecting sympathetic predominance, was associated with greater glycemic instability, as indicated by increased large amplitude of glycemic excursions (LAGE). Significant interaction effects demonstrated that the relationship between HRV and glycemic outcomes was context-dependent. Notably, higher SDNN in combination with greater MVPA was associated with reduced time in range (TIR), suggesting that autonomic flexibility may amplify glucose fluctuations during higher-intensity activity. ISM analyses further revealed that reallocating 30 minutes of sleep to any other behavior was associated with reduced TIR despite concurrent reductions in the coefficient of variation (CV), indicating a pattern consistent with maladaptive glycemic compression. In contrast, replacing sedentary time with LPA was associated with lower LAGE, suggesting fewer extreme glucose excursions. Conclusions: Optimizing glycemic stability in T1D requires an integrated approach that considers both physiological regulation and the behavioral composition of the 24-hour day. These findings highlight the importance of preserving sleep, reducing sedentary time, and tailoring physical activity recommendations according to individual autonomic profiles. Incorporating HRV-informed, time-aware strategies may enhance personalized diabetes management and contribute to the prevention of long-term cardiovascular complications.","abstract_has_math":false,"creators":["Pei Chen (252989)"],"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":"2026-05-01T00:00:00Z","date_published":"2026-05-01T00:00:00Z","updated_at":"2026-07-27T21:33:53Z","subjects":["Health Sciences","Nursing"],"languages":[],"rights":["In Copyright","Open Access after 2028-05-01"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.25417/uic.32995319.v1","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Pei Chen (252989)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2026-05-01T00:00:00Z"]},{"key":"dc:relation","label":"Dc Relation","values":["https://figshare.com/articles/thesis/Physical_Activity_Heart_Rate_Variability_Sleep_Parameters_and_Glycemic_Variability_in_T1D/32995319"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Health Sciences","Nursing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright","Open Access after 2028-05-01"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["10.25417/uic.32995319.v1"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Background: In individuals with type 1 diabetes (T1D), glycemic variability (GV), beyond mean glucose levels, is a critical determinant of cardiovascular risk and long-term complications. Although physical activity and sleep are key behavioral factors influencing glycemic control, prior research has largely examined these behaviors in isolation and has rarely accounted for underlying physiological regulation or the constrained nature of time within a 24-hour day. In particular, limited evidence exists on how autonomic nervous system (ANS) function, as measured by heart rate variability (HRV), interacts with daily movement behaviors to influence glycemic stability. Objective: This study aimed to examine (1) whether daily movement behaviors modify the association between HRV and glycemic outcomes and (2) how reallocating time across sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) affects glycemic variability in adults with T1D. Methods: This study integrated multi-sensor wearable data collected under free-living conditions in adults with T1D. Continuous glucose monitoring (CGM) was used to assess glycemic variability, accelerometry (ActiGraph) was used to quantify physical activity and sedentary time, a home-based EEG device (Zmachine) was used to measure sleep duration, and the Empatica E4 wearable device was used to derive HRV indices. Two complementary analytic approaches were applied. First, linear mixed-effects models with repeated daily measures were used to evaluate interactions between HRV indices and movement behaviors. Second, isotemporal substitution modeling (ISM) was used to estimate the effects of reallocating 30-minute time segments among behaviors while holding total daily time constant. Results: A higher LF/HF ratio, reflecting sympathetic predominance, was associated with greater glycemic instability, as indicated by increased large amplitude of glycemic excursions (LAGE). Significant interaction effects demonstrated that the relationship between HRV and glycemic outcomes was context-dependent. Notably, higher SDNN in combination with greater MVPA was associated with reduced time in range (TIR), suggesting that autonomic flexibility may amplify glucose fluctuations during higher-intensity activity. ISM analyses further revealed that reallocating 30 minutes of sleep to any other behavior was associated with reduced TIR despite concurrent reductions in the coefficient of variation (CV), indicating a pattern consistent with maladaptive glycemic compression. In contrast, replacing sedentary time with LPA was associated with lower LAGE, suggesting fewer extreme glucose excursions. Conclusions: Optimizing glycemic stability in T1D requires an integrated approach that considers both physiological regulation and the behavioral composition of the 24-hour day. These findings highlight the importance of preserving sleep, reducing sedentary time, and tailoring physical activity recommendations according to individual autonomic profiles. Incorporating HRV-informed, time-aware strategies may enhance personalized diabetes management and contribute to the prevention of long-term cardiovascular complications."]},{"key":"dc:title","label":"Title","values":["Physical Activity, Heart Rate Variability, Sleep Parameters, and Glycemic Variability in T1D"]}]}],"canonical_facts":{"dc:creator":["Pei Chen (252989)"],"dc:date":["2026-05-01T00:00:00Z"],"dc:description":["Background: In individuals with type 1 diabetes (T1D), glycemic variability (GV), beyond mean glucose levels, is a critical determinant of cardiovascular risk and long-term complications. Although physical activity and sleep are key behavioral factors influencing glycemic control, prior research has largely examined these behaviors in isolation and has rarely accounted for underlying physiological regulation or the constrained nature of time within a 24-hour day. In particular, limited evidence exists on how autonomic nervous system (ANS) function, as measured by heart rate variability (HRV), interacts with daily movement behaviors to influence glycemic stability. Objective: This study aimed to examine (1) whether daily movement behaviors modify the association between HRV and glycemic outcomes and (2) how reallocating time across sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) affects glycemic variability in adults with T1D. Methods: This study integrated multi-sensor wearable data collected under free-living conditions in adults with T1D. Continuous glucose monitoring (CGM) was used to assess glycemic variability, accelerometry (ActiGraph) was used to quantify physical activity and sedentary time, a home-based EEG device (Zmachine) was used to measure sleep duration, and the Empatica E4 wearable device was used to derive HRV indices. Two complementary analytic approaches were applied. First, linear mixed-effects models with repeated daily measures were used to evaluate interactions between HRV indices and movement behaviors. Second, isotemporal substitution modeling (ISM) was used to estimate the effects of reallocating 30-minute time segments among behaviors while holding total daily time constant. Results: A higher LF/HF ratio, reflecting sympathetic predominance, was associated with greater glycemic instability, as indicated by increased large amplitude of glycemic excursions (LAGE). Significant interaction effects demonstrated that the relationship between HRV and glycemic outcomes was context-dependent. Notably, higher SDNN in combination with greater MVPA was associated with reduced time in range (TIR), suggesting that autonomic flexibility may amplify glucose fluctuations during higher-intensity activity. ISM analyses further revealed that reallocating 30 minutes of sleep to any other behavior was associated with reduced TIR despite concurrent reductions in the coefficient of variation (CV), indicating a pattern consistent with maladaptive glycemic compression. In contrast, replacing sedentary time with LPA was associated with lower LAGE, suggesting fewer extreme glucose excursions. Conclusions: Optimizing glycemic stability in T1D requires an integrated approach that considers both physiological regulation and the behavioral composition of the 24-hour day. These findings highlight the importance of preserving sleep, reducing sedentary time, and tailoring physical activity recommendations according to individual autonomic profiles. Incorporating HRV-informed, time-aware strategies may enhance personalized diabetes management and contribute to the prevention of long-term cardiovascular complications."],"dc:identifier":["10.25417/uic.32995319.v1"],"dc:relation":["https://figshare.com/articles/thesis/Physical_Activity_Heart_Rate_Variability_Sleep_Parameters_and_Glycemic_Variability_in_T1D/32995319"],"dc:rights":["In Copyright","Open Access after 2028-05-01"],"dc:subject":["Health Sciences","Nursing"],"dc:title":["Physical Activity, Heart Rate Variability, Sleep Parameters, and Glycemic Variability in T1D"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T21:33:53Z"}