scholarly journals Can we walk away from cardiovascular disease risk or do we have to ‘huff and puff’? A compositional accelerometer data analysis among adults and older adults in the Copenhagen City Heart Study

2020 ◽  
Author(s):  
Melker Staffan Johansson ◽  
Karen Søgaard ◽  
Eva Prescott ◽  
Jacob Louis Marott ◽  
Peter Schnohr ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Older Adults ◽  
Data Analysis ◽  
Sedentary Behaviour ◽  
Lower Risk ◽  
Accelerometer Data ◽  
Physical Behaviour ◽  
Time In Bed ◽  
Heart Study ◽  
Copenhagen City Heart Study

Abstract Background: To decrease the risk of cardiovascular disease (CVD), it is unclear whether it is enough to walk more, or if high intensity physical activity (HIPA) is needed. It is also unclear if this differs between adults and older adults. We investigated how sedentary behaviour, walking, and HIPA, were associated with systolic blood pressure (SBP), waist circumference (WC) and low-density lipoprotein cholesterol (LDL-C) among adults and older adults in a general population sample using compositional data analysis. Specifically, the measure of association was quantified by reallocating time between sedentary behaviour and 1) walking, and 2) HIPA. Methods: Cross-sectional data from the fifth examination of the Copenhagen City Heart Study was used. We estimated daily time spent in physical behaviours from accelerometer data worn 24 h/day for 7 days (i.e., right frontal thigh and iliac crest; median wear time: 6 days, 23.8 h/day) using the software Acti4. SBP, WC and LDL-C were measured during a physical examination. Eligible participants had to have ≥5 days with ≥16 h of accelerometer recordings per day, and not use antihypertensives, diuretics or cholesterol lowering medicine. The 24-hour physical behaviour composition consisted of sedentary behaviour, standing, moving, walking, HIPA (i.e., sum of climbing stairs, running, cycling and rowing), and time in bed. We used fitted values from linear regression models to predict the difference in outcome given the investigated time reallocations. Results: Among the 1053 eligible participants we found an interaction between the physical behaviour composition and age. Age-stratified (i.e., </≥65 years; 773 adults, 280 older adults) analyses showed that less sedentary behaviour and more walking compared to the group-specific mean composition was marginally associated with lower SBP among older adults, but not among adults. Less sedentary behaviour and more HIPA was among both adults and older adults marginally associated with a lower SBP, associated with a smaller WC among adults (marginally among older adults) and associated with a lower LDL-C in both age groups. Conclusions: Less sedentary behaviour and more walking seems to be associated with lower risk of CVD among older adults, while HIPA types are associated with lower risk among adults.

scholarly journals Can we walk away from cardiovascular disease risk or do we have to ‘huff and puff’? A cross-sectional compositional accelerometer data analysis among adults and older adults in the Copenhagen City Heart Study

2020 ◽  
Author(s):  
Melker Staffan Johansson ◽  
Karen Søgaard ◽  
Eva Prescott ◽  
Jacob Louis Marott ◽  
Peter Schnohr ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cardiovascular Disease ◽  
Older Adults ◽  
Data Analysis ◽  
Sedentary Behaviour ◽  
Accelerometer Data ◽  
Cvd Risk ◽  
Cross Sectional ◽  
Heart Study ◽  
Copenhagen City Heart Study

Abstract Background: It is unclear whether walking can decrease cardiovascular disease (CVD) risk or if high intensity physical activity (HIPA) is needed, and whether the association is modified by age. We investigated how sedentary behaviour, walking, and HIPA, were associated with systolic blood pressure (SBP), waist circumference (WC), and low-density lipoprotein cholesterol (LDL-C) among adults and older adults in a general population sample using compositional data analysis. Specifically, the measure of association was quantified by reallocating time between sedentary behaviour and 1) walking, and 2) HIPA. Methods: Cross-sectional data from the fifth examination of the Copenhagen City Heart Study was used. Using the software Acti4, we estimated daily time spent in physical behaviours from accelerometer data worn 24 h/day for 7 days (i.e., right frontal thigh and iliac crest; median wear time: 6 days, 23.8 h/day). SBP, WC, and LDL-C were measured during a physical examination. Inclusion criteria were ≥5 days with ≥16 h of accelerometer recordings per day, and no use of antihypertensives, diuretics or cholesterol lowering medicine. The 24-hour physical behaviour composition consisted of sedentary behaviour, standing, moving, walking, HIPA (i.e., sum of climbing stairs, running, cycling and rowing), and time in bed. We used fitted values from linear regression models to predict the difference in outcome given the investigated time reallocations relative to the group-specific mean composition. Results: Among 1053 eligible participants, we found an interaction between the physical behaviour composition and age. Age-stratified analyses (i.e., </≥65 years; 773 adults, 280 older adults) indicated that less sedentary behaviour and more walking was associated with lower SBP among older adults only. For less sedentary behaviour and more HIPA, the results i) indicated an association with lower SBP irrespective of age, ii) showed an association with a smaller WC among adults, and iii) showed an association with a lower LDL-C in both age groups. Conclusions: Less sedentary behaviour and more walking seems to be associated with lower CVD risk among older adults, while HIPA types are associated with lower risk among adults. Therefore, to reduce CVD risk, the modifying effect of age should be considered in future physical activity-promoting initiatives.

scholarly journals Can we walk away from cardiovascular disease risk or do we have to ‘huff and puff’? A cross-sectional compositional accelerometer data analysis among adults and older adults in the Copenhagen City Heart Study

2020 ◽  
Author(s):  
Melker Staffan Johansson ◽  
Karen Søgaard ◽  
Eva Prescott ◽  
Jacob Louis Marott ◽  
Peter Schnohr ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cardiovascular Disease ◽  
Older Adults ◽  
Data Analysis ◽  
Sedentary Behaviour ◽  
Accelerometer Data ◽  
Cvd Risk ◽  
Cross Sectional ◽  
Heart Study ◽  
Copenhagen City Heart Study

Abstract Background: It is unclear whether walking can decrease cardiovascular disease (CVD) risk or if high intensity physical activity (HIPA) is needed, and whether the association is modified by age. We investigated how sedentary behaviour, walking, and HIPA, were associated with systolic blood pressure (SBP), waist circumference (WC), and low-density lipoprotein cholesterol (LDL-C) among adults and older adults in a general population sample using compositional data analysis. Specifically, the measure of association was quantified by reallocating time between sedentary behaviour and 1) walking, and 2) HIPA. Methods: Cross-sectional data from the fifth examination of the Copenhagen City Heart Study was used. Using the software Acti4, we estimated daily time spent in physical behaviours from accelerometer data worn 24 h/day for 7 days (i.e., right frontal thigh and iliac crest; median wear time: 6 days, 23.8 h/day). SBP, WC, and LDL-C were measured during a physical examination. Inclusion criteria were ≥5 days with ≥16 h of accelerometer recordings per day, and no use of antihypertensives, diuretics or cholesterol lowering medicine. The 24-hour physical behaviour composition consisted of sedentary behaviour, standing, moving, walking, HIPA (i.e., sum of climbing stairs, running, cycling and rowing), and time in bed. We used fitted values from linear regression models to predict the difference in outcome given the investigated time reallocations relative to the group-specific mean composition. Results: Among 1053 eligible participants, we found an interaction between the physical behaviour composition and age. Age-stratified analyses (i.e., </≥65 years; 773 adults, 280 older adults) indicated that less sedentary behaviour and more walking was associated with lower SBP among older adults only. For less sedentary behaviour and more HIPA, the results i) indicated an association with lower SBP irrespective of age, ii) showed an association with a smaller WC among adults, and iii) showed an association with a lower LDL-C in both age groups. Conclusions: Less sedentary behaviour and more walking seems to be associated with lower CVD risk among older adults, while HIPA types are associated with lower risk among adults. Therefore, to reduce CVD risk, the modifying effect of age should be considered in future physical activity-promoting initiatives.

scholarly journals GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies

2021 ◽  
pp. bjsports-2020-103604
Author(s):  
Jairo H Migueles ◽  
Eivind Aadland ◽  
Lars Bo Andersen ◽  
Jan Christian Brønd ◽  
Sebastien F Chastin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Sedentary Behaviour ◽  
Compositional Data ◽  
Epidemiological Studies ◽  
Future Research ◽  
Compositional Data Analysis ◽  
Accelerometer Data ◽  
Physical Behaviour ◽  
Analytical Approaches

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers’ decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

scholarly journals Reallocating time from device-measured sleep, sedentary behaviour or light physical activity to moderate-to-vigorous physical activity is associated with lower cardiovascular disease risk

2020 ◽  
Author(s):  
Rosemary Walmsley ◽  
Shing Chan ◽  
Karl Smith-Byrne ◽  
Rema Ramakrishnan ◽  
Mark Woodward ◽  
...  
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Cardiovascular Disease ◽  
Sedentary Behaviour ◽  
Lower Risk ◽  
Vigorous Physical Activity ◽  
Accelerometer Data ◽  
Uk Biobank ◽  
Light Physical Activity ◽  
Machine Learning Model

AbstractBackgroundModerate-to-vigorous physical activity (MVPA), light physical activity, sedentary behaviour and sleep have all been associated with cardiovascular disease (CVD). Due to challenges in measuring and analysing movement behaviours, there is uncertainty about how the association with incident CVD varies with the time spent in these different movement behaviours.MethodsWe developed a machine-learning model (Random Forest smoothed by a Hidden Markov model) to classify sleep, sedentary behaviour, light physical activity and MVPA from accelerometer data. The model was developed using data from a free-living study of 152 participants who wore an Axivity AX3 accelerometer on the wrist while also wearing a camera and completing a time use diary. Participants in UK Biobank, a prospective cohort study, were asked to wear an accelerometer (of the same type) for seven days, and we applied our machine-learning model to classify their movement behaviours. Using Compositional Data Analysis Cox regression, we investigated how reallocating time between movement behaviours was associated with CVD incidence.FindingsWe classified accelerometer data as sleep, sedentary behaviour, light physical activity or MVPA with a mean accuracy of 88% (95% CI: 87, 89) and Cohen’s kappa of 0·80 (95% CI: 0·79, 0·82). Among 87,509 UK Biobank participants, there were 3,424 incident CVD events. Reallocating time from any behaviour to MVPA, or reallocating time from sedentary behaviour to any behaviour, was associated with a lower risk of CVD. For example, for a hypothetical average individual, reallocating 20 minutes/day to MVPA from all other behaviours proportionally was associated with 9% (7%, 10%) lower risk of incident CVD, while reallocating 1 hour/day to sedentary behaviour was associated with 5% (3%, 7%) higher risk.InterpretationReallocating time from light physical activity, sedentary behaviour or sleep to MVPA, or reallocating time from sedentary behaviour to other behaviours, was associated with lower risk of incident CVD. Accurate classification of movement behaviours using machine-learning and statistical methods to address the compositional nature of movement behaviours enabled these insights. Public health interventions and guidelines should promote reallocating time to MVPA from other behaviours, as well as reallocating time from sedentary behaviour to light physical activity.FundingMedical Research Council.

scholarly journals Associations between objectively measured physical activity, sedentary behaviour and time in bed among 75+ community-dwelling Danish older adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li-Tang Tsai ◽  
Eleanor Boyle ◽  
Jan C. Brønd ◽  
Gry Kock ◽  
Mathias Skjødt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Sedentary Behaviour ◽  
Sleep Duration ◽  
Activity Level ◽  
Time In Bed ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity ◽  
Vector Magnitude

Abstract Background Older adults are recommended to sleep 7–8 h/day. Time in bed (TIB) differs from sleep duration and includes also the time of lying in bed without sleeping. Long TIB (≥9 h) are associated with self-reported sedentary behavior, but the association between objectively measured physical activity, sedentary behavior and TIB is unknown. Methods This study was based on cross-sectional analysis of the Healthy Ageing Network of Competence (HANC Study). Physical activity and sedentary behaviour were measured by a tri-axial accelerometer (ActiGraph) placed on the dominant wrist for 7 days. Sedentary behavior was classified as < 2303 counts per minute (cpm) in vector magnitude and physical activity intensities were categorized, as 2303–4999 and ≥ 5000 cpm in vector magnitude. TIB was recorded in self-reported diaries. Participants were categorized as UTIB (usually having TIB 7–9 h/night: ≥80% of measurement days), STIB (sometimes having TIB 7–9 h/night: 20–79% of measurement days), and RTIB (rarely having TIB 7–9 h/night: < 20% of measurement days). Multinominal regression models were used to calculate the relative risk ratios (RRR) of being RTIB and STIB by daily levels of physical activity and SB, with UTIB as the reference group. The models were adjusted for age, sex, average daily nap length and physical function. Results Three hundred and fourty-one older adults (median age 81 (IQR 5), 62% women) were included with median TIB of 8 h 21 min (1 h 10 min)/day, physical activity level of 2054 (864) CPM with 64 (15) % of waking hours in sedentary behavior. Those with average CPM within the highest tertile had a lower RRR (0.33 (0.15–0.71), p = 0.005) for being RTIB compared to those within the lowest tertile of average CPM. Accumulating physical activity in intensities 2303–4999 and ≥ 5000 cpm/day did not affect the RRR of being RTIB. RRR of being RTIB among highly sedentary participants (≥10 h/day of sedentary behavior) more than tripled compared to those who were less sedentary (3.21 (1.50–6.88), p = 0.003). Conclusions For older adults, being physically active and less sedentary was associated with being in bed for 7–9 h/night for most nights (≥80%). Future longitudinal studies are warranted to explore the causal relationship sbetween physical activity and sleep duration.

scholarly journals Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease

2021 ◽  
pp. bjsports-2021-104050
Author(s):  
Rosemary Walmsley ◽  
Shing Chan ◽  
Karl Smith-Byrne ◽  
Rema Ramakrishnan ◽  
Mark Woodward ◽  
...  
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Sedentary Behaviour ◽  
Lower Risk ◽  
Accelerometer Data ◽  
Uk Biobank ◽  
Free Living ◽  
Machine Learning Methods ◽  
Machine Learning Model ◽  
Incident Cardiovascular Disease

ObjectiveTo improve classification of movement behaviours in free-living accelerometer data using machine-learning methods, and to investigate the association between machine-learned movement behaviours and risk of incident cardiovascular disease (CVD) in adults.MethodsUsing free-living data from 152 participants, we developed a machine-learning model to classify movement behaviours (moderate-to-vigorous physical activity behaviours (MVPA), light physical activity behaviours, sedentary behaviour, sleep) in wrist-worn accelerometer data. Participants in UK Biobank, a prospective cohort, were asked to wear an accelerometer for 7 days, and we applied our machine-learning model to classify their movement behaviours. Using compositional data analysis Cox regression, we investigated how reallocating time between movement behaviours was associated with CVD incidence.ResultsIn leave-one-participant-out analysis, our machine-learning method classified free-living movement behaviours with mean accuracy 88% (95% CI 87% to 89%) and Cohen’s kappa 0.80 (95% CI 0.79 to 0.82). Among 87 498 UK Biobank participants, there were 4105 incident CVD events. Reallocating time from any behaviour to MVPA, or reallocating time from sedentary behaviour to any behaviour, was associated with lower CVD risk. For an average individual, reallocating 20 min/day to MVPA from all other behaviours proportionally was associated with 9% (95% CI 7% to 10%) lower risk, while reallocating 1 hour/day to sedentary behaviour from all other behaviours proportionally was associated with 5% (95% CI 3% to 7%) higher risk.ConclusionMachine-learning methods classified movement behaviours accurately in free-living accelerometer data. Reallocating time from other behaviours to MVPA, and from sedentary behaviour to other behaviours, was associated with lower risk of incident CVD, and should be promoted by interventions and guidelines.

scholarly journals Digital Peripheral Arterial Tonometry and Cardiovascular Disease Events: The Framingham Heart Study

Stroke ◽  
2021 ◽  
Author(s):  
Leroy L. Cooper ◽  
Na Wang ◽  
Alexa S. Beiser ◽  
José Rafael Romero ◽  
Hugo J. Aparicio ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Framingham Heart Study ◽  
Vascular Function ◽  
Lower Risk ◽  
Reactive Hyperemia ◽  
Pulse Amplitude ◽  
Peripheral Arterial Tonometry ◽  
Arterial Tonometry ◽  
Heart Study ◽  
Peripheral Arterial

Background and Purpose: Novel noninvasive measures of vascular function are emerging as subclinical markers for cardiovascular disease (CVD) and may be useful to predict CVD events. The purpose of our prospective study was to assess associations between digital peripheral arterial tonometry (PAT) measures and first-onset major CVD events in a sample of FHS (Framingham Heart Study) participants. Methods: Using a fingertip PAT device, we assessed pulse amplitude in Framingham Offspring and Third Generation participants (n=3865; mean age, 55±14 years; 52% women) at baseline and in 30-second intervals for 4 minutes during reactive hyperemia. The PAT ratio (relative hyperemia index) was calculated as the post-to-pre occlusion pulse signal ratio in the occluded arm, relative to the same ratio in the control (nonoccluded) arm, and corrected for baseline vascular tone. Baseline pulse amplitude and PAT ratio during hyperemia are measures of pressure pulsatility and microvascular function in the finger, respectively. We used Cox proportional hazards regression to relate PAT measures in the fingertip to incident CVD events. Results: During follow-up (median, 9.2 years; range, 0.04–10.0 years), 270 participants (7%) experienced new-onset CVD events (n=270). In multivariable models adjusted for cardiovascular risk factors, baseline pulse amplitude (hazard ratio [HR] per 1 SD, 1.04 [95% CI, 0.90–1.21]; P =0.57) and PAT ratio (HR, 0.95 [95% CI, 0.84–1.08]; P =0.43) were not significantly related to incident composite CVD events, including myocardial infarction or heart failure. However, higher PAT ratio (HR, 0.76 [95% CI, 0.61–0.94]; P =0.013), but not baseline pulse amplitude (HR, 1.15 [95% CI, 0.89–1.49]; P =0.29), was related to lower risk for incident stroke. In a sensitivity analysis by stroke subtype, higher PAT ratio was related to lower risk of incident ischemic stroke events (HR, 0.68 [95% CI, 0.53–0.86]; P =0.001). Conclusions: Novel digital PAT measures may represent a marker of stroke risk in the community.

scholarly journals Substitutions of physical activity, sedentary behaviour and sleep: associations with mental health in middle-aged and elderly persons

2021 ◽  
pp. jech-2020-215883
Author(s):  
Amy Hofman ◽  
Trudy Voortman ◽  
M. Arfan Ikram ◽  
Annemarie I Luik
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Older Adults ◽  
Depressive Symptoms ◽  
Sedentary Behaviour ◽  
Vigorous Physical Activity ◽  
Population Based ◽  
Elderly Persons ◽  
Accelerometer Data ◽  
Middle Aged

BackgroundPhysical activity, sedentary behaviour and sleep are potential risk factors of mental health disorders, but previous studies have not considered the dependency between these activity domains. Therefore, we examined the associations of reallocations of time among older adults’ physical activity, sedentary behaviour and sleep with depressive and anxiety symptoms using compositional isotemporal substitution analyses.MethodsWe included 1943 participants (mean age 71 years, SD: 9; 52% women) from the population-based Rotterdam Study. Between 2011 and 2016, we collected accelerometer data (mean duration 5.8 days, SD: 0.4) on physical activity, sedentary behaviour and sleep and self-reported data on depressive symptoms and anxiety.ResultsA reallocation of 30 min more moderate-to-vigorous physical activity was associated with a −0.55 (95% CI −1.04 to −0.06) points lower depressive symptoms score when replacing sleep and a −0.59 (95% CI −1.06 to −0.12) points lower score when replacing sedentary behaviour, but not when replacing light physical activity (−0.70, 95% CI −1.63 to 0.24). No associations were found for anxiety.ConclusionReplacing sedentary behaviour or sleep with more moderate-to-vigorous physical activity was associated with less depressive symptoms, suggesting that mainly intensive types of physical activity are important for middle-aged and older adults in relation to depressive symptoms.

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