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 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 Cross-sectional and prospective relationships of passive and mentally active sedentary behaviours and physical activity with depression

2019 ◽  
Vol 217 (2) ◽  
pp. 413-419 ◽  
Author(s):  
Mats Hallgren ◽  
Thi-Thuy-Dung Nguyen ◽  
Neville Owen ◽  
Brendon Stubbs ◽  
Davy Vancampfort ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Odds Ratio ◽  
Vigorous Physical Activity ◽  
Depression Symptoms ◽  
Vigorous Activity ◽  
Light Physical Activity ◽  
Cross Sectional ◽  
Sedentary Behaviours ◽  
Potential Impact

BackgroundSedentary behaviour can be associated with poor mental health, but it remains unclear whether all types of sedentary behaviour have equivalent detrimental effects.AimsTo model the potential impact on depression of replacing passive with mentally active sedentary behaviours and with light and moderate-to-vigorous physical activity. An additional aim was to explore these relationships by self-report data and clinician diagnoses of depression.MethodIn 1997, 43 863 Swedish adults were initially surveyed and their responses linked to patient registers until 2010. The isotemporal substitution method was used to model the potential impact on depression of replacing 30 min of passive sedentary behaviour with equivalent durations of mentally active sedentary behaviour, light physical activity or moderate-to-vigorous physical activity. Outcomes were self-reported depression symptoms (cross-sectional analyses) and clinician-diagnosed incident major depressive disorder (MDD) (prospective analyses).ResultsOf 24 060 participants with complete data (mean age 49.2 years, s.d. 15.8, 66% female), 1526 (6.3%) reported depression symptoms at baseline. There were 416 (1.7%) incident cases of MDD during the 13-year follow-up. Modelled cross-sectionally, replacing 30 min/day of passive sedentary behaviour with 30 min/day of mentally active sedentary behaviour, light physical activity and moderate-to-vigorous activity reduced the odds of depression symptoms by 5% (odds ratio 0.95, 95% CI 0.94–0.97), 13% (odds ratio 0.87, 95% CI 0.76–1.00) and 19% (odds ratio 0.81, 95% CI 0.93–0.90), respectively. Modelled prospectively, substituting 30 min/day of passive with 30 min/day of mentally active sedentary behaviour reduced MDD risk by 5% (hazard ratio 0.95, 95% CI 0.91–0.99); no other prospective associations were statistically significant.ConclusionsSubstituting passive with mentally active sedentary behaviours, light activity or moderate-to-vigorous activity may reduce depression risk in 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 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 Relationships of Accelerometer-based Measured Objective Physical Activity and Sedentary Behaviour with Cognitive Function: A Comparative Cross-sectional Study of China’s Elderly Population

2020 ◽  
Author(s):  
Zhi jian Wu ◽  
Zhu ying Wang ◽  
Bing qian Hu ◽  
Xu hui Zhang ◽  
Fan Zhang ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cognitive Function ◽  
Cognitive Ability ◽  
Sedentary Behaviour ◽  
Vigorous Physical Activity ◽  
The Elderly ◽  
Cross Sectional Study ◽  
Light Physical Activity ◽  
Cross Sectional Survey ◽  
Cross Sectional

Abstract Background: This study explored the effects of physical activity and sedentary behaviour on the decline of cognitive ability among the elderly. To compensate for the limitations of self-reported physical activity, objective measures were used. Methods: A cross-sectional survey of 308 aged people mean 68.66±5.377 years, in Nanjing, China, was conducted. Physical activity was measured using the ActiGraph GT3X+, and cognitive function was measured using the Montreal Cognitive Assessment. Results: The overall participant model, adjusted for age, BMI, education, and monthly average income, found that light physical activity (β=0.006, p<0.01), moderate-vigorous physical activity (β=0.068, p<0.001), and total physical activity (β=0.006, p<0.01) had a significant linear relationship with cognitive ability, while sedentary time did not (β=-0.020, p＞0.05). Further, light physical activity only affects the cognitive ability of elderly females (β=0.006, p<0.05). There was an inverted ‘U’ association between moderate-vigorous physical activity and cognitive ability. The association models found that moderate-vigorous physical activity in the 22.13 min·day–1～38.79 min·day–1 range affected cognitive ability most beneficially, with the highest beta coefficient among all groups (β=0.091, p<0.05). Conclusions: While physical activity can significantly improve cognitive ability among the elderly, sedentary behaviour is associated with decreased cognitive function across genders.

scholarly journals Relationships of Accelerometer-based Measured Objective Physical Activity and Sedentary Behaviour with Cognitive Function: A Comparative Cross-sectional Study of China’s Elderly Population

2020 ◽  
Author(s):  
Zhi jian Wu ◽  
Zhu ying Wang ◽  
Bing qian Hu ◽  
Xu hui Zhang ◽  
Fan Zhang ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cognitive Function ◽  
Cognitive Ability ◽  
Sedentary Behaviour ◽  
Vigorous Physical Activity ◽  
The Elderly ◽  
Cross Sectional Study ◽  
Light Physical Activity ◽  
Cross Sectional Survey ◽  
Cross Sectional

Abstract This study explored the effects of physical activity and sedentary behaviour on the decline of cognitive ability among the elderly. To compensate for the limitations of self-reported physical activity, objective measures were used. A cross-sectional survey of 308 aged people mean 68.66±5.377 years, in Nanjing, China, was conducted. Physical activity was measured using the ActiGraph GT3X+, and cognitive function was measured using the Montreal Cognitive Assessment. The overall participant model, adjusted for age, BMI, education, and monthly average income, found that light physical activity (β=0.006, p<0.01), moderate-vigorous physical activity (β=0.068, p<0.001), and total physical activity (β=0.006, p<0.01) had a significant linear relationship with cognitive ability, while sedentary time did not (β=-0.020, p＞0.05). Further, light physical activity only affects the cognitive ability of elderly females (β=0.006, p<0.05). There was an inverted ‘U’ association between moderate-vigorous physical activity and cognitive ability. The association models found that moderate-vigorous physical activity in the 22.13 min·day –1 ～38.79 min·day –1 range affected cognitive ability most beneficially, with the highest beta coefficient among all groups (β=0.091, p<0.05). In conclusion, while physical activity can significantly improve cognitive ability among the elderly, sedentary behaviour is associated with decreased cognitive function across genders.

scholarly journals Compositional analysis of the association between mortality and 24-hour movement behaviour from NHANES

2019 ◽  
pp. 204748731986778 ◽  
Author(s):  
Duncan E McGregor ◽  
Javier Palarea-Albaladejo ◽  
Philippa M Dall ◽  
Borja del Pozo Cruz ◽  
Sebastien FM Chastin
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Time Use ◽  
Compositional Data ◽  
Cox Regression ◽  
Vigorous Physical Activity ◽  
Lifestyle Factors ◽  
Accelerometer Data ◽  
Cox Regression Analysis ◽  
Daily Time

Aims Previous prospective studies of the association between mortality and physical activity have generally not fully accounted for the interplay between movement behaviours. A compositional data modelling approach accounts for relative scale and co-dependency in time-use data across physical activity behaviours of the 24-hour day. Methods A prospective analysis of the National Health and Nutrition Examination Survey 2005–2006 on N = 1468 adults ( d = 135 deaths) in ages 50–79 years was undertaken using compositional Cox regression analysis. Daily time spent in sedentary behaviour, light intensity (LIPA) and moderate-to-vigorous physical activity (MVPA) was determined from waist-mounted accelerometer data (Actigraph 7164) and supplemented with self-reported sleep data to determine the daily time-use composition. Results The composition of time spent in sedentary behaviour, LIPA, MVPA and sleep was associated with mortality rate after allowing for age and sex effects ( p < 0.001), and remained significant when other lifestyle factors were added ( p < 0.001). This was driven primarily by the preponderance of MVPA; however, significant changes are attributable to LIPA relative to sedentary behaviour and sleep, and sedentary behaviour relative to sleep. The final ratio ceased to be statistically significant after incorporating lifestyle factors. The preponderance of MVPA ceased to be statistically significant after incorporating health at outset and physical limitations on movement. Conclusions An association is inferred between survival rate and the physical activity composition of the day. The MVPA time share is important, but time spent in LIPA relative to sedentary behaviour and sleep is also a significant factor. Increased preponderance of MVPA may have detrimental associations at higher levels of MVPA.

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.

scholarly journals Accelerometer measured physical activity and the incidence of cardiovascular disease: Evidence from the UK Biobank cohort study

PLoS Medicine ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. e1003487
Author(s):  
Rema Ramakrishnan ◽  
Aiden Doherty ◽  
Karl Smith-Byrne ◽  
Kazem Rahimi ◽  
Derrick Bennett ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cardiovascular Disease ◽  
Lower Risk ◽  
Cox Regression ◽  
Moderate Intensity ◽  
Inverse Association ◽  
Uk Biobank ◽  
Reverse Causality ◽  
Vigorous Intensity ◽  
The Uk

Background Higher levels of physical activity (PA) are associated with a lower risk of cardiovascular disease (CVD). However, uncertainty exists on whether the inverse relationship between PA and incidence of CVD is greater at the highest levels of PA. Past studies have mostly relied on self-reported evidence from questionnaire-based PA, which is crude and cannot capture all PA undertaken. We investigated the association between accelerometer-measured moderate, vigorous, and total PA and incident CVD. Methods and findings We obtained accelerometer-measured moderate-intensity and vigorous-intensity physical activities and total volume of PA, over a 7-day period in 2013–2015, for 90,211 participants without prior or concurrent CVD in the UK Biobank cohort. Participants in the lowest category of total PA smoked more, had higher body mass index and C-reactive protein, and were diagnosed with hypertension. PA was associated with 3,617 incident CVD cases during 440,004 person-years of follow-up (median (interquartile range [IQR]): 5.2 (1.2) years) using Cox regression models. We found a linear dose–response relationship for PA, whether measured as moderate-intensity, vigorous-intensity, or as total volume, with risk of incident of CVD. Hazard ratios (HRs) and 95% confidence intervals for increasing quarters of the PA distribution relative to the lowest fourth were for moderate-intensity PA: 0.71 (0.65, 0.77), 0.59 (0.54, 0.65), and 0.46 (0.41, 0.51); for vigorous-intensity PA: 0.70 (0.64, 0.77), 0.54 (0.49,0.59), and 0.41 (0.37,0.46); and for total volume of PA: 0.73 (0.67, 0.79), 0.63 (0.57, 0.69), and 0.47 (0.43, 0.52). We took account of potential confounders but unmeasured confounding remains a possibility, and while removal of early deaths did not affect the estimated HRs, we cannot completely dismiss the likelihood that reverse causality has contributed to the findings. Another possible limitation of this work is the quantification of PA intensity-levels based on methods validated in relatively small studies. Conclusions In this study, we found no evidence of a threshold for the inverse association between objectively measured moderate, vigorous, and total PA with CVD. Our findings suggest that PA is not only associated with lower risk for of CVD, but the greatest benefit is seen for those who are active at the highest level.

scholarly journals Differences in daily objective physical activity and sedentary time between women with self-reported fibromyalgia and controls: results from the Canadian Health Measures Survey

2018 ◽  
Author(s):  
Paquito Bernard ◽  
Gabriel Hains-Monfette ◽  
Sarah Atoui ◽  
Célia Kingsbury
Keyword(s):  
Physical Activity ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Accelerometer Data ◽  
Light Physical Activity ◽  
Health Measures ◽  
Activity Promotion ◽  
Modifiable Factors ◽  
Canadian Health ◽  
Canadian Health Measures Survey

IntroductionPhysical activity and sedentary behaviors are important modifiable factors that influence health and quality of life in women with fibromyalgia. The purpose of this study was to compare objectively assessed physical activity and sedentary time in women self-reporting fibromyalgia with a control group. MethodData were drawn from the Canadian Health Measures Survey cycle 1, 2 and 3 conducted by Statistics Canada. We included women aged 18 to 79 years with complete accelerometer data. We performed one-way analyses of covariance (adjusted-for socio-demographic and health factors) to determine mean differences in physical activity and sedentary variables (minutes per day of moderate and vigorous physical activity, light physical activity, sedentary and daily steps) between women with and without fibromyalgia.ResultsIn total, 4132 participants were included. A cross-sectional weighted analysis indicated that 3,1% of participants self-reported a diagnosis of fibromyalgia. Participants with fibromyalgia spent less time than controls engaged in moderate and vigorous physical activity (M = 19.2 min/d (SE=0.7) vs M = 9.1 min/d (SE=1.2), p = 0.03, η2= 0.01). No significant differences were found for daily time spent in light physical activity, sedentary activities and number of steps.ConclusionWomen participants with self-reported fibromyalgia spent significantly less time in moderate and vigorous physical activity than control. Physical activity promotion interventions for women with self-reported fibromyalgia should, as a priority, target physical activities with moderate to vigorous intensity.

Sign in / Sign up

Export Citation Format

Share Document