Patterns of Sedentary Behavior and Mortality in U.S. Middle-Aged and Older Adults Motivational counseling to reduce sitting time: a community-based randomized controlled trial in adults. Objective vs. Self-Reported Physical Activity and Sedentary Time: Effects of Measurement Method on Relationships with Risk Biomarkers Total Worker Health Intervention Increases Activity of Sedentary Workers. Sedentary time and markers of inflammation in people with newly diagnosed type 2 diabetes
Adults are sedentary for an alarming 9 to 10 hours per day ( 1 ) . Accordingly , the popular press has coined the phrase sitting is the new smoking to describe a current epidemic of developed nations ( 24 ) . Evidence indicates that sedentary time is associated with incident cardiovascular disease , incidence of cardiovascular diseaserelated risk factors , and mortality ( 5 , 6 ) . Of note , the risk conferred by prolonged sedentariness is eliminated only by high levels of moderate- to vigorous-intensity physical activity ( MVPA ) ( about 60 to 75 min/d ) , which exceed physical activity recommendations ( 7 , 8) . As such , sedentary behavior is now believed to represent a clinical ly important aspect of a person 's physical activity profile and is no longer considered simply the extreme low end of the physical activity continuum ( 5 ) . Studies linking sedentary behavior to health outcomes have relied almost exclusively on self-reported  sedentary time  , which is subject to reporting bias and measurement error ( 9 ) . A 2015 systematic review ( 5 ) identified only 1 study ( NHANES [ National Health and Nutrition Examination Survey ] ) that examined the association between objective ly measured sedentary time and health outcomes , a study limited by a small event rate ( 10 ) . New studies using NHANES data have since been published , with longer follow-up and higher event rates ( 1115 ) . However , some of these studies have reported an association between objective ly measured sedentary time and mortality ( 11 , 14 , 15 ) , but others have not ( 12 , 13 ) . Additional cohort studies are thus needed to rectify evidence gaps . Furthermore , studies using accelerometers to objective ly measure sedentary behavior conventionally operationalize sedentary time as the total number of sedentary minutes per day . This approach ignores patterns of accumulated sedentary behavior over time . For example , accumulation of sedentary time in a few long bouts or many short bouts represents 2 distinct patterns of sedentary time accrual . Experimental studies have shown that acute periods of prolonged , uninterrupted sedentary behavior cause greater detrimental cardiometabolic effects than sedentary behavior that is periodically interrupted ( 1618 ) , suggestive that it is not just total sedentary time that is relevant to health outcomes , but also the manner in which it is accumulated . Few longitudinal studies , however , have explored the association between prolonged , uninterrupted sedentary behavior and mortality to corroborate these findings . To inform guidelines on reducing sedentary behavior ( target reductions in overall sedentary time or target interruption of prolonged sedentary bouts ) , evidence from prospect i ve studies is needed to 1 ) confirm the association between total sedentary time and mortality using objective measures , 2 ) determine whether prolonged sedentary bouts confer risk for death , and 3 ) eluci date whether the total volume of sedentary time and its pattern of accumulation individually or jointly contribute to risk for death . The purpose of this study , therefore , was to examine the association between objective ly measured sedentary time ( both total volume and accrual in prolonged bouts ) and all-cause mortality in a national cohort of U.S. middle-aged and older adults enrolled in the REGARDS ( Reasons for Geographic and Racial Differences in Stroke ) study . Methods Study Population REGARDS is a population -based study design ed to examine racial and regional disparities in stroke . It comprises 30239 white and black adults aged 45 years or older enrolled between 2003 and 2007 from across the contiguous United States ( 19 , 20 ) . Detailed design and methods for REGARDS are described elsewhere ( 21 ) . Briefly , demographic and cardiovascular risk factor data were collected by telephone interview and an in-home physical assessment on enrollment . A detailed summary of baseline measures is provided in the Supplement . Participants ( or their proxies ) were then followed for 6-month intervals to ascertain vital status . Objective measurements of sedentary behavior were collected from active REGARDS participants from 2009 to 2013 ( mean time from study enrollment , 5.7 years [ SD , 1.5 ] ; range , 1.9 to 9.5 years ) ( 22 ) . A total of 7985 participants adhered to accelerometer wear requirements ( 4 days with accelerometer wear 10 hours ) , provided follow-up data , and were available for the current analyses ( Supplement Figure 1 ) . Supplement Table 1 shows the characteristics of included versus excluded REGARDS participants . The REGARDS study protocol was approved by the institutional review boards of participating institutions . All participants provided informed consent . Supplement . Supplementary Material Accelerometer Data Collection Methods for accelerometer data collection are described elsewhere ( 22 ) . Briefly , participants were fitted with an Actical ( Philips Respironics ) accelerometer secured to their right hip using a nylon belt and were instructed to wear the device during waking hours for 7 consecutive days . The Actical had been vali date d formeasurement of physical activity and sedentary behavior and was shown to have acceptable reliability ( 2325 ) . Activity counts were summed over 1-minute epochs . Nonwear periods were defined as at least 150 consecutive minutes of 0 activity counts . This nonwear algorithm was previously vali date d against daily log sheets in REGARDS participants ( 26 ) . Measurements of 0 to 49 , 50 to 1064 , and at least 1065 counts per minute were defined as sedentary behavior , light-intensity physical activity , and MVPA , respectively , as determined in a laboratory-based calibration study ( 27 ) . A sedentary bout was defined as consecutive minutes in which the accelerometer registered fewer than 50 counts per minute . A sedentary break was defined as at least 1 minute in which 50 or more counts per minute were registered after a sedentary bout . Both sedentary bouts and breaks were exclusively continuous periods , with no interruptions or nonwear intervals allowed in the definition . Outcome Ascertainment All-cause mortality was the primary outcome , defined as any death after completion of the accelerometer protocol regardless of cause . Date s of death were confirmed through review of death certificates , medical records , and administrative data bases . Deaths through 4 September 2015 were included in the current analysis . Statistical Analysis Sedentary and physical activity variables were averaged across compliant days ( 10 hours of wear ) . Because of a high correlation between total sedentary time and wear time ( Supplement Figure 2 ) , we corrected for the influence of wear time by st and ardizing total sedentary time to 16 hours of wear time per day using the residuals obtained when regressing total sedentary time on wear time ( see Methods section of the Supplement ) ( 2830 ) . Participants were stratified into quartiles according to total sedentary time and , separately , mean sedentary bout duration ( a measure of overall prolonged , uninterrupted sedentary behavior ) . Cox proportional hazards regression modeling was used to calculate the hazard ratio ( HR ) for all-cause mortality associated with quartiles of total sedentary time ( and separately , mean sedentary bout length ) . Crude HRs were initially calculated . Subsequent HRs were calculated after adjustment for age , race , sex , region of residence , education , and season the accelerometer was worn ( model 1 ) , with further adjustment for current smoking , alcohol use , body mass index ( BMI ) , diabetes , hypertension , dyslipidemia , estimated glomerular filtration rate less than 60 mL/min/1.73 m2 , atrial fibrillation , history of coronary heart disease , and history of stroke ( model 2 ) . Models were additionally adjusted for MVPA expressed continuously ( model 3 ) . Tests for linear trend across quartiles were conducted by including the quartile for each participant as an ordinal variable in regression models . Proportional hazards assumptions were confirmed with a Kolmogorov-type supremum test ( 31 ) . The above analyses were then repeated in a fully adjusted model , testing interactions for age ( < 65 and 65 years ) , sex ( male and female ) , race ( black and white ) , BMI category ( normal weight and overweight or obese ) , and MVPA category ( < 150 min/wk and 150 min/wk ) . As a secondary analysis , we examined the continuous doseresponse relationship between each sedentary characteristic and all-cause mortality in a fully adjusted model ( model 3 ) using restricted cubic splines ( 32 ) . Cubic polynomials were fitted with the mean of each sedentary characteristic set as the reference and knots placed at the 5th , 35th , 65th , and 95th percentiles ( 33 ) . Nonlinear associations were evaluated using the likelihood ratio test . For nonlinear associations , spline models were used to describe the associations and when the association was determined to be linear , a linear model was used . Because of multicollinearity between total sedentary time and mean sedentary bout duration ( r= 0.61 ) , both variables were not included in the same model . Alternatively , to examine the individual and joint associations of total sedentary time and prolonged , uninterrupted sedentary behavior with mortality , participants were classified into 4 categories : low total sedentary time ( < 750 min/d ) and low prolonged sedentary bout time ( < 10 min/bout ) , low total sedentary time  and high prolonged sedentary bout time  ( 10 min/bout ) , high total sedentary time  ( 750 min/d ) and low prolonged sedentary bout time , and high total sedentary time and high prolonged sedentary bout time . Hazard ratios for all-cause mortality were calculated for each joint category in comparison with the lowlow group in a fully adjusted model ( model 3 ) . Thresholds for total sedentary time ( 750 min/d ) and mean sedentary bout duration ( 10 min/bout ) were selected on the basis of the restricted cubic splines and were confirmed using a method described by Contal and O'Quigley ( see Methods section of the Supplement ) ( 34 ) . To allow for the possibility that sedentary bouts BACKGROUND Sedentary behavior is regarded as a distinct risk factor for cardiometabolic morbidity and mortality , but knowledge of the efficacy of interventions targeting reductions in sedentary behavior is limited . PURPOSE To investigate the effect of an individualized face-to-face motivational counseling intervention aim ed at reducing sitting time . DESIGN A r and omized , controlled , observer-blinded , community-based trial with two parallel groups using open-end r and omization with 1:1 allocation . SETTING / PARTICIPANTS A total of 166 sedentary adults were consecutively recruited from the population -based Health2010 Study . INTERVENTION Participants were r and omized to a control ( usual lifestyle ) or intervention group with four individual theory-based counseling sessions . MAIN OUTCOME MEASURES Objective ly measured overall sitting time ( ActivPAL 3TM , 7 days ) ; secondary measures were breaks in sitting time , anthropometric measures , and cardiometabolic biomarkers , assessed at baseline and after 6 months . Data were collected in 2010 - 2012 and analyzed in 2013 - 2014 using repeated measures multiple regression analyses . RESULTS Ninety-three participants were r and omized to the intervention group and 73 to the control group , and 149 completed the study . The intervention group had a mean sitting time decrease of -0.27 hours/day , corresponding to 2.9 % of baseline sitting time ( hours/day ) ; the control group increased mean sitting time by 0.06 hours/day . The between-group difference in change , -0.32 hours/day ( 95 % CI=-0.87 , 0.24 , p=0.26 ) , was not statistically significant . Significant differences in change in fasting serum insulin of -5.9 pmol/L ( 95 % CI=-11.4 , -0.5 , p=0.03 ) ; homeostasis model assessment -estimated insulin resistance of -0.28 ( 95 % CI=-0.53 , -0.03 , p=0.03 ) ; and waist circumference of -1.42 cm ( 95 % CI=-2.54 , -0.29 , p=0.01 ) were observed in favor of the intervention group . CONCLUSIONS Although the observed decrease in sitting time was not significant , a community-based , individually tailored , theory-based intervention program aim ed at reducing sitting time may be effective for increasing st and ing and improving cardiometabolic health in sedentary adults . TRIAL REGISTRATION This study is registered at Clinical trials.gov ( NCT00289237 ) Purpose Imprecise measurement of physical activity variables might attenuate estimates of the beneficial effects of activity on health-related outcomes . We aim ed to compare the cardiometabolic risk factor dose-response relationships for physical activity and sedentary behaviour between accelerometer- and question naire-based activity measures . Methods  Physical activity and sedentary behaviour  were assessed in 317 adults by 7-day accelerometry and International Physical Activity Question naire ( IPAQ ) . Fasting blood was taken to determine insulin , glucose , triglyceride and total , LDL and HDL cholesterol concentrations and homeostasis model-estimated insulin resistance ( HOMAIR ) . Waist circumference , BMI , body fat percentage and blood pressure were also measured . Results For both accelerometer-derived sedentary time ( < 100 counts.min−1 ) and IPAQ-reported sitting time significant positive ( negative for HDL cholesterol ) relationships were observed with all measured risk factors – i.e. increased sedentary behaviour was associated with increased risk ( all p≤0.01 ) . However , for HOMAIR and insulin the regression coefficients were > 50 % lower for the IPAQ-reported compared to the accelerometer-derived measure ( p<0.0001 for both interactions ) . The relationships for moderate-to-vigorous physical activity ( MVPA ) and risk factors were less strong than those observed for sedentary behaviours , but significant negative relationships were observed for both accelerometer and IPAQ MVPA measures with glucose , and insulin and HOMAIR values ( all p<0.05 ) . For accelerometer-derived MVPA only , additional negative relationships were seen with triglyceride , total cholesterol and LDL cholesterol concentrations , BMI , waist circumference and percentage body fat , and a positive relationship was evident with HDL cholesterol ( p = 0.0002 ) . Regression coefficients for HOMAIR , insulin and triglyceride were 43–50 % lower for the IPAQ-reported compared to the accelerometer-derived MVPA measure ( all p≤0.01 ) . Conclusion Using the IPAQ to determine sitting time and MVPA reveals some , but not all , relationships between these activity measures and metabolic and vascular disease risk factors . Using this self-report method to quantify activity can therefore underestimate the strength of some relationships with risk factors INTRODUCTION Office employees are exposed to hazardous levels of sedentary work . Interventions that integrate health promotion and health protection elements are needed to advance the health of sedentary workers . This study tested an integrated intervention on occupational sedentary/physical activity behaviors , cardiometabolic disease biomarkers , musculoskeletal discomfort , and work productivity . DESIGN Two-group , RCT . Data were collected between January and August 2014 . SETTING / PARTICIPANTS Overweight/obese adults working in sedentary desk jobs were r and omized to : ( 1 ) a health protection-only group ( HPO , n=27 ) ; or ( 2 ) an integrated health protection/health promotion group ( HP/HP , n=27 ) . INTERVENTION HPO participants received an ergonomic workstation optimization intervention and three e-mails/week promoting rest breaks and posture variation . HP/HP participants received the HPO intervention plus access to a seated activity permissive workstation . MAIN OUTCOME MEASURES Occupational sedentary and physical activity behaviors ( primary outcomes ) , cardiometabolic health outcomes , musculoskeletal discomfort , and work productivity ( secondary outcomes ) were measured at baseline and post-intervention ( 16 weeks ) . RESULTS The HP/HP group increased occupational light intensity physical activity over the HPO group and used the activity permissive workstations 50 minutes/work day . Significant associations were observed between activity permissive workstation adherence and improvements in several cardiometabolic biomarkers ( weight , total fat mass , resting heart rate , body fat percentage ) and work productivity outcomes ( concentration at work , days missed because of health problems ) . CONCLUSIONS The HP/HP group increased occupational physical activity and greater activity permissive workstation adherence was associated with improved health and work productivity outcomes . These findings are important for employers interested in advancing the well-being of sedentary office workers . TRIAL REGISTRATION This study is registered at www . clinical trials.gov NCT02071420 Background and aims We investigated whether objective ly measured sedentary time was associated with markers of inflammation in adults with newly diagnosed type 2 diabetes . Methods and results We studied 285 adults ( 184 men , 101 women , mean age 59.0 ± 9.7 ) who had been recruited to the Early ACTivity in Diabetes ( Early ACTID ) r and omised controlled trial .  C-reactive protein ( CRP ) , adiponectin , soluble intracellular adhesion molecule-1 ( sICAM-1 ) , interleukin-6 ( IL-6 ) , and accelerometer-determined sedentary time and moderate-vigorous physical activity ( MVPA ) were measured at baseline and after six-months . Linear regression analysis was used to investigate the independent cross-sectional and longitudinal associations of sedentary time  with markers of inflammation . At baseline , associations between sedentary time and IL-6 were observed in men and women , an association that was attenuated following adjustment for waist circumference . After 6 months of follow-up  , sedentary time was reduced by 0.4 ± 1.2 h per day in women , with the change in sedentary time predicting CRP at follow-up . Every hour decrease in sedentary time  between baseline and six-months was associated with 24 % ( 1 , 48 ) lower CRP . No changes in sedentary time between baseline and 6 months were seen in men . Conclusions  Higher sedentary time  is associated with IL-6 in men and women with type 2 diabetes , and reducing sedentary time is associated with improved levels of CRP in women . Interventions to reduce sedentary time may help to reduce inflammation in women with type 2 diabetes
There was consistent evidence from cross-sectional data of an unfavourable association between total sedentary time and insulin sensitivity .
There was also some evidence that total sedentary time was unfavourably associated with fasting insulin , insulin resistance and triglycerides .
Furthermore , there was some evidence from cross-sectional data of a favourable association between breaks in sedentary time and triglycerides .
CONCLUSION Total sedentary time was consistently shown to be associated with poorer insulin sensitivity , even after adjusting for time spent in physical activity .
OBJECTIVE We conducted a systematic review to investigate the cross-sectional and prospect i ve associations of accelerometer-measured total sedentary time and breaks in sedentary time with individual cardiometabolic biomarkers in adults ≥18years of age .