Device-measured stationary behaviour and cardiovascular and orthostatic circulatory disease incidence: a population cohort study of 83,013 adults

Device-measured stationary behaviour and cardiovascular and orthostatic circulatory disease incidence: a population cohort study of 83,013 adults | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Device-measured stationary behaviour and cardiovascular and orthostatic circulatory disease incidence: a population cohort study of 83,013 adults Matthew N. Ahmadi , Pieter Coenen , Leon Straker , Emmanuel Stamatakis doi: https://doi.org/10.1101/2024.01.17.24301458 Matthew N. Ahmadi 1 Mackenzie Wearables Research Hub, Charles Perkins Centre, The University of Sydney , NSW, Australia 2 School of Health Sciences, Faculty of Medicine and Health, The University of Sydney , NSW, Australia PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: matthew.ahmadi{at}sydney.edu.au Pieter Coenen 3 Department of Public and Occupational Health, Amsterdam UMC location Vrije Universiteit , Amsterdam, the Netherlands 4 Societal Participation and Health, Amsterdam Public Health Research Institute , Amsterdam, the Netherlands PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Leon Straker 5 School of Allied Health, Curtin University , Perth, WA, Australia PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emmanuel Stamatakis 1 Mackenzie Wearables Research Hub, Charles Perkins Centre, The University of Sydney , NSW, Australia 2 School of Health Sciences, Faculty of Medicine and Health, The University of Sydney , NSW, Australia PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Importance Previous studies have indicated that standing maybe beneficially associated with surrogate metabolic markers, while more time spent sitting has an adverse association. Studies assessing the dose-response associations of standing, sitting, and composite stationary behaviour time with cardiovascular disease (CVD) and orthostatic circulatory disease are scarce and show an unclear picture. Objective To examine associations of daily sitting, standing, and stationary time with CVD and orthostatic circulatory disease incidence Methods We used accelerometer data from 83,013 adults (mean age±SD= 61.3±7.8; Female=55.6%) from the UK Biobank to assess daily time spent sitting and standing. Major CVD was defined as coronary heart disease, heart failure, and stroke. Orthostatic circulatory disease was defined as orthostatic hypotension, varicose vein, chronic venous insufficiency, and venous ulcers. Results During 6.9 (±0.9) years of follow-up 6,829 CVD and 2,042 orthostatic circulatory disease events occurred. When stationary time exceeded 12 hrs/day orthostatic circulatory disease risk was higher by an average HR [95% CI] of 0.22 [0.16, 0.29] per hour. Every additional hour above 10 hrs/day of sitting was associated with a 0.26 [0.18, 0.36] higher risk. Standing more than 2 hrs/day was associated with an 0.11 [0.05, 0.18] higher risk for every additional 30 min/day. For major CVD, when stationary time exceeded 12 hrs/day, risk was higher by an average of 0.13 [0.10, 0.16] per hour. Sitting time was associated with a 0.15 [0.11, 0.19] higher risk per extra hour. Time spent standing was not associated with major CVD risk. Conclusions Time spent standing was not associated with CVD risk but was associated with higher orthostatic circulatory disease risk. Time spent sitting above 10 hours/day was associated with both higher orthostatic circulatory disease and major CVD risk. The deleterious associations of overall stationary time were primarily driven by sitting. Collectively, our findings indicate increasing standing time as a prescription may not lower major CVD risk and may lead to higher orthostatic circulatory disease risk. Introduction Sitting and standing postures are termed collectively “stationary behaviour”, i.e. no ambulatory movement and low energy expenditure. 1 Both postures have attracted interest as independent risk factors for cardiovascular disease (CVD) and premature mortality 2 – 6 . Intervention and cross-sectional studies have suggested decreasing sitting (the main component of sedentary time) and standing may improve surrogate cardiovascular outcomes such as metabolic markers (e.g. density lipoproteins, total cholesterol, triglycerides) 7 , 8 . However, studies assessing clinical endpoints such as CVD hospitalisation and mortality risk are very scarce and show an unclear picture for the dose-response of both sitting and standing 9 , 10 . The majority of prospective sitting and standing time studies have relied on self-report measures, known for their inherent biases, eg. social desirability and recall, leading to imprecise evidence on links with cardiovascular disease incidence 11 – 13 . Importantly, prior studies have not differentiated orthostatic circulatory diseases from other CVD types when assessing sitting and standing time. Postural influences on autonomic neuropathy, and strain on the vascular (e.g., haemodynamic) and musculoskeletal systems may create distinctly separate mechanistic pathways between different postures (sitting and standing) and thus orthostatic circulatory diseases versus other CVD types such as coronary heart disease and stroke 14 – 18 . Collectively, these limitations may have contributed to the inconclusive evidence regarding the associations of standing time with CVD risk. Prior studies with mortality and CVD outcomes 19 – 21 have also unintentionally examined stationary behaviour by using waist attached wearable devices that only measured ambulatory activities and cannot differentiate between sitting and standing. Such misclassification in these studies, which were originally aimed at examining sedentary behaviour, may have distorted dose-response estimates of sitting time since standing often occupies approximately 20% to 30% of adults’ waking times (3-5 hours per day 22 , 23 ). Despite all these limitations of the current literature and the absence of consistent evidence with clinical endpoints 4 , 9 , standing has been recommended as health enhancing by clinicians and public health researchers 7 , 24 – 26 . In a large population sample of adults with device-based measures of posture and physical activity, we examined the prospective associations of stationary behaviour and its constituent components (sitting and standing) with major CVD incidence (coronary heart disease, stroke, and heart failure) and orthostatic circulatory disease. Methods Study participants Participants were included from the UK Biobank Study, a prospective cohort of 502,629 participants between 40-69 years. All participants were enrolled between 2006-2010 and provided informed written consent. Ethical approval was provided by the UK’s National Health Service, National Research Ethics Service (Ref 11/NW/0382). Participants completed physical examinations by trained staff and touchscreen questionnaires. 13 Orthostatic circulatory disease and CVD incidence ascertainment Participants were followed up through October 31 st , 2021, with deaths obtained through linkage with the National Health Service (NHS) Digital of England and Wales or the NHS Central Register and National Records of Scotland (September 30 th to October 31 st , 2021). Inpatient hospitalisation data were provided by either the Hospital Episode Statistics for England, the Patient Episode Database for Wales, or the Scottish Morbidity Record for Scotland (September 30 th 2021 for England, July 31 st for Scotland, and February 28 th 2018 for Wales). Primary care data were linked up to March 31 st to August 31 st 2017. We defined orthostatic circulatory disease events as orthostatic hypotension, varicose vein, chronic venous insufficiency, and venous ulcers 27 , 28 . Major CVD was defined as coronary heart disease, stroke, and heart failure. Full methods for the assessment of orthostatic circulatory disease and CVD events and ICD-10 codes are provided in Supplemental Table 1 . Sitting, standing, and non-stationary physical activity assessment Between 2013 and 2015, 103,684 participants wore an Axivity AX3 accelerometer (Axivity Ltd, Newcastle upon Tyne, UK) on their dominant wrist for 24-hrs/day for 7 days to measure physical activity. 24 Devices were calibrated and non-wear periods were identified according to standard procedures 29 – 31 . Primary exposures were daily time spent stationary (i.e. sitting and standing combined), sitting, and standing and were all classified with an accelerometer-based activity machine learning scheme that has been previously validated under free living conditions 32 , 33 . Briefly, this activity scheme uses features in the raw acceleration signal to identify and quantify time spent in sitting, standing, standing with movement, and walking/running in 60-second windows. Under free-living conditions, the activity classifier had a balanced accuracy (combination of sensitivity and specificity) of 88% for sitting time and 80% for standing time) 33 . We provide additional independent validation results in Supplemental Text 1 suggesting overall balanced accuracy of 84%. Covariates In line with previous analogous studies 9 , 34 and known correlates of posture 23 , covariates in our analyses included age, sex, body mass index 35 , smoking status, alcohol consumption, fruit and vegetable consumption, education, self-reported parental history of CVD, prevalent major CVD or orthostatic circulatory disease events as appropriate, and cholesterol, anti-hypertensive, or diabetes medication use. All analyses were also adjusted for accelerometer measured time spent stepping. We also included mutual adjustment for sitting time and standing time in the corresponding models. Complete covariate definitions are provided in Supplemental Table 2. Analyses We excluded participants with prevalent orthostatic circulatory disease and major CVD as appropriate, ascertained through self-report, hospital admission, and primary care linkage, as well as participants who were underweight (body mass index < 18.5 kg/m 2 ), had missing covariate data, or had an event within the first 12 months following the accelerometry measurements ( Supplemental Figure 1) . We calculated the adjusted dose-response absolute risk using Poisson regression, age- and sex-adjusted incidence rate ratios, and crude risk percent. We used Cox proportional hazards regression models to estimate the dose-response hazard ratios (HR) with 95% CIs for orthostatic circulatory disease and CVD events, with natural splines and knots placed at the 10 th , 50 th , and 90 th percentiles for stationary, standing and sitting time distributions. Fine-Gray subdistribution method was used with non-orthostatic circulatory disease or non-CVD mortality events treated as a competing risk, where appropriate. The proportional hazards assumption was assessed using Schoenfeld Residuals, and no violations were observed. Due to an absence of prior studies assessing clinical endpoints, we used the adjusted absolute risk curves to determine reference values for the three exposures, using the data point where orthostatic circulatory disease and CVD risk became pronounced ( Figures 1 - 2 ). The reference points were 12 hours/day, 10 hours/day, and 2.5 hours/day for stationary, sitting, and standing time, respectively. Departure from linearity was assessed by a Wald test examining the null hypothesis that the coefficient of the second spline was equal to zero. We calculated E-values to estimate the plausibility of bias from unmeasured confounding. The E-values indicate the required magnitude of the association unmeasured confounders to reduce findings to null. To provide conservative E-value point estimates, we assessed the minimal dose, defined as the duration of each exposure associated with 50% of the highest HR (‘minimum harmful dose’). Download figure Open in new tab Figure 1: Adjusted absolute risk of stationary, standing, and sitting time with orthostatic circulatory disease incidence Legend: Adjusted for age, sex, ethnicity, smoking history, alcohol consumption, time spent walking, mutual adjustment for time spent standing and sitting, education, diet, family history of CVD, prevalent CVD incidence, and medication use. Download figure Open in new tab Figure 2: Adjusted absolute risk of stationary, standing, and sitting time with major cardiovascular disease incidence Legend: Adjusted for age, sex, ethnicity, smoking history, alcohol consumption, time spent walking, mutual adjustment for time spent standing and sitting, education, diet, family history of CVD, prevalent orthostatic incidence, and medication use. To assess the influence of residual confounding, we used a negative control outcome of deaths and hospitalisation from accidents (excluding accidents that may be associated with physical activity. i.e. cycling, and falls incidence, or self-harm), an outcome that does not have a mechanistic link to stationary behaviour. Negative controls can improve causal inference by illustrating pervasive bias and confounding. If the negative control has a similar association pattern as the primary outcomes, then it is more plausible associations are due to bias and confounding than causal mechanisms 36 . We conducted sensitivity analyses to minimise bias attributable to reverse causation by: 1) exclusion of participants who were obese (body mass index >30 kg/m 2 ); 2) exclusion of participants reporting fair or poor health; or 3) those with an event within the first 24 months of follow-up. We performed all analyses using R statistical software. We reported this study as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline (see STROBE Statement in the Supplement). Results Our analytic sample for orthostatic circulatory disease incidence included 83,013 participants (average age [sd]= 61.3 (7.8) years; 55.6% female) followed-up for an average of 6.9 ± 0.9 years with 2,042 events. Our CVD incidence sample included 75,897 participants with 6,829 events. Mean (SD) time spent stationary, standing and sitting was 12.8 (1.6) hours/day, 2.1 (0.9) hours/day, and 10.7 (1.9) hours/day, respectively. Participants spent an average of 71.3 minutes/day ambulatory (walking/running) at any intensity and 64.0% of the participants were not smokers. Participant characteristics by stationary behaviour daily duration is provided in Table 1 . Participant characteristics by standing and sitting daily duration are presented in Supplemental Tables 3 and 4 . Participants in the higher quartiles of sitting were more likely to be male and have tertiary education, whilst participants in higher quartiles of standing were more likely to be female and less educated. View this table: View inline View popup Table 1: Participant descriptive characteristics by stationary time Absolute risk Supplemental Tables 5-6 present the crude risk and partially adjusted incidence rate ratios for orthostatic circulatory disease and major CVD events by quartiles of each exposure. For orthostatic circulatory disease, participants who had <12 hours/day of stationary time had a crude risk of 2.49% (95% CI= 2.46%, 2.52%), whereas ≥14 hours/day had a crude risk of 5.22% (5.14%, 5.29%). Corresponding values for CVD are 2.70% (2.67%, 2.74%) for <12 hours/day and 5.13% (5.05%, 5.20%) for ≥14 hours/day. The adjusted absolute risk dose-responses per 1,000 person years are shown in Figures 1 - 2 . For CVD and orthostatic circulatory disease incidence, the dose-response was non-linear for stationary and sitting time with risk becoming more pronounced after approximately 12 hours/day and 10.5 hours/day, respectively. For standing time, the risk became more pronounced after 2 hours/day for orthostatic circulatory disease, however we observed no changes in CVD incidence risk between 1 hour/day (e.g. 160 [95% CI= 157, 163] events/1,000 person-years) through 4 hours/day (160 [158, 162] events/1,000 person-years). For CVD incidence, more standing time was not associated with higher absolute risk. Multivariable adjusted associations for orthostatic circulatory disease When stationary time exceeded the 12 hours/day referent data point, risk increased by an average HR of 0.22 (95% CI= 0.16, 0.29) with every 1 hour increment ( Figure 3 ). Similarly, every 1 hour increment of sitting time above the reference data point of 10 hours/day (referent) was associated with an average HR increase of 0.26 (0.18, 0.36). For standing time, compared to the referent 2 hours/day, every 30 minute increment above 2 hours/day was associated with an average HR increase of 0.11 (0.05, 0.18). For all three exposures, we observed a null to weak protective association for time spent below the referent value. For example, 9 hours/day sitting and 1.5 hours/day standing was associated with an HR of 0.96 (0.93, 0.99) and 0.94 (0.90, 0.99). Download figure Open in new tab Figure 3: Dose-response associations of stationary, standing, and sitting time with orthostatic circulatory disease incidence Legend: Adjusted for age, sex, ethnicity, smoking history, alcohol consumption, time spent walking, mutual adjustment for time spent standing and sitting, education, diet, family history of CVD, prevalent CVD incidence, and medication use. Multivariable adjusted associations for major cardiovascular disease incidence When stationary time exceeded 12 hours/day, we observed higher CVD risk in a linear fashion ( Figure 4 ). Every 1 hour increment in stationary time above 12 hours/day was associated with an average HR increase of 0.13 (0.10, 0.16). We observed lower CVD risk when stationary time was below 12 hours/day. For example, at 9 hours/day we observed an HR of 0.87 (0.78, 0.96). We also observed a linear association for sitting time when the daily duration was above 10 hours/day. Every 1 hour increment above 10 hours/day associated with an average HR increase of 0.15 (0.11, 0.19). When sitting time was below 10 hours/day we observed lower CVD risk (e.g. 9 hours/day of sitting time had an HR of 0.95 (0.93, 0.97)). Contrary to sitting time, more time spent standing was not associated with a higher CVD risk. Overall, there was no association for higher or lower CVD risk throughout the range of standing duration. Download figure Open in new tab Figure 4: Dose-response association of stationary, standing, and sitting time with major cardiovascular disease incidence Legend: Adjusted for age, sex, ethnicity, smoking history, alcohol consumption, time spent walking, mutual adjustment for time spent standing and sitting, education, diet, family history of CVD, prevalent orthostatic incidence, and medication use. Additional and sensitivity analyses The association pattern for orthostatic circulatory disease and CVD incidence remained consistent after exclusion of participants who were: 1) obese; 2) reported fair or poor health; 3) or had an event within the first 24 months of follow-up ( Supplemental Figures 2 - 3 ). Negative control outcomes and E-values analyses for the minimum harmful dose indicated that residual and unmeasured confounding had minimal impact on the findings. Specifically, with the negative control outcome, associations for standing were non-significant with wide 95% CIs, and sitting behaviour point estimates were inconsistent with the main analysis showing a U-shaped association ( Supplemental Figure 4 ). The E-values suggest a substantial degree of unmeasured confounding would be required to reduce our observed associations at the minimum harmful dose for orthostatic circulatory disease (e.g., an association of 2.01 to 2.79) and CVD incidence (1.97 to 2.13) to null ( Supplemental Table 7 ). Discussion In a largest wearables-based study of stationary time and its constituent components of standing and sitting time in > 83,000 adults we observed a linear association for higher orthostatic circulatory disease risk from increased standing time with no protective association for CVD risk. After approximately 10.5 hours/day, we observed a deleterious association of increased sitting time with higher risk of both orthostatic circulatory disease and CVD risk. This calls to question current intervention strategies that focus on only replacing sitting with standing time without increasing physical activity 37 . Orthostatic circulatory disease risk stationary time as well as its constituent postures sitting and standing behaviours were all associated with increased risk of orthostatic circulatory disease. For stationary time, risk increased by an average 22% with every 1 hour increment, above 12 hours/day. For sitting time, above 10 hours/day, risk increased by an average 26% with every 1 hour. For standing time, risk increased by an average of 11% with every 30 minute increment above 2 hours/day. The pattern of the dose-response relationship appears similar for sitting and standing ( Fig 1 ) suggesting that a common aspect of sitting and standing, i.e. absence of ambulatory movement, is likely to be important in the mechanistic pathway for orthostatic circulatory disease. The lack of muscle movement during stationary time may result in a reduced venous return by skeletal muscle contraction and pumps contributing to venous pooling, causing orthostatic circulatory problems 38 . Therefore, a key implication of our finding is that non-stationary movement (e.g., walking, cycling, or other physical activities involving some degree of movement) is important to reduce orthostatic circulatory disease risk, aligning with current public health messaging to ‘move more’ 39 . If confirmed to be causal in future randomised control trials, our findings would have implications for patient care among those at high risk of CVD. Public health strategies that promote standing as a sufficient substitute to overcome the cardiovascular health risks of sitting (e.g., as seen by common advice to adopt standing desks in office environments) may not achieve their goal. Our findings also suggest the dose-risk association between stationary time and orthostatic circulatory disease is non-linear, with no association for lower risk below inflexion points of approximately 10 hours of sitting/day and 2 hours of standing/day. This suggests simple messaging to ‘sit less’ may not be optimal, as that would not lower the risk for those currently accumulating less than 10 hrs a day and may even increase risk of musculoskeletal 14 and circulatory issues by increasing the time spent standing. The non-linear associations we detected suggest that up to a certain level, neither sitting nor standing are harmful for orthostatic conditions, suggesting that a there may be a healthy balance between these two behaviours. This balance likely varies among individuals depending on co-morbidities, overall health status, and daily physical activity levels 40 , 41 . Cardiovascular disease risk Stationary and sitting behaviour were both associated with increased risk of CVD above certain thresholds. For stationary time, risk increased by an average of 13% with every 1 hour increment above the reference 12 hours/day. For sitting time, risk increased by an average of 15% with every 1 hour increment above 10 hours/day,. Standing time was not associated with CVD risk. The higher CVD risk we observed with sitting time is similar in magnitude to the associations reported in prior studies of sitting and CVD outcomes 2 , 34 , 42 . The pattern of dose-risk relationship appears similar for sitting and overall stationary but not for standing ( Figs 2 and 4 ), suggesting that the sitting component is driving these associations, rather than the absence of movement. There are additional possible mechanisms that are unique to sitting. For example, the lower cumulative energy expenditure of sitting and the muscular and musculoskeletal system engagement during standing 43 may partly explain the differential effects of the two postures. Although standing time was not associated with higher CVD risk, we did not observe a protective association. Collectively, the implications of our findings for public health messaging are supportive of current messages 39 encouraging sitting reductions for CVD health, however they do not support increasing standing time alone as a mitigation strategy cited in some guidelines 44 . Strengths and limitations A key strength of this study was that, unlike previous device-based studies, we were able to separately examine the components of stationary behaviours, enabling the estimation of risks associated with sitting versus standing, two postures that are underpin by different mechanisms and both have public health an clinical importance. We utilised the largest wearables -based data resource with rich contextual and linkage to health outcomes information. The wrist placement improves translation of our findings into public health messaging and immediate uptake by users of consumer level wrist wearables. Among the general public that tracks and provides feedback on time spent sitting, standing, and active throughout a day. Limitations of our study included the potential misclassification of posture and movement that is inherent to wrist worn devices, although our daily estimates are similar to sitting and standing time assessed from the gold standard of wearables postural assessment, thigh-worn devices, in other UK cohorts 23 , 45 . The observational design of our study precludes us from making causal interpretations. We cannot rule out the presence of unmeasured confounding, although our E-values indicated that unmeasured confounders would need to have to have a very strong association with the exposure and outcomes for the observed associations to be null. The UK Biobank had a low response rate, however previous work has shown that poor representativeness does not materially influence the associations between lifestyle risk factors and noncommunicable disease risk 46 . Conclusion The deleterious associations of stationary time with CVD and orthostatic circulatory disease we observed were primarily a consequence of time spent sitting. More time spent standing was not associated with CVD risk but was associated with substantially higher risk of orthostatic circulatory disease. Collectively, our findings are supportive of clinical and public health strategies to curtail excessive sitting time as an important risk factor for major CVD. However, standing time alone may not be a sufficient mitigation strategy for lower CVD risk, and may lead to a higher risk of circulatory conditions. Data Availability All data produced in the present study are available upon application to the UK BioBank. https://www.ukbiobank.ac.uk/ Footnotes Conflicts of interest: The authors have no conflicts to disclose. References 1. ↵ Tremblay MS , Aubert S , Barnes JD , Saunders TJ , Carson V , Latimer-Cheung AE , Chastin SFM , Altenburg TM , Chinapaw MJM . Sedentary Behavior Research Network (SBRN) – Terminology Consensus Project process and outcome . International Journal of Behavioral Nutrition and Physical Activity . 2017 ; 14 . doi: 10.1186/s12966-017-0525-8 OpenUrl CrossRef PubMed 2. ↵ Pandey A , Salahuddin U , Garg S , Ayers C , Kulinski J , Anand V , Mayo H , Kumbhani DJ , De Lemos J , Berry JD . Continuous Dose-Response Association Between Sedentary Time and Risk for Cardiovascular Disease . JAMA Cardiology . 2016 ; 1 : 575 . doi: 10.1001/jamacardio.2016.1567 OpenUrl CrossRef PubMed 3. Lavie CJ , Ozemek C , Carbone S , Katzmarzyk PT , Blair SN . Sedentary Behavior, Exercise, and Cardiovascular Health . Circulation Research . 2019 ; 124 : 799 – 815 . doi: 10.1161/circresaha.118.312669 OpenUrl CrossRef PubMed 4. ↵ Smith P , Ma H , Glazier RH , Gilbert-Ouimet M , Mustard C . The Relationship Between Occupational Standing and Sitting and Incident Heart Disease Over a 12-Year Period in Ontario, Canada . Am J Epidemiol . 2018 ; 187 : 27 – 33 . doi: 10.1093/aje/kwx298 OpenUrl CrossRef PubMed 5. Arnett DK , Khera A , Blumenthal RS . 2019 ACC / AHA Guideline on the Primary Prevention of Cardiovascular Disease : Part 1 , Lifestyle and Behavioral Factors . In; 2021 : 1043 – 1044 . 6. ↵ Visseren FLJ , Mach F , Smulders YM , Carballo D , Koskinas KC , Bäck M , Benetos A , Biffi A , Boavida J-M , Capodanno D , et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice . European Heart Journal . 2021; 42 : 3227 – 3337 . doi: 10.1093/eurheartj/ehab484 OpenUrl CrossRef PubMed 7. ↵ Healy GN , Winkler EA , Owen N , Anuradha S , Dunstan DW . Replacing sitting time with standing or stepping: associations with cardio-metabolic risk biomarkers . Eur Heart J . 2015 ; 36 : 2643 – 2649 . doi: 10.1093/eurheartj/ehv308 OpenUrl CrossRef PubMed 8. ↵ Torbeyns T , Bailey S , Bos I , Meeusen R . Active Workstations to Fight Sedentary Behaviour . Sports Medicine . 2014 ; 44 : 1261 – 1273 . doi: 10.1007/s40279-014-0202-x OpenUrl CrossRef PubMed 9. ↵ van der Ploeg HP , Chey T , Ding D , Chau JY , Stamatakis E , Bauman AE . Standing time and all-cause mortality in a large cohort of Australian adults . Prev Med . 2014 ; 69 : 187 – 191 . doi: 10.1016/j.ypmed.2014.10.004 OpenUrl CrossRef PubMed 10. ↵ Shockey TM , Luckhaupt SE , Groenewold MR , Lu M-L . Frequent exertion and frequent standing at work, by industry and occupation group—United States, 2015 . Morbidity and Mortality Weekly Report . 2018 ; 67 : 1 . OpenUrl 11. ↵ Reis JP , DuBose KD , Ainsworth BE , Macera CA , Yore MM . Reliability and validity of the occupational physical activity questionnaire . Medicine and science in sports and exercise . 2005 ; 37 : 2075 – 2083 . OpenUrl CrossRef PubMed Web of Science 12. Chastin S , Culhane B , Dall P . Comparison of self-reported measure of sitting time (IPAQ) with objective measurement (activPAL) . Physiological measurement . 2014 ; 35 : 2319 . OpenUrl CrossRef PubMed 13. ↵ Prince SA , Cardilli L , Reed JL , Saunders TJ , Kite C , Douillette K , Fournier K , Buckley JP . A comparison of self-reported and device measured sedentary behaviour in adults: a systematic review and meta-analysis . International Journal of Behavioral Nutrition and Physical Activity . 2020 ; 17 : 1 – 17 . OpenUrl 14. ↵ Coenen P , Willenberg L , Parry S , Shi JW , Romero L , Blackwood DM , Maher CG , Healy GN , Dunstan DW , Straker LM . Associations of occupational standing with musculoskeletal symptoms: a systematic review with meta-analysis . Br J Sports Med . 2018 ; 52 : 176 – 183 . doi: 10.1136/bjsports-2016-096795 OpenUrl Abstract / FREE Full Text 15. Coenen P , Parry S , Willenberg L , Shi JW , Romero L , Blackwood DM , Healy GN , Dunstan DW , Straker LM . Associations of prolonged standing with musculoskeletal symptoms—A systematic review of laboratory studies . Gait & Posture . 2017 ; 58 : 310 – 318 . doi: 10.1016/j.gaitpost.2017.08.024 OpenUrl CrossRef PubMed 16. Xin W , Mi S , Lin Z , Wang H , Wei W . Orthostatic hypotension and the risk of incidental cardiovascular diseases: A meta-analysis of prospective cohort studies . Prev Med . 2016 ; 85 : 90 – 97 . doi: 10.1016/j.ypmed.2016.01.007 OpenUrl CrossRef 17. Benvenuto LJ , Krakoff LR . Morbidity and mortality of orthostatic hypotension: implications for management of cardiovascular disease . Am J Hypertens . 2011 ; 24 : 135 – 144 . doi: 10.1038/ajh.2010.146 OpenUrl CrossRef PubMed 18. ↵ Juraschek SP , Daya N , Appel LJ , Miller ER , McEvoy JW , Matsushita K , Ballantyne CM , Selvin E . Orthostatic Hypotension and Risk of Clinical and Subclinical Cardiovascular Disease in Middle-Aged Adults . Journal of the American Heart Association . 2018 ; 7 : e008884 . doi: 10.1161/jaha.118.008884 OpenUrl Abstract / FREE Full Text 19. ↵ Vasankari V , Husu P , Vaha-Ypya H , Suni J , Tokola K , Halonen J , Hartikainen J , Sievanen H , Vasankari T . Association of objectively measured sedentary behaviour and physical activity with cardiovascular disease risk . Eur J Prev Cardiol . 2017 ; 24 : 1311 – 1318 . doi: 10.1177/2047487317711048 OpenUrl CrossRef 20. Healy GN , Matthews CE , Dunstan DW , Winkler EA , Owen N . Sedentary time and cardio-metabolic biomarkers in US adults: NHANES 2003–06 . European heart journal . 2011 ; 32 : 590 – 597 . OpenUrl CrossRef PubMed Web of Science 21. ↵ Ekelund U , Tarp J , Fagerland MW , Johannessen JS , Hansen BH , Jefferis BJ , Whincup PH , Diaz KM , Hooker S , Howard VJ , et al. Joint associations of accelerometer-measured physical activity and sedentary time with all-cause mortality: a harmonised meta-analysis in more than 44 000 middle-aged and older individuals . British Journal of Sports Medicine . 2020 ; 54 : 1499 – 1506 . doi: 10.1136/bjsports-2020-103270 OpenUrl Abstract / FREE Full Text 22. ↵ Van der Velde JH , Koster A , Van der Berg JD , Sep SJ , Van der Kallen CJ , Dagnelie PC , Schram MT , Henry RM , Eussen SJ , Van Dongen MC . Sedentary behavior, physical activity, and fitness-the Maastricht study . Medicine and Science in Sports and Exercise . 2017 ; 49 : 1583 – 1591 . OpenUrl PubMed 23. ↵ Hamer M , Stamatakis E . The descriptive epidemiology of standing activity during free-living in 5412 middle-aged adults: the 1970 British cohort study . J Epidemiol Community Health . 2020 ; 74 : 757 – 760 . OpenUrl Abstract / FREE Full Text 24. ↵ Healy GN , Winkler EA , Eakin EG , Owen N , Lamontagne AD , Moodie M , Dunstan DW . A Cluster RCT to Reduce Workers’ Sitting Time: Impact on Cardiometabolic Biomarkers . Medicine and science in sports and exercise . 2017 ; 49 : 2032 – 2039 . OpenUrl CrossRef PubMed 25. Saeidifard F , Medina-Inojosa JR , Supervia M , Olson TP , Somers VK , Prokop LJ , Stokin GB , Lopez-Jimenez F . The Effect of Replacing Sitting With Standing on Cardiovascular Risk Factors: A Systematic Review and Meta-analysis. Mayo Clinic Proceedings: Innovations , Quality & Outcomes . 2020 ; 4 : 611 – 626 . doi: 10.1016/j.mayocpiqo.2020.07.017 OpenUrl CrossRef 26. ↵ Aadahl M , Linneberg A , Møller TC , Rosenørn S , Dunstan DW , Witte DR , Jørgensen T . Motivational counseling to reduce sitting time: a community-based randomized controlled trial in adults . American journal of preventive medicine . 2014 ; 47 : 576 – 586 . OpenUrl CrossRef PubMed 27. ↵ Freeman R . Neurogenic Orthostatic Hypotension . New England Journal of Medicine . 2008 ; 358 : 615 – 624 . doi: 10.1056/nejmcp074189 OpenUrl CrossRef PubMed Web of Science 28. ↵ Eberhardt RT , Raffetto JD . Chronic Venous Insufficiency . Circulation . 2014 ; 130 : 333 – 346 . doi: 10.1161/circulationaha.113.006898 OpenUrl FREE Full Text 29. ↵ Ahmadi MN , Clare PJ , Katzmarzyk PT , Del Pozo Cruz B, Lee IM, Stamatakis E. Vigorous physical activity, incident heart disease, and cancer: how little is enough? Eur Heart J . 2022 . doi: 10.1093/eurheartj/ehac572 OpenUrl CrossRef 30. Stamatakis E , Ahmadi MN , Gill JMR , Thøgersen-Ntoumani C , Gibala MJ , Doherty A , Hamer M . Association of wearable device-measured vigorous intermittent lifestyle physical activity with mortality . Nature Medicine . 2022 ; 28 : 2521 – 2529 . doi: 10.1038/s41591-022-02100-x OpenUrl CrossRef 31. ↵ Ahmadi MN , Nathan N , Sutherland R , Wolfenden L , Trost SG . Non-wear or sleep? Evaluation of five non-wear detection algorithms for raw accelerometer data . Journal of Sports Sciences . 2020 ; 38 : 399 – 404 . doi: 10.1080/02640414.2019.1703301 OpenUrl CrossRef 32. ↵ Ellis K , Kerr J , Godbole S , Lanckriet G , Wing D , Marshall S . A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers . Physiological measurement . 2014 ; 35 : 2191 . OpenUrl CrossRef PubMed 33. ↵ Ellis K , Kerr J , Godbole S , Staudenmayer J , Lanckriet G . Hip and Wrist Accelerometer Algorithms for Free-Living Behavior Classification . Med Sci Sports Exerc . 2016 ; 48 : 933 – 940 . doi: 10.1249/MSS.0000000000000840 OpenUrl CrossRef PubMed 34. ↵ Stamatakis E , Gale J , Bauman A , Ekelund U , Hamer M , Ding D . Sitting Time, Physical Activity, and Risk of Mortality in Adults . J Am Coll Cardiol . 2019 ; 73 : 2062 – 2072 . doi: 10.1016/j.jacc.2019.02.031 OpenUrl FREE Full Text 35. ↵ Pedisic Z , Grunseit A , Ding D , Chau JY , Banks E , Stamatakis E , Jalaludin BB , Bauman AE . High sitting time or obesity: Which came first? Bidirectional association in a longitudinal study of 31,787 Australian adults . Obesity (Silver Spring) . 2014 ; 22 : 2126 – 2130 . doi: 10.1002/oby.20817 OpenUrl CrossRef PubMed 36. ↵ Lipsitch M , Tchetgen Tchetgen E , Cohen T . Negative controls: a tool for detecting confounding and bias in observational studies . Epidemiology . 2010 ; 21 : 383 – 388 . doi: 10.1097/EDE.0b013e3181d61eeb OpenUrl CrossRef PubMed Web of Science 37. ↵ Buckley JP , Hedge A , Yates T , Copeland RJ , Loosemore M , Hamer M , Bradley G , Dunstan DW . The sedentary office: an expert statement on the growing case for change towards better health and productivity . Br J Sports Med . 2015 ; 49 : 1357 – 1362 . doi: 10.1136/bjsports-2015-094618 OpenUrl Abstract / FREE Full Text 38. ↵ Gutkin M , Stewart JM . Orthostatic Circulatory Disorders: From Nosology to Nuts and Bolts . Am J Hypertens . 2016 ; 29 : 1009 – 1019 . doi: 10.1093/ajh/hpw023 OpenUrl CrossRef PubMed 39. ↵ Bull FC , Al-Ansari SS , Biddle S , Borodulin K , Buman MP , Cardon G , Carty C , Chaput J-P , Chastin S , Chou R , et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour . British Journal of Sports Medicine . 2020 ; 54 : 1451 – 1462 . doi: 10.1136/bjsports-2020-102955 OpenUrl Abstract / FREE Full Text 40. ↵ Straker L , Mathiassen SE , Holtermann A . The ‘Goldilocks Principle’: designing physical activity at work to be ‘just right’for promoting health . In: BMJ Publishing Group Ltd and British Association of Sport and Exercise Medicine ; 2018 : 818 – 819 . 41. ↵ Holtermann A , Rasmussen CL , Hallman DM , Ding D , Dumuid D , Gupta N . 24-Hour Physical Behavior Balance for Better Health for All: “The Sweet-Spot Hypothesis” . Sports Medicine - Open . 2021 ; 7 . doi: 10.1186/s40798-021-00394-8 OpenUrl CrossRef 42. ↵ Wilmot EG , Edwardson CL , Achana FA , Davies MJ , Gorely T , Gray LJ , Khunti K , Yates T , Biddle SJ . Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis . Diabetologia . 2012 ; 55 : 2895 – 2905 . OpenUrl CrossRef PubMed Web of Science 43. ↵ Mansoubi M , Pearson N , Clemes SA , Biddle SJ , Bodicoat DH , Tolfrey K , Edwardson CL , Yates T . Energy expenditure during common sitting and standing tasks: examining the 1.5 MET definition of sedentary behaviour . BMC Public Health . 2015 ; 15 . doi: 10.1186/s12889-015-1851-x OpenUrl CrossRef 44. ↵ Ross R , Chaput J-P , Giangregorio LM , Janssen I , Saunders TJ , Kho ME , Poitras VJ , Tomasone JR , El-Kotob R , McLaughlin EC . Canadian 24-Hour Movement Guidelines for Adults aged 18–64 years and Adults aged 65 years or older: an integration of physical activity, sedentary behaviour, and sleep. Applied Physiology , Nutrition, and Metabolism . 2020 ; 45 : S57 – S102 . OpenUrl 45. ↵ Hamer M , Stamatakis E , Chastin S , Pearson N , Brown M , Gilbert E , Sullivan A . Feasibility of measuring sedentary time with thigh worn accelerometry and sociodemographic correlates: the 1970 British Cohort Study . Available at SSRN 3464422 . 2019 . 46. ↵ Stamatakis E , Owen KB , Shepherd L , Drayton B , Hamer M , Bauman AE . Is Cohort Representativeness Passe? Poststratified Associations of Lifestyle Risk Factors with Mortality in the UK Biobank . Epidemiology . 2021 ; 32 : 179 – 188 . doi: 10.1097/EDE.0000000000001316 OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted January 18, 2024. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Device-measured stationary behaviour and cardiovascular and orthostatic circulatory disease incidence: a population cohort study of 83,013 adults Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Device-measured stationary behaviour and cardiovascular and orthostatic circulatory disease incidence: a population cohort study of 83,013 adults Matthew N. Ahmadi , Pieter Coenen , Leon Straker , Emmanuel Stamatakis medRxiv 2024.01.17.24301458; doi: https://doi.org/10.1101/2024.01.17.24301458 Share This Article: Copy Citation Tools Device-measured stationary behaviour and cardiovascular and orthostatic circulatory disease incidence: a population cohort study of 83,013 adults Matthew N. Ahmadi , Pieter Coenen , Leon Straker , Emmanuel Stamatakis medRxiv 2024.01.17.24301458; doi: https://doi.org/10.1101/2024.01.17.24301458 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Epidemiology Subject Areas All Articles Addiction Medicine (573) Allergy and Immunology (865) Anesthesia (302) Cardiovascular Medicine (4453) Dentistry and Oral Medicine (444) Dermatology (383) Emergency Medicine (609) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1515) Epidemiology (15242) Forensic Medicine (30) Gastroenterology (1131) Genetic and Genomic Medicine (6615) Geriatric Medicine (669) Health Economics (1001) Health Informatics (4552) Health Policy (1372) Health Systems and Quality Improvement (1614) Hematology (543) HIV/AIDS (1270) Infectious Diseases (except HIV/AIDS) (15929) Intensive Care and Critical Care Medicine (1106) Medical Education (624) Medical Ethics (147) Nephrology (670) Neurology (6625) Nursing (346) Nutrition (999) Obstetrics and Gynecology (1148) Occupational and Environmental Health (957) Oncology (3344) Ophthalmology (979) Orthopedics (369) Otolaryngology (421) Pain Medicine (436) Palliative Medicine (130) Pathology (665) Pediatrics (1696) Pharmacology and Therapeutics (693) Primary Care Research (714) Psychiatry and Clinical Psychology (5461) Public and Global Health (9252) Radiology and Imaging (2207) Rehabilitation Medicine and Physical Therapy (1371) Respiratory Medicine (1197) Rheumatology (597) Sexual and Reproductive Health (715) Sports Medicine (530) Surgery (714) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a02dd858fe57300f',t:'MTc3OTk3NzQ1MA=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();