headlines in recent newspaper and magazine articles have proclaimed  sitting is killing you ' , and ask  are you sitting too much ' ? this interest in sedentary behavior is justified , if exaggerated , by a growing body of evidence that points to a relationship between sedentary behavior and disease that is separate from the lack of moderate- or vigorous - intensity physical activity . throughout history even traditional societies that promote spirituality over physical growth , as in ancient hinduism , came up with a way of combating inactivity  yoga . because of the improvements in sedentary behavior measurement , we are now beginning to see the magnitude of the relationship between sedentary behavior and disease outcomes . the initial results are so compelling that researchers have decided that   in the future , investigators should focus as much attention on the lower end of the activity intensity continuum as has traditionally been placed on the higher end of that continuum ' . increased interest in sedentary behavior stems from four different health - related trends taking place at the same time . first , americans are increasingly relying on technology for our daily tasks , and therefore are more sedentary than they have ever been in the history of this country . second , there is new physiological evidence of specific metabolic effects that are unique to being sedentary and detrimental to health . third , we now know how to better use objective measurement tools , such as accelerometers , to closely measure sedentary time throughout the day . finally , as it has proven to be difficult to motivate the population to do regular , vigorous bouts of physical activity , reducing sedentary behavior may be a promising alternative or complementary intervention area for disease prevention . the combination of light - intensity activity (  puttering around ' ) and sedentary time makes up 96% of the average american 's waking hours , opening a large window of opportunity to make minor increases in activity intensity . the definition of sedentary behavior has been a moving target for researchers in the past , but there is consensus building around certain aspects of the definition . leading researchers in this field have defined sedentary behavior as a combination of sitting and low levels of energy expenditure ; anything with a sitting posture , unless it is an activity such as sitting on an exercise bike , qualifies as sedentary . these researchers and others have defined energy expenditures associated with sitting as less than 1.5 mets , or metabolic equivalents , which seems to be an accurate assessment of the energy - expenditure level for sitting with very little movement . unfortunately , this definition of sedentary would also include standing and other non - sitting activities . the assessment of television viewing time is also considered a measure of a sedentary behavior , but this will only give a description of leisure time behavior , not occupational behavior . in addition , accelerometers can provide objective measurement of the amount of time spent in low levels of activity . however , the assessment of sedentary behavior with these latter two measures remains problematic in terms of the recent consensus definition , because neither of the measures directly assess either sitting or energy expenditure . reducing sedentary behavior , although seen as a promising avenue for interventions aimed at disease prevention , remains a difficult challenge given that validated measures have not been established . therefore , it has been difficult to set guidelines as to what the goal of a sedentary behavior reduction intervention should be . recent research has taken a novel approach to finding the health effects of sedentary behavior by changing the focus from a lack of exercise to exploring the balance between sitting and moving around in light - intensity activity . in this model , the analysis controls for time spent in moderate and vigorous physical activity ( exercise ) to separate the health effects of exercise from sedentary time as an independent predictor of health outcomes . controlling for time spent exercising , a large study of canadians showed a dose  response relationship between time spent sitting , and all - cause mortality and mortality from cardiovascular disease , with the highest mortality rates being among the most sedentary and obese . in other studies , after controlling for exercise , sedentary behavior has been linked to a number of poor health outcomes , including metabolic syndrome , abnormal glucose metabolism , heart disease and obesity . inactivity physiology , a term coined to describe the molecular study of sedentary behavior , has shown one important mechanism that may be at work during sedentary behavior , and its relationship with health outcomes . regulation of lipoprotein lipase ( lpl ) is impaired during simulated sedentary behavior in rats , and simple standing motions are enough to reverse this effect . impaired lpl is associated with metabolic risk factors , and increasing light - intensity activity had a greater effect on lpl than the addition of exercise training , and the mechanism at work while being sedentary is different from the protective mechanism of exercise . there is a need to understand the mechanism governing the relationship between sedentary metabolism , with and without excess of calories , and the active metabolism during light - intensity physical activity . the plausibility of an association between sedentary behavior and obesity is obvious , but the directionality of the association is difficult to assess and may be bidirectional . when ekelund et al . studied the relationship between obesity and sedentary behavior , overweight subjects were more likely to be sedentary at a later time , but sedentary subjects were not more likely to be overweight at a later time . the strong link between obesity and sedentary behavior shows that in addition to an obesity epidemic in america , we most likely also have a  sedentary epidemic ' confirmed by the large amount of time in daily life americans spend in sedentary behavior . in addition , interventions aimed at reducing sedentary behaviors should be more intensely focused on an obese population . sedentary behavior measurement is difficult , because the mechanisms that lead to the detrimental health effects associated with sedentary behavior have not been defined . currently , there are either self - report questionnaires or objective measures of sedentary behavior . this discussion will focus on objective measures , and these measures are accelerometer- or motion - sensor - based devices . accelerometers are quite common tools for measurement , but they are usually embedded in some other device . smart phones all have accelerometers in them to play games and orient the screen correctly . objective physical activity measurement in research also relies mostly on accelerometer - based devices , such as the actigraph . unfortunately , as sedentary measurement is relatively new , the standards have not yet been established for objective monitors . the actigraph has been used in a number of studies to measure sedentary behavior , but there are limitations with using the actigraph that need to be understood when looking at the results of these studies . many investigators have used a cutoff point of 100  counts per min as their definition of sedentary behavior based on observation . fortunately , recent calibration studies have shown that this was a reasonable and possibly an optimal sedentary cutoff point . second , the standard positioning of the actigraph ( attached near the hip ) or any other hip - located accelerometer registers up to 100  counts per min while sitting , but there are similarly low counts for activities , such as standing in line , riding a stationary cycle , taking a nap , standing at a stand - up desk , or most other stationary activities that can be performed standing or lying down . it also does not directly measure energy expenditure , the other part of the recently established definition . it estimates higher levels of energy expenditure with some accuracy ( r values are around 0.55 when including daily activities ) , but it is not considered an acceptable measure for activities with lower energy expenditures . despite these noted limitations , the use of the actigraph has been widespread in epidemiological studies , and it is one of the few available approaches for scientists to control for or stratify populations based on time spent in sedentary behavior . the assumption that this device can be validly used to estimate sedentary behavior is reasonably sound , because most of the human activities are locomotion - based , and it does distinguish sitting activities such as sedentary and ambulation as active ; however , there is still considerable room for improvement . the actigraph and activpal have significant differences in measured sedentary time , with the actigraph reporting a higher number of minutes in sedentary behavior . the placement of the activpal is both a strength and a weakness for the device . in terms of assessing the  sitting ' component of sedentary behavior measurement , the activpal is the most accurate accelerometer - based device , because its orientation changes markedly when going from a standing to a sitting posture . in terms of activity intensity measurement , the energy expenditure estimates with this device can produce a significant underestimation , and as the device is attached to the thigh with a sticker , getting people to wear the device can prove difficult for any sort of long - term measurement . therefore , the selection of the appropriate sedentary measurement device will depend on how sedentary behavior is defined  a lack of increased energy expenditure versus sitting . in the future , measurement of sedentary behavior and the interventions designed to reduce sedentary behavior will likely be mobile - phone - based systems . collaboration between northeastern university , massachusetts institute of technology and stanford university has produced the wocket system . wockets are two accelerometers worn on wrist and ankle that communicate via a wireless signal to a mobile phone . the positioning of the wockets on the wrist and ankle have three advantages : the ankle provides counts that are similar to the counts produced at the hip , focus groups have confirmed that wearing the devices at these locations will improve compliance to the protocol , and the wrist and ankle provide the best data for activity - recognition algorithms . activity data are recorded on the phone and delivered through the data network to a secure server , and access to the server can be made through any web browser . this is a powerful system , because there is no user burden to upload the data ; the only requirement is to wear the accelerometers and keep the phone in normal use . it also allows real - time intervention either from the researchers accessing the data or directly through the phone . currently , the system delivers feedback to the user via text messages that are generated from the server without researcher intervention . given the unlimited possibilities of developing mobile phone applications that could deliver a tailored intervention targeted at the individual level , this system has the advantages of combining research in engineering , exercise and behavior . wockets are being developed as an open - source technology , and thus , it is available to researchers to customize and use for measurement and feedback depending on their needs ( http://wockets.wikispaces.com/ ) . the actigraph has been used in a number of studies to measure sedentary behavior , but there are limitations with using the actigraph that need to be understood when looking at the results of these studies . many investigators have used a cutoff point of 100  counts per min as their definition of sedentary behavior based on observation . fortunately , recent calibration studies have shown that this was a reasonable and possibly an optimal sedentary cutoff point . second , the standard positioning of the actigraph ( attached near the hip ) or any other hip - located accelerometer registers up to 100  counts per min while sitting , but there are similarly low counts for activities , such as standing in line , riding a stationary cycle , taking a nap , standing at a stand - up desk , or most other stationary activities that can be performed standing or lying down . it also does not directly measure energy expenditure , the other part of the recently established definition . it estimates higher levels of energy expenditure with some accuracy ( r values are around 0.55 when including daily activities ) , but it is not considered an acceptable measure for activities with lower energy expenditures . despite these noted limitations , the use of the actigraph has been widespread in epidemiological studies , and it is one of the few available approaches for scientists to control for or stratify populations based on time spent in sedentary behavior . the assumption that this device can be validly used to estimate sedentary behavior is reasonably sound , because most of the human activities are locomotion - based , and it does distinguish sitting activities such as sedentary and ambulation as active ; however , there is still considerable room for improvement . the actigraph and activpal have significant differences in measured sedentary time , with the actigraph reporting a higher number of minutes in sedentary behavior . the placement of the activpal is both a strength and a weakness for the device . in terms of assessing the  sitting ' component of sedentary behavior measurement , the activpal is the most accurate accelerometer - based device , because its orientation changes markedly when going from a standing to a sitting posture . in terms of activity intensity measurement , the energy expenditure estimates with this device can produce a significant underestimation , and as the device is attached to the thigh with a sticker , getting people to wear the device can prove difficult for any sort of long - term measurement . therefore , the selection of the appropriate sedentary measurement device will depend on how sedentary behavior is defined  a lack of increased energy expenditure versus sitting . in the future , measurement of sedentary behavior and the interventions designed to reduce sedentary behavior will likely be mobile - phone - based systems . collaboration between northeastern university , massachusetts institute of technology and stanford university has produced the wocket system . wockets are two accelerometers worn on wrist and ankle that communicate via a wireless signal to a mobile phone . the positioning of the wockets on the wrist and ankle have three advantages : the ankle provides counts that are similar to the counts produced at the hip , focus groups have confirmed that wearing the devices at these locations will improve compliance to the protocol , and the wrist and ankle provide the best data for activity - recognition algorithms . activity data are recorded on the phone and delivered through the data network to a secure server , and access to the server can be made through any web browser . this is a powerful system , because there is no user burden to upload the data ; the only requirement is to wear the accelerometers and keep the phone in normal use . it also allows real - time intervention either from the researchers accessing the data or directly through the phone . currently , the system delivers feedback to the user via text messages that are generated from the server without researcher intervention . given the unlimited possibilities of developing mobile phone applications that could deliver a tailored intervention targeted at the individual level , this system has the advantages of combining research in engineering , exercise and behavior . wockets are being developed as an open - source technology , and thus , it is available to researchers to customize and use for measurement and feedback depending on their needs ( http://wockets.wikispaces.com/ ) . preventive medicine focuses on several essential behaviors to protect the population from the burden of disease and to limit costs to the healthcare system . for example , the current model of preventing smoking , maintaining a healthy weight , consuming a healthful diet , regular exercise and appropriate medical care are considered optimal for disease prevention . given that the average american spends about 7.7  h per day in sedentary behavior , primarily sitting , this opens up a large amount of time that is ripe for intervention when you consider inactivity as a separate risk factor . the specific goal(s ) of an intervention to reduce sedentary behavior are still not well - defined . for example , increasing the frequency of breaks in sedentary behavior appears beneficial for reducing waist circumference , body mass index , 2-h fasting glucose and triglycerides . however , because few , if any , studies have looked at the frequency , intensity and duration of  breaks ' , further research is needed to define what is both practical and optimal for these breaks . another question needs to be answered to design an appropriate intervention : what mechanism makes sedentary behavior so detrimental to health ? currently , there are two leading hypotheses that could explain the relationship between sitting and disease . first , it could simply be that when humans are sedentary , we expend far less energy than when we are active . as proof , simply increasing energy expenditure without changes in weight or fitness will still improve metabolic risk . as an alternative explanation , inactivity physiologists ' propose that there is a different and detrimental metabolic mechanism at work when we sit , and it gets worse the longer we sit . if the reason sedentary behavior is related to disease is because of one or the other of these explanations , an alternative hypothesis , or because of both of the above , then the intervention design would have the goal of either increasing energy expenditure or avoiding prolonged sitting and these are not actually the same thing . for example , the intervention to reduce sitting time might include getting out of your chair every 15  min , or standing instead of sitting . the other intervention might be more focused on increasing movement such as walking workstations , walking meetings and foot pedals under the desk to significantly increase energy expenditure . an intervention on sedentary behavior may be easier to adopt than the typical intervention promoting moderate- and/or vigorous - intensity physical activity . in a study that compared adding exercise with reducing sedentary behavior in children , the sedentary group fared better for weight loss than the exercise group . if we test the hypothesis that sitting is unhealthy because of the low energy expenditure , we can compare an intervention on sedentary behavior with an exercise intervention designed to expend the same amount of additional calories . if you consider an 80-kg person who wants to burn an extra 100  kcal a day , the calculation is presented in figure 1 . as you can see , a moderate exercise intervention of walking for 30  min is equivalent to a standing intervention of 2  h. an argument could be made for the difficulty in changing exercise behavior versus reducing sedentary behavior in this context . methodologies for objective measurement of sedentary behavior are still in the preliminary phase of development , including the calibration of accelerometers for the sensitive and specific measurement of sedentary time . however , as an alternative to assessing sedentary time through a questionnaire , objective measurement is a vast improvement . a benefit of using accelerometers for sedentary measurement is that they are used for a number of other measures , including physical activity and sleep . currently , the actigraph software is calibrated for physical activity ( at the waist ) and sleep ( at the wrist ) , but not specifically sedentary time ( cutoff points can be input in the software ) . the activpal is calibrated for physical activity and sedentary time ( both on the thigh ) , but not sleep . the wockets have the potential for calibration in physical activity , sleep and sedentary behavior ( because of the wrist and ankle locations and the potential for 24  h measurement ) . there is room for great improvement in the calibration of accelerometers , including improving activity recognition and energy expenditure estimates from motion data . the wockets system has the potential to improve this calibration because it is a multiple - sensor system ( for activity recognition ) and an open - source accelerometer allowing access to all features of the raw signal ( for energy expenditure estimates ) . given the relatively new ability to measure sedentary behavior , physical activity and sleep with one objective device , this is an exciting time to study the relationship between the entire activity spectrum and a number of health outcomes . the challenge for obesity researchers is now to consider the entire daily activity pattern when designing studies and planning interventions . sedentary behavior alone will probably not prove to be the solution for preventing obesity , but a combination of daily exercise , decreasing sedentary behavior and adequate sleep will contribute to our understanding of treating and preventing obesity . new technology will also provide the potential to intervene in real time on all aspects of daily activity . the ability to collect data and provide feedback to the user through mobile devices , as with the wockets , offers the opportunity to intervene at the time when the choice of activity is being made . for example , imagine a system that could prompt the user to take a break after so many minutes of sitting , inform the user before the end of the day when physical activity goals have not been met , and summarize unhealthy sleep patterns and strategies to improve them in the same week when the user really needs the sleep . in addition , all of this 24-h behavioral guidance comes from wearing a few small sensors with minimal additional input from the user .
sedentary behavior is not a new topic , but trying to examine the direct links between sedentary behavior and health outcomes , independent of time spent in moderate- and vigorous - intensity physical activity , is a relatively new addition to the relationships between physical activity and health . defining sedentary behavior as a risk factor and target for intervention opens up novel avenues for disease prevention and health promotion . 
 the relationship between sedentary behavior and obesity is complex and not well understood , but the increased risk of disease due to sedentary behavior may be even greater in obese patients . 
 objective measurement of sedentary behavior is an important link in being able to understand the real effects of being sedentary , and a few measurement devices are described . 
 interventions targeting sedentary behavior should reduce total sedentary time , break long bouts of sitting with intermittent activity and encourage light - intensity activity throughout the day . 
 new technologies can both measure and deliver an intervention aimed at reducing sitting time , the most common category of sedentary behavior . 
 an optimal activity profile will include minimal amounts of sedentary behavior , in addition to regular physical activity and healthy sleep patterns .