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Fitness Moderates Glycemic Responses to Sitting and Light Activity Breaks


Author Information
Medicine & Science in Sports & Exercise: November 2017 - Volume 49 - Issue 11 - p 2216-2222
doi: 10.1249/MSS.0000000000001338


Adults in developed western countries typically spend 50% to 70% of their waking hours sat down (29), making sedentary behavior the new reference of modern living. Greater time spent in sedentary behaviors (defined as sitting or reclining with low energy expenditure) has been associated with an increased likelihood of metabolic syndrome (10), diabetes, cardiovascular disease (CVD), and all-cause mortality (4,26). The evidence of which appears to be the strongest and most consistent for the risk of type 2 diabetes mellitus (T2DM) (4).

However, recent epidemiological evidence has suggested that physical activity levels and cardiorespiratory fitness (CRF) may moderate these associations, such that the association between sedentary time and markers or outcomes of health may be weaker in those with higher fitness levels (7,22,24), or those undertaking greater physical activity (11). This suggests that sedentary behavior may be a less important determinant of health in those with adequate CRF or those that are physically active. Although experimental evidence largely confirms that breaking prolonged bouts of sitting with light-intensity walking can significantly reduce postprandial blood glucose and insulin in healthy nonobese individuals (2,23), in those who are overweight and obese (9,25), and in those with dysglycemia (15), no previous experimental trials have investigated whether these responses are modified by CRF or habitual physical activity levels.

CRF in particular is an important candidate for further investigation, because it is one of the strongest predictors of morbidity and mortality (19). Cardiorespiratory fitness has been shown to moderate the deleterious impacts of other exposures, such as body mass index (BMI), whereby obese individuals with moderate to high CRF levels have a lower risk of morbidity and mortality outcomes compared with normal weighted individuals with low CRF levels (12). It is therefore plausible that high levels of CRF may also protect against the deleterious impacts of prolonged sedentary behavior. Therefore, we hypothesized that CRF would modify the postprandial glucose response to breaking prolonged sitting with light walking breaks with lower CRF levels being associated with greater reductions to postprandial plasma glucose.


Study design

All participants attended the Leicester Diabetes Centre on three separate occasions between September 2014 and September 2015. The first visit involved consent, familiarization and a fitness assessment which was followed by two experimental condition visits that were at least 7 d apart. This was a randomized crossover trial, whereby each participant took part in two experimental treatment conditions in a random order, thereby acting as their own controls. Order randomization was conducted by a statistician using an online tool. Due to the nature of the trial, participants were not blinded to their randomized order; however, all outcomes including blood assays were analyzed blinded to the experimental condition that they derived from. Before commencing, this study received ethical approval from the University of Leicester-Health Sciences Department and from the local NHS Research and Development Committee.

This trial was also registered with (NCT0493309).


Thirty-six nonobese adults (BMI, <30 kg·m−2) age between 25 and 55 yr who worked in a predominantly seated environment were recruited from the general public via study-specific information distributed in the community, around the University of Leicester campus and University Hospitals of Leicester NHS Trust. Two individuals were withdrawn following enrolment in the study due to a change in personal circumstances (n = 2). This left 34 participants who went on to complete the remaining experimental conditions. This is detailed in Figure 1.

Trial CONSORT Profile.

Exclusion from taking part in this study came under the following circumstances: an inability to communicate in spoken English, a BMI ≥30 kg·m−2, pregnancy, steroid usage, regular smoking habits, diagnosed T2DM, CVD, or psychotic illness. As our study was predicated on having a broad range of fitness levels, and considering that most of the variance in CRF is explained by habitual physical activity levels (6), we stratified recruitment by self-reported leisure time physical activity. Consequently, we enrolled 12 inactive (0 min of moderate to vigorous physical activity (MVPA) per week), 12 moderately active (≥75 min to <150 min of MVPA per week), and 12 highly active (≥150 min of MVPA per week) individuals (see Table S-1, Supplemental Digital Content 1, Scope of CRF levels captured,

Consent, familiarization, and fitness assessment visit

On arrival, a researcher described in detail all study procedures and written informed consent was obtained. Participants were then shown the designated experimental area for the study.

A venous blood sample was taken to assess HbA1c and confirm absence of T2DM (<6.5% [<47.5 mmol·mol−1]) (28). Body weight (Tanita TBE 611; Tanita, West Drayton, UK), waist circumference (midpoint between lower costal margin and iliac crest), and height were measured to the nearest 0.1 kg, 0.5 cm, and 0.5 cm, respectively.

To assess CRF, participants undertook a maximal incremental exercise test on a motor driven treadmill (Technogym Excite® 700; TechnoGym USA, Fairfield, NJ). Following a 3-min warm-up at 4 km·h−1 (0% incline), participants would walk or jog at a constant speed that they felt comfortable with (6, 8, 10, or 12 km·h−1) while elevations in treadmill gradient occurred at a rate of 0.5% every 30 s. All participants received encouragement to continue this exercise for as long as possible. The test was terminated upon volitional exhaustion. Throughout the test, gas was sampled continuously and analyzed using a Metalyser 3B gas analyser (Cortex 3B; Cortex Biophysik, Leipzig, Germany). Peak oxygen consumption (V˙O2 peak) was calculated using the highest 10-s average throughout the testing period. Before each test, the gas analyser was calibrated according to the manufacturer’s recommendations. As a safety precaution, a 12-lead electrocardiogram was performed by a cardiac nurse for each participant at rest and during the exercise test.

Finally, participants were issued with two activity monitors; an ActiGraph GT3X+ accelerometer (Pensacola, FL) worn on the right anterior axillary line, and an activPAL3 physical activity monitor (PAL Technologies, Glasgow, UK) worn on the midline anterior portion of the right thigh. Participants were required to wear these for seven consecutive days, allowing insight into their habitual sitting and physical activity levels.

Experimental procedure

Participants were asked to avoid alcohol and caffeine for the 48 h preceding experimental treatment conditions. Because the influence of an acute bout of physical activity on insulin sensitivity can persist for 48 h (17), avoidance of moderate and vigorous physical activity for this timeframe was also instructed. Continuation in this study was subject to participants being able to confirm their compliance with these restrictions. After an ethical amendment to the protocol during this study, a subset of participants was asked to wear an accelerometer in the 2 d leading up to each experimental condition to confirm adherence to the exercise restriction (see Table S-2, Supplemental Digital Content 2, Activity data leading up to experimental conditions,

Participants fasted from 10:00 PM, the evening before each visit, and were asked to keep a record of all food eaten during the day leading up to their first experimental condition. This could then be replicated before their second experimental condition in an attempt to eliminate the potentially confounding influence of preexperimental food intake.

Participants underwent two separate 7.5-h experimental treatment conditions:

  1. Prolonged sitting—participants sat in a designated room (occupied with a desk, books, and laptop with internet services) while minimizing excessive movement. Lavatory breaks were permitted using a wheelchair to and from the lavatory to further reduce unnecessary movements that could otherwise confound the study.
  2. Light walking breaks—participants emulated the above, but interrupted sitting time with 5-min bouts of walking at a light intensity of 3 km·h−1 on the treadmill (Technogym Excite® 700) every 30 min. These bouts were performed 12 times, totalling 1 h of activity and 6.5 h of sitting throughout the course of the experimental day.

On arrival, participants had a cannula fitted into an accessible vein from which 10-mL samples were obtained throughout the day. Immediately following the two fasting samples (depicted at timepoints −1 and 0 in Fig. 2), participants were given a standardized meal consisting of 8 kcal·kg−1 of body weight, with a macronutrient composition reflective of coingestion in modern western diets (14% protein, 51% carbohydrate, and 35% fat). Once consumed (within ≤15 min), blood sampling commenced at 30, 60, 120, and 180 min thereafter, enabling us to capture the postprandial period. An identical meal was then issued (time point 3 in Fig. 2) and sampling continued in a similar fashion at 30, 60, 120, 180, and 210 min after this. Participants were supervised by study staff to ensure compliance with the protocol and were asked to wear an activPAL monitor to objectively confirm sitting and walking times during each experimental condition (see Table S-3, Supplemental Digital Content 3, Sitting and walking data during experimental conditions, Ad libitum water consumption was also noted and made consistent between conditions.

Effect of treatment condition on average blood glucose (A) and Insulin (B).

Biochemical analysis

Glucose was analysed on the day of collection by the University Hospitals of Leicester Pathology Department, using standard enzymatic techniques with commercially available kits (Beckman, High Wycombe, UK).

Centrifuged (4°C) plasma samples were stored in −80°C freezers and insulin was analysed from these collectively at the end of the trial using an electrochemiluminescence assay (Meso Scale Discovery, Maryland, USA). Each sample was ran in duplicate to ensure reliability of readings. Duplicate sample values with ≥20% variability were reanalyzed. Ambient conditions of the laboratory were kept consistent to reduce variability between assays.

Free-living activity monitor processing

ActivPAL data were downloaded using the manufacturers software (activPAL Professional Research Edition; PAL technologies, Glasgow, UK) and “Event” csv files were processed using a validated automated algorithm in STATA (StataCorp LP, College Station, TX) described in detail elsewhere (28).

Actigraph data (100 Hz) were downloaded using the manufacturer’s software (ActiLife version 6.10.4, Lite Edition), reintegrated into 60-s epoch files and processed using a bespoke tool (KineSoft, version 3.3.76; KineSoft, New Brunswick, Canada). Freedson cut points were used to categorize activity intensities (13). Nonwear time was defined as a minimum of 60 min of continuous zero counts, and when assessing habitual activity levels, days with at least 10 h of wear time were required to be considered valid.

The minimum amount of valid days utilised for both ActivPAL and ActiGraph data was 3 d.

Statistical analysis

Descriptive characteristics of those who completed this study are summarized overall (n = 34) and stratified by sex (Table 1) for descriptive purposes.

Metabolic, demographic, and anthropometric characteristics taken at baseline.

Missing glucose and insulin data during the experimental conditions accounted for roughly 2% of overall required samples (34 of 1496) (see Table S-4, Supplemental Digital Content 4, Summary of missing glucose and insulin data, These 34 missing data points were imputed using a regression model previously developed for an acute trial investigating breaking sedentary behavior (15). This approach uses key predictors (BMI, ethnicity, age, fasting values, and treatment condition) to derive a regression equation for the glucose and insulin values at each individual time point, this regression equation is then used to impute missing values.

The incremental area under the curve (iAUC) of glucose and insulin was calculated for each experimental condition. Total AUC was calculated by applying the trapezium rule and further subtraction of fasting levels gave a single value of iAUC for each participant. Using iAUC as opposed to total AUC is common practice in acute interventions where fasting levels should be unaffected by the intervention (20). Glucose iAUC was defined a priori as the primary outcome.

The effect of light walking breaks compared with continuous sitting on outcomes (glucose and insulin iAUC) and whether CRF modified this response was assessed using a repeated-measures ANOVA. Treatment was entered as a within-person variable, with CRF (as a continuous variable) entered as a between-subjects covariate. Sex was also entered as a between-subjects factor. “Treatment by CRF” and “treatment by sex” interaction terms were investigated to assess the modifying effect of fitness and sex respectively. Sex was included in the model given that it is a strong determinant of fitness and an important potential confounder. Treatment by CRF interactions were further explored by calculating the linear regression coefficients within each treatment condition. To highlight the direction of significant interactions, derived average glucose iAUC values for men and women at the 25th, 50th, and 75th centiles of the CRF distribution are shown in Figure 3.

Predicted glucose values (with 95% CI) at sex-specific centiles of CRF 25th centile of CRF corresponds to 42.5 mL·kg−1·min−1 for men, and 32.1 mL·kg−1·min−1 for women. 50th centile of CRF corresponds to 50.3 mL·kg−1·min−1 for men, and 34.0 mL·kg−1·min−1 for women. 75th centile of CRF corresponds to 60.5 mL·kg−1·min−1 for men, and 39.9 mL·kg−1·min−1 for women. Predicted glucose iAUC values were derived from the below equations gained from linear regression models entering glucose iAUC within each condition as the dependant variable with CRF and sex entered as independent variables. 95% CI values show the variability around the derived estimates; negative values represent postprandial glucose concentrations that are suppressed below fasting levels. The derived glucose iAUC values and 95% CI are within the range observed in this study (minimum observed glucose iAUC = −9.73 mmol·L−1·h−1, maximum observed glucose iAUC = 16.50 mmol·L−1·h−1) Glucose iAUC during prolonged sitting condition = 11.81 − (0.21; 95% CI, 0.05–0.38) × CRF + 3.00 if men. Glucose iAUC during walking breaks condition = 5.12 + (−0.07; 95% confidence interval, −0.21 to 0.08) × CRF + 0.72 if men.

Two-tailed P ≤ 0.05 was considered significant. Analyses were performed with SPSS (version 24; IBM, Armonk, NY). Results are presented as mean ± SE or regression coefficient (95% confidence interval [CI]) unless stated otherwise.


The key characteristics of those who successfully completed all three study visits are displayed in Table 1 (n = 34). Stratification of these characteristics for both men and women is also presented here.

Overall treatment condition effect

The average postprandial concentrations of glucose (A) and insulin (B) witnessed throughout the 7.5-h testing periods for both experimental conditions (“prolonged sitting” and “light walking breaks”) are depicted in Figure 2. There was a significant main effect of treatment for both glucose (F (1, 31) = 6.67, P = 0.015) and insulin (F (1, 31) = 7.00, P = 0.013) iAUC after adjustment for fitness and sex. Interrupting prolonged sitting time with light walking breaks reduced blood glucose iAUC by 35% (from 3.89 ± 0.7 mmol·L−1·h−1 to 2.51 ± 0.7 mmol·L−1·h−1) and insulin iAUC by 35% (from 241 ± 46 mU·L−1·h−1 to 156 ± 24 mU·L−1·h−1).

Impact of CRF and sex

There was a significant treatment by CRF interaction for glucose iAUC (F (1, 31) = 4.89, P = 0.035). The treatment by CRF interaction for insulin iAUC failed to reach significance (F (1, 31) = 3.76, P = 0.062). There was no treatment by sex interaction for glucose (F (1, 31) = 1.77, P = 0.194) or insulin (F (1, 31) = 1.54, P = 0.223) iAUC.

Stratified analysis revealed that each unit increment in CRF (per mL·kg−1·min−1) was associated with a lower glucose iAUC (−0.21 mmol·L−1·h−1; 95% CI, −0.38 to −0.05) (P = 0.013) in the prolonged sitting condition, whereas there was no association between CRF and glucose iAUC during the light walking breaks condition (−0.07 mmol·L−1·h−1; 95% CI, −0.21 to 0.07) (P = 0.335). In contrast, each unit increment in CRF was associated with a lower insulin iAUC (−10.93 mU·L−1·h−1; 95% CI, −19.48 to −2.37) (P = 0.014) in the prolonged sitting condition and a lower insulin iAUC (−6.35 mU·L−1·h−1; 95% CI, −10.90 to −1.83) (P = 0.007) in the light walking breaks condition.

Figure 3 uses the derived regression coefficients to show how the predicted average difference between conditions for glucose iAUC changes as CRF increases for men and women. This demonstrates that average blood glucose iAUC response for a man at the 25th centile of CRF within our cohort went from 5.80 to 2.98 mmol·L−1·h−1 (from prolonged sitting to light walking breaks, respectively), whereas average responses for a man at the 75th centile went from 1.99 to 1.78 mmol·L−1·h−1. Similar trends were observed for women.


This study found that interrupting prolonged sitting with regular light walking breaks reduced postprandial glucose and insulin levels in a healthy cohort. However, CRF modified the response for glucose such that individuals with lower levels of fitness received incrementally greater reductions in postprandial glucose. For example, the average response for a man at the 25th centile of CRF within our population (V˙O2 peak of 42.5 mL·kg−1·min−1) demonstrated relatively high postprandial glucose levels during prolonged sitting (5.80 mmol·L−1·h−1) but was able to almost half this level through using regular light walking breaks. In contrast, the average response for a man at the 75th centile of fitness (V˙O2 peak of 60.5 mL·kg−1·min−1) demonstrated relatively low levels of postprandial glucose during prolonged sitting (1.99 mmol·L−1·h−1) but only reduced this by a further 11% through using regular light walking breaks. The same pattern was demonstrated for women. These results were supported by further analysis which demonstrated that CRF was inversely associated with postprandial glucose during prolonged sitting, whereby every unit increment in V˙O2 peak (per mL·kg−1·min−1) was associated with an average reduction of 0.21 mmol·L−1·h−1 in glucose iAUC values. Taken together, our results suggest that having high CRF or using regular light walking breaks in those with low CRF can both reduce postprandial levels of glucose during periods of prolonged sitting activity. Elevated postprandial glucose levels are implicated with the development of T2DM and CVD (5) and therefore strategies to promote healthy glycemic responses when sedentary are of high importance.

Our observation that those with higher CRF demonstrate less metabolic benefit from light activity breaks is consistent with previous experimental research that has tended to show relatively lower metabolic benefits of light activity breaks in healthy cohorts (1,21) compared with both those with high risk of chronic disease (9,15). Our findings also correspond to cross sectional research that has shown the influence of sedentary time on a cluster of cardiometabolic issues to be significantly less pertinent in those with higher fitness levels (7,22,24). The concept that fitter individuals may gain less pronounced health benefits from lower levels of sitting time is supported by cross-sectional research that have stratified data by habitual MVPA level, finding that individuals with higher MVPA levels display significantly weaker associations between sedentary time with HbA1c (3), inflammation markers (16), and all-cause mortality (11).

In contrast, a recent meta-analysis found that the association between sedentary time and health outcomes persisted in sufficiently active individuals (4). However, this pooled analysis was predominantly derived from self-reported measures of sedentary time and MVPA which are prone to bias and consequently may have been insensitive to detecting true interactions. It should also be noted that although observational research linking sedentary behavior to health is plentiful, the vast majority have investigated the confounding rather than the modifying influence of physical activity (4,26) or fitness (24).

The growing observational and experimental data has supported new guidance and recommendation calling for reductions in sitting time (18). However, if the findings of the current study continue to be supported by further research, there may be reasonable grounds to embark on a more personalized/tailored approach to T2DM prevention. Precision medicine is important given that a one size fits all recommendation is rarely effective. For example, interventions to reduce sitting time may be optimized by targeting those with poor CRF, whereas those with high CRF may be better served by interventions aimed at maintaining CRF and physical activity levels across the lifespan. However, it should be noted that median levels of CRF within our population for men and women were 50.3 and 34.0 mL·kg−1·min−1, respectively, and that the average reductions in postprandial glucose at this level of CRF was 41%. As the majority of the general population within the age range included in this study are estimated to fall below the median levels of fitness within our population (8), the importance of interrupting sitting time with light activity breaks is likely to remain generalizable to the majority of the population.

This research also suggests that increasing CRF levels may be a viable way to protect against the potential harms of prolonged sitting. Although there are genetic contributions to fitness, the largest contributor to an individual’s fitness is their time spent in MVPA (6). Participation in regular MVPA outside of seated hours may therefore offer some protection, particularly in seated occupations such as driving.

Our observation that fitter individuals experienced less pronounced postprandial glycemic excursions during prolonged sitting may result from favorable physiological adaptations stemming from regular engagement in MVPA (one of the main determinants of fitness), such as increased skeletal muscle GLUT 4 protein expression (14). This would also leave less scope for further improvement, potentially explaining why the benefits of interrupting sitting time with light activity breaks appear to be blunted in those with higher fitness. However, given that CRF is determined by a mixture of both MVPA engagement and genetics (6), we cannot distinguish between behavioral and genetic mechanisms driving the results of the current study.

This study has some important limitations. Although this study provides an initial proof-of-concept from which future research can tailor to alternative study cohorts, findings should not be generalized outside the population investigated. In particular, given that the population utilised in this study were healthy, the extent to which CRF modifies responses in high risk or clinical population remains to be investigated. Our second limitation is that despite instructions to standardize food intake, and refrain from caffeine and alcohol consumption leading up to treatment conditions, we did not objectively test participant compliance and relied on self-reported adherence. In addition, fitness assessments were only conducted at one timepoint, thus direct causality cannot be inferred. Future interventions that actively set out to manipulate fitness levels and assess prospective change in experimental data are required to elucidate direct causality. Another concern was that those with higher fitness in this study were predominantly men and conversely, those with lower fitness were predominantly women. However, our results were adjusted for sex, and it was not found to modify the treatment effect for glucose which was in contrast to CRF. Therefore, the correlation between sex and CRF is unlikely to be confounding the results of this study.

In conclusion, participants with lower fitness had worse postprandial glucose and insulin responses during prolonged sitting, and were able to gain greater metabolic benefit through breaking their sitting time with light activities compared with individuals with higher fitness. Future interventions aimed at alleviating the deleterious metabolic impacts of sedentary behavior may therefore be optimized by tailoring to CRF levels of the general population.

This project was supported by the University of Leicester Clinical Trials Unit and the NIHR Leicester-Loughborough Diet, Lifestyle and Physical Activity Biomedical Research Unit which is a partnership between University Hospitals of Leicester NHS Trust, Loughborough University and the University of Leicester.

The authors would like to thank Steve Hartshorn, Lois Daniels, Dawn Newell, Tim Skelton, Balu Webb, Helen Waller, and Ros Downing for their assistance throughout the study. The authors thank the Reviewers’ of this manuscript for their help in the presentation and interpretation of the results and for strengthening the statistical analysis plan. Finally, the authors would like to thank the participants of this study, as without their time, patience, and goodwill, the authors could not have conducted this investigation.

Source of funding: This trial was funded by the National Institute for Health Research (NIHR) Leicester-Loughborough Diet, Lifestyle and Physical Activity Biomedical Research Unit. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Conflicts of interests: All authors declare support from the National Institute for Health Research (NIHR) Collaboration in Applied Health Research and Care for Leicestershire, Northamptonshire and Rutland alongside the Health Research Collaboration for Leadership in Applied Health Research and Care – East Midlands (NIHR CLAHRC – EM). M. M., T. Y., M. J. D., C. L. E., B. H. D., J. H., and J. K. declare support from the NIHR Leicester Biomedical Research Centre. K. K., M. J. D., and T. Y. were members (K. K. chair) of the NICE PH 38 (Preventing T2DM: risk identification and interventions for individuals at high risk) Program Development Group. M. J. D., K. K., and T. Y. are academic leads for a diabetes prevention program selected to be part of Healthier You: The NHS Diabetes Prevention Program in collaboration with Ingeus UK Limited. All authors declare no support from any other organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work; no other relationships or activities that could appear to have influenced the submitted work.

Aside from the information disclosed above, authors declare no conflict of interest. The results of the present study do not constitute endorsement by the American College of Sports Medicine. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.


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Supplemental Digital Content

© 2017 American College of Sports Medicine