Publications for James Sanders
Journal ArticlesThomas, JJC, Daley, AJ, Esliger, DW, Kettle, VE, Coombe, A, Stamatakis, E, Sanders, JP (2023) Accelerometer-Measured Physical Activity Data Sets (Global Physical Activity Data Set Catalogue) That Include Markers of Cardiometabolic Health: Systematic Scoping Review, Journal of Medical Internet Research, 25, pp.e45599-e45599, DOI: 10.2196/45599. Sanders, JP, Gokal, K, Thomas, JJC, Rawstorn, JC, Sherar, LB, Maddison, R, Greaves, CJ, Esliger, D, Daley, AJ (2023) Development of a Mobile Health Snacktivity App to Promote Physical Activity in Inactive Adults (SnackApp): Intervention Mapping and User Testing Study, JMIR Formative Research, 7, pp.e41114-e41114, DOI: 10.2196/41114. Daley, AJ, Griffin, RA, Moakes, CA, Sanders, JP, Skrybant, M, Ives, N, Maylor, B, Greenfield, SM, Gokal, K, Parretti, HM, Biddle, SJH, Greaves, C, Maddison, R, Mutrie, N, Esliger, DW, Sherar, L, Edwardson, CL, Yates, T, Frew, E, Tearne, S, Jolly, K (2023) Snacktivity™ to promote physical activity and reduce future risk of disease in the population: protocol for a feasibility randomised controlled trial and nested qualitative study, Pilot and Feasibility Studies, 9(1), 45, DOI: 10.1186/s40814-023-01272-8. Krouwel, M, Greenfield, SM, Chalkley, A, Sanders, JP, Parretti, HM, Gokal, K, Jolly, K, Skrybant, M, Biddle, SJH, Greaves, C, Maddison, R, Mutrie, N, Ives, N, Esliger, DW, Sherar, L, Edwardson, CL, Yates, T, Frew, E, Tearne, S, Daley, AJ (2023) Promoting participation in physical activity through Snacktivity: A qualitative mixed methods study, PloS one, 18(9), e0291040, DOI: 10.1371/journal.pone.0291040. Biddle, G, Sanders, J, Gokal, K, Madigan, C, Thomas, J, Pyle, A, Roalfe, A, Daley, A (2022) A Christmas themed physical activity intervention to increase participation in physical activity during Advent: pilot randomised controlled trial, BMJ, 379, e072807, ISSN: 1759-2151. DOI: 10.1136/bmj-2022-072807. Sharp, K, Sherar, L, Kettle, V, Sanders, J, Daley, A (2022) Effectiveness of interventions to increase device-measured physical activity in pregnant women: systematic review and meta-analysis of randomised controlled trials, International Journal of Behavioral Nutrition and Physical Activity, 19, 142, DOI: 10.1186/s12966-022-01379-w. Gokal, K, Amos-Hirst, R, Moakes, CA, Sanders, J, Esliger, D, Sherar, L, Ives, N, Biddle, SJH, Edwardson, C, Yates, T, Frew, E, Greaves, C, Greenfield, SM, Jolly, K, Skrybant, M, Maddison, R, Mutrie, N, Parretti, HM, Daley, A (2022) Views of the public about Snacktivity™: a small changes approach to promoting physical activity and reducing sedentary behaviour, BMC Public Health, 22(1), 618, DOI: 10.1186/s12889-022-13050-x. Tyldesley-Marshall, N, Greenfield, SM, Parretti, HM, Gokal, K, Greaves, C, Jolly, K, Maddison, R, Daley, A, Biddle, S, Edwardson, C, Esliger, D, Frew, E, Ives, N, Mutrie, N, Sanders, J, Sherar, L, Skrybrant, M, Yates, T (2021) Snacktivity™ to promote physical activity: a qualitative study, International Journal of Behavioral Medicine, 29(5), pp.553-564, ISSN: 1070-5503. DOI: 10.1007/s12529-021-10040-y. Sanders, J, Biddle, SJH, Gokal, K, Sherar, L, Skrybant, M, Parretti, HM, Ives, N, Yates, T, Mutrie, N, Daley, A (2021) ‘Snacktivity™’ to increase physical activity: Time to try something different?, Preventive Medicine, 153, 106851, ISSN: 0091-7435. DOI: 10.1016/j.ypmed.2021.106851. Kingsnorth, A, Whelan, ME, Sanders, J, Sherar, L, Esliger, D (2018) Using digital health technologies to understand the association between movement behaviors and interstitial glucose: Exploratory analysis, Journal of Medical Internet Research, 20(5), DOI: 10.2196/mhealth.9471. Loveday, A, Sherar, L, Sanders, J, Sanderson, P, Esliger, D (2016) Novel technology to help understand the context of physical activity and sedentary behaviour, Physiological measurement, 37(10), pp.1834-1851, ISSN: 0967-3334. DOI: 10.1088/0967-3334/37/10/1834. Sanders, J, Loveday, A, Pearson, N, Edwardson, CL, Yates, TE, Biddle, SJH, Esliger, D (2016) Devices for self-monitoring sedentary time or physical activity: a scoping review, Journal of medical Internet research, 18(5), p.90, ISSN: 1439-4456. DOI: 10.2196/jmir.5373. Edwardson, CL, Rowlands, AV, Bunnewell, S, Sanders, JP, Esliger, D, Gorely, T, O'Connell, S, Davies, MJ, Khunti, K, Yates, TE (2016) Accuracy of posture allocation algorithms for thigh- and waist-worn accelerometers, Medicine and Science in Sports and Exercise, ISSN: 0195-9131. DOI: 10.1249/MSS.0000000000000865. Bakrania, K, Yates, TE, Rowlands, AV, Esliger, D, Bunnewell, S, Sanders, J, Davies, MJ, Khunti, K, Edwardson, CL (2016) Intensity thresholds on raw acceleration data: Euclidean norm minus one (ENMO) and mean amplitude deviation (MAD) approaches, PLoS ONE, 11(10), DOI: 10.1371/journal.pone.0164045. Loveday, A, Sherar, L, Sanders, J, Sanderson, P, Esliger, D (2015) Technologies that assess the location of physical activity and sedentary behavior: a systematic review, JOURNAL OF MEDICAL INTERNET RESEARCH, 17(8), ISSN: 1438-8871. DOI: 10.2196/jmir.4761.
OtherKingsnorth, AP, Whelan, ME, Sanders, JP, Sherar, LB, Esliger, DW (2017) Using Digital Health Technologies to Understand the Association Between Movement Behaviors and Interstitial Glucose: Exploratory Analysis (Preprint),
Acute reductions in postprandial glucose excursions because of movement behaviors have been demonstrated in experimental studies but less so in free-living settings.
The objective of this study was to explore the nature of the acute stimulus-response model between accelerometer-assessed physical activity, sedentary time, and glucose variability over 13 days in nondiabetic adults.
This study measured physical activity, sedentary time, and interstitial glucose continuously over 13 days in 29 participants (mean age in years: 44.9 [SD 9.1]; female: 59%, 17/29; white: 90%, 26/29; mean body mass index: 25.3 [SD 4.1]) as part of the Sensing Interstitial Glucose to Nudge Active Lifestyles (SIGNAL) research program. Daily minutes spent sedentary, in light activity, and moderate to vigorous physical activity were associated with daily mean glucose, SD of glucose, and mean amplitude of glycemic excursions (MAGE) using generalized estimating equations.
After adjustment for covariates, sedentary time in minutes was positively associated with a higher daily mean glucose (mmol/L; beta=0.0007; 95% CI 0.00030-0.00103; P<.001), SD of glucose (mmol/L; beta=0.0006; 95% CI 0.00037-0.00081; P<.001), and MAGE (mmol/L; beta=0.002; 95% CI 0.00131-0.00273; P<.001) for those of a lower fitness. Additionally, light activity was inversely associated with mean glucose (mmol/L; beta=−0.0004; 95% CI −0.00078 to −0.00006; P=.02), SD of glucose (mmol/L; beta=−0.0006; 95% CI −0.00085 to −0.00039; P<.001), and MAGE (mmol/L; beta=−0.002; 95% CI −0.00285 to −0.00146; P<.001) for those of a lower fitness. Moderate to vigorous physical activity was only inversely associated with mean glucose (mmol/L; beta=−0.002; 95% CI −0.00250 to −0.00058; P=.002).
Evidence of an acute stimulus-response model was observed between sedentary time, physical activity, and glucose variability in low fitness individuals, with sedentary time and light activity conferring the most consistent changes in glucose variability. Further work is required to investigate the coupling of movement behaviors and glucose responses in larger samples and whether providing these rich data sources as feedback could induce lifestyle behavior change.