Investigating Context-specific Sedentary Behaviours and Cardiometabolic Health in College-based Young Adults (CONTEXT-SB): a Protocol for a Longitudinal Observational Study

Overview

Journal BMJ Open

Specialty General Medicine

Date 2024 Dec 28

PMID 39732498

Authors

Jake Christopher Diana

Aiden James Chauntry

Emma Cowley

Craig Paterson

Jeb F Struder

Patricia Pagan-Lassalle

Michelle L Meyer

Feng-Chang Lin

Justin B Moore

Erik D Hanson

Lee Stoner

Affiliations

Soon will be listed here.

Abstract

Background: Sedentary behaviour (SB) is detrimental to cardiometabolic disease (CMD) risk, which can begin in young adulthood. To devise effective SB-CMD interventions in young adults, it is important to understand which context-specific SB (CS-SB) are most detrimental for CMD risk, the lifestyle behaviours that cluster with CS-SBs and the socioecological predictors of CS-SB.

Methods And Analysis: This longitudinal observational study will recruit 500 college-aged (18-24 years) individuals. Two laboratory visits will occur, spaced 12 months apart, where a novel composite CMD risk score (eg, arterial stiffness, metabolic and inflammatory biomarkers, heart rate variability and body fat distribution) will be calculated, and questionnaires to measure lifestyle behaviours and levels of the socioecological model will be administered. After each laboratory visit, total SB (activPAL) and CS-SB (television, transportation, academic/occupational, leisure computer, 'other'; ecological momentary assessment) will be measured across 7 days.

Ethics And Dissemination: This study has received full ethical approval, and participants provide written informed consent. Our hypothesis is that certain CS-SB will show stronger associations with CMD risk, compared with total sedentary behaviour (T-SB), even after accounting for coexisting lifestyle behaviours. We also expect a range of intra-individual, inter-individual and physical environmental socioecological factors will predict CS-SB. Findings addressing both the primary and any secondary research aims will be submitted for publication in a high-impact peer-reviewed journal.

Citing Articles

Feasibility of Measuring Context Specific Sedentary Behavior and Pulse Wave Velocity in Endometrial Cancer Survivors.

Bates-Fraser L, Diana J, Chauntry A, Bae-Jump V, Meyer M, Moore J Integr Cancer Ther. 2025; 24:15347354251324912.

PMID: 40071631 PMC: 11898241. DOI: 10.1177/15347354251324912.

References

Prince S, Reed J, McFetridge C, Tremblay M, Reid R . Correlates of sedentary behaviour in adults: a systematic review. Obes Rev. 2017; 18(8):915-935. DOI: 10.1111/obr.12529. View

Geiss L, Wang J, Cheng Y, Thompson T, Barker L, Li Y . Prevalence and incidence trends for diagnosed diabetes among adults aged 20 to 79 years, United States, 1980-2012. JAMA. 2014; 312(12):1218-26. DOI: 10.1001/jama.2014.11494. View

Danielsson K, Sakarya A, Jansson-Frojmark M . The reduced Morningness-Eveningness Questionnaire: Psychometric properties and related factors in a young Swedish population. Chronobiol Int. 2019; 36(4):530-540. DOI: 10.1080/07420528.2018.1564322. View

Lim S, Vos T, Flaxman A, Danaei G, Shibuya K, Adair-Rohani H . A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012; 380(9859):2224-60. PMC: 4156511. DOI: 10.1016/S0140-6736(12)61766-8. View

Stoner L, Castro N, Kucharska-Newton A, Smith-Ryan A, Lark S, Williams M . Food Consumption Patterns and Body Composition in Children: Moderating Effects of Prop Taster Status. Nutrients. 2019; 11(9). PMC: 6770641. DOI: 10.3390/nu11092037. View

Ball K, Jeffery R, Abbott G, McNaughton S, Crawford D . Is healthy behavior contagious: associations of social norms with physical activity and healthy eating. Int J Behav Nutr Phys Act. 2010; 7:86. PMC: 3018448. DOI: 10.1186/1479-5868-7-86. View

Altenburg T, de Kroon M, Renders C, HiraSing R, Chinapaw M . TV time but not computer time is associated with cardiometabolic risk in Dutch young adults. PLoS One. 2013; 8(2):e57749. PMC: 3584035. DOI: 10.1371/journal.pone.0057749. View

OBrien S, Dozo N, Hinton J, Moeck E, Susanto R, Jayaputera G . SEMA: A free smartphone platform for daily life surveys. Behav Res Methods. 2024; 56(7):7691-7706. PMC: 11362263. DOI: 10.3758/s13428-024-02445-w. View

Sallis J, Cervero R, Ascher W, Henderson K, Kraft M, Kerr J . An ecological approach to creating active living communities. Annu Rev Public Health. 2006; 27:297-322. DOI: 10.1146/annurev.publhealth.27.021405.102100. View

10.

Harris P, Taylor R, Thielke R, Payne J, Gonzalez N, Conde J . Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2008; 42(2):377-81. PMC: 2700030. DOI: 10.1016/j.jbi.2008.08.010. View

11.

ODonoghue G, Perchoux C, Mensah K, Lakerveld J, van der Ploeg H, Bernaards C . A systematic review of correlates of sedentary behaviour in adults aged 18-65 years: a socio-ecological approach. BMC Public Health. 2016; 16:163. PMC: 4756464. DOI: 10.1186/s12889-016-2841-3. View

12.

Busschaert C, De Bourdeaudhuij I, Van Cauwenberg J, Cardon G, De Cocker K . Intrapersonal, social-cognitive and physical environmental variables related to context-specific sitting time in adults: a one-year follow-up study. Int J Behav Nutr Phys Act. 2016; 13:28. PMC: 4769505. DOI: 10.1186/s12966-016-0354-1. View

13.

Hobbs M, Pearson N, Foster P, Biddle S . Sedentary behaviour and diet across the lifespan: an updated systematic review. Br J Sports Med. 2014; 49(18):1179-88. DOI: 10.1136/bjsports-2014-093754. View

14.

Baghurst T, Kelley B . An examination of stress in college students over the course of a semester. Health Promot Pract. 2013; 15(3):438-47. DOI: 10.1177/1524839913510316. View

15.

Grandner M, Chakravorty S, Perlis M, Oliver L, Gurubhagavatula I . Habitual sleep duration associated with self-reported and objectively determined cardiometabolic risk factors. Sleep Med. 2013; 15(1):42-50. PMC: 3947242. DOI: 10.1016/j.sleep.2013.09.012. View

16.

Chinoy E, Cuellar J, Huwa K, Jameson J, Watson C, Bessman S . Performance of seven consumer sleep-tracking devices compared with polysomnography. Sleep. 2020; 44(5). PMC: 8120339. DOI: 10.1093/sleep/zsaa291. View

17.

Li G, Zhang P, Wang J, An Y, Gong Q, Gregg E . Cardiovascular mortality, all-cause mortality, and diabetes incidence after lifestyle intervention for people with impaired glucose tolerance in the Da Qing Diabetes Prevention Study: a 23-year follow-up study. Lancet Diabetes Endocrinol. 2014; 2(6):474-80. DOI: 10.1016/S2213-8587(14)70057-9. View

18.

Nagata J, Vittinghoff E, Dooley E, Lin F, Rana J, Sidney S . TV Viewing From Young Adulthood to Middle Age and Cardiovascular Disease Risk. Am J Prev Med. 2023; 66(3):427-434. PMC: 10922676. DOI: 10.1016/j.amepre.2023.11.004. View

19.

Buchan D, Baker J . Development and Evaluation of Sedentary Time Cut-Points for the activPAL in Adults Using the GGIR R-Package. Int J Environ Res Public Health. 2023; 20(3). PMC: 9915298. DOI: 10.3390/ijerph20032293. View

20.

Stoner L, Weatherall M, Skidmore P, Castro N, Lark S, Faulkner J . Cardiometabolic Risk Variables in Preadolescent Children: A Factor Analysis. J Am Heart Assoc. 2017; 6(10). PMC: 5721889. DOI: 10.1161/JAHA.117.007071. View