Cited by 486Physical Activity and HealthContext-Aware Activity Recognition SystemsObesity, Physical Activity, Diet

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Objective vs. Self-Reported Physical Activity and Sedentary Time: Effects of Measurement Method on Relationships with Risk Biomarkers

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Celis-Morales, Carlos A., Perez-Bravo, Francisco, Ibañez, Luis, Salas, Carlos, Bailey, Mark E. S., Gill, Jason M. R.·2012·PLoS ONE

DOI 10.1371/journal.pone.0036345PMC PMC3348936

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Abstract

PURPOSE: Imprecise measurement of physical activity variables might attenuate estimates of the beneficial effects of activity on health-related outcomes. We aimed to compare the cardiometabolic risk factor dose-response relationships for physical activity and sedentary behaviour between accelerometer- and questionnaire-based activity measures. METHODS: Physical activity and sedentary behaviour were assessed in 317 adults by 7-day accelerometry and International Physical Activity Questionnaire (IPAQ). Fasting blood was taken to determine insulin, glucose, triglyceride and total, LDL and HDL cholesterol concentrations and homeostasis model-estimated insulin resistance (HOMA(IR)). Waist circumference, BMI, body fat percentage and blood pressure were also measured. RESULTS: For both accelerometer-derived sedentary time (<100 counts.min(-1)) and IPAQ-reported sitting time significant positive (negative for HDL cholesterol) relationships were observed with all measured risk factors--i.e. increased sedentary behaviour was associated with increased risk (all p ≤ 0.01). However, for HOMA(IR) and insulin the regression coefficients were >50% lower for the IPAQ-reported compared to the accelerometer-derived measure (p<0.0001 for both interactions). The relationships for moderate-to-vigorous physical activity (MVPA) and risk factors were less strong than those observed for sedentary behaviours, but significant negative relationships were observed for both accelerometer and IPAQ MVPA measures with glucose, and insulin and HOMA(IR) values (all p<0.05). For accelerometer-derived MVPA only, additional negative relationships were seen with triglyceride, total cholesterol and LDL cholesterol concentrations, BMI, waist circumference and percentage body fat, and a positive relationship was evident with HDL cholesterol (p = 0.0002). Regression coefficients for HOMA(IR), insulin and triglyceride were 43-50% lower for the IPAQ-reported compared to the accelerometer-derived MVPA measure (all p≤0.01). CONCLUSION: Using the IPAQ to determine sitting time and MVPA reveals some, but not all, relationships between these activity measures and metabolic and vascular disease risk factors. Using this self-report method to quantify activity can therefore underestimate the strength of some relationships with risk factors.

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Authors: Celis-Morales, C. A., Perez-Bravo, F., Ibañez, L., Salas, C., Bailey, M. E. S., & Gill, J. M. R.
Affiliations: University of Glasgow (GB)
University of Concepción (CL)
Corresponding author: Gill, Jason M. R.
ORCID: Celis-Morales, Carlos A.
Salas, Carlos
Bailey, Mark E. S.
Gill, Jason M. R.
Venue: PLoS ONE
Publisher: Public Library of Science (PLoS)
Published: 2012-05-09
Volume: 7
Issue: 5
Pages: e36345
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0036345
PMC: PMC3348936
OpenAlex: W2156132533
Cited by: 486
References: 33
Citations by year: 2026: 12 · 2025: 12 · 2024: 31 · 2023: 25 · 2022: 28 · 2021: 41 · 2020: 53 · 2019: 40 · 2018: 41 · 2017: 49 · 2016: 47 · 2015: 48 · 2014: 33 · 2013: 24
FWCI: 22.51
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: PLoS ONE (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Universidad de Chile (submittedVersion, cc-by-nc-nd)
Newcastle University ePrints (Newcastle Univesity) (cc-by)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
Keywords: physical activity measurement, sedentary behavior, accelerometer, International Physical Activity Questionnaire, self-reported activity, moderate-to-vigorous physical activity, cardiometabolic risk factors, insulin resistance, HOMA-IR, insulin, triglycerides, HDL cholesterol, LDL cholesterol, waist circumference, body fat percentage, measurement bias
MeSH terms: Adolescent, Adult, Aged, Blood Glucose, Blood Pressure, Fasting, Female, Humans, Insulin, Insulin Resistance, Cholesterol, HDL, Cholesterol, LDL, Middle Aged, Motor Activity, Risk Factors, Triglycerides, Vascular Diseases, Biomarkers, Metabolic Syndrome, Self Report

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Objective vs. Self-Reported Physical Activity and Sedentary Time: Effects of Measurement Method on Relationships with Risk Biomarkers

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