Amount of Time Spent in Sedentary Behaviors in the United States, 2003-2004

Matthews, C. E.; Chen, K. Y.; Freedson, P. S.; Buchowski, M. S.; Beech, B. M.; Pate, R. R.; Troiano, R. P.

doi:10.1093/aje/kwm390

Cited by 2,631Physical Activity and HealthContext-Aware Activity Recognition SystemsObesity, Physical Activity, Diet

Amount of Time Spent in Sedentary Behaviors in the United States, 2003-2004

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Matthews, C. E., Chen, K. Y., Freedson, P. S., Buchowski, M. S., Beech, B. M., Pate, R. R., Troiano, R. P.·2008·American Journal of Epidemiology

DOI 10.1093/aje/kwm390PMC PMC3527832

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Abstract

Sedentary behaviors are linked to adverse health outcomes, but the total amount of time spent in these behaviors in the United States has not been objectively quantified. The authors evaluated participants from the 2003-2004 National Health and Nutrition Examination Survey aged >/=6 years who wore an activity monitor for up to 7 days. Among 6,329 participants with at least one 10-hour day of monitor wear, the average monitor-wearing time was 13.9 hours/day (standard deviation, 1.9). Overall, participants spent 54.9% of their monitored time, or 7.7 hours/day, in sedentary behaviors. The most sedentary groups in the United States were older adolescents and adults aged >/=60 years, and they spent about 60% of their waking time in sedentary pursuits. Females were more sedentary than males before age 30 years, but this pattern was reversed after age 60 years. Mexican-American adults were significantly less sedentary than other US adults, and White and Black females were similarly sedentary after age 12 years. These data provide the first objective measure of the amount of time spent in sedentary behavior in the US population and indicate that Americans spend the majority of their time in behaviors that expend very little energy.

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Older people lead a less-active lifestyle, sometimes because of limitations imposed by chronic illnesses.
“At the same time, older people lead a less-active lifestyle, sometimes because of limitations imposed by chronic illnesses.126”
From Evidence-Based Recommendations for Optimal Dietary Protein Intake in Older People: A Position Paper From the PROT-AGE Study Group (2013) · cites this paper as [126]
The “Differences by age and gender” section reports that adults aged 70–85 were the most sedentary group. The Discussion suggests that increased sedentary time after age 60 may reflect comorbid health conditions that limit activity, but it presents illness as a possible explanation rather than an established cause. Page numbers are not available in the supplied passages. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Americans spend more than half of their day in sedentary behavior, and 34% of patients with diabetes report less than 10 minutes per week of moderate or vigorous activity.
“Americans spend more than half of their day (55%) in sedentary behaviors such as sitting or lying down and 34% of patients with diabetes report less than 10 minutes a week of moderate/vigorous activity.”
From The Impact of Physical Activity in Patients With Type 2 Diabetes (2025) · cites this paper as [10]
The accuracy of the sedentary cutpoint may vary in different age groups.
“Similarly, while the cutpoint we used to define sedentary time has been evaluated for validity [17], it is possible that the accuracy of this threshold varies in different age groups.”
From Association of sedentary time with mortality independent of moderate to vigorous physical activity (2012) · cites this paper as [17]
The models' fit to the data was in line with previous reports, with moderate amount of variance explained for systolic blood pressure (R2 adj = 0.21), HDL (R2 adj = 0.22), CRP (R2 adj = 0.26), plasma glucose (R2 adj = 0.33), insulin (R2 adj = 0.40) and HOMA (R2 adj = 0.42).
“The models’ fit to the data was in line with previous reports [1,6,10,14–17], with moderate amount of variance explained for systolic blood pressure (R2 adj = 0.21), HDL (R2 adj = 0.22), CRP (R2 adj = 0.26), plasma glucose (R2 adj = 0.33), insulin (R2 adj = 0.40) and HOMA (R2 adj = 0.42).”
From Combined Effects of Time Spent in Physical Activity, Sedentary Behaviors and Sleep on Obesity and Cardio-Metabolic Health Markers: A Novel Compositional Data Analysis Approach (2015) · cites this paper as [15]

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Authors: Matthews, C. E., Chen, K. Y., Freedson, P. S., Buchowski, M. S., Beech, B. M., Pate, R. R., & Troiano, R. P.
Affiliations: Vanderbilt University (US)
National Institutes of Health (US)
University of Massachusetts Amherst (US)
University of South Carolina (US)
National Cancer Institute (US)
ORCID: Matthews, C. E.
Chen, K. Y.
Freedson, P. S.
Buchowski, M. S.
Beech, B. M.
Troiano, R. P.
Venue: American Journal of Epidemiology
Publisher: Oxford University Press (OUP)
Published: 2008-03-14
Volume: 167
Issue: 7
Pages: 875-881
ISSN: 0002-9262 (ISSN-L)
1476-6256
DOI: 10.1093/aje/kwm390
PMC: PMC3527832
OpenAlex: W2168524506
Cited by: 2,631
References: 52
Citations by year: 2026: 48 · 2025: 84 · 2024: 120 · 2023: 108 · 2022: 138 · 2021: 187 · 2020: 168 · 2019: 185 · 2018: 213 · 2017: 224 · 2016: 221 · 2015: 226 · 2014: 199 · 2013: 170 · 2012: 111
FWCI: 50.79
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: American Journal of Epidemiology (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
ScholarWorks@UMassAmherst (University of Massachusetts Amherst) (submittedVersion)
Scholarworks (University of Massachusetts Amherst) (submittedVersion)
Funders: National Cancer Institute
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK069465)
Topics: Health Sciences › Medicine › Physiology › 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: sedentary behavior, wearable activity trackers, accelerometry, NHANES, age and sex differences, Mexican American adults, racial and ethnic differences, energy expenditure
MeSH terms: Adolescent, Adult, Aged, Aged, 80 and over, Analysis of Variance, Child, Energy Metabolism, Ethnicity, Female, Humans, Male, Middle Aged, Motor Activity, Nutrition Surveys, Population Surveillance, Regression Analysis, Time, United States, Monitoring, Ambulatory

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