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Sedentary Behavior, Physical Activity, and Markers of Health in Older Adults
Open accessAbstract
INTRODUCTION: The purpose of this study was to examine the association between sedentary behavior (SB), cardiometabolic risk factors, and self-reported physical function by level of moderate-vigorous physical activity (MVPA). METHODS: Cross-sectional analysis was completed on 1914 older adults age ≥ 65 yr from the 2003-2006 U.S. National Health and Nutrition Examination Survey. MVPA and SB were derived from ActiGraph accelerometers worn for 1 wk. MVPA was categorized as sufficient to meet the current U.S. guidelines (≥ 150 min · wk(-1)) or not; SB was split into quartiles. Various biomarkers were examined in laboratory analyses and physical exams, and the number of functional limitations was self-reported. Statistical interaction between SB and MVPA on the biomarker associations was the primary analysis, followed by an examination of their independent associations with relevant covariate adjustment. RESULTS: Average SB was 9.4 ± 2.3 h · d(-1) (mean ± SD), and approximately 35% were classified as sufficiently active. Overall, no significant meaningful statistical interactions were found between SB and MVPA for any of the outcomes; however, strong independent positive associations were found between SB and weight (P < 0.01), body mass index (P < 0.01), waist circumference (P < 0.01), C-reactive protein (P < 0.01), plasma glucose (P = 0.04), and number of functional limitations (P < 0.01) after adjustment for MVPA. Similarly, MVPA was negatively associated with weight (P = 0.01), body mass index (P < 0.01), waist circumference (P < 0.01), diastolic blood pressure (P = 0.04), C-reactive protein (P < 0.01), and number of functional limitations (P < 0.01) after adjustment for SB. CONCLUSIONS: The results suggest that sufficient MVPA did not ameliorate the negative associations between SB and cardiometabolic risk factors or functional limitations in the current sample and that there was independence on a multiplicative scale in their associations with the outcomes examined. Thus, older adults may benefit from the joint prescription to accumulate adequate MVPA and avoid prolonged sitting.
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“There do exist data from several studies that used accelerometers to objectively measure sedentary behavior, showing unfavourable associations with risk factors (e.g., the Australian AusDiab study,[24] the Proactiv UK trial,[25] the US National Health and Nutrition Examination Survey[26]).”
From Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges (2014) · cites this paper as [26]
In the citing paper
“Most analyses to date integrate acceleration data from the vertical axis only into counts per user-specified time period (e.g., counts per minute, cpm) and utilize cutpoints for classifying time spent in sedentary behaviour or physical activity (higher cpm reflects higher intensity activities), which are then related to health outcomes.[24-26]”
From Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges (2014) · cites this paper as [26]
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Metadata
- Authors
- GENNUSO, K. P., GANGNON, R. E., MATTHEWS, C. E., THRAEN-BOROWSKI, K. M., & COLBERT, L. H.
- Affiliations
- University of Wisconsin–Madison (US)
- National Cancer Institute (US)
- Venue
- Medicine & Science in Sports & Exercise
- Published
- 2013-08
- Volume
- 45
- Issue
- 8
- Pages
- 1493-1500
- ISSN
- 0195-9131 (ISSN-L)
- PMC
- PMC5764165
- OpenAlex
- W2323944228
- Cited by
- 292
- References
- 25
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 14 · 2023: 15 · 2022: 11 · 2021: 26 · 2020: 34 · 2019: 28 · 2018: 32 · 2017: 27 · 2016: 26 · 2015: 32 · 2014: 25 · 2013: 3
- FWCI
- 19.96
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Medicine & Science in Sports & Exercise (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (Z99 CA999999)
- 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
- sedentary behavior, moderate-to-vigorous physical activity, older adults, cardiometabolic risk factors, functional limitations, C-reactive protein, body mass index, waist circumference, plasma glucose, diastolic blood pressure, physical function, sitting time, biomarkers
- MeSH terms
- Adult, Aged, Cardiovascular System, Cross-Sectional Studies, Female, Health Status Indicators, Health Surveys, Humans, Male, Middle Aged, Risk Factors, United States, Biomarkers, Exercise, Risk Assessment, Sedentary Behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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