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To assess, to control, to exclude: Effects of biobehavioral factors on circulating inflammatory markers
Open accessAbstract
Behavioral scientists have increasingly included inflammatory biology as mechanisms in their investigation of psychosocial dynamics on the pathobiology of disease. However, a lack of standardization of inclusion and exclusion criteria and assessment of relevant control variables impacts the interpretation of these studies. The present paper reviews and discusses human biobehavioral factors that can affect the measurement of circulating markers of inflammation. Keywords relevant to inflammatory biology and biobehavioral factors were searched through PubMed. Age, sex, and hormonal status, socioeconomic status, ethnicity and race, body mass index, exercise, diet, caffeine, smoking, alcohol, sleep disruption, antidepressants, aspirin, and medications for cardiovascular disease are all reviewed. A tiered set of recommendations as to whether each variable should be assessed, controlled for, or used as an exclusion criteria is provided. These recommendations provide a framework for observational and intervention studies investigating linkages between psychosocial and behavioral factors and inflammation.
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“Health behaviors were assessed using validated self-report items (O’Connor et al., 2009) including cigarette smoking status (never/former/current), alcohol use (drinks per week), and physical activity (minutes per week of moderate-to-vigorous intensity activity).”
From Strong Enough to Suffer: Emotional Suppression, Stress Exposure, and Physiological Health Among Men Across the Life Course (2026) · cites this paper as O’Connor et al., 2009
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“As explained by O’Connor et al. (2009), behavioral and biological pathways can also mediate the effects of psychological factors on the inflammatory markers, such as regulation strategies.”
From Strong Enough to Suffer: Emotional Suppression, Stress Exposure, and Physiological Health Among Men Across the Life Course (2026) · cites this paper as O’Connor et al., 2009
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“We examined alternative explanations by statistically controlling for plausible demographic and biobehavioral confounders (29).”
From Clustering of depression and inflammation in adolescents previously exposed to childhood adversity (2012) · cites this paper as [29]
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“Based on prior work,12,45,46 we controlled for extraneous factors associated with inflammation.”
From Social Media Use and Its Link to Physical Health Indicators (2022) · cites this paper as [48]
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“Based on prior work (Horn et al., 2018; Lee and Way, 2019; O'Connor et al., 2009), we controlled for extraneous factors that have been associated with inflammation.”
From Social media use and systemic inflammation: The moderating role of self-esteem (2021) · cites this paper as O'Connor et al., 2009
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“Biomarker participants were also similar on most health-related characteristics, but were less likely to smoke (p < .01).”
From Socioeconomic Status Interacts with Conscientiousness and Neuroticism to Predict Circulating Concentrations of Inflammatory Markers (2017) · cites this paper as [40]
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“Love and colleagues (40) reported that the biomarker sample was comparable to the broader MIDUS II sample on age, sex, race/ethnicity, marital status, and income, although participants were more likely to have a college degree (p < .01).”
From Socioeconomic Status Interacts with Conscientiousness and Neuroticism to Predict Circulating Concentrations of Inflammatory Markers (2017) · cites this paper as [40]
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Metadata
- Authors
- O’Connor, M.-F., Bower, J. E., Cho, H. J., Creswell, J. D., Dimitrov, S., Hamby, M. E., Hoyt, M. A., Martin, J. L., Robles, T. F., Sloan, E. K., Thomas, K. S., & Irwin, M. R.
- Affiliations
- University of California, Los Angeles (US)
- Carnegie Mellon University (US)
- ORCID
- Venue
- Brain, Behavior, and Immunity
- Publisher
- Elsevier BV
- Published
- 2009-10
- Volume
- 23
- Issue
- 7
- Pages
- 887-897
- ISSN
- 0889-1591 (ISSN-L)
- PMC
- PMC2749909
- OpenAlex
- W2131056323
- Cited by
- 500
- References
- 178
- Citations by year
- 2026: 18 · 2025: 26 · 2024: 23 · 2023: 34 · 2022: 52 · 2021: 43 · 2020: 39 · 2019: 37 · 2018: 31 · 2017: 27 · 2016: 29 · 2015: 30 · 2014: 22 · 2013: 25 · 2012: 34
- FWCI
- 6.98
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Brain Behavior and Immunity (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG026364, R01AG034588, K23AG028452, P30AG028748, K01AG028404)
- National Heart, Lung, and Blood Institute (R01HL079955)
- National Institute of Mental Health (T32MH019925, T32 MH 19925, T32MH018399)
- National Cancer Institute (R01CA119159)
- National Center for Research Resources (M01RR000865)
- Topics
- Life Sciences › Neuroscience › Biological Psychiatry › Tryptophan and brain disorders
- Life Sciences › Neuroscience › Behavioral Neuroscience › Stress Responses and Cortisol
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Keywords
- circulating inflammatory markers, biobehavioral factors, psychosocial factors, inflammation, confounding variables, control variables, exclusion criteria, age and sex effects, hormonal status, socioeconomic status, body mass index, physical activity, diet, caffeine, smoking, alcohol, sleep disruption, antidepressants, aspirin
- MeSH terms
- Anticholesteremic Agents, Antihypertensive Agents, Diet, Humans, Inflammation, Interleukins, Physical Fitness, Research Design, Risk Factors, Risk-Taking, Smoking, Social Class, Tumor Necrosis Factor-alpha, Biomarkers, Exercise, Epidemiologic Factors, Body Mass Index, Patient Selection, Antidepressive Agents, Second-Generation
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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