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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]
In the citing paper
“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]
In the citing paper
“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]
In the citing paper
“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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Psychoneuroimmunology and Mental Health Disorders
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Exploring longitudinal pathways from intelligence to morbidity and mortality risk
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Daily discrimination and inflammation patterns among Black and Hispanic adolescents
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Antici, E. E., Pressman, S. D., Odgers, C. L., & Kuhlman, K. R. (2026) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2026.106578
Hoyt, M. A., Llave, K., Carroll, J. E., & Haydon, M. D. (2026) · Social Science & Medicine · doi:10.1016/j.socscimed.2026.119332
“Participant age, income, and time since diagnosis were identified as statistical covariates and included in regression models (see O’Connor et al., 2009).”
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“Obesity indices are linked with elevated levels of inflammatory markers, with stronger evidence for IL-6 and CRP versus TNF-α [46], potentially due to differential physiological roles of these molecules [46, 47].”
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“Additionally empirical research has examined the negative impacts of bullying at work (Byrne et [19-20].”
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“For example, although higher BMI is associated with lower SES and worse cognition, it also is consistently associated with higher levels of inflammation (O ’ Connor et al ., 2009).”
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“All models adjusted for factors that may be associated with the immune and clinical variables as covariates (39,49), including age, race, ethnicity, body mass index, smoking status, cancer stage (0/I vs. II/III), surgery type, and cancer treatment (chemotherapy, radiation, endocrine therapy).”
Self-citation
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
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