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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]
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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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InfluentialInflammation and Schizophrenia
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BackgroundChildhood bullying involvement predicts low-grade systemic inflammation into adulthood
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“…in youth (e.g., age, race, gender, medications); for now, researchers can adapt guidelines that have been developed for adult populations (O’Connor et al., 2009) Based on the existing literature, we also recommend that at a minimum, researchers test and report interactions between…”
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“…in adulthood (Taylor et al., 2006), increased body mass index (Slopen et al., 2011), greater susceptibility to infection (Dowd et al., 2009), and poorer health behaviors including poor diet, cigarette smoking, low physical activity, and excess alcohol consumption (O'Connor et al., 2009).”
BackgroundPsychiatric Symptoms and Proinflammatory Cytokines in Pregnancy
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BackgroundGiollabhui, N. M., Ellman, L. M., Coe, C. L., Byrne, M. L., Abramson, L. Y., & Alloy, L. B. (2020) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2020.01.023 · Cited by 130
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“” Those who practice in moderation have lower concentrations than those who abstain or practice in excess (74).”
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“We examined the relationship of HCC and other biological markers to potential covariates including sex, age, race, SES, Body Mass Index (BMI), adiposity as measured by waist-hip circumference (WHC), smoking, and time of blood draw (O'Connor et al., 2009).”
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Cytokine Genetic Variations and Fatigue Among Patients With Breast Cancer
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“Eligibility criteria for the parent trial were as follows: diagnosis of stage 0 to IIIA breast cancer; primary cancer treatment (ie, surgery, radiation therapy, and/or chemotherapy) completed within the past 3 months and endocrine therapy not yet started; age 21 to 65 years; and no neurologic or immune-related medical…”
MethodSelf-citationNegative emotions predict elevated interleukin-6 in the United States but not in Japan
Miyamoto, Y., Boylan, J. M., Coe, C. L., Curhan, K. B., Levine, C. S., Markus, H. R., Park, J., Kitayama, S., Kawakami, N., Karasawa, M., et al. (2013) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2013.07.173 · Cited by 126
Expression of Anger and Ill Health in Two Cultures
Kitayama, S., Park, J., Boylan, J. M., Miyamoto, Y., Levine, C. S., Markus, H. R., Karasawa, M., Coe, C. L., Kawakami, N., Love, G. D., et al. (2015) · Psychological Science · doi:10.1177/0956797614561268 · Cited by 119
“We controlled for several variables, including age, gender, waist-to-hip ratio (WHR), chronic health conditions, smoking status, alcohol consumption, social status, and experience of negative emotions, all of which have been linked to these biomarkers in previous work (Coe et al., 2011; O’Connor et al., 2009).”
MethodInflammatory Biomarkers, Comorbidity, and Neurocognition in Women With Newly Diagnosed Breast Cancer
Patel, S. K., Wong, A. L., Wong, F. L., Breen, E. C., Hurria, A., Smith, M., Kinjo, C., Paz, I. B., Kruper, L. L., Somlo, G., et al. (2015) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djv131 · Cited by 121
“eligible if they were postmenopausal (to control for variability in cytokine levels associated with pre- vs postmenopausal status) (17), had no history of other cancer in the past five years, had no history of major neurologic or psychiatric disorder, were English speaking, had no metastatic disease (to eliminate impa…”
BackgroundSelf-citationLockwood, K. G., Marsland, A. L., Matthews, K. A., & Gianaros, P. J. (2018) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13939 · Cited by 119
Multivariate Brain Prediction of Heart Rate and Skin Conductance Responses to Social Threat
Eisenbarth, H., Chang, L. J., & Wager, T. D. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.3672-15.2016 · Cited by 118
Chiang, J. J., Eisenberger, N. I., Seeman, T. E., & Taylor, S. E. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1120972109 · Cited by 114
Szabo, Y. Z., & Slavish, D. C. (2020) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2020.105069 · Cited by 98
Orre, I. J., Reinertsen, K. V., Aukrust, P., Dahl, A. A., Fosså, S. D., Ueland, T., & Murison, R. C. C. (2011) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2011.04.003 · Cited by 112
“hypothyroidism or anemia), socio-demographic factors, body mass index (BMI), physical activity, smoking and alcohol use, medication, insomnia and/or depression [13].”
BackgroundCho, H. J., Seeman, T. E., Kiefe, C. I., Lauderdale, D. S., & Irwin, M. R. (2015) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2015.02.023 · Cited by 108
“Potential Biobehavioral Confounders Covariates were chosen based on the published recommendations on the assessment of control variables for the studies investigating linkages between behavioral factors and inflammation (O’Connor et al., 2009), and all of them were assessed at baseline.”
MethodSelf-citationLam, J. C. W., Shields, G. S., Trainor, B. C., Slavich, G. M., & Yonelinas, A. P. (2019) · Stress and Health · doi:10.1002/smi.2835 · Cited by 107
“Age, sex, and body mass index were included in analyses including covariates, given that these factors influence stress‐related physiology (Kajantie & Phillips, 2006; O'Connor et al., 2009).”
Gender, Obesity and Repeated Elevation of C-Reactive Protein: Data from the CARDIA Cohort
Ishii, S., Karlamangla, A. S., Bote, M., Irwin, M. R., Jacobs, D. R., Cho, H. J., & Seeman, T. E. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036062 · Cited by 107
“, gender by BMI and BMI-squared) based on literature review [5,7,14–20].”
MethodSelf-citationMitigating Cellular Inflammation in Older Adults: A Randomized Controlled Trial of Tai Chi Chih
Irwin, M. R., & Olmstead, R. E. (2011) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e3182330fd3 · Cited by 107
Self-citationMiklowitz, D. J., Portnoff, L. C., Armstrong, C. C., Keenan‐Miller, D., Breen, E. C., Muscatell, K. A., Eisenberger, N. I., & Irwin, M. R. (2016) · Psychiatry Research · doi:10.1016/j.psychres.2016.04.120 · Cited by 104
“BMI was included as a covariate in these ANOVA models given evidence that BMI correlates with inflammation (O’Connor et al., 2009).”
Self-citationPlasma cytokine abnormalities in drug-naïve, comorbidity-free obsessive–compulsive disorder
Rao, N. P., Venkatasubramanian, G., Ravi, V., Kalmady, S. V., Cherian, A. V., & Janardhan Reddy, Y. C. (2015) · Psychiatry Research · doi:10.1016/j.psychres.2015.07.009 · Cited by 106
Meta‐analysis of total and differential white blood cell counts in schizophrenia
Jackson, A. J., & Miller, B. J. (2019) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13140 · Cited by 105
Szabo, Y. Z., Slavish, D. C., & Graham-Engeland, J. (2020) · Brain, behavior, and immunity · doi:10.1016/j.bbi.2020.04.078 · Cited by 89
“Reviews in blood (47) and saliva (13) recommend considering exercise, smoking, medication use, menstrual cycle, age, gender, socioeconomic status, ethnicity, BMI, alcohol use, medication use, and sleep as potential confounds that may influence salivary and systemic inflammatory markers.”
BackgroundShanahan, L., Copeland, W., Worthman, C. M., Erkanli, A., Angold, A. C., & Costello, E. J. (2013) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2013.04.010 · Cited by 102
“The impact of alcohol and illegal drugs on inflammatory processes is less well understood, with some research suggesting that alcohol use is negatively associated with CRP (O’Connor et al., 2009).”
BackgroundInfluentialA Systematic Review of the Association Between Bereavement and Biomarkers of Immune Function
Knowles, L. M., Ruiz, J. M., & O'Connor, M. (2019) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000693 · Cited by 104
Self-citationSickness behaviors across vertebrate taxa: proximate and ultimate mechanisms
Lopes, P. C., French, S. S., Woodhams, D. C., & Binning, S. A. (2021) · Journal of Experimental Biology · doi:10.1242/jeb.225847 · Cited by 109
Piber, D., Cho, H. J., Lee, O. S., Lamkin, D. M., Olmstead, R. E., & Irwin, M. R. (2022) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2022.08.004 · Cited by 101
Self-citationKern, S., Skoog, I., Börjesson-Hanson, A., Blennow, K., Zetterberg, H., Östling, S., Kern, J., Gudmundsson, P., Marlow, T., Rosengren, L., et al. (2014) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2014.05.006 · Cited by 94
“As BMI 158 and smoking status are confounders for CSF IL-6 (O'Connor et al 2009), we added these 159 variables to the regression model.”
MethodWhen grief makes you sick: Bereavement induced systemic inflammation is a question of genotype
Schultze-Florey, C. R., Martínez-Maza, O., Magpantay, L., Breen, E. C., Irwin, M. R., Gündel, H., & O’Connor, M.-F. (2012) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2012.06.009 · Cited by 92
“…of studies have linked subjects who are homozygous for the A allele at the IL-1b 511 SNP (also described as homozygous T, referring to the complementing T allele) with higher production of IL-1b compared to G allele carriers (G/A or G/G) (Hall et al., 2004; Hwang et al., 2002; Pociot et al., 1992).”
ResultSelf-citationSleep depth and fatigue: Role of cellular inflammatory activation
Thomas, K. S., Motivala, S. J., Olmstead, R., & Irwin, M. R. (2010) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2010.07.245 · Cited by 91
“Based on previous findings that age, BMI, gender, and ethnicity are associated with inflammation and sleep (Hong et al., 2005; Lim et al., 2005; O’Connor et al., 2009, 2007), these variables were entered as covariates on Block 1 of the model.”
Self-citationInflammation Mediates Exercise Effects on Fatigue in Patients with Breast Cancer
Hiensch, A. E., Mijwel, S., Bargiela, D., Wengström, Y., May, A. M., & Rundqvist, H. (2020) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000002490 · Cited by 106
“BA IC SC EN C ES changes in BMI and inflammatory markers, as suggested by earlier research (37).”
ResultUchino, B. N., Bosch, J. A., Smith, T. W., Carlisle, M., Birmingham, W. C., Bowen, K. S., Light, K. C., Heaney, J. L. J., & O’Hartaigh, B. W. J. (2013) · Health Psychology · doi:10.1037/a0033515 · Cited by 95
“One possibility is that these associations may be due to health behaviors (O’Connor et al., 2009).”
BackgroundMethodAdverse Childhood Events and Health Biomarkers: A Systematic Review
Soares, S., Rocha, V., Kelly‐Irving, M., Stringhini, S., & Fraga, S. J. D. S. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.649825 · Cited by 96
Milrad, S. F., Hall, D. L., Jutagir, D. R., Lattie, E. G., Ironson, G. H., Wohlgemuth, W. K., Vera-Nunez, M. A., Garcia, L., Czaja, S. J., Perdomo, D. M., et al. (2016) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2016.12.008 · Cited by 94
Negative and positive affect as predictors of inflammation: Timing matters
Graham-Engeland, J. E., Sin, N. L., Smyth, J. M., Jones, D. R., Knight, E. L., Sliwinski, M. J., Almeida, D. M., Katz, M. J., Lipton, R. B., & Engeland, C. G. (2018) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2018.09.011 · Cited by 77
Munkholm, K., Weikop, P., Kessing, L. V., & Vinberg, M. (2014) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2014.09.021 · Cited by 83
Major depressive disorder and immunity to varicella-zoster virus in the elderly
Irwin, M. R., Levin, M. J., Carrillo, C., Olmstead, R., Lucko, A., Lang, N., Caulfield, M. J., Weinberg, A., Chan, I. S. F., Clair, J. B. S., et al. (2011) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2011.02.001 · Cited by 84
“Alternatively, we and others have found that sleep disturbance, prevalent in persons with depressive disorders, has a robust and independent effect on innate immune and inflammatory responses (Irwin et al., 1996, 2006, 2008; O’Connor et al., 2009), and increases the risk of viral infections (Cohen et al.”
BackgroundSelf-citationCostello, E. J., Copeland, W., Shanahan, L., Worthman, C. M., & Angold, A. C. (2013) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2013.08.027 · Cited by 83
“Variables included as covariates or stressors were those associated with variation in CRP levels (Woodward et al., 2003; Elovainio et al., 2006b; O’connor et al., 2009) or used as covariates in other longitudinal studies involving CRP (Gimeno et al.”
MethodSleep and Inflammation During Adolescence
Park, H., Tsai, K. M., Dahl, R. E., Irwin, M. R., McCreath, H. E., Seeman, T. E., & Fuligni, A. J. (2016) · Psychosomatic Medicine · doi:10.1097/psy.0000000000000340 · Cited by 80
“Ethnicity is associated with inflammatory markers (25), but prior research linking sleep and inflammation during adolescence has had limited ethnic diversity in the adolescent samples.”
BackgroundSelf-citationAu, B., Smith, K. J., Gariépy, G., & Schmitz, N. (2015) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4250 · Cited by 79
“We identified potentially relevant sociodemographic, lifestyle, and clinical contributors in the link between inflammation and depression based on recommendations from a review by O’Connor et al. (2009).”
BackgroundStress and cognition: A user’s guide to designing and interpreting studies
Shields, G. S. (2020) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2019.104475 · Cited by 80
Jacoby, A. S., Munkholm, K., Vinberg, M., Pedersen, B. K., & Kessing, L. V. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.03.040 · Cited by 82
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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