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. 2025 Sep 10:49:101098.
doi: 10.1016/j.bbih.2025.101098. eCollection 2025 Nov.

Associations of lifetime stressors and health behaviors with inflammation in young adults previously placed in youth residential care

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Associations of lifetime stressors and health behaviors with inflammation in young adults previously placed in youth residential care

David Bürgin et al. Brain Behav Immun Health. .

Abstract

Background: Early life stressors (ELS) and stressful life events (SLEs) increase the risk for various physical health conditions, and health behaviors can modulate stress-associated risks. A key mechanism linking both lifetime stress and health behaviors with physical health outcomes is chronic low-grade inflammation. However, it is unclear how both stressor exposure and more proximal health behaviors are associated with inflammation in highly stress-exposed groups.

Objectives: Here, we investigated associations of lifetime stressors and health behaviors with peripheral inflammation in a highly stress exposed sample of young adults previously placed within youth residential care in Switzerland.

Method: We examined 126 young adults (M Age = 26.3 years; 31 % female) who completed questionnaires to assess ELS, SLEs, and risky and protective health behaviors. Inflammatory markers (C-reactive protein [CRP], interleukin [IL]-6, tumor necrosis factor [TNF]-α, IL-10, and IL-1ra) were measured in venous blood using high sensitivity enzyme-linked immunosorbent assays (hsELISAs). Regressions estimated associations between ELS, SLEs, and health behaviors with each inflammatory marker.

Results: Our sample reported high levels of ELS and SLEs, as well as high levels of risky health behaviors. ELS and SLEs were mostly unassociated with young adult health behaviors, and both ELS and SLEs were not associated with inflammatory markers, adjusting for covariates. Regarding behavior, nicotine dependence was associated with higher pro-inflammatory markers and alcohol abuse marginally with a lower anti-inflammatory marker, while physical activity and better sleep quality were associated with lower pro-inflammatory markers, adjusting for covariates.

Conclusions: Among individuals with high levels of lifetime stress, cumulative ELS and SLEs were unassociated with inflammation, whereas risky behaviors were associated with higher, and protective behaviors with lower inflammatory markers. Interventions that reduce risky and promote protective health behaviors may lower inflammation and promote long-term health among individuals who have experienced high lifetime stressors exposure.

Keywords: Adversity; Care leaver; Cytokines; Health behaviors; Inflammation; Maltreatment; Out-of-home care; Stressors; Youth residential care.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1
Associations of ELS and SLEs with inflammatory markers. Notes. Pooled estimates of multiple regression models across all imputed datasets. Different inflammatory markers are predicted by early life stressors (ELS), stressful life events (SLEs), age, sex, and BMI. All dimensional variables are standardized, all binary variables are coded using zero and one. Error bars represent pooled 95 %-Confidence Intervals. Within the supplementary materials tables of these regression models are provided in Supplementary Table 5.
Fig. 2
Fig. 2
Associations of risky and protective health behaviors with inflammatory markers. Notes. Pooled estimates of multiple regression models across all imputed datasets. Different inflammatory markers are predicted by individual risky and protective health behaviors, age, sex, and BMI. All dimensional variables are standardized, all binary variables are coded using zero and one. Error bars represent pooled 95 %-Confidence Intervals. Within the supplementary materials tables of these regression models are provided in Supplementary Table 6.
Fig. 3
Fig. 3
Associations of ELS, SLEs, and risky and protective health behaviors with inflammatory markers. Notes. Pooled estimates of multiple regression models across all imputed datasets. Different inflammatory markers are predicted by ELS, SLEs, individual risky and protective health behaviors, age, sex, and BMI. All dimensional variables are standardized, all binary variables are coded using zero and one. Error bars represent pooled 95 %-Confidence Intervals. Within the supplementary materials tables of these regression models are provided in Supplementary Table 7.

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