Hostinar et al., 2015. Additive contributions of childhood adversity and recent stressors to inflammation at midlife: Findings from the MIDUS study.

Hostinar, C. E., Lachman, M. E., Mroczek, D. K., Seeman, T. E., & Miller, G. E. (2015). Additive contributions of childhood adversity and recent stressors to inflammation at midlife: Findings from the MIDUS study. Developmental psychology, 51(11), 1630.

Year: 
2015
Status: 
complete
Abstract: 

We examined the joint contributions of self-reported adverse childhood experiences (ACEs) and recent life events (RLEs) to inflammation at midlife, by testing 3 competing theoretical models: stress generation, stress accumulation, and early life stress sensitization. We aimed to identify potential mediators between adversity and inflammation. Participants were 1,180 middle-aged and older adults from the Midlife in the United States (MIDUS) Biomarker Project (M age = 57.3 years, SD = 11.5; 56% female). A composite measure of inflammation was derived from 5 biomarkers: serum levels of C-reactive protein, interleukin-6, fibrinogen, E-selectin, and ICAM-1. Participants provided self-report data regarding ACEs, RLEs, current lifestyle indices (cigarette smoking, alcohol consumption, physical exercise, waist circumference), current depressive symptoms, and demographic/biomedical characteristics. We also used indices of hypothalamic–pituitary–adrenocortical outflow (12-hr urinary cortisol) and sympathetic nervous system output (12-hr urinary norepinephrine and epinephrine). Analyses indicated that ACEs and RLEs were independently associated with higher levels of inflammation, controlling for each other’s effects. Their interaction was not significant. The results were consistent with the hypothesis that associations between ACEs and inflammation were mediated through higher urinary norepinephrine output, greater waist circumference, smoking, and lower levels of exercise, whereas higher waist circumference and more smoking partially mediated the association between RLEs and inflammation. In support of the stress accumulation model, ACEs and RLEs had unique and additive contributions to inflammation at midlife, with no evidence of synergistic effects. Results also suggested that norepinephrine output and lifestyle indices may help explain how prior stressors foster inflammation at midlife. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

 

Rast et al., 2014. The identification of regions of significance in the effect of multimorbidity on depressive symptoms using longitudinal data: an application of the Johnson-Neyman technique.

Rast, P., Rush, J., Piccinin, A., & Hofer, S. M. (2014). The identification of regions of significance in the effect of multimorbidity on depressive symptoms using longitudinal data: An application of the Johnson-Neyman technique. Gerontology60(3), 274-281.

Year: 
2014
Status: 
complete
Abstract: 

Background: The investigation of multimorbidity and aging is complex and highly intertwined with aging-related changes in physical and cognitive capabilities, and mental health and is known to affect psychological distress and quality of life. Under these circumstances it is important to understand how the effects of chronic conditions evolve over time relative to aging-related and end-of-life changes. The identification of periods in time where multimorbidity impacts particular outcomes such as depressive symptoms, versus periods of time where this is not the case, reduces the complexity of the phenomenon. 

Objective: We present the Johnson-Neyman (JN) technique in the context of a curvilinear longitudinal model with higher-order terms to probe moderatorst and to identify regions of statistical significance. In essence, the JN technique allows one to identify conditions under which moderators impact an outcome from conditions where these effects are not significant. 

Methods: To illustrate the use of the JN technique in a longitudinal sample, we used data from the Health and Retirement Study. Analyses were based on time-to-death models including participants who died within the study duration of 12 years. 

Results: Multimorbidity differentially affects rates of change in depression. For some periods in time the effects are statistically significant while in other periods the same effects are not statistically different from zero. 

Conclusion: The JN technique is useful to continuously probe moderating effects and to identify particular interactions with the model for time when certain effects are or are not statistically significant. In the context of multimorbidity this method is particularly useful for interpreting the complex interactions with differential change over time.