The Biobehavioral Family Model: Close relationships and allostatic load

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Abstract

Rationale: This study tested the inclusion of allostatic load as an expansion of the biobehavioral reactivity measurement in the Biobehavioral Family Model (BBFM). The BBFM is a biopsychosocial approach to health which proposes biobehavioral reactivity (anxiety and depression) mediates the relationship between family emotional climate and disease activity. Methods: Data for this study included a subsample of n = 1255 single and married, English-speaking adult participants (57% female, M age = 56 years) from the National Survey of Midlife Development in the United States (MIDUS II), a nationally representative epidemiological study of health and aging in the United States. Participants completed self-reported measures of family and marital functioning, anxiety and depression (biobehavioral reactivity), number of chronic health conditions, number of prescribed medications, and a biological protocol in which the following indices were obtained: cardiovascular functioning, sympathetic and parasympathetic nervous system activity, hypothalamic pituitary adrenal axis activity, inflammation, lipid/fat metabolism, and glucose metabolism. Results: Structural equation modeling indicated good fit of the data to the hypothesized family model (χ 2 = 125.13 p = .00, SRMR = .03, CFI = .96, TLI = .94, RMSEA = .04) and hypothesized couple model (χ2 = 132.67, p = .00, SRMR = .04, CFI = .95, TLI = .93, RMSEA = .04). Negative family interactions predicted biobehavioral reactivity for anxiety and depression and allostatic load; however couple interactions predicted only depression and anxiety measures of biobehavioral reactivity. Conclusion: Findings suggest the importance of incorporating physiological data in measuring biobehavioral reactivity as a predicting factor in the overall BBFM model.

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Priest, J. B., Woods, S. B., Maier, C. A., Parker, E. O., Benoit, J. A., & Roush, T. R. (2015). The Biobehavioral Family Model: Close relationships and allostatic load. Social Science and Medicine, 142, 232–240. https://doi.org/10.1016/j.socscimed.2015.08.026

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