Depressive symptoms are associated with allostatic load among community-dwelling older adults

Physiology & Behavior (Impact Factor: 2.98). 01/2014; 123:223–230. DOI: 10.1016/j.physbeh.2013.10.014


The allostatic load model has been used to quantify the physiological costs of the body's response to repeated stressful demands and may provide a useful, integrative perspective on the various correlates of late-life depressive symptoms. We interviewed 125 Rochester, NY adults, ranging in age from 67 to 94 years. We employed an allostatic load score as a measure of multisystem dysfunction in hypothalamic–pituitary–adrenal axis function, immune function, anabolic activity, and cardiovascular activity. Overall, affective, and somatic depressive symptom scores were computed using the 20-item Center for Epidemiologic Studies Depression Scale. Multiple linear regression models were used to estimate associations between allostatic load scores and affective, somatic, and overall depressive symptoms. Among our sample of mean age 76.1 years, the one-week prevalence of clinically significant depressive symptoms was 12.8%. In models adjusting for demographic, socioeconomic, and health-related factors, higher allostatic load scores were associated with elevated scores for overall, affective, and somatic depressive symptoms: beta = 1.21 (95% CI = 0.38, 2.05); beta = 0.14 (95% CI = 0.040, 0.24); beta = 0.60 (95% CI = 0.23, 0.97), respectively. Our results suggest that allostatic load measure is associated with late-life depressive symptoms. This association appears to be of clinical significance, as the magnitude of the effect size was comparable (but opposite in direction) to that of antidepressant use. Future research should examine the inter-relationships of allostatic load, psychological stress, and late-life depressive symptoms.

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    • "In the past few years, this literature has begun to document neighborhood associations with allostatic load (AL), an indicator of cumulative biological risk (Bird et al., 2010; King et al., 2011; Merkin et al., 2009; Schulz et al., 2012; Stimpson et al., 2007; Theall et al., 2012; Wallace et al., 2013). AL has been linked to higher cardiovascular disease, type 2 diabetes, arthritis (Mattei et al., 2010), higher risk of 10-year all-cause mortality (Hwang et al., 2014) and depression (Kobrosly et al., 2014). A larger body of literature has documented gradients in AL by individual-level SES, where higher SES individuals generally (although not universally) exhibit lower AL (Dowd et al., 2009). "
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    ABSTRACT: Neighborhood context may influence health and health disparities. However, most studies have been constrained by cross-sectional designs that limit causal inference due to failing to establish temporal order of exposure and disease. We tested the impact of baseline neighborhood context (neighborhood socioeconomic status factor at the block-group level, and relative income of individuals compared to their neighbors) on allostatic load two years later. We leveraged data from the Boston Puerto Rican Health Study, a prospective cohort of aging Puerto Rican adults (aged 45-75 at baseline), with change in AL modeled between baseline and the 2nd wave of follow-up using two-level hierarchical linear regression models. Puerto Rican adults with higher income, relative to their neighbors, exhibited lower AL after two years, after adjusting for NSES, age, gender, individual-level SES, length of residence, and city. After additional control for baseline AL, this association was attenuated to marginal significance. We found no significant association of NSES with AL. Longitudinal designs are an important tool to understand how neighborhood contexts influence health and health disparities. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Health & Place 05/2015; 33. DOI:10.1016/j.healthplace.2015.02.001 · 2.81 Impact Factor
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    ABSTRACT: Advances in research concerning the mental health implications of dietary patterns and select nutrients have been remarkable. At the same time, there have been rapid increases in the understanding of the ways in which non-pathogenic microbes can potentially influence many aspects of human health, including those in the mental realm. Discussions of nutrition and microbiota are often overlapping. A separate, yet equally connected, avenue of research is that related to natural (for example, green space) and built environments, and in particular, how they are connected to human cognition and behaviors. It is argued here that a 'disparity of microbiota' might be expected among the socioeconomically disadvantaged, those whom face more profound environmental forces. Many of the environmental forces pushing against the vulnerable are at the neighborhood level. Matching the developing microbiome research with existing environmental justice research suggests that grey space may promote dysbiosis by default. In addition, the influence of Westernized lifestyle patterns, and the marketing forces that drive unhealthy behaviors in deprived communities, might allow dysbiosis to be the norm rather than the exception in those already at high risk of depression, subthreshold (subsyndromal) conditions, and subpar mental health. If microbiota are indeed at the intersection of nutrition, environmental health, and lifestyle medicine (as these avenues pertain to mental health), then perhaps the rapidly evolving gut-brain-microbiota conversation needs to operate through a wider lens. In contrast to the more narrowly defined psychobiotic, the term eco-psychotropic is introduced.
    Journal of PHYSIOLOGICAL ANTHROPOLOGY 05/2015; 34(1):23. DOI:10.1186/s40101-015-0061-7 · 1.27 Impact Factor

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