Factor structure underlying components of allostatic load

Abstract

Allostatic load is a commonly used metric of health risk based on the hypothesis that recurrent exposure to environmental demands (e.g., stress) engenders a progressive dysregulation of multiple physiological systems. Prominent indicators of response to environmental challenges, such as stress-related hormones, sympatho-vagal balance, or inflammatory cytokines, comprise primary allostatic mediators. Secondary mediators reflect ensuing biological alterations that accumulate over time and confer risk for clinical disease but overlap substantially with a second metric of health risk, the metabolic syndrome. Whether allostatic load mediators covary and thus warrant treatment as a unitary construct remains to be established and, in particular, the relation of allostatic load parameters to the metabolic syndrome requires elucidation. Here, we employ confirmatory factor analysis to test: 1) whether a single common factor underlies variation in physiological systems associated with allostatic load; and 2) whether allostatic load parameters continue to load on a single common factor if a second factor representing the metabolic syndrome is also modeled. Participants were 645 adults from Allegheny County, PA (30-54 years old, 82% non-Hispanic white, 52% female) who were free of confounding medications. Model fitting supported a single, second-order factor underlying variance in the allostatic load components available in this study (metabolic, inflammatory and vagal measures). Further, this common factor reflecting covariation among allostatic load components persisted when a latent factor representing metabolic syndrome facets was conjointly modeled. Overall, this study provides novel evidence that the modeled allostatic load components do share common variance as hypothesized. Moreover, the common variance suggests the existence of statistical coherence above and beyond that attributable to the metabolic syndrome.

Figure 1. Model 1: Factor structure of the metabolic syndrome.

Age, sex and race covaried; relevant medications excluded. MS – Second-order metabolic syndrome factor; IR – insulin resistance factor; boxes represent indicator variables and circles reflect latent factors. χ² = 57.51, df = 12, p<0.001, N = 645; CFI = .98, average absolute standardized residuals = .02, RMSEA = .08.

Figure 2. Model 2: Single second-order factor model: common factor underlying allostatic load parameters.

Age, sex and race covaried; relevant medications excluded. AL – Second-order allostatic load factor; IR – insulin resistance factor; boxes represent indicator variables and circles reflect latent factors. χ² = 145.05, df = 42, p<0.001, N = 645; CFI = .97, average absolute standardized residuals = .03, RMSEA = .06.

Figure 3. Model 3: Two second-order factor model: allostatic load and metabolic syndrome factors.

Age, sex and race covaried; relevant medications excluded. MS resid.: Second-order metabolic syndrome factor with allostatic load parameters simulataneously modeled; AL resid.: Second-order allostatic load factor with metabolic syndrome pathways simultaneously modeled; IR – insulin resistance factor; boxes represent indicator variables and circles reflect latent factors. χ² = 125.00, df = 38, p<0.001, N = 645; CFI = .97, average absolute standardized residuals = .02, RMSEA = .06. Δχ² (4) = 20.05, p<0.01.