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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.

SUBMITTER: McCaffery JM

PROVIDER: S-EPMC3480389 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Factor structure underlying components of allostatic load.

McCaffery Jeanne M JM Marsland Anna L AL Strohacker Kelley K Muldoon Matthew F MF Manuck Stephen B SB

PloS one 20121024 10

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 r ...[more]

PMID: 23112812

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Project description:Background Prevention of hearing loss via addressing potentially modifiable risk factors may offer means of reducing the global burden of hearing loss. Prior studies reported associations between individual markers of inflammation and risk of hearing impairment. Allostatic load is an index of cumulative physiological stressors, including inflammation, to multiple biological systems. Our aims were to investigate associations between allostatic load and both audiometric and self-reported hearing impairment and examine whether associations are stronger over time due to prolonged high allostatic load. Methods Data were taken from the English Longitudinal Study of Ageing (ELSA), a nationally representative study of people aged 50+ living in England over 3 time points between 2008 and 2014. Allostatic load score was comprised of thirteen different measures available at baseline and 4 years post-baseline (high-density lipoprotein/total cholesterol, triglyceride, fibrinogen, haemoglobin A1c, C-reactive protein, insulin-like growth factor 1 (IGF-1), systolic and diastolic blood pressure, mean arterial pressure, resting pulse rate, peak expiratory flow, BMI and waist circumference), measured using clinical cut-off points for normal biomarker parameters. Hearing acuity was measured with a simple handheld tone-producing device at follow-up 7 years post-baseline, while self-reported hearing impairment was measured at time point. Results We included samples of 4373 and 4430 for the cross-sectional and longitudinal analysis, respectively. In the cross-sectional model high allostatic load was associated both self-reported (OR = 1.08, 95% CI 1.0,1.1; p < 0.01) and objective hearing loss (OR = 1.10, 95% CI 1.1,1.2; p < 0.001) adjusting for age and sex. Cross-sectional associations between allostatic load and hearing were not significant after further adjustment for covariates (qualification, physical activity and smoking). In longitudinal modelling, high allostatic load was associated with both audiometric (Z score OR = 1.11, 95% CI 1.1,1.2; p < 0.001) and self-reported hearing impairment (OR = 1.08, 95% CI 1.0,1.1; p < 0.001) adjusting for age and sex. Allostatic load was no longer associated with self-reported hearing loss but the association with audiometric hearing impairment (OR = 1.08, 95% CI 1.03,1.13; p < 0.001) remained following additional adjustment for baseline self-reported hearing, education, physical activity, and smoking. Conclusions Prolonged high allostatic load was associated with risk of hearing impairment. Reducing allostatic load via healthy lifestyle changes including non-smoking, healthy diet and exercise may offer an opportunity to reduce the risk of hearing impairment in later life. Highlights • Allostatic load captures cumulative physiological stress which has consequence for subsequent hearing function.• Prolonged high allostatic load was associated with risk of objectively measured hearing impairment.• This association is shown in nationally representative longitudinal ageing study.

Project description:Allostatic load is commonly operationalized using a sum-score of high-risk biomarkers. However, this method implies that biomarkers contribute equally to allostatic load, as each is given equal weight. Our goal in this methodological paper is to evaluate this, and complementarily, to identify biomarkers that are most informative and least informative for developing an allostatic load index. Item response theory models provide an alternate approach to calculating the allostatic load score, by treating individual biomarkers (e.g. “items”) as indicators of a latent allostatic load construct. Item response theory scores account for the data-driven discriminating power of each biomarker, and an individual’s pattern of biomarker responses. To demonstrate feasibility of this approach, we used data from the 2015–2016 National Health Examination and Nutrition Survey (NHANES; N = 3751), with twelve allostatic load biomarkers representing immune response, metabolic function and cardiovascular health. Item response theory models revealed that body-mass-index and C-reactive protein were the most informative biomarkers for allostatic load. Both higher allostatic load sum-score and allostatic load item response theory score were associated with lower socio-economic status (p = 0.008; p<0.001, respectively). Further, both formulations of allostatic load were positively associated with a nine-item depression screener (p<0.001 for both), but only the item response theory score was also positively associated with the impact of depressive symptoms on daily life (p = 0.045). Item response theory scores may be more finely tuned to tease out effects, compared to sum-scores, and also provide more flexibility when there are missing biomarker measurements. Supplemental R code for our approach are included. Highlights • Methodological paper to introduce item response theory for calculating allostatic load.• Biomarker data from NHANES 2015–2016 representative of United States adults.• Body-mass-index and C-reactive protein most informative for allostatic load.• Item response theory captures more variability in allostatic load compared to sum-scores.• Future work - item response theory can standardize allostatic load across datasets.

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Factor structure underlying components of allostatic load.

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Factor structure underlying components of allostatic load.

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