Allostatic Load (AL) is posited to provide a measure of cumulative physiological dysregulation across multiple biological systems and demonstrates promise as a sub-clinical marker of overall health. Despite the large heterogeneity of measures employed in the literature to represent AL, few studies have investigated the impact of different AL scoring systems in predicting health. This study uses data for 4477 participants aged 50+ years participating in the Irish Longitudinal Study on Ageing (TILDA) to compare the utility of 14 different scoring algorithms that have been used to operationalise AL (i.e. count-based high-risk quartiles, deciles, two-tailed cut-points, z-scores, system-weighted indices, clinical cut-points, sex-specific scores, and incorporating medication usage). Model fit was assessed using R2, Bayesian Information Criterion (BIC), and the area under the Receiver Operating Characteristic curve (AUC). The measure incorporating medications predicted walking speed and SRH marginally better than others. In general, AL was not predictive of grip strength. Overall, the results suggest that the choice of AL scoring algorithm exerts a relatively modest influence in predicting a number of important health outcomes.
Keywords: Allostatic load; Biomarkers; Grip strength; Self-rated health; Walking speed.
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