The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Allostatic load as a predictor of all-cause and cause-specific mortality in the general population: Evidence from the Scottish Health Survey
Open accessAbstract
Allostatic load is a multiple biomarker measure of physiological 'wear and tear' that has shown some promise as marker of overall physiological health, but its power as a risk predictor for mortality and morbidity is less well known. This study has used data from the 2003 Scottish Health Survey (SHeS) (nationally representative sample of Scottish population) linked to mortality records to assess how well allostatic load predicts all-cause and cause-specific mortality. From the sample, data from 4,488 men and women were available with mortality status at 5 and 9.5 (rounded to 10) years after sampling in 2003. Cox proportional hazard models estimated the risk of death (all-cause and the five major causes of death in the population) according to allostatic load score. Multiple imputation was used to address missing values in the dataset. Analyses were also adjusted for potential confounders (sex, age and deprivation). There were 258 and 618 deaths over the 5-year and 10-year follow-up period, respectively. In the fully-adjusted model, higher allostatic load (poorer physiological 'health') was not associated with an increased risk of all-cause mortality after 5 years (HR = 1.07, 95% CI 0.94 to 1.22; p = 0.269), but it was after 10 years (HR = 1.08, 95% CI 1.01 to 1.16; p = 0.026). Allostatic load was not associated with specific causes of death over the same follow-up period. In conclusions, greater physiological wear and tear across multiple physiological systems, as measured by allostatic load, is associated with an increased risk of death, but may not be as useful as a predictor for specific causes of death.
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“Fortunately, although diagnosable disease does not occur until later in life, there are several reliable indices of early damage to regulatory systems, allostatic load (Hwang et al., 2014; Robertson et al., 2017; Seeman et al., 2001), and cellular aging such as inflammation, telomere length, and epigenetic clock (Chen et al., 2016; Codd et al., 2013; Emerging Risk Factors Collaboration et al., 201”
From More than a feeling: A unified view of stress measurement for population science (2018) · cites this paper as Robertson et al., 2017
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Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
Stress, adaptation, and disease. Allostasis and allostatic load
McEWEN, B. S. (1998) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.1998.tb09546.x · Cited by 5,092
How Many Imputations are Really Needed? Some Practical Clarifications of Multiple Imputation Theory
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“Weathering” and Age Patterns of Allostatic Load Scores Among Blacks and Whites in the United States
Geronimus, A. T., Hicken, M., Keene, D., & Bound, J. (2006) · American Journal of Public Health · doi:10.2105/ajph.2004.060749 · Cited by 2,525
Allostasis and Allostatic Load Implications for Neuropsychopharmacology
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Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging
Seeman, T. E., McEwen, B. S., Rowe, J. W., & Singer, B. H. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.081072698 · Cited by 1,385 · cited 2×
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MethodSeeman, T. E. (1997) · Archives of Internal Medicine · doi:10.1001/archinte.1997.00440400111013 · Cited by 1,368
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Criminal legal system contact and markers of biological aging: A systematic review
Rodrigues, M., Cuevas, A. G., Crump, A. A., Lindenfeld, Z., Rouhani, S., & Bather, J. R. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106942
Allostatic load predicts symptom burden among breast cancer survivors
Guan, Y., Shen, J., Boyle, J., Daniel, K. E., Chow, P. I., Fuemmeler, B. F., & Zhao, H. (2026) · Breast Cancer Research · doi:10.1186/s13058-026-02389-3
Metadata
- Authors
- Robertson, T., Beveridge, G., & Bromley, C.
- Affiliations
- University of Stirling (GB)
- Scottish Collaboration for Public Health Research and Policy (GB)
- UK Statistics Authority (GB)
- Corresponding author
- Robertson, Tony
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2017-08-16
- Volume
- 12
- Issue
- 8
- Pages
- e0183297
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC5559080
- OpenAlex
- W2747845624
- Cited by
- 102
- References
- 32
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 9 · 2023: 16 · 2022: 9 · 2021: 14 · 2020: 17 · 2019: 13 · 2018: 2
- FWCI
- 9.71
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Stirling Online Research Repository (University of Stirling) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- Medical Research Council (MR/K023209/1)
- Topics
- Social Sciences › Health › Health disparities and outcomes
- Health Sciences › Medicine › Pathology and Forensic Medicine › Alcohol Consumption and Health Effects
- Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
- Keywords
- allostatic load, mortality prediction, all-cause mortality, cause-specific mortality, biomarkers, physiological health, Scottish Health Survey
- MeSH terms
- Adolescent, Adult, Aged, Cause of Death, Female, Health Surveys, Humans, Male, Middle Aged, Scotland, Proportional Hazards Models, Allostasis, Young Adult
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