Allostatic Load (algorithm)

Allostatic Load (algorithm)

Filenames of files needed to construct Allostatic load composite:
LASAz004 (sex),
LASAC151 (bloodpressure),
LASAC160 (glucose levels),
LASAC161 (height, weight and waist circumference),
LASAC861 (interleukin-6 and C-reactive protein),
LASAC867 (HDL cholesterol and total cholesterol).

Contact: Martijn Huisman


Allostasis refers to the process of adaptation to acute stress through physiological and/or behavioural changes (1). Allostasis is essential in order to maintain internal viability amid changing conditions. The autonomic nervous system, HPA axis, cardiovascular, immune and metabolic system are activated in response to these stresses and lead to the protection and adaption of our body to the new situation. Allostatic load (AL) has been proposed as an indicator of the cumulative biological burden that is exacted on the body as a result of daily stress (2). An assumption underlying the research on AL is that AL can significantly affect the ageing process in terms of health and longevity. There have been several studies that investigated associations of social (i.e. chronic and pervasive) determinants of stress with AL, often finding positive associations (3-6)

Measurement instruments in LASA

The components that are used to construct AL have been collected using a range of measurements; i.e. via blood collection, height and weight scores and blood pressure measurement. The most elaborate measurement of indicators of allostatic load was conducted in the 1995/95 measurement (C-wave; respondents aged 65-88 years). Important information on several of the necessary indicators for AL is not available from other measurement waves. The measure is designed to provide an overarching indication of disease risk related to different physical regulatory systems: cardiovascular risk, inflammatory risk and metabolic risk. Further information about relevant measurement instruments can be obtained from the corresponding documentation of each of the specific indicators. A list of indicators that is used to measure AL is provided here.


Not applicable for this topic.

Variable information

The Allostatic Load (AL) score was constructed using 9 biological markers. The following biomarkers and indicators were used:

  • Systolic and diastolic blood pressure (mm Hg) as indicators of cardiovascular activity (4)(6)(7).
  • IL-6 (>5pg/ml) and CRP (μg/mL) as indicators of inflammation (6)(8)(9).
  • Glucose (mMol/L) as an indicator of metabolism (10).
  • Waist-hip ratio and BMI (kg/m2) as indicators of adipose tissue deposition and metabolism (4)(7)(11).
  • Cholesterol/HDL ratio and HDL (/L), related to the development of arteriosclerosis (6)(12).

This approach for constructing AL was derived from Seeman et al. (2008) (6).

The SPSS syntax for constructing the AL variable can be obtained here.

Availability of information per wave


Systolic BloodpressureMeMeMeMeMeMeMeMeMeMe
Diastolic BloodpressureMeMeMeMeMeMeMeMeMeMe

C-reactive protein


BMI from height and weight measuresMeMeMeMeMeMeMeMeMeMe
Waist hip ratio

HDL cholesterol

Total cholesterol


¹ More information about the LASA data collection waves is available here.

*  2B=baseline second cohort;
3B=baseline third cohort;
MB=migrants: baseline first cohort;
I, J=under construction;
K=future wave 2021-2022

Me=data collected in medical interview

Note: For more elaborate information on each of these indicators separately, we refer to the respective documentation pages.

Previous use in LASA

Allostatic load was constructed in LASA and investigated for a bachelor thesis (D. Namiotko, 2012), covering the link between socioeconomic status and chronic disease and the potential mediating role of Allostatic load in this association. Results demonstrated that there was no statistical evidence of an association of Allostatic load with the number of chronic diseases in cross-sectional analyses (1995/96) and of Allostatic load with the number of chronic diseases during follow-up measurements. There was no statistical evidence for an association of education level with Allostatic load in multivariate models, but respondents with a medium level of income had higher Allostatic load scores than participants with high income levels (but no statistical difference between low income groups and high income groups in Allostatic load was observed).


  1. McEwen BS. Allostasis and allostatic load: implications for neuropsychopharmacology. Neuropsychopharmacology 2000;22:108-124.
  2. Seeman TE, McEwen BS, Rowe JW, Singer BH. Allostatic load as a marker of cumulative biological risk: MacArthur studies of successful aging. PNAS 2001;98:4770-4775.
  3. Schulz AJ, Mentz G, Lachance L, et al. Associations between socioeconomic status and allostatic load: effects of neighborhood poverty and tests of mediating pathways. Am J Public Health 2012;102:1706-1714.
  4. Gruenwald TL, Karlamanga AS, Hu P, et al. History of socioeconomic disadvantage and allostatic load in later life. Soc Sci Med 2012;74:75-83.
  5. Seeman T, Epel E, Gruenewald T, Karlamanga A, McEwen BS. Socio-economic differentials in peripheral biology: cumulative allostatic load. Ann N Y Acad Sci 2010;1186:223-239.
  6. Seeman T, Merkin SS, Crimmins E, et al. Education, income and ethnic differences in cumulative biological risk profiles in a national sample of US adults: NHANES III (1988-1994). Soc Sci med 2008;66:72-87.
  7. McEwen BS. Stress, adaptation, and disease: allostasis and allostatic load. Ann N Y Acad Sci 1998;840:33-44.
  8. Bremmer MA, Beekman ATF, Deeg DJH, Penninx BWJH, Dik MG, Hak CE, Hoogendijk WJG. Inflammatory markers in late-life depression: results from a population-based study. J Affect Dis 2008;106:249-255.
  9. Schaap LA, Pluijm SMF, Deeg DJH, Visser M. Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am J Med 2006;119:526.e9-526.e17.
  10. Kubzansky L, Kawachi I, Sparrow D. Socioeconomic status and risk factor clustering in the normative aging study: any help from the concept of allostatic load? Ann Behav Med 1999;21:330-338.
  11. Hawkley LC, Lavelle LA, Berntson GG, Cacioppo JT. Mediators of the relationship between socioeconomic status and allostatic load in the Chicago Health, Aging and Social Relations Study (CHARRS). Psychophysiol 2011;48:1134-1145.
  12. Tanaka G, Kato Y, Matsumara K, Horiguchi M, Ogasawara H, Sadawa Y. The association between chronic psychosocial stress, allostatic load, and vascular health in asymptomatic young men: a pilot study using a novel finger arterial stiffness index. Jap Psychol Res 2011;53:140-154.

Date of last update: September 3, 2015