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The gender and age perspectives of allostatic load
Nikola Volarić1, Dunja Šojat2, Mile Volarić3,4
1Department of Pathophysiology, Physiology and Immunology, Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia.
Abstract:
The role of chronic stress in the development of chronic diseases, especially multimorbidity, through the pathways of increasing allostatic load, and finally, allostatic overload (the state when a compensatory mechanism is likely to fail) is being emphasized. However, allostatic load is a dynamic measure that changes depending on sex, gender, age, level and type of stress, experience of a stressful situation, and coping behaviors. Many other factors such as race, ethnicity, working environment, lifestyle, and circadian rhythm of sleep are also important. The aim of this paper was to synthesize the available information on allostatic load differences, especially those connected to sex/gender and age, and to provide a model for the future study of allostatic load, with a focus on these differences. By carefully studying allostatic load factors, we realized that many studies do not take this allostatic load difference into account in the analysis methods. In this paper, we also support the idea of further research to develop new allostatic load analysis strategies that will include all knowledge about sex/gender differences and that will, in more detail, explain numerous changeable social and educational factors that are currently accepted as biological ones. Furthermore, specific allostatic load biomarkers are expressed differently in different age groups, indicating that the discrepancies cannot be attributed solely to sex/gender disparities. This kind of approach can be valuable, not only for better explaining the differences in the frequency and age of onset of chronic diseases and multimorbidity, but also for the potential planning and development of preventive actions based on the aforementioned sex/gender and age disaparities, in order to prevent the most frequent diseases and to establish specific biomarker cut-off values for each sex/gender and age group.
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