Autoren:
Dusan Petrovic | CHUV | Switzerland
Dr Edward Pivin | CHUV | Switzerland
Dr Belen Ponte | HUG | Switzerland
Dr Nasser Dhayat | INSEL | Switzerland
Prof. Menno Pruijm | CHUV | Switzerland
Dr Georg Ehret | HUG | Switzerland
Prof. Dr Idris Guessous | HUG | Switzerland
Dr Daniel Ackermann | INSEL | Switzerland
Sandrine Estoppey Younes | CHUV | Switzerland
Prof. Antoinette Pechère-Bertschi | HUG | Switzerland
Prof. Bruno Vogt | INSEL | Switzerland
Prof. Markus Mohaupt | INSEL | Switzerland
Prof. Pierre-Yves Martin | HUG | Switzerland
Prof. Dr. Fred Paccaud | CHUV | Switzerland
Prof. Dr Michel Burnier | CHUV | Switzerland
Prof. Murielle Bochud | CHUV | Switzerland
PD Dr Silvia Stringhini | CHUV | Switzerland
Background: Allostatic load (AL) is a marker of generalized physiological dysregulation which is thought to reflect exposure to chronic stress. High AL has been related to poorer health, and several determinants of AL have been identified, including socioeconomic status (SES), lifestyle behaviors and psychosocial exposures. Moreover, the complex physiological nature of allostatic load might also involve genetic determinants. Here, we examine the association of socioeconomic factors and lifestyle indicators with AL. Further, we investigate the extent to which AL is genetically determined by assessing narrow sense heritability.
Methods and findings: We use data from the SKIPOGH study, a population and family-based study initiated in 2009 in Switzerland. We included 803 participants (52% women, mean age 48±16 years) for which we computed an AL index aggregating cardiovascular, metabolic, lipidic, oxidative, hypothalamus-pituitary-adrenal and inflammatory markers. Education, occupational position and an aggregative SES score were used as indicators of socioeconomic status. Marital status, stress, alcohol, smoking, meat consumption, physical activity and fruit and vegetable consumption were used as lifestyle indicators. All analyses were adjusted for age, sex and the city/region of residence, and mutually adjusted for lifestyle indicators and SES. Narrow sense heritability of AL was estimated by maximum likelihood, after adjusting for age, sex and the city/region of residence (simple model), and for SES and lifestyle behaviors (full model). All three SES indicators were associated with AL, where low SES individuals had higher AL (education: OR= 2.66, 95% Confidence Interval (CI) [1.26;5.61] for Primary or lower education vs. University education). Physical activity was inversely associated with AL (OR=0.37, 95% CI: [0.24;0.58] for high vs. low physical activity). Moderate and high meat consumption were associated with increased AL (OR=2.57, 95% CI: [1.26;5.26] for high vs. low meat consumption). About 30% (28.4% ±10.1%) of the AL score was heritable.
Conclusion: In a representative sample of the Swiss population, socioeconomic status, meat consumption and physical activity were associated with AL. Heritability analysis of AL may indicate a genetic origin for this trait. Our results suggest that generalized physiological dysregulation, as measured by AL, is determined by both environmental and genetic factors.