Life-Course Socioeconomic Trajectories and Biological Aging: The Importance of Lifestyles and Physical Wellbeing

Overview

Journal Nutrients

Date 2024 Oct 16

PMID 39408320

Authors

Simona Esposito

Marialaura Bonaccio

Augusto Di Castelnuovo

Emilia Ruggiero

Mariarosaria Persichillo

Sara Magnacca

Amalia De Curtis

Chiara Cerletti

Maria Benedetta Donati

Giovanni de Gaetano

Licia Iacoviello

Alessandro Gialluisi

The Moli-Sani Study Investigators

Affiliations

Soon will be listed here.

Abstract

Background/objectives: Studies investigating the associations between life-course socioeconomic status (SES) and biological aging (the difference between biological and chronological age, Δage) have mostly been focused on epigenetic clocks and on a limited number of mediators. The aim of this study was to investigate this relationship using a blood-based aging clock, as well as the potential mediation of different factors including lifestyles or their proxies and physical and mental wellbeing.

Methods: A deep-learning aging clock based on 36 blood markers was deployed, in a large Italian population cohort: the Moli-sani study (N = 4772; ≥35 years; 48% men). SES was defined as an eight-level trajectory over the life course, which was tested with Δage in linear models incrementally adjusted for age, sex, and prevalent health conditions. Moreover, the proportion of associations explained by diverse potential mediators, including diet, smoking, physical activity, alcohol, body mass index (BMI), and physical and mental quality of life (QoL) was estimated.

Results: Compared to participants with a stably high SES, those showing an educational and financial downward trajectory were older than their CA (β (95%CI) = 1.28 (0.73-1.83) years), as were those with a stably low SES (0.75 (0.25-01.25) years). These associations were largely explained by the tested mediators (overall proportion: 36.2% and 66.3%, respectively), prominently by physical QoL (20.7% and 41.0%), BMI (16.8% and 34.3%), lifestyle (10.6% and 24.6%), and dietary inflammatory score (5.3% and 9.2%).

Conclusions: These findings indicate that life-course socioeconomic inequalities are associated with accelerated biological aging, suggesting physical wellbeing and pro-inflammatory lifestyles as potential public health targets to slow down this process in susceptible socioeconomic strata of the population.

References

Karimi M, Castagne R, Delpierre C, Albertus G, Berger E, Vineis P . Early-life inequalities and biological ageing: a multisystem Biological Health Score approach in . J Epidemiol Community Health. 2019; 73(8):693-702. PMC: 6678052. DOI: 10.1136/jech-2018-212010. View

Cunliffe V . The epigenetic impacts of social stress: how does social adversity become biologically embedded?. Epigenomics. 2016; 8(12):1653-1669. PMC: 5289034. DOI: 10.2217/epi-2016-0075. View

Raffington L, Schwaba T, Aikins M, Richter D, Wagner G, Harden K . Associations of socioeconomic disparities with buccal DNA-methylation measures of biological aging. Clin Epigenetics. 2023; 15(1):70. PMC: 10148429. DOI: 10.1186/s13148-023-01489-7. View

Petrovic D, Carmeli C, Sandoval J, Bodinier B, Chadeau-Hyam M, Schrempft S . Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study. Psychoneuroendocrinology. 2022; 147:105976. DOI: 10.1016/j.psyneuen.2022.105976. View

Richiardi L, Bellocco R, Zugna D . Mediation analysis in epidemiology: methods, interpretation and bias. Int J Epidemiol. 2013; 42(5):1511-9. DOI: 10.1093/ije/dyt127. View

Bao Y, Gorrie-Stone T, Hannon E, Hughes A, Andrayas A, Neilson G . Social mobility across the lifecourse and DNA methylation age acceleration in adults in the UK. Sci Rep. 2022; 12(1):22284. PMC: 9790005. DOI: 10.1038/s41598-022-26433-2. View

Stringhini S, Dugravot A, Shipley M, Goldberg M, Zins M, Kivimaki M . Health behaviours, socioeconomic status, and mortality: further analyses of the British Whitehall II and the French GAZEL prospective cohorts. PLoS Med. 2011; 8(2):e1000419. PMC: 3043001. DOI: 10.1371/journal.pmed.1000419. View

Carlos S, de la Fuente-Arrillaga C, Bes-Rastrollo M, Razquin C, Rico-Campa A, Martinez-Gonzalez M . Mediterranean Diet and Health Outcomes in the SUN Cohort. Nutrients. 2018; 10(4). PMC: 5946224. DOI: 10.3390/nu10040439. View

Gialluisi A, Santoro A, Tirozzi A, Cerletti C, Donati M, de Gaetano G . Epidemiological and genetic overlap among biological aging clocks: New challenges in biogerontology. Ageing Res Rev. 2021; 72:101502. DOI: 10.1016/j.arr.2021.101502. View

10.

Washburn R, Adams L, Haile G . Physical activity assessment for epidemiologic research: the utility of two simplified approaches. Prev Med. 1987; 16(5):636-46. DOI: 10.1016/0091-7435(87)90047-8. View

11.

Mamoshina P, Kochetov K, Cortese F, Kovalchuk A, Aliper A, Putin E . Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers. Sci Rep. 2019; 9(1):142. PMC: 6333803. DOI: 10.1038/s41598-018-35704-w. View

12.

Shannon O, Ashor A, Scialo F, Saretzki G, Martin-Ruiz C, Lara J . Mediterranean diet and the hallmarks of ageing. Eur J Clin Nutr. 2021; 75(8):1176-1192. DOI: 10.1038/s41430-020-00841-x. View

13.

Schroder S, Richter M, Schroder J, Frantz S, Fink A . Socioeconomic inequalities in access to treatment for coronary heart disease: A systematic review. Int J Cardiol. 2016; 219:70-8. DOI: 10.1016/j.ijcard.2016.05.066. View

14.

Trichopoulou A, Costacou T, Bamia C, Trichopoulos D . Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med. 2003; 348(26):2599-608. DOI: 10.1056/NEJMoa025039. View

15.

Hughes A, Smart M, Gorrie-Stone T, Hannon E, Mill J, Bao Y . Socioeconomic Position and DNA Methylation Age Acceleration Across the Life Course. Am J Epidemiol. 2018; 187(11):2346-2354. PMC: 6211240. DOI: 10.1093/aje/kwy155. View

16.

Ainsworth B, Haskell W, Whitt M, Irwin M, Swartz A, Strath S . Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000; 32(9 Suppl):S498-504. DOI: 10.1097/00005768-200009001-00009. View

17.

Apolone G, Mosconi P . The Italian SF-36 Health Survey: translation, validation and norming. J Clin Epidemiol. 1998; 51(11):1025-36. DOI: 10.1016/s0895-4356(98)00094-8. View

18.

Schrempft S, Belsky D, Draganski B, Kliegel M, Vollenweider P, Marques-Vidal P . Associations Between Life-Course Socioeconomic Conditions and the Pace of Aging. J Gerontol A Biol Sci Med Sci. 2021; 77(11):2257-2264. DOI: 10.1093/gerona/glab383. View

19.

Fiorito G, Polidoro S, Dugue P, Kivimaki M, Ponzi E, Matullo G . Social adversity and epigenetic aging: a multi-cohort study on socioeconomic differences in peripheral blood DNA methylation. Sci Rep. 2017; 7(1):16266. PMC: 5701128. DOI: 10.1038/s41598-017-16391-5. View

20.

Schmitz L, Zhao W, Ratliff S, Goodwin J, Miao J, Lu Q . The Socioeconomic Gradient in Epigenetic Ageing Clocks: Evidence from the Multi-Ethnic Study of Atherosclerosis and the Health and Retirement Study. Epigenetics. 2021; 17(6):589-611. PMC: 9235889. DOI: 10.1080/15592294.2021.1939479. View