The concept of allostatic load (AL) refers to the idea of a global physiological ‘wear and tear’ resulting from the adaptation to the environment through the stress response systems over the life span. The link between socioeconomic position (SEP) and mortality has now been established, and there is evidence that AL may capture the link between SEP and mortality. In order to quantitatively assess the role of AL on mortality, we use data from the 1958 British birth cohort including eleven year mortality in 8,113 adults. Specifically, we interrogate the hypothesis of a cumulative biological risk (allostatic load) reflecting 4 physiological systems potentially predicting future risk of death (N = 132). AL was defined using 14 biomarkers assayed in blood from a biosample collected at 44 years of age. Cox proportional hazard regression analysis revealed that higher allostatic load at 44 years old was a significant predictor of mortality 11 years later [HR = 3.56 (2.3 to 5.53)]. We found that this relationship was not solely related to early-life SEP, adverse childhood experiences and young adulthood health status, behaviours and SEP [HR = 2.57 (1.59 to 4.15)]. Regarding the ability of each physiological system and biomarkers to predict future death, our results suggest that the cumulative measure was advantageous compared to evaluating each physiological system sub-score and biomarker separately. Our findings add some evidence of a biological embodiment in response to stress which ultimately affects mortality.

Chronic inflammation has been proposed as having a prominent role in the construction of social inequalities in health. Disentangling the effects of early life and adulthood social disadvantage on inflammation is key in elucidating biological mechanisms underlying socioeconomic disparities. Here we explore the relationship between socioeconomic position (SEP) across the life course and inflammation (as measured by CRP levels) in up to 23,008 participants from six European cohort studies from three countries conducted between 1958 and 2013. We find a consistent inverse association between SEP and CRP across cohorts, where participants with a less advantaged SEP have higher levels of inflammation. Educational attainment is most strongly related to inflammation, after adjusting for health behaviours, body mass index and later-in-life SEP. These findings suggest socioeconomic disadvantage in young adulthood is independently associated with later life inflammation calling for further studies of the pathways operating through educational processes.

Socioeconomic position as measured by education may be embodied and affect the functioning of key physiological systems. Links between social disadvantage, its biological imprint, and cause-specific mortality and morbidity have not been investigated in large populations, and yet may point towards areas for public health interventions beyond targeting individual behaviours. Using data from 366,748 UK Biobank participants with 13 biomarker measurements, we calculated a Biological Health Score (BHS, ranging from 0 to 1) capturing the level of functioning of five physiological systems. Associations between BHS and incidence of cardiovascular disease (CVD) and cancer, and mortality from all, CVD, cancer, and external causes were examined. We explored the role of education in these associations. Mendelian randomisation using genetic evidence was used to triangulate these findings. An increase in BHS of 0.1 was associated with all-cause (HR = 1.14 [1.12–1.16] and 1.09 [1.07–1.12] in men and women respectively), cancer (HR = 1.11 [1.09–1.14] and 1.07 [1.04–1.10]) and CVD (HR = 1.25 [1.20–1.31] and 1.21 [1.11–1.31]) mortality, CVD incidence (HR = 1.15 [1.13–1.16] and 1.17 [1.15–1.19]). These associations survived adjustment for education, lifestyle-behaviours, body mass index (BMI), co-morbidities and medical treatments. Mendelian randomisation further supported the link between the BHS and CVD incidence (HR = 1.31 [1.21–1.42]). The BHS contributed to CVD incidence prediction (age-adjusted C-statistic = 0.58), other than through education and health behaviours. The BHS captures features of the embodiment of education, health behaviours, and more proximal unknown factors which all complementarily contribute to all-cause, cancer and CVD morbidity and premature death.

Social position is known to play a role in the quality of ageing, notably through the stimulation/dysregulation of key physiological systems in response to external stresses. Using data from one wave of Understanding Society including 9088 participants, we defined, as an extension of the allostatic load, a synthetic Biological Health Score (BHS) capturing the wear-and-tear of four physiological systems (endocrine, inflammatory, cardiovascular and metabolic systems) and two organs (liver and kidney). We used 16 established blood-derived biomarkers of these systems to calculate the BHS and explored the relative contribution of socioeconomic position to the BHS and its main components across age groups. We identified a systematic decreasing education-related gradient of the BHS (p<0.001) leading to lower biological risk in participants with longer education. Education-related differences in the BHS were detected early in life, and were not attributable to lifestyle and behavioural factors. We found a consistent contribution of the inflammatory and metabolic systems to the overall score throughout from early adulthood onwards, while the contribution of the other four systems seems to vary across age groups and gender. Our findings highlight the social-to-biological processes ultimately leading to health inequalities, and suggest that such disparities can already be detected in the 20–40 years old age group and cannot be fully explained by lifestyle and behavioural factors. This may define early adulthood social condition as a precursor to accelerated biological ageing and as an important target for public health policies.

Background Occupying a low socioeconomic position is associated with increased mortality risk. To disentangle this association, previous studies considered various dimensions of socioeconomic trajectories across the life course. However, they used a limited number of stages. We simultaneously examined various dimensions of the whole professional trajectory and its association with mortality. Methods We used a large sample (337 706 men and 275 378 women) of the data obtained by linking individuals’ annual occupation (collected in 1976–2002 from a representative panel of the French salaried population in the semipublic and private sectors) with causes of death obtained from registries. All-cause and cause-specific HRs were estimated using Cox's regression models adjusted for the occupational class at the beginning of the follow-up, the current occupational class, the transition rates between occupational categories and the duration of time spent in occupational categories. Results An increase in the time spent in the clerk class increased men and women's cardiovascular mortality risk compared with that in the upper class (HRs=1.59 (1.14 to 2.20) and 2.65 (1.14 to 6.13) for 10 years increase, respectively, for men and women). Men with a high rate of transitions had about a 1.2-fold increased risk of all-cause and external-cause mortality compared with those without transitions during their professional life. This association was also observed for women's all-cause mortality. Conclusions Strong associations between professional trajectories and mortality from different causes of death were found. Long exposure to lower socioeconomic conditions was associated with increased mortality risk from various causes of death. The results also suggest gradual associations between transition rates and mortality.

Although smoking and oxidative stress are known contributors to lung carcinogenesis, their mechanisms of action remain poorly understood. To shed light into these mechanisms, we applied a novel approach using Cys34‐adductomics in a lung cancer nested case–control study (n = 212). Adductomics profiles were integrated with DNA‐methylation data at established smoking‐related CpG sites measured in the same individuals. Our analysis identified 42 Cys34‐albumin adducts, of which 2 were significantly differentially abundant in cases and controls: adduct of N‐acetylcysteine (NAC, p = 4.15 × 10⁻³) and of cysteinyl‐glycine (p = 7.89 × 10⁻³). Blood levels of the former were found associated to the methylation levels at 11 smoking‐related CpG sites. We detect, for the first time in prospective blood samples, and irrespective of time to diagnosis, decreased levels of NAC adduct in lung cancer cases. Altogether, our results highlight the potential role of these adducts in the oxidative stress response contributing to lung carcinogenesis years before diagnosis.