Psychological Distress, Socioeconomic Position and Inflammatory Biomarkers Across the Life Course:Elucidating the Interplay Using Causal Inference...

心理健康问题属于疾病负担的主要贡献者之一。抑郁和焦虑与身体健康恶化有关，这会放大它们对个人和健康经济的影响。由于人群的心理困扰程度很高，研究的重点是确定其对健康的负面影响的生物学途径。慢性全身炎症是一个主要的可疑机制，因为促炎生物标志物可以通过压力系统的激活直接增加，也可以通过不健康的行为间接增加。心理痛苦通常反映潜在的不利社会经济条件。因此，虽然心理干预可以减轻心理困扰的一些影响，但它们本身可能不足以解决更广泛的心理健康危机。炎症生物标志物也显示出社会梯度，研究发现，社会经济地位较低的人炎症水平更高。尽管心理困扰可能部分解释了这种联系，但其他机制也是合理的，包括有限的资源获取和不同的社会环境。此外，更多地获得资源也可能使个人能够更好地应对心理健康问题，这表明社会经济指标和心理痛苦之间可能对健康结果产生交互影响。社会经济指标、心理困扰和炎症之间的关系可能会在一个人的一生中演变。血浆炎症生物标志物水平随着年龄的增长而增加，其浓度的社会经济差异也会随着时间的推移而变化。尽管在生命过程建模方面取得了进展，但传统的分析方法并不具备充分的能力来阐明这些关系，因为它们不能处理时变的混淆或将调解与互动结合起来。解决这些局限性需要使用因果推理方法。本项目旨在将因果推理方法应用于：1.评估心理困扰对全身炎症生物标志物的时变影响。评估社会经济指标(教育程度、收入/财富)和心理困扰对全身炎症生物标志物的因果交互作用。将社会经济指标对炎症生物标记物的平均因果效应分解为心理痛苦介导的效应、暴露-介体相互作用的效应以及通过其他途径发挥作用的效应。为了实现这些目标，该项目将使用跨越不同生命阶段的三个全面的队列数据集：雅芳父母和儿童纵向研究、国家儿童发展研究和英语老龄化纵向研究。为了在队列中实现更大的可比性，将使用基于项目反应理论的联系来校准心理痛苦的测量。社会经济指标将包括最能反映一个人在不同人生阶段获得资源的金融和教育指标。这些将包括父母或家庭收入，积累的财富，以及父母或个人的教育资格。令人感兴趣的主要生物标志物将是C反应蛋白的血浆浓度。分析将分别对每个数据集进行，从而对发现进行定性综合。这些发现将促进对社会状况、心理健康挑战和身体健康之间联系机制的理解。由于许多干预措施要么单独针对心理问题，要么单独针对社会逆境，因此综合方法可能对于改变社会弱势个人的健康轨迹至关重要。此外，在因果推理框架内整合生命过程视角可能会突出心理健康-炎症关系中的特定时期，为有效干预的时机提供洞察力。

Mental health issues belong among the primary contributors to the disease burden. Depression and anxiety are linked to deteriorating physical health, which amplifies their impact on individuals and the health economy. Due to high population levels of psychological distress, research has focused on identifying biological pathways that underpin its negative effects on health. Chronic systemic inflammation is a major suspected mechanism, as pro-inflammatory biomarkers can increase both directly through stress system activation and indirectly through unhealthy behaviours.Psychological distress often reflects underlying adverse socioeconomic conditions. Consequently, although psychological interventions can mitigate some of the impacts of psychological distress, they alone might not be sufficient in addressing the broader mental health crisis. Inflammatory biomarkers also show a social gradient, with studies finding higher inflammation levels in those with a lower socioeconomic position. Although psychological distress might partly explain this association, other mechanisms are plausible, including limited access to resources and different social environments. Additionally, increased access to resources might also enable individuals to cope better with mental health issues, suggesting possible interactive effects between socioeconomic indicators and psychological distress on health outcomes. The relationships between socioeconomic indicators, psychological distress, and inflammation likely evolve throughout an individual's life. Plasma inflammatory biomarker levels increase with age, and socioeconomic disparities in their concentration also change over time. Despite advancements in life course modelling, traditional analytical methods are not fully equipped to elucidate these relationships, as they cannot handle time-varying confounding or integrate mediation with interaction. Addressing these limitations necessitates the use of causal inference approachesThis project aims to apply causal inference approaches to:1. Assess the time-varying impacts of psychological distress on biomarkers of systemic inflammation.2. Estimate the causal interactive effect of socioeconomic indicators (education, income/wealth) and psychological distress on biomarkers of systemic inflammation.3. Decompose the average causal effect of socioeconomic indicators on biomarkers of inflammation into the effect mediated by psychological distress, the effect due to exposure-mediator interactions, and the effect operating through other pathways. To meet these aims, the project will use three comprehensive cohort datasets spanning various life stages: The Avon Longitudinal Study of Parents and Children, the National Child Development Study, and the English Longitudinal Study of Ageing. To achieve greater comparability of findings across cohorts, measures of psychological distress will be calibrated using item-response theory-based linking. Socioeconomic indicators will comprise financial and educational metrics that best reflect one's access to resources at different life stages. These will encompass parental or household income, accumulated wealth, and either parental or personal educational qualifications. The main biomarker of interest will be the plasma concentration of C-reactive protein. Analyses will be conducted separately on each dataset, resulting in a qualitative synthesis of findings.The findings will advance the understanding of the mechanisms connecting social conditions, mental health challenges, and physical health. As many interventions target either psychological issues or social adversity separately, combined approaches may be essential to change the health trajectories of socially disadvantaged individuals. Moreover, integrating a life course perspective within a causal inference framework may highlight specific periods in the mental health-inflammation relationship, offering insights into the timing for effective interventions