生命历程法
社会经济地位
衰老
疾病
基因表达
生物
老年学
表达式(计算机科学)
人口学
基因
心理学
医学
遗传学
内科学
发展心理学
社会学
计算机科学
人口
程序设计语言
作者
Cecilia Potente,Julien Bodelet,Hira Himeri,Steve W. Cole,Kathleen Mullan Harris,Michael J. Shanahan
标识
DOI:10.1136/jech-2023-221812
摘要
Background Socioeconomic status (SES) is associated with many chronic diseases, indicators of senescence and mortality. However, the changing salience of SES in the prediction of adult health is not well understood. Using mRNA-seq abundance data from wave V of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examine the extent to which SES across the early life course is related to gene expression-based signatures for chronic diseases, senescence and inflammation in the late 30s. Methods We use Bayesian methods to identify the most likely model of life course epidemiology (critical, sensitive and accumulation models) that characterises the changing importance of parental SES and SES during young (ages 27–30) and mid-adulthood (ages 36–39) in the prediction of the signatures. Results For most signatures, SES is an important predictor in all periods, although parental SES or SES during young adulthood are often the most predictive. For three signatures (components of diabetes, inflammation and ageing), critical period models involving the exclusive salience of SES in young adulthood (for diabetes) or parental SES (for inflammation and ageing) are most probable. The observed associations are likely mediated by body mass index. Conclusion Models of life course patterns of SES may inform efforts to identify age-specific mechanisms by which SES is associated with health at different points in life and they also suggest an enhanced approach to prediction models that recognise the changing salience of risk factors.
科研通智能强力驱动
Strongly Powered by AbleSci AI