期刊
JOURNAL OF EPIDEMIOLOGY AND COMMUNITY HEALTH
卷 75, 期 11, 页码 1084-1090出版社
BMJ PUBLISHING GROUP
DOI: 10.1136/jech-2020-215608
关键词
ageing; health inequalities; social and life-course epidemiology; socio-economic
资金
- Economic and Social Research Council/Biotechnology and Biological Sciences Research Council Soc-B Centre for Doctoral Training [ES/P000347/1]
- UK Medical Research Council [MC_UU_00019/1]
- Economic and Social Research Council [ES/K000357/1]
- Alzheimer's Society [469]
- Economic and Social Research Council/Biotechnology and Biological Sciences Research Council Soc-B Centre a grant from the Economic and Social Research Council [ES/N000404/1]
- ESRC [ES/K000357/1, ES/N000404/1] Funding Source: UKRI
- MRC [MC_UU_00019/1] Funding Source: UKRI
This study investigated the association between socioeconomic position and DNAm age acceleration, finding that childhood and adult socioeconomic disparities are related to a faster biological ageing process. Exposure to social disadvantage was associated with higher age acceleration, indicating the impact of social disadvantage on the ageing process.
Background Ageing biomarkers can help us better understand how well-established socioeconomic position (SEP) disparities in ageing occur. A promising new set of DNAm methylation (DNAm)-based ageing biomarkers indicate through their age acceleration (AA) measures if biological ageing is slower or faster than chronological ageing. Few studies have investigated the association between SEP and DNAm AA. Methods We used linear regression to examine the sex-adjusted relationships between childhood social class, adult social class, intergenerational social class change, education and adult household earnings with first (Horvath AA and Hannum AA) and second generation (PhenoAge AA and GrimAge AA) DNAm AA markers using data from the MRC National Survey of Health and Development. Results In the first-generation biomarkers, there was little evidence of any associations with Horvath AA but associations of childhood social class and income with Hannum AA were observed. Strong associations were seen between greater disadvantage in childhood and adult SEP and greater AA in the second generation biomarkers. For example, those with fathers in an unskilled occupational social class in childhood had 3.6 years greater PhenoAge AA (95% CI 1.8 to 5.4) than those with fathers from a professional social class. Individuals without qualifications had higher AA compared with those with higher education (4.1 years greater GrimAge AA (95% CI 3.1 to 5.0)). Conclusion Our findings highlight the importance of exposure to social disadvantage in childhood to the biological ageing process. The second generation clocks appear to be more sensitive to the accumulation of social disadvantage across the life course.
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