Evidence map›Paper›PMID 33906906›Full record

ArticleJournal of epidemiology and community health2021

Life course socioeconomic position and DNA methylation age acceleration in mid-life.

Anitha George, Rebecca Hardy, Juan Castillo Fernandez, Yvonne Kelly, Jane Maddock

Abstract read
In one paragraph

Article in Journal of epidemiology and community health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Using Epigenetic Clocks to Characterize Biological Aging in Studies of Children and Childhood Exposures: a Systematic Review.Prevention science : the official journal of the Society for Prevention Research · 2023
    Pooled it
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  7. Impact of socioeconomic conditions across the life course on epigenetic age acceleration: evidence from a longitudinal cohort.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anitha GeorgeDepartment of Epidemiology & Public Health, UCL, London, UK anitha.george.16@ucl.ac.uk.ORCID 0000-0002-5592-2323
Rebecca HardyUCL Social Research Institute, UCL, London, UK.ORCID 0000-0001-9949-0799
Juan Castillo FernandezDepartment of Twin Research & Genetic Epidemiology, King's College London, London, UK.ORCID 0000-0002-0034-8029
Yvonne KellyDepartment of Epidemiology & Public Health, UCL, London, UK.ORCID 0000-0002-2936-3994
Jane MaddockMRC Unit for Lifelong Health and Ageing, Faculty of Population Health, UCL, London, UK.ORCID 0000-0002-7975-4221

Funding

Biotechnology and Biological Sciences Research CouncilMedical Research Council MC_UU_00019/1Medical Research Council MC_UU_00019/2Medical Research Council MC_UU_00019/4Medical Research Council MC_UU_12015/2
6 · The paper itself

Abstract

backgroundAgeing 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.

methodsWe 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.

resultsIn 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)).

conclusionOur 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.

Indexed as

DNA MethylationEpigenesis, GeneticAccelerationAdultAgingHumansSocial Classageinghealth inequalitiessocial and life-course epidemiologysocio-economic

Identifiers

PMID33906906
PMCPMC8515099

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.