The interaction of socioeconomic stress and race on telomere length in children: A systematic review and meta-analysis

Abstract

RationaleProposed mechanisms relating early life exposures to poor health suggest that biologic indicators of risk are observable in childhood. Telomere length (TL) is a biomarker of aging, psychosocial stress, and a range of environmental exposures. In adults, exposure to early life adversity, including low socioeconomic status (SES), is predictive of shorter TL. However, results in pediatric populations have been mixed. Defining the true relation between TL and SES in childhood is expected to enhance the understanding of the biological pathways through which socioeconomic factors influence health across the life span. ObjectiveThe aim of this meta-analysis was to systematically review and quantitatively assess the published literature to better understand how SES, race, and TL are related in pediatric populations. MethodsStudies in the United States in any pediatric population with any measure of SES were included and identified through the following electronic databases: PubMed, EMBASE, Web of Science, Medline, Socindex, CINAHL, and Psychinfo. Analysis utilized a multi-level random-effects meta-analysis accounting for multiple effect sizes within a study. ResultsThirty-two studies were included with a total of 78 effect sizes that were categorized into income-based, education-based, and composite indicators. Only three studies directly tested the relation between SES and TL as the primary study aim. In the full model, there was a significant relation between SES and TL (r = 0.0220 p = 0.0286). Analysis by type of SES categorization identified a significant moderating effect of income on TL (r = 0.0480, 95% CI: 0.0155 to 0.0802, p = 0.0045) but no significant effect for education or composite SES. ConclusionsThere is an overall association between SES and TL that is predominately due to the association with income-based SES measures implicating income disparities as a key target for efforts to address health inequity across the life span. Identification of associations between family income and biological changes in children that predict life-span health risk provides key data to support public health policies addressing economic inequality in families and presents a unique opportunity to assess the effect of prevention efforts at the biologic level.