Engagement in Enriching Early-Life Activities Is Associated With Larger Hippocampal and Amygdala Volumes in Community-Dwelling Older Adults

Abstract

Objectives Numerous studies show benefits of mid- and late-life activity on neurocognitive health. Yet, few studies have examined how engagement in enriching activities during childhood, when the brain is most plastic, may confer long-term neurocognitive benefits that may be especially important to individuals raised in low-income settings. We examined associations between enriching early-life activities (EELAs) and hippocampal and amygdala volumes in a sample of predominantly African-American, community-dwelling older adults. We further assessed whether these associations were independent of current activity engagement. Methods Ninety participants from the baseline Brain Health Substudy of the Baltimore Experience Corps Trial (mean age: 67.4) completed retrospective activity inventories and an magnetic resonance imaging scan. Volumes were segmented using FreeSurfer. Results Each additional EELA was associated with a 2.3% (66.6 mm3) greater amygdala volume after adjusting for covariates. For men, each additional EELA was associated with a 4.1% (278.9 mm3) greater hippocampal volume. Associations were specific to these regions when compared with the thalamus, used as a control region. Discussion Enriching lifestyle activities during an important window of childhood brain development may be a modifiable factor that impacts lifelong brain reserve, and results highlight the importance of providing access to such activities in historically underserved populations.

Traits and treadmills: Association between personality and perceived fatigability in well-functioning community-dwelling older adults.

“…For instance, openness may be malleable with nonpsychopharmacological intervention in older adults (Roberts et al, 2017)—making it an encouraging modifiable target to decrease the risk of high fatigability. Our associations between openness and fatigability further support facilitating novelty-seeking activities pathway to improve functioning in later life (Carlson et al, 2012; Chan & Carlson, 2017; Chan et al, 2019; Moored et al, 2020; Wu et al, 2016). Additionally, conscientiousness is also a promising malleable trait that can be fostered through intervention (Magidson et al, 2014).…”

Environmental influences on the pace of brain development

“…There is initial evidence from a prospective study that traces of childhood SES are still present in the brain structure of young adults aged 23-25 years, even when adulthood SES is controlled for 189 . We do not yet know whether this is also true of older adults, but studies suggest that cognitive enrichment might be important: cognitive stimulation in childhood is associated with larger brain volumes 190 and better cognition in old age 191 when adulthood SES is controlled for. Furthermore, a longitudinal study showed that higher levels of early cognitive stimulation are associated with slower cognitive decline and less neuropathology with ageing 192 .…”

Exploring the Relationship Between Engagement in Enriching Early-Life Activities During Adolescence and Cognition in Later-Life: Results From the Health and Retirement Study

“…Quantifying cognitive reserve relies primarily on educational attainment as an early-life surrogate measure (Stern, 2002). Our findings suggest that we can extend beyond selfreported years of formal education and measure the benefits of early-life extracurricular activities among older adults to supplement existing markers of cognitive reserve (Chan et al, 2019;Moored et al, 2018;. To better understand the EELA-cognition relationship, future nationwide epidemiological surveys can administer brief, early-life retrospective questionnaires as an additional source of enriching behavior to complement measures of formal education.…”

“…Model 2 further adjusted for age (mean centered at 65), gender, race/ethnicity, father's and mother's education (mean centered), and cohort by birth year. These covariates have been used previously to account for potential confounding of the EELA-cognition relationship (Chan et al, 2019;Moored et al, 2018;Wilson et al, 2005). Additional covariates of total wealth, smoking status, diabetes status, BMI, alcohol intake, hypertension status, depressive symptoms, and geographic region born were incorporated into the fully adjusted model to further address potential confounding (Model 3).…”