Summary: New research indicates that declines in abstract reasoning during later life can predict increases in depressive symptoms over time. The study found a consistent association between reduced abstract reasoning and worsening depressive symptoms among older adults.
Source: APS
Declines in abstract reasoning with age forecast growing depressive symptoms in later years, according to longitudinal data from older adults in Scotland. The research appears in Psychological Science.
“Mental health in later life is an increasingly important concern as populations age worldwide,” says Stephen Aichele of the University of Geneva. “Our findings suggest that monitoring cognitive changes in later adulthood could help target interventions and reduce the risk of subsequent depression.”
Some cognitive decline is common in the later decades of life. Previous research has established a correlation between cognitive impairment and depression in older adults: as cognitive abilities diminish, depressive symptoms frequently increase. However, the direction and dynamics of this relationship have been unclear. Specifically, researchers have sought to determine whether cognitive decline drives later depression, whether depression contributes to cognitive decline, or whether both processes reinforce each other over time.
To clarify how these factors interact across years, Aichele and colleagues analyzed data from the Lothian Birth Cohort 1936, a long-term study of community-dwelling older adults in Scotland. Their analytic sample included 1,091 participants who were first assessed at age 70 and then re-evaluated up to three more times at roughly three-year intervals, finishing near age 79.
Rather than focusing on memory changes commonly linked to Alzheimer’s disease, the researchers concentrated on abstract reasoning—sometimes referred to as fluid intelligence—which relates closely to everyday problem-solving and the ability to reason with novel information. Participants completed multiple tasks measuring abstract reasoning, such as identifying missing elements in geometric patterns and reconstructing visuospatial models from component parts.
Depressive symptoms were measured using the Hospital Anxiety and Depression Scale, a commonly used self-report questionnaire for screening mood symptoms in clinical and research settings.
Across the sample, both abstract reasoning and mood tended to decline over the study period. Importantly, the analyses revealed a time-ordered relationship: lower abstract reasoning scores at one assessment predicted increases in depressive symptoms during the following interval. By contrast, higher depressive symptoms at a given assessment were not associated with later declines in abstract reasoning.
The research team applied advanced longitudinal statistical models to capture the dynamic coupling between fluid intelligence and depressive symptoms. These models showed that the effect of lower fluid intelligence on rising depressive symptoms significantly improved the fit of their models and produced a moderately strong effect size. On average, poorer performance in abstract reasoning was associated with an accumulated increase in depressive symptoms across the observed age range.
Importantly, this relationship remained after accounting for a range of sociodemographic and health-related factors. Variables such as education, socioeconomic status, and diagnoses related to cardiovascular disease, stroke, and diabetes did not substantially alter the pattern of association between declining abstract reasoning and increasing depressive symptoms.
Why reductions in abstract reasoning predict later depressive symptoms is not yet fully understood. The authors note several plausible pathways that future research should explore: unmeasured disease processes that affect both cognition and mood, genetic vulnerabilities that predispose individuals to both decline and depressive symptoms, and declines in daily functioning that reduce independence and increase risk for depression.
The team plans to extend their work by investigating interventions and supports that might weaken the link between cognitive decline and depression. Potential targets include cognitive training, clinical treatments for mood symptoms, and social or practical supports that preserve functional ability and daily engagement.
“We hope this research will be useful to older adults experiencing cognitive changes, as well as to family members and care providers seeking ways to support mental health in later life,” Aichele adds.
Funding: The study received support from the Swiss National Centre of Competence in Research LIVES and funding from the Swiss National Science Foundation (Grant 51NF40-160590). Data collection for the Lothian Birth Cohort 1936 was supported by Age UK (Disconnected Mind project), the UK Medical Research Council, and the Centre for Cognitive Ageing and Cognitive Epidemiology, which receives support from the Medical Research Council and the Biotechnology and Biological Sciences Research Council.
Source: Anna Mikulak – APS
Publisher: NeuroscienceNews.com
Image source: Public domain image
Abstract
Fluid Intelligence Predicts Change in Depressive Symptoms in Later Life: The Lothian Birth Cohort 1936
This study examined time-ordered, reciprocal associations between age-related changes in fluid intelligence and depressive symptoms. Participants were 1,091 community-dwelling older adults from the Lothian Birth Cohort 1936 who were assessed repeatedly at three-year intervals between ages 70 and 79. On average, fluid intelligence and depressive symptoms both worsened with age. The analyses revealed a dynamic coupling: low fluid intelligence at one time point predicted increasing depressive symptoms over the subsequent three-year interval, whereas elevated depressive symptoms did not predict later declines in fluid intelligence. Model comparisons indicated that including this coupling parameter significantly improved model fit and showed a moderately strong effect size, with lower cognitive performance accounting on average for an accumulated increase in depressive symptoms across the observed age range. Adjusting for sociodemographic and health-related covariates did not substantially alter the association. These findings suggest that monitoring cognitive changes in later life may help guide interventions to reduce related increases in depression risk.