Abstract

Loneliness and cognitive decline are pressing concerns among older adults, yet little research has explored cognition as a predictor of loneliness. This study investigates the dynamic relationship between loneliness and cognitive function in older adults using the random intercept cross-lagged panel model (RI-CLPM). Data were drawn from Waves 9-14 of the Health and Retirement Study (HRS), encompassing 8,473 individuals aged 65 years and older. Loneliness was assessed using the UCLA Loneliness Scale, and cognitive function was measured using immediate and delayed word recall and serial 7s from the HRS RAND file. Age, gender, education, marital status, self-health report, and depression were included as covariates. Using Mplus, we computed RI-CLPMs. The first three models were conducted on loneliness and cognitive functions. Then unconditional RI-CLPMs with no exogenous predictors were computed. Three conditional model results showed that age, gender, marital status, self-health report, and depression were significantly associated with loneliness in the first wave, but only age and self-health report were significantly associated with immediate and delayed word recall at the first wave, not with serial 7s. For carry-over effects, loneliness showed significant positive associations across consecutive waves, but cognitive functions showed significant positive associations just in the last two waves. Some spill-over effects were found between loneliness and cognitive functions. For within-person effects, although initially non-significant, a negative association between loneliness and immediate and delayed word recall emerged in later waves (11-12 and 13-14). The conditional models indicated that older age, not being married, male gender, low self-reported health, and high depression levels were positively associated with loneliness. However, only older age and lower self-reported health were positively linked to cognitive functions. This study underscores the link between loneliness and cognitive function decline in older adults, emphasizing the need to address loneliness to potentially reduce cognitive decline. Insights into demographic predictors of loneliness and cognitive function could inform targeted interventions for promoting successful aging.

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