Loneliness and Cognitive Decline Among U.S. Adults: A Stratified Analysis of the BRFSS
Fasokun, M. E.; Ogundare, T.; Ogunyankin, F.; Gordon, K.; Ikugbayigbe, S.; Michael, M.; Hughes, K.; Akinyemi, O.
Show abstract
BackgroundLoneliness is an emerging public health concern linked to adverse mental and physical outcomes. It may play a key role in cognitive aging, yet its population-level association with subjective cognitive decline (SCD) across demographic groups is not well characterized. We evaluated how the frequency of loneliness relates to SCD in U.S. adults and whether associations differ by sex, age and race/ethnicity. MethodsWe performed a cross-sectional analysis of adults aged [≥]16 years using nationally representative 2016-2023 Behavioral Risk Factor Surveillance System data (BFRSS). Loneliness was categorized as never, rarely, sometimes, usually or always. The primary outcome was self-reported SCD in the past year. Survey-weighted logistic regression models adjusted for sociodemographic factors, health insurance, metropolitan status and survey year were used to estimate adjusted marginal probabilities of SCD across loneliness categories. Interaction terms and stratified margins evaluated effect modification by sex, age group (16-44, 45-64 and [≥]65 years) and race/ethnicity (non-Hispanic White, non-Hispanic Black and Hispanic). ResultsAmong 85,969 adults who reported loneliness, 13,879 (16.2%) experienced subjective cognitive decline (SCD), with a mean age of 65.7 {+/-} 10.6 years. Loneliness showed a strong dose-response relationship with SCD. Predicted probabilities of SCD increased from 9.9 % (95 % CI, 9.3-10.5 %) among respondents who never felt lonely to 15.0 % (14.1-15.9 %) for rarely, 24.9 % (23.6-26.1 %) for sometimes, 38.4 % (34.4-42.5 %) for usually and 45.7 % (41.0-50.4 %) for always lonely adults (p < 0.001). Women who were always lonely had an adjusted probability of SCD that was 10.7 percentage points higher than men; sex differences were negligible at lower loneliness levels. Age differences were minimal across most loneliness categories; however, among adults who were always lonely, those aged >64 years had significantly lower predicted cognitive function compared with adults aged 18-64 years (p < 0.001). Racial and ethnic differences were modest; the only significant contrast was a 1.7 percentage-point lower probability of SCD for non-Hispanic Black adults compared with Whites among those who never felt lonely. Other subgroup differences were not statistically significant. ConclusionsLoneliness is independently and strongly associated with higher likelihood of subjective cognitive decline among U.S. adults, and this relationship is most pronounced for chronic loneliness. While sex and age modified the effect of loneliness, racial/ethnic disparities were minimal. These findings identify loneliness as a modifiable social determinant of cognitive health, supporting the need for broad social connection initiatives and targeted efforts for women and mid-life adults with chronic loneliness.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Genetic risk for Alzheimer disease, cognition and Mild Behavioral Impairment in healthy older adults 92%
- Clinical Validation and Machine Learning Optimization of MyCog: A Self-Administered Cognitive Screener for Primary Care Settings 92%
- Persistence of Neuropsychiatric Symptoms and Dementia Prognostication: A Comparison of Three Operational Definitions of Mild Behavioral Impairment 92%
Similar papers in this journal
Similar papers in this journal
- Everyday functioning in a community-based volunteer population: Differences between participant- and study partner-report 94%
- High blood uric acid is associated with reduced risks of mild cognitive impairment among older adults in China: a 9-year prospective cohort study 93%
- Enriching hippocampal memory function in older adults through real-world exploration 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.