Multimorbidity Patterns in US Adults with Subjective Cognitive Decline and Their Relationship with Functional Difficulties
Bibliographic record
Abstract
OBJECTIVES: This study identified different multimorbidity patterns among adults with subjective cognitive decline (SCD) and examined their association with SCD-related functional difficulties. METHODS: Data were obtained from the 2019 Behavioral Risk Factor Surveillance System. Latent class analysis was applied to identify different patterns of chronic conditions. Logistic regression was implemented to examine relationships between multimorbidity patterns and risk of SCD-related functional difficulties. RESULTS: Five multimorbidity patterns were identified: severely impaired (14.6%), respiratory/depression (18.2%), obesity/diabetes (18.6%), age-associated (22.3%), and minimal chronic conditions group (26.3%). Compared with minimal chronic conditions group, severely impaired group was most likely to report SCD-related functional difficulties, followed by respiratory/depression and obesity/diabetes group. DISCUSSIONS: Individuals in the three multimorbidity groups had elevated risk of SCD-related functional difficulties compared with minimal chronic conditions group. Characteristics of the high-risk groups identified in this study may help in development and implementation of interventions to prevent serious consequences of having multiple chronic conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".