Social determinant of health patterns and mortality outcomes in US adults
Bibliographic record
Abstract
Abstract Background Social Determinants of Health (SDOH) influences healthcare access, especially in patients with chronic diseases. However, SDOHs were often investigated as single variables. Combination patterns and joint effects of multiple SDOHs are much understudied. This study seeks to identify SDOH patterns in the US general population and their influence in all-cause and specific mortality. Methods This study included US adults aged 18 to 79 from 2002 to 2018 National Health Interview Survey (NHIS) and NHIS Linked Mortality Files. 12 SDOHs from 5 domains (healthcare access, education and literacy, economic stability, social isolation, neighborhood cohesion) were selected and binarized from the NHIS, including: material, psychological, and behavioral medical financial hardship, delayed care due to transportation and due to non-transportation factors, education, employment, food security, income, housing security, marital status, and neighborhood cohesion. Key outcomes, including all-cause, cancer-specific mortality, and cardiovascular disease-specific death were identified at quarter and year of death. Results From the 105,824 younger adults (18–64 years), and the 23,825 older adults (65–79 years), five distinct SDOH patterns were identified: pattern 1 (31%, few barriers); 2 (20%, unmarried); 3 (17%, unemployed); 4 (15%, both unmarried and unemployed); and 5 (16%, with relatively high rate of non-married status, housing insecurity, and material, psychological, or behavioral medical financial hardships). Compared to pattern 1, pattern 4 and 5 had worse prognosis in all mortality outcomes in both age groups, including all-cause mortality, cancer-specific mortality, and cardiovascular disease-specific mortality in both age groups. Conclusions In this study, we found that SDOHs could be clustered into five distinct patterns. Patients who were unmarried and unemployed (pattern 4) or with multiple concurrent adverse SDOHs (pattern 5) had poorest key health outcomes. These findings support comprehensive screening for SDOH profiles to understand cumulative influences of SDOHs on quality of life and clinical outcomes of patients with chronic medical conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".