A typology of neighborhoods and blood pressure in the RECORD Cohort Study
Bibliographic record
Abstract
BACKGROUND: Studies of associations between neighborhood environments and blood pressure (BP) have relied on imprecise characterizations of neighborhoods. This study examines associations between SBP and DBP and a neighborhood typology based on numerous residential environment characteristics. METHODS: Data from the Residential Environment and Coronary Heart Disease Study involving 7290 participants recruited in 2007-2008, aged 30-79 years, and residing in the Paris metropolitan area were analyzed. Cluster analysis was applied to measures of the physical, services and social interactions aspects of neighborhoods. Six contrasting neighborhood types were identified and examined in relation to SBP and DBP using multivariable linear regression, adjusting for individual/neighborhood socioeconomic status and individual risk factors for hypertension. RESULTS: The neighborhood typology included suburban to central urban neighborhood types with varying levels of adverse social conditions. SBP was 2-3 mmHg higher among participants residing in suburban neighborhood types and in the urban with low social standing neighborhood type, compared to residents of central urban with intermediate social standing neighborhoods (reference). The association between residing in urban low social standing neighborhoods and SBP remained after adjusting for individual/neighborhood socioeconomic status and individual risk factors for hypertension. Overall, an inverse association between DBP and level of urbanicity of the neighborhood was observed, even after adjustment for individual risk factors for hypertension. CONCLUSIONS: Variations in BP were observed by levels of urbanicity and social conditions of residential neighborhoods, with different patterns for SBP and DBP. Population interventions to reduce hypertension targeted towards specific neighborhood types hold promise.
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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 | 0.002 | 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".