Analyse de l'hypertension en France : pour une analyse intersectionnelle de la cascade de soins
Bibliographic record
Abstract
In metropolitan France, estimates suggest that more than one in three adults has hypertension. Low-cost treatments are available, yet fewer than one in four hypertensive adults has a controlled level of hypertension below 140/90 mmHg. This rate is higher in other high-income countries such as Canada (65%) or Germany (52%). Using a ‘cascade of care’ model, that decomposes the hypertension care continuum in awareness, treatment, and control, provides a better understanding of the origins of poor control. Furthermore, the theoretical framework of intersectionality, which simultaneously considers social positions of gender, class, and ethno-racial origin, could be used to understand the complexity of the social inequalities observed in hypertension-related outcomes. In this article we conducted a critical review of the international literature to identify new lines of analyses that could be applied to examine complex inequalities in France. En France métropolitaine, on estime que plus d'un adulte sur trois est hypertendu. Les traitements à faible coût sont disponibles, pourtant moins d'une personne hypertendue sur quatre a une hypertension maîtrisée sous le seuil de 140/90 mmHg. Le contrôle de l'hypertension est plus élevé dans d'autres pays à hauts revenus comme le Canada (65 %) ou l'Allemagne (52 %). Le recours au modèle de la cascade de soins, qui décompose le continuum de soins de l'hypertension du diagnostic au contrôle, en passant par le traitement, permet de mieux situer les origines d'un faible contrôle. Par ailleurs, le cadre théorique de l'intersectionnalité qui tient compte simultanément des positions sociales de genre, de classe et d'appartenance ethno-raciale pourrait permettre de donner sens aux inégalités sociales de santé observées en matière d'hypertension. Cet article propose une revue critique de la littérature internationale pour dégager des pistes d'analyses qui pourraient être appliquées aux données françaises de la cohorte CONSTANCES.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".