Examining the impact of racial residential segregation on birth weight: an instrumental variable approach
Notice bibliographique
Résumé
Background: Racial residential segregation is a persistent phenomenon in the Unites States and has been linked to racial differences in birth outcomes, with several studies reporting associations between segregation and birth weight. However, segregation is likely endogenous: unobserved factors driving segregation and birth outcomes at the individual and neighborhood levels are unaccounted for in standard regression models, leading to biased estimates and prompting calls for novel methods in order to adequately control for confounding. In addition, many of the individual and neighborhood-level covariates often included in prior models are likely mediators, further obscuring any impact of segregation on birth weight. I attempted to address these concerns by 1) using the Railroad Division Index (RDI) as an instrument for segregation, and 2) reassessing the role of covariates, and thus the conceptual causal model, based on existing research. Methods: Four data sources were merged to create a cross-sectional record of all non-Hispanic black and white singleton births to US-born/resident mothers in 2000, which were linked to segregation indices at the metropolitan statistical area (MSA) level. The main exposure was black-white residential segregation, measured via the dissimilarity index. The two outcomes of interest were birth weight, measured in grams, and the MSA-level black/white gap in birth weight, both modeled as continuous variables. Race-stratified standard linear regression (OLS) models were compared to two-stage least squares (2SLS) models, with cluster-robust standard errors. I performed several validity checks to assess RDI's suitability as an instrument. Results: The analytical sample contained 574,747 birth records across 93 MSAs. The magnitude of effect estimates yielded by OLS and 2SLS varied considerably. For black infants, OLS estimated a 1.17 gram decrease in individual birth weight for every one-percentage point increase in segregation (95% CI: -1.85, -.50), whereas 2SLS estimated a 2.76 gram decrease (95% CI: -6.01, .48). For white infants, OLS yielded an estimate of .53 (95% CI: -.23, 1.29), while the 2SLS estimate was in the opposite direction (-.68, 95% CI: -3.48, 2.11). Falsification checks revealed that the effect of RDI on birth weight was essentially the same for both races in locations where demand for segregation was low, further suggesting that the effect of segregation is differential by race. Conclusions: Evidence from instrumental variable models were consistent with a causal impact of segregation on birth outcomes, but 2SLS estimates were imprecise and the proposed causal mechanism was likely more plausible for blacks than for whites. OLS may underestimate the effect of segregation on birth weight in blacks. Future research should prioritize similar analytic methods using longitudinal data sources and nationally representative samples.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,054 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».