2015
DOI: 10.1016/j.annepidem.2014.11.021
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Neighborhood deprivation and preterm birth: an application of propensity score matching

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Cited by 28 publications
(32 citation statements)
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“…Although these studies have attempted to control for individual level factors on adverse perinatal outcomes, the definition of a deprived neighborhood has not been consistent across studies, nor were the numbers of social factors included in adjusted models . In ethnicity‐adjusted studies from the USA, associations of living in a deprived area and preterm birth disappear, but the neighborhood effect on birth outcomes differed between non‐Hispanic blacks and non‐Hispanic whites, indicating an interaction . An intriguing finding was the observed low risk on preterm birth in deprived areas found in our study.…”
Section: Discussioncontrasting
confidence: 53%
See 1 more Smart Citation
“…Although these studies have attempted to control for individual level factors on adverse perinatal outcomes, the definition of a deprived neighborhood has not been consistent across studies, nor were the numbers of social factors included in adjusted models . In ethnicity‐adjusted studies from the USA, associations of living in a deprived area and preterm birth disappear, but the neighborhood effect on birth outcomes differed between non‐Hispanic blacks and non‐Hispanic whites, indicating an interaction . An intriguing finding was the observed low risk on preterm birth in deprived areas found in our study.…”
Section: Discussioncontrasting
confidence: 53%
“…To explore and evaluate the contextual effect on birth outcomes, a PS‐based method was used to control for individual maternal and social factors known to influence outcomes. The use of propensity scores for the present analyses were inspired by previous work in the area; this statistical approach is an alternative to adjustment of confounders on the outcome, as random assignment of residence is not feasible. An important advantage is that various variables describing and predicting an individual probability to live in a certain neighborhood could be included in our model without concern of overfitting or collinearity .…”
Section: Discussionmentioning
confidence: 99%
“…For example, the study population in Messer et al (2006b) included over 200,000 mothers from Pennsylvania, Maryland, Michigan, and North Carolina, and Messer et al (2006a) examined over 13,000 mothers from North Carolina. Ma et al (2014) included mothers from all over SC, and the variability in NDI for all block groups in SC was higher than that of the subset of block groups examined in the current study (data not shown). Additionally, our study population was based on prevalence of ID and DD in study areas, suggesting population homogeneity on risk factors associated with these outcomes.…”
Section: Discussionmentioning
confidence: 55%
“…Of the few that have employed propensity score methods, significant differences were detected among Blacks, but not Whites. 34 …”
Section: Discussionmentioning
confidence: 99%
“…To account for potential differences between women living in neighborhoods with high and low domestic violence rates (selection bias), 34 propensity for living in a high domestic violence neighborhood (those with a domestic violence rate above the 75 th percentile of sample distribution) was estimated by a regression model including maternal age, education, smoking status, Medicaid enrollment, and number of previous live births.…”
Section: Methodsmentioning
confidence: 99%