Neighborhood deprivation increases the risk of Post-induction cesarean delivery

Association of Community Characteristics as Measured by Social Deprivation Index Score with Prenatal Care and Obstetrical Outcomes

OBJECTIVE

 We aimed to determine the relationships between socioeconomic disadvantage, as measured by the Social Deprivation Index (SDI), and prenatal care (PNC) utilization, obstetrical outcomes, and neonatal complications.

STUDY DESIGN

 All spontaneously conceived singleton deliveries of nulliparous gravida with residence zip code available (n = 4,786) were identified in a population-based database. Deliveries were assigned SDI scores based on preconception zip code. SDI scores (1-100) are a composite measure of seven community demographic characteristics of poverty, education, transportation, employment, and household composition. SDI scores were categorized into quartiles and grouped for analysis (Q1 [n = 1,342], Q2 + 3 [n = 1,752], and Q4 [n = 1,692]) with higher scores indicative of greater disadvantage. Statistical analysis was performed using a generalized linear mixed method.

RESULTS

 Among our cohort, gravida in the lowest (least-deprived) SDI quartile (Q1) were older, had lower prepregnancy body mass indices, and were more likely to receive PNC from a physician specializing in Obstetrics and Gynecology. Gravida residing in the highest (most-deprived) SDI quartile (Q4) attended fewer prenatal visits (mean [standard deviation] 11.17 [2.9]) than those living in Q1 (12.04 [2.3], p < 0.0001). Gravida in Q4 were less likely to receive sufficient PNC compared with those in Q1 (52 vs. 64.2%, p < 0.0001) and were more likely to fail to achieve appropriate gestational weight gain (GWG) (19.6 in Q4 vs. 15.9% in Q1, p < 0.01). No significant differences in composite maternal (CMM) or neonatal morbidity (CNM) were associated with SDI quartile.

CONCLUSION

 Outer quartile social deprivation was associated with higher proportions of primigravida not meeting recommendations for GWG and attending fewer prenatal visits, but it did not affect CMM or CNM. Improving care access and providing nutritional support to all gravida are likely important steps toward health equity.

KEY POINTS

· Neighborhood social deprivation was not associated with composite maternal or neonatal morbidity.. · Community-level deprivation was associated with decreased PNC utilization.. · It is important to understand the underlying disparities that lend to suboptimal patterns of PNC.. · Doing so may inform programs that promote favorable birth outcomes in at-risk communities..

Socioeconomic disadvantage and racial/ethnic disparities in low-risk cesarean birth in California

Our objective was to assess the relationship of socioeconomic disadvantage and race/ethnicity with low-risk cesarean birth. We examined birth certificates (2007-2018) linked with maternal hospitalization data from California; the outcome was cesarean birth among low-risk deliveries (ie, nulliparous, term, singleton, vertex [NTSV]). We used generalized estimation equation Poisson regression with an interaction term for race/ethnicity (n = 7 groups) and a measure of socioeconomic disadvantage (census tract-level neighborhood deprivation index, education, or insurance). Among 1 815 933 NTSV births, 26.6% were by cesarean section. When assessing the joint effect of race/ethnicity and socioeconomic disadvantage among low-risk births, risk of cesarean birth increased with socioeconomic disadvantage for most racial/ethnic groups, and disadvantaged Black individuals had the highest risks. For example, Black individuals with a high school education or less had a risk ratio of 1.49 (95% CI, 1.45-1.53) relative to White individuals with a college degree. The disparity in risk of cesarean birth between Black and White individuals was observed across all strata of socioeconomic disadvantage. Asian American and Hispanic individuals had higher risks than White individuals at lower socioeconomic disadvantage; this disparity was not observed at higher levels of disadvantage. Black individuals have a persistent, elevated risk of cesarean birth relative to White individuals, regardless of socioeconomic disadvantage.

Enrichment of a Data Lake to Support Population Health Outcomes Studies Using Social Determinants Linked EHR Data

The integration of electronic health records (EHRs) with social determinants of health (SDoH) is crucial for population health outcome research, but it requires the collection of identifiable information and poses security risks. This study presents a framework for facilitating de-identified clinical data with privacy-preserved geocoded linked SDoH data in a Data Lake. A reidentification risk detection algorithm was also developed to evaluate the transmission risk of the data. The utility of this framework was demonstrated through one population health outcomes research analyzing the correlation between socioeconomic status and the risk of having chronic conditions. The results of this study inform the development of evidence-based interventions and support the use of this framework in understanding the complex relationships between SDoH and health outcomes. This framework reduces computational and administrative workload and security risks for researchers and preserves data privacy and enables rapid and reliable research on SDoH-connected clinical data for research institutes.

Association between Gentrification and Health and Healthcare Utilization

There is tremendous interest in understanding how neighborhoods impact health by linking extant social and environmental drivers of health (SDOH) data with electronic health record (EHR) data. Studies quantifying such associations often use static neighborhood measures. Little research examines the impact of gentrification-a measure of neighborhood change-on the health of long-term neighborhood residents using EHR data, which may have a more generalizable population than traditional approaches. We quantified associations between gentrification and health and healthcare utilization by linking longitudinal socioeconomic data from the American Community Survey with EHR data across two health systems accessed by long-term residents of Durham County, NC, from 2007 to 2017. Census block group-level neighborhoods were eligible to be gentrified if they had low socioeconomic status relative to the county average. Gentrification was defined using socioeconomic data from 2006 to 2010 and 2011-2015, with the Steinmetz-Wood definition. Multivariable logistic and Poisson regression models estimated associations between gentrification and development of health indicators (cardiovascular disease, hypertension, diabetes, obesity, asthma, depression) or healthcare encounters (emergency department [ED], inpatient, or outpatient). Sensitivity analyses examined two alternative gentrification measures. Of the 99 block groups within the city of Durham, 28 were eligible (N = 10,807; median age = 42; 83% Black; 55% female) and 5 gentrified. Individuals in gentrifying neighborhoods had lower odds of obesity (odds ratio [OR] = 0.89; 95% confidence interval [CI]: 0.81-0.99), higher odds of an ED encounter (OR = 1.10; 95% CI: 1.01-1.20), and lower risk for outpatient encounters (incidence rate ratio = 0.93; 95% CI: 0.87-1.00) compared with non-gentrifying neighborhoods. The association between gentrification and health and healthcare utilization was sensitive to gentrification definition.