A distributed geospatial approach to describe community characteristics for multisite studies

Ryan, Patrick; Brokamp, Cole; Blossom, Jeff; Lothrop, Nathan; Miller, Rachel L.; Beamer, Paloma I.; Visness, Cynthia M.; Zanobetti, Antonella; Andrews, Howard; Bacharier, Leonard B.; Hartert, Tina V.; Johnson, Christine Cole; Ownby, Dennis R.; Lemanske, Robert F.; Gibson, Heike; Réquia, Weeberb J.; Coull, Brent A.; Zoratti, Edward M.; Wright, Anne L.; Martínez, Fernando D.; Seroogy, Christine M.; Gern, James E.; Gold, Diane R.

doi:10.1017/cts.2021.7

Cited by 4 publications

(7 citation statements)

References 23 publications

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“…Similar variability has been previously shown in the census factors across all cohorts. 9 eFigure 2 in Supplement 1 shows the distribution of child's race and ethnicity by categories of neighborhood characteristics. In tracts with low proportions of the population below the poverty level, 83% of the children were White; in tracts with high proportions of the population below the poverty level, 49% of the children were Black and 35% Hispanic, while only 13% were White.…”

Section: Resultsmentioning

confidence: 99%

“…decades with attention to longitudinal comparability of income, poverty, and geographic boundaries. 9 Our De-GAUSS approach enabled cohort data managers to assign census information to birth record addresses in a decentralized manner, preserving protections for the participants.…”

Section: Discussionmentioning

confidence: 99%

“…Briefly, US Census data including population density (population per kilometer squared), median household income, percentage below poverty level (percentage of individuals in tract whose income is below the federal poverty level), percentage of low-income households (income <$7500, $12 500, $20 000, and $25 000 for census years 1980, 1990, 2000, and 2010, respectively), percentage without high school diploma, percentage occupied housing, median gross rent, median housing value, percentage with a female head of household, percentage with a single-parent head of household, and percentage unemployed. Boundary files for the years 1980, 1990, 2000, and 2010 were provided along with R code in a Docker container to each cohort . Cohort data managers merged census data to participant birth address using census year nearest to the birth year and then removed identifiable information.…”

Section: Methodsmentioning

confidence: 99%

“…We ascertained census tract-level information for all CREW participants at their birth address using our previously described Decentralized Geomarker Assessment for Multi-site Studies (DeGAUSS) approach. 9 Briefly, US Census data including population density (population per kilometer squared), median household income, percentage below poverty level (percentage of individuals in tract whose income is below the federal poverty level), percentage of low-income households (income <$7500, $12 500, $20 000, and $25 000 for census years 1980, 1990, 2000, and 2010, respectively), percentage without high school diploma, percentage occupied housing, median gross rent, median housing value, percentage with a female head of household, percentage with a single-parent head of household, and percentage unemployed. Boundary files for the years 1980, 1990, 2000, and 2010 were provided along with R code in a Docker container to each cohort.…”

Section: Neighborhood Socioeconomic Factorsmentioning

confidence: 99%

“…Boundary files for the years 1980, 1990, 2000, and 2010 were provided along with R code in a Docker container to each cohort. 9 Cohort data managers merged census data to participant birth address using census year nearest to the birth year and then removed identifiable information.…”

Section: Neighborhood Socioeconomic Factorsmentioning

confidence: 99%

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Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

et al. 2022

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IMPORTANCEIn the United States, Black and Hispanic children have higher rates of asthma and asthma-related morbidity compared with White children and disproportionately reside in communities with economic deprivation.OBJECTIVE To determine the extent to which neighborhood-level socioeconomic indicators explain racial and ethnic disparities in childhood wheezing and asthma. DESIGN, SETTING, AND PARTICIPANTSThe study population comprised children in birth cohorts located throughout the United States that are part of the Children's Respiratory and Environmental Workgroup consortium. Cox proportional hazard models were used to estimate hazard ratios (HRs) of asthma incidence, and logistic regression was used to estimate odds ratios of early and persistent wheeze prevalence accounting for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, and region and decade of birth.EXPOSURES Neighborhood-level socioeconomic indicators defined by US census tracts calculated as z scores for multiple tract-level variables relative to the US average linked to participants' birth record address and decade of birth. The parent or caregiver reported the child's race and ethnicity.MAIN OUTCOMES AND MEASURES Prevalence of early and persistent childhood wheeze and asthma incidence. RESULTSOf 5809 children, 46% reported wheezing before age 2 years, and 26% reported persistent wheeze through age 11 years. Asthma prevalence by age 11 years varied by cohort, with an overall median prevalence of 25%. Black children (HR, 1.47; 95% CI, and Hispanic children (HR, 1.29; 95% CI, 1.09-1.53) were at significantly increased risk for asthma incidence compared with White children, with onset occurring earlier in childhood. Children born in tracts with a greater proportion of low-income households, population density, and poverty had increased asthma incidence. Results for early and persistent wheeze were similar. In effect modification analysis, census variables did not significantly modify the association between race and ethnicity and risk for asthma incidence; Black and Hispanic children remained at higher risk for asthma compared with White children across census tracts socioeconomic levels. CONCLUSIONS AND RELEVANCEAdjusting for individual-level characteristics, we observed neighborhood socioeconomic disparities in childhood wheeze and asthma. Black and Hispanic children had more asthma in neighborhoods of all income levels. Neighborhood-and individual-level characteristics and their root causes should be considered as sources of respiratory health inequities.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Neighborhood Socioeconomic Factorsmentioning

confidence: 99%

Section: Neighborhood Socioeconomic Factorsmentioning

confidence: 99%

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Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

et al. 2022

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High Resolution and Spatiotemporal Place-Based Computable Exposures at Scale

Rasnick

Ryan

Vancil

et al. 2022

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Hospital Access Patterns of Children With Technology Dependence

et al. 2023

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OBJECTIVES We studied hospital utilization patterns among children with technology dependence (CTD). We hypothesized that increasing pediatric healthcare concentration requires those caring for CTD to selectively navigate healthcare systems and travel greater distances for care. METHODS Using 2017 all-encounter datasets from 6 US states, we identified CTD visits defined by presence of a tracheostomy, gastrostomy, or intraventricular shunt. We calculated pediatric Hospital Capability Indices for hospitals and mapped distances between patient residence, nearest hospital, and encounter facility. RESULTS Thirty-five percent of hospitals never saw CTD. Of 37 108 CTD encounters within the remaining 543 hospitals, most emergency visits (70.0%) and inpatient admissions (85.3%) occurred within 34 (6.3%) high capability centers. Only 11.7% of visits were to the closest facility, as CTD traveled almost 4 times further to receive care. When CTD bypassed nearer facilities, they were 10 times more likely to travel to high-capability centers (95% confidence interval: 9.43–10.8), but even those accessing low-capability facilities bypassed less capable, geographically closer hospitals. Transfer was more likely in nearest and low-capability facility encounters. CTD with Medicaid insurance, Black race, or from lower socioeconomic communities had lower odds of encounters at high-capability centers and of bypassing a closer institution than those with white race, private insurance, or from advantaged communities. CONCLUSIONS Children with technology dependence routinely bypass closer hospitals to access care in facilities with higher pediatric capability. This access behavior leaves many hospitals unfamiliar with CTD, which results in greater travel but less transfers and may be influenced by sociodemographic factors.

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A distributed geospatial approach to describe community characteristics for multisite studies

Cited by 4 publications

References 23 publications

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

Childhood Asthma Incidence, Early and Persistent Wheeze, and Neighborhood Socioeconomic Factors in the ECHO/CREW Consortium

High Resolution and Spatiotemporal Place-Based Computable Exposures at Scale

Hospital Access Patterns of Children With Technology Dependence

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