Asthma Ambulatory Care Quality in Foreign-Born Latino Children in the United States

How Schools Can Help Address Social Determinants of Health in Asthma Management

Schools are in a unique position to address social determinants of health (SDOHs) in pediatric asthma management because of their potential to provide resources and facilitate collaboration with health care providers and services for children at risk within their community. SDOHs include economic factors, educational attainment and health literacy, neighborhood factors and the built environment, social and community aspects including discrimination and racism, and health care access and quality. These factors have a significant impact on asthma health in children, and certain populations such as minoritzed populations and those living in high-poverty environments have been shown to be at greater risk for adverse effects of SDOHs on asthma outcomes. School-based asthma programs address several SDOHs including health literacy, the built environment, and health care quality and access and have been shown to improve asthma outcomes. Key components include connection between the school and the health care team, self-management education, and directly observed therapy. School nurses play a key role in directing and managing effective programs because they can evaluate and support a student's health while considering the effect of SDOHs at interpersonal, institutional, community, and policy levels.

Latino Adolescent-Mother Language Concordance, Neighborhood Deprivation, and Vaccinations in Community Health Centers

INTRODUCTION

Latino adolescents may face numerous barriers) to recommended vaccinations. There is little research on the association between Latino adolescent-mother preferred language concordance and vaccination completion and if it varies by neighborhood. To better understand the social/family factors associated with Latino adolescent vaccination, we studied the association of adolescent-mother language concordance and neighborhood social deprivation with adolescent vaccination completion.

METHODS

We employed a multistate, electronic health record (EHR) based dataset of community health center patients to compare three Latino groups: (1) English-preferring adolescents with English-preferring mothers, (2) Spanish-preferring adolescents with Spanish-preferring mothers, and (3) English-preferring adolescents with Spanish-preferring mothers with non-Hispanic white adolescent-mother pairs for human papilloma virus (HPV), meningococcal, and influenza vaccinations. We adjusted for mother and adolescent demographics and care utilization and stratified by the social deprivation of the family's neighborhood.

RESULTS

Our sample included 56,542 adolescent-mother dyads. Compared with non-Hispanic white dyads, all three groups of Latino dyads had higher odds of adolescent HPV and meningococcal vaccines and higher rates of flu vaccines. Latino dyads with Spanish-preferring mothers had higher vaccination odds/rates than Latino dyads with English-preferring mothers. The effects of variation by neighborhood social deprivation in influenza vaccination rates were minor in comparison to differences by ethnicity/language concordance.

CONCLUSION

In a multistate analysis of vaccinations among Latino and non-Latino adolescents, English-preferring adolescents with Spanish-preferring mothers had the highest completion rates and English-preferring non-Hispanic white dyads the lowest. Further research can seek to understand why this language dyad may have an advantage in adolescent vaccination completion.

Disaggregating Latino nativity in equity research using electronic health records

OBJECTIVE

To develop and validate prediction models for inference of Latino nativity to advance health equity research.

DATA SOURCES/STUDY SETTING

This study used electronic health records (EHRs) from 19,985 Latino children with self-reported country of birth seeking care from January 1, 2012 to December 31, 2018 at 456 community health centers (CHCs) across 15 states along with census-tract geocoded neighborhood composition and surname data.

STUDY DESIGN

We constructed and evaluated the performance of prediction models within a broad machine learning framework (Super Learner) for the estimation of Latino nativity. Outcomes included binary indicators denoting nativity (US vs. foreign-born) and Latino country of birth (Mexican, Cuban, Guatemalan). The performance of these models was compared using the area under the receiver operating characteristics curve (AUC) from an externally withheld patient sample.

DATA COLLECTION/EXTRACTION METHODS

Census surname lists, census neighborhood composition, and Forebears administrative data were linked to EHR data.

PRINCIPAL FINDINGS

Of the 19,985 Latino patients, 10.7% reported a non-US country of birth (5.1% Mexican, 4.7% Guatemalan, 0.8% Cuban). Overall, prediction models for nativity showed outstanding performance with external validation (US-born vs. foreign: AUC = 0.90; Mexican vs. non-Mexican: AUC = 0.89; Guatemalan vs. non-Guatemalan: AUC = 0.95; Cuban vs. non-Cuban: AUC = 0.99).

CONCLUSIONS

Among challenges facing health equity researchers in health services is the absence of methods for data disaggregation, and the specific ability to determine Latino country of birth (nativity) to inform disparities. Recent interest in more robust health equity research has called attention to the importance of data disaggregation. In a multistate network of CHCs using multilevel inputs from EHR data linked to surname and community data, we developed and validated novel prediction models for the use of available EHR data to infer Latino nativity for health disparities research in primary care and health services research, which is a significant potential methodologic advance in studying this population.