Literature DB >> 28181157

Comprehensive Neighborhood Portraits and Child Asthma Disparities.

Ashley W Kranjac1, Rachel T Kimbro2, Justin T Denney2, Kristin M Osiecki3, Brady S Moffett4, Keila N Lopez4.   

Abstract

Objectives Previous research has established links between child, family, and neighborhood disadvantages and child asthma. We add to this literature by first characterizing neighborhoods in Houston, TX by demographic, economic, and air quality characteristics to establish differences in pediatric asthma diagnoses across neighborhoods. Second, we identify the relative risk of social, economic, and environmental risk factors for child asthma diagnoses. Methods We geocoded and linked electronic pediatric medical records to neighborhood-level social and economic indicators. Using latent profile modeling techniques, we identified Advantaged, Middle-class, and Disadvantaged neighborhoods. We then used a modified version of the Blinder-Oaxaca regression decomposition method to examine differences in asthma diagnoses across children in these different neighborhoods. Results Both compositional (the characteristics of the children and the ambient air quality in the neighborhood) and associational (the relationship between child and air quality characteristics and asthma) differences within the distinctive neighborhood contexts influence asthma outcomes. For example, unequal exposure to PM2.5 and O3 among children in Disadvantaged and Middle-class neighborhoods contribute to asthma diagnosis disparities within these contexts. For children in Disadvantaged and Advantaged neighborhoods, associational differences between racial/ethnic and socioeconomic characteristics and asthma diagnoses explain a significant proportion of the gap. Conclusions for Practice Our results provide evidence that differential exposure to pollution and protective factors associated with non-Hispanic White children and children from affluent families contribute to asthma disparities between neighborhoods. Future researchers should consider social and racial inequalities as more proximate drivers, not merely as associated, with asthma disparities in children.

Entities:  

Keywords:  Asthma; Children and youth; Environmental quality; Neighborhood disadvantage; Quantitative analysis

Mesh:

Substances:

Year:  2017        PMID: 28181157      PMCID: PMC6707800          DOI: 10.1007/s10995-017-2286-z

Source DB:  PubMed          Journal:  Matern Child Health J        ISSN: 1092-7875


  31 in total

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Authors:  Robert J Sampson
Journal:  AJS       Date:  2008-07

Review 2.  Maternal stress and T-cell differentiation of the developing immune system: possible implications for the development of asthma and atopy.

Authors:  Leena C von Hertzen
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Review 3.  Health effects of fine particulate air pollution: lines that connect.

Authors:  C Arden Pope; Douglas W Dockery
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Authors:  Waltraud Eder; Markus J Ege; Erika von Mutius
Journal:  N Engl J Med       Date:  2006-11-23       Impact factor: 91.245

5.  Racial and ethnic differences in asthma diagnosis among children who wheeze.

Authors:  Lara J Akinbami; Julia C Rhodes; Marielena Lara
Journal:  Pediatrics       Date:  2005-05       Impact factor: 7.124

6.  An exploration of the complex relationship of socioecologic factors in the treatment and outcomes of acute myocardial infarction in disadvantaged populations.

Authors:  J J Shen; T T Wan; J B Perlin
Journal:  Health Serv Res       Date:  2001-08       Impact factor: 3.402

Review 7.  Respiratory effects of air pollution on children.

Authors:  Fiona C Goldizen; Peter D Sly; Luke D Knibbs
Journal:  Pediatr Pulmonol       Date:  2015-07-24

8.  Socioeconomic status in childhood asthma.

Authors:  E A Mitchell; A W Stewart; P K Pattemore; M I Asher; A C Harrison; H H Rea
Journal:  Int J Epidemiol       Date:  1989-12       Impact factor: 7.196

9.  Neighborhood socioeconomic status, Medicaid coverage and medical management of myocardial infarction: atherosclerosis risk in communities (ARIC) community surveillance.

Authors:  Randi E Foraker; Kathryn M Rose; Eric A Whitsel; Chirayath M Suchindran; Joy L Wood; Wayne D Rosamond
Journal:  BMC Public Health       Date:  2010-10-21       Impact factor: 3.295

Review 10.  Possible molecular mechanisms linking air pollution and asthma in children.

Authors:  Susanna Esposito; Rossana Tenconi; Mara Lelii; Valentina Preti; Erica Nazzari; Silvia Consolo; Maria Francesca Patria
Journal:  BMC Pulm Med       Date:  2014-03-01       Impact factor: 3.317

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  5 in total

Review 1.  Ambient Air Pollution and Asthma-Related Outcomes in Children of Color of the USA: a Scoping Review of Literature Published Between 2013 and 2017.

Authors:  Anthony Nardone; Andreas M Neophytou; John Balmes; Neeta Thakur
Journal:  Curr Allergy Asthma Rep       Date:  2018-04-16       Impact factor: 4.806

2.  Association Between Neighborhood Disadvantage and Pediatric Readmissions.

Authors:  Carrie L Nacht; Michelle M Kelly; M Bruce Edmonson; Daniel J Sklansky; Kristin A Shadman; Amy J H Kind; Qianqian Zhao; Christina B Barreda; Ryan J Coller
Journal:  Matern Child Health J       Date:  2022-01-11

3.  Social and Environmental Neighborhood Typologies and Lung Function in a Low-Income, Urban Population.

Authors:  Jamie L Humphrey; Megan Lindstrom; Kelsey E Barton; Prateek Man Shrestha; Elizabeth J Carlton; John L Adgate; Shelly L Miller; Elisabeth Dowling Root
Journal:  Int J Environ Res Public Health       Date:  2019-03-29       Impact factor: 3.390

Review 4.  Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review.

Authors:  Elizabeth Golembiewski; Katie S Allen; Amber M Blackmon; Rachel J Hinrichs; Joshua R Vest
Journal:  JMIR Public Health Surveill       Date:  2019-10-07

5.  A geographic identifier assignment algorithm with Bayesian variable selection to identify neighborhood factors associated with emergency department visit disparities for asthma.

Authors:  Matthew Bozigar; Andrew Lawson; John Pearce; Kathryn King; Erik Svendsen
Journal:  Int J Health Geogr       Date:  2020-03-18       Impact factor: 3.918

  5 in total

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