Literature DB >> 29957506

Associations between environmental quality and adult asthma prevalence in medical claims data.

Christine L Gray1, Danelle T Lobdell2, Kristen M Rappazzo3, Yun Jian4, Jyotsna S Jagai5, Lynne C Messer6, Achal P Patel7, Stephanie A DeFlorio-Barker8, Christopher Lyttle9, Julian Solway10, Andrey Rzhetsky11.   

Abstract

As of 2014, approximately 7.4% of U.S. adults had current asthma. The etiology of asthma is complex, involving genetics, behavior, and environmental factors. To explore the association between cumulative environmental quality and asthma prevalence in U.S. adults, we linked the U.S. Environmental Protection Agency's Environmental Quality Index (EQI) to the MarketScan® Commercial Claims and Encounters Database. The EQI is a summary measure of five environmental domains (air, water, land, built, sociodemographic). We defined asthma as having at least 2 claims during the study period, 2003-2013. We used a Bayesian approach with non-informative priors, implementing mixed-effects regression modeling with a Poisson link function. Fixed effects variables were EQI, sex, race, and age. Random effects were counties. We modeled quintiles of the EQI comparing higher quintiles (worse quality) to lowest quintile (best quality) to estimate prevalence ratios (PR) and credible intervals (CIs). We estimated associations using the cumulative EQI and domain-specific EQIs; we assessed U.S. overall (non-stratified) as well as stratified by rural-urban continuum codes (RUCC) to assess rural/urban heterogeneity. Among the 71,577,118 U.S. adults with medical claims who could be geocoded to county of residence, 1,147,564 (1.6%) met the asthma definition. Worse environmental quality was associated with increased asthma prevalence using the non-RUCC-stratified cumulative EQI, comparing the worst to best EQI quintile (PR:1.27; 95% CI: 1.21, 1.34). Patterns varied among different EQI domains, as well as by rural/urban status. Poor environmental quality may increase asthma prevalence, but domain-specific drivers may operate differently depending on rural/urban status. Published by Elsevier Inc.

Entities:  

Keywords:  Asthma; Bayesian; Claims; Environment; MarketScan

Mesh:

Year:  2018        PMID: 29957506      PMCID: PMC6110955          DOI: 10.1016/j.envres.2018.06.020

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   6.498


  44 in total

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8.  The associations between environmental quality and preterm birth in the United States, 2000-2005: a cross-sectional analysis.

Authors:  Kristen M Rappazzo; Lynne C Messer; Jyotsna S Jagai; Christine L Gray; Shannon C Grabich; Danelle T Lobdell
Journal:  Environ Health       Date:  2015-06-09       Impact factor: 5.984

9.  Statistical Approaches for Assessing Health Effects of Environmental Chemical Mixtures in Epidemiology: Lessons from an Innovative Workshop.

Authors:  Kyla W Taylor; Bonnie R Joubert; Joe M Braun; Caroline Dilworth; Chris Gennings; Russ Hauser; Jerry J Heindel; Cynthia V Rider; Thomas F Webster; Danielle J Carlin
Journal:  Environ Health Perspect       Date:  2016-12-01       Impact factor: 9.031

10.  Minimal difference in the prevalence of asthma in the urban and rural environment.

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  5 in total

1.  Associations between cumulative environmental quality and ten selected birth defects in Texas.

Authors:  Alison K Krajewski; Kristen M Rappazzo; Peter H Langlois; Lynne C Messer; Danelle T Lobdell
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Journal:  J Health Pollut       Date:  2020-02-28

3.  Trends and regional distribution of outpatient claims for asthma, 2009-2016, Germany.

Authors:  Manas K Akmatov; Jakob Holstiege; Annika Steffen; Jörg Bätzing
Journal:  Bull World Health Organ       Date:  2019-11-01       Impact factor: 9.408

4.  Comorbidity profile of patients with concurrent diagnoses of asthma and COPD in Germany.

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Journal:  Sci Rep       Date:  2020-10-21       Impact factor: 4.379

5.  A cross-sectional analysis of associations between environmental indices and asthma in U.S. counties from 2003 to 2012.

Authors:  Patrick Hurbain; Yan Liu; Matthew J Strickland; Dingsheng Li
Journal:  J Expo Sci Environ Epidemiol       Date:  2021-04-24       Impact factor: 5.563

  5 in total

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