Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
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.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110955 | PMC |
http://dx.doi.org/10.1016/j.envres.2018.06.020 | DOI Listing |
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