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
To determine the major factors affecting the urinary levels of 2,4-dichlorophenoxyacetic acid (2,4-D) among county noxious weed applicators in Kansas, we used a regression technique that accounted for multiple days of exposure. We collected 136 12-h urine samples from 31 applicators during the course of two spraying seasons (April to August of 1994 and 1995). Using mixed-effects models, we constructed exposure models that related urinary 2,4-D measurements to weighted self-reported work activities from daily diaries collected over 5 to 7 days before the collection of the urine sample. Our primary weights were based on an earlier pharmacokinetic analysis of turf applicators; however, we examined a series of alternative weighting schemes to assess the impact of the specific weights and the number of days before urine sample collection that were considered. The derived models accounting for multiple days of exposure related to a single urine measurement seemed robust with regard to the exact weights, but less to the number of days considered; albeit the determinants from the primary model could be fitted with marginal losses of fit to the data from the other weighting schemes that considered a different numbers of days. In the primary model, the total time of all activities (spraying, mixing, other activities), spraying method, month of observation, application concentration, and wet gloves were significant determinants of urinary 2,4-D concentration and explained 16% of the between-worker variance and 23% of the within-worker variance of urinary 2,4-D levels. As a large proportion of the variance remained unexplained, further studies should be conducted to try to systematically assess other exposure determinants.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2823960 | PMC |
http://dx.doi.org/10.1038/jes.2009.14 | DOI Listing |
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