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
Objective: The purpose of this study was to evaluate grouping schemes for exposure to total dust in cement industry workers using non-repeated measurement data.
Methods: In total, 2370 total dust measurements taken from nine Portland cement factories in 1995-2009 were analyzed. Various grouping schemes were generated based on work process, job, factory, or average exposure. To characterize variance components of each grouping scheme, we developed mixed-effects models with a B-spline time trend incorporated as fixed effects and a grouping variable incorporated as a random effect. Using the estimated variance components, elasticity was calculated. To compare the prediction performances of different grouping schemes, 10-fold cross-validation tests were conducted, and root mean squared errors and pooled correlation coefficients were calculated for each grouping scheme.
Results: The five exposure groups created a posteriori by ranking job and factory combinations according to average dust exposure showed the best prediction performance and highest elasticity among various grouping schemes.
Conclusion: Our findings suggest a grouping method based on ranking of job, and factory combinations would be the optimal choice in this population. Our grouping method may aid exposure assessment efforts in similar occupational settings, minimizing the misclassification of exposures.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1093/annhyg/mev033 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!