Skip directly to search Skip directly to A to Z list Skip directly to page options Skip directly to site content

NIOSHTIC-2 Publications Search

Search Results

Detecting patterns of occupational illness clustering with alternating logistic regressions applied to longitudinal data.

Authors
Preisser-JS; Arcury-TA; Quandt-SA
Source
Am J Epidemiol 2003 Sep; 158(5):495-501
NIOSHTIC No.
20029230
Abstract
In longitudinal surveillance studies of occupational illnesses, sickness episodes are recorded for workers over time. Since observations on the same worker are typically more similar than observations from different workers, statistical analysis must take into account the intraworker association due to workers' repeated measures. Additionally, when workers are employed in groups or clusters, observations from workers in the same workplace are typically more similar than observations from workers in different workplaces. For such cluster-correlated longitudinal data, alternating logistic regressions may be used to model the pattern of occupational illness clustering. Data on 182 Latino farm workers from a 1999 North Carolina study on green tobacco sickness provided an estimated pairwise odds ratio for within-worker clustering of 3.15 (95% confidence interval (CI): 1.84, 5.41) and an estimated pairwise odds ratio for within-camp clustering of 1.90 (95% CI: 1.22, 2.97). After adjustment for risk factors, the estimated pairwise odds ratios were 2.13 (95% CI: 1.18, 3.86) and 1.41 (95% CI: 0.89, 2.24), respectively. In this paper, a comparative analysis of alternating logistic regressions with generalized estimating equations and random-effects logistic regression is presented, and the relative strengths of the three methods are discussed.
Keywords
Statistical-analysis; Occupational-health; Workers; Worker-health; Farmers; Agriculture; Agricultural-workers; Agricultural-industry; Occupational-diseases; Demographic-characteristics; Racial-factors; Models; Tobacco; Occupational-exposure; Risk-factors
CODEN
AJEPAS
CAS No.
54-11-5
Publication Date
20030901
Document Type
Journal Article
Email Address
jpreisse@bios.unc.edu
Funding Amount
891533
Funding Type
Grant
Fiscal Year
2003
NTIS Accession No.
NTIS Price
Identifying No.
Grant-Number-R01-OH-003648
Issue of Publication
5
ISSN
0002-9262
Priority Area
Work Environment and Workforce: Special Populations
Source Name
American Journal of Epidemiology
State
NC
Performing Organization
Wake Forest University, Winston-Salem, North Carolina
TOP