Comparison of two different approaches for the analysis of data from a prospective cohort study: an application to work related risk factors for low back pain

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Abstract

AIMS: To compare the results of a traditional approach using standard regression for the analysis of data from a prospective cohort study with the results of generalised estimating equations (GEE) analysis.

METHODS: The research was part of a three year prospective cohort study on work related risk factors for low back pain. The study population consisted of a cohort of 1192 workers with no low back pain at baseline. Information on work related physical and psychosocial factors and the occurrence of low back pain was obtained by means of questionnaires at baseline and at the three annual follow up measurements. In a traditional standard logistic regression model, physical and psychosocial risk factors at baseline were related to the cumulative incidence of low back pain during the three year follow up period. In a GEE logistic model, repeated measurements of the physical and psychosocial risk factors were related to low back pain reported at one measurement point later.

RESULTS: The traditional standard regression model showed a significant effect of flexion and/or rotation of the upper part of the body (OR = 1.8; 95% CI: 1.2 to 3.0), but not of moving heavy loads (OR = 1.4; 95% CI: 0.7 to 3.1). The GEE model showed a significant effect of both flexion and/or rotation of the upper part of the body (OR = 2.2; 95% CI: 1.5 to 3.3) and moving heavy loads (OR = 1.5; 95% CI: 1.0 to 2.4). No significant associations with low back pain were found for the psychosocial work characteristics with either method, but the GEE model showed weaker odds ratios for these variables than the traditional standard regression model.

CONCLUSIONS: Results show that there are differences between the two analytical approaches in both the magnitude and the precision of the observed odds ratios.

Original languageEnglish
Pages (from-to)459-65
Number of pages7
JournalOccupational and Environmental Medicine
Volume59
Issue number7
Publication statusPublished - Jul 2002

Cite this

@article{544aff699a1b4908b7dba27b3977cc1e,
title = "Comparison of two different approaches for the analysis of data from a prospective cohort study: an application to work related risk factors for low back pain",
abstract = "AIMS: To compare the results of a traditional approach using standard regression for the analysis of data from a prospective cohort study with the results of generalised estimating equations (GEE) analysis.METHODS: The research was part of a three year prospective cohort study on work related risk factors for low back pain. The study population consisted of a cohort of 1192 workers with no low back pain at baseline. Information on work related physical and psychosocial factors and the occurrence of low back pain was obtained by means of questionnaires at baseline and at the three annual follow up measurements. In a traditional standard logistic regression model, physical and psychosocial risk factors at baseline were related to the cumulative incidence of low back pain during the three year follow up period. In a GEE logistic model, repeated measurements of the physical and psychosocial risk factors were related to low back pain reported at one measurement point later.RESULTS: The traditional standard regression model showed a significant effect of flexion and/or rotation of the upper part of the body (OR = 1.8; 95{\%} CI: 1.2 to 3.0), but not of moving heavy loads (OR = 1.4; 95{\%} CI: 0.7 to 3.1). The GEE model showed a significant effect of both flexion and/or rotation of the upper part of the body (OR = 2.2; 95{\%} CI: 1.5 to 3.3) and moving heavy loads (OR = 1.5; 95{\%} CI: 1.0 to 2.4). No significant associations with low back pain were found for the psychosocial work characteristics with either method, but the GEE model showed weaker odds ratios for these variables than the traditional standard regression model.CONCLUSIONS: Results show that there are differences between the two analytical approaches in both the magnitude and the precision of the observed odds ratios.",
keywords = "Follow-Up Studies, Humans, Logistic Models, Low Back Pain/etiology, Occupational Diseases/etiology, Odds Ratio, Prospective Studies, Risk Factors, Surveys and Questionnaires",
author = "Hoogendoorn, {W E} and Bongers, {P M} and {de Vet}, {H C W} and Twisk, {J W R} and {van Mechelen}, W and Bouter, {L M}",
year = "2002",
month = "7",
language = "English",
volume = "59",
pages = "459--65",
journal = "Occupational and Environmental Medicine",
issn = "1351-0711",
publisher = "BMJ Publishing Group",
number = "7",

}

TY - JOUR

T1 - Comparison of two different approaches for the analysis of data from a prospective cohort study

T2 - an application to work related risk factors for low back pain

AU - Hoogendoorn, W E

AU - Bongers, P M

AU - de Vet, H C W

AU - Twisk, J W R

AU - van Mechelen, W

AU - Bouter, L M

PY - 2002/7

Y1 - 2002/7

N2 - AIMS: To compare the results of a traditional approach using standard regression for the analysis of data from a prospective cohort study with the results of generalised estimating equations (GEE) analysis.METHODS: The research was part of a three year prospective cohort study on work related risk factors for low back pain. The study population consisted of a cohort of 1192 workers with no low back pain at baseline. Information on work related physical and psychosocial factors and the occurrence of low back pain was obtained by means of questionnaires at baseline and at the three annual follow up measurements. In a traditional standard logistic regression model, physical and psychosocial risk factors at baseline were related to the cumulative incidence of low back pain during the three year follow up period. In a GEE logistic model, repeated measurements of the physical and psychosocial risk factors were related to low back pain reported at one measurement point later.RESULTS: The traditional standard regression model showed a significant effect of flexion and/or rotation of the upper part of the body (OR = 1.8; 95% CI: 1.2 to 3.0), but not of moving heavy loads (OR = 1.4; 95% CI: 0.7 to 3.1). The GEE model showed a significant effect of both flexion and/or rotation of the upper part of the body (OR = 2.2; 95% CI: 1.5 to 3.3) and moving heavy loads (OR = 1.5; 95% CI: 1.0 to 2.4). No significant associations with low back pain were found for the psychosocial work characteristics with either method, but the GEE model showed weaker odds ratios for these variables than the traditional standard regression model.CONCLUSIONS: Results show that there are differences between the two analytical approaches in both the magnitude and the precision of the observed odds ratios.

AB - AIMS: To compare the results of a traditional approach using standard regression for the analysis of data from a prospective cohort study with the results of generalised estimating equations (GEE) analysis.METHODS: The research was part of a three year prospective cohort study on work related risk factors for low back pain. The study population consisted of a cohort of 1192 workers with no low back pain at baseline. Information on work related physical and psychosocial factors and the occurrence of low back pain was obtained by means of questionnaires at baseline and at the three annual follow up measurements. In a traditional standard logistic regression model, physical and psychosocial risk factors at baseline were related to the cumulative incidence of low back pain during the three year follow up period. In a GEE logistic model, repeated measurements of the physical and psychosocial risk factors were related to low back pain reported at one measurement point later.RESULTS: The traditional standard regression model showed a significant effect of flexion and/or rotation of the upper part of the body (OR = 1.8; 95% CI: 1.2 to 3.0), but not of moving heavy loads (OR = 1.4; 95% CI: 0.7 to 3.1). The GEE model showed a significant effect of both flexion and/or rotation of the upper part of the body (OR = 2.2; 95% CI: 1.5 to 3.3) and moving heavy loads (OR = 1.5; 95% CI: 1.0 to 2.4). No significant associations with low back pain were found for the psychosocial work characteristics with either method, but the GEE model showed weaker odds ratios for these variables than the traditional standard regression model.CONCLUSIONS: Results show that there are differences between the two analytical approaches in both the magnitude and the precision of the observed odds ratios.

KW - Follow-Up Studies

KW - Humans

KW - Logistic Models

KW - Low Back Pain/etiology

KW - Occupational Diseases/etiology

KW - Odds Ratio

KW - Prospective Studies

KW - Risk Factors

KW - Surveys and Questionnaires

M3 - Article

VL - 59

SP - 459

EP - 465

JO - Occupational and Environmental Medicine

JF - Occupational and Environmental Medicine

SN - 1351-0711

IS - 7

ER -