Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts

Objectives: Exposure–outcome studies, for instance on work-related low-back pain (LBP), often classify workers into groups for which exposures are estimated from measurements on a sample of workers within or outside the specific study. The present study investigated the influence on bias and power i...

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Main Authors: Coenen, Pieter, Mathiassen, S., Kingma, I., Boot, C., Bongers, P., Van Dieën, J.
Format: Journal Article
Published: Oxford University Press 2015
Online Access:http://hdl.handle.net/20.500.11937/32510
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author Coenen, Pieter
Mathiassen, S.
Kingma, I.
Boot, C.
Bongers, P.
Van Dieën, J.
author_facet Coenen, Pieter
Mathiassen, S.
Kingma, I.
Boot, C.
Bongers, P.
Van Dieën, J.
author_sort Coenen, Pieter
building Curtin Institutional Repository
collection Online Access
description Objectives: Exposure–outcome studies, for instance on work-related low-back pain (LBP), often classify workers into groups for which exposures are estimated from measurements on a sample of workers within or outside the specific study. The present study investigated the influence on bias and power in exposure–outcome associations of the sizes of the total study population and the sample used to estimate exposures. Methods: At baseline, lifting, trunk flexion, and trunk rotation were observed for 371 of 1131 workers allocated to 19 a-priori defined occupational groups. LBP (dichotomous) was reported by all workers during 3 years of follow-up. All three exposures were associated with LBP in this parent study (P < 0.01). All 21 combinations of n = 10, 20, 30 workers per group with an outcome, and k = 1, 2, 3, 5, 10, 15, 20 workers actually being observed were investigated using bootstrapping, repeating each combination 10000 times. Odds ratios (OR) with P values were determined for each of these virtual studies. Average OR and statistical power (P < 0.05 and P < 0.01) was determined from the bootstrap distributions at each (n, k) combination. Results: For lifting and flexed trunk, studies including n ≥ 20 workers, with k ≥ 5 observed, led to an almost unbiased OR and a power >0.80 (P level = 0.05). A similar performance required n ≥ 30 workers for rotated trunk. Small numbers of observed workers (k) resulted in biased OR, while power was, in general, more sensitive to the total number of workers (n). Conclusions: In epidemiologic studies using a group-based exposure assessment strategy, statistical performance may be sufficient if outcome is obtained from a reasonably large number of workers, even if exposure is estimated from only few workers per group.
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spelling curtin-20.500.11937-325102023-02-22T06:24:15Z Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts Coenen, Pieter Mathiassen, S. Kingma, I. Boot, C. Bongers, P. Van Dieën, J. Objectives: Exposure–outcome studies, for instance on work-related low-back pain (LBP), often classify workers into groups for which exposures are estimated from measurements on a sample of workers within or outside the specific study. The present study investigated the influence on bias and power in exposure–outcome associations of the sizes of the total study population and the sample used to estimate exposures. Methods: At baseline, lifting, trunk flexion, and trunk rotation were observed for 371 of 1131 workers allocated to 19 a-priori defined occupational groups. LBP (dichotomous) was reported by all workers during 3 years of follow-up. All three exposures were associated with LBP in this parent study (P < 0.01). All 21 combinations of n = 10, 20, 30 workers per group with an outcome, and k = 1, 2, 3, 5, 10, 15, 20 workers actually being observed were investigated using bootstrapping, repeating each combination 10000 times. Odds ratios (OR) with P values were determined for each of these virtual studies. Average OR and statistical power (P < 0.05 and P < 0.01) was determined from the bootstrap distributions at each (n, k) combination. Results: For lifting and flexed trunk, studies including n ≥ 20 workers, with k ≥ 5 observed, led to an almost unbiased OR and a power >0.80 (P level = 0.05). A similar performance required n ≥ 30 workers for rotated trunk. Small numbers of observed workers (k) resulted in biased OR, while power was, in general, more sensitive to the total number of workers (n). Conclusions: In epidemiologic studies using a group-based exposure assessment strategy, statistical performance may be sufficient if outcome is obtained from a reasonably large number of workers, even if exposure is estimated from only few workers per group. 2015 Journal Article http://hdl.handle.net/20.500.11937/32510 10.1093/annhyg/meu102 Oxford University Press unknown
spellingShingle Coenen, Pieter
Mathiassen, S.
Kingma, I.
Boot, C.
Bongers, P.
Van Dieën, J.
Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts
title Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts
title_full Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts
title_fullStr Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts
title_full_unstemmed Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts
title_short Bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: Effects of study size and exposure measurement efforts
title_sort bias and power in group-based epidemiologic studies of low-back pain exposure and outcome: effects of study size and exposure measurement efforts
url http://hdl.handle.net/20.500.11937/32510