The effect of the presence and characteristics of an outlying group on exposure-outcome associations

Abstract

Objectives Physical exposures (eg, lifting or bending) are believed to be risk factors for low-back pain (LBP), but the literature is inconsistent. Exposure and LBP prevalence differ considerably between occupations, and exposure–outcome associations could be severely modified by the presence of particular occupational groups. We aimed to investigate the influence of such outlying groups on the properties of associations between exposure and LBP.Methods Lifting and trunk flexion were observed for 371 of 1131 workers within 19 groups. LBP was obtained from all workers during three follow-up years. Both exposure variables were associated with LBP (P<0.01) in this parent dataset. By removing the 19 groups one-by-one and performing logistic regressions analysis on the 18 remaining groups, we demonstrated that one group, mainly road workers, with outlying exposures and LBP prevalence substantially affected the exposure–outcome association in the total population. In order to further examine this phenomenon, we assessed, by simulation, the influence of realistic sizes (n=4, 8, 16, 32, 64, 128), mean exposures (e=2000, 3000, 4000 lifts and e=30, 40, 50% trunk flexion time) and LBP prevalences (p=70, 80, 90, 100%) of the outlying group on the strength and certainty of the eventual relationship between exposure and LBP.For each combination of n, e and p, 3000 virtual studies were constructed, including the simulated group together with the other 18 original groups from the parent data-set. Average odds ratios (OR), 95% confidence limits, and power (P<0.05) were calculated across these 3000 studies as measures of the properties of each virtual study design.Results OR were attenuated more towards 1 and power decreased with smaller values of n, e, and p in the outlying group. Changes in group size and prevalence had a larger influence on OR and power than changes in mean exposure.Conclusions The size and characteristics of a single group with high exposure and outcome prevalence can strongly influence both the OR point estimate and the likelihood of obtaining significant exposure–outcome associations in studies of large populations. These findings can guide interpretations of prior epidemiological studies and support informed design of future studies.