The size of exposure variability in the three groups differed in a similar fashion; the car mechanics showed more variability than the machinists did, but less than the house painters did.
We have not been able to identify any data or studies with regression analyses of changes in pain corresponding to a certain amount of work time spent with one activity to guide our estimation of the effect size of exposure on pain.
While a wide variety of confounding factors have been considered in the study, there may still be residual confounding present, resulting in distortions in the estimated effect size of exposures.
Relevant data included the first author's last name, publication year, year of the study conducted, study design, study location, source population, sample size (cases and controls or cohort size), measure of exposure and outcome, length of follow-up (if applicable), variables adjusted in the analysis, and the risk estimates with corresponding 95% CIs.
Therefore, this study aims to quantify the effect sizes of SHS exposure for three major outcomes: IHD, COPD, and stroke.
Our statistical power to detect small (0.02), medium (0.15), or large (0.35) effect sizes of phytoestrogen exposure on ovary development was 0.05, 0.13, and 0.58, respectively.
Our statistical power to detect small (0.02), medium (0.15), or large (0.35) effect sizes of phytoestrogen exposure on endogenous testosterone was 0.05, 0.16, and 0.71, respectively, while our power to detect effect sizes for estrogen were 0.05, 0.17, and 0.74.
This would lead to an underestimation of the effect sizes of pesticide exposure on depression, especially in those with an HPEE or pesticide poisoning, where the effects appear to be greater.
Even though the effect sizes of our exposure variables were not dramatic, variations within the normal range were associated with mortality increases on the order of 15%, and for those highly exposed this mortality increase was as high as 30%.
