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Even though we did not find statistical association with health care workers and history of imprisonment; we forced them into the model, because these variables have been associated with resistant TB [18], [19], [20], [21], [22], [23], [24].
This may be partly because these variables have been confounded with the type of event being remembered.
Here we present results from abnormal white matter and total gray matter volume because these variables have previously been associated with diabetes (2– 8).
Randomization is conducted centrally by an independent statistician, in blocks of two, stratified for tumour site (LC vs. HNC) and stage (stage I-II vs. III-IV), because these variables have prognostic relevance and need to be distributed evenly across both conditions.
While this could suggest that the diseases considered are not on the causal pathway between smoking and outcome, the lack of attenuation could be because these variables have not adequately captured disease history or because they were derived using history of ever having these conditions and thus do not capture smoking-induced incident disease.
Total fat, n-6 polyunsaturated fatty acids (PUFAs), wine and fermented milk were also examined as potential confounders because these variables have been associated with breast cancer risk in previous studies in the MDC cohort (Wirfält et al, 2002a; Mattisson et al, 2003b; Wirfält et al, 2003).
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The latest DWECS was chosen because it contains better measures of psychosocial work variables than earlier additions and because we have data showing that these variables have been stable over our study period [ 39].
This is because these variables had gender and age differences, while being significantly associated with QOL.
The variations we observed in the expression of the parity signature by ER status are unlikely to have been driven by age, age at first birth or years since most recent birth, because these variables had similar distributions in the ER + and ER - cases evaluated.
Although we were able to adjust for most of the known risk factors of breast cancer, we were not able to correct the results for physical activity and oral contraceptive use because these variables had a large number of missing values.
Lepp et al. (2015: 7) argue that more research is needed in these topics because relationship between these variables has been proved but relationship does not mean, necessarily, causality: "[f]uture research should examine the many potential underlying reasons for the negative relationship identified here, including time spent studying and multitasking".
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com