Table 2.

Quality assessment of included studies

Bias in study designBias in instrument to measure physical activityBias in accounting for confounding variablesOverall quality of study
Cohort studies
Huarta et al. (14)LowLowLowHigh
Leitzmann et al. (13)LowLowLowHigh
Wannamethee et al. (30)LowLowLowHigh
Yun et al. (32)LowLowLowHigh
Inoue et al. (16)LowLowLowHigh
Sjodahl et al. (29)LowHighLowLow
Severson et al. (33)LowLowLowHigh
Case–control studies
Boccia et al. (24)HighHighHighLow
Brownson et al. (34)HighHighLowLow
Campbell et al. (25)LowHighLowLow
Campbell 2 et al. (25)LowHighLowLow
Dosemeci et al. (26)HighHighHighLow
Huang et al. (27)HighHighHighLow
Parent et al. (28)LowHighLowLow
Vigen et al. (15)LowHighLowLow
Wen et al. (31)HighHighLowLow

NOTE: Briefly, we used a three-item checklist to identify whether studies were at low or high risk of bias, based on: (i) study design—low risk of bias if cohort or population-based case–control studies, and high risk of bias if hospital-based case control or exclusively cancer registry based; (ii) instrument used to measure physical activity—low risk of bias if instrument valid and reliable as shown in index study or related study, and high risk of bias if not reported; (iii) key variables adjusted or accounted for: if a study adjusted, matched or accounted for the potential confounding effect of age, sex, and obesity in their analysis, then those studies were considered to be at low risk of bias, otherwise they were considered to be at high risk of bias. Overall, if a study was deemed to be at low risk of bias across all these domains, then it was considered a high-quality study, otherwise it was considered a low-quality study.