BACKGROUND: Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements.
METHODS: Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time.
RESULTS: Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (β -0.010, 95%CI -0.025, 0.005; β -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (β -1.001, 95%CI -1.888, -0.131).
CONCLUSIONS: The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.

After anterior cruciate ligament reconstruction (ACL-R), many studies have reported a deficit of performance on the injured leg during multi-joint tasks. However, the total mechanical joint work (WTotal ), parameter best related to the vertical displacement of the body mass center during vertical jumping, has not yet been studied. The aim of this research was to compare asymmetries between ACL-R subjects and healthy matched subjects, through the analysis of the kinematics and kinetics during a single-leg squat jump. Asymmetries are defined by the Limb Symmetry Index (LSI). A greater LSI was observed for WTotal in the ACL-R group than in the healthy group. There was no difference in LSI for knee joint work between the two groups, while the LSI for hip and ankle joint work was significantly larger in the ACL-R group. This was explained by greater LSI for the hip and ankle joint range of motion in the ACL-R group than in the healthy group. After ACL-R, patients exhibited greater asymmetries than healthy subjects during single-leg squat jump. Physiotherapists should focus on quality execution of multi-joint movement, especially on hip and ankle joints range of motion in order to reduce asymmetries and to improve vertical jumping performance.