Cardiovascular risk factors in relation to hair polycyclic aromatic hydrocarbons in the NESCAV study.

Previous studies have found associations between exposure to polycyclic aromatic hydrocarbons (PAHs) and cardiovascular risk factors. However, the internal dose of PAH exposure was often examined by quantifying monohydroxylated metabolites of PAHs (OH-PAHs) in urine, which can only reflect recent exposure. On the other hand, hair covers wider temporal windows than urine and has been demonstrated to be a suitable matrix for PAH exposure assessment.

Exposure to pesticides, persistent and non - persistent pollutants in French 3.5-year-old children: Findings from comprehensive hair analysis in the ELFE national birth cohort.

Introduction: Exposure to endocrine disruptors during early childhood poses significant health risks. This study examines the exposure levels of French 3.5-year-old children to various persistent and non-persistent pollutants and pesticides using hair analysis as part of the ELFE national birth cohort.

Glucocorticoid hormones in relation to environmental exposure to bisphenols and multiclass pesticides among middle aged-women: Results from hair analysis.

Bisphenols and pesticides have been shown to alter circulating glucocorticoids levels in animals, but there is limited human data. Moreover, measurements from biological fluids may not be able to reflect long-term status of non-persistent pollutants and glucocorticoids due to the high variability in their levels. Using hair analysis, we examined the associations between glucocorticoid hormones and environmental exposure to multi-class organic pollutants among a healthy female population aged 25-45 years old.

Hair-Derived Exposome Exploration of Cardiometabolic Health: Piloting a Bayesian Multitrait Variable Selection Approach.

Cardiometabolic health is complex and characterized by an ensemble of correlated and/or co-occurring conditions including obesity, dyslipidemia, hypertension, and diabetes mellitus. It is affected by social, lifestyle, and environmental factors, which in-turn exhibit complex correlation patterns. To account for the complexity of (i) exposure profiles and (ii) health outcomes, we propose to use a multitrait Bayesian variable selection approach and identify a sparse set of exposures jointly explanatory of the complex cardiometabolic health status.