Defining and Identifying Per-protocol Effects in Randomized Trials.

In trials with noncompliance to assigned treatment, researchers might be interested in estimating a per-protocol effect-a comparison of two counterfactual outcomes defined by treatment assignment and (often time-varying) compliance with a well-defined treatment protocol. Here, we provide a general counterfactual definition of a per-protocol effect and discuss examples of per-protocol effects that are of either substantive or methodologic interest. In doing so, we seek to make more concrete what per-protocol effects are and highlight that one can estimate per-protocol effects that are more than just a comparison of always taking treatment in two distinct treatment arms. We then discuss one set of identifiability conditions that allow for identification of a causal per-protocol effect, highlighting some potential violations of those conditions that might arise when estimating per-protocol effects.

Structural Equation Modelling in the exploration and analysis of intrauterine environmental exposures with infant health effects.

INTRODUCTION: In epidemiology, generalized linear models are the main statistical methods used to explore associations. However, the use of other methods such as Structural Equation Modelling (SEM) is gradually increasing. OBJECTIVE: The aim of the study was to illustrate the use of SEM in the assessment of salivary cortisol concentration in infants as a biomarker of perinatal exposure to inorganic arsenic. MATERIAL AND METHODS: This was a cohort study of pregnant women recruited from public health care centres in Arica, Chile, in 2013. Socio-demographic information and urine samples to assess inorganic arsenic were collected during the second trimester of pregnancy. Saliva samples were collected to assess cortisol in infants between 18-24 months of age. Four linear regression models (LRMs) and two SEMs were run to estimate the effect of prenatal exposure to inorganic arsenic on cortisol concentration in infants. RESULTS: According to LRMs and SEMs, prenatal exposure to inorganic arsenic and salivary cortisol were not associated. However, the association between maternal cortisol and cortisol in infants was statistically significant in all models; for each increase in standard deviation of the covariate Ln(maternal cortisol), the outcome Ln(cortisol in infant) increased by 0.49 units of variance in both SEMs. CONCLUSIONS: LRMs and SEMs were useful to assess the effect of prenatal exposure to inorganic arsenic on cortisol in infants. However, SEM allowed the adjustment of estimations by an estimated latent that obtained the information about income, occupation, education and ethnicity in a more comprehensive way than achieved by LRM.

Is prenatal arsenic exposure associated with salivary cortisol in infants in Arica, Chile? An exploratory cohort study.

INTRODUCTION: In animal models, gestational exposure to inorganic arsenic has been associated with higher corticosterone concentration and consequent impairment of stress control in offspring. An equivalent association relating cortisol, a glucocorticoid hormone, in humans has not been previously studied. OBJECTIVE: The aim of the study was to explore the association between prenatal inorganic arsenic exposure and salivary cortisol in infants from Arica, Chile. MATERIAL AND METHODS: A cohort study of 168 mother-child dyads was recruited. In the 2nd trimester of pregnancy, urinary inorganic arsenic was assessed; 18-24 months after delivery, salivary cortisol was measured in the children. Maternal cortisol, maternal depression, stress, and socio-economic status were also evaluated. RESULTS: The adjusted association was estimated with multiple linear regression after evaluating confounding through a directed acyclic graph. Median urinary inorganic arsenic in pregnant women was 14.1 µg/L (IQR: 10.4-21.7) while salivary cortisol in the children was 0.17 µg/L (IQR: 0.11-0.38). Among children from the highest income families (> 614 USD/month), arsenic exposure was associated with salivary cortisol. Children in the third quartile of arsenic exposure had -0.769 units of the logarithm of salivary cortiso, compared with those in the first quartile (p = 0.045). CONCLUSIONS: In this sample, prenatal exposure to arsenic was associated with salivary cortisol (third quartile of inorganic arsenic), only in infants belonging the highest income strata (> 614 USD). More studies are needed to confirm these preliminary results.