Search

There are limited and inconsistent data suggesting that mild iodine deficiency in pregnancy might be associated with poorer developmental outcomes in children. Between 2011 and 2015, we conducted a prospective cohort study in Australia examining the relationship between maternal iodine intake in pregnancy and childhood neurodevelopment, assessed using Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III), in 699 children at 18 months. Maternal iodine intake and urinary iodine concentration (UIC) were assessed at study entry (<20 weeks' gestation) and at 28 weeks' gestation. Maternal iodine intake in the lowest (<220 μg/day) or highest (≥391 μg/day) quartile was associated with lower cognitive, language, and motor scores (mean differences ranged from 2.4 (95% confidence interval (CI): 0.01, 4.8) to 7.0 (95% CI: 2.8, 11.1) points lower) and higher odds (odds ratios ranged from 2.7 (95% CI: 1.3, 5.6) to 2.8 (95% CI: 1.3, 5.7)) of cognitive developmental delay (Bayley-III score <85) compared with mothers with an iodine intake in the middle quartiles. There was no association between UIC in pregnancy and Bayley-III outcomes regardless of whether UIC and the outcomes were analyzed as continuous or categorical variables. Both low and high iodine intakes in pregnancy were associated with poorer childhood neurodevelopment in this iodine-sufficient population. [ABSTRACT FROM AUTHOR]

In observational studies on cancer patients, progression of performance status over time can be described by using a multistate model in which state-to-state transitions represent changes in a patient's health condition. Although a patient experiences transitions in continuous time, assessments on the patient are often made at irregularly spaced time points. In this paper, the authors formulate a Markov 4-state model for examining longitudinal data on performance status collected under intermittent observation. The cohort consisted of 11,342 patients diagnosed with cancer in Ontario, Canada, from 2007 to 2009. The authors extend the model to estimate the predicted probability of reaching the absorbing state, death, over various time intervals. The authors also illustrate what happens to the estimated transition intensities if the true observational scheme is overlooked. Methods for multistate analysis should be used by epidemiologists, since they prove particularly useful for examining the complexities of disease processes. [ABSTRACT FROM PUBLISHER]