How many microplastics do you need to (sub)sample?

Analysis of microplastics in the environment requires polymer characterization as a confirmation step for suspected microplastic particles found in a sample. Material characterization is costly and can take a long time per particle. When microplastic particle counts are high, many researchers cannot characterize every particle in their sample due to time or monetary constraints. Moreover, characterizing every particle in samples with high plastic particle counts is unnecessary for describing the sample properties. We propose an a priori approach to determine the number of suspected microplastic particles in a sample that should be randomly subsampled for characterization to accurately assess the polymer distribution in the environmental sample. The proposed equation is well-founded in statistics literature and was validated using published microplastic data and simulations for typical microplastic subsampling routines. We report values from the whole equation but also derive a simple way to calculate the necessary particle count for samples or subsamples by taking the error to the power of negative two. Assuming an error of 0.05 (5 %) with a confidence interval of 95 %, an unknown expected proportion, and a sample with many particles (> 100k), the minimum number of particles in a subsample should be 386 particles to accurately characterize the polymer distribution of the sample, given the particles are randomly characterized from the full population of suspected particles. Extending this equation to simultaneously estimate polymer, color, size, and morphology distributions reveals more particles (620) would be needed in the subsample to achieve the same high absolute error threshold for all properties. The above proposal for minimum subsample size also applies to the minimum count that should be present in samples to accurately characterize particle type presence and diversity in a given environmental compartment.

Pregnant Adolescents Admitted to an Inpatient Child and Adolescent Psychiatric Unit: An Eight-Year Review.

STUDY OBJECTIVE: To assess patient outcomes and describe demographic data of pregnant adolescents admitted to an inpatient child and adolescent psychiatric unit, as well as to determine if it is safe to continue to admit pregnant adolescents to such a unit. DESIGN, SETTING, AND PARTICIPANTS: A descriptive retrospective chart review conducted at a free-standing pediatric hospital in northeast Ohio of all pregnant adolescents aged 13 to 17 years admitted to the inpatient child and adolescent psychiatric unit from July 2005 to April 2013. MAIN OUTCOME MEASURES: Data collection included details on demographic, pregnancy status, and psychiatric diagnoses. RESULTS: Eighteen pregnant adolescents were admitted to the psychiatric unit during the time frame. Sixteen of those were in the first trimester of pregnancy. Pregnancy was found to be a contributing factor to the adolescent's suicidal ideation and admission in 11 of the cases. Admission to an inpatient psychiatric facility did not lead to adverse effects in pregnancy. CONCLUSION: Pregnant adolescents did not have negative pregnancy outcomes related to admission to an inpatient psychiatric unit. Results of this study suggest that it is safe to continue to admit uncomplicated pregnant adolescents in their first trimester to an inpatient child and adolescent psychiatric unit for an acute stay.