Problem Several studies have reported the increased risk of preterm birth, premature rupture of membranes, and low birth weight in patients with recurrent pregnancy loss (RPL). There have been a limited number of large population‐based studies examining adverse pregnancy and perinatal outcome after RPL. Multiple‐imputed analyses (MIA) adjusting for biases due to missing data is also lacking. Method of study A nationwide birth cohort study known as the “Japan Environment and Children’s Study (JECS)” was conducted by the Ministry of the Environment. The subjects consisted of 104 102 registered children (including fetuses or embryos). Results No increased risk of a congenital anomaly, aneuploidy, neonatal asphyxia, or a small for date infant was observed among the children from women with a history of RPL. A novel increased risk of placental adhesion and uterine infection was found. The adjusted ORs using MIA in women with three or more PL were 1.76 (95% CI, 1.04‐2.96) for a stillbirth, 1.68 (1.12‐2.52) for a pregnancy loss, 2.53 (1.17‐5.47) for placental adhesion, 1.87 (1.37‐2.55) and 1.60 (.99‐2.57) for mild and severe hypertensive disorders of pregnancy, respectively, 1.94 (1.06‐3.55) for uterine infection, 1.28 (1.11‐1.47) for caesarean section and .86 (.76‐.98) for a male infant. Conclusion MIA better quantified the risk, which could encourage women who might hesitate to attempt a subsequent pregnancy.

Objectives: Objective measurements using built-in smartphone sensors that can measure physical activity/inactivity in daily working life have the potential to provide a new approach to assessing workers' health effects. The aim of this study was to elucidate the characteristics and reliability of built-in step counting sensors on smartphones for development of an easy-to-use objective measurement tool that can be applied in ergonomics or epidemiological research. Methods: To evaluate the reliability of step counting sensors embedded in seven major smartphone models, the 6-minute walk test was conducted and the following analyses of sensor precision and accuracy were performed: 1) relationship between actual step count and step count detected by sensors, 2) reliability between smartphones of the same model, and 3) false detection rates when sitting during office work, while riding the subway, and driving. Results: On five of the seven models, the inter-class correlations coefficient (ICC (3,1)) showed high reliability with a range of 0.956-0.993. The other two models, however, had ranges of 0.443-0.504 and the relative error ratios of the sensor-detected step count to the actual step count were ±48.7%-49.4%. The level of agreement between the same models was ICC (3,1): 0.992-0.998. The false detection rates differed between the sitting conditions. Conclusions: These results suggest the need for appropriate regulation of step counts measured by sensors, through means such as correction or calibration with a predictive model formula, in order to obtain the highly reliable measurement results that are sought in scientific investigation.

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