Longitudinal Associations Between Maternal Glucose Levels and Ultrasonographic Fetal Biometrics in a Shanghai Cohort.

Importance: Evidence on the timing of fetal growth alterations associated with gestational diabetes or on the association of the maternal glycemic trajectory with fetal growth during pregnancy remains lacking. Objective: To examine the associations between maternal glucose levels and offspring intrauterine growth. Design, Setting, and Participants: This cohort study used data from 4574 eligible pregnant women and their offspring in the Shanghai Maternal-Child Pairs Cohort collected from April 10, 2016, to April 30, 2018. Group-based trajectory modeling was used to classify fasting plasma glucose levels during pregnancy into 3 glycemic trajectories (trajectory 1, consistently normal glucose levels in all 3 trimesters; trajectory 2, hyperglycemia only in late pregnancy; and trajectory 3, hyperglycemia in all 3 trimesters [ie, consistently high glucose levels]). Statistical analysis was performed from April 25, 2020, to October 1, 2021. Exposures: Gestational diabetes, which was defined using the results of an oral glucose tolerance test. Main Outcomes and Measures: Longitudinal fetal biometrics during gestational weeks 11 to 40 and birth outcomes were obtained from medical records. Pregnancy was partitioned into 3 periods (<24, 24-34, and >34 weeks' gestational age). The differences in offspring growth (log-transformed) and maternal glucose levels were compared using generalized linear mixed models. Results: A total of 4121 pregnant women had oral glucose tolerance test results (mean [SD] age, 28.8 [4.1] years), 3746 of whom had glycemic trajectory data (mean [SD] age, 28.6 [4.1] years); 983 women (23.8%) had gestational diabetes. Throughout the pregnancy period and compared with the women without gestational diabetes or with women in the trajectory 1 group, the fetal biometrics for the women with gestational diabetes or for those in the trajectory 3 group were significantly higher (except for biparietal diameter), with an estimated increase in fetal weight in the group with gestational diabetes (ß = 1.82; 95% CI, 1.03-2.61) and in the trajectory 3 group (ß = 1.50; 95% CI, 0.54-2.47; P = .002). Fetal biometric alterations among women with gestational diabetes appeared before 24 weeks' gestational age, with neonatal birth weight significantly higher than in the group without gestational diabetes at 40.4 g (95% CI, 9.8-71.1 g) along with an increased risk of large size for gestational age (odds ratio, 1.36; 95% CI, 1.05-1.75) and macrosomia (odds ratio, 1.47; 95% CI, 1.12-1.94). However, pregnant women in the trajectory 2 group manifested significantly reduced fetal biometrics, and abdominal circumference was significantly augmented after 34 weeks' gestational age (increase, ß = 1.92; 95% CI, 0.87-2.99). Conclusions and Relevance: In this cohort study, pregnant women who received a diagnosis of gestational diabetes in midpregnancy or had hyperglycemia during all 3 trimesters showed an association with altered fetal growth patterns, including increased estimated fetal weight that appeared before 24 weeks' gestational age, increased birth weight, and the risk for large size for gestational age and macrosomia.

A Longitudinal Study of the Effects of Bed-Sharing Experience in Infancy on Sleep Outcomes at 2 Years Old.

OBJECTIVE: To assess the effects of bed-sharing experiences in infancy on sleep patterns and sleep problems at 2 years of age. STUDY DESIGN: A total of 1564 children from an ongoing Shanghai Maternal-Child Pairs Cohort were included. Bed-sharing experiences were collected when children were 2, 6, and 24 months old via caregiver-completed questionnaires (whether caregivers shared a bed with children during the night), and children's bed-sharing experiences were classified as follows: no bed-sharing, early-only bed-sharing, late-onset bed-sharing, and persistent bed-sharing. Sleep outcomes at month 24 were assessed using the Brief Infant Sleep Questionnaire. Sleep patterns and problems were compared among the 4 types of bed-sharing experiences. RESULTS: Of the 1564 infants, 10.10% had no bed-sharing, 18.35% had early-only, 27.94% had late-onset, and 43.61% had persistent bed-sharing. Compared with children with no bed-sharing, children with late-onset and persistent bed-sharing had shorter nighttime sleep durations and longer daytime sleep durations (P < .05) and were more likely to snore (aOR 1.87 [95% CI 1.25-2.79]; aOR 1.68 [95% CI 1.14-2.47]) and have sleep onset difficulty (aOR 2.06 [95% CI 1.37-3.09]; aOR 2.07 [95% CI 1.41-3.05]). However, caregivers of infants in the late-onset and persistent bed-sharing groups perceived less problematic sleep (aOR 0.38 [95% CI 0.26-0.56] and aOR 0.40 [95% CI 0.28-0.58]). CONCLUSIONS: Bed-sharing is a common experience among Chinese children. Although bed-sharing may reduce caregivers' perception of children's problematic sleep, late-onset or persistent bed-sharing in infancy is associated with sleep problems at 2 years of age.

Application of a combined model with seasonal autoregressive integrated moving average and support vector regression in forecasting hand-foot-mouth disease incidence in Wuhan, China.

Hand-foot-mouth disease (HFMD) is a serious public health problem with increasing cases and substantial financial burden in China, especially in Wuhan city. Hence, there is an urgent need to construct a model to predict the incidence of HFMD that could make the prevention and control of this disease more effective.The incidence data of HFMD of Wuhan city from January 2009 to December 2016 were used to fit a combined model with seasonal autoregressive integrated moving average (SARIMA) model and support vector regression (SVR) model. Then, the SARIMA-SVR hybrid model was constructed. Subsequently, the fitted SARIMA-SVR hybrid model was applied to obtain the fitted HFMD incidence from 2009 to 2016. Finally, the fitted SARIMA-SVR hybrid model was used to forecast the incidence of HFMD of the year 2017. To assess the validity of the model, the mean square error (MSE) and mean absolute percentage error (MAPE) between the actual values and predicted values of HFMD incidence (2017) were calculated.From 2009 to 2017, a total of 107636 HFMD cases were reported in Wuhan City, Hubei Province, and the male-to-female ratio is 1.60:1. The age group of 0 to 5 years old accounts for 95.06% of all reported cases and scattered children made up the large proportion (accounted for 56.65%). There were 2 epidemic peaks, from April to July and September to December, respectively, with an emphasis on the former. High-prevalence areas mainly emerge in Dongxihu District, Jiangxia District, and Hongshan District. SARIMA (1,0,1)(0,0,2)[12] is the optimal model given with a minimum Akaike information criterion (AIC) (700.71), then SVR model was constructed by using the optimum parameter (C = 100000, =0.00001, =0.01). The forecasted incidences of single SARIMA model and SARIMA-SVR hybrid model from January to December 2017 match the actual data well. The single SARIMA model shows poor performance with large MSE and MAPE values in comparison to SARIMA-SVR hybrid model.The SARIMA-SVR hybrid model in this study showed that accurate forecasting of the HFMD incidence is possible. It is a potential decision supportive tool for controlling HFMD in Wuhan, China.