Prevalence and Risk Factors of Gestational Diabetes in Twin Pregnancies: Population Based Study

Objective: To assess the prevalence and risk factors of gestational diabetes (GDM) in twin compared with singleton pregnancies. Methods: Population-based study using CDC birth data from 2016-2020. Higher order pregnancies and pre-pregnancy diabetes were excluded. A Chi-square test of independence was performed to identify significant factors associated with GDM in twin versus singleton pregnancies and within each group independently. Multivariable regression analyses were performed first to assess risk factors that are significantly associated with GDM in twins and second to assess the risk of GDM in twin compared with singletons, adjusted for the significant risk factors. P value<0.01 was considered statistically significant Results: Total of 18,173,365 singleton and 611,043 twin pregnancies were included during the study period. Following the regression model, maternal age≥30 years, nulliparous, IVF, chronic hypertension, Hispanic and Non-Hispanic (NH) Asian, foreign-born, overweight and obesity class I/II/II remained significantly associated with GDM in twins. However, maternal age<25 years, NH Black, and W.I.C program reduced that risk. Factors that more than doubled the risk in twins were maternal age≥40 years (OR 2.06 (1.97 – 2.14), P<0.001), NH Asian (OR 2.12 (2.04 – 2.20), P<0.001), and obesity class I, II, and III (OR: 2.22 (2.16 – 2.29), P<0.001, OR:3.01 (2.92 – 3.11), P<0.001, OR: 3.80 (3.67 – 3.93), p<0.001, respectively). Following adjustment for all the significant risk factors, twin pregnancy remained significantly associated with increasing the risk of GDM in twin compared to singleton pregnancies (OR 1.22 (1.21 – 1.23), P<0.001). Conclusion: Of the significant risk factors, maternal age≥40 years, NH Asian, and obesity class I, II, and III more than doubled the risk of GDM in twins. Regardless of maternal demographics, obstetric history, and endocrine factors, twin pregnancy remained significantly associated with GDM compared to singleton pregnancies. These factors can be used in risk prediction models to better counsel and manage twin pregnancies

Development and Validation of a New Bitumen Fume Generation System which Generates Polycyclic Aromatic Hydrocarbon Concentrations Proportional to Fume Concentrations

Bitumen fumes emitted during road paving and roofing contain polycyclic aromatic compounds (PACs) of potential health concern. Little information is available for an experimental device devoted to inhalation experiments with animals exposed to bitumen fumes, and in all studies the systems were never validated for a range of fume concentrations, which prohibited their use for toxicological concentration-effect studies. Therefore, the purpose of this study was to validate a new experimental device able to generate bitumen fumes at different total particulate matter (TPM) concentrations with a linear correlation between TPM and the concentrations of different PACs, thus allowing toxicological dose-response studies with fumes representative of those in the field. Atmosphere samples collected from an animal exposure chamber allowed the determination of TPM, toluene soluble matter, polycyclic aromatic hydrocarbons (PAHs) and semi-volatiles. The particulate size distributions were determined in order to assess the deposition pattern in the respiratory tract. The temperature of 170°C was chosen by analogy with the upper range of the temperature used during paving operations. The temperature of the air passing over the fume emission area was regulated to 20°C and stirring of the heated bitumen was restricted to 90 r.p.m. The data show that the objective of developing a static fume generation system that reproducibly produces fumes in the inhalation chamber for specified target concentrations (TPM) were successful. The within-day variation coefficients for TPM were between 2.5 and 6.1%. The day-to-day variations for TPM concentration were between 4.1 and 5.8%. The concentrations of the 4-5 ring PAHs and the polycyclic aromatic sulphur heterocycles were proportional to the TPM concentration. The 2 and 3 ring PAH concentrations showed a deviation from proportionality with the TPM, probably due to their re-evaporation during sampling. The mass median aerodynamic diameter of airborne particles varied from 1.4 µm at a fume concentration of 5 mg/m3 to 3.2 µm at 100 mg/m3. In conclusion, this equipment was suitable for nose-only inhalation studies in the 5-100 mg/m3 range of TPM. Bitumen fumes were generated with a good reproducibility under well-controlled conditions. Finally, the PAH profiles from atmospheric samples were in good agreement with those measured during road pavin

Development and validation of a new bitumen fume generation system which generates polycyclic aromatic hydrocarbon concentrations proportional to fume concentrations

Bitumen fumes emitted during road paving and roofing contain polycyclic aromatic compounds (PACs) of potential health concern. Little information is available for an experimental device devoted to inhalation experiments with animals exposed to bitumen fumes, and in all studies the systems were never validated for a range of fume concentrations, which prohibited their use for toxicological concentration-effect studies. Therefore, the purpose of this study was to validate a new experimental device able to generate bitumen fumes at different total particulate matter (TPM) concentrations with a linear correlation between TPM and the concentrations of different PACs, thus allowing toxicological dose-response studies with fumes representative of those in the field. Atmosphere samples collected from an animal exposure chamber allowed the determination of TPM, toluene soluble matter, polycyclic aromatic hydrocarbons (PAHs) and semi-volatiles. The particulate size distributions were determined in order to assess the deposition pattern in the respiratory tract. The temperature of 170 degrees C was chosen by analogy with the upper range of the temperature used during paving operations. The temperature of the air passing over the fume emission area was regulated to 20 degrees C and stirring of the heated bitumen was restricted to 90 r.p.m. The data show that the objective of developing a static fume generation system that reproducibly produces fumes in the inhalation chamber for specified target concentrations (TPM) were successful. The within-day variation coefficients for TPM were between 2.5 and 6.1%. The day-to-day variations for TPM concentration were between 4.1 and 5.8%. The concentrations of the 4-5 ring PAHs and the polycyclic aromatic sulphur heterocycles were proportional to the TPM concentration. The 2 and 3 ring PAH concentrations showed a deviation from proportionality with the TPM, probably due to their re-evaporation during sampling. The mass median aerodynamic diameter of airborne particles varied from 1.4 micro m at a fume concentration of 5 mg/m(3) to 3.2 micro m at 100 mg/m(3). In conclusion, this equipment was suitable for nose-only inhalation studies in the 5-100 mg/m(3) range of TPM. Bitumen fumes were generated with a good reproducibility under well-controlled conditions. Finally, the PAH profiles from atmospheric samples were in good agreement with those measured during road paving

Machine learning prediction of hypertension and diabetes in twin pregnancies using characteristics at prenatal care entry: a nationwide study.

OBJECTIVES: To develop a prediction model for hypertensive disorders in pregnancy (HDP) and gestational diabetes (GDM) in twin pregnancies utilizing characteristics at the prenatal care entry level. METHODS: Cross-sectional study using the US national live birth data between 2016 and 2021. The association of all prenatal candidate variables with HDP and GDM was tested with uni- and multi-variable logistic regression analyses. Prediction models were built with generalized linear models using the logit link function and classification and regression tree approach (XGboost) machine learning (ML) algorithm. Performance was assessed with repeated 2-fold cross-validation and performance metrics we considered were area under the curve (AUC). P value <0.001 was considered statistically significant. RESULTS: A total of 707,198 twin pregnancies were included in the HDP analysis and 723,882 twin pregnancies for the GDM analysis. The incidence of HDP and GDM significantly increased from 12.2% in 2016 to 15.4% in 2021 and from 8.1% in 2016 to 10.7% in 2021, respectively. Factors that increase the risk of HDP in twin gestations are maternal age <20, age≥35, infertility, prepregnancy DM, non-Hispanic Black population, obesity, and those with Medicaid insurance (p<0.001). Factors that more than doubled the risk are obesity class II and III (p<0.001). Factors that increase the risk of GDM in twin gestations are age <25, age≥30, history of infertility, prepregnancy hypertension, non-Hispanic Asian population, non-US nativity, and obesity (p<0.001). Factors that more than doubled the risk are maternal age ≥ 30 years, non-Hispanic Asian, and class I, II, and III maternal obesity ( p<0.001). For both HDP and GDM, the performance of the ML and logistic regression model was mostly similar with negligible difference in terms of all tested performance domains. The AUC of the final ML model for HDP and GDM were 0.62±0.004, and 0.67±0.004, respectively. CONCLUSIONS: The incidence of HDP and GDM in twin gestations is increasing. The predictive accuracy of the machine learning model for both HDP and GDM in twin gestations is similar to that of the logistic regression model. Both models had modest performance, well-calibrated, and neither had a poor fit. This article is protected by copyright. All rights reserved