Triglyceride-glucose index in early pregnancy predicts the risk of gestational diabetes: a prospective cohort study.

OBJECTIVE: This study aimed to investigate the association between the triglyceride-glucose (TyG) index in early pregnancy and the development of gestational diabetes mellitus (GDM) in the second trimester. The primary objectives were to evaluate the predictive potential of the TyG index for GDM, determine the optimal threshold value of the TyG index for GDM assessment, and compare the predictive performance of the TyG index alone versus its combination with maternal age and pre-pregnancy body mass index on GDM. Moreover, the study explored the association between the TyG index in early pregnancy and the risk of other pregnancy-related complications (PRCs), such as placental abruption and gestational hypertension. PATIENTS AND METHODS: This prospective cohort study recruited 1,624 pregnant women who underwent early pregnancy antenatal counseling and comprehensive assessments with continuous monitoring until delivery. To calculate the TyG index, health indicators, including maternal triglycerides and fasting plasma glucose, were measured in early pregnancy (< 14 weeks of gestation). The predictive power of the TyG index for evaluating GDM in Chinese pregnant women was determined using multifactorial logistic regression to derive the odds ratios and 95% confidence interval (CI). Subgroup analyses were conducted, and the efficacy of the TyG index in predicting PRCs was assessed via receiver operating characteristic (ROC) curve analysis and restricted cubic spline, with the optimal cutoff value calculated. RESULTS: Logistic regression analyses revealed a 2.10-fold increase in the GDM risk for every 1-unit increase in the TyG index, after adjusting for covariates. The highest GDM risk was observed in the group with the highest TyG index compared with the lowest quintile group (odds ratios: 3.25; 95% CI: 2.23-4.75). Subgroup analyses indicated that exceeding the recommended range of gestational weight gain and an increased GDM risk were significantly associated (P = 0.001). Regarding predictive performance, the TyG index exhibited the highest area under the curve (AUC) value in the ROC curve for GDM (AUC: 0.641, 95% CI: 0.61-0.671). The optimal cutoff value was 8.890, with both sensitivity and specificity of 0.617.The combination of the TyG index, maternal age, and pre-pregnancy body mass index proved to be a superior predictor of GDM than the TyG index alone (AUC: 0.672 vs. 0.641, P < 0.01). After adjusting for multiple factors, the analyses indicated that the TyG index was associated with an increased risk of gestational hypertension. However, no significant association was noted between the TyG index and the risk of preeclampsia, placental abruption, intrauterine distress, or premature rupture of membranes. CONCLUSION: The TyG index can effectively identify the occurrence of GDM in the second trimester, aligning with previous research. Incorporating the TyG index into routine clinical assessments of maternal health holds significant practical implications. Early identification of high-risk groups enables healthcare providers to implement timely interventions, such as increased monitoring frequency for high-risk pregnant women and personalized nutritional counseling and health education. These measures can help prevent or alleviate potential maternal and infant complications, thereby enhancing the overall health outcomes for both mothers and babies.

Influencing factors of sleep quality in pregnant: a structural equation model approach.

BACKGROUND: To describe the changes in the level of sleep quality during pregnancy among pregnant women in Urumqi; also to construct a structural equation model of the factors influencing the sleep quality of pregnant women, to analyze the path relationship between the influencing factors, and to take reasonable interventions to prevent and reduce the occurrence of sleep disorders among pregnant women. METHODS: 986 pregnant women who gave birth in Urumqi Maternal and Child Health Hospital and Urumqi Youai Hospital between August 2021 and May 2023 were selected. The Pittsburgh Sleep Quality Index (PSQI), Self-Rating Anxiety Scale (SAS), and Edinburgh Postpartum Depression Scale (EPDS) were used to assess the sleep, anxiety, and depression of pregnant women, Building a structural equation model based on AMOS 23.0 Tools. RESULTS: The results of structural equation modeling showed that: basic characteristics, obstetrical characteristics, tocolysis, lifestyle, psychological had a direct effect on the PSQI, with path coefficients of 0.243, 0.106, 0.140, 0.174, 0.658, the corresponding T-values for each path are 4.585, 2.677, 2.578, 2.297, and 9.036. The indirect effect of basic characteristics, obstetric characteristics and lifestyle on PSQI was 0.123, 0.020, 0.027. CONCLUSIONS: The high incidence of sleep disorders in pregnant women and their close association with psychological symptoms in pregnant women should focus on screening and counseling regarding psychological disorders in pregnant women, thus improving the quality of sleep in pregnant women.

Interaction between air pollutants and meteorological factors on pulmonary tuberculosis in northwest China: A case study of eight districts in Urumqi.

Meteorological factors and air pollutants are associated with the spread of pulmonary tuberculosis (PTB), but few studies have examined the effects of their interactions on PTB. Therefore, this study investigated the impact of meteorological factors and air pollutants and their interactions on the risk of PTB in Urumqi, a city with a high prevalence of PTB and a high level of air pollution. The number of new PTB cases in eight districts of Urumqi from 2014 to 2019 was collected, along with data on meteorological factors and air pollutants for the same period. A generalized additive model was applied to explore the effects of meteorological factors and air pollutants and their interactions on the risk of PTB incidence. Segmented linear regression was used to estimate the nonlinear characteristics of the impact of meteorological factors on PTB. During 2014-2019, a total of 14,402 new cases of PTB were reported in eight districts, with March to May being the months of high PTB incidence. The exposure-response curves for temperature (Temp), relative humidity (RH), wind speed (WS), air pressure (AP), and diurnal temperature difference (DTR) were generally inverted "U" shaped, with the corresponding threshold values of - 5.411 °C, 52.118%, 3.513 m/s, 1021.625 hPa, and 8.161 °C, respectively. The effects of air pollutants on PTB were linear and lagged. All air pollutants were positively associated with PTB, except for O3, which was not associated with PTB, and the ER values for the effects on PTB were as follows: 0.931 (0.255, 1.612) for PM2.5, 1.028 (0.301, 1.760) for PM10, 5.061 (0.387, 9.952) for SO2, 2.830 (0.512, 5.200) for NO2, and 5.789 (1.508, 10.251) for CO. Meteorological factors and air pollutants have an interactive effect on PTB. The risk of PTB incidence was higher when in high Temp-high air pollutant, high RH-high air pollutant, high WS-high air pollutant, lowAP-high air pollutant, and high DTR-high air pollutant. In conclusion, both meteorological and pollutant factors had an influence on PTB, and the influence on PTB may have an interaction.