ABSTRACT:Objective To explore the risk factors for maternal adverse pregnancy outcomes.Methods An unmatched case-control study based on hospital was performed.Univariate and multivariate Logistic regression were used to analyze the related factors of maternal adverse pregnancy outcomes,including general condition,history of fertility,abnormal symptoms and diseases during pregnancy.Results Univariate analysis results showed that high education level of gravida might be the protective factors of adverse pregnancy outcomes.The risk factors for adverse pregnancy outcome might include advanced maternal age,intensive workload,frequent pregnancy,history of spontaneous abortion,severe morning sickness,and sickness during pregnancy or progestation.Multivariate Logistic regression analysis showed that high education level of gravida (OR=0.63,95% CI:0.50-0.80)was the protective factor of adverse pregnancy outcomes;severe morning sickness (OR=2 .1 3 ,9 5% CI:1 .6 3-2 .7 9 )and sickness during progestation (OR=2.25,95% CI:1.06-4.77)were the risk factors for maternal adverse pregnancy outcomes.Conclusion The level of maternal education should be improved.We should attach great importance to preventive education and thorough treatment of severe morning sickness. Couples should be encouraged to have physical examination before marriage and pregnancy.Corresponding pregnancy care guidance should be given to pregnant women with different physical conditions so as to effectively reduce the occurrence of adverse pregnancy outcomes.

Objective To analyze the incidence of preterm delivery among single live neonates and the association between maternal reproductive history and preterm birth.Methods A questionnaire survey was conducted on reproductive history among women at childbearing age who were selected through multi-stage stratified random sampling method in Shaanxi,during 2010-2013.Samples would include women at childbearing age and in pregnancy or having had definite pregnancy outcomes.Results A total of 29 608 women at childbearing age with their infants,were studied.The overall incidence of premature delivery among the single live birth neonates under this study,was 2.7％ during 2010-2013.Results from the logistic regression model showed that factors as:having had history with preterm delivery (OR=7.99,95％CI:5.59-11.43),age of the mothers,older than 35 (OR=2.03,95％CI:1.59-2.59) and with history of birth defects (OR=1.54,95％CI:1.01-2.34) were at higher risks for premature delivery in neonates.Intervals on pregnancies between 3-4 years (compared with ≤2 years,OR=0.74,95％CI:0.58-0.93),between 5-6 years (compared with ≤2 years,OR=0.66,95％CI:0.52-0.82),or ＞6 years (compared with ≤2 years,OR=0.48,95％CI:0.37-0.61)together with numbers of parity as 1 (compared with primiparas,OR=0.80;95％CI:0.67-0.95),as ≥2 (compared with primiparas,OR=0.62,95％ CI:0.39-0.97) etc.were protective factors to preterm delivery.Factors as:history of preterm delivery,mothers age (older than 35 years) and intervals of pregnancy,appeared influential to the age of gestation,under the ordinal polytomous logistic regression analysis.Conclusion The incidence of preterm births among single live birth neonates in Shaanxi was lower than the average national level.Programs related to health care services prior to conception and during pregnancy,together with increasing the self-care consciousness of childbearing aged women etc,should all be strengthened in order to reduce the occurrence of preterm birth,in Shaanxi province.

【Objective】 To understand the epidemiological characteristics of COVID-19 in Shaanxi Province from December 9, 2021 to January 20, 2022, and analyze the factors influencing the interval from isolation to diagnosis. 【Methods】 We collected the data of local COVID-19 cases from December 9, 2021 to January 20, 2022 published on the official website of Health Commission of Shaanxi Province. Descriptive statistical method was used to analyze the epidemiological characteristics of COVID-19 in Shaanxi Province. Mann-Whitney U test and Kruskal-Wallis H test were used to compare the differences between groups. The unconditional Logistic regression model was applied to analyze the factors influencing the interval between isolation and diagnosis. 【Results】 The outbreak of COVID-19 in Shaanxi Province started on December 9, 2021 and ended on January 20, 2022. The overall change trend of the outbreak showed an "inverted V" shape. A total of 2,080 confirmed local cases were reported, and the main type of disease was mild, with an incidence rate of 5.26/100,000. Xi’an had the most cases, accounting for 98.69% of the total. The reported cases were mainly concentrated in people aged 21 to 55 years old, with a male-to-female sex ratio of 1.19∶1. The median interval from isolation to diagnosis was 3 days, the shortest interval being 0 day and the longest interval being 21 days. Unconditional Logistic regression model analysis showed that the way of finding cases was the factor influencing the interval from isolation to diagnosis. Compared with the way of isolation of the key population, the way of the nucleic acid screening could reduce the risk of late detection of confirmed cases by 89% (OR=0.11, 95% CI: 0.07-0.16). 【Conclusion】 The way of finding cases is the factor influencing the interval from isolation to diagnosis. In the face of the recent intensification of the spread of Omicron variant in mainland China, accurate and rapid identification and detection of confirmed cases can not only reduce the risk of the spread of the epidemic, but also endeavor more time and initiative for the treatment of patients, which is the key to curbing the spread of the epidemic.