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Objective:To study the characteristics of vaginal microbiota in pregnant women with premature rupture of membranes (PROM) and to establish prediction models for PROM.Methods:This study involved 35 women with preterm premature rupture of membranes (PPROM), 180 with term premature rupture of membranes (TPROM) and 255 term birth cases without premature rupture of membranes (TBWPROM, control group). The V3-V4 hypervariable region sequences in the vaginal samples collected at 16-28 weeks of gestation were detected by 16S rRNA gene next-generation sequencing. The differences in Alpha and Beta diversity, and the attributes and metabolic function prediction of each recognized species among the three groups were analyzed. Subsequently, a random forest model was used to establish the prediction models for PROM using vaginal microbiota species and environmental risk factors.Results:Compared with the control group, the Alpha diversity of the PPROM group was higher (Observed features, P=0.022; Faith_pd index, P=0.024) and Beta diversity was also significantly different (Unweighted UniFrac, P=0.010; Jaccard index, P=0.008). In PPROM cases, Megasphaera genomosp. typeⅠ was significantly increased ( P=0.017) and Lactobacillus mulieris was significantly decreased ( P=0.003). In the patients with TPROM, Megasphaera was significantly increased ( P=0.009) and Lactobacillus mulieris was significantly decreased ( P=0.002). In terms of functional pathways, sulfur oxidation ( P=0.021), methanogenesis from acetate ( P=0.036), L-histidine biosynthesis ( P=0.009), adenosylcobalamin biosynthesis ( P=0.041) and fucose degradation ( P=0.001) were significantly increased in patients with PPROM; L-histidine biosynthesis ( P<0.001) and fucose degradation ( P=0.030) were significantly increased in patients with TPROM. The prediction models were established using the random forest model with vaginal microbiota species and environmental risk factors and the prediction model for PPROM performed well [AUC: 0.739 (95%CI: 0.609-0.869), sensitivity: 0.928, specificity: 0.659, positive predictive value: 0.750, negative predictive value: 0.906], which had a certain reference value. Conclusions:Vaginal microbiota might be related to the development and progression of PROM. Studying the differences in vaginal microbiota might provide a new idea for the prevention and treatment of PROM. Functional prediction provided a direction for further research on the mechanism of PROM. The established prediction model could prevent the occurrence of PPROM and promote maternal and infant health.
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Objective:To study the characteristics and influencing factors of vaginal microbiota in normal pregnant women.Methods:This study was based on a cohort of pregnant women established in Anqing Municipal Hospital Affiliated to Anhui Medical University from February 2018 to February 2020. Vaginal samples of normal pregnant women who met the inclusion and exclusion criteria were ordered by the gestational weeks at sampling. Five samples were randomly selected from each gestational week group and if the samples were less than five, all samples were included. Sequencing of the V3-V4 region of the 16S rRNA gene was performed. Dominant species were analyzed by MicrobiomeAnalyst. Alpha diversity was measured with Chao1, Observed Features, Shannon diversity, Simpson diversity, Faith_pd and Pielou′s Evenness. The dominant status of Lactobacillus was also described and compared. Multiple linear regression and logistic regression were used to analyze the factors influencing vaginal microbiota. Analysis of variance and Kruskal Wallis test were used for statistical analysis of continuous variables, and Chi-square test and Fisher′s exact test were used for categorical data. The differences were considered statistically significant when the P value was less than 0.05. Results:This study enrolled 91 pregnant women (91 vaginal samples) with an average age of (27.37±3.60) years. There were 18, 56 and 17 vaginal samples collected at the median gestational age of 11.93 weeks (the first trimester), 19.43 weeks (the second trimester) and 38.29 weeks (the third trimester), respectively. The relative abundance of Firmicutes and Lactobacillus was 91.30% and 87.67%, respectively. Lactobacillus iners and Lactobacillus crispatus had a relative abundance of 43.95% and 36.33%, respectively. Moreover, Lactobacillus iners-dominated vaginal microbiota was detected in all trimesters. The number of samples with high relative abundance of Lactobacillus iners gradually decreased with gestational age. Lactobacillus crispatus-dominated vaginal microbiota was found in the second and third trimesters and the number of samples with high relative abundance gradually increased during pregnancy. The Alpha diversity of vaginal microbiota had a decreasing trend during the gestation. There were significant differences in Pielou′s Evenness diversity index of vaginal microbiota between different smoking groups ( P<0.05) and in Shannon diversity index between different drinking groups ( P<0.05). There were significant differences in Chao1, Observed Features and Faith_pd diversity index of vaginal microbiota between pregnant women with different education ( P<0.05) and in Shannon and Simpson diversity index between different income groups ( P<0.05). Conclusions:Vaginal microbiota was dominated by Lactobacillus in normal pregnant women. The dominance of Lactobacillus iners gradually decreased, while that of Lactobacillus crispatus increased during gestation. In normal pregnant women, the Alpha diversity of vaginal microbiota was correlated with smoking, drinking, education and family annual income. Smoking cessation and drinking before pregnancy were related to lower Alpha diversity of vaginal microbiota in pregnant women, while lower education and higher family income were associated with higher Alpha diversity.
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Objective To understand the incidence characteristics and epidemic tendency of notifiable infectious diseases （NID） among children aged 0 to 6 years old in Hudong Community of Shanghai from 2011 to 2018， in order to provide a scientific basis for the accurate prevention and control measures. Methods Descriptive epidemiology was used to analyze the data of NID. Results A total of 1 401 cases of eight different NID were reported in children aged 0 to 6 from 2011 to 2018 in Hudong Community， with an average annual incidence rate of3 536.63/105， and there were no dead cases. The incidence rates of different years were statistically significant （P<0.001）. The top five diseases were hand， foot and mouth disease （HFMD）， chickenpox， mumps， influenza and scarlet fever， which accounted for 97.79% of all cases. The incidence of intestinal infectious diseases peaked during the months of May to September and November， and that of respiratory infectious diseases peaked from April to June and from November to January. The average incidence rate of males was 4 118.81/105， and that of females was 2 930.87/105. The gender ratio （male︰female） was 1.41∶1， with statistical significance （P<0.001）. The intestinal infectious diseases mainly occurred in children aged one to four years old， accounting for 79.09%， and the respiratory infectious diseases mainly occurred in children aged four to six years old， accounting for 63.46%. The incidence and spectrum of NID varied in different age groups. The main population affected was those children from kindergartens， which accounted for 55.46% of all cases. Conclusion Infectious diseases threatening the health of children aged 0~6 years old in Hudong Community are mainly intestinal infectious diseases， especially HFMD. The targeted prevention and control strategies should be carried out according to the epidemic features so as to prevent the occurrence of outbreaks and epidemics of infectious diseases.
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Epidemiology is a branch of science that mainly involves in the etiology studies of non-randomness phenomenon among homogenous populations. In this paper, we use causal-thinking, supported by its tool-Directed Acyclic Graphs, to illustrate how the estimation of effects is affected by the issues as relations between effect and association, time sequences between variables and their measured counterparts, natural picture of dynamic population, formation of susceptible population, selection of study population, impact of covariates and types of cases etc., on the estimation of effects. This type of thinking may help us to re-capture the epidemiological theories, methods and related applications. Thus, causal-thinking should be strengthened.
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Cohort study is an irreplaceable method for studies related to maternal and child health.Compared with other countries,China's maternal and child cohort studies started relatively later but has its unique developing track.This paper summarizes the basic information and characteristics of the maternal and child cohorts with wide and great influence in China in the past 25 years.
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Cohort study is an irreplaceable method for studies related to maternal and child health.Compared with other countries,China's maternal and child cohort studies started relatively later but has its unique developing track.This paper summarizes the basic information and characteristics of the maternal and child cohorts with wide and great influence in China in the past 25 years.
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Confounding affects the causal relation among the population.Depending on whether the confounders are known,measurable or measured,they can be divided into four categories.Based on Directed Acyclic Graphs,the strategies for confounding control can be classified as (1) the broken-confounding-path method,which can be further divided into single and dual broken paths,corresponding to exposure complete intervention,restriction and stratification,(2) and the reserved-confounding-path method,which can be further divided into incomplete exposure intervention (in instrumental variable design and non-perfect random control test),mediator method and matching method.Among them,random control test,instrumental variable design or Mendelian randomized design,mediator method can meet the requirements for controlling all four types of confounders,while the restriction,stratification and matching methods are only applicable to known,measurable and measured confounders.Identifying the mechanisms of confounding control is a prerequisite for obtaining correct causal effect estimates,which will be helpful in research design.
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One of the commonly accepted merits of cohort studies (CSs) refers to the exposure precedes outcome superior to other observational designs.We use Directed Acyclic Graphs to construct a causal graph among research populations under CSs.We notice that the substitution of research population in place of a susceptible one can be used for effect estimation.Its correctness depends on the outcome-free status of the substituted population and the performance of both screening and diagnosis regarding the outcomes under study at baseline.The temporal precedence of exposure over outcome occurs theoretically,despite the opposite happens in realities.Correct effect estimate is affected by both the suitability of population substitution and the validities of outcome identification and exclusion.
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Objective To investigate the association between maternal pre-pregnant body mass index and gestational weight gain,as well as their interaction on neonatal birthweight.Methods We built a cohort in Anqing Municipal Hospital from January 2014 to March 2015,enrolling pregnant women who decided to give birth in this hospital.All women were asked to fill a questionnaire for basic information collection.Medical information of both pregnant women and their newborns were obtained through electronic medical record.Chi-square analysis,multinomial logistic regression,multiplicative and additive interaction methods were used to analyze the association between prepregnant body mass index and gestational weight gain as well as their interactions on birth weight of the neonates.Results A total of 2 881 pregnant women were included in this study.Of the 2 881 newborns,359 (12.46％) were small for gestational age (SGA) and 273 (9.48％) were large for gestational age (LGA).After adjusting the possible confounding factors,results from the multinomial logistic regression showed that pre-pregnancy underweight women were more possible to deliver SGA (aRR=1.33,95％CI:1.02-1.73).If the gestational weight gain was below the recommended criteria,the risk of SGA (aRR=1.64,95％ CI:1.23-2.19) might increase.Pre-pregnancy overweight/obese could increase the risk of being LGA (aRR=1.86,95％ CI:1.33-2.60).Maternal gestational weight gain above the recommendation level was associated with higher rates of LGA (aRR=2.03,95％CI:1.49-2.78).Results from the interaction analysis showed that there appeared no significant interaction between pre-pregnancy BMI and gestational weight on birthweight.Conclusion Pre-pregnancy body mass index and gestational weight gain were independently associated with neonatal birthweight while pre-pregnancy BMI and gestational weight gain did not present interaction on birthweight.
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The overall details of causality frames in the objective world remain obscure,which poses difficulty for causality research.Based on the temporality of cause and effect,the objective world is divided into three time zones and two time points,in which the causal relationships of the variables are parsed by using Directed Acyclic Graphs (DAGs).Causal DAGs of the world (or causal web) is composed of two parts.One is basic or core to the whole DAGs,formed by the combination of any one variable originating from each time unit mentioned above.Cause effect is affected by the confounding only.The other is an internal DAGs within each time unit representing a parent-child or ancestor-descendant relationship,which exhibits a structure similar to the confounding.This paper summarizes the construction of causality frames for objective world research (causal DAGs),and clarify a structural basis for the control of the confounding in effect estimate.
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Confounding affects the causal relation among the population.Depending on whether the confounders are known,measurable or measured,they can be divided into four categories.Based on Directed Acyclic Graphs,the strategies for confounding control can be classified as (1) the broken-confounding-path method,which can be further divided into single and dual broken paths,corresponding to exposure complete intervention,restriction and stratification,(2) and the reserved-confounding-path method,which can be further divided into incomplete exposure intervention (in instrumental variable design and non-perfect random control test),mediator method and matching method.Among them,random control test,instrumental variable design or Mendelian randomized design,mediator method can meet the requirements for controlling all four types of confounders,while the restriction,stratification and matching methods are only applicable to known,measurable and measured confounders.Identifying the mechanisms of confounding control is a prerequisite for obtaining correct causal effect estimates,which will be helpful in research design.
ABSTRACT
One of the commonly accepted merits of cohort studies (CSs) refers to the exposure precedes outcome superior to other observational designs.We use Directed Acyclic Graphs to construct a causal graph among research populations under CSs.We notice that the substitution of research population in place of a susceptible one can be used for effect estimation.Its correctness depends on the outcome-free status of the substituted population and the performance of both screening and diagnosis regarding the outcomes under study at baseline.The temporal precedence of exposure over outcome occurs theoretically,despite the opposite happens in realities.Correct effect estimate is affected by both the suitability of population substitution and the validities of outcome identification and exclusion.
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Objective To investigate the association between maternal pre-pregnant body mass index and gestational weight gain,as well as their interaction on neonatal birthweight.Methods We built a cohort in Anqing Municipal Hospital from January 2014 to March 2015,enrolling pregnant women who decided to give birth in this hospital.All women were asked to fill a questionnaire for basic information collection.Medical information of both pregnant women and their newborns were obtained through electronic medical record.Chi-square analysis,multinomial logistic regression,multiplicative and additive interaction methods were used to analyze the association between prepregnant body mass index and gestational weight gain as well as their interactions on birth weight of the neonates.Results A total of 2 881 pregnant women were included in this study.Of the 2 881 newborns,359 (12.46％) were small for gestational age (SGA) and 273 (9.48％) were large for gestational age (LGA).After adjusting the possible confounding factors,results from the multinomial logistic regression showed that pre-pregnancy underweight women were more possible to deliver SGA (aRR=1.33,95％CI:1.02-1.73).If the gestational weight gain was below the recommended criteria,the risk of SGA (aRR=1.64,95％ CI:1.23-2.19) might increase.Pre-pregnancy overweight/obese could increase the risk of being LGA (aRR=1.86,95％ CI:1.33-2.60).Maternal gestational weight gain above the recommendation level was associated with higher rates of LGA (aRR=2.03,95％CI:1.49-2.78).Results from the interaction analysis showed that there appeared no significant interaction between pre-pregnancy BMI and gestational weight on birthweight.Conclusion Pre-pregnancy body mass index and gestational weight gain were independently associated with neonatal birthweight while pre-pregnancy BMI and gestational weight gain did not present interaction on birthweight.
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The overall details of causality frames in the objective world remain obscure,which poses difficulty for causality research.Based on the temporality of cause and effect,the objective world is divided into three time zones and two time points,in which the causal relationships of the variables are parsed by using Directed Acyclic Graphs (DAGs).Causal DAGs of the world (or causal web) is composed of two parts.One is basic or core to the whole DAGs,formed by the combination of any one variable originating from each time unit mentioned above.Cause effect is affected by the confounding only.The other is an internal DAGs within each time unit representing a parent-child or ancestor-descendant relationship,which exhibits a structure similar to the confounding.This paper summarizes the construction of causality frames for objective world research (causal DAGs),and clarify a structural basis for the control of the confounding in effect estimate.
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Objective Intrahepatic cholestasis during pregnancy (ICP) and its relation to incidence of preterm birth (PTB) were under study.Methods A prospective cohort study was carried out that including all the hospitalized pregnant women with live singleton births,from January 2014 to March 2015 in Anqing Municipal Hospitals.Informed consent was followed in every pregnant woman with related demographic information collected through questionnaire and hospital electronic medical record system.Both univariate and multi-variate statistical methods were used to analyze the relations between ICP and incidence of PTB.Results A total of 2 758 pregnant women were included in this study.The incidence proportions of ICP and PTB appeared as 7.25％ and 16.28％ respectively.Results from the logistic regression analysis showed that ICP increased the risk of both overall PTB (RR=2.33,95％CI:1.67-3.25) and medically indicated PTB (RR=8.46,95％CI:5.45-13.12),but not the spontaneous PTB (RR=0.94,95％CI:0.57-1.54).Conclusion ICP seemed to have increased the risk on medically indicated PTB but not the spontaneous PTB.
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The lateral wall,a new concept in the study of trochanteric hip fractures,has a great influence on the choice of internal fixation methods,stability of the fracture and prognosis of the patients.Currently,the research on the lateral wall focuses on the factors leading to its rupture,its anatomical features and its effect on internal fixation,but results in controversial views which are mostly influenced by the subjective and experimental factors.This review deals with how the concept of lateral wall was proposed,the importance and anatomical features of lateral wall,the causes for lateral wall rupture and current treatment perspectives of trochanteric hip fractures,aiming at increasing the awareness of the lateral wall among orthopedic surgeons and related researchers.
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Objective To evaluate and compare the detection consistency of hepatitis B surface antigen (HBsAg) by two immunoassays: enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescent immunoassay (ECLIA). Methods A prospective study was conducted among 2296 pregnant women recruited consecutively from January 1, 2014 to January 31, 2015 in a hospital. Blood samples were collected from them for the detection of HBsAg by using ELISA and ECLIA, Ka ppa test was performed on the results. Nested polymerase chain reaction and sequencing of HBV S gene were also performed in all samples. Phylogenetic analysis was performed using Mega 6.0 software. Results The two methods had high detection consistence of HBsAg ( Ka ppa=0.71). There were significant differences in detection result of B genotype and adw2 serotype HBV strains between two methods. Among 123 identified HBV strains, 113 belonged to genotype B and available for further analysis. The difference in detection of substitution rates between two methods or different positive groups were not significant. Compared with ELISA single positive group, the ECLIA single positive group had completely different substitution sites. Conclusion The two methods had high detection consistence of HBsAg, but there were still 32.4% HBV DNA positive cases in ELISA/ECLIA single positive group, and complete complementary substitution sites between ELISA single positive group and ECLIA single positive group. Our results suggested that more effective detection procedure should be considered for the possible impact of the HBV silent transmission and infection.
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Nearly all scientific studies explore causality,which will be met by directed acyclic graphs (DAGs).This paper systematically introduces graphic language,basic and interference rules of DAGs,and their applications into identifying research questions,understanding and undertaking research designs,guiding data analysis,classifying biases,etc.DAGs play key roles in causality studies.
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Objective To evaluate and compare the detection consistency of hepatitis B surface antigen (HBsAg) by two immunoassays: enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescent immunoassay (ECLIA). Methods A prospective study was conducted among 2296 pregnant women recruited consecutively from January 1, 2014 to January 31, 2015 in a hospital. Blood samples were collected from them for the detection of HBsAg by using ELISA and ECLIA, Ka ppa test was performed on the results. Nested polymerase chain reaction and sequencing of HBV S gene were also performed in all samples. Phylogenetic analysis was performed using Mega 6.0 software. Results The two methods had high detection consistence of HBsAg ( Ka ppa=0.71). There were significant differences in detection result of B genotype and adw2 serotype HBV strains between two methods. Among 123 identified HBV strains, 113 belonged to genotype B and available for further analysis. The difference in detection of substitution rates between two methods or different positive groups were not significant. Compared with ELISA single positive group, the ECLIA single positive group had completely different substitution sites. Conclusion The two methods had high detection consistence of HBsAg, but there were still 32.4% HBV DNA positive cases in ELISA/ECLIA single positive group, and complete complementary substitution sites between ELISA single positive group and ECLIA single positive group. Our results suggested that more effective detection procedure should be considered for the possible impact of the HBV silent transmission and infection.
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Nearly all scientific studies explore causality,which will be met by directed acyclic graphs (DAGs).This paper systematically introduces graphic language,basic and interference rules of DAGs,and their applications into identifying research questions,understanding and undertaking research designs,guiding data analysis,classifying biases,etc.DAGs play key roles in causality studies.