We sought to determine risk factors associated with fetal macrosomia and to explore the long-term consequence of infant macrosomia at the age of 7 years.A prospective population based cohort study was designed to exam...We sought to determine risk factors associated with fetal macrosomia and to explore the long-term consequence of infant macrosomia at the age of 7 years.A prospective population based cohort study was designed to examine the associations between maternal and perinatal characteristics and the risk of macrosomia.A nested case-control study was conducted to explore the long-term health consequence of infant macrosomia.The mean maternal age of the macrosomia group was 24.74±3.32 years,which is slightly older than that in the control group(24.35±3.14 years,P = 0.000).The mean maternal body mass index(BMI) at early pregnancy was 22.75±2.81 kg/m 2,which was also higher than that in the control group(21.76±2.59 kg/m 2,P = 0.000).About 64.6% of macrosomic neonates were males,compared with 51.0% in the control group(P = 0.000).Compared with women with normal weight(BMI:18.5-23.9 kg/m 2),women who were overweight(BMI:24-27.9 kg/m 2) or obese(BMI ≥ 28 kg/m 2),respectively,had a 1.69-fold(P = 0.000) and a 1.49-fold(P = 0.000) increased risks of having a neonate with macrosomia,while light weight(BMI<18.5 kg/m 2) women had an approximately 50% reduction of the risk.Furthermore,macrosomia infant had a 1.52-fold and 1.50-fold risk,respectively,of developing overweight or obesity at the age of 7 years(P = 0.001 and P = 0.000).Older maternal age,higher maternal BMI at early pregnancy and male gender were independent risk factors of macrosomia.Macrosomic infant was associated with an increased predisposition to develop overweight or obesity at the beginning of their childhood.展开更多
Expression of estrogen receptors is correlated with breast cancer risk,but inconsistent results have been reported.To clarify potential estrogen receptor(ESR)-related breast cancer risk,we analyzed genetic variants of...Expression of estrogen receptors is correlated with breast cancer risk,but inconsistent results have been reported.To clarify potential estrogen receptor(ESR)-related breast cancer risk,we analyzed genetic variants of ESR1 in association with breast cancer susceptibility.We performed a meta-analysis to investigate the association between rs2234693,rs1801132,and rs2046210(single nucleotide polymorphisms of ESR1),and breast cancer risk.Our analysis included 44 case-control studies.For rs2234693,the CC genotype had a higher risk of breast cancer compared to the TT or CT genotype.For rs2046210,the AA,GA,or GA + GG genotype had a much higher risk compared to the GG genotype.No significant association was found for the rs 1801132 polymorphism with breast cancer risk.This meta-analysis demonstrates association between the rs2234693 and rs2046210 polymorphisms of ESR1 and breast cancer risk.The correlation strength between rs2234693 and breast cancer susceptibility differs in subgroup assessment by ethnicity.展开更多
The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern.A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological pa...The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern.A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological parameters,explore and project the trends of the COVID-19,and assess the effects of intervention or control measures.We identified 63 studies and summarized the three aspects of these studies:epidemiological parameters estimation,trend prediction,and control measure evaluation.Despite the discrepancy between the predictions and the actuals,the dynamic model has made great contributions in the above three aspects.The most important role of dynamic models is exploring possibilities rather than making strong predictions about longer-term disease dynamics.展开更多
The occurrence of coronavirus disease 2019(COVID-19)was followed by a small burst of cases around the world;afterward,due to a series of emergency non-pharmaceutical interventions(NPIs),the increas-ing number of confi...The occurrence of coronavirus disease 2019(COVID-19)was followed by a small burst of cases around the world;afterward,due to a series of emergency non-pharmaceutical interventions(NPIs),the increas-ing number of confirmed cases slowed down in many countries.However,the lifting of control measures by the government and the public’s loosening of precautionary behaviors led to a sudden increase in cases,arousing deep concern across the globe.arousing deep concern across the globe.This study evaluates the situation of the COVID-19 pandemic in countries and territories worldwide from January 2020 to February 2021.According to the time-varying reproduction number(R(t))of each country or territory,the results show that almost half of the countries and territories in the world have never controlled the epidemic.Among the countries and territories that had once contained the occurrence,nearly half failed to maintain their prevention and control,causing the COVID-19 pandemic to rebound across the world—resulting in even higher waves in half of the rebounding countries or territories.This work also proposes and uses a time-varying country-level transmission risk score(CTRS),which takes into account both R(t)and daily new cases,to demonstrate country-level or territory-level transmission potential and trends.Time-varying hierarchical clustering of time-varying CTRS values was used to successfully reveal the countries and territories that contributed to the recent aggravation of the global pandemic in the last quarter of 2020 and the beginning of 2021,and to identify countries and territories with an increasing risk of COVID-19 transmission in the near future.Furthermore,a regression analysis indicated that the introduction and relaxation of NPIs,including workplace closure policies and stay-at-home requirements,appear to be associated with recent global transmission changes.In conclu-sion,a systematic evaluation of the global COVID-19 pandemic over the past year indicates that the world is now in an unexpected situation,with limited lessons learned.Summarizing the lessons learned could help in designing effective public responses for constraining future waves of COVID-19 worldwide.展开更多
Since late 2019,the beginning of coronavirus disease 2019(COVID-19)pandemic,transmission dynamics models have achieved great development and were widely used in predicting and policymaking.Here,we provided an introduc...Since late 2019,the beginning of coronavirus disease 2019(COVID-19)pandemic,transmission dynamics models have achieved great development and were widely used in predicting and policymaking.Here,we provided an introduction to the history of disease transmission,summarized transmission dynamics models into three main types:compartment extension,parameter extension and population-stratified extension models,highlight the key contribution of transmission dynamics models in COVID-19 pandemic:estimating epidemiological parameters,predicting the future trend,evaluating the effectiveness of control measures and exploring different possibilities/scenarios.Finally,we pointed out the limitations and challenges lie ahead of transmission dynamics models.展开更多
基金supported by grants from the Jiangsu Birth Defects Intervention Program(No.JS200302)the Natural Science Foundation of Jiangsu Province(No.BK2008501)
文摘We sought to determine risk factors associated with fetal macrosomia and to explore the long-term consequence of infant macrosomia at the age of 7 years.A prospective population based cohort study was designed to examine the associations between maternal and perinatal characteristics and the risk of macrosomia.A nested case-control study was conducted to explore the long-term health consequence of infant macrosomia.The mean maternal age of the macrosomia group was 24.74±3.32 years,which is slightly older than that in the control group(24.35±3.14 years,P = 0.000).The mean maternal body mass index(BMI) at early pregnancy was 22.75±2.81 kg/m 2,which was also higher than that in the control group(21.76±2.59 kg/m 2,P = 0.000).About 64.6% of macrosomic neonates were males,compared with 51.0% in the control group(P = 0.000).Compared with women with normal weight(BMI:18.5-23.9 kg/m 2),women who were overweight(BMI:24-27.9 kg/m 2) or obese(BMI ≥ 28 kg/m 2),respectively,had a 1.69-fold(P = 0.000) and a 1.49-fold(P = 0.000) increased risks of having a neonate with macrosomia,while light weight(BMI<18.5 kg/m 2) women had an approximately 50% reduction of the risk.Furthermore,macrosomia infant had a 1.52-fold and 1.50-fold risk,respectively,of developing overweight or obesity at the age of 7 years(P = 0.001 and P = 0.000).Older maternal age,higher maternal BMI at early pregnancy and male gender were independent risk factors of macrosomia.Macrosomic infant was associated with an increased predisposition to develop overweight or obesity at the beginning of their childhood.
基金supported by the National NaturalScience Foundation of China(No.81373102 to YZ,No.61301251 to LG)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.12KJB310003)+2 种基金Priority Academic Program Development of Jiangsu Higher Education Institution(PAPD)Flagship Major Development of Jiangsu Higher Education Institutionssupported by the Qing-lan Project of Jiangsu Province and the Excellent Young Teach Project of Nanjing Medical University
文摘Expression of estrogen receptors is correlated with breast cancer risk,but inconsistent results have been reported.To clarify potential estrogen receptor(ESR)-related breast cancer risk,we analyzed genetic variants of ESR1 in association with breast cancer susceptibility.We performed a meta-analysis to investigate the association between rs2234693,rs1801132,and rs2046210(single nucleotide polymorphisms of ESR1),and breast cancer risk.Our analysis included 44 case-control studies.For rs2234693,the CC genotype had a higher risk of breast cancer compared to the TT or CT genotype.For rs2046210,the AA,GA,or GA + GG genotype had a much higher risk compared to the GG genotype.No significant association was found for the rs 1801132 polymorphism with breast cancer risk.This meta-analysis demonstrates association between the rs2234693 and rs2046210 polymorphisms of ESR1 and breast cancer risk.The correlation strength between rs2234693 and breast cancer susceptibility differs in subgroup assessment by ethnicity.
文摘The outbreak and rapid spread of COVID-19 has become a public health emergency of international concern.A number of studies have used modeling techniques and developed dynamic models to estimate the epidemiological parameters,explore and project the trends of the COVID-19,and assess the effects of intervention or control measures.We identified 63 studies and summarized the three aspects of these studies:epidemiological parameters estimation,trend prediction,and control measure evaluation.Despite the discrepancy between the predictions and the actuals,the dynamic model has made great contributions in the above three aspects.The most important role of dynamic models is exploring possibilities rather than making strong predictions about longer-term disease dynamics.
基金supported by the National Natural Science Foundation of China (82041024 to Feng Chen, 82041026 to Hongbing Shen, and 81973142 to Yongyue Wei)partially supported by the Bill&Melinda Gates Foundation (INV-006371)
文摘The occurrence of coronavirus disease 2019(COVID-19)was followed by a small burst of cases around the world;afterward,due to a series of emergency non-pharmaceutical interventions(NPIs),the increas-ing number of confirmed cases slowed down in many countries.However,the lifting of control measures by the government and the public’s loosening of precautionary behaviors led to a sudden increase in cases,arousing deep concern across the globe.arousing deep concern across the globe.This study evaluates the situation of the COVID-19 pandemic in countries and territories worldwide from January 2020 to February 2021.According to the time-varying reproduction number(R(t))of each country or territory,the results show that almost half of the countries and territories in the world have never controlled the epidemic.Among the countries and territories that had once contained the occurrence,nearly half failed to maintain their prevention and control,causing the COVID-19 pandemic to rebound across the world—resulting in even higher waves in half of the rebounding countries or territories.This work also proposes and uses a time-varying country-level transmission risk score(CTRS),which takes into account both R(t)and daily new cases,to demonstrate country-level or territory-level transmission potential and trends.Time-varying hierarchical clustering of time-varying CTRS values was used to successfully reveal the countries and territories that contributed to the recent aggravation of the global pandemic in the last quarter of 2020 and the beginning of 2021,and to identify countries and territories with an increasing risk of COVID-19 transmission in the near future.Furthermore,a regression analysis indicated that the introduction and relaxation of NPIs,including workplace closure policies and stay-at-home requirements,appear to be associated with recent global transmission changes.In conclu-sion,a systematic evaluation of the global COVID-19 pandemic over the past year indicates that the world is now in an unexpected situation,with limited lessons learned.Summarizing the lessons learned could help in designing effective public responses for constraining future waves of COVID-19 worldwide.
基金the National Natural Science Foundation of China(No.82041024 to F.C.,81973142 to Y.W.)the Bill&Melinda Gates Foundation(Investment ID:INV-006371).
文摘Since late 2019,the beginning of coronavirus disease 2019(COVID-19)pandemic,transmission dynamics models have achieved great development and were widely used in predicting and policymaking.Here,we provided an introduction to the history of disease transmission,summarized transmission dynamics models into three main types:compartment extension,parameter extension and population-stratified extension models,highlight the key contribution of transmission dynamics models in COVID-19 pandemic:estimating epidemiological parameters,predicting the future trend,evaluating the effectiveness of control measures and exploring different possibilities/scenarios.Finally,we pointed out the limitations and challenges lie ahead of transmission dynamics models.
