Respiratory distress syndrome (RDS) is one of the commonest complication preterm neonates suffer and accounts for a significant morbidity and mortality in low and middle income countries (LMICs). Addressing RDS is therefore crucial in reducing the under 5 mortality in LMICs. This study aimed at describing early outcomes  of preterm neonates with RDS and identify factors associated with the outcomes among neonates admitted at Muhimbili national hospital, Tanzania.P-value less than 0.05 were considered as significant.Between October 2019 and January 2020 we conducted a prospective study on 246 preterm neonates with RDS at Muhimbili National Hospital. These were followed up for 7 days. We generated Kaplan–Meier survival curve to demonstrate time to death. We performed a cox regression analysis to ascertain factors associated with outcomes. The risk of mortality was analyzed and presented with hazard ratio. Confidence interval of 95% and p = 0.015), lack of antenatal steroids (AHR = 4.59 (1.11–18.9), CI95%; p = 0.035), 5th minute APGAR score of < 7 (AHR = 2.18 (1.33–3.56), CI95%; p = 0.002) and oxygen saturation < 90% at 6 hours post admission (AHR = 4.45 (1.68–11.7), CI95%; p = 0.003).Of the 246 study participants 51.6% were male. The median birth weight and gestational age of participants (Inter-Quartile range) was 1.3 kg  and 31 weeks  respectively. Majority (60%) of study participants were inborn. Only 11.4% of mothers of study participants received steroids. Of the study participants 49 (20%) received surfactant. By day 7 of age 77/246 (31.3%) study participants had died while the majority of those alive 109/169 (64.5%) continued to need some respiratory support. Factors independently associated with mortality by day 7 included birth weight of < 1500 g (AHR = 2.11 (1.16–3.85), CI95%; Our study reports that there was high mortality among preterm neonates admitted with RDS mainly occurring within the first week of life. Preterm neonates with very low birth weight (VLBW), whose mother did not receive antenatal steroid, who scored < 7 at 5th minute and whose saturation was < 90% at 6 hours were at higher risk of dying. There is need to scale up antenatal corticosteroids, neonatal resuscitation training and saturation monitoring among preterm neonates with RDS. Respiratory distress syndrome (RDS) is among the major complications of preterm birth . The risThe clinical signs of RDS manifest within the first minutes or hours after birth and progress over the first 48 to 72 hours thereafter, begins to resolve. The subsequent improvement coincides with increased production of endogenous surfactant resulting in resolution of symptoms by one week of age .The diagnosis of RDS is based on clinical findings of a preterm infant with onset of progressive respiratory distress shortly after birth and a characteristic chest radiograph, which demonstrates low lung volume and diffuse reticulogranular ground glass appearance with air bronchograms .The management of RDS has evolved over the past few decades in the developed countries , 6. DespThe findings of previous studies in the globe revealed that several factors are associated with mortality in preterm neonates with RDS. These include: gestational age –12, birtDespite interventions recommended by WHO to improve outcome of preterm neonates, mortality of preterm neonates in low- and middle-income countries remains significant. Tanzania is among countries with high preterm births and hence of RDS. Neonatal mortality contributes a significant proportion to under 5 deaths. We conducted this study to ascertain outcome of preterm neonates admitted with RDS and identifying factors associated with the outcomes. This knowledge is important in identifying area needing improvement to reduce preterm neonatal deaths and hence under 5 deaths.A prospective study was conducted at the newborn intensive care unit (NICU) of Muhimbili National Hospital (MNH), Dar-es-Salaam, Tanzania. MNH is a national tertiary level referral hospital for Tanzania and a teaching hospital for Muhimbili University of Health and Allied Sciences. Neonatal unit is located at the maternity block, second floor, it has two wards one for preterm (ward 37) and another for term babies (ward 36). In preterm ward there are 4 cubes, with a total bed capacity of 60 beds. At the time of the study the unit has wall mounted oxygen, 3 mechanical ventilators, 5 radiant warmers, 5 wall cardiac monitors, 5 diamedic continuous positive airway pressure (CPAP), 10 high flow CPAP and 20 infusion pumps. It has well trained staffs for premature care, 7 specialist, 3 registered medical officers, 3–5 Paediatric resident’s, minimum of 4 intern medical doctors and well-trained nurses. MNH has approximately 10,000 neonates born per year both term and preterm. Admissions in preterm unit is approximately 4–10 babies per day with monthly admission rate of 120–280 neonates and an annual admission rate of 1440–3360 neonates, of which RDS is one of the admission diagnoses. MNH neonatal unit therefore was selected purposively because most preterm infants with RDS are admitted here.Inborn preterm neonates are received by midwives in the delivery rooms and transferred immediately to NICU. Delayed cord clamping is hardly observed for preterm infants and no CPAP is provided in the delivery rooms.Preterm neonates receive intravenous fluids, antibiotics, and aminophylline. They are cared for on open radiant warmers with on many occasions one warmer hosting 2-3infants. Preterm neonates with SAS score of > 3 are commenced on CPAP with blended oxygen but not with heated air. Infants needing < 30% oxygen with SAS score < 3 are transitioned to nasal prong oxygen 2 l/min and gradually weaned off. Surfactant is given to infants with severe distress whose parents can purchase.Tanzania is a lower-middle-income country, it has an estimated population of about 60 million people. Health services in the United Republic of Tanzania are delivered through a decentralized system. Access to health care in Tanzania is still a challenge especially in women. Health insurance coverage is still low approximately 32%.All preterm neonates < 24 hours old with clinical signs of RDS. Clinical signs of RDS which starts in < 6 hours after birth were tachypnea, nasal flaring, expiratory grunting, intercostal, subcostal, and subxiphoid retractions, and cyanosis.The outcome for this study was Death or Survival at 7 days of life.In this study, maternal and Preterm neonates variables were considered. Antenatal steroid, Place of delivery, Mode of delivery, pPROM> 18 hours, maternal fever. Gestational age, Birth weight, Sex, APGAR score at 5th minute, Age at admission, SAS at admission and 6 hours, Oxygen saturation at commence of care and at 6 hours, Body temperature, random blood sugar, Surfactant.Between October 2019 and January 2020, all preterm neonates < 24 hours of age whose respiratory distress commenced < 6 hours after birth were enrolled. New Ballard score  was usedAll study variables were obtained from maternal history, antenatal cards and NICU records. These were entered in the data sheet.Daily follow-up was done, vital signs and oxygen saturations were observed daily or obtained from the nursing charts.p value < 0.05 were entered in the multivariable Cox regression model to identify and quantify predictors of deaths while controlling for potential confounder. The risk of mortality was explored and presented with hazard ratio and 95% confidence interval. P-value less than 0.05 was considered as significant.The data was analysed using SPSS software packages version 23.0. Frequency distribution and Kaplan–Meier survival curves were used to show pattern of death in 7 days for birth weight and gestational age. Independent and adjusted relationships of different predictors with preterm neonates’ survival were assessed with Cox regression model. Factors associated with mortality in crude model with a The median birth weight of participants (Inter-Quartile range) was 1.3  kilograms. Of the study participants 79/246 (32%) were small for gestational age (SGA). The median gestational age (Inter-Quartile range) was 31  weeks. The median age of participants (Inter-Quartile range) was 1.3  hours at admission and median age at start of respiratory support (Inter-Quartile range) was 1.66  hours.Most 240 (97.6%) preterm neonates presented with respiratory rate > 60breath/minute and nasal flaring at recruitment. Other clinical presentation were subcostal retractions 202 82.1%) and grunting 131 (53.3%).  deaths occurred in the first 72 hours. Mortality among preterm neonates with birth weight < 1500 g was 40% and those with birth weight ≥ 1500 g was 17%. Among preterm neonates who were alive in the first week of life, 109 (64.5%) were still in need of respiratory support.P = 0.002) indicating that having a GA above 32 weeks was significantly associated with better survival  indicating that those with birth weight ≥ 1500 g were more likely to survive , CI95%; p = 0.015), preterms whose mother’s lack antenatal steroids (AHR = 4.59 (1.11–18.9), CI95%; p = 0.035), preterm neonates with APGAR score at 5th minute of 4–7 (AHR = 2.18 (1.33–3.56), CI95%; p = 0.002) and preterm neonates with oxygen saturation < 90% at 6 hours post admission (AHR = 4.45 (1.68–11.7), CI95%; p = 0.003), , whose mother did not receive antenatal steroid, who scored APGAR < 7 at 5th minute and whose oxygen saturation was < 90% at 6 hours were at higher risk of dying.The mortality rate of preterm neonates with RDS have a wide variation ranging from 6.5 to 88% , 28–30. In this study birth weight was found to be independently associated with outcome death. Mortality was higher among neonates with weight < 1500 g (40%) compared to those > 1500 g (17%), this might be because those < 1500 g were more premature and had more severe disease than those > 1500 g .p = 0.003). This is similar to one study done by Sathenahalli et al. [We observed that preterm neonates with low oxygen saturation < 90% were at higher risk for mortality (AHR = 4.45 (1.68–11.7), CI95%; i et al.  Infants i et al. .Infants with RDS and Apgar score at 5th minute of 4–7 had higher mortality rate of 40% compared to those with Apgar score at 5th minute of more than 7 which was 25.6%. Thus, low Apgar score at 5th minute was an independent predictor of mortality. This finding is comparable to other two studies which showed increase in RDS and mortality in preterm babies with low Apgar score , 16. ThiOnly 2/28 (7.1%) study participants whose mother received steroids died and 75/200 (34.4%) of those whose mothers did not receive steroids died. These findings were comparable with a study done in India by Palod P. H et al. . SimilarPreterm neonates who received surfactant had less mortality; however, it was not an independent predictor of mortality. These finding are similar to the study done by Niknafs et al.  which shWe still observe high mortality in our setting (LMIC) as compared to high income countries. Our setting is equipped but overwhelmed by number of premature babies delivered with complications, and thus compromising quality of care and availability of resources. Low uptake of ACS as demonstrated from our findings it talks about our poor health care access as well as lack of surfactant due to cost implication which parents need to cover while most of our mothers can’t afford.Lack of chest radiography to confirm the diagnosis, severity, and possible complications such as air leaks was lacking, and this would affect the interpretation of some findings.All preterm neonates are managed empirically with antibiotics for presumed sepsis without appropriate investigations hence difficulty to delineate between sepsis and RDS.Lack of routine cranial scan on these vulnerable infants made it difficult to ascertain other contributors to poor outcome including death.Mortality of premature neonates with respiratory distress syndrome (RDS) admitted at MNH was 31.3% in the first week of life. Preterm neonates with very low birth weight (VLBW), whose mother did not receive antenatal steroid, who scored < 7 at 5 min and whose saturation was < 90% at 6 hours were at higher risk of dying.Tailored interventions addressing risk factors should be devised to improve the preterm neonate’s survival in the study area. Close attention to early stabilization and improve preterm care may further reduce the mortality associated with this disorder especially to those with low birth weight and lower gestational age.


The aim of this study was to investigate whether maternal exposure to air pollutants  in Suzhou city from 2015 to 2019 were obtained. The distribution of demographic characteristics of children with birth defects and exposure to air pollutant concentrations during different pregnancy periods were analyzed, Chi-square test was used to analyze whether there were statistical differences in the distribution of parturient woman age, pregnant weeks, times of pregnancy, as well as fetal sex and birth weight among children with congenital heart defects and other defects. Logistic regression model was further established to calculate the adjusted odds ratios (aORs) and 95% confidence intervals (CI) for the association between exposure to these ambient air pollutants during pregnancy and CHDs.Based on the birth defect monitoring system of Suzhou city and the Environmental Health Department of Suzhou CDC, the birth defect monitoring data and concentrations of five air pollutants  per a 10 μg/m3 change in PM2.5 concentration. Maternal NO2 exposure was significantly associated with CHDs in first trimester .A total of 5,213 infants with birth defects were recruited in this study from 2015 to 2019, the top five birth defects in Suzhou were syndactyly, congenital heart disease, ear malformation, cleft lip and palate, and hypospadias, and the proportion of congenital heart disease increased. The level of maternal exposures (mean ± sd) was highest in first trimester amongst pregnant women in Suzhou city. Compared to other birth defects, we observed significant increasing associations between PM2.5 and NO2 is thought to increase the risk of CHDs, but comprehensive description of these associations will be needed in future studies.Our study contributes to explore the current state of Suzhou air quality and the association between maternal air pollution exposure and congenital heart defects. Exposure to PM Congenital heart defects (CHDs) is a serious structural abnormality of the large blood vessels in the heart or chest cavity. It is one of the most common types of birth defects in the world, as well as the leading cause of infant death and physical disability, which has a significant impact on individuals, families and society . There w3, CO, SO2, NO2, PM) may contribute individually or in combination to adverse pregnancy outcomes like low birth weight (LBW), preterm birth (PTD) and congenital abnormalities of small gestational age (SGA) , sulfur dioxide (SO2), carbon monoxide (CO), particulate matter with aerodynamic diameter smaller than 10 μm (PM10) and 2.5 μm (PM2.5). In addition, we estimated the timing of susceptibility during pregnancy.Environmental pollutants have been considered as one of the important causes of congenital malformations. The role of prenatal exposure to ambient air pollution on birth defects has gradually become a research hotspot . “Barkerge (SGA) , 7. Prevnewborns , 9. In cnewborns –12. TherOur data on birth defects were extracted from the birth defect monitoring sub-module system in the Suzhou Maternal and Child Health Monitoring Manual during 2015 to 2019. This includes records from perinatal babies born between 28 weeks' gestation and 7 days after birth (including live births and stillbirths), reported by midwifery agencies. The diagnosis of Birth Defects was performed by qualified doctors of medical institutions based on the “International Statistical Classification of Diseases and Related Health Problems, Tenth Edition” (ICD-10). For neonates classified as “congenital heart defects to be confirmed”, we followed up until 3 months after birth and made a supplementary report according to the follow-up results to avoid omissions. “Birth Defects Registration Card” was used to collect information including date of birth, gestational age, infant sex, maternal age, gravidity, and parity. The data included mothers living in Suzhou during pregnancy, according to maternal residential address. Excluding pregnant women whose permanent residence outside Suzhou in the Maternal and Child Health Monitoring Manual, a total of 5,213 infants with birth defects were recruited in this study, of which 1,039 infants were diagnosed with CHDs. This study was approved by the Ethics committee of Suzhou Municipal Hospital . In the final database, only mothers and newborns numbers were listed. All personal information was kept confidential.We divided the entire pregnancy into three trimesters. Daily exposures were averaged over three exposure windows: the first trimester (1–13 + 6 weeks gestation), the second trimester (14–27 + 6 weeks gestation), the third trimester (28 weeks to delivery) , sulfur dioxide (SO2), carbon monoxide (CO), particulate matter with aerodynamic diameter smaller than 10 μm (PM10) and 2.5 μm (PM2.5) in Suzhou city. Daily 24–h average concentrations of these pollutants were obtained from 11 national air quality monitoring stations and 11 provincial air quality monitoring stations during 2014–2019 that included the period of maternal pregnancy in the present study. These air quality monitoring stations are evenly distributed in 10 districts and counties in Suzhou, including two in Zhangjiagang, two in Changshu, two in Taicang, three in Kunshan, three in Wujiang, two in Wuzhong, two in Xiangcheng, one in Gusu, two in Suzhou industrial park, and three in Suzhou National Hi-Tech District.3.Firstly, the average daily concentration was calculated by the obtained daily concentrations from the 22 monitoring stations. Exposure during the first, second and third trimesters was, respectively, calculated as the average of the monthly mean concentrations of NO2, SO2, CO,PM10, and PM2.5 during the first to third month, the fourth to sixth month, and the seventh to the last month of pregnancy. The concentrations of the pollutants were expressed as μg/mP < 0.05 was considered statistically significant.The database was analyzed using SPSS 17.0 software . Potential confounding variables are obtained from the “Birth Defects Registration Card” including gestational age, infant sex, maternal age, gravidity, and parity. The date of conception was defined as the 14th day after the date of the last menstruation, which was classified into spring (March to May), summer (June to August), autumn (September to November), and winter (December to February) according to the climate characteristics in the city. Categorical variables are presented as numbers and frequencies while continuous variables are represented by mean ± standard deviation. Distributions of ambient air pollutant concentrations were presented by quartile and interquartile range (IQR) averaged during different trimester of pregnancy. Pearson correlation between exposures to air pollutants and between trimesters was analyzed. Chi-square test was performed to examine statistically significant differences in social demographic characteristics between infants with CHDs and infants with other BDs. 3 increase in concentration ultimately for each air pollutant.We used multiple logistic regression models to evaluate the association between maternal exposure to ambient air pollution during different trimesters and risk of congenital heart defects by adjusting for potential confounding covariates. CHDs was the dependent variable, and the individual exposure concentration of air pollutants during different trimesters of pregnancy were the independent variables. Exposure variables were included in the models as continuous variables, with separate models for each pollutant. Multi-pollutant models were further performed to adjust the effects of other air pollutants. Corresponding odds ratio (OR) and 95% confidence interval (95% CI) were calculated after important covariates were controlled. Results are presented as the change in outcome every 10 mg/mAll deliveries were examined by a physician after birth and a professional doctor or nurse at each registered hospital was required to complete the Birth Defects Registration Card. Quality control measures were monitored regularly in respective hospitals, monthly at the county level and every half year at the municipal level in order to ensure the authenticity of the reported information. The quality requirements for birth defect monitoring data included: 100% completion rate of form, form items error rate < 1%, input error rate < 1%, and a rate of missed birth defects < 1%.P < 0.05). There were no statistically differences for total previous live births and season of conception, which were no longer included in the Logistic regression model as shown in There were statistically significant differences in the distribution of maternal age, number of pregnancies, as well as infant gender and birth weight among children with congenital heart defects and others  was highest in the first trimester of pregnancy. The daily average concentrations of PM10, PM2.5, NO2, CO, SO2 were 71.88, 48.79, 49.11, 849.62, 15.61 μg/m3, respectively. Descriptive statistics of maternal ambient air pollution exposure during different gestation are shown in 2.5, we observed a significant association with BDs for every 10 μg /m3 increase in concentration particularly in the second  and third  trimester of pregnancy. But the risk of congenital heart disease was 1.318 (95% CI: 1.210–1.435) for every 10 μg/m3 increase in NO2 in the first trimester. We did not observe significant association between PM10 and CHDs. More specifically, CO and SO2 were significant negatively correlated to CHDs in all trimesters of pregnancy.Due to the effective implementation of prevention measures for primary and secondary birth defects, perinatal neural tube defects, congenital hydrocephalus and other fatal or severely disabling birth defects have continued to decline, and are no longer the main types of birth defects. Our results showed that congenital heart disease has become the major birth defect in recent years. One of the most likely reasons is that the congenital heart disease screening program for children aged 0–3 years was carried out as a government free practical project in Suzhou. The expansion of the screening population for congenital heart disease has resulted in an increase in the detection rate of mild congenital heart disease.With the rapid development of urbanization and industrialization, most parts of China are suffering from serious air pollution in the past few decades. Suzhou is located in central Yangtze River Delta, suffering from severe air-pollution in recent years due to fast growing economic development. The “2016 Report on the State of the Environment in China” revealed that air quality index (AQI) of Suzhou ranked 44th in 74 survey cities. It has gradually become an important public health problem that cannot be ignored. Some scholars have observed that alveolar ventilation rate of pregnant women increased and the air pollutants inhaled may be much higher than those non-pregnant women . As a re2.5 increased the risk of CHDs. However, the effect might be influenced by the period of exposure during pregnancy. Existing studies have generally agreed that maternal exposure to environmental pollutants is one of the high risk factors for premature and low birth weight infants  and 1.022 (95% CI: 1.015–1.029), for every 1 μg/m3 increase in PM2.5 in the second and third trimester, respectively. Our studies thus revealed that adverse effects of environmental pollutants may have cumulative effects, and the susceptibility window may not be directly consistent with the critical stage of fetal heart development. Findings from a study in Hefei also supported this hypothesis, researchers assessed the effect of weekly air pollutants exposure on CHDs to fully reflect the sensitivity of the specific window, results showed that exposure to air pollutants  increase the risk of CHDs and the main susceptible exposure windows are second and third trimester of pregnancy  deposit more in the upper bronchus, while smaller particles (PM2.5) deposit more in the deep lung with a higher surface area to mass ratio, which may lead to enhanced toxicity.Most early studies measured the average level of pollutants within 3–8 weeks after pregnancy to determine the association between exposure and the incidence of congenital heart disease when analyzing the susceptibility window period of exposure to environmental pollutants during pregnancy , 17–19.  studies . Possibl2.5 exposure and CHDs when the type of congenital heart defects was subdivided. The results of National Birth Defects Prevention Study (NBDPS) in the United States revealed that exposure to fine particulate matter was positively associated with hypoplastic left heart syndrome (HLHS) and negatively associated with atrial septal defects . Written informed consent from the participants was not required for this study in accordance with the local legislation and institutional requirements.LS: collecting data, data analysis, paper writing, and quality control. QW: collecting data and quality control. HW, JL, and YS: collecting data. RX, TG, XP, and BZ: data analysis. All authors contributed to the article and approved the submitted version.


National guidance (Saving Babies Lives Care Bundle Version 2 (SBLCBv2) Element 5) was published in 2019, with the aim to standardise preterm care in England. We plan to identify how many preterm birth surveillance clinics there are in England, and to define current national management in caring for women who are both asymptomatic and high-risk of preterm birth, and who arrive symptomatically in threatened preterm labour, to assist preterm management both nationally and internationally.An online survey comprising of 27 questions was sent to all maternity units in England between February 2021 to July 2021.Data was obtained from 96 units. Quantitative analysis and free text analysis was then undertaken. We identified 78 preterm birth surveillance clinics in England, an increase from 30 preterm clinics in 2017. This is a staggering 160% increase in 4 years. SBLCBv2 has had a considerable impact in increasing preterm birth surveillance clinic services, with the majority (61%) of sites reporting that the NHS England publication influenced their unit in setting up their clinic. Variations exist at every step of the preterm pathway, such as deciding which risk factors warrant referral, distinguishing within particular risk factors, and offering screening tests and treatment options.While variations in care still do persist, hospitals have done well to increase preterm surveillance clinics, under the difficult circumstances of the COVID pandemic and many without specific additional funding.The online version contains supplementary material available at 10.1186/s12884-023-05388-w. Around 40% of neonatal deaths globally are due to prematurity (birth before 37 weeks’ gestation) . In 2020The Department of Health is understandably keen to reduce the preterm birth rate in the UK to 6% by 2025 , which hPrevious surveys examining preterm birth surveillance and prevention practice in the United Kingdom have shown wide variations of care , 9. The A more focussed survey to evaluate the impact of the new guidelines, SBLCBv2, was therefore performed. We plan to identify how many preterm birth surveillance clinics there are in England, and to define current national management in caring for women who are both asymptomatic and high-risk of preterm birth and who arrive symptomatically in threatened preterm labour, to assist preterm management both nationally and internationally.An online survey comprising of 27 questions ).The data was downloaded onto an Excel spreadsheet. Free text questions where numerical answers were given were standardised. If a site gave a range of numbers as an answer, then the mean of this range was taken to produce a single number. In cases where the mean would be inappropriate then the number was rounded up . Two sites did not provide their birth rate, so this information was entered by the research team using information taken from CQC reports.The project was registered with King’s College London Research Governance Office .This project was undertaken as part of the IMPART study  [n = 2), and duplicate responses, (n = 6), data was obtained from 96 units . This achieved an overall response rate of 51% (96/187), with a response rate of 61% (94/155) from obstetric led intrapartum units, which is similar to the 2017 questionnaire response rate.After removing blank responses  reported that they had a preterm birth surveillance clinic . Overall, 28% (27/96) have a Level 1/ Special Care Baby Unit (for babies born over 32 weeks’ gestation), 38% (36/96) have a Level 2/ Local Neonatal Unit (for babies born 28–32 weeks’ gestation) and 34% (33/96) have a Level 3/ Neonatal Intensive Care Unit (for babies born before 28 weeks’ gestation). The two units who referred women to another hospital for preterm surveillance care antenatally, have less than 2,800 births per year and both have Level 1/ Special Care Baby Units.Most preterm birth surveillance clinics are run weekly 82%), fully funded by the NHS (91%) and led by an NHS consultant who is principally obstetrics based (82%)  accept women who had a previous delivery by caesarean section at full (10 cm) cervical dilatation  reported that SBLCBv2 influenced their unit in setting up their preterm birth surveillance clinic. Meanwhile 38% (29/77) said SBLCBv2 did not influence their unit’s clinic, and one site said they did not know. Most sites , felt their referral criteria had changed because of SBLCBv2, 34% of sites (29/85) said their referral criteria had not changed as a result SBLCBv2, and one site did not know. Of the sites that gave their clinic’s referral criteria, 36% (31/86) included all the risk factors that are outlined in the SBLCBv2 ‘’suggested risk assessment’’ for preterm birth [1%, 47/77Nearly half of sites 47%, 40/86) reported that they sometimes offered asymptomatic women a prophylactic vaginal cerclage on history alone  felt that SBLCBv2 helped. Some, 22% (16/73) felt that having someone motivated (either a midwife or obstetrician) helped. Some, 14% (10/73) noted external support . Of those that stated this, 3 sites mentioned St Thomas’ Hospital, London specifically, 3 sites mentioned emailing NC (author), 1 site mentioned Liverpool Women’s Hospital and 1 site mentioned Leeds Teaching Hospitals NHS Trust. Eight sites, (11%) felt nothing particularly helped. Four sites (5%) highlighted the aid of additional funding. The form of this funding varied . Four sites felt strong managerial support enabled them to successfully set up their clinic, and 2 sites felt that good practical facilities  helped.Seventy-two sites left free text comments regarding what hindered implementation of their clinic. Over half of respondents  highlighted capacity issues. These ranged from too many referrals to cope with, a lack of appropriate clinical space, a lack of staff, and/or a lack of resources. This included 19% (14/72) who specifically mentioned a lack of clinicians able to scan and/or lack of scanning equipment. Several sites  required a clinic midwife. Some  highlighted absent inclusion in job roles and 3% (2/72) mentioned delays in business case approvals. This leads to sites unable to implement ‘in full accordance with SBLCBv2’. Three sites felt their small numbers of appropriate women created difficulty in assigning a clinical lead, and pragmatically included these women in their general obstetric antenatal clinic. COVID was mentioned  as hindering implementation. One site felt ambiguity on how sites should care for these women, partly due to guidance overload. Meanwhile 29% (21/72) felt nothing hindered set up.Full results regarding the impact of preterm birth surveillance clinics and caring for women who arrive in threatened preterm labour, can be seen in Supporting Information Additional file We have now identified 78 preterm birth surveillance clinics in England, an increase from 30 preterm clinics in 2017 . This isSBLCBv2 has had a considerable impact in increasing preterm birth surveillance clinic services, with the majority (61%) of sites reporting that the NHS England publication influenced their unit in setting up their clinic. Most sites, 65%, also felt that their referral criteria had changed because of SBLCBv2.The overall response rate was 51%, with a response rate of 61% from obstetric led intrapartum units. We feel we achieved effective geographical spread and representation from sites across England, including a range of units with different delivery rates, and units with a variety of neonatal levels. These results could assist preterm management both nationally and internationally.Often units that provide obstetric-led intrapartum care manage higher risk pregnancies antenatally and are more likely to have antenatal preterm birth services. This may be one reason why we did not receive a high response from units that provide maternity-led intrapartum care and/or antenatal/community care. However, it was important that the questionnaire was sent to individual units, not hospital trusts. This meant we could understand how units work both individually and how they interact  with other units in their local area.However, referrals from other units did not include women who purposefully booked their pregnancy at a unit with a good reputation for preterm birth surveillance care. The continuing expansion of online support groups and awareness of risk factors means we cannot underestimate the impact of women rightfully influencing their own care in this way, especially in densely populated cities where a variety of hospitals can easily be accessed.While SBLCBv2 has succeeded in promoting preterm surveillance care and clinics, it has not achieved standardised care across England. Variations in practice still exist at every step of the preterm pathway, such as deciding which risk factors warrant referral, distinguishing within particular risk factors, and offering screening tests and treatment options. The 2017 questionnaire found three common risk factors across all clinics . This questionnaire found only one common risk factor across all clinics (which was having a previous spontaneous preterm birth or mid-trimester loss).suggested risk assessment, which 36% of clinics seem to be following. However, SBLCBv2 also expressed that alternative risk assessments that have been agreed with site’s local commissioners could be equally appropriate meaning remaining sites may be working under an agreed alternative.This could be due to different reasons, one of which being the non-prescriptive nature of SBLCBv2. For example, SBLCBv2 provides a Variations in care could be due to capacity issues, which was highlighted by 56% of respondents as hindering implementation. This has led to some operating a preterm surveillance clinic with a slimmed-down referral criteria that do not cover all the risk factors mentioned in SBLCBv2.A lack of, or unclear, evidence bases, could also lead to these variations of care which was highlighted by respondents. The C-STITCH study  results The questionnaire demonstrated the pragmatic capability of sites in setting up new preterm birth surveillance pathways. Preterm surveillance can be just as effective situated within an antenatal clinic, rather than a standalone specific preterm surveillance clinic – which sites with smaller numbers noted in the free text comments. Nearly a fifth (14%) noted how collegial external support helped them implement their clinic, highlighting the importance of networking between local sites and more experienced sites being open to sharing their resources such as protocols and guidelines.Biomarker tests, specifically quantitative fetal fibronectin, are the most popular tool for assessing symptomatic women in threatened preterm labour. One site did highlight how they did not have 24/7 access to cervical length scanning, which could explain why only 38% of sites routinely undertake cervical length scans on women arrive in threatened preterm labour. While training clinicians to scan is time consuming, individual cervical length scans are inexpensive compared to biomarker tests.Nearly half (49%) of sites are using the QUiPP App in asymptomatic women, and just over half (51%) in symptomatic women where it is recommended in the majority (78%) of local guidelines. Its popularity may have been boosted by the recent EQUIPTT study –20 and tHospital sites in England have done well to increase preterm surveillance clinics, under the difficult circumstances of the COVID pandemic and many without specific additional funding.Wide variations of preterm care, some at variance with guidelines and the evidence base, in both asymptomatic and symptomatic women, exists. Increased collaboration between sites will hopefully result in more homogenous care.Nearly all clinics (91%) are funded by the NHS, demonstrating the readiness to have this incorporated into mainstream care. Future work (such as the IMPART study ), will uAdditional file 1: Appendix S1. Additional file 2: Appendix S2.


Preterm birth is a global problem with about 12% of births in sub-Saharan Africa occurring before 37 weeks of gestation. Several studies have explored a potential association between vaginal microbiota and preterm birth, and some have found an association while others have not. We performed a study designed to determine whether there is an association with vaginal microbiota and/or placental microbiota and preterm birth in an African setting.Women presenting to the study hospital in labor with a gestational age of 26 to 36 weeks plus six days were prospectively enrolled in a study of the microbiota in preterm labor along with controls matched for age and parity. A vaginal sample was collected at the time of presentation to the hospital in active labor. In addition, a placental sample was collected when available. Libraries were constructed using PCR primers to amplify the V6/V7/V8 variable regions of the 16S rRNA gene, followed by sequencing with an Illumina MiSeq machine and analysis using QIIME2 2022.2.Forty-nine women presenting with preterm labor and their controls were enrolled in the study of which 23 matched case–control pairs had sufficient sequence data for comparison. Lactobacillus was identified in all subjects, ranging in abundance from < 1% to > 99%, with Lactobacillus iners and Lactobacillus crispatus the most common species. Over half of the vaginal samples contained Gardnerella and/or Prevotella; both species were associated with preterm birth in previous studies. However, we found no significant difference in composition between mothers with preterm and those with full-term deliveries, with both groups showing roughly equal representation of different Lactobacillus species and dysbiosis-associated genera. Placental samples generally had poor DNA recovery, with a mix of probable sequencing artifacts, contamination, and bacteria acquired during passage through the birth canal. However, several placental samples showed strong evidence for the presence of Streptococcus species, which are known to infect the placenta.The current study showed no association of preterm birth with composition of the vaginal community. It does provide important information on the range of sequence types in African women and supports other data suggesting that women of African ancestry have an increased frequency of non-Lactobacillus types, but without evidence of associated adverse outcomes. Preterm birth (PTB) is defined as birth before 37 completed weeks of gestation . It is oCommunity State Types (CST). Four CSTs have predominantly Lactobacillus, including CST I (Lactobacillus crispatus), CST II (Lactobacillus gasseri), CST III (Lactobacillus iners), and CST V (Lactobacillus jensenii). CST IV comprises strict anaerobes that are often associated with bacterial vaginosis (BV) such as Prevotella, Gardnerella, Sneathia and Atopobium species. In that study, CST I was the most common CST among European women while CST IV was the most common in African American women [Maternal–fetal factors and gene–environment interactions play roles in determining the length of gestation. Some of these factors include African ancestry (in the US and the UK), time of less than six months after a previous pregnancy, low prepartum maternal weight, previous preterm birth, multiplex pregnancy, and maternal infection or vaginal dysbiosis, as well as numerous other known or suspected risk factors , 8. The an women . Other san women , 12. Howan women .Lactobacillus-poor) with PTB that was more pronounced with the presence of Gardnerella or Ureaplasma [Gardnerella, Lactobacillus, and Aerococcus were associated with third trimester preterm birth.Attempts to determine associations between PTB and specific CST types or other designations of vaginal microbiota have also produced differing results. These studies of women with PTB have shown an association of PTB for Caucasian women with an increased Shannon Diversity Index , no correaplasma . A receneaplasma , 14–17 feaplasma . They alData available at the time of initiating the study suggested the presence of a distinct placental microbiota , and alsA better comprehension of the changes in vaginal microbiota during pregnancy could pave the way to predictive diagnostics and focused treatments of the complications associated with the intricate process of pregnancy, labor and birth. In the current study, we used a cohort study to determine whether there was a difference in the microbiota of women presenting with preterm labor compared to full term. In addition, we analyzed the placental microbiota to investigate any potential associations with preterm labor.Aga Khan University Hospital (AKUH) is a 280-bed teaching hospital in Nairobi, Kenya that is accredited by the US-based Joint Commission International and has a full range of obstetric and neonatal services. Approximately 3600 deliveries per year are performed.Pregnant women over the age of 18 years presenting in active labor or with preterm pre-labor rupture of membranes (PPROM) between 26 and 36 6/7 weeks gestation were recruited into the study from March 2018 to March 2019. Patients were excluded if they had medically indicated preterm delivery , antibiotics given more than 24 h prior to enrollment or within the last 4 weeks, cervical cerclage, progesterone supplementation, or HIV infection.A control group of mothers matching the study group as closely as possible for age and parity but presenting in labor at term (37 completed weeks) were enrolled in a 1:1 ratio. We considered a pregnancy to be normal if there were no obstetric or medical complications. Comparisons between the cases (preterm) and controls (term) were made using the Chi-square test and for nonparametric data, the Mann–Whitney test was used.A physician or midwife collected the vaginal samples under direct visualization by swabbing the posterior vaginal fornix 3 to 5 times using sterile Snappable Polystyrene & Viscose Amies Swabs . Samples were stored at -80 ˚C until testing. Genomic DNA extraction was carried out using QIAamp DNA Mini Kit  as per manufacturer’s protocol.The placenta was collected into a clean ziplock bag after delivery and immediately transferred to a dedicated 4 °C refrigerator. Aseptically, a placental sample was cut from both fetal and maternal internal structures to minimize the risk of surface contamination. The samples were transferred to a -80 °C freezer for storage until DNA extraction. DNA extraction was carried out using Dneasy Blood & Tissue Kit  as per manufacturer’s protocol.https://imr.bio/protocols.html#library; in brief, extracted DNA was amplified using PCR, targeting the conserved 16S ribosomal RNA gene. PCR primers amplified the V6/V7/V8 variable regions of the gene, providing over 400 nucleotides to use for species identification. Amplified DNA libraries were sequenced using an Illumina MiSeq machine. Sequencing runs were stored as FASTQ files; vaginal files with at least 2,000 associated reads were retained for subsequent analysis, while the minimum threshold for inclusion of placental samples was 100 reads.Extracted DNA samples were shipped to the Dalhousie Integrated Microbiome Resource  for sequencing. The protocol for sequencing is described at Lactobacillus species for CST I (L. crispatus), II (L. gasseri), III (L. iners), and V (L. jensenii); samples that were dominated BV-associated taxa such as Prevotella, Gardnerella, Sneathia and Atopobium were assigned to CST IV. Tests for significant differences for the control vs. pre-term cohorts were performed using ALDEx2 [p-values were calculated using the QIIME2 “q2-aldex2” plugin’s “effect_plot” command, which computes both the Welch’s t-test and Wilcoxon test with Benjamini–Hochberg correction for multiple hypotheses. Alpha diversity values were computed for all samples using the Faith’s phylogenetic diversity and Shannon entropy measures, rarefaction curves were generated, and group differences between case and control samples were tested by the nonparametric Kruskal–Wallis test.Downstream analysis of DNA sequence data was performed using QIIME2 2022.2 . SequencEthics approval was obtained from the AKUH Ethics Review committee (2017/REC-86). Samples were collected only once during routine evaluation of women presenting with labor. For women in early labor, a written consent was followed by sample collection. For those in active labor, verbal assent was sought during labor for the sample collection; then written consent was sought after delivery. If the written consent was denied, the samples were discarded.n = 94, 95.9%) and did not have a history of prior PTB . The majority of the controls  were delivered vaginally, in comparison with only 18 (36.7%) in the preterm group. In addition, there was a significant difference in the gestational age by days between the two groups. The preterm group had a mean gestational age of 224.6 while the term group had a mean of 276.9 . Rarefaction curves of the vaginal samples suggest sequencing depth was sufficient to capture the majority of abundant taxa (data not shown), and a test of group differences revealed no significant difference in alpha diversity between case and control vaginal samples , L. crispatus , and L. jensenii . An additional six named species were observed in lower abundance, most notably L. vaginalis which was found in 34 individuals but with an average abundance of only 0.16% , Corynebacterium , and Atopobium . Streptococcus was found in 21 samples  with an average abundance of 1.9% and a maximum of 82.75%.At the genus level, 73 out of 74 vaginal samples contained at least a small number of reads that were assigned to L. crispatus), 18 pre-term birth cases and 10 controls; 17 individuals associated with CST III (L. iners), 12 pre-term birth cases and 5 controls; 1 individual associated with CST V (L. jensenii), a control; and 27 individuals associated with CST IV, 13 pre-term birth cases and 14 controls  had a corresponding vaginal abundance of 0.78%; a rectal swab taken from the neonate immediately after birth yielded 99.6% Streptococcus, with the remaining sequence reads assigned to Enterobacteriaceae.However, five placental samples showed evidence of ecovered . The samThe present study is the first gene sequencing‐based vaginal microbiota study to date in Kenya with a case–control design comparing the vaginal microbiota of between women with spontaneous preterm labor with those who went to full term. The major objective was to identify whether there were any vaginal microbiota patterns associated with preterm labor in the Kenya population. We found no difference in CSTs between cases with preterm labor and controls with term labor.Lactobacillus; however, the number of distinct species groupings according to our ASV analysis was small, with the predominant species identified being L. iners and L. crispatus , unclassified sequences, or eukaryotic sequences and the Bradyrhizobium group that are likely contaminants. The very low read recovery in many placental samples may reflect difficulty in recovering viable DNA samples from placental matter. However, the presence of organisms including Lactobacillus and Veillonella suggests the more likely explanation that many “placental” samples are dominated by bacteria acquired during passage through the birth canal. These observations are consistent with reports that suggest placentally derived bacteria  are rare [Streptococcus, which is interesting in light of the common association of S. agalactiae (Group B streptococci) with adverse maternal and neonatal outcomes [Our study also addressed the question of whether a placental microbiome is associated with PTB. This is especially important since some studies have suggested a placental microbiome or an association with certain outcomes , while oare rare –36. Thusoutcomes .In summary, these results contribute to the increasing data that shows that there is a spectrum of diversity in the vaginal microbiota without clear evidence of specific microbiota types that have a correlation with preterm labor. Therefore, an understanding of the variables associated with African ethnicity that contribute to this diverse microbiota has important implications regarding reproductive health outcomes.This study is a fundamental step towards gathering more information on the relationship of vaginal microbiota and PTB which would help us to establish a greater degree of accuracy on future implications of this portentous relationship.


Preterm birth rate depending on parental educational level in recent years has not been surveyed in Japan. In this study, we showed the trend in preterm birth rate depending on parental educational level from 2000 to 2020 by linking data from the Census regarding individuals’ educational level and parents in birth data of the vital statistics. Four types of parental educational level, namely junior high school, high school, technical school or junior college, and university or graduate school, were compared. Slope and relative indexes of inequality for preterm birth by educational level were computed by binomial models. Data on 3,148,711 births and 381,129,294 people were used in the analysis, and data on 777,086 singleton births were used after data linkage. The preterm birth rate (%) for junior high school graduate mothers and fathers was 5.07 and 5.21 in 2020, respectively. Contrarily, the preterm birth rate (%) for parents who graduated from a university or graduate school was 4.24 for mothers and 4.39 for fathers, and the rate tended to increase as educational level decreased, irrespective of parental gender. Results of inequality indexes showed that a statistically significant inequality by parental educational level persisted from 2000 to 2020. Preterm birth rate is one of the representative adverse birth outcomes, and it can affect early neonatal mortality or infant mortality ,2. PretePreterm birth rate is known to vary depending on sociodemographic factors, such as parental educational level, race, and income ,7,8. In The aim of this study is to show a trend in preterm birth rate by parental educational levels in recent decades in Japan and evaluate whether a disparity by parental educational levels persisted or not. Individual-level birth data from vital statistics and the Census were employed for the analysis. The Ministry of Health, Labour, and Welfare of Japan as well as the Ministry of Internal Affairs and Communications provided the data. The data in 2000, 2010, and 2020 were used because the Census surveyed educational levels in those periods. In 2000, 2010, and 2020, there were 126,925,843, 128,057,352, and 126,146,099 people, respectively. The Census contains information on a person’s prefecture, municipality, household, gender, marital status, birth year, birth month, and degree of education. Educational level is classified as “currently studying at school” and graduates, and graduates are divided into junior high school, high school, “technical school or junior college”, and “university or graduate school”. The four types of graduates were compared in the analysis. The birth data for each infant comprises the infant’s birth year, prefecture, municipality, gender, parents’ birth year and month, parity, multiple births, mother’s age, household occupation, and gestational age. Preterm birth was defined as a birth whose gestational age was less than 37 weeks. Maternal age groups were categorized into <20 years, 20–24 years, 25–29 years, 30–34 years, 35–39 years, and ≥40 years. Parity was categorized into two types: primiparous and multiparous. Household occupation means the main occupation in the household, and it is categorized as self-employed, farmer, full-time worker 1, full-time worker 2, other occupations, or unemployed. Full-time worker 1 describes workers working in a company that has less than 100 employees, and full-time worker 2 describes other workers working in a company or as public servants. Data linkage was performed to link individuals’ educational level data in the Census and parents’ birth data. Common ID does not exist in Japan, and deterministic data linkage was carried out using common information in both datasets, that is, birth year, birth month, gender, prefecture, and municipality. However, in this case, too many candidate men or women existed for parents of one birth. Therefore, we added two restrictions in the linkage. First, candidate men or women in the Census were restricted to married men and women to avoid the possibility that non-married men or women are matched with birth data of legitimate children. Additionally, parents of a single birth were matched only with men and women who reside in the same household because it is considered that the majority of parents giving birth do so. Only one-to-one matching pairs between parents of birth data and couples in the Census were used in the following analyses. As performed in earlier research ,5, only The number of births for each characteristic was calculated for each year, and the preterm birth rate was calculated by year and parental educational levels. A trend test was performed to verify whether a rise in parental education levels would result in a drop in the preterm birth rate. Furthermore, the slope index of inequality and relative index of inequality was calculated to evaluate a disparity in preterm birth depending on parental educational level. The relative index of inequality is the rate ratio between the highest and lowest educational levels, whereas the slope index of inequality is the absolute difference (%) in preterm birth between the two educational levels . A quantAlthough it was possible to use educational level as a categorical variable in a regression analysis, it is difficult to determine whether or not a disparity by educational level changed over time from the analysis. By using the disparity indexes, it becomes easier to compare degree of disparity over the years. Additionally, as it was revealed that the crude preterm birth rate tended to decrease with an increase in educational level linearly, we employed a method assuming a linear association between preterm birth rate and educational level. Furthermore, we included both the maternal and paternal educational levels in the regression model because one of them may be a confounding factor for the other. It is important to take into account of the influence of maternal educational level when evaluating the effects of paternal educational level.https://www.R-project.org/ (accessed on 01 February 2023)). The authors’ analysis of national data yielded the statistical results presented in this paper, which differ from statistical data published by the Ministries.As for the primary analysis, a complete case analysis was performed. Additionally, sensitivity analysis for missing data was performed, and hot-deck imputation was used as the imputation method . All stap-values < 0.05), regardless of the gender of the parents or the year.In 2000, 2010, and 2020, the rank correlation coefficient between the quantitative variables for paternal and maternal educational level was 0.434, 0.436, and 0.422, respectively.Results of the slope index of inequality and relative index of inequality for preterm birth rate depending on parental educational levels when applying an imputation approach are shown in In this study, we linked data from the Census and vital statistics and evaluated a disparity in preterm birth depending on parental educational levels. It was revealed that preterm birth rate tended to increase with a decrease in parental educational levels from 2000 to 2020. In addition, results of inequality indexes by regression models showed that an inequality in preterm birth depending on parental educational levels persisted from 2000 to 2020. A similar association between preterm birth and low parental educational levels has been shown in European countries and the United States in these periods ,24,25. IRegarding a possible link between lower educational level and preterm birth, smoking is one possible factor. An association between smoking and preterm birth has been shown in previous studies ,27,28. IAdditionally, it was suggested that maternal socioeconomic position influences preterm birth directly, without the use of mediators . MoreoveThe study results implied that more support and guidance for these high-risk people may be required during a pregnancy period. This has meaningful implications for the mechanism and reasons for the association between educational level and preterm birth in Japan. In addition, seeking a method to aid pregnant women with lower educational levels who do not fully utilize prenatal care is also needed. Increasing opportunities for education about pregnancy and prenatal care in schools or providing financial aid are possible methods. Furthermore, not only support from medical facilities but also workplaces and communities are important because the health behaviors of pregnant women are affected by the neighborhood environment .We employed nationwide vital statistics data for the analysis, which is a strength of this study. In contrast, there are some limitations in this study. As a limitation of this study, the result is based on data linkage. Therefore, some errors, such as mismatches, might exist in the process of data linkage. For example, marital status may change in one year, and it is considered that some of the couples were not matched with birth data. In addition, many birth data could not be used in the analysis because they did not match with the Census data. Second, some essential maternal characteristics, such as body mass index, prenatal care use, and smoking habits, are not available within vital statistics data in Japan. Furthermore, there was a lack of information regarding medical comorbidities, antepartum infections, and neonatal variables such as congenital defects. To scrutinize the mechanism of the disparity, an epidemiological study surveying these factors is required. Third, this study is based on data on singleton births, and multiple births were not used.In this study, we showed the trend in preterm birth rate depending on parental educational level from 2000 to 2020 using national data. As a result, it was shown that the preterm birth rate increased as educational level decreased, irrespective of parental gender and year. In addition, slope and relative indexes of inequality for preterm birth showed that a statistically significant inequality by parental educational level persisted from 2000 to 2020.


This cohort study assesses the association of interpregnancy interval with low birth weight, small for gestational age, and preterm birth outcomes among sibling pairs in China. How long is the optimal interpregnancy interval (IPI), and what is the association between IPI and subsequent adverse birth outcomes?In this cohort study of 725 392 sibling pairs in Guangdong Province, China, short or long IPI was associated with increased odds of adverse birth outcomes.Findings of this study may inform family planning policies and provide prepregnancy advice to those who are planning for another pregnancy in China. Many studies have reported an association of interpregnancy interval (IPI) between 2 consecutive births with adverse birth outcomes in low- and middle-income countries. However, most of these studies ignore the implications of some unmeasured confounders.To explore the association of IPI with adverse perinatal outcomes.This large-scale cohort study used the Guangdong Provincial Women and Children Health Information System in Guangdong Province, China, to obtain birth data recorded between January 1, 2014, and December 31, 2020. Matched-sibling design was used. The final cohort included first-born and second-born sibling pairs delivered by mothers who were permanent residents of Guangdong Province.The exposure variable was IPI, which was categorized as follows: less than 6, 6 to 11, 12 to 17, 18 to 23, 24 to 29, 30 to 35, and 36 or more months.The outcome variables were adverse birth outcomes: preterm birth , low birth weight , and small for gestational age (SGA). Adjusted odds ratio (OR) and interaction odds ratio (IOR) associated with IPI were calculated.The study consisted of 725 392 sibling pairs of multiparous mothers. Among these mothers, 718 111 (99.0%) were aged 20 to 34 years, and 715 583 (98.7%) were of Han Chinese ethnicity. Unmatched analysis showed that a short IPI of less than 6 months was associated with higher risks of PTB , LBW , and SGA  compared with an IPI of 18 to 23 months. These associations were attenuated in the matched-sibling analysis. An association of short IPI (<6 months) with PTB , LBW , and SGA  remained in the matched analysis. For IPI of 36 months or more, the odds of PTB  and LBW  in the unmatched analysis were also greater than the reference interval (18-23 months), but not for SGA . Associations between a long IPI (≥36 months) and PTB  and LBW  remained through the sibling comparisons.Results of this study indicated that mothers with a short (<6 months) or long (≥36 months) IPI had greater odds of adverse birth outcomes. The findings may inform family planning policies and guide individuals and families who are planning for another pregnancy in China. Variation in these findings may be attributed to differences in medical care, industrial development, and maternal characteristics. Thus, research in different locations can be beneficial for a comprehensive understanding of how IPI affects adverse birth outcomes. In addition, most studies on IPI and adverse birth outcomes are traditional retrospective cohort studies that did not adjust for certain unmeasured confounders.15 Not adjusting for confounders may raise the possibility of underestimating or overestimating the association between IPI and birth outcomes of interest. According to previous studies, IPI is associated with many potential confounders, such as maternal age, ethnicity, and socioeconomic status.16 For example, short IPIs are more common among young mothers.17 It is unclear to what extent this association is attributed to some unmeasured confounding factors. Several studies involving populations in high-income countries used a sibling-matched design to account for some unmeasured confounders, such as genetic factors and lifestyles.21 However, only a few studies explored the association of IPI with adverse birth outcomes among the Chinese population.23 Nevertheless, these studies did not account for some unmeasured confounders.A number of studies investigated whether IPI is associated with PTB, LBW, and SGA.24 In the context of changes in the birth policy, more families may consider having another child. Therefore, it is vital to formulate guidelines for appropriate IPI that are based on evidence obtained from large-scale cohort studies involving Chinese populations. With large-scale population data collected from Guangdong Province in China, we conducted this cohort study to explore the association of IPI with adverse perinatal outcomes using a matched-sibling design.In 2015, China’s 1-child policy was replaced with a universal 2-child policy. In 2021, a 3-child policy was announced in the country in response to the decline in total fertility rates.STROBE) reporting guideline.This study was approved by the Medical Ethics Committee at the Guangdong Women and Children Hospital. The birth surveillance data used in this study were extracted without personally identifiable information; therefore, the study was considered to be exempt from informed consent by the Medical Ethics Committee. We followed the Strengthening the Reporting of Observational Studies in Epidemiology . Gestational age (weeks) is then ascertained by obstetricians using the date of the mother’s last menstrual period and ultrasonographic examination. The information is checked by quality control physicians or nurses from the regional medical facility before being submitted to the Health Information System. Professional medical workers verify the accuracy of the information. The birth registration database in the Health Information System includes the neonate’s birth date, birth weight, and sex; maternal age and ethnicity; mode of delivery; and gestational age.25 Furthermore, we excluded nonconsecutive single births (n = 7 941 924). We restricted births to mothers who permanently resided in Guangdong Province (n = 1 518 092). After exclusion of births with missing information, including neonate’s sex and birth weight, maternal age and ethnicity (as recorded in the database and including Han Chinese and 55 ethnic minority groups), and mode of delivery (n = 2836), 1 515 256 births with complete information remained. Births with implausible weight (<500 g or >5000 g) or gestational age (<20 weeks or >42 weeks [n = 6780]) and births at third or higher parity (n = 57 692) were also excluded. The final cohort included 725 392 first-born and second-born sibling pairs.There were 12 534 139 births recorded in the database from January 1, 2014, to December 31, 2020 . Of thes22 we classified IPI into 7 categories , and the 18- to 23-month category was used as the reference group.Interpregnancy interval, defined as the period between the delivery date for one child and the conception date for the next child, was the exposure variable. We calculated IPI by subtracting the gestational age of the second birth from the time elapsed between the first and second deliveries. Following previous research,26 Preterm birth was grouped by moderate PTB (33-36 weeks), very PTB (28-32 weeks), and extreme PTB (<28 weeks).21 Small for gestational age was defined as birth weight below the 10th percentile of the Chinese fetal growth gestational age and sex-specific reference.27 Because this reference applies only to neonates with a gestational age of 24 to 42 weeks, newborns with a gestational age less than 24 weeks were excluded from the SGA analysis.Adverse birth outcomes of LBW (<2500 g), PTB , and SGA were used as the dependent or outcome variables. Low birth weight was classified into 2 subcategories: very LBW (<1500 g) and extremely LBW (<1000 g).28 several potential confounders were considered: maternal age at first birth, maternal ethnicity, mode of delivery at first birth, season of birth, and socioeconomic status. Socioeconomic status was derived in 2 steps. First, we collected the mean income of each city from the Statistics Bureau of Guangdong Province as the income of mothers living in the same region. Second, we grouped the income into quintiles according to the population in Guangdong Province.In accordance with previous studies,2 test. Because the outcome variables were binary data, we used a logistic regression model to estimate the odds ratios (ORs) and corresponding 95% CIs for adverse perinatal outcomes and IPI, with 18 to 23 months as the reference group. In the unmatched analysis, we fitted an unadjusted model containing only IPI and an adjusted model including maternal age, maternal ethnicity, season of birth, socioeconomic status, and mode of delivery.We described the basic characteristics of mothers by IPI category , and then we compared the differences between the groups using χ21 to control for some unmeasured confounding factors. With this method, we matched the first 2 consecutive births with different birth outcomes from the same mother with a discordant sibling pair . The information of first birth was not incorporated into the model in the unmatched analysis. However, in the matched analysis, the information was used to adjust some unmeasured confounders. For matched analysis, we adopted an interaction term for birth order  multiplied by IPI in the conditional logistic model to ensure that only the association between adverse birth outcomes and IPI for the second birth was estimated. Detailed methods are provided in the eAppendix in the We used a matched-sibling design, which was proposed in a previous study,In addition, we conducted several sensitivity analyses and subgroup analyses according to maternal age and mode of delivery. We constructed a model without adjusting for delivery mode. We also conducted supplemental analyses of subcategories of PTB and LBW.P < .05.Analyses of data were conducted with SAS, version 9.4 (SAS Institute Inc). Statistical significance was denoted by 2-tailed A total of 725 392 sibling pairs from multiparous mothers were included in the study. Of the sibling pairs, 181 172 second-born siblings (25.0%) were born with an IPI of 12 to 17 months. Of the mothers, 718 111 (99.0%) were aged 20 to 34 years, 715 583 (98.7%) were of Han ethnicity, 49 485 (6.8%) had an IPI of less than 6 months, and 54 988 (7.6%) had a long IPI of 36 months or more. We observed a shorter IPI of less than 6 months for mothers aged 20 to 24 years (30 400 [61.4%]), of Han Chinese ethnicity (48 966 [99.0%]), who delivered their first child in autumn (14 800 [29.9%]), and who had a vaginal delivery (48 368 [97.7%]). Mothers with a socioeconomic status in the highest quintile (17 168 [31.2%]) tended to have a longer IPI (≥36 months). Characteristics of the mothers at their first pregnancy based on IPI categories are presented in Odds of adverse birth outcomes by IPI in the unmatched analysis are presented in Significant differences were observed between short and long IPIs and LBW . Similar results were found between subcategories of LBW and IPI. We observed an association between extremely LBW and IPI after 36 months   or long (>36 months) IPI was associated with increased risks of adverse birth outcomes. The findings have substantial implications for public health policy. Many families in China are planning for another child in the context of the shifts in the birth policy.49 A well-controlled analysis is important in reliably measuring the outcome of IPI. Third, we conducted a more specific analysis to investigate the association between IPI and subcategories of birth outcomes.This study has several strengths. First, this cohort study was a large-scale investigation. Second, the matched-sibling method enabled us to incorporate information about first-born siblings into the model to control some unmeasured confounders. If uncontrolled, confounders could lead to the overestimation or underestimation of the risks of adverse birth outcomes and IPI. According to a previous study, mothers with previous adverse birth outcomes are more likely to experience adverse birth outcomes in subsequent pregnancies.23 this study included only live, consecutive, single-birth data. Thus, these results might not apply to women who had experienced a miscarriage or stillbirth between deliveries. Given the paucity of guidance on optimal IPI after a stillbirth, further studies on IPI that consider stillbirth are needed. Third, we did not analyze spontaneous PTB and indicated PTB separately because the data were unavailable. Fourth, primary medical institutions report birth surveillance data with varying degrees of lag time. Fifth, there are inherent limitations to retrospective cohort studies because data collection is not controlled by the researchers; this study may not overcome these limitations. These factors may potentially alter the study results.This study also has some limitations. First, the study period was restricted from 2014 to 2020, which resulted in a relatively limited amount of data on long IPI (>60 months), making it difficult to explore the association between long IPI and adverse perinatal outcomes. Second, consistent with previous studies,This large-scale population-based cohort study conducted in Guangdong Province, China, found that a short IPI of less than 6 months was associated with greater odds of PTB, LBW, and SGA. The study observed that optimal IPI ranged from 18 to 23 months, indicating a shorter optimal IPI than a previous recommendation (24 months). These findings can inform family planning policies and guide individuals and families planning on conceiving another child in China. Further high-quality studies are necessary to explore the association between IPI and adverse birth outcomes in different populations and to examine the underlying mechanisms.


Background: Psoriasis vulgaris is an inflammatory skin disease. Observational studies have shown associations between circulating cytokine levels and psoriasis vulgaris. But the causal relationship between circulating cytokine and psoriasis vulgaris remains elusive.Methods: To assess the causal effects of cytokine levels on the risk of psoriasis vulgaris and vice versa, we performed a two-sample Mendelian randomization (MR) study by using the inverse-variance weighted (IVW), weighted median, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) in genome-wide association summary statistics of 41 circulating cytokines in up to 8,293 individuals and psoriasis vulgaris in 399,883 individuals.Results: We identified that increasing RANTES level induced an elevated risk of psoriasis vulgaris in IVW . This causal effect showed consistency across the weighted median  and MR-PRESSO method .Conclusions: Our results suggest a potential causal effect of elevated RANTES concentration on the increased risk of psoriasis vulgaris. Psoriasis vulgaris is a chronic inflammatory skin disease, affecting about 2% of the population around the world . The preSince observational studies are susceptible to reverse causality and confounding factors, it is unable to provide convincing evidence for causality alone . For insMendelian randomization (MR) uses genetic variation that are strongly associated with a possible exposure as instrumental variables (IVs) to assess the causality of the given exposure on an outcome of interest . CompareTo better understand the causal role of cytokines in the development of psoriasis vulgaris and to search for disease prevention and treatment targets of potential, we performed a two-sample MR to evaluate the causal relationship between circulating cytokines concentrations and the risk of psoriasis vulgaris. We identified single nucleotide polymorphisms (SNPs) from GWAS meta-analysis for 41 circulating cytokines in 8,293 Finns as IVs. We evaluated the causal effect of circulating cytokines on psoriasis vulgaris with SNPs which were identified, and the genome-wide association statistics for psoriasis vulgaris in the United Kingdom biobank. Our study suggests a potential causal association between circulating RANTES levels and the risk of psoriasis vulgaris. This finding helps identify a potential target for the intervention of psoriasis.We accessed genome-wide association summary-level statistics for 41 circulating cytokines and psoriasis vulgaris. In brief, the summary-level data for 41 cytokines included ∼ 10.7 million SNPs and 8,293 Finnish individuals from the Cardiovascular Risk in Young Finns study, FINRISK 1997, and FINRISK 2002 . The cytWe used genome-wide association statistics for psoriasis vulgaris in the United Kingdom biobank . The UniP < 1 × 10−6 in cytokine GWAS summary statistics using LD r2 < 0.1 in distance≥500 kilobases (kb) (The IVs for MR have three assumptions: 1) IVs must be strongly associated with exposure. 2) IVs are not associated with any known confounders related to outcome or exposure. 3) IVs cannot affect the outcome in other ways except through exposure . To idenses (kb) . After sp < 0.05 to define a significant causal effect . The numbers of IVs for each cytokine are shown in For 35 of the 41 cytokines, we identified at least three genetic variants available at p < 0.05; β = 0.325, S.E. = 0.119, p = 0.006), weighted median , and MR-PRESSO (β = 0.325, S.E. = 0.106, p = 0.028; p = 0.55; p = 0.62; p for intercept = 0.69; Among the 35 cytokines, genetically predicted RANTES, SDF-1α, MIP-1β and IL-17 were associated with the risk of psoriasis vulgaris in at least 1 MR method at the significance threshold (p < 0.05 in at least one of the 3 MR methods based on MR results from p > 0.05; p > 0.05 and MR Egger’s regression intercept p > 0.05; Reversely, we identified causal effects of the onset of psoriasis vulgaris on 11 circulating cytokine levels including IL-1ra, IL-5, CTACK, MIG, VEGF, IL-8, IL-9, IL-13, IL-12p70, TNF-α, and IL-2 at Studies have shown significant associations between circulating cytokines and psoriasis vulgaris, but the causal relationship between cytokines and psoriasis vulgaris remain unclear. In our study, we leveraged large-scale GWAS for 41 circulating cytokines and psoriasis vulgaris and evaluated the causal relationship between circulating cytokines and psoriasis vulgaris by using three two-sample MR approaches. We identified a causal effect of elevated RANTES levels on the increased risk of psoriasis vulgaris. We also assessed the causal effects of psoriasis vulgaris risk on circulating cytokine concentrations, which found that increased risk of psoriasis vulgaris resulted in elevated circulating levels of IL-1ra, IL-5, and MIG.epidermis and dermis (Psoriasis vulgaris is characterized by abnormal epidermal hyperplasia and differentiation, with accumulation and infiltration of neutrophils and pro-inflammatory T cells in the d dermis . RANTES d dermis . RANTES d dermis . Studiesd dermis . The expd dermis . Photothd dermis . Accordid dermis . Howeverd dermis . PreviouWe consistently found that psoriasis vulgaris affects the circulating levels of IL-1ra, IL-5, and MIG, which are consistent with previous findings. Abundant IL-ra expression was found in psoriatic lesions . IL-ra ep-value threshold at 1 × 10–6 instead of 5 × 10–8. The lenient P-value threshold increased the number of available IVs for MR but might cause weak IV bias. Thirdly, our MR study could only demonstrate the lifetime effects of higher cytokines on psoriasis vulgaris, and the effect of short-term regulation of cytokines, such as biological agents targeting cytokines, on psoriasis vulgaris is difficult to assess. Therefore, in the future studies, we need to further explore the biological functions of cytokines to better understand the relationship between cytokines and psoriasis vulgaris.Compared with traditional observational studies, our MR study overcomes the bias caused by confounding and reverse causality issues and provides more reliable evidence for assessing the causal relationship between circulating cytokine concentrations and the risk of psoriasis vulgaris. However, there are some limitations in our MR study, which may influence the causal inference between cytokines and psoriasis vulgaris. Firstly, the sample size of the cytokine GWAS was limited, limiting the statistical power of causal assessment in MR. This may explain IL-17, IL-23, and TNF-α whose biologics are effective for treating psoriasis but did not yield statistically significant results in our MR analysis. Secondly, we used the significance We identified a causal effect of circulating RANTES levels on the risk of psoriasis vulgaris. This finding might help explore the mechanisms of RANTES in the pathogenesis and development of psoriasis and guide the evaluating of RANTES as a potential intervention target for psoriasis vulgaris.


Maternal and neonatal health significantly improves when birth is attended at health institutions where there are quality services and skilled attendants. In contrary, home birth results in high rates of maternal and neonatal mortality. Thus, this study aimed to determine the spatial distribution of home birth and to identify determinants of place of birth in Ethiopia based on the recent national survey.p-value of < 0.05 were used to declare statistical significance. The Global Moran’s I analysis was done by using ArcMap 10.8 to evaluate the clustering of home birth. The prevalence of home birth was predicted by ordinary kriging interpolation. Then, scanning was done by SaTScan V.9.6 software to detect scanning windows with low or high rates of home birth.Ethiopian mini-DHS-2019 data was used in this analysis. A weighted sample of 5423 mothers were included. While health facility was a reference, home and health post were used as comparison categories to identify determinants of place of birth in a survey multinomial logistic regression model. An adjusted relative risk ratio, marginal effect, and a corresponding 95% confidence interval and a Prevalence of home birth in Ethiopia was 52.19% (95% CI: 46.49 – 57.83). Whereas, only 2.99% (95% CI: 1.68 – 5.25) of mothers gave birth in the health posts. Bigger family size, family wealth, multiparity, none and fewer antenatal visits, and low coverage of cluster level 4 + antenatal visits were predictors of home birth. Also, home birth was clustered across enumeration areas and it was over 40% in most parts of the country with > 75% in the Somali region. SaTScan analysis detected most likely primary clusters in the Somali region and secondary clusters in the rest five regions of the country.Home birth is a common practice in Ethiopia. Among public health facilities, health posts are the least utilized institutions for labor and delivery care. Nationally, implementing the 2016 WHO’s recommendations on antenatal care for a positive pregnancy experience and providing quality antenatal and delivery care in public facilities by qualified providers and back-up systems in place could be supportive. Maternal mortality is a worldwide public health concern and a global estimate indicated that 211 Maternal Mortality Ratios (MMR) pre-100,000live births occurred in 2017. Southern Asia and sub-Saharan Africa countries contributed about 86% of the global MMR [Globally, between 2003 and 2013, about 72% of all maternal deaths occurred mainly due to hemorrhage, hypertensive disorder, and sepsis . SimilarSeveral interventions are in place to combat maternal mortality. From the three risk periods of maternal mortality namely antepartum, intrapartum and postpartum; antenatal coverage was significantly reduced antepartum mortality, and the presence of skilled attendants at childbirth dropped intrapartum and early postpartum mortality . AmongstA recent quantitative study done in Ethiopia revealed that giving birth at home is a common practice. Rural residence, distance to health facility, low antenatal care coverage, and economic status are common societal factors. Also, low education, not planning for place birth, and unknown due date –12 were In most studies conducted in the past ten years in Ethiopia, the place of birth was measured as home and health facility. The health posts, the one in the primary health care systems  in the cThe mini-Ethiopian demographic and health survey (EDHS) was conducted in Ethiopia. The survey was a nationwide mini-survey and included all nine reginal and two city administration areas. Besides regions and city administrations, the country is further subdivided into 68 zones, 817 districts, and 16,253 kebeles (the lowest level of administration) administrative structures .The sampling frame used in the survey was the census enumeration areas (EAs) created for the upcoming Ethiopian Population and Housing Census (PHC). The EDHS is a nationally representative two-stage cluster cross-sectional survey. As described in detail in the EDHS 2019 report [In this study, the outcome variable was the places of birth of the most recent child and places were categorized as .Health institutions are public hospitals and health centers, private hospitals and clinics, and nongovernmental organization (NGO) health facilities. These institutions are generally providing basic and comprehensive health services and labor and delivery care is usually provided by skilled providers.Health posts: according to the three-tier health care delivery system of Ethiopia, are among the primary health care units and are satellite sites for health centers. Each health post is expected to serve a population of 3,000 – 5,000 and is a functional unit of health extension workers in rural areas . These fThe independent variables used in this analysis were both individual and community-level variables. Maternal age, media access, family size, maternal education attainment, family wealth index, parity, and antenatal care utilization were among individual-level variables. Whereas, place of residence, poverty level of the community, media accessibility of the community, literacy level of the community, and ≥ 4 antenatal care coverage at the community/cluster level were community-level variables included in the analysis.Community-level variables such as poverty, media access, literacy, and cluster-level ≥ 4 antenatal care coverage were generated by aggregating individual-level variables at the community (cluster) level. Poorest and poorer family income categories were re-categorized as ‘poor’; maternal education category of no education was categorized as ‘illiteracy’; and family who didn’t access television or radio or both television and radio was categorized as ‘no’. Then, the prevalence of these variables was divided by the cluster size, and the generated value was further categorized as ‘low’ and ‘high’ based on the median value. Four and more antenatal care visits coverage was computed the same way but finally categorized in percentages as ‘below 25%’,’25–50%’, ‘51 – 74%’, and ‘ ≥ 75%’.Sociodemographic and reproductive characteristics of the study participants and the outcome variable were described in frequency and percentage.p-value of < 0.2 were considered for the final multivariable model. The final survey multinomial multivariable model was selected based on the log likely (LL) ratio and the one with the highest LL ratio was selected. In the final model, an adjusted relative risk ratio (aRRR), its 95% confidence interval was computed. Also, marginal effect and its 95% confidence interval was calculated [p-value of < 0.05 were interpreted and used to declare statistical significance.A survey multinomial logistic regression model was used to analyze the association between the outcome and independent variables. Individual independent variables that had an association with place of birth at a lculated . Then, tThe Global Moran’s I analysis was done by using ArcMap 10.8 to evaluate whether home birth is clustered, random, or dispersed across the study areas. Since home birth was clustered, spatial interpolation by using ArcMap 10.8 and scan statistics by using a SaTScan V.9.6 were carried out to predict the magnitude and to detect clusters and a scanning window with low or high rates of home birth.Prevalence of place of birth, Socio-demographic, and reproductive characteristics of study participants.The prevalence of home delivery in Ethiopia was 52.19% (95% CI: 46.49 – 57.83). Whereas delivery at health facilities was 44.83% (95% CI: 39.57 – 50.20) and only 2.99% (95% CI: 1.68 – 5.25) mothers gave birth in the health posts.Nearly two-thirds (62.08%) of the mothers who didn’t expose access media in their household had given birth at home. Similarly, two-third and more mothers, whose family size was greater than six members were delivered at home. Giving birth at home showed a decreasing prevalence as mothers’ level of education and the family wealth index increases.While most (86.34%) of the mothers who hadn’t get antenatal care, gave birth at home. The majority (66.35%) of grand multiparous mothers similarly delivered at home. Almost one-third of urban and two-third of rural residents gave home birth for their most recent delivery. From the regions in Ethiopia, Afar and Somali were the most common home birth regions in the country Table .Table 1SSpatial distribution of home birth in Ethiopia.p-value < 0.001)  Fig. . In addip-value of < 0.001. In addition, the most likely secondary cluster areas with a high magnitude of home birth were spotted in the central zones of Amhara and eastern zones of South Nations, Nationalities, and People’s Region (SNNPR)  = 1.72, and a PR) Fig. , Table 2The survey multinomial multivariable analysis identified that the relative probability of giving birth at home rather than health facility was about one and half times higher for mothers who had a family size of six to ten members than less than six members ). The marginal effect analysis also indicated that the probability of giving birth at home was on average five percentage ) points higher for mothers who had a family size of six to ten members. Whereas, the relative probability of giving birth at health post rather than health institution was 0.02 ) for mothers who had a family size greater than ten than less than six members implies that the probability of giving birth at health post on average three percentage ) points lower for mothers who had largest family size than lowest family size.The family wealth index was also found to be a predictor for a home birth. As compared to the richest family, the relative probability of giving birth at home rather than health facility among mothers was about two times higher for richer aRRR 2.13 , more than four times higher for the middle ) and poorer ), and ten times higher for poorest ) family. As shown by the marginal effect analysis, the probability of giving birth at home among mothers was higher at 12 percentage points for richer, around 25 percentage points for middle and poorer families. Whereas, home birth was 38 percentage points higher for the poorest family.In addition, the relative probability of giving birth at home rather than health facility was nearly twice higher for multiparous ) and grand multiparous ) mothers than primiparous mothers. The marginal effect analysis also revealed that the probability of giving birth at home was about ten percentage points higher among multiparous and grand multiparous than primiparous mothers.Moreover, as compared to mothers who attended four and more antenatal care visits, the relative probability of giving birth at home rather than at a health facility was more than one times ) higher for mothers who attended less than four antenatal care visits and over six times ) higher for mothers who didn’t attend antenatal care during the index pregnancy. In the marginal effect analysis, the probability of giving birth at home was eight percentage points higher among mothers who attended less antenatal care visits and 30 percentage points higher among mothers who didn’t attend antenatal care than who attended four and more antenatal care visits. Likewise, the probability of giving birth at health posts on average two percentage ) points lower for mothers who didn’t attend antenatal care.Similarly, the relative probability of giving birth at home rather than health facility was more than two times ) higher among mothers who residing in the clusters in which 51—74% of mothers attended 4 + antenatal care visits than those residing in the clusters of ≥ 75% 4 + antenatal care visits coverage. And it was about five times ) higher among mothers who residing in the clusters in which 25 – 50% of mothers attended 4 + antenatal care visits and about seven times ) higher among mothers who residing in the clusters in which < 25% of mothers attended 4 + antenatal care visits as compared to those who residing in the clusters of ≥ 75% 4 + antenatal care visits coverage. The marginal analysis also showed that the probability of giving birth at home was 37 percentage points higher among mothers who residing in the clusters in which < 25% of mothers attended 4 + antenatal care visits, 30 percentage points higher among mothers who residing in the clusters in which 25 – 50% of mothers attended 4 + antenatal care vists, and 14 percentage points higher among mothers who residing in the clusters in which 51 – 74% of mothers attended 4 + antenatal care visits as compared to mothers who residing in the clusters in which ≥ 75% of mothers attended a coverage of 4 + antenatal care visits (Table In Ethiopia, the practice of giving birth at home showed a decreasing trend since 2005. From about 95% in 2005, home birth significantly dropped to 52% in 2019 . As explMothers from a family size above five members and those who were multiparous inclined to give birth at home than smaller family size and nulliparous mothers. Family size is directly related to birth order and similar studies also identified that higher birth order and multiparity were found to be significant factors for home birth . ScientiThis study further identified that antenatal care attendance at an individual level and its frequency, as well as community-level coverage of 4 + antenatal care, played a significant role in determining the place of birth. Several small- and large-scale studies also revealed that receiving no antenatal care  and delaIn Ethiopia, home birth is a common practice. In contrast, health posts, which are community-level governmental health units, are the least utilized facilities for labor and delivery service. Individual-level none and fewer visits of antenatal care and lower cluster level coverage of 4 + antenatal care played a significant role in predicting home birth in Ethiopia. Nationally adapting the 2016 WHO’s recommendations on antenatal care for a positive pregnancy experience and providing quality antenatal and delivery care in public facilities by skilled provisers and systems of back-up in place could be helpful. Also, piloting the benefits of planned home birth with qualified professionals for low-risk pregnancies could be worth more.