Preterm birth is a leading cause of death among children under five years. Previous estimates indicated global preterm birth rate of 10.6% (14.8 million neonates) in 2014. We aim to update preterm birth estimates at global, regional, and national levels for the period 2010 to 2019.Preterm birth is defined as a live birth occurring before 37 completed gestational weeks, or <259 days since a woman’s last menstrual period. National administrative data sources for WHO Member States with facility birth rates of ≥80% in the most recent year for which data is available will be searched. Administrative data identified for these countries will be considered if ≥80% of UN estimated live births include gestational age information to define preterm birth. For countries without eligible administrative data, a systematic review of studies will be conducted. Research studies will be eligible if the reported outcome is derived from an observational or intervention study conducted at national or sub-national level in population- or facility-based settings. Risk of bias assessments will focus on gestational age measurement method and coverage, and inclusion of special subgroups in published estimates. Covariates for inclusion will be selected a priori based on a conceptual framework of plausible associations with preterm birth, data availability, and quality of covariate data across many countries and years. Global, regional and national preterm birth rates will be estimated using a Bayesian multilevel-mixed regression model.Accurate measurement of preterm birth is challenging in many countries given incomplete or unavailable data from national administrative sources, compounded by limited gestational age assessment during pregnancy to define preterm birth. Up-to-date modelled estimates will be an important resource to measure the global burden of preterm birth and to inform policies and programs especially in settings with a high burden of neonatal mortality.PROSPERO registration:CRD42021237861. Preterm birth (birth occurring before 37 completed weeks of gestation) is a leading cause of death in children under five years of age globally. In 2019, preterm birth accounted for approximately 16% of deaths in this age group and 35% of neonatal deaths . PretermAchieving significant declines in neonatal deaths will require strong commitment to the reduction of mortality among preterm newborns. Estimates of the burden of preterm birth are therefore critical to plan appropriate strategies to reduce preterm birth-related mortality and morbidity, as well as for achieving Sustainable Development Goal (SDG) 3.2 , which aEvery Newborn Action Plan [Yet, the accurate measurement of preterm birth has been challenging in many countries given incomplete or unavailable data from national administrative systems. Data constraints are further compounded by limited ascertainment of gestational age during pregnancy, particularly in low-resource settings, which is critical to classify a birth as preterm. The improved measurement of preterm birth has therefore been highlighted as an important priority of the ion Plan , led joiGiven these data constraints and the ongoing need to strengthen national data reporting on preterm births, it is necessary to develop comparable model-based estimates of preterm birth at global, regional and national levels, while at the same time continuing to support improved national administrative data systems that will help to improve preterm birth measurement in the future.Three analyses of the global burden of preterm birth have been published to date –21. The Global estimates of preterm birth require regular updates to enable the inclusion of new data and to best reflect current levels and trends. Up-to-date global preterm birth estimates are crucial to understand the recent epidemiology of preterm birth and its variations across regions and countries; to support the development and implementation of policies for newborn health; to inform resource allocation within health systems; and to aid impact assessments of interventions to promote newborn health. These estimates will also help to raise awareness about preterm birth as a leading global public health challenge and will be critical for highlighting the need for continued investments in national administrative data systems to improve preterm birth measurement and reporting in the future. Finally, the current round of preterm birth estimates will be the first to cover the beginning of the SDG era, and will also inform the Survive, Thrive, Transform agenda of the Global Strategy for Women’s, Children’s and Adolescents’ Health (2016–2030) .The main objective of this protocol is to describe the methodology for the data compilation and the statistical modelling that will be applied to develop the fourth round of global estimates for preterm birth for the period 2010 to 2019, with associated uncertainty intervals.A Steering Group, comprised of experts from the WHO, UNICEF and the London School of Hygiene and Tropical Medicine (LSHTM), will implement this protocol. The work will be supported by an Estimates Consultative Group (ECG), which is comprised of global experts in preterm birth measurement including obstetricians, neonatologists, statisticians, preterm birth researchers, and program staff working in the measurement field. The ECG will provide technical guidance on the estimation process, as well as review data inputs and preliminary estimates prior to finalization. An official country consultation will be conducted with WHO Member States to inform Member States of the methodology , as wellth revision (ICD-11) uses the WHO definition of preterm birth, namely: “All births before 37 completed weeks of gestation or fewer than 259 days since the first day of a woman’s last menstrual period” [The International Statistical Classification of Diseases and Health Problems, 11 period” . The WHOWHO recommends reporting the preterm birth rate using the following indicator:The primary outcome for this study is therefore defined as a live birth occurring before 37 completed weeks of gestation, or fewer than 259 days since the woman’s last menstrual period. The secondary outcome includes preterm birth based on different gestational age ranges including: (1) extremely preterm (<28 completed weeks of gestation); (2) very preterm (28 to <32 weeks of gestation); (3) moderately preterm (32 to <34 weeks of gestation); and late preterm (34 to <37 weeks of gestation).Gestational age measurement to classify a preterm is limited in many countries. Furthermore, the method used to define a preterm birth may substantially impact reported national rates . UltrasoThere are two broad categories of data sources that may be used for preterm birth estimation; national administrative data and research studies including Reproductive Health Surveys . Nationabirth, gestational age, and preterm (with appropriate translations for non-English websites). Non-English websites will be searched by researchers who speak the relevant language.For administrative data sources, we will conduct a systematic search of Ministry of Health and National Statistical Office  publicatA systematic review of studies will be conducted for WHO Member States that do not meet the threshold to search administrative data sources and that lack eligible administrative data for the estimation work (see “Eligibility Criteria"). We will search the following electronic databases: MEDLINE, EMBASE, WHO Global Index Medicus, CINAHL, PsycINFO, and the Cochrane Central Register of Controlled Trials (CENTRAL). All searches will be restricted to publication dates after 1 January 2015 in order to update the database from the previous estimation round . There wFor administrative data sources, all CRVS, HMIS or Medical Birth Registry data identified through the search will be eligible for inclusion if at least 80% of the United Nations (UN) estimated live births in a given country for a given year are reported with gestational age information to define preterm birth . For admFor studies, all data sources identified through the search will be eligible for inclusion if the outcome is derived from an observational or intervention study design conducted at national or sub-national level in either population- or facility-based settings. Study designs may include randomized controlled trials, non-randomized trials, cross-sectional studies, controlled before-after studies, or longitudinal studies with a sample size of least 500 births. For intervention studies, outcomes reported for the control arm will be used. In addition, for research studies, eligible gestational age measurement methods to classify a preterm birth may include: ultrasound in any trimester, last menstrual period, symphysis-fundal height, post-natal assessment, or any combination of these measures (see “Risk of Bias Assessment” section).For administrative data, all CRVS, HMIS and Medical Birth Registry data identified through the search will be reviewed against eligibility criteria. For research studies, all titles and abstracts of identified studies will be independently screened by two reviewers for potential eligibility and, if disagreements occur, the full text will be reviewed. The full text of potentially eligible studies, plus studies where disagreements occur, will be retrieved and independently assessed by the same two reviewers. Any disagreements during the full-text review stage will be discussed to reach consensus or will be settled through consultation with a third reviewer. Exclusion reasons will be documented for the full-text review stage.For all eligible data sources, the following data points will be extracted: country, data source type, study design type (if applicable), time period, citation or website, outcome definition, method for gestational age measurement, gestational age range(s), total preterm births, total live births, and any covariate data.For administrative data sources, data will be extracted into an excel-based form  as part st project [All data sources reporting gestational age in months or where less than 3% of live births are reported to be preterm will be excluded. This cut-off is aligned with the lowest proportions of preterm birth (3.4%) reported for countries by the Intergrowth 21 project .For administrative data only, datasets that provide gestational age information for less than 80% of UN estimated live births in a given country for a given year will be excluded;For research studies only, the following additional exclusion criteria will be applied:Study populations derived from high-risk sub-national groups will be excluded. For example, studies including only women with specific medical or obstetric complications; studies based on other high-risk sub-national populations only .Case-control studies will be excluded due to the potential for selection bias.Table 1 describes the potential sources of bias which focus on the coverage and method of gestational age measurement, and the representativeness of the liveborn neonate population from which the outcome is derived.Assessing the risks of bias informs the extent to which the reported preterm birth prevalence observed in the data source may differ from the “true” prevalence at the national level. For administrative data sources, the biases will be assessed as part of data extraction phase. For eligible studies, two independent reviewers will conduct the assessment. Any disagreements will be discussed to reach consensus or will be settled through consultation with a third reviewer. The results of the risk of bias assessment will inform statistical analyses through potential inclusion as model inputs or sensitivity analyses and will also be used to interpret results and discuss potential study limitations.The database from previous estimation rounds will be updated with newly eligible data points from the current systematic searches and review. If there are duplicate data points, the latest extracted data point will be maintained in the database. All data points from studies extracted into Covidence  will be The development of the models for the preterm birth estimates will utilize country-level covariates from available United Nations and other sources. Covariates for inclusion will be selected a priori, based on the conceptual framework of plausible associations with preterm birth, data availability, and quality of covariate data. The covariate time-series data will include a well-documented methodology on construction of the time-series data and handling of missing covariate data across countries and years. We will explore methods for handling missing data such as; interpolation , replacing with the nearest available value  or, multiple imputation . Covariates with high degree of missing data or if uncertainty exists will be excluded.The modelling will follow a similar strategy to that applied for the previous preterm estimates i.e., using a Bayesian multilevel-mixed regression model . The modEstimates of preterm birth at global, regional, and national levels for 2010–2019 will be predicted from the models in step 2 using a Bayesian multilevel-mixed regression model . Fitted estimates generated from the model that includes data on year (time), source characteristics, and covariate data will be used to predict estimates for country-years with no available data. The Markov chain Monte Carlo method will be used to estimate the preterm birth rates based on priors , data inputs, and covariate information to generate predictions for all country-years from the estimated model parameters. Logit or log transformations will be applied, as appropriate, to ensure that preterm birth estimates obtained from the fitted model are within a plausible range i.e., 0% and 100%.th and 90th percentiles for uncertainty intervals around the estimate will be presented. We plan to conduct sensitivity analyses on the preterm birth outcome according to the risks of bias assessed (Table 1). We will publish national-level preterm birth rates for those countries with at least one eligible data point included in the estimation period, although all country-level estimates will contribute to the overall global and regional preterm birth rate estimates.Country level point estimates with the 10There are several methodological challenges in the development of global preterm birth estimates that are anticipated in this work and should be noted as part of the study protocol.First, national administrative data sources are often incomplete or unavailable for many countries, particularly low- and middle-income countries (LMICs). National administrative data sources, may also exclude marginalized or vulnerable groups  who may face greater risks of preterm birth. Given the paucity of data from national administrative sources, we will use research studies from sub-national areas or populations as a supplemental data source. Research studies may have their own potential biases since they are often conducted at tertiary settings and/or in special population subgroups  and may not accurately reflect the composition of the national population.Second, gestational age measurement to classify a preterm birth is limited in many countries, and even when assessed and recorded during pregnancy, may not be aggregated into routine data systems. This is a considerable limitation affecting data availability from national administrative data sources for this estimation work. Access to early pregnancy ultrasound is limited across LMICs, and less accurate measures are commonly used as alternatives, such as last menstrual period, symphysis-fundal height assessment, or ultrasound scan in later trimesters that may lead to biases in either direction. Differences in gestational age measurements used to define preterm birth will also affect comparisons over time or across countries. Many national reports may also not specify the method of gestational age measurement used to define preterm birth, making interpretation of national results and comparisons across countries or over time more difficult.Third, different definitions of preterm birth may be used across settings complicating cross-country comparisons .Fourth, the preterm birth definition used in this study includes only newborns who are born alive and preterm, which will underestimate the burden of prematurity as a public health issue since stillbirths are not included. In addition, misclassification of live preterm births who die shortly after birth as stillbirths can occur, this is most common around the thresholds of viability in all contexts, where signs of life may be harder to identify, and resuscitation may not be attempted While this current round of preterm birth estimates does not include stillbirths in the definition, work is currently underway to develop methods to include stillbirths in future estimation rounds.The work described in this protocol aims to generate estimates of preterm birth rates at global, regional, and national levels for the period 2010 to 2019, which builds closely on the methodology used in the previous estimation rounds. In each successive estimation round, improvements in administrative data systems allow for an expanded number of national data points to be included in the estimation work in order to improve overall estimates. Some national household surveys are also initiating data collection on women who received an ultrasound during pregnancy, which could further expand data availability for this estimation round and going forward .The current round of preterm birth estimates for the period 2010 to 2019 are the first to cover the beginning of the SDG era, and will inform the Survive, Thrive, Transform agenda of the Global Strategy for Women’s, Children’s and Adolescents’ Health (2016–2030) . Up-to-dNot applicable. This work is based on secondary analyses of public data from administrative sources and studies identified through a systematic search and review process.In compliance with GATHER guidelines , the finThis work will result in publication of global, regional and national preterm birth estimates for the period 2010–2019 in an open-access peer-reviewed journal. We will also publish the final protocol, database and preterm birth estimates online through the WHO Global Health Observatory and UNICEF websites according to GATHER guidelines , as descPROSPERO registration number CRD42021237861.Protocol date: 4th June 2021; Protocol version: v.20. This protocol is not an amendment of a previously completed or published protocol. Any important protocol amendments will be documented in a protocol addendum and in the final report or manuscript.S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S3 Appendix(XLS)Click here for additional data file.


To determine if maternal plasma CRH and preterm birth history were associated with recurrent preterm birth risk in a high-risk cohort.Secondary analysis of pregnant women with a prior preterm birth ≤35 weeks receiving 17-alpha hydroxyprogesterone caproate for the prevention of recurrent spontaneous preterm birth. All women with a 24-week blood sample were included. Maternal plasma CRH level at 24- and 32-weeks’ gestation was measured using both enzyme-linked immunosorbent assay (ELISA) and extracted radioimmunoassay (RIA) technologies. The primary outcome was spontaneous preterm birth <37 weeks. The association of CRH, prior preterm birth history, and the two combined was assessed in relation to recurrent preterm birth risk.Recurrent preterm birth in this cohort of 169 women was 24.9%. Comparing women who subsequently delivered <37 versus ≥37 weeks, mean levels of CRH measured by RIA were significantly different at 24 weeks  and 32 weeks . The area under the receiver operating curve (AUC) at 24 and 32 weeks for (1) CRH level was 0.68 (95% CI 0.59–0.78) and 0.70 (95% CI 0.59–0.81), (2) prior preterm birth history was 0.75 (95% CI 0.67–0.83) and 0.78 (95% CI 0.69–0.87), and (3) combined was 0.81  and 0.81  respectively for delivery <37 weeks. CRH measured by ELISA failed to correlate with gestational age or other clinical parameters.In women with a prior preterm birth, CRH levels were higher and had an earlier rise in women who experienced recurrent preterm birth. Second trimester CRH may be useful in identifying a sub-group of women with preterm birth due to early activation of the placenta-fetal adrenal axis. Assay methodology is a variable that contributes to difficulties in reproducibility of CRH levels in the obstetric literature. Preterm birth occurred in 10.02% all of births in 2018 in the United States and remains a substantial cause of neonatal morbidity and mortality . Pre. Pre3]. CRH was first suggested as a marker of a placental clock regulating the length of gestation in a seminal study by McLean et al. (1995) that found that measurement of CRH as early as 16–20 weeks identified women destined to deliver preterm as distinct from term or post-term delivery . MultiplWomen with a prior history of preterm birth have a subsequent risk of recurrent preterm birth that is in part determined by their prior history. Previous studies have shown that the number of preterm births, temporal order of prior preterm births, and severity  all interplay to determine a women’s subsequent preterm birth risk –19. BaseA prospective cohort study of women receiving 17-alpha hydroxyprogesterone caproate (17 OHP-C) was conducted and has previously been reported elsewhere . BrieflyThis is an analysis of a subset of patients enrolled in the parent study with maternal blood obtained from women delivering between August 2, 2014, and September 16, 2017. A total of 430 women with at least one prior spontaneous preterm birth between 20 0/7 and 35 0/7 weeks’ gestation were enrolled in the parent study and received weekly 250 mg intramuscular injections of 17 OHP-C commencing between 16 0/7 and 20 6/7 weeks’ and continuing until 36 6/7 weeks’ gestational age or delivery. These women were analyzed in a prospective inception cohort study that utilized a 3:1 matched historical cohort for preterm birth profile, maternal race, and body mass index (BMI). This trial found that 17 OHP-C was ineffective for prevention of recurrent preterm birth and was associated with an increased rate of gestational diabetes .Venous blood was collected in a sub-cohort of the total study population coinciding with routine prenatal care blood draws at 24 and 32-weeks’ gestational age prior to administration of a scheduled weekly 17 OHP-C injection. Venous samples were collected from women who consented to blood collection and attended their prenatal visit during the gestational age window at 24 and 32 weeks. Samples obtained were processed within 4 hours of blood collection, aliquoted, and stored at -80°C until analyzed. This study was approved by the Institutional Review Board of the University of Texas Southwestern Medical Center and by the Human Research Ethics Committee of the University of Newcastle, Australia.CRH levels were initially assessed via enzyme-linked immunosorbent assay (ELISA) kit  without extraction. Analysis was performed at the University of Texas Southwestern Medical Center in batch fashion at a single laboratory by a research associate masked to pregnancy outcomes. All samples were run parallel in duplicate. The intra- and interassay coefficients of variance (CV) were 6.1 and 5.3% respectively.Frozen plasma samples were also transported on dry ice to the Mothers and Babies Research Centre, University of Newcastle, Australia and processed as previously described . PregnanDemographic data and two-group comparisons of delivery outcome  data were analyzed using the Pearson chi-square test for categorical data and the Student’s t-test for continuous measures. If the continuous measures were not judged as a normal distribution, then the Wilcoxon rank-sum test was used. Due to differences in rates of PTB between Hispanic and Black patients, a two-factor  analysis of variance with interaction was performed based on CRH level.In order to present CRH levels across gestational ages for the delivery outcome categories, the CRH values were log transformed and an analysis of variance (ANOVA) with interaction was conducted on the transformed CRH levels. Significance levels and estimates were drawn from these transformed data. The estimates were then back-transformed to the measured domain using an exponential transformation prior to plotting.To determine the association of CRH, prior preterm birth history, and the combination of these two with delivery outcome, the areas under the receiver operating characteristic curves were estimated through logistic regression. Prior preterm birth history was determined using a rank-order pattern of up to the last three deliveries. This pattern was based on the number and order of prior term and preterm deliveries. Further details on this rank-order pattern are provide in supporting information . Areas uGiven that all women in the cohort received weekly 17 OHP-C injections a Pearson correlation coefficient was calculated for 17 OHP or 17 OHP-C maternal blood levels and CRH at 24 weeks.At our institution, 17 OHP-C was studied in a total of 564 women, and venous blood sampling was begun midway through the parent 17 OHP-C study . A totalThe overall rate of recurrent preterm birth in the CRH measurement cohort of 169 patients was 24.9% at <37 weeks and 14.2% at <35 weeks. There were 15 indicated total births, only one of which was preterm at 35–36 weeks. All other preterm births were spontaneous. The population consisted of primarily young, obese, multiparous and predominantly Hispanic women, similar to the original cohort . There wInitial CRH results based on an ELISA for samples at 24 and 32 weeks showed a linear relationship without an increase across gestation . Due to A single CRH measurement at 24 and 32-weeks based on delivery outcome of less than 37 or 35 weeks was associated with an area under the receiver operating characteristic curve (AUC) of less than or equal to 0.70. Using the 24-week samples, the AUC was 0.68 (95% CI 0.59–0.78) for delivery <37 weeks and 0.68 (95%CI 0.55–0.84) for <35 weeks. For the 32 week samples, the AUC was 0.70 (95% CI 0.59–0.81) for delivery <37 weeks and 0.69 (95% CI 0.51–0.87) for <35 weeks. The minimum absolute difference of sensitivity and specificity was at a 24-week CRH level of 70 pg/mL  for delivery <37 weeks and 77 pg/mL  for <35 weeks. For the 32-week CRH level, these levels were 300 pg/mL  for deliveries <37 weeks and 310 pg/mL  <35 weeks respectively.Prior preterm birth history alone was slightly more strongly associated with recurrent preterm birth risk than CRH levels alone. Assessed at 24 weeks, the AUC was 0.75 (95% CI 0.67–0.83) for delivery < 37 weeks and 0.75 (95% CI 0.67–0.84) for delivery <35 weeks. Using 32 weeks, the AUC was 0.78 (95% CI 0.69–0.87) for delivery <37 weeks and 0.81 (95% CI 0.71–0.90) for delivery <35 weeks. The combination of CRH and prior preterm birth was significantly more associated with recurrent preterm birth risk than CRH alone .There were four principal findings for this study of CRH in women with prior preterm birth. Firstly, similar to women without a preterm birth history, in women with a prior spontaneous preterm birth CRH measured by extracted RIA increased with increasing gestational age. Secondly, those delivering either <37 weeks or <35 weeks had a significantly increased CRH compared to those delivering at term. Third, while CRH measurement alone had poor prognostic value, second trimester CRH in combination with prior preterm birth history was better able to identify a subgroup of women at risk for recurrent preterm birth. This indicates a potential ability to distinguish those whose preterm birth results from early activation of the placenta-fetal adrenal axis. Fourth, assay methodology is a variable that contributes to difficulties in reproducibility of CRH levels in the obstetric literature.Our results are notable in that they confirm the rise in CRH is reproducible across variable populations, provided the correct methodology is followed. An earlier rise of CRH is observed in both women with and without a prior preterm birth history who experience preterm delivery in the observed pregnancy , 7–13. POver the years there have been differences reported in plasma processing, extraction technique, as well as in the method of measurement of CRH . Extract8 pg/mL) for cases who delivered <35 weeks and controls who delivered >37 weeks  weeks. The 32-week samples were collected at a mean of 31.6±1.0 weeks and median of 31.6  weeks. Plasma samples were not available from all participants, and it is possible there is selection bias among the samples tested. We did compare demographic data among participants with and without samples and found a greater percentage of non-Hispanic black compared to Hispanic women and a higher percentage of preterm birth in the unsampled women. The effect of 17 OHP-C injections on CRH levels is unclear. The only study to look for such an effect did not find a difference between women receiving 17 OHP-C and those that did not, but we have concerns with the methodology used in that study as outlined in the previous section . We did In pregnant women with a prior history of spontaneous preterm birth higher maternal plasma CRH levels were observed with an earlier rise in those who experienced preterm birth. This is a similar to the rise of CRH in women without a history of preterm birth. The rise in maternal plasma CRH may be useful in identifying early activation of the placenta-fetal adrenal axis as an etiological factor in women at-risk for recurrent preterm birth. Assay methodology is a variable that contributes to difficulties in reproducibility in the obstetric literature.S1 FigUnits for 17 OHP ng/mL, 17 OHP-C ng/mL, and CRH pg/mL.(TIF)Click here for additional data file.S1 FileExplanation of rank-order applied for preterm birth history to construct ROC curve.(DOCX)Click here for additional data file.S2 FileData Analysis by gestational age epochs and spontaneous preterm births.(DOCX)Click here for additional data file.S3 File(SAS7BDAT)Click here for additional data file.S4 FileThis routine contains the formats applied to the variables in Shareddata.sas7bdat.(SAS)Click here for additional data file.S5 FileThe data dictionary for the data in Shareddata.sas7bdat.(DOCX)Click here for additional data file.


Preterm birth is associated with numerous adversities, however, data on positive developmental outcomes remain limited. We examined if preterm and term born adults differ in dispositional optimism/pessimism, a personality trait associated with health and wellbeing. We assessed if birth weight z-score, neurosensory impairments and parental education modified the outcome.We systematically searched PubMed and Web of Science for cohort or case-control studies(born ≥ 1970) with data on gestational age and optimism/pessimism reported using the Life-Orientation-Test-Revised in adulthood(≥18 years). The three identified studies provided data for the two-step random-effects linear regression Individual-Participant-Data meta-analysis.Preterm and term borns did not differ on optimism(p = 0.76). Preterms scored higher on pessimism than term borns, although not after full adjustment. Preterm born participants, but not term born participants, with higher birth weight z-score, had higher optimism scores ; preterm vs term x birth weight z-score interaction p = 0.004).Preterm and term born adults display similar optimism. In preterms, higher birth weight may foster developmental trajectories promoting more optimistic life orientations. Worldwide approximately 15 million preterm  births occur annually, equating to 1 in every 10 deliveries , pretermWhile evidence continues to mount on the negative outcomes following preterm birth, data remains limited on positive developmental outcomes—leaving a disproportionate picture as not all preterms experience adversities. One positive developmental outcome may be dispositional optimism , 13. IndTo our knowledge, no study has explored if preterm and term born adults differ in dispositional optimism and pessimism. Hence, we systematically reviewed the literature and explored in an individual participant meta-analysis (IPD-MA), if young adults born preterm and at term differed in self-reported dispositional optimism and pessimism. Additionally, we also examined if the differences between preterm and term born adults in optimism and pessimism varied by birth weight z-score, neurosensory impairment, and parental education, because they have been identified as effect modifiers in previous literature on preterm birth , 28. As No protocol has been published.Cohort and longitudinal case-control studies with published or unpublished data beginning at birth or before, which had measured optimism/pessimism using the Life Orientation Test-Revised (LOT-R) in young adulthood (18–30 years), and had any gestational age data. Study populations born before 1970 were excluded due to the major changes in neonatal medicine.The original electronic search was performed in PubMed and Web of Science (inception to 2019) and an updated search was performed in June 2021 in PubMed, Web of Science, ProQuest and EBSCO/Host. The full search strategies are provided in S1 File. The study also collaborated with three major international preterm birth study networks where the availability of unpublished data could, also be assessed; PremLife , RECAP , APIC 33, 31–33,Study selection from the electronic searches occurred in three rounds; 1) Title review of all results for relevance, 2) Abstract review of identified studies for inclusion/exclusion criteria, and 3) Full-text review for final inclusion . For unpThe authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committee on human experimentation with the Helsinki Declaration of 1975, as revised in 2008. All study protocols were approved by the respective ethics committee of each participating institution and informed consents were obtained from all participants and their parents/guardian.We included all studies that met the inclusion criteria: ALSPAC , 36, theAll measures for exposure, outcomes and covariates and moderators were pre-specified at the onset of the study. All included studies provided the requested LOT-R, gestational age, birth weight, perinatal and adult follow-up variables outlined below.In uncertain times, I usually expect the best.’) were summed to calculate the optimism score and the negatively worded items (n = 3) to pessimism score (e.g. ‘I rarely count on good things to happen to me.’) [Item level data for the participants’ LOT-R  measurinto me.’) . The stuto me.’) .After harmonizing the LOT-R items, optimism and pessimism scales were scored as described previously . In the Gestational age measured via ultrasound or date of the mother’s last menstrual period was obtained from medical records. Preterm birth was defined as ≤36+6 (weeks+days) of gestational age and term birth as ≥37+0 gestational age. We further categorized preterm birth to Early Preterm, Moderate Preterm , and Late Preterm  births.The variables considered as covariates included participant’s sex (women/men), as well as maternal mode of delivery, smoking during pregnancy(yes/no), age at childbirth(years) and preeclampsia(yes/no), which were taken from medical records for all studies. The variables considered both as covariates and moderators included birth weight z-score, neurosensory impairment and parental education. Education level variables were harmonized according to the International Standard Classification of Education (ISCED)  and dich2 value. Low heterogeneity was defined as an I2 value of 0% to 25%, moderate heterogeneity as an I2 of 25% to 75%, and high heterogeneity as an I2 of 75% to 100%.To examine if preterm and term born young adults differed in optimism/pessimism and if optimism/pessimism varied according to the degree of prematurity, we employed a two-stage random-effects IPD meta-analysis. We fitted the linear regression models to the data from each cohort and then derived the random inverse-variance weighted pooled effects accounting for between-study heterogeneity tested using the Cochran’s Q statistic and quantified by the IApplying the same analytic approach, we examined if participant’s birth weight z-score, neurosensory impairments or parental education modified the developmental outcomes of those born preterm and at term. This was studied by including interaction terms of preterm birth vs term birth x birth weight z-score, preterm birth vs term birth x yes vs no neurosensory impairment and preterm birth vs term birth x parental education into the regression equations following the main effects of these variables.We present the findings as adjusted for sex and for those covariates that were associated with dispositional optimism/pessimism. In preterm and term comparisons, we also conducted sensitivity analyses excluding participants with neurosensory impairment.The study utilized Stata 15.With alpha level 0.05 and 80% power we were able to detect differences between preterm born and term born adults and detect interactions that in effect size were small .The electronic search of PubMed and Web of Science yielded 165 studies. Hand searching of grey literature and the preterm birth cohort networks yielded another 23 possible studies. The updated search yielded an addition 100 studies. After title and abstract review, 5 published studies underwent full-text review. None of the published studies from the electronic search met the inclusion criteria. Of the preterm birth networks’ cohorts with unpublished data, 3 studies met inclusion criteria . After cAs no published studies met the inclusion criteria, the quality of previously published evidence could not be assessed. To evaluate IPD data integrity, the datasets received from each cohort were checked for abnormalities, missing data, out-of-range, inconsistent items or for harmonization issues. No issues were identified when reviewing the IPD provided from any of the three cohort studies. We assessed the risk of bias in the IPD in duplicate  on the cohort level, using a modified version of the criteria set out by Crawford and colleagues  S1 Tabl. AlthougThe IPD-MA study population comprised three birth cohorts: ALSPAC; Born 1990–92, UK , 36, AYLAmong the combined datasets, mothers of preterm born participants were more likely than mothers of term borns to be primiparous, to have delivered via caesarean section, and to have had a multiple pregnancy or pre-eclampsia . Fig 2 sIn the pooled IPD-MA adjusted for participant’s sex, preterm born and term born young adults did not differ on optimism , but preDegree of preterm birth was not associated with optimism (p>0.47 for unadjusted and adjusted models), but by each category decrease in preterm from term birth, pessimism scores increased by 0.14 raw score units [. This increase in pessimism, became non-significant after covariate adjustment (p = 0.26).x yes vs no neurosensory impairment and preterm birth vs term birth x parental education on optimism and pessimism were not significant .In the pooled IPD-MA adjusted for participants’ sex, preterm born adults with higher birth weight z-score scored higher on optimism, while birth weight z-score was not associated with optimism in individuals born at term . There wYoung adults born preterm and at term report no differences on optimism. This is in contrast to what we expected. However, we also found that preterm born adults scored higher on pessimism, although this difference was not significant after adjustments for covariates. A similar finding was observed according to the degree of prematurity in categorical gestational age groups. These findings help illuminate the similarities between preterm born and term born adults. Albeit surprisingly, given that preterm born individuals more often report neurocognitive, socioemotional and physical and mental health adversities , 10, whith and 90th percentile) report less often a depression diagnosis, use less often antidepressant medication, score lower on depressive symptoms [th percentile). Furthermore, young adults born very preterm who were not born with VLBW have better neurodevelopmental and physical health outcomes than preterms born with VLBW [However, in line with our hypothesis, we found that individuals born preterm with higher birth weight z-score had more optimistic life orientations. This finding aligns with previous literature where individuals born preterm and at Very Low Birth Weight, but whose birth weight was appropriate for gestational age, reduces heterogeneity in study’s findings. The inclusion criteria that all cohorts included were from the modern neonatal medicine era, reduces confounding from different neonatal medicine practices, and curtails data attrition as more participants survived into adulthood. The collective statistical power of the IPD-MA, provides the largest assessment t of the optimism/pessimism in preterm born individuals to date. Study limitations include follow-up data attrition limiting the generalizability of the findings, as preterm born and term born individuals that did not participate in the follow-up may differ. While we were able to account for important covariates, we could not adjust for age at follow-up, as ALSPAC data precludes the sharing of birth dates and hence, calculation of age. However, all ALSPAC participants were followed-up at the age of 23 and the overall age range in the cohorts was 19 to 27.1 years.Our IPD-MA showed that preterm born and term born young adults do not differ in dispositional optimism. Important childhood, maternal and familial covariates explained the difference observed in the higher pessimism scores. However, preterm born adults with higher birth weight z-scores were more optimistic than lower birth weight preterm born adults, suggesting that higher birth weights in preterm born infants may foster developmental trajectories that promote more optimistic life orientations. To better reflect the reality of preterm born individuals, positive developmental outcomes following preterm birth warrant further investigation.S1 Checklist(DOC)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S1 File(PDF)Click here for additional data file.


Father involvement in South Africa is low, despite evidence that it can improve maternal and child health and wellbeing. Within a larger randomised controlled trial, we assessed whether father involvement during and after pregnancy increased birth weight and exclusive breastfeeding through improved maternal mental health. At 6‐week postnatal, mothers completed questionnaires on birth, feeding practices, social support, father involvement and postnatal depression. Father involvement during pregnancy was measured by their attendance at antenatal care and the study intervention, whereas postnatal involvement was measured by attendance at antenatal care and type of paternal support provided. Structural equation modelling was used to identify associations between father involvement, maternal depression, low birth weight and exclusive breastfeeding. Among the 212 mother–baby pairs, father involvement was very low with only 43%, 33% and 1% of partners attending early ultrasound, antenatal care and the birth of the child, respectively. Twenty‐nine percent of the mothers showed signs of depression during pregnancy, compared with 7% after birth. Eighteen percent of the infants were born low birth weight, and 57% of mothers reported exclusively breastfeeding at 6 weeks. Father involvement was directly associated with postnatal depression, but it did not directly or indirectly impact exclusive breastfeeding or low birth weight. We conclude that postnatal father involvement can improve postnatal maternal depression and that men would benefit from specific guidance on how they can support mothers during and after pregnancy. Father attendance at pregnancy ultrasound was low despite a personal invitation and the service being offered on a weekend.Structural barriers within the public health system in South Africa continue to limit male attendance at the birth of their child.Father involvement during and after pregnancy was associated with improved maternal mental health.Interventions to improve male involvement should provide men with specific information and guidance on how best to support their partners during and after pregnancy.Research is needed to assess the long‐term impacts of father involvement on maternal wellbeing and healthy child growth and development.1The first 1,000 days of life, from conception to a child's second birthday, are a time of both tremendous potential and vulnerability , In order to improve father involvement during the antenatal and postnatal period, we invited the partners of pregnant women to attend a pregnancy ultrasound, part of an antenatal intervention to improve child growth and development. In the postnatal follow up of the intervention at 6 weeks, we assessed whether father involvement during and after pregnancy is associated with improved birth weight and exclusive breastfeeding in an urban setting in South Africa. We hypothesised that these relationships are mediated by maternal mental health.22.1This paper reports on the 6‐week follow up from a randomised controlled trial assessing the impact of augmented ultrasound during pregnancy on healthy child growth and development compared with standard practice of care. Recruited participants were blindly allocated to the intervention or control arms. A routine ultrasound scan was offered to all participants in the study. The ultrasound examination in the control group followed standard practice of care, whereas the intervention group received additional messages to promote early childhood development, an educational baby book and a printed and electronic image of their ultrasound scan. Full details of the trial intervention and methods can be found in Richter et al. .2.2The study is situated in Soweto, South Africa's largest township located near Johannesburg. All study procedures took place between March 2019 and August 2020 in a research unit at Chris Hani Baragwanath Hospital (CHBH), a tertiary hospital in Soweto.2.3Participants were recruited from the Foetal Medicine Unit (FMU) at CHBH and invited to participate if they had a singleton pregnancy <25 weeks gestation and were over the age of 18 years and lived within Soweto. Women who were found to have severe maternal comorbidities or major foetal abnormalities were excluded from the study but remained in clinical care at CHBH. Participants who attended the ultrasound were requested to attend follow‐up visits with their infant 6 weeks after birth. Mothers in both the intervention and control groups were encouraged to invite the father of the baby to attend all study appointments and were provided with invitation cards to give to their male partner on recruitment.2.4During the ultrasound visit, women completed individual questionnaires on their sociodemographic characteristics and relationship status with the father of the baby. Antenatal depression was measured using the Edinburgh Postnatal Depression Scale (EPDS), a 10‐item self‐reported depression scale that has been validated for use during the antenatal period  was calculated using a principal component analysis (PCA) based on data collected at baseline. Variables included in the index were crowding (number of rooms used for sleeping), household water and sanitation, internet access, and ownership of a washing machine, satellite television, DVD player, computer and car. The index was divided into tertiles. Antenatal father involvement was based on whether the partner attended the study ultrasound or additional antenatal health visits and was recorded as none, at least one or both. Postnatal father involvement was measured using a cumulative score comprising different forms of father involvement, such as responsibility or provisioning as per recommendations from Greene et al. . This in2.5Data were captured and analysed using Stata I/C 14. Categorical descriptive statistics are presented as frequencies and proportions. Continuous descriptive statistics are presented as minimum, maximum, mean and standard deviations.p value < 0.10 were included in the SEM. For the main outcome variables (birth weight and exclusive breastfeeding), simple linear and univariate logistic regression, respectively, was conducted with all potential confounding maternal variables included in the SEM if the p value was <0.10. Intervention arm was controlled for both models. Figures β coefficients. We assess the fit of each model using the root square mean error of approximation (RMSEA), the comparative fit index (CFI) and the Tucker–Lewis index (TLI). A well‐fitting model has RMSEA < 0.05, and CFI and TLI > 0.95. All statistical tests were considered significant with a p value of <0.05, and 95% confidence intervals are presented.Using structural equation modelling (SEM), two individual models were built to test our hypotheses; Model 1 assessed whether antenatal father involvement improved birth weight by improving antenatal maternal mental health, and Model 2 assessed whether father involvement during and after pregnancy increased exclusive breastfeeding through improved postnatal mental health. Antenatal variables were used in Model 1, whereas a combination of antenatal and postnatal variables was used in Model 2. Simple linear regression was undertaken to identify potential confounding variables for antenatal and postnatal maternal mental health. Variables with a 2.6The required sample size for the trial was 100 participants per arm. In total, 249 pregnant women were enrolled in the trial, with 212 attending the 6‐week follow up. We conducted a reverse power analysis using G*power to determine whether the sample size of 212 was sufficient to conduct an SEM analysis. Based on an effect size of 0.17, alpha of 0.05 and two predictors, the power was 0.99 and the sample size sufficient for analysis.2.7The study was approved by the Human Research Ethics Committee  of the University of the Witwatersrand, South Africa (M181915). An amendment was approved by the University of the Witwatersrand in order to film some of the ultrasound appointments. Permission was obtained from CHBH to conduct the study and to oversee adherence to the study protocol. The trial is registered with the Pan African Clinical Trials Registry (PACTR201808107241133). Participants provided written consent and were given a unique study identifier to maintain confidentiality.3Out of the 249 mothers who attended the ultrasound appointment at baseline, 12 of their babies died within their first 6 weeks of life, and 25 were lost‐to‐follow‐up. Presented results are based on the 212 mother–baby pairs who attended the 6‐week follow‐up visit.3.1The sociodemographic characteristics of the participants at baseline are shown in Table 3.2Mode of delivery was almost evenly distributed between normal vaginal delivery and caesarean section at 47% and 53%, respectively. Sixteen percent of mothers and 14% of babies reported experiencing complications at birth, respectively. Complications for the mother included excessive bleeding (9%), hypertension (27%) and infection (35%). Complications for the baby included preterm birth (27%), respiratory difficulties (17%) and jaundice (20%). Eighteen percent of babies were born low birth weight and the mean, minimum and maximum birth weight was 2.96 (SD = 0.57), 0.93 and 4.38 kg, respectively. Just over half (57%) of mothers reported that they put their baby to the breast within an hour after birth and by 6 weeks, 57% of the mothers were exclusively breastfeeding.3.3As seen in Table 3.4Twenty‐nine percent of mothers scored more than 10 on the EPDS during pregnancy compared with 7% after birth. The mean antenatal depression score was seven (SD = 4.96), wereas the mean postnatal depression score was five (SD = 5.18). The maximum score on both occasions was 27.3.5βdirect = −0.0088, p = 0.865, 95% confidence interval (CI) = −0.11 to 0.09] or indirectly impact birth weight , nor did it directly affect antenatal maternal depression . The model also indicated that antenatal maternal depression did not directly impact birth weight . The results of the RMSEA and CFI suggested a well‐fitted model , but the TLI suggested a poorly fitted model (TLI = 0.411).Table βdirect = −0.1578, p = 0.019, 95%CI = −0.29 to −0.03) but that it does not indirectly  or directly  influence exclusive breastfeeding. The results also indicated that postnatal depression did not directly influence whether a mother exclusively breastfed her infant .The fit indexes for Model 2 fit the criteria for a well‐fitting model . The results indicated that postnatal father involvement can directly impact maternal postnatal depression  or lobola (bride price), poverty, housing shortages or incarceration .


Globally, approximately 4.1 million infants died, accounting for 75% of all under-five deaths. In sub-Saharan Africa (SSA), infant mortality was 52.7/1000 live births in 2018 This study aimed to assess the pooled estimate of infant mortality rate (IMR), time to death, and its associated factors in SSA using the recent demographic and health survey dataset between 2010 and 2018.P-value < 0.05.Data were retrieved from the standard demographic and health survey datasets among 33 SSA countries. A total of 93,765 samples were included. The data were cleaned using Microsoft Excel and STATA software. Data analysis was done using R and STATA software. Parametric shared frailty survival analysis was employed. Statistical significance was declared as a two-side The pooled estimate of IMR in SSA was 51 per 1000 live births : 46.65–55.21). The pooled estimate of the IMR was 53 in Central, 44 in Eastern, 44 in Southern, and 57 in Western Africa per 1000 live births. The cumulative survival probability at the end of 1 year was 56%. Multiple births (Adjusted Hazard ratio (AHR) = 2.68, 95% CI: 2.54–2.82), low birth weight infants , teenage pregnancy , preceding birth interval <  18 months , birth order ≥ four , home delivery , and unimproved water source , female sex , immediately breastfeed , and educated mother  and educated father  were statistically significant factors for infant mortality.Significant number of infants died in SSA. The most common cause of infant death is a preventable bio-demographic factor. To reduce infant mortality in the region, policymakers and other stakeholders should pay attention to preventable bio-demographic risk factors, enhance women education and improved water sources.The online version contains supplementary material available at 10.1186/s12887-021-02895-7. Infant Mortality Rate (IMR) is the death of an infant before celebrating the first birthday per thousand live births in a given population . Infant Globally in 2017, approximately 4.1 million deaths occurred within the first year of life, accounting for 75% of all under-five deaths . AccordiThe United Nations (UN) Sustainable Development Goal (SDG) 3 target 3.2 calls reducing under-five mortality to at least 25/1000 live births . In lineEven though most SSA countries go on off-track to the SDG targets regarding infant death, there is a paucity of information on pooled estimates and factors affecting infant death in SSA. So far, there has been no pooled estimate regarding IMR in SSA controlling Country-level frailty using Demographic and Health Survey (DHS) datasets. Conducting and documenting the pooled estimate of IMR, time to death, and its determinants in SSA would help policymakers and health planners for each country to achieve the SDG agenda. Therefore, this study aimed to assess the pooled estimate of IMR, time to death and its associated factors among infant’s mortality in SSA.https://dhsprogram.com/.The data for this study extracted from the recent standard DHS (2010–2018) datasets of 33 SSA countries. Standard Demographic and Health Surveys (DHSs) are nationally representative and population-based surveys collected through uniform questionnaires and manuals that are comparable across countries. The data were collected using multi-stage stratified, cluster sampling techniques for each country. The details of the recorded data are available at The source population consisted of all live births preceding 5 years of the survey period across 33 SSA countries. The study populations were all live births preceding 5 years of the survey period in the selected Enumeration Areas (EAs) for each country. Data extracted from the birth record (BR) file from the standard DHS dataset of SSA countries with at least one recent survey from 2010 to 2018. A total of 93,765 infants were included from 12 East African, 7 Central African, 13 West African, and 3 South African countries. The details of the samples included for each country is available in the supplementary file  did not have a DHS survey report after the 2010/2011 survey year was excluded due to the recent updates. Because the datasets are not publicly available, three SSA Countries  were excluded from this study.The outcome variable of this study was time to infant death in months. The survival time of an infant beyond 12 months was declared censored. Infant death between birth and 12 months was declared as an event. The outcome variable coded 0 as censored and 1 as event .Socioeconomic and demographic variables include mothers and husband education , household wealth index , residence , latrine source , water source , and County income. Maternal reproductive and obstetric variables include preceding birth interval , teenage pregnancy , place of delivery , antenatal care visit , and birth order . Moreover, infant characteristic variables include the child sex , weight of the child at birth , and plurality of the child .The data were cleaned, coded, and extracted using Microsoft Excel and STATA version 16/MP software. Sample weighting was performed for each country before further analysis.DHS.rates R package in R software. The DHS.rates R package can estimate the point estimate of IMR with their standard error for each country [metan” STATA command.Infants born in different cohorts do not contribute equally to the denominator of the IMR calculation. As a result, all live birth infants do not contribute equally to the infant mortality calculation in the DHS dataset. The pooled estimate of IMR in SSA was estimated using the  country . After cθ provides information on the variability (dependency) of the population in the same Country. Infants in Country i with ui > 1 and ui < 1 have a more frail than higher risk and lower risk respectively. Based on the different frailty term one frailty term was employed using Country taken as random effect dependency. For a single frailty term, the model specification is given by [The Frailty model has an unobserved multiplicative effect on the hazard rate for all individuals in the same group. In the shared frailty model infants in the same Country share the same nuisance (frailty) factor. Parameter given by .\documeni = exp.(wi) is the frailty for the ith Country. ui’s, i = 1,. .., s, are the actual values of a sample from density fU.where uThe parametric frailty model fitted using the Gompertz baseline hazard distributional assumption and the gamma frailty distribution model fitted in Country taken as random effects frailty for the independent variables.θ) by two-plus frailty(θ). The higher the frailty(θ) the higher dependency and the higher Kendall’s tau (τ) [The correlation between any two event times from the same country was measured using Kendall’s tau (τ). Kendall’s tau (τ) measured the dependency of two events in the same country, dividing the frailty ( tau (τ) .\documenThe best fit model was selected using Akakian Information Criteria (AIC) and the Log-likelihood ratio test. The lowest Akakian Information Criteria and the highest Log-likelihood ratio value indicates the best fit model. The Cox-Snell residual plot also employed for the model diagnosis. If the model fits the data well, the Cox-Snell residuals should have a standard exponential distribution with λ = 1. One way to verify the fit is to calculate an empirical estimate of the cumulative hazard function based on the Kaplan–Meier survival estimates taking the Cox–Snell residuals as the time variable. If the model fits the data, the plot should be a straight line with a slope of 1.091/26/1006/12). As well, a waiver of written informed consent secured from the International Review Board of Demographic and Health Surveys (DHS) program data archivists to download the dataset for this study. The dataset was not shared or passed on to other bodies.This study was performed under the ethical standards of the Helsinki declaration and its subsequent amendments. The ethical clearance approved by the University of Gondar Institutional Review Board (IRB) (ref:The mean age of the mother was 28 (± 7 SD) years and, most (74%) of the mothers were in the age group of 20 to 34 years. The majority (92%) of the mothers were married. Most 71%) of the respondents were rural inhabitants. Eighty per cent of the households headed by males and more than three-fourth (78%) of the households used an open water source. Among SSA countries, 60% of them were low-income countries  were males. Ninety-five per cent of infant births were singleton. Only 59,480 (82%) of infants were born with a preceding birth interval greater than 2 years. Twenty per cent of infants had been low birth weight. Only 40% of infants were immediately breastfed at birth. Moreover, 57,416 (63%) infants were delivered at the health facility. Only 4785 (5%) of them give birth by cesarean section . The pooled estimate of IMR was 53 per 1000 live births (95% CI: 43.13–63.44) across six Countries of Central Africa region, 44 per 1000 live births (95% CI: 39.65–48.48) in 11 Countries of the East Africa region, 44 per 1000 live births (95% CI: 31.06–57.53) among three South African Countries, and 57 per 1000 live births (95% CI: 49.62–64.63) across 13 West African Countries Fig. . The pooFrom a total of 93,765 infants, 20,865 infants were died before celebrating their first birthday. The cumulative survival probability of infants at the end of 1 year was 56% (95% CI: 0.55–0.57). The cumulative survival probability of surviving at the end of 6 months was 81%. The cumulative survival probability at the end of 1 year was 55% among males and 58% among females . The negative shape parameter indicates the hazard of death among infants were decreased exponentially as the age of infants increases. The dependency (heterogeneity) of infant death in the same Country estimated by the model was statistically significant with a value theta (θ) = 0.06 , and the dependence within-country was τ = 3% (95% CI: 0.02–0.05) which the lowest dependency was 2% and the highest 5% across the country.After controlling country-level frailty, the results from Gompertz parametric baseline hazard distribution revealed that infant, maternal reproductive and obstetrics, and socioeconomic characteristics were statistically significant predictors for infant survival Table .Table 5RInfant sex, plurality, birth weight, and immediate breastfeeding status after birth had a statistically significant association with infant survival. The estimated hazard of death among female infants was lower by 14% as compared to male infants . The risk of death among multiple-birth infants was 2.68 times higher than singleton birth infants . The hazard of infant death among smaller than average birth weight infants at birth was higher by 28% than the average birth size at birth . Infants with larger than average birth weights were 5% less likely to die than the reference category . Moreover, the estimated hazard of death among infants who initiated immediately breastfeed after birth was lower by 66% as compared to their counterparts .Teenage pregnancy was a risk for infant survival. Infants born from whose mothers age between 15 and 19 years were 19% more likely to die as compared to infants born from mothers older than 20 years . The estimated hazard of death among infants born less than 18 months preceding birth interval was 3.27 times higher than infants born greater than 2 years preceding birth interval . As well, infants born between 18 and 23 months preceding birth interval were 93% higher risk of death as compared to the reference category . Higher birth order greater than four were higher risk of death by 14% than their counterparts . Moreover, the hazard of death among infants born at home was higher by 8% as compared to infants born at a health facility .The estimated hazard of death among infants born from an educated mother (secondary and above) was reduced by 12% as compared to infants born from non-educated mothers . Besides, infants born from an educated father who had primary education and secondary and above education level were 5 and 10% lower than infants born from non-educated fathers respectively. Furthermore, infants born from households that use unimproved water sources were 7% more likely to die than households that used unimproved water sources  had a statistically significant highest estimate of IMR in the region. The pooled estimate of IMR in the East Africa region was 44.07 per 1000 live births lower than the pooled estimate SSA. Mozambique (64.12/1000 live birth) had the highest and Rwanda (32.29/1000 live birth) had the lowest estimate of IMR as compared to other East Africa region countries. The pooled estimate of IMR in the Southern Africa region was 44 per 1000 live births which are lower than SSA estimate but not statistically significant. Lesotho had the highest point prevalence of IMR in the South Africa region. Furthermore, the pooled estimate of IMR in the West African region (57 per 1000 live births) was higher than the rest regions of SSA. Sierra Leone had a significantly higher estimate of IMR; Whereas, Gambia and Ghana had a significantly low estimate of IMR than the West Africa region pooled estimate.The pooled estimate of IMR in SSA was alike to the recent Inter-agency Group for Child Mortality estimation in SSA in 2018 (52.7/1000 live births)  whereas,This study revealed that infant death was reduced by 14% among female infants as compared to male infants which is supported by different kinds of literature –19. AnotThis study evidenced that the risk of death among multiple-birth infants was higher by 2.68 times than singleton births. This finding was similar to previous studies conducted in Ethiopia , a birthIn the present study, a higher risk of death was found among smaller than average birth weight infants which had a higher risk of death by 28% than average birth weight infants. This finding is in line with existing literatures , 19, 29.Moreover, infants who had immediately breastfeeding status at birth had a lower risk of death by 66% in the infantile period which was similar to the previous studies , 32–34. Teenage pregnancy had a higher risk of infant death by 19% as compared to their counterparts. Similar studies witnessed that teenage pregnancy is a risk factor for infant survival , 29. AnoThis study showed that a short birth interval was a significant predictor of infant mortality. The hazard of death among infants born less than 18 months preceding birth interval was higher by 3.27 times than infants born with a birth interval of more than 2 years. As well the risk of death was also higher by 93% among infants born with a birth interval between 18 and 23 months as compared to the reference category. Different studies supported the findings of this study. Evidence from 52 Demographic and Health Surveys indicates that short birth interval had a risk of infant survival . AnotherPlace of delivery was a significant predictor for infant survival. Infants born at the home had a high risk of death by 8% as compared to health facility birth similar to previous studies . ContrarFurthermore, born from educated mothers (secondary and above) benefited by a 12% increased survival than infants born from non-educated mothers; which is similar to previous existing literatures , 46–48. This study follows some limitation and strengths: Since the study was conducted based on a nationally representative multi-country large dataset that could enhance the generalizability of the estimates in infant mortality in SSA. Controlling country-level dependency using a shared frailty model could give an unbiased effect size. Another strength of this study was estimating the pooled estimate of IMR in SSA and sub-regions will give invaluable information for region-specific interventions. However, the data were collected cross-sectionally at a different point in time by self-reported interview, which would be prone to recall and social desirability bias. Substantial statistically significant heterogeneity was observed in pooled estimate IMR that would affect the interpretation of the pooled estimate. The drawback of the secondary nature of data was inevitable.Even though the IMR in SSA becomes decreasing, still a significant number of infants were dying. West and Central Africa regions had the highest infant death. The most cause of infant death is preventable bio-demographic factors such as immediate breastfeeding status, teenage pregnancy, preceding birth interval, and birth order. As well, infant sex, multiple pregnancies, place of delivery, birth weight, mother and father education, and water source were statistically significant factors for infant mortality in SSA.To tackle infant mortality in SSA, policymakers and other stakeholders of the country should give prior attention to modifiable bio-demographic factors such as preceding birth interval, immediate breastfeeding status, and teenage pregnancy.Additional file 1: Table A. Sample size for infant survival in SSA for each country. Table B. Infant mortality rate with their standard error for each SSA country. Figure A. Forest plot of the pooled estimate of IMR in urban inhabitants across SSA countries using the recent DHSs between 2010 to 2018, 2020. Figure B. Forest plot of the pooled estimate of IMR in rural inhabitants across SSA countries using the recent DHS between 2010 to 2018, 2020. Figure C. Forest plot of the pooled estimate of IMR by country income across SSA countries using the recent DHS between 2010 to 2018, 2020.


Adverse birth outcome is a common health problem consisting of several health effects involving pregnancy and the newborn infant. Infants with one or more adverse birth outcomes are at greater risk for mortality and a variety of health and developmental problems. Factors such as the age of the mother, antepartum hemorrhage, history of abortion, gestational age, anemia, and maternal undernutrition have predisposed the mother to adverse birth outcome. For appropriate prevention of the adverse birth outcomes, data pertaining to determinants of adverse birth outcomes are important. Therefore, this study was aimed to assess the determinants of adverse birth outcomes among women who give birth in public hospitals of western Ethiopia.P-value < 0.05.An institutional-based unmatched prospective case-control study was conducted from February 15 to April 15, 2020, in selected public hospitals of western Ethiopia. From mothers who gave birth in public hospitals of Wollega zones, 165 cases and 330 controls were selected. Mothers with adverse birth outcomes were cases and mothers without adverse birth were controls. Data was collected by structured interviewer-administered questionnaires. In addition to the interview, the data collectors abstracted clinical data by reviewing the mother and the babies’ medical records. The collected data were entered into Epi info version 7 and exported to SPSS version 21 for analysis. Finally, multivariable logistic regression was used to identify determinants of adverse birth outcomes at A total of 495 mothers (165 cases and 330 controls) were included in the study with a mean age of 28.48 + 5.908. Low ANC visit , premature rupture of membrane , being Anemic , pregnancy induced-hypertension , not getting dietary supplementation , and physical abuse  were significantly associated with the development of the adverse birth outcome.Low antenatal care visit, being anemic, premature rupture of membrane, pregnancy-induced hypertension, not getting dietary supplementation, and physical abuse were determinants of adverse birth outcomes. The clinicians should play a pivotal role to improve antenatal care follow up, counsel, and supplement recommended diets and minimize violence and abuse during pregnancy.The online version contains supplementary material available at 10.1186/s13690-021-00776-0. The adverse birth outcome is a common health problem consisting of several health effects involving pregnancy and the newborn infant. Birth outcomes are measures of health at birth and their magnitude is dramatically decreased in the past 40 years. However; there is still a large gap between developing and developed countries. Infants with one or more adverse birth outcomes are at greater risk for mortality and a variety of health and developmental problems. For appropriate prevention of adverse birth outcomes, data pertaining to determinants of adverse birth outcomes are important. An institutional-based unmatched prospective case-control study was conducted from February 15 to April 15, 2020, in selected public hospitals of western Ethiopia. In this study, low Antenatal care (ANC) visits, being anemic, premature rupture of membrane, pregnancy-induced hypertension, not getting dietary supplementation, and physical abuse were determinants of adverse birth outcomes. The clinicians should play a pivotal role to improve ANC follow up, counsel, and supplement recommended diets and minimize violence and abuse during pregnancy.The online version contains supplementary material available at 10.1186/s13690-021-00776-0. Although most pregnancy and childbirth are a joyful experience for most women, it sometimes ends up in adverse birth outcome . The advBirth outcomes are measures of health at birth and their magnitude is dramatically decreased in the past 40 years. However; there is still a large gap between developing and developed countries . GloballInfants with one or more adverse birth outcomes are at greater risk for mortality and a variety of health and developmental problems . Babies The etiologies of adverse birth outcomes are multifactorial and not completely understood yet. Studies have shown that sociodemographic factors such as the age of the mother , 23, 24,For appropriate planning and implementing proper interventions to prevent the adverse birth outcome, data pertaining to determinants of adverse birth outcome are very important. Although there are studies on the various forms of adverse birth outcomes, there is limited data on the overall adverse birth outcomes in Ethiopia. To the best of our knowledge, this is the first study to assess adverse birth outcomes and their associated factors in the western part of Ethiopia. Therefore, this study was aimed to assess the determinants of adverse birth outcomes among women who gave birth in public hospitals of western Ethiopia. The finding of this study will help the health care providers in planning health interventions to improve the wellbeing of children and women.An institutional-based unmatched prospective case-control study was conducted from February 15 to April 15, 2020, in selected public hospitals of Wollega zones, western Ethiopia. According to the 2010 Central Statistical Agency (CSA) report, the total population of Wollega zone is 3,345,675  . The WolAll mothers who gave birth at the selected hospitals of Wollega zones were included in the study. Women with induced termination of pregnancy for medical reasons, women with a serious general medical condition, unknown last menstrual period (LMP) or not reliable ultrasonography and unable to communicate were excluded. Cases were mothers with at least one adverse birth outcome . Controls were mothers without adverse birth outcomes .The Sample size was calculated using the double population proportion using EPI-Info 3.5.1 statistical software. The proportion of low educational status, advanced maternal age, rural residence, age at first sex ≤14, and the age difference between the partner at first intercourse ≥5 years was used to determine the sample size from a study done in Debre Tabor town . MaternaEligible cases were selected consecutively and the consecutive two controls were selected until the required sample size was achieved. The number of cases and controls were proportionally allocated to each hospital based on the number of mothers who gave birth at each of the selected hospitals in 4 months before the data collection time. Then, the average number of mothers expected to give birth per 2 months in each of the respective hospitals was estimated. Accordingly, we included 42 cases and 84 controls in Nekemte specialized Hospital, 38 cases and 76 controls in Wollega university specialized hospital, 27 cases and 54 controls in Gimbi general Hospital, 22 cases and 44 controls in Shambu general hospital, 29 cases and 58 controls in Nedjo hospital and 23 cases and 46 controls in Arjo Hospital.Data was collected by structured interviewer-administered questionnaire adapted from the Ethiopian Demographic and Health Survey (EDHS) and other similar studies , 27, 30.The questionnaire was translated to the local language Afan Oromo and then back to English by two different language experts to check for consistency. Five percent of the questionnaire (27 participants) was pre-tested at the same study area 5 days before data collection and modification was made based on the pre-test result. The ratio of a case to control used in the pretest was 1:2 (9 cases and 18 controls). Five days of training on the objectives of the study, sampling technique, ethical consideration, and data collection techniques was given for data collectors and supervisor. Continuous follow-up and supervision of data collection were made by the supervisors. The collected data were checked by the supervisor daily for completeness.P-value less than 0.25 were entered into a multivariable logistic regression model. A multivariable logistic regression model was fitted to identify independent determinants of adverse birth outcomes. Model fitness was tested with Hosmer-Lemeshow goodness of fit test and omnibus tests of model coefficients. Variance inflation factor (VIF) and tolerance test were also used to check multicollinearity. Adjusted odds ratio (AOR) with a 95% confidence interval (CI) was calculated to determine the strength of an association. P-value < 0.05 was considered statistically significant in multivariable logistic regression.The collected data were coded, cleaned, and entered into Epi info version 7 and exported to SPSS version 21 for analysis. Descriptive statistics like frequencies and percentages were performed as univariate analysis. In this study, cases were coded as 1, and controls were coded as 0 for analysis. Bivariable logistic regression analysis was used to assess the unadjusted effect of each independent variable on the dependent variable. Variables that have a Preterm birth: is when a baby is born before 37 completed weeks of gestation but after 28 weeks of gestation. Low birth weight: is when a baby’s birth weight is below 2500 g or below 2.5 kg. Macrosomia: is defined as birth-weight over 4 kg irrespective of gestational age. Stillbirth: is when the infant died in the womb or during the intrapartum period after 28 weeks of gestation. Birth defect/congenital anomaly: is when there are structural changes in one or more parts of the infant’s body that are present at birth. Adverse birth outcome: is when a woman met at least one of the above conditions. No adverse birth outcome: Those women who gave normal live birth without the above-mentioned abnormal birth outcome [From the total of 543 eligible participants (181 cases and 362 controls), 495 mothers (165 cases and 330 controls) were participated in the study making a response rate of 91.2%. The mother’s age was lying between 15 and 44 years with a mean of 28.48 + 5.908 SD. The majority of the study participants, 141 (85.45%) of the cases and 286 (86.67%) of the controls were Oromo. Regarding the religion of the respondents, 86 (52.12%) of the cases, and 160 (48.48%) of the controls were protestant. About 153 (92.73%) of the cases and 311 (94.24%) of the controls were married. Regarding educational status, 47 (28.48%) of the cases and 108 (32.7%) of controls had a diploma and above. The majority of the study participants, 104 (63.03%) of the cases and 212 (64.24%) of controls were from rural. More than half of the study participants, 105 (63.64%) of the cases and 189 (57.27%) of the controls were married at an age between 18 and 23 years. Regarding monthly income, 37(22.42%) of the cases and 75 (22.73%) of the controls get a monthly income of 2001–3000 Ethiopian birr. Concerning family size, 107 (64.85%) of the cases, and 197(59.7%) of the controls have 4–6 family size  of the cases and 217 (65.76%) of the controls have less than 3 births. The birth space for 54 (32.73%) cases and 121 (36.67%) of controls were more than 23 months. The majority of the study participants, 118 (71.52%) of the cases 247 (74.85%) of the controls were used family planning before the current pregnancy. The majority of participants, 125 (75.76%) of the cases and 260 (78.79%) of the controls were planned their pregnancy. About 60 (36.4%) of the cases and 182 (55.15%) of the controls were attended ANC more than four times. Concerning danger signs, 123 (74.55%) of the cases and 267 (80.9%) of the controls were didn’t experienced danger signs during pregnancy. More than half, 88 (53.33%) of the cases and 196 (59.39%) of the controls were delivered through SVD. Concerning the previous history of adverse birth outcomes, 131 (79.4%) of the cases, and 271 (82.12%) of the controls had no history of adverse birth outcomes. About 106 (64.24%) of the cases and 280 (84.85%) of the controls didn’t experience PROM, and most of the labor started spontaneously for 125 (75.76%) of cases and 269 (81.52%) of controls  of the controls and 124 (75.15%) of the cases and nearly all, 322 (97.58%) of the controls and 160 (96.97%) of the cases had no history of hypertension and cardiac diseases respectively. Three hundred eleven (94.24%) of the controls and 154 (93.33%) of the cases were HIV negative. The majority of participants, 291 (88.18%) of the controls and 120 (72.73%) of the cases, 317 (96.06%) of the controls and 154 (93.33%) of the cases, and 289 (87.58%) of the controls and 154 (93.3%) of the cases had no history of Anemia, malaria, and STI respectively.2. The majority of the participants, 281 (85.15%) of the controls and 108 (64.45%) of the cases had no pregnancy-induced hypertension. More than half, 192 (58.18%) of the controls and 111 (67.27%) of the cases had a height of < 150 cm. Regarding the time of ANC visit, 90 (54.55%) of the cases and 167 (50.6%) of the controls visited in the 2nd trimester. Almost all,321 (97.27%) of the controls and 163 (98.79%) of the cases delivered a single child. Labor duration has lasted for 8–15 h in 143 (43.33%) of the controls and 65 (39.4%) of the cases. The majority of participants, 217 (65.75%) of the controls and 102 (61.82%) of the cases travel less than 1 h to reach the health facility  of the controls, and 122 73.94%) of the cases had 18–24 kg/m.94% of tThe majority of the participants, 281 (85.15%) of the controls and 128 (77.58%) of the cases had no history of substance use. Three hundred seven (93.03%) of the controls and 144 (87.27%) of the cases had no history of physical abuse and harassment. Almost all, 313 (94.85%) of the controls and 159 (96.36%) of the cases were not used traditional medicine, and about 254 (76.97%) of the controls and 113 (68.48%) of the cases didn’t experience stress during pregnancy . The odds of developing adverse birth outcomes were 2.83 times higher among mothers who developed PROM than mothers who do not develop . The odds of developing adverse birth outcomes were 2 times higher among anemic mothers than their counterparts . The study revealed that mothers who developed pregnancy-induced hypertension were 2.3 times higher odds of developing adverse birth outcomes than their counterparts . The odds of developing adverse birth outcomes were 2.47 times higher among mothers who didn’t get dietary supplementation than mothers who got dietary supplementation . Mothers who experienced physical abuse were 2.13 times more likely to develop adverse birth outcomes than mothers who do not exposed to physical abuse/harassment  . This finding is congruent with the results from Gonder , HawassaThe odds of developing adverse birth outcomes were 2 times higher among anemic mothers than their counterparts . This finding is consistent with the study done in Dessie , Tigray Premature rupture of the membrane (PROM) is one of the significant factors associated with adverse birth outcomes . The finThe hypertensive disorder is one of the most common problems encountered during pregnancy and contribute to the adverse birth outcome. This study revealed that mothers who developed pregnancy-induced hypertension were 2.3 times higher odds of developing adverse birth outcomes than their counterparts . This finding is supported by a study done in Suhul hospital Shire  and GondThe study results also revealed that the odds of developing adverse birth outcomes were 2.47 times higher among mothers who didn’t get dietary supplementation than their counterparts . A systematic review study indicated that nutrients have a profitable effect on reducing adverse birth outcomes . AnotherThe study findings also indicated that mothers who experienced physical abuse were 2.13 times more likely to develop adverse birth outcomes than mothers who do not exposed to physical abuse . This finding is supported by the study done in Tigray  and HosaIn this study, low ANC visits, being anemic, premature rupture of membrane, pregnancy-induced hypertension, not getting dietary supplementation, and physical abuse were determinants of adverse birth outcomes. The clinicians should play a pivotal role to improve ANC follow up, counsel, and supplement recommended diets and minimize violence and abuse during pregnancy.Additional file 1.


The occurrence of a mesenteric cyst (MC) is common in adults while in children and in infants is rare. In adults mesenteric cysts are often asymptomatic and discovered incidentally; however, in children they commonly present with symptoms of abdominal pain or distension with fever and leucocytosis. We report on a rare case, in our experience, of Mesenteric Chylous cyst (MCC) in an infant with signs and symptoms of intestinal obstruction. Discussion of literature is also reported. Mesenteric cyst (MC) is common in adults while in children and in infants is extremely rare –3. CliniWe present a case of a baby boy, born at 37 weeks GA . The prenatal ultrasound performed in the third trimester of pregnancy showed any anomalies. At birth he had no clinical signs of obstruction. At 4 months of age he was hospitalized for bloody stool, fever and bilious vomiting. He was febrile to 38.9 °C and tachycardic to 205 beats per minute, with a blood pressure of 88/45. On physical exploration the abdomen was soft and mildly distended. White blood cell count and PCR were severely increased. Plain abdominal x-ray showed air fluid levels . AbdominThe infant reached the full enteral feeding on day 3rd post-operative and discharged home in good condition at day 6th. The follow up performed for 1, 2, and 4 years after surgery did not showed recurrence.sign (We report a baby boy 4 month old with chylous MC. The chylous mesenteric cyst is rarely been reported in the literature. Those cysts are commonly observed in adults but rarely seen in children . MC are sign  or an “asign  have beesign , 15. In Our reported case, can be considered one of the few MCC patients presenting as intestinal obstruction in early infancy. The need of differential diagnosis with lymphangioma or other abdominal cystic lesions and the curative role of MCC excision are important elements for the pediatric surgeon to consider MCC as a possible cause of intestinal obstruction. In fact, early detection of MCC may limit the need of intestinal resection of interested bowel . A prompThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.AS and FI conceived the study. VC, RC, FC, CM, and MN collected and analyzed the data. FB supervised the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.