Early nutritional factors were compared between the lowest and highest growth quartiles. Although the highest growth quartile experienced less days of parenteral nutrition and higher enteral caloric density in the first week, as the data was analyzed, potential statistical pitfalls became apparent. Therefore, the aim of this study was to investigate selection bias and cohort effect related to both the inclusion criteria for this cohort as well as the inherent challenges in comparison of preterm infant growth trajectories by standard fetal growth charts.Growth in preterm infants is associated with improved outcomes during both the initial hospitalization and long-term. A single center investigation evaluated preterm infant in-hospital growth trajectory and how it related to early nutritional practices as a way to identify areas for quality improvement. Infants born <34 weeks’ gestational age and with discharge at or prior to 40 weeks’ gestational age were included and were divided into quartiles based on their change in weight  Measuring postnatal growth is a critical component of preterm infant hospital care, and growth trajectory before term equivalent age is linked to neurodevelopmental outcomes ,2,3,4,5.z-scores from birth to discharge among preterm infants who were discharged by 40 weeks’ gestational age. In particular, we aimed to investigate whether feeding practices in the first postnatal month are associated with growth in this population of premature infants. In our investigation of the factors associated with high or low change in weight z-score, we encountered two interesting phenomena with respect to the chosen outcome of interest and its association with in-hospital feeding practices. In this paper, we aim to evaluate the role of selection bias in studies of preterm infant growth trajectory and the potential for confounding due to cohort effect.Since neurodevelopmental outcomes have been linked to postnatal growth, a single institutional quality improvement initiative, in a tertiary NICU, was designed to identify potential factors affecting postnatal growth rates and, thereby, to identify opportunities for positive change. The factors investigated were focused around early nutritional practices, including days of parenteral nutrition, feeding type: mother’s own milk or donor milk, and fortification: highest calories achieved at different time points in the first postnatal month. At the conception of this project, we parameterized postnatal growth as the change in weight The subjects in this retrospective observational study were infants born between 1 June 2016 and 31 May 2018 and admitted into the NICU at Yale New Haven Hospital. Our two inclusion criteria were (1) gestational age at birth between 22 and 34 weeks, and (2) hospital discharge before or at 40 weeks’ gestational age. Birth weight was intentionally not used in assessment of eligibility to avoid the skew towards infants born smaller at 30 to 34 weeks’ gestational age that occurs when very low birth weight (VLBW) is an inclusion criterion.z-score, calculated by the Fenton growth chart as the primary measure of growth [z-score at birth and discharge, obtained by inputting infant’s sex, gestational age at birth and discharge, and respective infant weights. We then calculated postnatal in-hospital growth as the difference between discharge and birth weight z-scores. Infants were grouped into quartiles of the observed change in z-scores. Following the example set by Ehrenkranz et al. of comparing growth trajectory by quartiles, we used the first and last quartiles of this change in weight z-score to define two groups: low growth quartile (LGQ) and high growth quartile (HGQ) [As this study was part of a quality improvement initiative to improve in-hospital growth of preterm infants, we chose weight f growth . We usedle (HGQ) . We focuTo identify correlates of high and low growth, we compared the two groups with respect to infant demographic and clinical characteristics, as well as feeding experiences among these infants. Comorbidities commonly associated with growth failure such as intraventricular hemorrhage (IVH), necrotizing enterocolitis (NEC), patent ductus arteriosus (PDA), and small-for-gestational age (SGA) status at birth were collected, as well as head circumference and length at birth and discharge. The comorbidities were collected by Internal Classification of Diseases (ICD) codes for the respective diagnosis. For feeding experiences, we collected first postnatal day without parenteral nutrition (PN), as a proxy for days to full enteral feeds. Additionally, we collected the highest concentration of enteral calories received  and types of feeds the infant was receiving, i.e., mother’s own milk (yes/no) or donor milk (yes/no) per week over the first postnatal month. The feeds were not quantified by amount. They were counted as “yes” if any mother’s own milk or donor milk were received by the infant. Calories were based on documentation from the medical record system, as less than 24 kcal, 24 kcal, or greater than 24 kcal. Less than 24 kcal included both 22 kcal or 20 kcal (no fortification) feeds, and greater than 24 kcal included feeds with any fortification over 24 kcal. Standard fortification is used in the unit where this study was performed, as opposed to adjusted or targeted with recommendation for addition of human milk fortification at 100 mL/kg/day enteral feed volume. There was no data collected regarding the specific calorie content in each category or the type of fortification used.z-score, weight gain was compared as growth velocity. Average growth velocity was calculated as g/kg/day from birth to hospital discharge using the exponential model [z-score for an infant of a given sex and gestational age will come from the underlying distribution of infants of that sex who are born at that gestational age, i.e., an infant’s trajectory of change in his or her z-score up to the term gestational age is assumed to be composed of serial z-scores reflecting how well that infant is doing relative to a fetus born at that gestational age. However, an infant’s gestational age at birth can be viewed as exhibiting a cross-sectional, or cohort, effect on his or her longitudinal trajectory of change in growth. Therefore, simply using weight z-scores obtained from serial cross-sectional data (cohort-averaged growth) has the potential to conflate the cross-sectional or cohort effect of gestational age at birth and the longitudinal effect of gestational age, expressed as the postnatal day from birth. Therefore, our second growth outcome was the average change in infant’s weight across gestational age, separating the cohort-averaged effect of gestational age on weight into cross-sectional and longitudinal effects. Similar to the primary outcome of change in weight z-score from baseline to discharge, we investigated whether patient demographic and clinical characteristics, as well as feeding practices were associated with the mean change in weight. All data was collected via electronic medical records using the Joint Data Analytics Team at our institution.In addition to the comparison of change in weight al model . Calculaz-score and used parametric (Student’s t-test) and non-parametric (Mann–Whitney U test) approaches to compare continuous variables between LGQ and HGQ groups. Chi-square or Fisher’s exact tests (as appropriate for expected counts of less than five) were used to compare the two extreme groups of postnatal growth for categorical variables. We visually summarized the dependency of the change in weight z-score from baseline to discharge on gestational age at birth and birth weight z-score, using a three-dimensional figure resembling a heat-map.Descriptive summary statistics, such as mean (standard deviation), median (range), as well as count (percent) were used to summarize characteristics of preterm infants. Distributions of continuous variables were visually examined for deviations from normality and for presence of potential outliers using box plots and Q-Q plots. We tabulated demographic and clinical characteristics, as well as feeding practices by the quartiles of change in weight z-score (the primary outcome)—were known to confound the association between type of feeding and change in weight z-score. This is described as selection bias. To balance groups of infants receiving and not receiving mother’s own milk in the first postnatal month with respect to confounders, we used augmented inverse probability weighting (AIPW), to estimate the average causal or treatment effect (ATE) of mother’s own milk on the change in weight z-score in the full cohort [z-score, gestational age at birth, growth velocity in kg/g/d, and days on PN. Inverse probability weights were then calculated by taking the inverse of the propensity scores and were applied in modeling the causal association between the mother’s own milk variable and change in weight z-score using linear regression. An absolute value of a standardized difference of <0.10 was used to indicate balance in potential confounders [Because infants were not randomized to receive mother’s own milk in the first postnatal month, other factors associated with both—the probability of receiving mother’s own milk (the exposure variable of interest) and change in weight l cohort ,11,12,13founders . We usedMean change in weight across gestational age  was modeled using linear mixed effects (LME) approach, with race, sex, mother’s own milk by postnatal day 28, and highest number of calories achieved per week in the first month , with a random intercept and a random slope for each infant to account for the within-infant correlation in weights across gestational age. Likelihood ratio test  using a mixture of two chi-square distributions for the level of significance confirmed that we needed to retain both random effects. To examine whether a model with the decomposed effect of gestational age  fits the data better than a model with time-varying gestational age (cohort-averaged), we tested the equality of the cross-sectional and longitudinal parameters via LRT . To show all three possible effects of gestational age on change in weight, we plotted: (1) smoothed mean trajectories of change in weight over gestational age by birth gestational age, (2) the cross-sectional effect of gestational age by smoothing over weights at birth gestational age only, and (3) the cohort-averaged effect by smoothing over weight values across all gestational ages. Smoothed trajectories were obtained using locally estimated scatterplot smoothing (LOESS), with second-degree polynomial effect of gestational age at the center of neighboring observations and the smoothing parameter set to 0.6.p < 0.15 because we did not power our study. Analyses were performed using SAS 9.4  and R-statistical software.Statistical significance was established at the two-sided alpha of 0.05, but because such a threshold is a convention and we did not want to discount a clinically meaningful effect, we also reported 95% CIs and noted z-score was −1.0 . As described, the cohort was divided into quartiles based on change in weight z-score. A change in weight z-score of ≤−1.34 defined the LGQ. A change in weight z-score of >−0.57 defined the HGQ. The complex dependency of the change in weight z-score from birth to discharge on the birth gestational age and birth weight z-score is illustrated in z-scores and less favorable change in weight z-scores as shown by more negative values (pins on the red color spectrum). In contrast, infants born later had lower weight z-scores at birth and more favorable change in z-score at discharge (pins on the green color spectrum).Our initial search yielded 204 preterm infants, with a mean birth gestational age of 30.3 weeks (SD = 2.24), and a mean birth weight of 1393.9 g (SD = 379.5). No outlying values were identified. For the cohort, the mean and the median change in weight p > 0.05) were found with respect to sex or race, as well as comorbidities in this cohort of preterm infants with hospital discharge prior to or at 40 weeks’ gestational age , and higher enteral caloric density in the first postnatal week , lower mother’s own milk intake in the first postnatal week  and month , and lower donor milk intake in the first week  and month . After accounting for confounders, the average change in weight z-score from birth to discharge was −1.0 vs. −1.2 if receiving mother’s own milk by postnatal day 28 vs. not, respectively. This translated into ATE = 0.2 , meaning that receiving mothers’ own milk may translate into higher growth change. Additionally, in this model, for every one week of increase in gestational age at birth, the change in z-score favorably changed by an average of 0.16 (p < 0.001).The nutritional practices of earlier enteral nutrition, less mother’s own and donor milk feeding, and higher enteral caloric density were all significantly associated with higher growth when expressed as the change in weight p < 0.0001). Therefore, we need both, the cross-sectional and the longitudinal effects of gestational age, when modeling growth as expressed by infant’s weight. z-score calculations, can be separated into a higher rate of change in weight as the gestational age at birth increases and into a slower rate of change based on the longitudinal or time since birth effect of time. Therefore, when we use the change in z-score to track growth, we effectively expect weight to go up at a higher rate than is explained by the longitudinal decomposition of change in weight, especially in the first two postnatal weeks, and, hence, the resulting change in z-scores is more negative than it should be. Of note, the only other significant predictor of weight change across gestational age in the LME models was the caloric density by postnatal day 28 (p < 0.0001).Our analysis of weight change across gestational age revealed that gestational age at birth played an important role in the subsequent weight change during postnatal stay in the hospital . In addition, there was not adequate sample size to stratify the data by gestational age at birth. An infant born at 22 weeks’ gestational age is vastly different from an infant born at 32 weeks’ gestational age, including enteral nutrition exposures and, likely, as shown in our study, in growth trajectory potential. For comorbidities, reliance on ICD codes may have missed non-coded diagnoses, and data was not collected on other common comorbidities such as chronic lung disease or metabolic bone disease. In addition, all of the data was from a single center.Some limitations with this study include the innate limitations with retrospective data collection, the biases as described above, lack of detailed information on feeding practices of different gestational ages at the time the data was collected, and the absence of nutritional laboratory data. Although we saw improved change in weight z-scores at birth and demonstrated better growth trajectories, defined by change in weight z-score. These patterns observed in a preterm infant cohort should be taken into consideration when evaluating the association between preterm infant growth and infant outcomes. Due to selection bias as seen in our study population, it is difficult to interpret these results. In addition, the cohort effect due to varying gestational age at birth, as seen in this method of tracking growth, also must be taken into consideration when investigating studies of relating growth and outcomes.The results of this study demonstrate a significant role of early factors in hospital growth trajectory. When evaluating these preterm infants, infants with higher gestational age had lower z-scores over time are useful guides for physical growth progression and monitoring nutritional practices in this population, especially early after birth, the inherent bias and cohort effect may have a significant impact on the growth outcomes. Therefore, the best way to track this growth and to investigate optimal nutritional interventions remain critical research questions.While patterns of weight


Some studies hypothesize that birth month—as a proxy of exposure to ultraviolet radiation in early infancy—is associated with increased risk of skin tumors.We studied a national cohort of all 5 874 607 individuals born in Sweden to parents of Swedish or Nordic origin as a proxy for Caucasian origin, 1950 to 2014. The cohort was followed for incident skin tumors, including squamous cell carcinomas and melanomas but not basal cell carcinomas, through 2015 from birth up to age 65 for the oldest cohort. Cox regression estimated the association between month of birth and risk of skin tumors in models adjusted for sex, calendar period, and education. Crude observed to expected ratios were also calculated.There were 33 914 cases of skin tumors, of these, 3025 were squamous cell cancer, 16 968 malignant melanoma and 8493 melanoma in situ/other and 5 428 squamous cell in situ/other in 192 840 593 person‐years of follow‐up. Observed to expected ratios by month of birth showed no association between month of birth and risk of skin tumors, and the same result was seen when Cox regression analysis was used. Subgroup analyses by sex, educational level, calendar period, or age at follow‐up similarly showed no association.This large register‐based cohort study showed no evidence of a higher risk of skin tumors in those born during the spring. Thus, this study lends no support to the hypothesis that birth during spring is a major risk factor for later skin tumors. A study of six million persons born in Sweden from 1950 to 2014 lends no support to the hypothesis that birth during spring is a major risk factor for later skin tumors.  Restricting the cohort to those born in Sweden to Swedish born parents or those born in neighboring Nordic countries helped ensure that individuals were most likely of Caucasian origin (N = 5 874 607). Information on date of birth, date of death and date of emigration was obtained from the Total Population Register.2.2Date of birth for all 5.9 million individuals was categorized into birth month with March as the reference. Also, summer  was reference to spring , autumn , and winter  in the analyses of season of birth.2.3Registration of all new primary malignancies is statutory in Sweden and the completeness of the Cancer Register is estimated to be high.2.4The year of birth was categorized in 5‐year calendar periods, 1950‐1954, 1955‐1959, 1960‐1964, 1965‐1969, 1970‐1974, 1975‐1979, 1980‐1984, 1985‐1989, 1990‐1994, 1995‐1999, 2000‐2004, 2005‐2009, 2010‐2014. Information on educational level at age 30 was ascertained from the Longitudinal Integration Database for Health Insurance and Labour Market Studies, held by Statistics Sweden. Highest attained educational level was categorized as: primary (ie less than 10 years of education), secondary (ie 10‐12 years of education), and tertiary .2.5We calculated age‐adjusted incidence rates by birth month for men and women separately, stratified by calendar period and by age at follow‐up. The distribution of birth month among skin tumor cases was compared to percentages of births per month and by percentages of person‐time at risk in the general population by birth months as ratios of observed to expected cases. Also, we estimated hazard ratios (HR) of skin tumor between strata of birth month by multivariable Cox regression, using age as timescale with 95% confidence intervals (95% CIs). Analyses were adjusted for sex and calendar year and additionally for education level where applicable. In sensitivity analyses we restricted the outcome to malignant melanoma cases only. Also, in a secondary analysis we used the same time period, reference  and inclusion criteria as Crump et al3The study population consisted of 5 874 607 individuals, including 3 018 521 men (51.4%) and 2 856 086 women (48.6%) yielding 99 032 088 and 93 0808 505 person‐years of follow‐up, respectively. Characteristics of the 33 914 skin tumor cases are shown in Table A crude comparison of observed to expected ratios of skin tumor cases by birth month showed the highest estimates in April for men and March for women, and the lowest in September for men and November for women. Table .Incidence of skin tumor by sex stratified by calendar birth period, presented by the first five years within each 10‐year calendar birth period, or age at follow‐up showed no difference between months of birth Figures . SubgrouP = .682) (not shown). Mimicking the previous analyses on Swedish data by Crump et al,There was no association between month or season of birth and risk of skin tumor in the regression analyses. Table . Also, r4This large national register‐based study of 5.9 million individuals of Caucasian origin born from 1950 to 2014 showed no association between birth month and later risk of skin tumors. Our negative findings support a similarly large study from Germany showing no association.The main strengths of this study include the total population‐based cohort design, the large sample size, the complete nationwide coverage of the study exposures (birth month), outcome (skin tumor) and covariates and complete follow‐up using valid national Swedish registers with negligible missing data. Also, restricting the study population to those born in Sweden to Nordic born parents ensured that the vast majority of the study population was of Caucasian origin known to have a higher risk of skin tumors.There is an on‐going debate on the most appropriate methodology to test the hypothesis that birth month is associated with increased risk of skin tumors in adulthood.Previous studies that reported an association were considerably smaller: 210, 1745 and 1595, melanoma cases, respectively.The negative findings in a large German study analyzed 28 374 melanoma cases of all ages.The hypothesis tested is the assumption that infants born in spring are more exposed to strong ultraviolet radiation in a susceptible period of life. In Sweden there are guidelines explicitly recommending avoidance of direct sun light for children below one year of age.In conclusion, we found no association between birth month and later development of skin tumor in a large national cohort study of nearly six million individuals with complete information on exposure, outcome and person‐time at risk.None declared.RL is Professor of epidemiology at the Swedish Medical Products Agency, SE‐751 03 Uppsala, Sweden. The views expressed in this paper do not necessarily represent the views of the Government agency.All authors contributed to design, interpretation of data, and read, revised and approved the final version. MT analyzed data. RL drafted the manuscript.The study was approved by the Regional Ethical Review Board in Stockholm, Sweden .


Preterm infants are at risk of neurodevelopmental delay, but data on long-term outcomes in low-income and middle-income countries remain scarce.To examine neurodevelopment using Bayley Scales of Infant and Toddler Development-3rd edition (Bayley-III) and neurological findings in 2-year-old preterm infants, and to compare with healthy Vietnamese infants. Further, to assess factors associated with neurodevelopmental impairment.Cohort study to follow up preterm infants discharged from a neonatal intensive care unit (NICU) of a tertiary children’s hospital in Vietnam.Infants born at <37 weeks of gestational age.Bayley-III assessment and neurological examination at 2-year corrected age (CA) compared with healthy Vietnamese infants.Of 294 NICU preterm infants, Bayley-III scores of all 184/243 (76%) survivors at 2 years CA were significantly lower than those of healthy Vietnamese peers in all three domains: cognition (mean (SD): 84.5 (8.6) vs 91.4 (7.5), p<0.001), language (mean (SD): 88.7 (12.5) vs 95.9 (11.9), p<0.001) and motor (mean (SD): 93.1 (9.0) vs 96.8 (9.3), p=0.003). The mean differences in Bayley-III scores between preterm and healthy Vietnamese infants were −6.9 (−9.1 to −4.7), −7.2 (−10.5 to −3.8) and −3.7 (−6.1 to −1.2) for cognitive, language and motor scores, respectively. The prevalence of neurodevelopmental impairment was 17% for cognitive, 8% for language and 4% for motor performance. In total, 7% were diagnosed with cerebral palsy. Higher maternal education was positively associated with infant neurodevelopment .Vietnamese preterm infants in need of neonatal intensive care showed poor neurodevelopment at 2 years. Higher maternal education was positively associated with infant neurodevelopment. Standard follow-up programmes for preterm infants should be considered in low-resource settings. Preterm infants are at high risk of neurodevelopmental impairment.Data on long-term outcomes for preterm infants are scarce in low-income and middle-income countries.Both biological and environmental factors influence child development.Vietnamese preterm infants in need of neonatal intensive care have lower neurodevelopmental scores compared with healthy Vietnamese peers.Higher maternal education is positively associated with infant neurodevelopment in limited-resource settings.To identify preterm infants with neurodevelopmental impairment, follow-up programmes should be considered in Vietnam and other low-income and middle-income countries.Premature birth, defined as birth before 37 completed weeks of gestation, accounts for approximately 10% of live births worldwideChallenges in the care of preterm infants are reflected in high mortality and also in noticeable morbidity.One of the main difficulties in establishing a well-organised follow-up programme has been the absence of neurodevelopmental assessment tools validated in a similar context. The Bayley Scales of Infant and Toddler Development-3rd edition (Bayley-III) is one of the most frequently used tools to evaluate neurodevelopmental delay, with the tests covering cognitive, language and motor skills considered highly informative in terms of delineating outcomes for preterm infants.Information on long-term outcomes is crucial for both policy making and future planning for healthcare, social and educational services and for counselling caregivers about expected outcomes following preterm birth.Our study was conducted at the NICU at Children’s Hospital 1 (CH1) in Ho Chi Minh City, one of the two major tertiary centres responsible for critical care of newborns in southern Vietnam. The NICU has 30 beds and 1200 admissions annually, of which the vast majority are transferred from healthcare facilities providing obstetric care and the others are admitted from home via the emergency room. The study was approved by the Institutional Review Board of CH1 and written parental consent was obtained for each study participant.All preterm newborns admitted to the unit from July 2013 to September 2014 were eligible for enrolment if they fulfilled the following criteria: <37 completed weeks gestation at birth, age at admission <29 days, no congenital brain malformations or chromosomal anomalies. Newborns admitted to NICU for <72 hours for stabilisation only, or for treatment of retinopathy of prematurity (ROP), were excluded.http://public.vtoxford.org). Hearing and visual function were assessed by caregivers’ report and neurological examination, and hearing screening using otoacoustic emission testing was carried out before discharge or at the first visit before 6 months. If there was any suspicion of impairment, the infant was referred to an otolaryngologist for auditory brainstem responses, or an ophthalmologist for formal assessment of vision, as appropriate.After discharge, participating infants were followed up until 24-month CA.At the 24-month CA visit, neurodevelopment was assessed using a locally adapted Bayley-III assessment tool, previously shown to have acceptable reliability and validity in a Vietnamese population. All tests were conducted by a group of six certified Bayley assessors who were blind to the details of the infants’ birth and hospital course. Tests were performed at CH1 in a quiet, air-conditioned room, and the results were recorded on standard assessment forms, licensed by Pearson publisher.We classified overall outcome using a composite of the Bayley-III scores, the neurological examination and the sensory function assessment. Infants with missing information for one or more of these assessments that could have altered their final category were considered unclassifiable. The category ‘significant neurodevelopmental impairment (significant NDI)’ included infants with a Bayley-III score on any composite score <−2SD, a GMFCS level 3–5, moderate/severe neurological abnormality, or blindness or deafness. The category ‘any neurodevelopmental impairment (any NDI)’ included infants with a Bayley-III score on any composite score <−1SD, a GMFCS level ≥1 or any neurological abnormality.Summary statistics are presented as mean (SD) or median (IQR) for continuous variables, and in absolute counts and percentages for categorical variables. Bayley-III scores between preterm Vietnamese infants and healthy Vietnamese infants were compared using Student’s t-test and presented with mean difference (95% CI). Effect sizes were also presented using Cohen’s d method defined by the difference between two means divided by the pooled SD of those means.For each Bayley-III domain, the Z-score was calculated by comparing the infant’s score with the mean and SD of the score for the same domain derived from healthy Vietnamese infants. The reference population comprised a group of 78 full-term healthy Vietnamese infants assessed at 24 months. These infants had been recruited for the validation of the Bayley-III adaptation and as the control group for another study on hand-foot-and-mouth disease  enrolled during the study period, 243 survived to 2 years CA, and of these 184 (76%) were evaluated at this time . Among tBoys accounted for 117/184 (64%) of all the infants followed up, but the mean (SD) of BW and GA were similar between boys and girls  g vs girls, 1695 (546) g, GA: boys, 31.7 (2.4) weeks vs girls, 31.6 (2.7) weeks).In total, major birth defects were diagnosed in 25/184 (14%) infants; these defects were more frequent in MLP infants. In contrast, the EVP infants spent more days in the hospital and had a higher risk of acquiring chronic lung disease compared with MLP infants. Sepsis was diagnosed clinically in 67/86 (78%) infants in the EVP group compared with 56/98 (57%) in the MLP group. Among them, confirmed sepsis (at least one positive culture from blood or another sterile site) was only identified in 22/123 (18%) infants. As expected, ROP laser treatment was administered mostly in EVP infants, EVP versus MLP: 12/82 (15%) versus 1/49 (2%).A total of 177 infants had at least one cerebral ultrasound performed either during the NICU stay  or after discharge . Among them, 140 (79%) infants had normal scans, while mild intraventricular haemorrhage (IVH) (grades 1 or 2) was identified in 26 (15%), severe IVH (grades 3 or 4) in 3 (2%) and periventricular leukomalacia (PVL) in 2 (1%) infants.The mean (SD) for age at Bayley-III assessment was 23.9 (0.6) months CA, with a range from 22 months 29 days to 25 months 15 days CA (183/184), except for one infant assessed at 20 months 24 days. The mean (SD) of all scale and composite Bayley-III scores for the preterm infants were significantly lower than those of the healthy Vietnamese infants, except for the gross motor score which was comparable (9.0 (1.9) vs 9.2 (2.1), p=0.37). The mean (SD) of the composite cognitive Z-score was −0.91 (1.13), whereas the mean (SD) of the composite language and composite motor Z-scores were −0.60 (1.05) and −0.39 (0.96). The mean differences in Bayley-III scores between preterm and healthy Vietnamese infants were −6.9 (−9.1 to −4.7), −7.2 (−10.5 to −3.8) and −3.7 (−6.1 to −1.2) for cognitive, language and motor scores, respectively. The prevalence of moderate/severe NDI was 32/184 (17%) for cognitive, 14/179 (8%) for language and 8/180 (4%) for motor performance. The percentages of infants classified as having mild  or moderate/severe  impairment in each score are presented in table A in the Appendix.Neurological examination was abnormal in 15/181 (8%) infants, with CP diagnosed in 13/181 (7%) infants, including two (1%) unable to walk (GMFCS level 3) due to spastic diplegia and other 11 (6%) able to walk but with some restriction (GMFCS level 1 or 2). The other two infants had mild neurological findings, while three infants were uncooperative with the examination. Blindness and deafness were not detected in any infant in our cohort. A total of 101/184 (55%) infants met our definition for ‘any NDI’ at the 2-year follow-up, among whom 43/183 (23%) infants were classified as ‘significant NDI’. One infant who attended could not be classified for the significant NDI outcome.Our study reports neurodevelopmental outcomes for Vietnamese preterm infants at 2-year CA and contributes to the evidence of adverse outcomes for preterm infants in LMICs.The low cognitive and language scores of our preterm infants are consistent with previous reports,Although the motor composite score was significantly lower than the norm, the gross motor scores were comparable. Our results are consistent with a meta-analysis indicating that preterm infants are typically in the normal range, but at the lower end of motor performance compared with full-term counterparts.Our findings suggest that a formal follow-up programme similar to those used in high-income countries should be considered for preterm infants in LMICs, especially for those requiring neonatal intensive care. The study indicates that the anticipated poor neurodevelopment in these infants may be alleviated by involvement and education of their caregivers. Therefore, caregivers need to understand the risk of impairment and their role in maximising their child’s cognitive and language potential. A recent meta-analysis concluded that the impact of perinatal risk factors on the cognitive development of preterm infants is likely to lessen over time, whereas the effects of environmental factors become more prominent.The prospective design is one of the strengths of our study and the cohort represents one of the largest and longest followed-up groups of preterm infants in Southeast Asia. Further, the Bayley-III assessments were conducted by independent examiners unaware of the children’s history, and the tool that we used had been previously adapted and validated for Vietnamese infants. On the other hand, we acknowledge several limitations including the bias inherent in a single-centre study involving the most severe out-born newborns and only representing a certain region of Vietnam. These issues may limit the generalisation of our findings to the broader population of children born prematurely across the country. Furthermore, nearly 25% of the infants were lost to follow-up, potentially resulting in bias. Finally, the low predictive ability of Bayley assessment in early childhoodIn conclusion, preterm Vietnamese infants in need of intensive neonatal care showed poor performance in all domains of neurodevelopment assessed at 2 years CA. Higher maternal education was positively associated with neurodevelopmental performance of these preterm infants. Our study suggests consideration of long-term neonatal follow-up programmes in LMICs that could assist in ensuring this vulnerable group of children fulfil their potential.


Preterm birth, small size for gestational age (SGA) and large size for gestational age (LGA) at birth are major risk factors for neonatal and long-term morbidity and mortality. It is unclear which periods of pregnancy are optimal for ultrasound screening to identify fetuses at risk of preterm birth, SGA or LGA at birth. We aimed to examine whether single or combined second and third trimester ultrasound in addition to maternal characteristics at the start of pregnancy are optimal to detect fetuses at risk for preterm birth, SGA and LGA.In a prospective population-based cohort among 7677 pregnant women, we measured second and third trimester estimated fetal weight (EFW), and uterine artery pulsatility and umbilical artery resistance indices as placenta flow measures. Screen positive was considered as EFW or placenta flow measure < 10th or > 90th percentile. Information about maternal age, body mass index, ethnicity, parity, smoking, fetal sex and birth outcomes was available from questionnaires and medical records. Screening performance was assessed via receiver operating characteristic (ROC) curves and area under the curve (AUC) along with sensitivity at different false-positive rates.Maternal characteristics only and in combination with second trimester EFW had a moderate performance for screening for each adverse birth outcome. Screening performance improved by adding third trimester EFW to the maternal characteristics (AUCs for preterm birth 0.64 (95%CI 0.61 to 0.67); SGA 0.79 (95%CI 0.78 to 0.81); LGA 0.76 ). Adding third trimester placenta measures to this model improved only screening for risk of preterm birth (AUC 0.72 (95%CI 0.66 to 0.77) with sensitivity 37% at specificity 90%) and SGA (AUC 0.83 (95%CI 0.81 to 0.86) with sensitivity 55% at specificity 90%). Combining second and third trimester fetal and placental ultrasound did not lead to a better performance as compared to using only third trimester results.Combining single third trimester fetal and placental ultrasound results with maternal characteristics has the best screening performance for risks of preterm birth, SGA and LGA. As compared to second trimester screening, third trimester screening may double the detection of fetuses at risk of common adverse birth outcomes.The online version of this article (10.1186/s12916-020-01540-x) contains supplementary material, which is available to authorized users. Preterm birth, small size for gestational age (SGA) and large size for gestational age (LGA) at birth explain up to 30% of neonatal death and are strong risk factors for short-term and long-term morbidity , 2. The We used data from a population-based observational study among 7670 pregnant women to examine whether single or combined second or third trimester fetal and placental ultrasound examinations, in addition to maternal characteristics, are optimal to detect fetuses at risk for preterm birth, SGA and LGA.n = 1130), non-singleton live-births (n = 33), and women with outcome data missing (n = 46). This led to a population for analysis of 7670 pregnant women  was calculated and categorized for clinical purposes: normal weight (BMI < 25 kg/m2), overweight (BMI 25.0–30.0 kg/m2) and obese (BMI ≥ 30.0 kg/m2) [We selected maternal characteristics known at the start of pregnancy, which are important determinants of adverse birth outcomes , 18–20. 0 kg/m2) . InformaBMI 25.0–0.0 kg/m2Ultrasound examinations were carried out in two dedicated research centres in first  12.2 to 14.7), second  and third trimester  . GA-adjuUterine artery resistance indices (UtA-RI) and umbilical artery pulsatility indices (UA-PI) are measures of vascular resistance in the uterine and umbilical arteries, respectively. Increased UtA-RI and UA-PI are associated with impaired placental vascular development and increased risks of abnormal intrauterine growth and adverse perinatal outcomes , 25–29. Information about offspring sex, GA and weight at birth, gestational hypertensive disorders, assisted vaginal delivery and cesarean delivery was obtained from medical records . GA-adjuFirst, we calculated the absolute percentages of screen positive second and third trimester fetal ultrasounds among newborns born preterm, SGA and LGA. Second, we aimed to assess screening performance for preterm birth, SGA and LGA based on different predefined screening models. We constructed five predefined logistic regression models for screening of preterm birth, SGA and LGA, respectively. Preterm birth, SGA and LGA were the dependent variables in these different predefined logistic regression models. For each logistic regression model, we assessed the variance explained of the model. We obtained predicted values from these regression models and further assessed model performance via receiver operating characteristic (ROC) curves and calculation of the area under the curve (AUC), along with the sensitivity at different false-positive rates (1-specificity). The five predefined logistic regression models for screening of preterm birth, SGA and LGA were as follows: (1) maternal characteristics model including maternal age, BMI, ethnicity, parity and smoking and fetal sex; (2) second trimester model (model 1 plus screening result based on second trimester EFW); (3) third trimester model (model 1 plus screening result based on third trimester EFW); (4) combined second and third trimester model (model 1 plus screening result based on second and third trimester EFW); (5) second-to-third trimester fetal growth model (model 4 plus second-to-third trimester EFW change). To compare model performance of the different predefined models, we assessed the change in effect size of the obtained AUCs from the different models. If the change in effect size was considered clinically relevant, we used the method by DeLong et al. for assessing whether the AUCs for two or more correlated receiver operating characteristic curves were statistically significantly different . PositivTable p value for AUC comparison to the maternal characteristics model < 0.01, Additional file p value for model comparison to the third trimester EFW model < 0.01, Additional file Figure We observed similar model performances when we only took spontaneous preterm birth into account  and 0.72 (95% CI 0.70 to 0.74), respectively) (Fig. Model performance was the same when screen-positive was defined separately for SGA and LGA, as when screen-positive was defined as one screening test for both SGA and LGA (Additional file Our results suggest that third trimester ultrasound examination in addition to maternal characteristics has the best screening performance for detecting fetuses at risk for preterm birth, SGA and LGA, compared to second trimester ultrasound or combined second and third trimester ultrasound. Compared to second trimester ultrasound screening, third trimester ultrasound screening would nearly double detection of fetuses at risk of these adverse birth outcomes in a low-risk population.Preterm birth, SGA and LGA are strongly related to perinatal morbidity and mortality and have long-term consequences for disease risk , 4, 33. . The additional value of placenta measures to the screening model may be explained by the role of placental dysfunction in preterm birth [Despite reported associations of suboptimal fetal growth and impaired placental function with preterm birth, no previous studies assessed the screening performance of second and third trimester ultrasound for preterm birth risk , 34. We rm birth . We obserm birth . Anotherrm birth . A recenrm birth . This strm birth . In our rm birth , 38. AltIt is well-established that newborns born SGA or LGA may be both constitutionally or pathologically small or large for their gestational age . It has Overall, we observed slightly lower sensitivities for screening for SGA and LGA than previous studies, which could be explained by taking into account maternal characteristics, our relatively healthy low-risk population and the earlier timing of third trimester ultrasound , 38. As Our findings suggest that implementation of third trimester fetal and placental ultrasound, combined with common maternal characteristics, would nearly double detection of fetuses at risk for common adverse birth outcomes compared to second trimester ultrasound and provides further evidence for critical evaluation of current obstetric care guidelines. Improved detection of fetuses at risk of preterm birth, SGA and LGA provides the clinician the opportunity to optimize monitoring and interventions . MonitorWe had a prospective data collection from early pregnancy onwards and a large sample of 7670 women with fetal growth measurements available. The non-response at baseline might have led to selection of a more healthy population, which might affect the generalizability of results to high-risk populations. We also had a relatively small number of cases of adverse birth outcomes, which might further indicate a selection towards a low-risk population. To assess whether a screening model improved by adding additional maternal, fetal or placental characteristics, we assessed if changes in AUC effect estimates of different screening models were clinically relevant and whether the differences in AUCs of two different models were statistically significant. What is considered clinically relevant may be arbitrary. Based on previous studies focused on screening for similar adverse birth outcomes, we considered an approximate 4–5% change in effect estimate of the AUC as clinically relevant, as this change is likely associated with a detectable increase in sensitivity , 28, 44.Maternal characteristics together with single third trimester fetal and placental ultrasound has the best screening performance for preterm birth, and SGA and LGA at birth, compared to using only second trimester ultrasound or combined second and third trimester ultrasound. Compared to second trimester ultrasound screening, third trimester ultrasound screening would nearly double detection of fetuses at risk of these common adverse birth outcomes in low-risk populations.Additional file 1Index supplemental material.Additional file 2STROBE checklist.


To build a novel and simple model to predict iatrogenic preterm birth in pregnant women with scarred uteri.In this retrospective, observational, single-centre cohort study, data from 2315 patients with scarred uteri were collected. Multiple logistic regression analysis and mathematical modelling were used to develop a risk evaluation tool for iatrogenic preterm birth. After modelling, the calibration and discrimination of the model along with decision curve analysis were checked and performed to ensure clinical applicability.P = 0.003; 13 to < 24 months (reference), 25 to < 60 months, OR 1.80 (95% CI 0.96–3.40), P = 0.068; ≥ 60 months, OR 1.60 (95% Cl 0.86–2.97), P = 0.14), height , P = 0.003), parity (parity ≤1 (reference), parity = 2, OR 2.92 (95% CI 1.71–4.96), P < 0.0001; parity ≥3, OR 8.26, (95% CI 2.29–29.76), P = 0.001), number of vaginal bleeding , P < 0.0001), hypertension in pregnancy (OR 9.52 (95% CI 6.46–14.03), P < 0.0001), and placenta previa , P < 0.0001). Finally, a nomogram was developed.Among the 2315 patients, 417 (18.0%) had iatrogenic preterm births. The following variables were included in the model: interpregnancy interval , In this study, we built a model to predict iatrogenic preterm birth for pregnant women with scarred uteri. The nomogram we created can assist doctors in evaluating the risk of iatrogenic preterm birth and help in making referrals; thus, better medical care can be given to improve the prognosis of patients and foetuses. Preterm birth (PTB) remains a major unsolved problem in modern obstetrics and is significantly associated with infant mortality, long-term morbidity and neurodevelopmental impairment. The prevalence of preterm birth is 5–18% of all live births worldwide , socio-eChina has one of the highest caesarean section rates in the world. With new family planning policies emerging, an increasing number of women have decided to have a second child, which makes pregnancy with a scarred uterus an increasingly prominent problem. Pregnancy with a scarred uterus has been considered risky and closely related to adverse pregnancy outcomes . Those wThis study included data from a large retrospective cohort study in Northeast China from 2014 to 2017 at Shengjing Hospital, a regional tertiary medical centre. The study was approved by the local ethics committee  in Shenyang. The original cohort study recruited 8697 patients with scarred uterus from all 69,931 deliveries made during the study period to evaluate the impact of scarred uterus on the subsequent pregnancies. The inclusion criteria for this study were all women with a scarred uterus from caesarean section or myomectomy AND singleton pregnancies at gestational week 20 or beyond. (including cases of stillbirth). The patients were excluded if they had severe systematic disease, had a twin or greater pregnancy, were unable to speak Chinese, or had no access to a telephone. Finally, 2315 patients remained after exclusion.Preterm deliveries are those that occur at less than 37 weeks of gestational age. Our study recruited pregnant women who went into labour between the 20th and 42nd weeks of gestation. Diagnostic records and actual labour weeks were checked to determine whether the patient had iatrogenic preterm birth. Patients with spontaneous preterm birth were also included in this study and treated as controls. A patient could start labour before 37 weeks of gestation and finish with CS due to maternal or foetal medical concerns; cases such as this were still considered spontaneous preterm births. Delivery of the baby according to indications and decided by obstetricians was considered an iatrogenic preterm birth. Methods of termination included CS and TOLAC.The other variables included in our study were as follows: maternal age, height, weight before delivery, parity, interpregnancy interval (IPI), number of vaginal bleeding during the pregnancy, foetal position, myomectomy, dysmenorrhea, regularity of prenatal examination, conception method, placenta previa, hypertension during pregnancy, and gestational diabetes mellitus. These data were all collected from a computerized medical record system including all data concerning basic individual information, medical and obstetric histories, and pregnancy outcomes. Both maternal age and height were collected at the first prenatal visit. Regarding weight, the data collected in our study are the weights before delivery because of the loss of data on weight at the first prenatal visit. Hypertension during pregnancy was defined according to the American College of Obstetrics and Gynecology (ACOG) criteria . Placentn = 1566) and validation set (n = 749). Distributions of continuous variables were assessed for normality using the Kolmogorov-Smirnov test; none of the continuous variables were normally distributed in this study. Categorical variables are presented as percentages, and continuous variables are presented as the median (25 and 75% quantiles). Bivariate analyses were performed by the Mann-Whitney U test or Fisher’s exact test.A total of 2315 cases were randomly split into a training  and 95% confidence intervals (CIs) were calculated. The level of significance for the P value was set as 0.05.Simple and multiple logistic regression analyses were used to model risk factors for preterm birth. The interaction between variables may lead to differences in the results of univariable and multivariable analysis. To avoid missing important risk factors, variables with Other important assessments are outlined here. Discriminative ability was assessed using the AUC c-statistic. The Hosmer-Lemeshow test was used to determine the adequacy of calibration, and a calibration plot was drawn. To evaluate multicollinearity, the variance inflation factor, tolerance, eigenvalue, and condition index were checked. Decision curve analysis was used to determine the clinical practicability. Finally, a nomogram was developed.SPSS version 25.0  was used for statistical modelling. STATA Release 12 Software  was used to perform the Hosmer-Lemeshow test and decision curve analysis. R (R Core Development Team) version 3.1.1 was used to develop calibration tests and the nomogram.n = 2057, 88.9%) and had less than 2 periods of labour . Over half  of the patients had an IPI of more than 60 months, and the fewest proportion of patients hand an IPI of 0 to < 12 months . Hypertension in pregnancy was reported for 9.1% of the patients, while placenta previa was present in 14.1% of all patients. Further details of the population characteristics are shown in Table Of the 2315 enrolled patients, 417 (18.0%) had an iatrogenic preterm birth, and 160 (6.9%) had a spontaneous preterm birth. The median age was 32 (IQR 30–35) years. The median height was 162 (IQR 160–165) cm. The majority of those enrolled had not experienced vaginal bleeding during pregnancy  and abnormal foetal position .Among the 417 patients who had iatrogenic preterm birth, 318 (76.3%) were attributed to maternal reasons, 43 (10.3%) were attributed to foetal reasons, and the remaining 56 (13.4%) were associated with both maternal and foetal reasons. Among the maternal indications, placenta previa and hypertension during pregnancy accounted were the most common reasons for iatrogenic preterm birth. Other common indications included a threat of uterine rupture, GDM, and oligohydramnios. The maternal index of iatrogenic preterm birth (IPTB) is shown in Fig. OR = 9.52, 95% CI 6.46–14.03), followed by a parity of more than 2  and an interpregnancy interval of 0 to < 12 months . Increased height could protect patients from iatrogenic preterm birth. Further details are shown in Table After multivariable analysis, parity, interpregnancy interval, hypertension in pregnancy, placenta previa, height and number of vaginal bleeding during pregnancy were included in the final model. Among these factors, patients with hypertension during pregnancy had the highest risk of iatrogenic preterm birth  in the training set and 0.776 (95% Cl 0.728–0.823) in the whole validation set. The suggested cutoff for this model was 0.15, and the false positive and false negative rates for the given cutoff were 29.1 and 21.6%, respectively. The calibration plots for the two sets are shown in Fig. Finally, to justify the clinical usefulness of the model, we assessed whether nomogram-assisted decisions would improve patient outcomes by performing decision curve analysis. Decision curves can help us calculate the net benefit of the use of our nomogram. The results of the decision curve analysis are shown in Fig. In this study, six parameters were selected discreetly in the estimation of the overall risk of iatrogenic preterm birth: shorter maternal height, extremely low or advanced IPI, greater vaginal number of vaginal bleeding during pregnancy, higher parity, hypertension during pregnancy and placenta previa. By combining these factors, the risk of iatrogenic preterm birth can be well predicted.Many studies have attempted to establish a simple way to predict preterm birth, but most focused on spontaneous preterm birth. In our study, many variables were used to predict iatrogenic preterm birth. Most of the underlying variables have been previously reported to impact preterm birth, while myomectomy and dysmenorrhea were included tentatively to assess their relationship with iatrogenic preterm birth. Maternal and foetal indications are the direct reasons for obstetricians to consider a patient at high risk of iatrogenic preterm birth or to tend to terminate the pregnancy. Severe complications during pregnancy, such as uterine rupture, are likely to lead to iatrogenic preterm birth. Although the prevalence of such complications is usually low, quick treatment is needed for these complications. Meanwhile, common foetal reasons for iatrogenic preterm birth, such as foetal distress, also require quick treatment given their sudden occurrence. Therefore, we mainly focused on chronic pregnancy complications, such as placenta previa and GDM, when we included complications into the model.A shorter height has been associated with a progressive increase in the odds of having an infant born preterm , 18. OurPlacenta previa is a risk factor for preterm birth . The forn = 35,1.5%) because most of the women with IPIs less than 12 months were recommended for delivery of the baby. The 12 to < 24 months category was chosen as the reference group based on Mckinney’s study, and an IPI of 12 to < 24 months was associated with the lowest risk of preterm birth in both Mckinney’s and our studies.IPI is defined as the time from the most recent prior birth to conception of the index birth by Mckinney and his coworkers . An IPI Self-reported vaginal bleeding during pregnancy is predictive for preterm birth. The odds ratio of vaginal bleeding was 2.7 (95% Cl 2.03–3.70) in our study, with an incidence of 10.9%, smaller than that in other studies , 22. Ourn = 2171, 93.8%) and in the general population. This demographic characteristic is quite different in China due to the singleton policy that had been in place over the past years. Nulliparous and highly multiparous women are at higher risk of adverse pregnancy outcomes than those with low multiparity [Women with a parity of less than two composed the majority of our data . The influence of maternal weight on preterm birth is complicated. We decided to collect all the data on weight and weight gain for all trimesters at first. Due to data loss, only weight before delivery was included in this study. (2). A total of 2315 cases were divided into a training set and a validation set; the nature of internal validation indicates one of the weakness of our study. (3). Due to the retrospective nature of this study, the data we collected, except for age and height, were all acquired before delivery. Therefore, the model is only valid for pregnant women with more than 20 gestational weeks.We built a model to predict iatrogenic preterm birth for pregnant women with scarred uteri. The variables included in the model were height, parity, IPI, vaginal bleeding during pregnancy, placenta previa, and hypertension during pregnancy. The nomogram we developed can assist doctors in evaluating the risk of iatrogenic preterm birth and deciding whether these patients should be referred to an higher tier medical centre; thus, better medical care can be provided to prevent adverse pregnancy outcomes and poor foetal conditions.


The objectives of this analysis were to document trends in and risk factors associated with the cesarean birth rate in low- and middle-income country sites participating in the Global Network for Women’s and Children’s Health Research .This is a secondary analysis of a prospective, population-based study of home and facility births conducted in the Global Network sites.Cesarean birth rates increased uniformly across all sites between 2010 and 2018. Across all sites in multivariable analyses, women younger than age twenty had a reduced risk of cesarean birth  and women over 35 had an increased risk of cesarean birth  compared to women aged 20 to 35. Compared to women with a parity of three or more, less parous women had an increased risk of cesarean . Four or more antenatal visits , multiple pregnancy , abnormal progress in labor , antepartum hemorrhage , and hypertensive disease  were all associated with an increased risk of cesarean birth, p < 0.001. For multiparous women with a history of prior cesarean birth, rates of vaginal birth after cesarean were about 20% in the Latin American and Southeast Asian sites and about 84% at the sub-Saharan African sites. In the African sites, proportions of cesarean birth in the study were highest among women without a prior cesarean and a single, cephalic, term pregnancy. In the non-African sites, groups with the greatest proportion of cesarean births were nulliparous women with a single, cephalic, term pregnancy and all multiparous women with at least one previous uterine scar with a term, cephalic pregnancy.Cesarean birth rates continue to rise within the Global Network. The proportions of cesarean birth are higher among women with no history of cesarean birth in the African sites and among women with primary elective cesarean, primary cesarean after induction, and repeat cesarean in the non-African sites. Globally, cesarean birth rates are on the rise . Many coThis analysis was conducted using data from a prospective study conducted in communities at seven sites in six low- and middle-income countries for births from January 2010 through December 2018 ; Chimaltenango, Guatemala; Nagpur, and Belagavi, India; western Kenya; Thatta District, Pakistan; and sites near Lusaka, Zambia), through the Global Network. The DRC site initiated enrollment in 2014, and data were collected on the Robson criteria in all sites starting in 2017. The Robson criteria classify women by common obstetric variables into ten mutually exclusive groups .The Global Network’s prospective registry, the MNHR, includes pregnancy related data and outcomes from rural or semi-urban geographical areas. Each site includes between 6 and 24 distinct communities . Each coThe analyses presented here used MNHR data to determine trends in cesarean birth across study sites over time, risk factors associated with cesarean birth among registrants, and the prevalence of cesarean birth among the Robson subgroups since 2017. The population studied included women screened for the MNHR who were eligible, consented, and delivered in the study period. Data were excluded from women who were enrolled but lost to follow-up prior to delivery, maternal deaths prior to labor and delivery, miscarriages, medically terminated pregnancies, and those with missing data for delivery mode.The primary outcome of this analysis was cesarean birth as the mode of delivery, including rates over time, and risk factors associated with cesarean birth. The secondary outcomes were rates of vaginal birth after previous cesarean birth and the proportion of cesarean birth in each Robson subgroup.We used descriptive statistics to produce counts and percentages of cesarean births per Global Network site per year using standard contingency table techniques. Then we observed independent variables associated with cesarean birth, and performed comparisons of sociodemographic and antenatal covariates that we hypothesized might be associated with mode of delivery. Relative risks, 95% confidence intervals and p values were obtained from log binomial models as a function of each individual risk factor using generalized estimating equations to account for the correlation of outcomes within cluster. Backward selection was used to identify risk factors to include in the final multivariate model starting with all risk factors that were found to be associated with cesarean birth . We performed a separate model for African  and non-African  sites given the substantial differences in cesarean rates in the African sites compared to the other sites. The final multivariable Poisson models used to evaluate the relationship of associated or potential risk factors with cesarean birth included non-colinear, statistically significant covariates and used generalized estimating equations to account for the correlation of outcomes within cluster. We then observed the vaginal birth after cesarean birth rate among women with a history of prior cesarean birth.To consider subgroups contributing to cesarean birth rates, our secondary outcome, we utilized the WHO-recommended Robson Classification System, which is a method of comparing cesarean birth rates over time within and across institutions to classify women by common obstetric variables into ten mutually exclusive groups , 6. ThesThe appropriate institutional review boards/ethics research committees of the participating institutions approved the MNHR study. Individual informed consent for study participation was requested and obtained from each study participant. A Data Monitoring Committee, appointed by the National Institute of Child Health and Human Development reviewed the study semi-annually .Figure Figure Table Table Figure We applied the Robson Classification System for cesarean birth to determine the percentage of cesareans at each site in each group as shown in Table Cesarean birth rates within the Global Network appear to continue to rise across all sites, although rates are substantially lower in the African sites. For our primary outcome, the strongest predictors of cesarean birth in adjusted analyses in the African sites were multiple pregnancy, a university or higher level of education, antepartum hemorrhage, and hypertension in pregnancy. In the non-African sites, the factors most strongly associated with cesarean birth in adjusted analyses were advanced maternal age, a primary school or higher level of education, parity less than three, greater than four antenatal visits, multiple gestation, abnormal progress in labor, antepartum hemorrhage, and hypertensive disease.For our secondary outcome, in all sites with cesarean birth rates at or above the historically recommended WHO rate of 10–15% , vaginal birth after cesarean rates were around 20%. Conversely, in the African sites where cesarean birth rates are very low, vaginal birth after cesarean rates were around 84%. We also found that primary or first cesarean (among nulliparous and multiparous women) accounted for the largest proportion of cesareans performed in the African sites, while pre-labor primary cesarean or primary cesarean after induction of labor among nulliparous women, and repeat cesarean among multiparous women accounted for a higher proportion of cesareans in the non-African sites. Overall, the proportion of cesarean births accounted for by preterm singletons was about 11%.We used statistical modeling to identify risk factors associated with cesarean birth in the sub-Saharan African sites that might be of interest in considering interventions to modify cesarean birth rates, either to increase or decrease the rate given the site. For hypertensive disease in pregnancy, mode of delivery should be determined by routine obstetric considerations—hypertensive disease in itself is not an indication for cesarean birth –12. HoweIn the model involving the non-African sites, additional risk factors that might be modified include age, adherence to antenatal care, and management of abnormal progress in labor. Advanced maternal age is a known risk factor for cesarean birth, although this may be a proxy measure of other unknown confounders . Many inPerformance of cesarean birth is always a complicated decision given the many factors contributing to any one woman’s labor and delivery, but mode of delivery after a history of cesarean birth is even more complex , 22. TheOur final analysis was to use the WHO-recommended Robson Cesarean Birth Classification System to subset our cohort into ten mutually exclusive groups to see which women accounted for the greatest proportion of cesarean births in our Global Network sites. Other large studies have used the Robson classification, previously . A WHO aAlthough this analysis represents a large dataset and a globally representative sample, it is limited by the short timeframe during which the Robson classification variables were collected, the multiple comparisons made, the lack of information available on maternal preference for elective cesarean birth, and the lack of context in which to interpret these trends and findings. For example, determinants of rising rates are likely very different in Latin America as compared to southeast Asia, but we have only basic sociodemographic, antepartum, intrapartum, and postpartum data with which to analyze our outcomes. Similarly, with respect to cesarean birth, optimizing cesarean birth utilization in the African sites based on prior research requires greater use of cesarean birth, while appropriate use of cesarean birth in our non-African sites may necessitate reduced use of the procedure. We also note that our a priori stratification of sites may have resulted in missing potential associations and conclusions, and variability of site data included in these grouping may not be fully explored. Having limited contextual data on the determinants of these trends constrains our ability to draw specific conclusions or make evidence-based recommendations from this analysis.However, this analysis provides excellent preliminary data for further research. It highlights the gaps in knowledge about determinants of cesarean birth rates in varied low- and middle-income country settings and identifies areas for future research. These include the fields of prevention of the primary cesarean, appropriate use of vaginal birth after cesarean, and identifying subpopulations ideal for induction of labor and pre-labor cesarean specific to the low- and middle-income country context that account for variability in cesarean access and utilization across regions. It also offers some direction on additional risk factors that can be targets for interventions or for guideline development in low-resource settings that include mode of delivery in the setting of multiple gestation, hypertensive disease, and antepartum hemorrhage.In conclusion, cesarean birth rates appear to be increasing within the Global Network sites. Advanced maternal age, education, parity less than three, greater than four antenatal visits, multiple gestation, antepartum hemorrhage, and hypertensive disease in pregnancy are associated with cesarean birth in our study population. Proportions of cesarean birth are higher among women with no history of cesarean birth in the African sites and among women with primary elective cesarean, primary cesarean after induction, and repeat cesarean in the non-African sites.


Are paternal and maternal preconception urinary metabolite concentrations of phthalates and phthalate substitutes associated with singleton preterm birth?In this preconception cohort study of 420 singleton infants, maternal preconception urinary concentrations of di-(2-ethylhexyl) phthalate and di(isononyl)cyclohexane-1,2-dicarboxylate  were associated with an increased risk of preterm birth. Fathers’ preconception concentrations of these biomarkers were not associated with preterm birth in offspring.Female exposure to select plasticizers during the preconception period may be a potential risk factor for adverse pregnancy outcomes. Although phthalate exposure during pregnancy has been associated with preterm birth, the association of preconception exposure in either parent with preterm birth constitutes a knowledge gap.To examine the association of paternal and maternal preconception urinary concentrations of biomarkers of phthalates and phthalate substitutes with singleton preterm birth.This study, conducted at an academic fertility center in Boston, Massachusetts, included a prospective preconception cohort of subfertile couples comprising 419 mothers and 229 fathers and their 420 live-born singleton offspring born between January 1, 2005, and December 31, 2018. Statistical analysis was performed from August 1 to October 31, 2019.Urinary concentrations of metabolites of phthalates and phthalate substitutes obtained before conception.Gestational age was abstracted from delivery records and validated using the American College of Obstetricians and Gynecologists guidelines for births after medically assisted reproduction. The risk ratio (RR) of preterm birth (live birth before 37 completed weeks’ gestation) was estimated in association with urinary concentrations of 11 individual phthalate metabolites, the molar sum of 4 di-(2-ethylhexyl) phthalate (ΣDEHP) metabolites, and 2 metabolites of 1,2-cyclohexane dicarboxylic acid diisononyl ester  using modified Poisson regression models adjusted for covariates.P = .01) and cyclohexane-1,2-dicarboxylic acid monohydroxy isononyl ester  concentrations  were associated with an increased risk of preterm birth. After additional adjustment for prenatal ΣDEHP or MHiNCH concentrations, the association of maternal preconception exposure to ΣDEHP and preterm birth remained robust , while the association of maternal preconception exposure to MHiNCH and preterm birth was attenuated . The remaining urinary metabolites examined in either parent showed no association with preterm birth.The mean (SD) age of the 419 mothers was 34.7 (4.0) years, the mean (SD) age of the 229 fathers was 36.0 (4.5) years, and the mean (SD) gestational age of the 420 singleton children (217 boys) was 39.3 (1.7) weeks, with 34 (8%) born preterm. In adjusted models, maternal preconception ΣDEHP concentrations (RR, 1.50; 95% CI, 1.09-2.06; In this prospective cohort of subfertile couples, maternal preconception exposure to ΣDEHP metabolites was associated with an increased risk of preterm birth. The results suggest that female exposure to select phthalate plasticizers during the preconception period may be a potential risk factor for adverse pregnancy outcomes, which may need to be considered in preconception care strategies. This cohort study examines the association of paternal and maternal preconception urinary concentrations of biomarkers of phthalates and phthalate substitutes with singleton preterm birth. Substitution of phthalates with DINCH warrants further screening in human populations29 because its metabolites are biologically active and understudied.30Phthalates are a family of chemicals widely used in many consumer products. Phthalates are known reproductive and developmental toxicants in experimental animals31 Even less is known about the association of paternal preconception exposures with offspring health.32 Environmental-epigenetic mechanisms in the preconception and periconception period are likely associated with the etiopathologic characteristics of preterm birth.35 However, studies addressing the association of parental preconception exposure to phthalates with outcomes in gametes, fertilization, implantation, placentation, and gestation are limited.31 Therefore, we aimed to investigate whether higher paternal and maternal preconception urinary concentrations of metabolites of phthalates and phthalate substitutes were associated with an increased risk of preterm birth among couples undergoing fertility care.The maternal preconception period remains an important but largely unexplored critical window of exposure for perinatal and infant outcomes.36 In brief, women aged 18 to 46 years and men aged 18 to 55 years, using their own gametes, were eligible. Participants enrolled independently or as a couple and were followed up from study entry through their fertility care, pregnancy, and labor and delivery. The present analysis included 419 female and 229 male EARTH cohort participants who gave birth to a singleton infant between January 1, 2005, and December 31, 2018, for whom we had at least 1 urine sample quantified for biomarker metabolites during the period before conception of the index pregnancy. One singleton live birth was from a male participant enrolled without a female partner, thus leaving 228 couples (STROBE) reporting guideline.The Environment and Reproductive Health (EARTH) Study is an ongoing prospective preconception cohort of couples seeking fertility evaluation and medically assisted reproductive treatment at the Massachusetts General Hospital Fertility Center. The EARTH Study was designed to investigate environmental and nutritional factors for both women and men across preconception and prenatal periods in association with fertility, pregnancy, and birth outcomes. The cohort has been described elsewhere. couples . TrainedMale and female participants provided 1 spot urine sample at study entry. Women provided up to 2 additional spot urine samples per fertility treatment cycle: one obtained during the follicular phase of the cycle (days 3-9) and the other on the day of the fertility procedure. Men provided an additional spot urine sample per cycle on the day when their female partner underwent the fertility procedure. Women also provided 1 spot urine sample per trimester at a median of 6, 21, and 35 weeks’ gestation. We used the biomarker concentrations from the multiple urine samples obtained per participant from study entry up to and including the samples from the treatment cycle of conception of the index birth to estimate the mean exposure in the preconception window.37 The concentrations of the following phthalate metabolites were measured: monoethyl phthalate, mono-n-butyl phthalate (MBP), mono-isobutyl phthalate (MiBP), monobenzyl phthalate (MBzP), mono(2-ethylhexyl) phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono(3-carboxypropyl) phthalate, monocarboxyisooctyl phthalate, and monocarboxyisononyl phthalate. The urinary concentrations of 2 DINCH metabolites, cyclohexane-1,2-dicarboxylic acid monohydroxy isononyl ester (MHiNCH) and cyclohexane-1,2-dicarboxylic acid monocarboxyisooctyl ester (MCOCH), were also measured in a subset of participants  of each sample was quantified with a handheld refractometer . The urine samples were then divided into aliquots, frozen for long-term storage at −80 °C, and shipped on dry ice overnight to the Centers for Disease Control and Prevention . For each urine sample, the concentrations of metabolites of phthalates and phthalate substitutes were quantified using solid-phase extraction coupled with high-performance liquid chromatography–isotope dilution tandem mass spectrometry.icipants . The lim39 The summary estimate  was calculated by multiplying the SG-adjusted concentration of each of these 7 individual metabolites by their antiandrogenic potency and summing the weighted concentrations: ΣAAPhthalates = MBP + (0.24 × MiBP) + (0.26 × MBzP) + (0.61 × MEHP) + (0.61 × MEHHP) + (0.61 × MEOHP) + (0.61 × MECPP).40We calculated the molar sum of 4 di(2-ethylhexyl) phthalate (DEHP) metabolites by dividing each metabolite concentration by its molecular weight and then summing: ΣDEHP = {[MEHP × (1/278.34)] + [MEHHP × (1/294.34)] + [MEOHP × (1/292.33)] + [MECPP × (1/308.33)]}. We multiplied the molar sum by the molecular weight of MECPP (308.33) to convert ΣDEHP to nanograms per milliliter. We also calculated a summary measure of phthalate metabolites with antiandrogenic properties , as previously described.41 The fertility treatment setting permitted us to estimate gestational age with high accuracy using in vitro fertilization protocol dates, substantially reducing the number of misclassifications of preterm births due to inaccuracies in pregnancy dating.42 For in vitro fertilization pregnancies, the gestational age was estimated as (Outcome Date − Transfer Date + 14 Days + Cycle Day of Transfer).41 For intrauterine insemination and nonmedically assisted or naturally conceived pregnancies, we used the birth date minus the cycle start date or the last menstrual period date. Preterm birth was defined as any live birth less than 37 completed weeks’ gestation (<259 days). We corrected for 3 pregnancies for which the medical delivery record estimates (criterion standard) differed from the American College of Obstetricians and Gynecologists–based estimates by more than 6 days through additional delivery record verification.We abstracted gestational age in days from delivery records and validated it using the American College of Obstetricians and Gynecologists guidelines for dating births after medically assisted reproduction.44 The type of medically assisted reproduction used in the conception cycle of the index birth was abstracted from the electronic medical records by trained study staff and dichotomized as ART procedures  vs non-ART protocols .Data on paternal and maternal age, educational level, race/ethnicity, and smoking status were obtained from self-reported questionnaires administered at enrollment. Research study staff measured the height and weight of the participants at baseline, and body mass index was calculated as weight in kilograms divided by height in meters squared. The treating infertility physician diagnosed the underlying cause of infertility using the Society for Assisted Reproductive Technology (ART) definitions.45 The SG-adjusted biomarker concentrations were natural log-transformed to standardize the distribution and reduce the effect of extreme values. We estimated the geometric mean paternal and maternal preconception biomarker concentrations by averaging each participant’s natural log concentration obtained from study entry (baseline) and at each treatment cycle up to and including the cycle of the index conception of the singleton offspring. We calculated descriptive statistics for biomarker concentrations and the percentage of values below the LOD, as well as Spearman correlation coefficients for each natural log concentration between couples .Statistical analysis was performed from August 1 to October 1, 2019. To account for urinary dilution, each biomarker concentration was multiplied by [(SGp − 1)/(SGi − 1)], where SGi is the SG of the participant’s sample and SGp is the mean SG for all male  or all female  participants included in the study.46 Modified Poisson models were fit by using a log-link function with a Poisson distribution to yield estimated risk ratios (RRs) and 95% CIs for preterm birth for every natural log unit increase in metabolite concentration. We fit a separate model for each of the 13 individual biomarkers of interest as well for the ΣDEHP and ΣAAPhthalates summary measures.We examined the clinical and demographic characteristics, reported as mean (SD) values or as numbers and percentages, of study participants in the total cohort. We fit modified Poisson regression models to evaluate the association of continuous urinary biomarker concentrations with dichotomous preterm birth outcomes.P < .05 was considered statistically significant.We selected covariates a priori as potential confounders based on substantive knowledge using a directed acyclic graph . P < .20 was considered potential evidence of effect modification by infant sex on the multiplicative scale. Third, because our analyses on DINCH metabolites MHiNCH and MCOCH were limited by low detection rates, we dichotomized these parental preconception biomarkers by their median values and fit modified Poisson regression models for dichotomous DINCH metabolite concentrations and preterm birth, adjusting for covariates. We also fit multivariable general linear regression models for continuous parental preconception concentrations of MHiNCH and MCOCH with continuous gestational age to address concerns of lower power given the smaller sample size and therefore smaller number of cases of preterm birth in this subset in which DINCH biomarkers were measured. Coefficient estimates and 95% CIs represent the mean difference in gestational age for each natural log unit increase in urinary DINCH biomarker concentration. To assess the linearity assumption of our positive maternal DEHP results, we fit models across biomarker quartiles and estimated P values for trend across quartiles.First, we restricted the maternal preconception analyses to 228 couples to obtain more comparable results across models within couples. Second, to examine potential differences by infant sex, we stratified analyses and estimated sex-specific RRs and 95% CIs. Effect-measure modification The study cohort included 419 mothers  and 229 fathers  (228 couples) at the time of enrollment . Among tIn total, 1700 maternal preconception urine samples and 590 paternal preconception urine samples were analyzed for phthalate and DINCH metabolites. Women provided a mean (SD) of 4.1 (3.0) urine samles , and men provided a mean (SD) of 2.6 (1.7) urine samples . The distribution of metabolites, detection frequencies, and correlations can be found in eTable 1 and eTable 2 in the P = .01). Risk ratios increased slightly in models accounting for maternal prenatal ΣDEHP concentrations  (P = .17) (eTable 3 in the P = .11) . In sensitivity analyses, maternal preconception MHiNCH concentrations above the median were associated with a suggested increased risk of preterm birth . Maternal preconception MHiNCH concentrations were associated with reduced gestational age   . This asP = .09) (P = .82). The results of MHiNCH and MCOCH models in association with preterm birth were imprecise owing to low power. In sensitivity analyses, paternal preconception MHiNCH or MCOCH concentrations were not associated with continuous gestational age  . HoweverP < .001), as well as in models additionally adjusting for prenatal  or paternal preconception  ΣDEHP concentrations (eTable 5 in the P = .07); however, associations became imprecise in models adjusting for covariates  , the absence of any associations within the paternal preconception window across all of the metabolites examined, and the attenuation of any potential paternal finding after accounting for maternal preconception biomarker exposure. Furthermore, the maternal preconception DEHP associations remained robust and internally consistent across all of the models analyzed. Last, our significant results have biological underpinnings from prior toxicologic studies and are consistent with previous epidemiologic evidence.This study also has some limitations. One limitation was the modest number of preterm birth cases, which precluded us from studying clinical subtypes of preterm birth. Given that previous research has shown elevated odds of spontaneous preterm birth in association with prenatal phthalate exposure,In this prospective study, maternal preconception urinary ΣDEHP metabolite concentrations were associated with an increased risk of preterm birth. Our results suggest that female exposure to DEHP before conception might be an unrecognized risk factor for adverse pregnancy outcomes, often overlooked in clinical practice. These findings may have important clinical and public health implications, given the ubiquity of DEHP exposure, the importance of the outcome, and that prevention strategies rarely focus on preconception care. Although future studies should validate these associations, it is appropriate to inform couples planning conception about measures to reduce phthalate exposure.