The consequences of lacking birth certificates remain largely unexplored in the economic literature. We intend to fill this knowledge gap studying the effect of lacking birth certificates on immunization of children in the Dominican Republic. This is an interesting country because a significant number of children of Haitian descent face the consequences of lacking proper documentation. We use the distance to the civil registry office and the mother’s document of identification as instrumental variables of the child’s birth certificate. After controlling for distance to immunization services and other determinants, this paper finds that children between 0 and 59 months of age that do not have birth certificates are behind by nearly one vaccine  compared to those that have birth certificates. Birth registration, which provides legal proof of a child’s existence and nationality, is considered a fundamental human right according to the Convention on the Rights of the Child (1989). In many countries, identity documents are required to access benefits such as school diplomas, health care services, conditional cash transfers, pensions, banking services, civil rights, adoption, divorce, marriage and inheritance.This paper to sheds light on the effect of birth under-registration on health access. Childhood immunizations, a key component of health care services, are intended to be administered to all children on a standardized schedule. The paper focuses on the effect of under-registration of births on childhood immunization in the Dominican Republic, the country with the second highest percentage (22%) of children under the age of 5 without birth certificates in Latin American and Caribbean (LAC) countries (UNICEF ) Fig. 11.Fig. 1PStudying the factors that affect immunization in the region is important because proper vaccination can reduce infant morbidity , polio eradication saved governments US$1.5 billion per year in treatment and rehabilitation costs . The InAfter controlling for well-established socioeconomic determinants of immunization and endogeneity, this study found that those children without birth certificates have 0.7 vaccines fewer than children with birth certificates. As variables were included that might be correlated to the instruments, the results were found to be robust to threats to the exclusion restriction of the instrumental variables such as location of immunization centers and mobile immunization campaigns.The reason that undocumented children receive fewer vaccinations is because they cannot be registered in the Dominican social security system, which guarantees access to public vaccination facilities or reimburses costs incurred in private health facilities. Moreover, the lack of a birth certificate makes it difficult to prove age, and most countries, including the Dominican Republic, follow WHO’s immunization schedule, which is based on the age of the child. The two vaccines that have lower probability of being delivered are the first doses of polio (OPV1), and pertussis, tetanus, and diphtheria (DTP1). The result is reduced immunization rates and/or delays in vaccine administration.The rest of the paper is organized as follows. Section 2 reviews the related literature and examines factors associated with the registration of children’s births and immunization. Section 3 presents the data used and the methodology and potential econometric difficulties, and Section 4 analyzes the results and provides conclusions.Qualitative studies in the LAC region have shown that children without identity documents have more difficulty accessing public services, including health services. Bracamonte and Ordonez  cover thBut the consequences of the lack of birth certificates are only beginning to be studied. In this regard, Castro and Rud  find a cThis paper examines the consequences of the lack of birth certificates on immunization. Immunization is studied rather than other health care services due to the availability of data, but other health-related programs, such as maternal care, may also be affected by the lack of a legal identity. Immunization programs have been more successful in reaching segments of the most disadvantaged populations in developing countries. In fact, according to WHO, by 2010, LAC countries had achieved coverage above 90% of measles vaccines (MCV) and the three recommended doses of DTP among children aged 12-23 months. Worldwide, coverage rates are typically above 75%, even in the least developed regions.Notwithstanding these high coverage rates, they are not complete. The lack of services due to system failures, poor public awareness, and misconceptions even in well-developed countries are among the reasons behind incomplete immunization schedules  of the Dominican Republic. The DHS includes extensive information on health and education outcomes, as well as household socioeconomic characteristics. It is among the few surveys with information on identity documents.The main variables of interest are immunization outcomes. All children with complete or incomplete vaccinations and those who had never been vaccinated were included in the econometric analysis. Only those children who died before the data was collected are not part our sample. Of the 5,157 children in our sample 4% reported that a child had died, however we do not have information on the immunization records or birth registration of the deceased children. The survey does not contain information about the cause of death which might include unvaccinated children dying from diseases that vaccination might have prevented. For this reason, it is difficult to say anything about the type of bias or censoring this might introduce to our analysis. More problematic could be inaccurate recall of the immunization records of the children without immunization cards. For these children, their parents might have stated incorrectly the number of doses received of a given vaccine included, causing inconsistent estimations in our econometric analysis. Fortunately, the survey recorded information from immunization cards, which were available in 71% of the children in our sample. We used information from vaccination cards for a robustness check in Table 8.one dose of Bacillus Calmette-Guerin (BCG) and one of hepatitis b (HEPB)three doses of Diphtheria Tetanus Pertussis (DTP) or three doses of pentavalent which includes five vaccines in one shot against diphtheria, tetanus, pertussis, hepatitis B and haemophilus influezae bthree doses of Polio (OPV)one dose of measles (MCV) or one dose of triple viral containing vaccines against measles, mumps and rubella (MMR) in one shotThe focus is on the nine vaccines recommended by the WHO in its extended program of immunization (EPI) worldwide. Hence, the vaccines analyzed in this paper are the following:Figure During the survey, mothers were asked to show the vaccination card (70% compliance) to verify whether or not the children had been vaccinated. The cards also contained the day, month, and year of vaccination. Those mothers who reported not having their children’s vaccination card responded from memory but did not provide the date of vaccination. Some literature has found that data using parental recall slightly underreports immunization rates  and the Law on the Dominican Social Security System (Ley 87-01), both passed in 2001. They divide the health system into public and private providers. Figure With regard to the legal framework, the two laws that define the structure of the health system in the Dominican Republican are the General Law on Health Ley 2-01 and Article 3 of Law 42-01 grants Dominican citizens and foreign legal residents the right to health care. Law 87-01 also states that the Social Security System must serve all Dominicans and legal residents in the country without discrimination. In theory, these laws do not exclude undocumented people from public access to health care. In practice, the fact that 98% of women give birth in a health center or a hospital seems to corroborate what the laws state.This paper answers several questions. Does lacking a birth certificate reduce the number of vaccines delivered? Which vaccines are primarily affected? What are the potential mechanisms? Does birth under-registration reduce timely vaccination?To address these questions, we ran several econometric models using the dependent variables described above on uptake and timely vaccination. The empirical strategy uses different limited dependent-variable models that relate vaccine outcomes to birth registration, children’s characteristics, mother’s characteristics, and other controls frequently used in the immunization literature.Our empirical strategy takes into account potential endogeneity of our variable of interest, lack of a birth certificate. Vaccination may increase the incentive to register a child’s birth, generating reverse causation. In this case, the association between immunization and birth certificates would increase if vaccination increased the number of children with birth certificates. In such cases, children vaccinated will be more likely to have birth certificates. Nonetheless, the direction of the bias is jointly determined by the other factor that causes endogeneity. The association of omitted factors with vaccination and their correlation with birth registration is unknown. These omitted factors could include preference for health care services, in particular attitudes on vaccination, and birth registration. Thus, the bias of the coefficient is a priori unknown.(cédula de identidad). Following Corbacho and Osorio [To address this potential endogeneity, we used two instrumental variables: (i) distance from the household cluster to the civil registry office, and (ii) whether or not the mother has an identity document d Osorio  and Britd Osorio , we use d Osorio  also finWe explore the validity of these instrumental variables using a battery of econometric tests and by adding controls that might be correlated with the instrumental variables. For example, the distance to civil registry offices and the mother not having an identity document could be negatively correlated with the existence of health care services such as immunization centers. Thus, to our basic specification, we add as a control the distance to immunization centers to check for the stability of the coefficients in the presence of controls likely correlated with our instruments. After controlling for other determinants of vaccination, our two instrumental variables should not be expected to have an independent effect on vaccines, while being good predictors of birth registration. We also checked in (i)First stage: correlation of birth certificates with distance and mother's IDIn the first stage, we explored the relationship between birth certificates, distance to civil registries, and mother’s identity document after controlling for other socioeconomic characteristics. Table Xi, and household dummies in some cases and province or municipality dummies in others. The Dominican Republic is divided into provinces, including the national district where the capital city is located. The next political subdivision is municipalities. We denote these political subdivisions as γi in our regressions.We used as the dependent variable whether or not the child had a birth certificate and, as predictors, the distance from each cluster of household where child i lives to the nearest civil registry office, a dummy variable indicating whether or not his/her mother lacked an identity document,controls (ii)Second stage: impact of birth registration on immunizationColumns 1 through 4 show a strong and significant effect of both intended instrumental variables on the probability of not possessing a birth certificate. The marginal effects show that every kilometer is associated with an increase in the probability of a child not having a birth certificate of 0.01 percentage points. The mother possessing an identity document increases the probability of registering a child’s birth by at least 0.35 percentage points.What is the impact of birth registration on immunization? The basic empirical specification is:The second stage of our analysis looked at the question: Vacci is any of the immunization variables listed in the summary statistics above for child i; NoBirthCerti is a binary variable that indicates if child i does not have a birth certificate; Xi is a list of controls; γj are household dummies in some regressions and province or municipality dummies in others; and εi is the error of the equation. We used a combination of linear and non-linear models such as OLS, 2SLS and MLEVacci is a discrete variable.where Vacci is the number of vaccines for children aged 0-59 months. MLE is a maximum likelihood estimator that derives a two-step estimator. In the first stage of the MLE, regression (1) is estimated, with NoBirthCerti* being an unobserved probability. The only thing observed is when the child has a birth certificate, in which case the variable used in the first and second stage NoBirthCerti is equal to 1 and is 0 otherwise. Marginal coefficients are reported as they are easier to interpret in the case of non-linear models.The results of the regressions are reported in Table The first OLS estimate in Table With respect to other determinants, we find that children with their vaccination cards receive around 0.2 more vaccines than others. Those born in hospitals and health centers receive more vaccines than those born elsewhere, although the significance is not robust across the econometric specifications. This could be associated with the fact that it may be affecting only the BCG and HEPB vaccines, both given during the first two months of life, usually after birth. This is also consistent with the fact that these first vaccines have the highest uptake rates, as explored in further detail below.One of the most robust findings in the literature on vaccines is that birth order affects the immunization of children in the same households. Older children receive more vaccines than their younger siblings, even after accounting for the difference attributable to their age. In fact, these results are statistically significant across most econometric specifications, except in the case when household dummies are introduced in column 1.Mothers’ education increases vaccination, but the effect is small compared to other determinants. Children born of parents born abroad (the majority of whom are Haitian) receive at least 0.3 fewer vaccines than children whose parents are Dominicans. This could be due to myriad factors, such as language barrier, discrimination, or lack of awareness of the importance of vaccination. With regard to household characteristics, only two are significant: (i) lack of water or electricity; and (ii) wealth, but this characteristic is not robust across specifications, therefore we omitted it. It is also surprising that rural areas do not have lower immunization records than urban areas.The next step was to add more controls in order to check the robustness of the results. The most immediate threat to the exclusion restriction is that parents who live far from health facilities may also live farther from civil registry offices and lack identity documents. If this threat to the exclusion restriction is real and the variables that capture access to immunization centers are unobserved, the coefficients in columns 3 and 4 would be biased despite using instrumental variables. Fortunately, we found information on access to health centers, mobile immunization campaigns, and location of permanent immunization centers.vaccinated in a campaign, which measures if the child was vaccinated in any mobile vaccination campaign; ii) health center far away, which captures self-reported perception of distance to the health center; iii) distance to nearest immunization center in km, which involved collecting data on the location of more than 800 permanent immunization centers in the Dominican Republic; and iv) immunization center open morning/afternoon. To obtain data related to variables iii and iv, the address, hours of operation, and latitude and longitude of the immunization centers were collected. The results appear in columns 2 through 7 in Table The variables added were: i) We used the standard battery of econometric tests performed to assess the validity of instruments. The tests at the bottom of Table (iii) Effect on individual vaccinesWith regard to the new controls added to check for robustness of the basic specifications, we find that vaccination campaigns are strongly associated with immunization. Specifically, a child vaccinated in a mobile vaccination campaign receives 0.07 more vaccines than children vaccinated only at permanent immunization centers. The fact that the mother considers the health center far away is associated with a reduction in the number of vaccines by 0.12. Finally, the actual linear distance to the immunization center was not significant.The results so far established that lacking a birth certificate reduces the number of vaccines in children under 59 months of age. But, what can be said about the effect on each individual vaccine? We explore this in Table Three vaccines seem to be affected by the lack of a birth certificate: the DTP1, OPV1 and MCV. The coefficients were statistically significant also when we included dummy variables at the household level in OLS regressions (except for the MCV). Children without birth certificates have 13, 11, and 30 percentage points less likelihood of being vaccinated with DTP1, OPV1, and MCV, respectively. These results should be of great concern to national authorities and civil society because polio destroys motor neurons and causes muscle weakness, resulting in permanent physical damage. Diphtheria, tetanus, and pertussis are highly contagious and develop into epidemics quickly in large, populated areas. According to the WHO, measles is a leading cause of vaccine-preventable child mortality.We also repeated the analysis using the sample of children with vaccination cards. The results are contained in the Why does the lack of a birth certificate affect vaccination?(b)Does the lack of a birth certificate produce delays in vaccination?One mechanism of transmission could be related to the need to prove a child’s age in order to receive a specific vaccine. Given that in the Dominican Republic there is a schedule of vaccinations that recommends that vaccines be given at a particular age, not having proof of age-appropriateness could be one channel of transmission. The vaccination schedule is based on the fact that the immune system’s response is optimal at the recommended age. Undocumented immigrants are also afraid to enter public services facilities, where proof of documentation is needed, in order to avoid problems with their immigration status. Therefore, it is highly likely that mothers whose children lack identity documents avoid visiting immunization centers.We also examined the effect of lack of birth certificates on delays in immunization delivery. The results are reported in Table Among children without birth certificates, the proportion of age-due vaccines decreases by about 10% according to the estimate in column 1. Up to date vaccinations at 7 months is not affected by the lack of a birth certificate. However, the probability of having complete, up-to-date vaccinations at 12 months is reduced by 27 percentage points if the child lacks a birth certificate, as suggested by the IVPROBIT regression in column 3.Healthy children do better in school, and as adults they are more productive at work. Health care at an early age, including immunization, is thus a crucial component of long-term economic prosperity. However, while much research on the socioeconomic characteristics of infant vaccination has been conducted, nothing has been said about the effect of the lack of legal identity on access to health services. This is the first study that aims to quantify a causal impact of the lack of a birth certificate on infant vaccination. The Dominican Republic is a highly relevant case because it is one of the few countries in Latin America and the Caribbean where under-registration birth is considerable.We found that children without birth certificates are behind by 0.7 vaccines compared to those with birth certificates. In addition, the probability of vaccination with DTP1, OPV1, and MCV is reduced by 8, 7, and 19 percentage points respectively. Moreover, timely vaccination is less likely to occur when a child lacks a birth certificate. The proportion of age-due vaccines for children of a given age is reduced by 10 percent, and the probability of vaccination in due time at 12 months of age is reduced by 23 percentage points.These findings have important policy implications. Around 98% children are born in hospitals and health centers and more than 90% receive at least the first two vaccines, BCG and HEPB. Given that health services have better coverage and far more outreach activities than civil registries, there is an opportunity to integrate their work in order to reduce the percentage of children without birth certificates and increase immunization rates.


To assess the value of single and serial fetal biometry for the prediction of small- (SGA) and large-for-gestational-age (LGA) neonates delivered preterm or at term.th centile) and LGA (>95th centile) at birth based on INTERGROWTH-21st gender-specific standards. Fetus-specific estimated fetal weight (EFW) trajectories were calculated by linear mixed-effects models using data up to a fixed gestational age (GA) cutoff  for fetuses having two or more measurements before the GA cutoff and not already delivered. A screen test positive for single biometry was based on Z-scores of EFW at the last scan before each GA cut-off so that the false positive rate (FPR) was 10%. Similarly, a screen test positive for the longitudinal analysis was based on the projected (extrapolated) EFW at 40 weeks from all available measurements before each cutoff for each fetus.A cohort study of 3,971 women with singleton pregnancies was conducted from the first trimester until delivery with 3,440 pregnancies  meeting the following inclusion criteria: 1) delivery of a live neonate after 33 gestational weeks and 2) two or more ultrasound examinations with fetal biometry parameters obtained at ≤36 weeks. Primary outcomes were SGA  and femur length (FL) , mainly due to differences in the measurement technique. Single biometry based on EFW at the last scan at ≤32 weeks (GA IQR: 27.4–30.9 weeks) had a sensitivity of 50% and 53% (FPR = 10%) to detect preterm and term SGA and LGA neonates, respectively (AUC of 82% both). For the detection of LGA using data up to 32- and 36-week cutoffs, single biometry analysis had higher sensitivity than longitudinal analysis . Restricting the analysis to subjects with the last observation taken within two weeks from the cutoff, the sensitivity for detection of LGA, but not SGA, increased to 65% and 72% for single biometry at the 32- and 36-week cutoffs, respectively. SGA screening performance was higher for preterm (<37 weeks) than for term cases  for single biometry at ≤32 weeks.Fetal abdominal and head circumference measurements, as well as birth weights in the Detroit population, matched well to the INTERGROWTH-21When growth abnormalities are defined based on birth weight, growth velocity  does not provide additional information when compared to the last measurement for predicting SGA and LGA neonates, with both approaches detecting one-half of the neonates (FPR = 10%) from data collected at ≤32 weeks. Unlike for SGA, LGA detection can be improved if ultrasound scans are scheduled as close as possible to the gestational-age cutoff when a decision regarding the clinical management of the patient needs to be made. Screening performance for SGA is higher for neonates that will be delivered preterm. The detection of fetal growth disorders is an important goal in modern prenatal care –4. SonogAn important issue is whether serial fetal biometry should be used in all pregnancies ,22. A prEunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), and Wayne State University, at Hutzel Women’s Hospital, Detroit, Michigan, from January 2009 until December 2014. All patients provided written informed consent and were enrolled in research protocols approved by the Human Investigation Committee of Wayne State University and by the Institutional Review Board of the NICHD.This longitudinal study was conducted at the Center for Advanced Obstetrical Care and Research of the Perinatology Research Branch, The study population consisted of 3,971 eligible women with singleton pregnancies without congenital or chromosomal anomalies, who underwent serial ultrasound examination every four weeks until 24 weeks of pregnancy and thereafter every two weeks until delivery. However, since the gestational age at first scan varied among patients and not all patients returned to the clinic on schedule, the number and gestational ages at ultrasound examinations varied among patients Exclusion criteria were: delivery prior to 33 gestational weeks, missing data about gestational age at delivery, fetal gender, and birth weight. To be included in this analysis, subjects must have undergone at least two fetal biometry examinations at ≤36 weeks with biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) measurements. The resulting dataset of 3,440 pregnancies  was analyzed to predict SGA and LGA outcomes for three different time points: 1) delivery after 28 weeks, 2) delivery after 32 weeks, and 3) delivery after 36 weeks. Subjects were included if they underwent two or more fetal biometric examinations at least three weeks apart prior to delivery.10(EFW) = 1.4035+0.0441∙AC+0.177∙FL-0.0037∙AC∙ FL+0.0027∙BPD2. [Gestational age was determined by the crown-rump length measurement or by the biparietal diameter during the first ultrasound scan . The BPD, HC, AC, and FL measurements were obtained by following the recommendations of the International Society of Ultrasound in Obstetrics and Gynecology . Fetal w27∙BPD2. st birthweight standards according to gestational age at delivery and fetal sex were used to define SGA and LGA neonates [st birth weight standards were defined for neonates delivered at 33 weeks or more, we limited the study group herein to those delivering a neonate at ≥ 33 gestational weeks. SGA was defined as a birthweight <5th centile, and LGA was defined as a birthweight >95th centile.The INTERGROWTH-21neonates . Since t+1, 33+1, and 36+1 weeks, respectively). These scenarios allow assessing how SGA and LGA prediction performance changes as more data becomes available prior to delivery. Although the population of patients changes somewhat from one scenario to another the comparison between single biometry and longitudinal analysis is performed on the data from the same patients.Two approaches described below  were used to screen pregnancies under three scenarios that differ by: i) the gestational age cut-off  up to which ultrasound scans were used for prediction of outcomes, provided that two or more scans were available up to the cut-off and ii) the earliest gestational age at delivery of patients included in the analysis , LGA positive (Z score EFW > zFPR = 10%) or appropriate for GA, otherwise. The cut-off zFPR = 10% represents the Z-score percentile that resulted in a false positive rate of 10% for each outcome (SGA or LGA) separately to enable direct comparison between the sensitivity of different prediction methods and cut-off points.The first approach used for screening relied on a single (last) EFW evaluation before the GA cut-off under consideration. To account for differences in the GA values at last evaluation between subjects, EFW data was transformed into Z-scores by subtracting the mean and dividing by the standard deviation computed from longitudinal EFW profiles of all fetuses included in this study as previously suggested . The meaal bones . The scrThe procedure to predict an outcome (SGA or LGA) based on two or more longitudinal measurements collected up to a given GA cutoff involved two main steps:1) For each subject, forecast (extrapolate) the EFW value at term (GA = 40 weeks) from longitudinal determinations of EFW up to the GA cut-off considered using linear mixed-effects models. This step is similar to that reported by Albert  implemenThe linear mixed-effects model included, in addition to the fixed effects coefficients , a corresponding random effect that allowed the trajectory of each subject to depart from the overall population average. The model was fit using the complete dataset to compute fixed effects coefficients, variance components, and properties of the distribution of random effects. For each subject separately, the EFW at two or more time points until the GA cut-off were used to compute subject-specific random effects. Using population-derived fixed effects and subject-specific random effects, the EFW at 40 weeks of gestation was determined (projected).40) were used to set the screen status of each patient as SGA positive (EFW40< cFPR = 10%) or LGA positive (EFW40> cFPR = 10%), where cFPR = 10% is the percentile on EFW40 such that the false positive rate is 10% for each outcome (SGA or LGA) separately.2) The resulting projections of EFW at 40 weeks GA (EFWth percentile) and 174 (5.1%) were classified as LGA (>95th percentile) based on the INTERGROWTH-21st birth weight standards.Demographic characteristics of the population in this study are presented in The rates of SGA were higher among nulliparous, preeclamptic, and women who reported smoking during pregnancy, while being lower in obese women . The rates of LGA were higher in obese women as well as those with gestational diabetes Mellitus  see .st project [st study, while the 95% confidence intervals diverged by up to 10% for BPD and 7% for FL. These results suggest systematic differences in the protocols for measurements of lengths but similar protocols for circumferences between the current study and INTERGROWTH-21st standards  three gestational age cut-off scenarios  and two types of analysis methods  as shown in Single biometry analysis had a sensitivity of 39%, 51%, and 56% (FPR = 10%) to identify preterm and term SGA neonates delivered after 28, 32, and 36 weeks of gestation based on the last evaluation of EFW available at ≤28, ≤32, ≤36 weeks, respectively . The lonboth single biometry and longitudinal analysis for all three cutoffs in the restricted analysis compared to the overall analysis.Since ultrasound scans were not scheduled at fixed gestational weeks for each woman, there was substantial variability in the gestational age at the last sample of women included in the SGA and LGA prediction analysis for each of the cutoffs considered . th percentile was used as the outcome instead of the SGA<5th percentile. Similar improvements were observed for longitudinal analysis as well  and 5.1% as LGA (>95th centile).Birthweights in the cohort of 3,440 pregnancies from our study population were similar to those of the INTERGROWTH-21st study standards for fetal head and abdominal circumferences  but not those for biparietal diameter and femur length .Our locally derived reference for fetal size parameters matched the INTERGROWTH-21th centile) (FPR = 10%). For LGA prediction at the ≤32- and ≤36-week cutoffs, single biometry is preferable (p<0.05).Single biometry (the last available assessment of EFW) as well as longitudinal analysis  at ≤32 weeks can identify one-half of neonates who will be SGA  SGA cases are easier to detect based on a single biometry at ≤32 than term SGA cases .st project define optimal fetal size and birth weight based on a population of healthy, well-nourished pregnant women and their fetuses [st project, this was not the case for two of the four ultrasound parameters . The most likely reasons for discrepancies are differences in the measurement techniques between the two studies (for BPD) and racial differences for femur length [st standards to classify neonates as SGA and LGA but relied on locally derived reference ranges for fetal biometry.Universal standards generated by the INTERGROWTH-21 fetuses . These s fetuses . Althougr length ,32. TherMost studies reporting prediction performance of ultrasound-based biometry rely on a single measurement taken at a fixed gestation  or ath percentile) and LGA (>95th percentile) for a single EFW evaluation between 30–34 weeks in a Caucasian population of 3,690 women. A similar performance was obtained by Fadigas et al. [th centile) neonates with delivery at ≥37 weeks when the EFW assessed at 30–34 weeks was combined with maternal factors, uterine artery PI, mean arterial pressure, and serum placental growth factor. The results described herein for single biometry at ≤32 weeks in a mostly African-American population are in very good agreement with these previous findings as we report about a 50% sensitivity for both SGA (<5th centile) and LGA (>95th centile) prediction (FPR = 10%).Performance estimates for single biometry were reported by Souka et al.  to be abs et al.  reportedth. For the same outcome (SGA <10th) using single biometry at ≤36 weeks, we obtained a 55% sensitivity (AUC = 0.85) (st birth weight standards vs a UK reference), as well as the differences in the distribution of GA at scan for this analysis  . The gooThe primary aim of this study was to evaluate whether the knowledge of fetal-size parameters from prior ultrasound examinations can improve prediction of SGA and LGA neonates compared to the last available fetal biometry examination prior to a given GA cut-off. Previous studies analyzing longitudinal ultrasound data involved either different outcomes and/or asked different questions regarding the benefit of considering longitudinal biometry as a part of clinical care ,38.3) at birth, and those who will develop suboptimal neonatal outcomes [For example, Chang et al  reportedoutcomes . The infgrowth vs. size, suggesting that these should be conditional at early measurements in each subject as opposed to one-fits-all growth rate standards. Owen et al. [Subsequently, Royston  describen et al.  reportedn et al.  studied Others have reported that two ultrasound examinations increase the detection of small fetuses and those at a higher risk of perinatal complications; however, the data were treated as separate evaluations, and no growth rate information was used .More recently, a framework to summarize longitudinal biometry by extrapolating individual growth trajectories at a fixed time point in pregnancy  was proposed ,43, yet For preterm and term SGA detection, a single (most recent) or multiple biometry provide similar performance, while for detection of LGA after 32 weeks of gestation, single biometry is preferred . For LGAst fetus sex-specific birth weight standards as opposed to local reference ranges for birth weight or fixed cutoffs on birth weight. Moreover, by using multiple GA cut-offs, we have assessed the differences between these methods both earlier and later in pregnancy for preterm and term delivered neonates. To these strengths we can add a large sample size of 3,440 women. The main limitation of this study is that the number and gestational age at ultrasound scans varied among patients.Among the strengths of this study is the fact that the comparison between single biometry and longitudinal analysis for SGA and LGA screenings was based on outcomes defined using the INTERGROWTH-21S1 FigBirthweight (g) as a function of Estimated Fetal Weight (g) are shown in pregnancies where the last scan was taken within one week from the delivery. The Hadlock model with original coefficients has a bias, i.e. the smaller the baby the more underestimated is the fetal weight (left). Using a revised formula in which the coefficients are updated for the current population removed the bias (right).(TIF)Click here for additional data file.S1 TableGA: gestational age. FPR: False Positive Rate.(XLS)Click here for additional data file.S2 TableSGA and LGA prediction performance, sensitivity at 10% false positive rate (FPR), and area under the receiver operating characteristic curve (AUC) is shown for the original analysis as well as two other scenarios.(XLS)Click here for additional data file.


The percentages of low birth weight (LBW) increased from 7.7% in 2005 to 11.3% in 2011 and declined to 8.1% in 2017. For very low birth weight (VLBW) individuals, the proportion declined −1.0% annually, from 2.5% in 2005 to 1.4% in 2017. Among moderately low birth weight (MLBW) individuals, the proportion first increased 12.8% annually, from 5.0% in 2005 to 9.3% in 2011, and then declined −3.8% annually, from 9.4% in 2011 to 7.0% in 2017. The percentages of macrosomia monotone decreased from 4.0% in 2005 to 2.5% in 2017, an annual decline of −4.0%. Multiple regression analyses showed that boys, maternal age, hypertensive disorders complicating pregnancy (HDCP), and diabetes were significant risk factors for LBW. Boys, maternal age, gestational age, HDCP, diabetes, and maternal BMI were significant risk factors for macrosomia. Although the relevant figures declined slightly in our study, it is likely that LBW and macrosomia will remain a major public health issue over the next few years in China. More research aimed at control and prevention of these risk factors for LBW and macrosomia and their detrimental outcome in the mother and perinatal child should be performed in China. Studies have shown that LBW infants die 40 times as much as normal weight infants, and LBW infants are many times more likely to end up with long-term handicapping conditions2. Children with LBW increased over the past two decades in many countries6. The prevalence of LBW is estimated to be 19% in developing countries and 5% to 7% in developed countries. According to Report of National Health Services Survey of China, the proportion of low birth weight has a ratio of 2.7% in 2006, and continuously increased with the scale-up of cities. Another research7 including 39 hospital in 14 different provinces in China reported the incidence of LBW in mainland China was 6.1%. The risk factors for LBW, such as older maternal age, anemia, hypertension, and poor nutritional status, are widely reported in recent studies9.Low birth weight  is a most important factor of neonatal mortality and a major determinant of postnatal infant mortality, as well as morbidity in infancy and in older childhood11. Macrosomia are associated with increased risk of cesarean delivery, abnormal hemorrhage, shoulder dystocia, and post-term pregnancy, as well as keep the babies at a risk of perinatal asphyxia, fracture, cerebral hemorrhage even death13. Besides, studies have shown that there is a higher risk of developing obesity and metabolic disorders of macrosomia infants14. The proportion of macrosomia increased over the past thirty years in many countries18, with frequency ranging from 0.5% to 14.9% in Asia, Africa and Latin America10. In particular, the number in China noted an increased from 6.0% in 1994 to 7.8% in 200515. There is an increase of 15–25% reported in the past three decades mainly due to an increase of maternal obesity and diabetes19. It is strong evidence to show that male, older maternal age, maternal diabetes, gestational body-mass index (BMI) and higher parity were significantly associated with increased odds for macrosomia in all regions20.Macrosomia refers to the body weight reaching or exceeding 4000 g, which can increase the risks of a poor pregnancy outcome in mothers and newbornsThere are many studies focus on the incidence and risk factors of low birth weight and macrosomia, but little data on their long-term trends and their continuous observations in China. Besides, the etiology of low birth weight and macrosomia cannot be thoroughly explained by current researchs, so more observational studies are necessary. The purpose of our study was to examine the secular trend of LBW and macrosomia in Foshan, a city located in the south China, and explored relevant factors associated with LBW and macrosomia, to provide valuable information to reduce maternal and neonatal morbidity and mortality due to LBW and macrosomia.The entire study population consisted of 102,526 individuals with a mean age ± SD of 28.3 ± 4.8 y. 25 to 29 year olds had the highest proportion of all individuals, reaching 43.2%, followed by 30 to 34 years (24.1%) and 20 to 24 years (20.0%). 61.7% of the study population were primiparae. The vast majority (98.6%) were Han Chinese. Clinical characteristics of the study population are described in Table Among VLBW individuals, the proportion of which declined by −1.0% annually , from 2.5% in 2005 to 1.4% in 2017. Among MLBW individuals, the proportion of which increased by 12.8% annually , from 5.0% in 2005 to 9.3% in 2011, and declined by −3.8% annually , from 9.4% in 2011 to 7.0% in 2017. The proportion of normal neonatal weight remained relatively stable, ranged 85.0% to 89.3%, then declined by −0.5% annually (95% CI: −0.7 to −0.3) during 2005 to 2011 and increased by 0.6% (95% CI: 0.3 to 0.8) annually during 2011 to 2017. The proportion of macrosomia has declined from 4.1% to 2.5%, among which declined by −4.0% annually (95% CI: −5.5 to 2.5) during this period , 2142 (SD:267), 3182 (SD:342) and 4198 (SD:447) grams, respectively  and 1209 grams (95% CI 984 to 1434).The mean weight of MLBW group between 2005 to 2017 has slightly increased from 2110 grams (95% CI 1842 to 2378) to 2136 grams (95% CI 1853 to 2419). The mean weight of Normal group between 2005 and 2017 was 3192 grams (95% CI 2848 to 3536) and 3210 grams (95% CI 2870 to 3549). The mean weight of macrosomia group between 2005 and 2017 was 4176 grams (95% CI 3933 to 4419) and 4353 grams (95% CI 4021 to 4284)  and 0.62 (95% CI: 0.47 to 0.83) in 2017 respectively, reference to 2005 (RR = 1), after adjusted for maternal age, parity and gestational age. The relative risk of MLBW rose rapidly at first during 2005 to 2010, with a peaked in 2010 , and then declined slowly during 2010 to 2017 . The RR value of normal weight infants dropped first and then increased, and the RR values were slightly increased in 2017 , comparing with 2005 , maternal age 20 to 24 years , maternal age 25 to 29 years , maternal age 30 to 34 years , maternal age >35 years , HDCP , diabetes  were significant risk factors for LBW in the multiple logistic regression model.Boys , maternal age 30 to 34 years , maternal age >35 years , HDCP , diabetes , gestational age during 37 to 41 weeks , gestational age ≥42 weeks , BMI 25 to 30 , BMI > 30  were significant risk factors for macrosomia in the multiple logistic regression model , and the incidence of LBW infants has been between 3.3% and 4.9% in Beijing urban area in the past 20 years5, which was slightly lower than reported in our study. On one hand, this reduction reflects dramatic advances in medical technology and continuously improved expectant management for LBW births over the past 20 years in China. On the other hand, differences in case definition between studies, regions and nations, and the institution based tertiary care settings of many previous studies may also have played a role in the observed reduced incidence. According to World Health Organization public data22, the incidence rates of LBW infants in major western countries respectively were as follows: Australia (7%), Canada (6%), Germany (7%), France (7%) and US (8%) respectively, which were similar or slightly lower to our results. Furthermore, our data showed that more than 70.1% of the low birth weight infants were preterm births, which were similar to previous studies in Beijing5. We consider the main reason for this pattern was due to the increasing survival rates of preterm births and the extremely LBW newborns in China; therefore, it is reasonable to assume that preterm birth was the primary cause of LBW in our study. In addition, this hospital is an emergency care center for the emergency care of critically ill mothers and newborns in the city. Full term LBW infants should also deserve public attention, because these babies or their mothers maybe more likely to develop severe complications or have a worse outcome.Many studies have focused on the incidence and risk factors of LBW and macrosomia, but there is little data on the long-term trends and ongoing observations in China. In this study, we determined the proportion of LBW and macrosomia in Foshan during 2005 to 2017, and identified the independent risk factors of LBW and macrosomia using a logistic regression model. The proportion of VLBW monotone decreased from the years 2005 to 2017, at an annual 1.0% of decline. However, the proportion of MLBW first increased and then declined during the same period, which resulted in a slight increase in the incidence of total LBW from 7.7% to 8.1% between 2005 and 2017. A national survey showed infants with birth weights less than 1500 g (VLBW) accounted for 3.8% in 1998, in the major cities of China23. Other studies7 have shown that LBW infants have an increased risk of hypertension, kidney disease, type 2 diabetes, obesity, and coronary heart disease; however, the etiology for these complications remains unclear. LBW infants include infants who are small for their gestational age and with fetal growth restriction (FGR). A premature infant (<37 weeks of gestation) generally has an LBW, which might otherwise have been an appropriate weight if growth had continued normally until fullterm, but could also be a result of FGR. FGR is not an indication for a caesarean section, but FGR infants are likely to suffer from hypoxia and are not responsive to contractions. Thus, it is necessary to select the appropriate time for caesarean section as required, in FGR infants and identify potential risk factors to facilitate early intervention. Antepartum electronic fetal heart monitoring could be used closely during labor, and the delivery mode should be determined according to amniotic fluid volume and the duration of labor.Epidemiological studies show that a 1000 g reduction in birth weight results in a 1.7 fold increase in the risk of proteinuria in children, and a 3-fold increased risk of proteinuria in adulthood24, but the incidence was lower than in the northern part of China5. It has been reported that, since 2000, the incidence of macrosomia has been increasing across the United States and in other developed countries26. From the results of this study, although the proportion of pregnant women with an increased nutritional intake ratio has increased along with the improvement in the economy, the incidence of macrosomia showed a downward trend. This steady downward decline occurred later in Foshan, which may be explained through increased medical and health awareness and improved nutrition, education supervision and advice for all pregnant women, encouraging them to control their weight to within an acceptable range. Foshan is an economically developed city with low infant mortality rates, and the debate about whether caesarean section is needed for macrosomia has focused mainly on avoiding serious consequences such as shoulder dystocia, clavicular fractures, possible postpartum hemorrhage, and brachial nerve injuries. Obstructed labor has resulted in notable adverse outcomes for mothers and infants in developing countries27, and cephalopelvic disproportion due to macrosomia is one of the most important outcomes28. However, aprenatal diagnosis of suspected macrosomia is challenging. Therefore, it remains controversial whether to perform a caesarean section in cases of suspected macrosomia. For a pregnant woman with an underlying disease, or with a small pelvis or who is malnourished, a caesarean section should be performed to prevent serious consequences, as fetal macrosomia is a major risk factor for infant morbidity and mortality.The prevalence of macrosomia was relatively muted, varying from 4.0% to 2.5%, and the downward trend is consistent with previous reports in China29. This should alert gynecologists to be attentive to an early diagnosis of preeclampsia and eclampsia, which involve the two serious phases of HDCP, through testing mean arterial pressure, undertaking the roll-over test or hematological examinations. Although no consensus on macrosomia standards have been reached, there is evidence that the risk of adverse neonatal outcomes increases when the birth weight is 4000 g or greater30. As such, in this study of Asian women, a cut-off point of 4000 g seemed appropriate. In our study, being pregnant with diabetes, older gestational age and maternal age, high parity, and obesity were risk factors strongly associated with macrosomia. With an ageing population and an increasing maternal age following the introduction of the universal two-child policy in China, in addition to growing numbers of people with diabetes and obesity, macrosomia will continue to be an important public health issue in the future.Our findings showed that HDCP were strong risk factors associated with LBW, which is consistent with several other studies19, and this may have resulted in biased estimates. Finally, this paper takes LBW as the research object, rather than the concepts of “small for gestational age” and “intrauterine growth restriction” which were commonly used by obstetrician. All these potential limitations should be considered when interpreting the results of this study.Electronic health records (EHRs) are an increasingly utilized resource for clinical and public health research, but there are several potential limitations with this study. First, despite this hospital being the largest maternity and child health care hospital in Foshan, with a stable number of more than 13000 deliveries per year, Berkson’s bias is likely, due to this being a single-center study. Therefore, the results might not be generalizable to other cities or countries discussed in this study. Additionally, the hospital’s electronic information system has been upgraded several times between 2005 and 2017, and may have an approximate 5% error rate, with some values missing from previous information. In the data cleaning and analysis phase, we corrected some of the obvious errors and either completed or deleted the missing values, which reduced errors to a minimum. Furthermore, our electronic information system does not provide information about gestational weight gain, which has been associated with macrosomia in previous studiesConstant urbanization and increasing growth in the national economy, coupled with the lifting of the one-child policy in China, means that the risk factors for LBW and macrosomia, such as hypertension, diabetes, obesity, and an older maternal age of childbearing women, will continue to increase rapidly. Thus, despite the relevant figures having declined slightly in our study, LBW and macrosomia will continue to be a major public health issue. More research aimed at controlling and preventing LBW and macrosomia risk factors and the detrimental outcomes in mothers and perinatal children is needed in China.The city of Foshan, located in South China, is the one of the largest city with a population of nearly 7.4 million of China. The entire study population consisted of 102,526 individuals at least 20 weeks gestation from Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan city, Guangdong province, China between January 2005 and March 2017. All mothers who had singleton births at the hospitals during this period were put into analysis. There were totally 109,780 live births in our study sites. The study excluded 4.708 births with missing birth weight, or newborns outside the range of 20–44 weeks, 2,500 cases of multiple pregnancies, and 46 cases with incredible weight range. Finally, a total of 102,526 cases were included in the study. This hospital was a tertiary university-affiliated medical center with a stable number of approximately 10,000 to 13,000 deliveries per year, which is accounting for 1/8 of total number of newborns in Foshan city. An informed consent was obtained from all participants. In order to ensure patient privacy, our data did not include the patient’s name, phone number, home address, or other sensitive information.30.The study was approved by the Human Subjects Committee of the Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan and all methods were performed in accordance with the relevant guidelines and regulations32. Diabetes including diabetes mellitus (DM) and gestational diabetes mellitus (GDM). Diagnostic criteria with reference to the recommendation from the Chinese Medical Association Obstetrics Group33. GDM was diagnosed when one of the following condition was met: (1) fasting plasma glucose ≥5.8 mmol /L twice or more times; (2) two or more test results are equal or above the following values after a 100 g-load OGTT: fasting, 5.8 mmol/L; 1-hour, 10.6 mmol/L; 2-hour, 9.2 mmol/L; 3-hour, 8.6 mmol/L; (3) 50 g glucose challenge test ≥11.1 mmol/L and fasting plasma glucose ≥5.8 mmol/L. All diagnosis of HDCP and diabetes was confirmed by obstetricians or specialist physician. Body mass index (BMI) was calculated from height and weight before delivery (BMI = weight in kg/height2 in meter). To ensure the reliability of data, systematic training was provided for data entry operator for understanding of the study objective and methods.Refered to the standard of the WHO, low birth weight (LBW) is defined as birth weight less than 2500 grams, and subdivided further into very low birth weight  and moderately low birth weight . Macrosomia is defined as birth weight more than 4000 grams. The major covariates studied included the following characteristics of the mother: infant sex , age , mode of delivery , parity , gestational age , hypertensive disorder complicating pregnancy(HDCP) or not, diabetes mellitus or not, body mass index (BMI) . We calculated gestational age on the basis of the actual delivery date in the medical record. HDCP  can be classified into five groups: (1)gestational hypertension, (2)preeclampsia, (3)eclampsia, (4)superimposed preeclampsia on chronic hypertension and (5) chronic hypertension in pregnancyp-Values of two-sided tests, 0.05 were considered statistically. All analyses were performed with R for Windows version 3.4.1.For descriptive analysis, mean and SD were calculated for continuous variables, and percentages for categorical variables. Birth weight was analyzed by categorizing into four outcome variables: VLBW (<1500 g), MLBW (1500 to 2499 g), normal birth weight (2500 to 4000 g) and macrosomia (≥4000 g). Trend analysis were quantified using the Join point Regression Program , version 4.4.0.0, which uses permutation analysis to fit a series of straight lines on a logarithmic scale to observed rates to estimate annual percent change (APC), resulting in trends of variable length. The Annual Percent Change (APC) is significantly different from zero at the alpha = 0.05 level. Binary logistic regression was used to estimate the relative risk (RR) and corresponding 95% confidence interval (CI) of the association between low birth weight and macrosomia. We mutually adjusted the analysis of the risk factors for LBW and macrosomia for infant sex, maternal age, parity, mode of delivery, gestational age, HDCP, diabetes, body mass index (BMI) in the model. The variables were considered based on literature review for their relevance to LBW and macrosomia and availability of data.


Introduction: The U.S. Food and Drug Administration (FDA) has estimated the economic impact of Graphic Warning Labels (GWLs). By omitting the impact on tobacco consumption by pregnant women, the FDA analysis underestimates the economic benefits that would occur from the proposed regulations. There is a strong link between the occurrence of low birth weight babies and smoking while pregnant. Low birth weight babies in turn generate much higher hospital costs than normal birth weight babies. This study aims to fill the gap by quantifying the national hospital cost savings from the reductions in prenatal smoking that will arise if GWLs are implemented in the U.S. Data and Methods: This study uses several data sources. It uses Natality Data from the National Vital Statistics System of the National Center for Health Statistics (NCHS) in 2013 to estimate the impact of prenatal smoking on the likelihood of having a low-birth-weight baby, controlling for socio-economic and demographic characteristics as well as medical and non-medical risk factors. Using these estimates, along with the estimates of Huang et al. (2014) regarding the effect of GWLs on smoking, we calculate the change in the number of LBW (low birth weight) babies resulting from decreased prenatal smoking due to GWLs. Using this estimated change and the estimates from Russell et al. (2007) and AHRQ (2013) on the excess hospital costs of LBW babies, we calculate cost saving that arises from reduced prenatal smoking in response of GWLs. Results and Conclusions: Our results indicated that GWLs for this population could lead to hospital cost savings of 1.2 billion to 2.0 billion dollars over a 30 year horizon. Maternal smoking during pregnancy is strongly linked to infant low birth weight . Because maternal smoking during pregnancy is a significant factor for LBW babies and treating LBW babies is expensive, maternal smoking imposes high medical costs. Russell et al. (2007)  estimateThe U.S. Food and Drug Administration (FDA), which was charged with regulating tobacco products by the 2009 Family Smoking Prevention and Tobacco Control Act (FSPTCA), proposed and finalized a regulation requiring large graphic warning labels (GWLs) to be added to cigarette packs sold in the U.S. Although court challenges by tobacco companies prevented FDA from implementing the rule, FDA has said it remains committed to implementing its responsibilities under the FSPTCA, which include revising cigarette warning labels. Thus, estimating the various public health benefits that would result from GWLs remains important from a policy perspective .Cigarette package warnings that are graphic, larger, and more comprehensive in content are effective in communicating the health risks of smoking . These gIn this paper, we examine potential hospital cost savings generated by the reduction of low birth weight babies that arise from graphic warning labels. First, we provide new estimates of the link between cigarette consumption by pregnant women and their baby’s birth weight. Our estimates use the U.S. 2013 Natality File, a comprehensive, large data set of nearly 4 million observations. Controlling for a myriad of confounding factors including mother and baby characteristics, characteristics of the delivery, socio-economic factors, and sources of payment, we estimate the impact maternal smoking has on the probabilities of giving birth to a low birth weight baby, a very low birth weight baby, and an extremely low birth weight baby.Using these new estimates, along with the Huang et al.’s 2014)  estimate4  estimaWe extracted data from the 2013 Natality File that contains micro-level data on all births registered in the 50 United States, the District of Columbia, and New York City in calendar year 2013. The National Center for Health Statistics (NCHS) in conjunction with the Centers for Disease Control and Prevention (CDC) collects this data from individual records processed by each registration area, through the Vital Statistics Cooperative Program. Births are limited to births occurring within the United States. Births occurring to United States citizens outside of the United States are not included in the file. In total, the data set contains detailed information on 3,940,764 births occurring in the United States in 2013.We created three dichotomous dependent variables representing different low birth weight categories. The first dependent variable, low birth weight, takes on a value of one if the baby was born with a weight of at least 1500 g but less than 2500 g, zero if the baby was born with a weight greater than or equal to 2500 g, and missing if the baby was born with a weight of less than 1500 g. The second dependent variable, very low birth weight, takes on a value of one if the baby was born with a weight of at least 1000 g but less than 1500 g, zero if the baby was born with a weight greater than or equal to 1500 g, and missing if the baby was born with a weight of less than 1000 g. Finally, the third dependent variable, extremely low birth weight, takes on a value of one if the baby was born with a weight of less than 1000 g, and zero otherwise.We created a rich set of independent variables to control for the determinants of low birth weight. Of particular importance to this research is whether or not the mother smoked during pregnancy. We created a dichotomous indicator equal to one if the mother smoked during pregnancy, and equal to zero otherwise.We also created variables to control for characteristics of the mother including the mother’s age at pregnancy, the mother’s height and weight before pregnancy, and the number of pounds gained by the mother during pregnancy. We created a dichotomous indicator equal to one if the mother was married at the time of the birth and zero otherwise. In addition, we created mutually exclusive but all inclusive race/ethnicity indicators for the mother . Moreover, we created mutually exclusive but all inclusive indicators of the mother’s highest level of education .We created variables to control for characteristics of the delivery and the baby. We created a dichotomous indicator equal to one if the baby was born in a hospital, and equal to zero otherwise. We created a dichotomous indicator equal to one if the baby was born via a cesarean delivery, and equal to zero otherwise. We created a dichotomous indicator for the gender of the baby equal to one if the baby was male, and equal to zero otherwise . We created a dichotomous indicator equal to one if the baby was born as part of a multiple birth, and equal to zero otherwise . Finally, we created a continuous variable to reflect the birth order of the baby.We also created mutually exclusive but all inclusive indicators for the source of payment for the delivery . In addition, we created a dichotomous indicator equal to one if the mother receiving Women, Infants, and Children (WIC) benefits, and equal to zero otherwise. Finally, we created dichotomous birth month indicators to control for seasonality of birth.We used logistic regressions to estimate the determinants of low birth weight babies. Holding all other determinants of birth weight constant, we find cigarette use during pregnancy to have a positive and significant effect on all three low birth weight outcomes. The marginal effects found in With respect to the other results, the mother’s age is found to have a positive and significant effect on all three measure of low birth weight. Mothers who are Black are significantly more likely than whites to have all three measures of low birth weight babies. Mothers who are American Indian or Alaskan Native are significantly less likely to have a low birth weight baby than are Whites. Mothers who are Asian or Pacific Islanders are less likely to have an extremely low birth weight baby, but, more likely to have a low birth weight baby than are Whites. Hispanic mothers are less likely to have a very low birth weight and low birth weight baby than Whites. Mothers who are married are significantly less likely to have all three measures of low birth weight babies. Mothers who are high school graduates or have attended some college are more likely to have an extremely low birth weight baby, but, less likely to have a low birth weight baby than mothers who did not complete high school. Mothers who completed college or have a graduate degree are significantly less likely to have all three measures of low birth weight babies than mothers who did not complete high school. Birth order, pounds gained during pregnancy, higher pre-pregnancy weight, participation in WIC, and having a male baby are found to have a significant negative effect on all three measure of birth weight. Mother’s height is found to be negatively related to the probability of having a low birth weight baby, but positively related to having a very low birth weight or extremely low birth weight baby. Having a cesarean delivery or being part of a multiple birth increases the likelihood of all three low birth weight measures. The use of Medicaid to pay for the delivery increases the likelihood of all three low birth weight measures compared to insurance paying. Whereas, paying out of pocket increases extremely low birth weight babies, but, decreases low birth weight babies relative to paying with insurance. Using any other form of payment  increases the likelihood of all three measures of low birth weight relative to insurance paying for the delivery. Finally, mothers who deliver in hospitals are more likely to have a very low birth weight or low birth weight baby than mothers who deliver elsewhere.In The causal effect of GWLs on extra hospital costs due to low birth weight babies can be expressed as:We can therefore rewrite the equation for the causal effect of GWLs on extra hospital costs due to low birth weight babies as:Equation (4) shows that the decline in extra hospital costs due to prenatal smoking is equal to the number of women who do not smoke during pregnancy as a result of GWLs, times the reduction in risk of having a low birth weight baby due to becoming a non-smoker, times the average extra cost per low birth weight baby relative to a normal weight baby. Estimates of ps − pn come from Our projections in To summarize, we find that GWLs would reduce hospital costs of low birth-weight babies due to prenatal smoking by $60.1 to $100.2 million per year. As this would be a recurrent benefit, the total expected benefits of this averted smoking would be far larger. For example, if we assume that the number of averted low birth-weight births remains in our estimated range of 1700–2900 per year, and using the 3% discount rate that is expected to be used in federal benefit-cost analyses, our annual cost savings would amount to $1.2 billion to $2.0 billion over a 30-year time horizon.The 2009 FSPTCA (Family Smoking Prevention and Tobacco Control Act) gave the U.S. FDA authority to regulate the tobacco industry. The FDA conducted an economic impact analysis to assess the costs and benefits associated with proposed regulations as part of the rulemaking process required by the 2009 Family Smoking Prevention and Tobacco Control Act. Part of the regulation mandates graphic warning labels (GWLs) covering the top 50% of the front and back of cigarette packages. In 2011, the FDA issued regulations which required tobacco companies to add GWLs to cigarette packs. Chaloupka et al. 2015)  reviewed  revieweThis study has other limitations. This study assumes that the effect of GWLs in reducing maternal smoking during pregnancy is the same in magnitude as for the general population. This study uses estimates of the effects of GWLs on smoking prevalence among general population obtained from Huang et al. 2014)  to compu14  to coTo the extent that pregnant women would respond more to graphic warning labels than the general population and no other short or longer term costs on LBW are included in our projections, our estimated cost savings of between $60.1 million to $100.2 million would be conservative estimates of the true effects of GWL on cost savings. Finally, our estimates of the effects of maternal smoking during pregnancy on the probability of having low birth weight babies are based on 2013 birth data. It is possible that the smoking behavior of pregnant women will change in the future which could affect future probabilities of having low birth weight babies and cost savings estimates.The reductions in the number of LBW babies attributed to GWLs translate into substantial cost savings. We estimated the annual cost savings resulting from GWL lie between 60.1 million dollars and 100.2 million dollars which translates to a long term saving of between 1.2 and 2.0 billion dollars over a 30 horizon. Through decreased smoking by pregnant women, GWLs protect the health of newborns and lead to substantial cost savings for society.


The World Health Organization estimates the prevalence of preterm birth to be 5–18% across 184 countries of the world. Statistics from countries with reliable data show that preterm birth is on the rise. About a third of neonatal deaths are directly attributed to prematurity and this has hindered the achievement of Millennium Development Goal-4 target. Locally, few studies have looked at the prevalence of preterm delivery and factors associated with it. This study determined the prevalence of preterm birth and the factors associated with preterm delivery at Kenyatta National Hospital in Nairobi, Kenya.A cross-sectional descriptive study was conducted at the maternity unit of Kenyatta National Hospital in Nairobi, Kenya in December 2013. A total of 322 mothers who met the eligibility criteria and their babies were enrolled into the study. Mothers were interviewed using a standard pretested questionnaire and additional data extracted from medical records. The mothers’ nutritional status was assessed using mid-upper arm circumference measured on the left. Gestational age was assessed clinically using the Finnstrom Score.p = < 0.05) although maternal age less < 20 years appeared to be protective. Only pregnancy induced hypertension, antepartum hemorrhage and prolonged prelabor rupture of membranes remained significant after controlling for confounders. Marital status, level of education, smoking, alcohol use, antenatal clinic attendance, Human Immunodeficiency Virus status, anemia, maternal middle upper arm circumference and interpregnancy interval were not associated with preterm birth.The prevalence of preterm birth was found to be 18.3%. Maternal age, parity, previous preterm birth, multiple gestation, pregnancy induced hypertension, antepartum hemorrhage, prolonged prelabor rupture of membranes and urinary tract infections were significantly associated with preterm birth (The prevalence of preterm birth in Kenyatta National Hospital was 18.3%. Maternal age ≤ 20 years, parity > 4, twin gestation, maternal urinary tract infections, pregnancy induced hypertension, antepartum hemorrhage and prolonged prelabor rupture of membranes were significantly associated with preterm birth. The latter 3 were independent determinants of preterm birth. At-risk mothers should receive intensified antenatal care to mitigate preterm birth. Of the estimated 130 million babies born each year globally, approximately 15 million are born preterm. Prematurity is a major cause of neonatal mortality and morbidity as well as a significant contributor to long term adverse health outcomes. Prematurity is a major hindrance to the attainment of the Millennium Development Goals (MDG)-4 target given its high contribution to neonatal mortality. The survival chances of babies born preterm vary significantly depending on where they are born. The risk of neonatal death due to complications of preterm birth is at least 12 times higher for an African baby than for a European baby. Preterm birth (PTB) is a global problem with prevalence ranging between 5 and 18% across 184 countries. The highest rates of preterm birth are in Sub-Saharan Africa and Asia which account for half the world’s births, more than 60% of the world’s preterm babies and over 80% of the world’s 1.1 million neonatal deaths annually due to complications related to preterm birth. Though most countries especially the low and middle income ones lack reliable data on preterm birth, nearly all of those with reliable trend data show an increase in preterm birth rates over the past 20 years. Indeed, all but 3 out of 65 countries in the world with reliable trend show an increase in preterm birth rates in the last 20 years. Significant progress has been made in the care of premature infants but not in reducing the prevalence of preterm birth which is generally on the rise. Causes of preterm birth are unknown in over 50% of spontaneous preterm labor while mechanisms of preterm labor remain poorly understood . IdentifKenya like most developing countries lacks reliable data on the burden of preterm delivery. Kenyatta National Hospital (KNH) is the largest regional referral and handles many high risk pregnancies some of which result in preterm birth. Despite this, few published studies on the burden of preterm birth and the factors associated with it exist locally. This study aimed to determine the prevalence of preterm birth and the factors associated with PTB. The findings of the study are presented in this article.A hospital based descriptive cross-sectional study was conducted using interviewer administered questionnaire. Additional information was obtained from medical records of the mothers and babies.KNH is the largest referral hospital in Kenya and Eastern and Central Africa and also serves as a teaching hospital for the University of Nairobi and the Kenya Medical Training College. It is located in Nairobi which is the capital city of Kenya with a population of about 4 million. The hospital has a busy maternity unit registering over 10,000 deliveries annually. It also has a busy newborn unit (NBU) which offers specialised neonatal care. Being a teaching and referral hospital, KNH handles many high risk pregnancies whose outcomes often include preterm birth.The study population comprised of all mothers who had live births at Kenyatta National Hospital and their newborns. A total of 322 mothers who met the eligibility criteria were enrolled into the study. These mothers delivered a total of 331 babies 18 of which were twins.All mothers who had live births at KNH in December 2013 were identified using the birth register within 24 h of delivery. Systematic sampling was used to recruit mother-baby pairs. Mothers were traced to the postnatal wards. Informed consent was obtained from the mothers and babies admitted to the newborn unit were also traced. A standard pretested questionnaire was administered to the mothers while additional data was obtained from the mothers’ and babies’ medical records as required. The records examined for additional data included the mothers’ antenatal and admission records and the babies’ medical records for those admitted in the NBU after delivery. Information collected from the mother included maternal age, marital status, level of education, occupation, smoking and alcohol use during pregnancy, parity, date of last normal menstrual period, date of current and preceding delivery  and history of previous preterm birth. Information obtained from medical records included antenatal clinic (ANC) attendance and number of visits, Human Immune Deficiency (HIV) status, hemoglobin level, mode of delivery, onset of labor , pregnancy outcome (singleton or multiple), birthweight (to nearest 10 g), baby’s gender, prelabor rupture of membranes (PROM) for > 18 h, pregnancy induced hypertension (PIH), antepartum hemorrhage (APH), history of burning sensation during pregnancy or treatment for urinary tract infection (UTI). Anemia was defined as hemoglobin level of < 10 g/dl. PIH was defined clinically as a blood pressure of > 140/90 mmHg after 20 weeks of gestation with or without proteinuria and/or edema as diagnosed and documented by the attending clinician. APH was defined as any vaginal bleeding in the mother after 24 weeks of gestation as documented in the records by the attending clinician. UTI was defined as a documented clinical/laboratory diagnosis of UTI any time during the pregnancy and/or a positive history of treatment of burning sensation with micturition as reported by the mother. Maternal nutritional status was assessed by measuring the left mid-upper arm circumference (MUAC) using non-stretchable World Food Program MUAC tapes used for screening pregnant mothers. A low MUAC was defined as a measurement of less than 24 cm. Gestational age was calculated using a standard obstetric wheel based on menstrual dates and confirmed within 24 h of birth by clinical assessment using the Finnstrom Score. This method was developed by Finnstrom et al. in 1977. Seven (7) physical parameters which are scalp hair, skin opacity, length of fingernails, breast size, nipple formation, ear cartilage and plantar skin creases were used. This tool is not only easy to use but is also sensitive with an accuracy of +/− 2 weeks when administered within 24 h of birth [Data was entered into Microsoft Access database, cleaned and stored in a password protected external storage device. Data was analyzed using Stata 11.0. Mean, median, frequencies and percentages were reported to describe the variables and inferential statistics were used to establish associations between prematurity and the various risk factors using a chi-square analysis. Multivariate logistic regression was used to determine the factors independently associated with preterm birth.The mean maternal age was 26 ± 5 years with majority (89%) being aged 20 years and above. Most of the mothers (83%) were married. About 85% of the mothers had attained post-primary level of education. About 97% of the enrolled mothers had singleton deliveries while 82% delivered at term. Fifty three percent of all the babies in the study were males. The mean birth weight of term babies was 3059 ± 538 g. The median weight of preterm babies was 2110 g (IQR 1650–2400). The mean gestation was 39 ± 3 weeks and 33 ± 3 weeks for term and preterm babies respectively. Of the preterm births, 62% were late preterms (34–36 weeks), 19% were moderate preterms (32-33 weeks), 16% were severe preterm (28–31 weeks) and 3% were extreme preterm (< 28 weeks).The prevalence of preterm birth among live births was 18.3%  of 14.1–22.5%).p = 0.034). The proportions of mothers aged 35 years and above were similar in the two groups. There was no difference between the preterm and term groups in terms of marital status (p = 0.133), maternal level of education (p = 0.330), occupation (p = 0.823), smoking (p = 0.728), antenatal alcohol use (p = 0.501) and maternal MUAC (p = 0.651). None of the socio-demographic factors was significantly associated with preterm birth except maternal age less than 20 years which was negatively associated with preterm delivery (OR 0.236). Table About 80% of mothers in the term and 90% in the preterm group were aged 20–34 years. Thirteen percent of mothers aged less than 20 years delivered at term compared to 3.4% who had preterm delivery and this was significant . About 35% of mothers who delivered before term had a history of previous preterm delivery compared to 16% of those who delivered at term and this was significant (p = 0.010). Approximately 6% of mothers in the preterm group and 11% in the term group had an interpregnancy interval of < 24 months but this was not statistically significant (p = 0.357)). The relationship between previous pregnancy characteristics and preterm birth is summarized in Table Most mothers had a parity of less than four. Women with a parity of 4 or more were nearly 5 times more likely to deliver preterm compared to those whose parity was < 4 (p = 0.621). Mothers who had not had any antenatal care were one and a half times more likely to deliver preterm (OR 1.503). About 29% of mothers in term and 37% in preterm group had less than 3 antenatal visits but this was statistically insignificant (p = 0.256). Approximately 13% of preterm mothers and 12% of term mothers were HIV positive. There was no association between HIV status and preterm delivery (p = 0.834). The proportion of women who had anemia during pregnancy was the same for the two groups (p = 0886). Table The proportion of mothers who did not attend ANC in the term and preterm groups was 2.3 and 3.4% respectively and this was not significant (p = 0.049). About 28 and 36% of mothers in the term and preterm group respectively had induced labor or medically indicated C/S. However, there was no association between onset of labour and preterm birth (p = 0.231). The proportion of twin pregnancy among women who delivered at term and preterm was 2 and 7% respectively and this was significant (p = 0.040). Twin pregnancy conferred nearly a 4-fold increase in the risk of preterm birth (OR 3.753). Table Approximately 40% of preterm deliveries were via Caesarean section (C/S) compared to 26% among those who delivered vaginally. Women who delivered via Caesarean section were nearly two times (OR 1.832) more likely to deliver preterm than those who delivered vaginally. Delivery via Caesarean section had significant but marginal association with preterm birth (p < 0.05).About 32 and 8% of mothers in the preterm and term groups had PIH while 13 and 5% of mothers in the two groups had APH respectively. Mothers with PIH and those with APH had a 5-fold and 3-fold increase in risk of preterm birth (OR 5.203 and 2.790). Approximately 27% of mothers who had preterm delivery and 8% of those who delivered at term had a history of PROM for more than 18 h while 47.5% of mothers in preterm group and 32% of those in the term group respectively reported having had UTI or burning sensation with micturition during pregnancy. As shown in Table Maternal age, parity, previous preterm birth, twin gestation, UTI, PIH, prolonged PROM and APH were found to be significantly associated with preterm birth. However, on multivariate logistic regression only PIH, APH and prolonged PROM remained significant. The risk of preterm birth increased 8-fold with PIH (OR 7.805), 5-fold if the mother had prolonged PROM (OR 5.319) and 4-fold with APH OR 4.264) after controlling for confounders. The multivariate logistic regression is summarized in Table 4 after cMost developing countries lack reliable data on the prevalence of preterm birth , 4. Thisp value =0.034, OR = 0.236), this is both unexpected and different from other studies [The current study did not show any association between the maternal socio-demographic factors except maternal age < 20 years that appeared to be marginally protective. Though our findings showed a marginal negative association between maternal age < 20 years and PTB ( studies –14. Alth studies , 14. Tho studies . The cur studies , 14. Hig studies , 17. It Delivery via Caesarean Section was significantly associated with preterm birth but onset of labor was not. This was similar to the finding of Olugbenga et al. . OperatiTwin gestation was significantly associated with preterm birth in this study. This is similar to the findings of J Etuk and others . MutipleANC attendance as well as number of antenatal visits was not associated with preterm birth in our study. This is different from what Feresu A et al. had reported in Zimbabwe . This maResults of the current study demonstrated that after controlling for confounders, prolonged PROM, PIH and APH remained significantly associated with preterm birth. These findings are similar to those reported in other studies. PROM has been associated with chorioamnionitis which may be subclinical and chlamydial vaginitis. Microorganisms that cause bacterial vaginosis can easily ascend in prolonged PROM and cause intrauterine infections. It is postulated that subclinical chorioamnionitis and other unidentified infections may trigger the release of inflammatory mediators such as interleukin 1 leading to release of prostaglandins from the uterine decidua that ultimately induce preterm labor. PIH which is one of the major obstetric complications was significantly associated with PTB in the current study. Though the pathophysiology of this condition remains poorly understood, uteroplacental ischemia is a plausible explanation for the poor pregnancy outcomes associated with PIH including preterm delivery and low birthweight. Furthermore, PIH is a common reason for indicated preterm deliveries and this may explain its association with PTB even though this may not be causal in nature. Like PIH, APH is also a major contributor to indicated preterm deliveries whether vaginally or operatively without necessarily having a temporal relationship with PTB , 15. ThiOnly mothers who had live births were interviewed and their babies assessed for gestational age. The study did not address factors associated with preterm stillbirth. UTI in pregnancy was partly based on mothers’ self report of symptoms and not on laboratory confirmation and therefore over-reporting was likely. Clinical assessment of gestation using the Finnstrom method that solely relied on physical characteristics is also a limitation of this study. Use of secondary data for some variables is another limitation of our study.Preterm birth among women delivering at KNH in Nairobi Kenya is a significant problem. Prolonged PROM, PIH and APH are independent determinants of preterm birth. Better management of these obstetric complications and research to elucidate the mechanisms by which they cause preterm birth, offers a practical approach of reducing the high preterm birth rates.