Low birth weight  is a strong predictor of infant mortality. Yet low birth weight, in isolation, is uninformative since it is comprised of two intertwined components: preterm delivery and reduced fetal growth. Through nonparametric logistic regression models, we examine the effects of gestational age, fetal growth, and maternal smoking on neonatal mortality.We derived data on over 10 million singleton live births delivered at ≥ 24 weeks from the 1998–2000 U.S. natality data files. Nonparametric multivariable logistic regression based on generalized additive models was used to examine neonatal mortality (deaths within the first 28 days) in relation to fetal growth , gestational age, and number of cigarettes smoked per day. All analyses were further adjusted for the confounding effects due to maternal age and gravidity.The relationship between standardized birth weight and neonatal mortality is nonlinear; mortality is high at low z-score birth weights, drops precipitously with increasing z-score birth weight, and begins to flatten for heavier infants. Gestational age is also strongly associated with mortality, with patterns similar to those of z-score birth weight. Although the direct effect of smoking on neonatal mortality is weak, its effects  appear to be largely mediated through reduced fetal growth and, to a lesser extent, through shortened gestation. In fact, the association between smoking and reduced fetal growth gets stronger as pregnancies approach term.Our study provides important insights regarding the combined effects of fetal growth, gestational age, and smoking on neonatal mortality. The findings suggest that the effect of maternal smoking on neonatal mortality is largely mediated through reduced fetal growth. This isDisentangling the intricate pathways of gestational age and fetal growth to neonatal mortality gets even more complicated by the consideration of a third factor – maternal smoking during pregnancy. Smoking has been clearly associated with poor reproductive outcomes, including increased risk of preterm birth, stillbirth, and a range of other outcomes -6. Receni.e., z-score birth weight), gestational age, and smoking during pregnancy. We applied nonparametric logistic regression based on generalized additive models to examine neonatal mortality in relation to 3 factors.To better understand the relationship among these indices of "fetal wellbeing", we examined neonatal mortality in relation to standardized birth weight , assembled by the National Center for Health Statistics of the Centers for Disease Control and Prevention .Information on smoking during pregnancy was available in two forms on the vital statistics data: one as an indicator variable (yes or no), and the other as a continuous variable denoting the number of cigarettes smoked per day during pregnancy. Both of these smoking measures were based on maternal self-report. Information on smoking patterns across different trimesters in pregnancy was not available on the vital records.Fetal growth was defined as birth weight-for-gestational age, and was expressed as gestational age-specific birth weight z-score. This z-score construct is interpreted as units of standard deviations from the population-specific mean birth weight at each gestational age. The z-score or standardized birth weight follows a Gaussian distribution with mean 0 and variance 1.e.g., infant delivered at 26 weeks with a birth weight of 4,000 g) on neonatal mortality.In addition to the full analysis, we also examined in a sub-analysis the impact of implausible birth weight/gestational age combinations on overall results. These implausible birth weight/gestational ages were identified if infants' birth weights were outside the gestational age-specific birth weight cutoffs . This waThere were 11,677,103 singleton live births from which we excluded infants with missing birth weight or gestational age , and birth weight <500 g or gestational age <24 weeks n = 28,732). Since smoking data was not reported on vital statistics in California, Indiana, New York state, and South Dakota [,732. Sini.e., continuity of the dose-response function and its low-order derivatives [We examined the distributions of z-score birth weight, gestational age, and number of cigarettes smoked per day, and compared these distributions between the two groups of neonatal mortality. Neonatal mortality was then modeled using nonparametric logistic regression based on generalized additive models . GAM is ivatives . When coivatives  could bei.e., number of pregnancies). We examined the associations between neonatal mortality and each of the 3 factors z-score birth weight, gestational age, and number of cigarettes smoked per day separately. We then fit a full model for mortality after forcing all 3 predictors (in addition to the confounders) as described in the Appendix [see i.e., comparing the residual deviances from a full model to a model without the predictor). Under the large sample assumption, the deviance has an approximate chi-square distribution, with degrees-of-freedom for the test being the difference in the degrees of freedom between the nested models being compared. We also examined the distribution of partial residuals [All regression models were adjusted for the confounding effects due to maternal age and gravidity , none provided any additional insights that were different from a model that contained no interaction terms. Therefore, we did not consider assessing two-way interactions in the analysis.gam function based on the it loess scatterplot smoother [All statistical analyses were performed in S-Plus  version 6.2 on the UNIX . Nonparametric logistic regression models were fit using the smoother , using tThe overall neonatal mortality rate was 2.4 per 1,000 live births. The distribution of z-score birth weight among infants that died during the neonatal period was shifted more towards lower standardized birth weights than among those that survived the neonatal period .We first separately examined the effect of each of the 3 covariates standardized birth weight, gestational age, and number of cigarettes smoked per day, on neonatal mortality. This was done by fitting nonparametric logistic regression models (GAM). The univariable GAM strongly suggests that the unadjusted association between standardized z-score birth weight and neonatal mortality is nonlinear (not shown). The association between gestational age and neonatal mortality was also nonlinear, whereas the association between number of cigarettes smoked per day mortality was virtually flat. The adjusted smooth curves for these 3 covariates, along with their corresponding 95% point-wise confidence bands are displayed in Figure Since smoking was weakly associated with neonatal mortality, we examined if the effect of smoking on mortality was mediated through either standardized birth weight or gestational age (or both). We therefore modeled neonatal mortality in relation to these 2 covariates (and adjusted for confounders) within broad categories of smokers and nonsmokers Fig . CompareThe logistic regression models discussed thus far are based on the implicit assumption that the combined effects of standardized birth weight and gestational age are multiplicative on a logistic scale. We examined the sensitivity of this assumption by modelling neonatal mortality by allowing an interaction term between these two factors based on nonparametric smooth fit. The joint effect of standardized birth weight and gestational age on neonatal mortality reveals that both reduced fetal growth and early delivery result in increasing mortality risk, with the mortality plane progressively diminishing with increasing standardized birth weight and gestational age Fig .For decades, several researchers have focused on trying to understand the complex biological relationship among pregnancy duration, infant size, and neonatal mortality. Not only are gestational age and birth weight highly correlated, but both are powerful predictors of neonatal mortality -16. The The inverted "J"-shaped relationship between birth weight and mortality essentially holds for analyses relating to gestational age and mortality. While birth weight is considered a marker for fetal size, gestational age is thought of as an indicator of fetal maturity. Almost 3 decades ago, Susser and colleagues  proposedOn these similar lines, Herman and Hastie  examinedIt is widely acknowledged that smoking mothers give birth to infants that are lighter compared with those born to nonsmoking mothers. This reduction in birth weight is thought mainly to result in fetal growth restriction, as well as to shortened gestation ,20. AlthOur study has some limitations. First, errors in the estimation of gestational age ,26 are lApplication of generalized additive regression models to examine neonatal mortality appears useful towards understanding the complex biological relationship amongst the predictors. However, we make no claim that GAMs serve as adjuncts to other modeling approaches; on the contrary, we believe that GAMs can provide the first step toward modeling complex exposure-disease relationships.Our study provides important insights about the combined effects of gestational age, fetal growth, and smoking during pregnancy on neonatal mortality. Both standardized z-score birth weight and preterm delivery are strongly associated with neonatal mortality, and the effect of maternal smoking appears largely mediated largely through reduced fetal growth and, to a smaller extent, through shortened gestation.The author(s) declare that there are no competing interests.CVA and RWP conceived the idea for the study. CVA assembled the data and performed all statistical analyses. CVA drafted the manuscript with essential contributions from RWP. Both authors critically reviewed the manuscript, edited it for content, and revised it to the final form.Both authors have read and approve the final manuscript.The pre-publication history for this paper can be accessed here:Description of generalized additive models.Click here for file


Several studies have linked low birth weight to adverse levels of cardiovascular risk factors and related diseases. However, information is sparse at a community level in the U.S. general population regarding the effects of low birth weight on the longitudinal trends in cardiovascular risk factor variables measured concurrently from childhood to adolescence.th percentile; n = 123) and control  groups.Longitudinal analysis was performed retrospectively on data collected from the Bogalusa Heart Study cohort  followed from childhood to adolescence by repeated surveys between 1973 and 1996. Subjects were categorized into low birth weight (below the race-specific 10Low birth weight group vs control group had lower mean HDL cholesterol (p = 0.05) and higher LDL cholesterol (p = 0.05) during childhood (ages 4–11 years); higher glucose (p = 0.02) during adolescence. Yearly rates of change from childhood to adolescence in systolic blood pressure (p = 0.02), LDL cholesterol (p = 0.05), and glucose (p = 0.07) were faster, and body mass index (p = 0.03) slower among the low birth weight group. In a multivariate analysis, low birth weight was related independently and adversely to longitudinal trends in systolic blood pressure (p = 0.004), triglycerides (p = 0.03), and glucose (p = 0.07), regardless of race or gender. These adverse associations became amplified with age.Low birth weight is characterized by adverse developmental trends in metabolic and hemodynamic variables during childhood and adolescence; and thus, it may be an early risk factor in this regard. The growth of a fetus in an undernourished intrauterine environment is considered to result in adaptive fetal programming or metabolic imprinting with pathophysiologic consequences later in life -4. It isSeveral studies including our own have examined the association between low birth weight and selected cardiovascular risk factor variables in childhood and adolescence -27. HoweBetween 1973 and 1996, 7 cross-sectional surveys of children and adolescents were conducted in the community  of Bogalusa, LA. This panel design, based on repeated cross-sectional examinations performed every 3 to 4 years, resulted in serial observations required for the longitudinal analysis. For the present report, two sets of data were merged as described previously : 1) singth percentile  were categorized as low birth weight group; those (n = 296) in the upper normal range of 50–75th percentile  as control group. Birth weights above the 75th percentile were not included in the control group because of the u-shaped associations between birth weight and risk factors or disease [Low birth weight and control groups were selected from the eligible cohort, according to birth weight percentile cut points . Subject disease . Race-sp disease .Identical protocols were used by trained examiners across all surveys . SubjectHeight and weight were measured 2 times; subscapular skinfold thickness 3 times. Body mass index (BMI) calculated as weight in kg divided by the square of the height in meters was used as a measure of overall adiposity; subscapular skinfold for truncal fatness. The reproducibility in terms of intraclass (intra-observer) correlation coefficient was greater than 0.99 for weight and height, and greater than 0.97 for subscapular skinfold.Blood pressure levels were measured in 6 replicates by 2 randomly assigned nurses on the right arm of subjects in a relaxed, sitting position. Systolic and diastolic blood pressures were recorded at the first, fourth, and fifth Korotkoff phases using mercury sphygmomanometer. For this analysis fourth phase was used for diastolic blood pressure because in our experience the fourth phase is more reliably measured in children and more predictive of adult hypertension .From 1973 to 1986 cholesterol and triglyceride levels in serum were measured using chemical procedures on Technicon Autoanalyzer II . Since then these measurements were done using enzymatic procedures on Abbott VP instrument . Serum lipoprotein cholesterols were analyzed by a combination of heparin-calcium precipitation and agar-agarose gel electrophoresis procedures . Both chPlasma immunoreactive insulin levels were measured by a commercial radioimmunoassay kit . Plasma glucose was measured by a glucose oxidase method either using a Beckman glucose analyzer  or as part of a multichemistry (SMA20) profile. The intraclass correlation coefficient between blind duplicate values ranged from 0.94 to 0.98 for insulin and 0.86 to 0.98 for glucose. An index of insulin resistance was calculated according to the homeostasis assessment model formula : HOMA-IR2, race and gender and their interaction with birth weight (low vs control). A backward stepwise method was used to remove nonsignificant terms.For test of significance glucose and insulin were logarithmically transformed to approach normality. The average of multiple measurements for subjects within age groups 4 to 11 and 12 to 18 years corresponding to childhood and adolescence periods was used to calculate mean levels of risk variables by birth weight status and age groups. Mean levels of risk variables within each age group were compared between low birth weight and control group by a general linear model, adjusting for age, race, and gender. The longitudinal rates of change in risk variables was assessed by the generalized estimation equation (GEE) method  with ageMean levels of cardiovascular risk variables during childhood ages 4–11 years) and adolescence (ages 12–18 years) periods are shown in table 1 years aLongitudinal rates of change in cardiovascular risk variables from childhood to adolescence, adjusted for race and gender, are presented in table In a multivariate analysis, low birth weight was retained as an independent predictor variable for adverse longitudinal trends in systolic blood pressure, triglycerides, and glucose  from childhood to adolescence, regardless of race or gender table . FurtherInformation is sparse at a community level in the U.S. general population regarding the effects of low birth weight on the longitudinal trends in C-V risk factor variables measured serially and concurrently from childhood to adolescence. The present community-based study demonstrates the adverse effects of low birth weight on the longitudinal  trends in systolic blood pressure, triglycerides, and glucose during childhood and adolescence, regardless of race or gender. These observations are in accord with the emerging evidence supporting the concept of intrauterine imprinting and its pathophysiologic consequences enunciated by the fetal origin or thrifty phenotype hypothesis .Many, but not all, previous studies in children and adolescents have found adverse associations between birth weight and levels of cardiovascular risk factor variables -27. In tAlthough observational studies like the present one can not establish causality, several putative mechanisms link low birth weight to adverse trends in risk factor variables. It has been suggested that insulin resistance may be one mechanism by which intrauterine events may program disease risk . UndernuThis study has certain limitations. The lack of information on the duration of gestation precluded us from adjusting the birth weight for gestational age, a potential confounder. However, earlier studies have found that adverse effects of low birth weight on cardiovascular risk factor variables were independent of gestation period ,17,49. FLow birth is characterized by adverse developmental trends in metabolic and hemodynamic variables during childhood and adolescence, especially as the children get older. These observations in conjunction with earlier findings support the view that low birth weight, albeit a crude marker of prenatal growth and physiological environment, is a potential early risk factor for the emergence of metabolic and hemodynamic disorders and related diseases ,50.BMI, body mass index; LDL, low-density lipoprotein; HDL, high-density lipoproteinThe author(s) declare that they have no competing interests.MGF participated in study design, data analysis and manuscript preparation. SRS and GSB contributed to study concept and design, data collection, acquisition of funding and manuscript preparation. JX was involved in measurements of laboratory variables. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


One of every 6 United Status birth certificates contains no information on fathers. There might be important differences in the pregnancy outcomes between mothers with versus those without partner information. The object of this study was to assess whether and to what extent outcomes in pregnant women who did not have partner information differ from those who had.We carried out a population-based retrospective cohort study based on the registry data in the United States for the period of 1995–1997, which was a matched multiple birth file . We divided the study subjects into three groups according to the availability of partner information: available, partly missing, and totally missing. We compared the distribution of maternal characteristics, maternal morbidity, labor and delivery complications, obstetric interventions, preterm birth, fetal growth restriction, low birth weight, congenital anomalies, fetal death, neonatal death, post-neonatal death, and neonatal morbidity among three study groups.There were 304466 twins included in our study. Mothers whose partner's information was partly missing and  totally missing tended to be younger, of black race, unmarried, with less education, smoking cigarette during pregnancy, and with inadequate prenatal care. The rates of preterm birth, fetal growth restriction, low birth weight, Apgar score <7, fetal mortality, neonatal mortality, and post-neonatal mortality were significantly increased in mothers whose partner's information was partly or  totally missing.Mothers whose partner's information was partly and  totally missing are at higher risk of adverse pregnant outcomes, and clinicians and public health workers should be alerted to this important social factor. Pregnancy outcomes are not only important measures of health status of the mothers and infants, but are important measures of socioeconomic development in a society. For example, infant mortality has been considered the single most comprehensive measure of the health and wealth in a society ,2. Both Epidemiologic studies based on a data with missing information on exposure, outcomes, and potential confounders can bias the study results, unless the missing occurred randomly . PreviouWe used a large twin registry data in the United States to examine this issue. This data has been used in several peer-reviewed studies -14. The We used the matched multiple birth file created by the National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention . The mulThere were two variables for the partners in the data: partner's age and race. The eligible study subjects were divided into three groups according to the availability of the two variables of the partners: both available (group 1), one missing (group 2), and both missing (group 3).nd stage <3 hours), prolonged labor (2nd stage >20 hours), dysfunctional labor, breech, malpresentation, cephalopelvic disproportion, cord prolapse, anesthetic complications, and fetal distress), and obstetric interventions  among the three study groups. Finally we compared the rates of fetal and neonatal mortality and morbidity among the three study groups. We used the Chi-square test to test the difference of all rates among the three study groups, used the normal approximate method to calculate the 95% confidence interval of the rates of maternal medical complications, labor and delivery complications, obstetric interventions, and the fetal and neonatal mortality and morbidity. We calculated the relative risk in group 2 and group 3 compared with group 1 for all the outcomes mentioned above. Fetal death was defined as stillbirth weighing 500 grams or more, or if weight was unknown, 20 completed gestation weeks or more. Neonatal death was defined as live-born infant died at 0–27 days of age, and post-neonatal death was defined as those died at 28–364 days of age. Preterm birth (PTB) was defined as gestational age < 37 weeks. Fetal growth restriction (FGR) was defined as less than 10th percentile of birth weight-for-gestational-age z score. The birth weight-for-gestational-age z score was calculated using the following formula:We first described the distribution of the maternal characteristics  of the three study groups. The prenatal care service was defined as adequate, intermediate, and inadequate according to the time of prenatal care visit initiation and the number of prenatal visit using the method described by Kessner et al . If the Z = (observed birth weight - mean of birth weight)/SDWhere mean and SD was based on all infants in the database, stratified by gender and gestational week. Low birth weight (LBW) was defined as birth weight <2500 grams. Low Apgar score was defined as five minute Apgar score < 7. Anemia was defined as hemoglobin <13. Other fetal and infant outcomes examined included birth injury, hyaline membrance disease, meconium aspiration syndrome, assisted ventilation (<30 minutes and > = 30 minutes), seizures, central nervous system anomalies, circulatory / respiratory anomalies, digestive system anomalies, urogenital system anomalies, musculoskeletal / integumental anomalies, and chromosomal anomalies.There were 304466 twins (152233 twin pairs) in the database. Of which, father's age and race were recorded in 259302 twins , father's age or race was missing in 6036 twins , and both father's age and race were missing in 39128 twins .Table Table Table Our large population based study found that the risks of fetal and infant mortality, low birth weight, preterm birth, fetal growth restriction, Apgar score <7, and the need for mechanical ventilation were increased in infants born to mothers with missing information on partner's age or race, especially when both variables of the partner were missing. The women reported no information (or reported only part of the information) on partners appear to have higher prevalence / incidence of most of the maternal morbidity and obstetric complications than in mothers with available information on partners. The poorer pregnancy outcomes observed in women with partner's information been partly and  totally missing than in women with available information on partners were due largely to known important socioeconomic factors for adverse pregnancy outcomes. Many of these women were teenagers, black race, unmarried, with low education, high frequency of cigarette smoking, and inadequate prenatal care services. Teenagers , black rOur findings that the rates of FGR, LBW, Apgar score <7, hyaline membrane disease, and assisted ventilation were significantly higher in the group with paternal information totally missing than the group of only partly missing suggest that the totally missing group is a particularly high risk group, whereas in the partly missing group, the missing may have occurred in randomly.Exceptions did occur, however. For example, the occurrences of several maternal medical conditions, such as cardiac disorders, diabetes, and RH sensitization, were actually lower in women with no available information on partners (group 2 and 3) than women with available information on partners (group 1). This may, in part, be due to the younger maternal age in groups 2 and 3 than in group 1. The risk of cardiac disorders and diabetes increases rapidly with advancing age ,22. YounOur study examined the difference of adverse pregnancy outcomes among three study groups in twins only. It is biologically plausible to apply the study findings to singletons and higher order of multiple pregnancies as well, although the magnitude of the differences may be smaller in singletons and larger in higher order of multiple pregnancies than in twins.Since in the database, there was no indication why a particular variable was not recorded, we can only speculate the reason of missing partner's information. Corresponding variables  for the mothers, including those mothers with missing information on partners, were completely recorded. These women may have no relationship or only remote relationship with their partners, as suggested by the extraordinarily high unmarried rates (61% for women missing one variable on their partners and 96% for women missing both variables on their partners). As a result, they may have difficulty or for unknown reasons they may be reluctant to provides partner's information. The paternal information missing may be a comprehensive measure and may be related with age, education, socioeconomic status, race, religion background, or even the reporting quality in different place. Our study only described the association between the paternal information missing and the adverse pregnancy outcomes. Exploration of the reasons of missing partner information and its relationship with adverse pregnancy outcomes require in-depth analysis of data with relevant information.Women with no available information (or partly) on partners appear to have higher risks of developing adverse pregnancy outcomes. For this reason, extra attention for these women and their offspring by health care providers and public health workers is needed.The authors declare that they have no competing interests.Hongzhuan Tan carried out the data analysis and drafted the manuscript. Shi Wu Wen designed the study and helped in results interpretation. Mark Walker participated in the sequence alignment and participated in the results interpretation. Kitaw Demissie participated in the study design and results interpretation.The pre-publication history for this paper can be accessed here:


To investigate whether low birth weight increases the risk of myocardial infarction later in life in women.Nationwide population-based case-control study. Patients and controls: 152 patients with a first myocardial infarction before the age of 50 years in the Netherlands. 568 control women who had not had a myocardial infarction stratified for age, calendar year of the index event, and area of residence.th percentile in controls) compared to higher than 3000 gram was 1.7 (95%CI 1.1–2.7), while the odds ratio for myocardial infarction for children with a low birth weight (< 2000 g) compared to a birth weight ≥ 2000 g was 2.4 (95%CI 1.0 – 5.8). Both figures did not change after adjustment for putative confounders .Birth weight in the patient group was significantly lower than in control women . The odds ratio for myocardial infarction, associated with a birth weight lower than 3000 gram (20Low birth weight is associated with an increased risk of myocardial infarction before age of 50 in Dutch women.


Fetal growth restriction is associated with significantly increased risks of neonatal death and morbidity and with susceptibility to hypertension, cardiovascular disease and NIDDM later in life. Human birth weight has a substantial genetic component, with at least a quarter of the variation attributable to additive genetic effects.One hundred twenty-five subjects (83 control and 42 case) were selected using stringent inclusion/exclusion criteria. DNA sequencing was used to identify 26 single nucleotide polymorphisms in the pituitary growth hormone gene (GH1) at which all subjects were genotyped. Association with fetal growth restriction was tested by logistic regression for all sites with minor allele frequencies greater than 5%.Logistic regression identified significant association with fetal growth restriction of C alleles at sites -1 and +3 (relative to the start of transcription) that are in complete linkage disequilibrium. These alleles are present at higher frequency (6% vs. 0.4%) in fetal growth restricted subjects and are associated with an average reduction in birth weight of 152 g in normal birth weight and 97 g in low birth weight subjects.There is suggestive association between fetal growth restriction and the presence of C alleles at sites -1 and +3 of the pituitary growth hormone gene. Fetal growth restriction (FGR) is a major risk factor for illness in the perinatal period and throughout life, with the smallest 7.5 percent of infants accounting for two-thirds of infant deaths . Term, lIt is difficult to distinguish the genetic and environmental components of human birth weight variation, but recent studies support a major genetic component to birth weight variation. Clausson et al.'s  study ofThe five genes of the human growth hormone locus reside within about 45 kb on chromosome 17 . PituitaHere we use DNA sequencing to identify and to determine the frequencies of both 12 newly-identified single nucleotide polymorphisms (SNPs) in the promoter and coding region of the GH1 gene and 15 previously reported SNPs ,18. Usinth percentile of size for gestational age [th percentile of female and lowest 6.5 percentile of male deliveries [DNA was extracted from placental tissue from 125 live births  at Baystate Medical Center  in a case-control study of the genetic predisposition to fetal growth restriction. All subjects were Caucasian, both Hispanic and non-Hispanic. Classification of newborns as fetal growth restricted  followed the definition of the American College of Obstetricians and Gynecologists as those newborns below the 10onal age . Our cutliveries . StringeThe region from -624  to +1,726 (197 nucleotides after the termination codon) of GH1 was amplified in two overlapping fragments: -624 to +541  and +450 to +1,726 . Approximately 50 ng of DNA was used as a template in a polymerase chain reaction with 30 cycles of 95°C (1 minute), 62°C (1 minute), and 72°C (2 minutes 30 seconds). PCR products were purified from agarose using a QIAquick PCR Purification kit (Qiagen) and sequenced directly with BigDye v2.0 chemistry (Applied Biosystems) and run on either an ABI Prism 377 or 3100 automated DNA sequencer. PCR products were sequenced with the PCR primers and additional internal primers: 5' AAGCACAGCCAATAGATTG 3', -459 to -441; 5' GCACAAGCCCGTCAGTGGCC 3', -108 to -89; 5' GGATTTTAGGGGCGCTTACC 3', +71 to +90; 5' CATCTCCCTGCTGCTCATC 3', +931 to+949; 5' GCGCTTGGGYACTGTTCCCT 3', +1280 to +1299.Sequence traces were aligned and assembled into contigs by the program Polyphred . ContigsThe five genes of the human growth hormone locus exhibit high sequence similarity, and the paralogous regions corresponding to the portion of GH1 sequenced in this study  were multiply aligned. Nucleotide positions , as defined in the methods. Of the invariant sites, 5 are polymorphic in GH1, while 21 of the variant sites are polymorphic. A comparison of the proportion of polymorphic sites at invariant and variant sites by Fisher's Exact Test is highly significant (P <<0.001). This result indicates that there is a strong bias for polymorphisms in GH1 to occur at the minority of sites that exhibit sequence divergence among the paralogous genes. The high correspondence between the sequence of minor alleles in GH1 and nucleotides present in paralogs of GH1 supports previous assertions that the unusually high polymorphism of the GH1 gene is driven by gene conversion ,18.A proportion of this bias may be explained by selective constraint, in that sites that are polymorphic within GH1 may be under less selective constraint and thus more free to exhibit sequence divergence among paralogs. However, to entirely explain the bias towards polymorphism at sites of divergence, one must assume that about 1,804 (91%) of the invariant sites are selectively constrained and not free to vary. Given that a substantial proportion  of the sequence surveyed in this study is composed of introns, this assumption seems unreasonable.Logistic regression Table  was perfAlthough the A/C polymorphism at site -1 was not significant in a reduced model, we decided to investigate this site for three reasons. First, the C allele at site -1 is in complete linkage disequilibrium with C at site +3. Second, both of these sites are located at the start of transcription, making them good candidates for affecting the level of transcription of GH1. Third, the only paralog that shares C at these sites is CS-5, a pseudogene, consistent with the possibility that C at sites -1 and +3 is disadvantageous. The C allele at both sites exhibits a much higher frequency in low birth weight (6%) versus normal birth weight 0.4%) subjects. Restricting examination only within the normal or low birth weight subjects, the AC genotype is associated with an average reduction of birth weight of 152 g and 97 g in normal and low birth weight subjects, respectively. However, this difference does not achieve significant in an ANOVA on the A/C polymorphism and gestational age  did among British army recruits (0.4% vs. 0.3%) but that among the low birth weight subjects the frequency of the C allele is substantially higher (6%). Comparing all the other allele frequencies . There are two possible explanations for this observation. First, site -1 could be a hotspot for nucleotide mutation, with transversions from A to C/T occurring often. Second, GH1 may be the recipient of gene conversion events from more than one paralog within the GH locus. Among the four other genes of the GH locus, all three alleles observed at site -1 occur Table . Given tIt must be pointed out that the common wisdom is that GH1 plays no role in regulating fetal growth because the GH receptor is expressed fairly late in gestation and because anencephalic infants or those born without a pituitary achieve nearly normal length . ImportaIn a stringently selected set of subjects, C alleles at sites -1 and +3 relative to the start of transcription of GH1 have a higher frequency (0.4% vs. 6%) in fetal growth restricted newborns. These two alleles are in complete linkage disequilibrium and their presence is associated with a reduction in birth weight of 152 g in term, normal birth weight subjects and 97 g in term, low birth weight  subjects. In combination with environmental, behavioural and other genetic factors, these alleles may contribute to fetal growth restriction.The author(s) declare that they have no competing interests.RMA conceived the project and directed its design and execution. CC and RV performed the molecular genetic work and participated in preliminary analyses. TKB performed the subject selection.The pre-publication history for this paper can be accessed here:


Some currently available birth weight for gestational age standards are customized but others are not. We carried out a study to provide empirical justification for customizing such standards by sex and for whites and blacks in the United States.We studied all male and female singleton live births and stillbirths  in the United States in 1997 and 1998. White and black singleton live births and stillbirths were also examined. Qualitative congruence between gestational age-specific growth restriction and perinatal mortality rates was used as the criterion for identifying the preferred standard.The fetuses at risk approach showed that males had higher perinatal mortality rates at all gestational ages compared with females. Gestational age-specific growth restriction rates based on a sex-specific standard were qualitatively consistent with gestational age-specific perinatal mortality rates among males and females. However, growth restriction patterns among males and females based on a unisex standard could not be reconciled with perinatal mortality patterns. Use of a single standard for whites and blacks resulted in gestational age-specific growth restriction rates that were qualitatively congruent with patterns of perinatal mortality, while use of separate race-specific standards led to growth restriction patterns that were incompatible with patterns of perinatal mortality.Qualitative congruence between growth restriction and perinatal mortality patterns provides an outcome-based justification for sex-specific birth weight for gestational age standards but not for the available race-specific standards for blacks and whites in the United States. Birth weight-specific perinatal mortality curves among male and female births intersect to produce a paradox: overall perinatal mortality rates and perinatal mortality rates at lower birth weights are relatively higher among male births, while at higher birth weights perinatal mortality rates are relatively higher among female births . This puIn this paper, we demonstrate the paradoxical crossover of birth weight-specific perinatal mortality curves among male and female births and show how this phenomenon is resolved using the fetuses at risk approach. We also explore issues related to fetal growth restriction among males and females using the same approach. This latter issue is particularly important from a conceptual and clinical standpoint because the current literature on birth weight for gestational age standards  is confusing. Some standards provide unisex reference values -24, seveWe used the fetuses at risk approach to contrast growth restriction and perinatal mortality rates among males and females in order to provide empirical justification for sex-specific (vs unisex) birth weight for gestational age standards. We also constructed and compared gestational age-specific growth restriction and perinatal mortality curves among whites vs blacks in order to evaluate currently available birth weight for gestational age standards (single standard vs separate standards for whites and blacks in the United States).We used data on all reported live births and stillbirths in the United States in 1997 and 1998 . Live births and infant death records for these years have been previously linked and gestational duration has been calculated based on the last menstrual period (LMP). Missing or inconsistent information on gestational age has been imputed or replaced in a small fraction (approximately 7 percent) of records by the National Center for Health Statistics . Gestational age was imputed from the month and year of the LMP when the exact LMP day was missing . LMP-basAnalyses were restricted to singleton live births and stillbirths ≥22 weeks gestational age and ≥500 g birth weight in order to eliminate potential problems arising from regional differences in birth registration. Male and females births were first contrasted in terms of their gestational age and birth weight distributions. Birth weights were categorized into 500 g intervals for this purpose . Birth weight-specific perinatal mortality rates, calculated within these birth weight categories, were computed as per convention by dividing the number of stillbirths and early neonatal (0 to 6 days) deaths in any birth weight category by the number of total births (stillbirths and live births) in that birth weight category. Similarly, gestational age-specific perinatal mortality rates among male and female births were contrasted, with rates computed by dividing perinatal deaths at any given gestation by the number of total births at that gestation.The numbers of fetuses at risk for stillbirth and early neonatal death at each gestation were then used to calculate a second set of perinatal mortality rates. Under this fetuses at risk formulation, the stillbirth rate at 28 weeks gestation was computed by dividing the number of stillbirths at 28 weeks by the number of live births and stillbirths at 28 or more completed weeks of gestation. This implies that fetuses who delivered at 29, 30, 31 and 32 or more weeks gestation were also at risk of stillbirth at 28 weeks -19,41-44th percentile cut-off from a birth weight for gestational age standard based on live births in the United States [th percentile values provided by this standard [th percentile of birth weight for gestational age  compared with appropriate-for-gestational age births at the 50th percentile of birth weight for gestational age . We also examined gestational age-specific growth restriction differences among males and females using rate ratios  and contrasted these with gestational age-specific differences in stillbirth and neonatal mortality rates . This was done to ascertain the relationship between patterns of growth restriction and patterns in the two components of perinatal mortality .We also examined gestational age-specific patterns of fetal growth restriction using the fetuses at risk approach ,17-19. Td States . Gestatistandard  to evaluComparisons of male and female gestational age-specific growth restriction and gestational age-specific perinatal mortality patterns were contrasted with similar comparisons according to maternal race. Specifically, live births and stillbirths ≥22 weeks of gestational age and ≥500 g birth weight in the United States in 1997 and 1998 were used to compare gestational age-specific growth restriction and perinatal mortality rates among whites vs blacks.Identification of SGA live births among blacks and whites was carried out using a single standard for both races  and alsoDifferences in rates were assessed using rate ratios and excess risks. Taylor series 95% confidence intervals were calculated on all rate ratios. All p values presented are two-sided. Sensitivity analyses were carried out to assess the potential effect of gestational age errors on patterns of growth restriction and perinatal mortality among males and females. Specifically, we reassessed growth restriction and mortality patterns among males and females after excluding all births for whom menstrual-based gestational age was either imputed or replaced by the clinical estimate of gestation.There were 3,905,694 singleton male births in the United States in 1997 and 1998 . The low birth weight  rate among male live births was 5.5%, and 10.5% of male live births were born preterm (<37 weeks). There were 3,723,153 female births in the United States during the same period and relative to males, female live births had a higher rate of low birth weight  but a lower rate of preterm birth . Males had a 14%  higher perinatal mortality than females; perinatal mortality rates among males and females were 6.78 and 5.95 per 1,000 total births, respectively.The gestational age distribution of male live births Figure  was 'shiGestational age-specific perinatal mortality rates calculated using the fetuses at risk approach showed that perinatal mortality rates increased with increasing gestational age Figure . Males hhigher growth restriction rate than females at the same gestational week (sex-specific standard) and this was qualitatively congruent with a 17 percent  higher perinatal death rate among males compared with females at 35 weeks gestation. On the other hand, when a unisex standard was used to identify growth restricted live births, males had a lower rate of growth restriction at all gestational ages and this was not qualitatively congruent with the higher gestational age-specific pattern of perinatal mortality among males .Figure s Figure . For insOverall growth restriction rates based on a sex-specific standard showed that rates were 3% (95% CI 2 to 3) higher among males. Stillbirth and early neonatal mortality differences (rate ratios) among male vs female births both favored females , despite a significantly higher perinatal mortality rate among blacks at 40 weeks gestation . On the other hand, rates of gestational age-specific growth restriction were qualitatively congruent with patterns of gestational age-specific perinatal mortality when growth restriction among blacks and whites was defined using a single birth weight for gestational age standard . Growth restriction (based on a single standard for both races) and perinatal mortality rates were substantially higher among births to black mothers as compared with births to white mothers at all gestational ages  for identifying fetal growth restriction at all gestational ages. Our findings challenge the former assumption and show that in fact fetal growth restriction rates are better viewed as increasing with advancing gestational age . This may be a consequence of the use of sex-specific birth weight for gestational age standards or sex-specific ultrasound-based fetal growth standards and, as mentioned, probably also reflects higher rates of suspected fetal compromise among pregnancies with male fetuses. Despite the marginally higher rates of labor induction among pregnancies with male fetuses, however, mortality differences persist. Research should be directed at ascertaining whether excess neonatal mortality among males can be successfully reduced through explicit recognition of male sex as a factor for altering the threshold for obstetric intervention.Although contemporary birth weight for gestational age standards have substantial face validity ,47,48, tOur study has limitations that are typical of studies that use large data bases. Errors in gestational age information are inevitable, although the magnitude of these errors is likely to be similar among male and female births. The overall rate of missing gestational age was low, however (0.9 percent among white live births and 0.8 percent among black live births). Our estimates of gestational age-specific fetal growth restriction rates are approximate. Ideally, estimation of the incidence of fetal growth restriction requires identification of fetal growth restriction on a longitudinal basis among continuing pregnancies . The altThe fetuses at risk approach resolves the paradox of intersecting perinatal mortality curves. Male births have higher rates of gestational age-specific perinatal mortality than female births. There is empirical justification for using sex-specific standards of birth weight for gestational age since gestational age-specific growth restriction patterns based on such standards correspond qualitatively with gestational age-specific perinatal mortality patterns. On the other hand, a single birth weight for gestational age standard for whites and blacks in the United States appears more appropriate than currently available race-specific standards since gestational age-specific growth restriction patterns among blacks and whites (based on a single standard) are qualitatively congruent with gestational age-specific patterns of perinatal mortality.The author(s) declare that they have no competing interests.KSJ proposed the study, carried out the analyses and drafted the manuscript. The results of the analyses were presented and discussed at a meeting of the Fetal and Infant Health Study Group of the Canadian Perinatal Surveillance System. All authors contributed to revising the manuscript for intellectual content. All authors read and approved the final version.The pre-publication history for this paper can be accessed here:


As multiple pregnancies show a higher incidence of complications than singletons and carry a higher perinatal risk, the calculation of birth weight – and gestational age (GA)-specific perinatal mortality rates (PMR) for multiple births is necessary in order to estimate the lowest PMR for these groups.Details of all reported twins  in Japan between 1990 and 1999 were analyzed and compared with singletons  in the annual report of vital statistics of Japan. The fetal death rate (FDR) and PMR were calculated for each category of birth weight at 500-gram intervals and GA at four-week intervals. The FDR according to birth weight and GA category was calculated as fetal deaths/ × 1000. The perinatal mortality rate (PMR) according to birth weight and GA category, was calculated as / × 1000. Within each category, the lowest FDR and PMR were assigned with a relative risk (RR) of 1.0 as a reference and all other rates within each category were compared to this lowest rate.The overall PMR per 1,000 births for singletons was 6.9, and the lowest PMR was 1.1 for birth weight (3.5–4.0 kg) and GA (40- weeks). For twins, the overall PMR per 1,000 births was 36.8, and the lowest PMR was 3.9 for birth weight (2.5–3.0 kg) and GA (36–39 weeks). At optimal birth weight and GA, the PMR was reduced to 15.9 percent for singletons, and 10.6 percent for twins, compared to the overall PMR. The risk of perinatal mortality was greater in twins than in singletons at the same deviation from the ideal category of each plurality.PMRs are potentially reduced by attaining the ideal birth weight and GA. More than 90 percent of mortality could be reduced by attaining the optimal GA and birth weight in twins by taking particular care to ensure appropriate pregnancy weight gain, as well as adequate control for obstetric complications. Multiple birth rates are increasing world wide ,2 as a cIn Japan, while infertility therapy is in its introductory stages in comparison to the U.S., the twinning rate has continued to rise steadily since the middle of the 1970s ,7. In coIn Japan, birth, death and stillbirth (GA more than 12 weeks) certificates are systematically stored on magnetic tape data files by the Ministry of Health, Labor and Welfare (MHLW). These certificates are filled in by obstetric clinicians or midwives following obstetric recording in the hospitals or clinics, and are filed in the city health department and changed into computerized files at the MHLW. This database contains information relating to sex, birth weight, birth length, GA, parity, ages of father and mother, and dates of birth and death. We used birth, infant death and stillbirth certificates of all multiple births reported between 1990 and 1999.Among all live births and fetal deaths with a GA of 22 weeks and over, cases that correspond to the abnormal or missing data that occurred during data collection in the municipalities or during entry onto the magnetic tape database were excluded. This resulted in a 0.68 percent reduction of cases from the original population. Because birth and death certificates were not linked to each other, birth and death certificates of the same municipalities on the same day with the same job of the family were identified to be the same individuals. 96.5% certificates of early neonatal death were linked to birth certificates. The final study sample constituted 10,021,275 live births, 63,972 fetal deaths and 16,862 early neonatal deaths for singletons, which appeared in the table of the annual report from the MHLW, and 192,987 live births, 5,539 fetal deaths and 1,830 early neonatal deaths for twins from the magnetic tape database. For singletons, data on birth weight and GA-specific frequencies of births and perinatal deaths published in the MHLW annual reports were collected, and then compared with those relating to twins. Frequencies were categorized by 500 grams for birth weight and by four week intervals for GA.The FDR of each plurality, according to the birth weight and GA category, was calculated as follows: fetal deaths/ × 1000. Similarly, the perinatal mortality rate (PMR) of each plurality, according to the birth weight and GA category, was calculated as follows: / × 1000.For each plurality type, the lowest FDR and PMR were identified within the categories of birth weight and GA. Within each category, the lowest FDR and PMR were assigned with a relative risk (RR) of 1.0 as a reference and all other rates within each category were compared to this lowest rate, calculating RRs ± 95 percent confidence intervals (CIs). RR was also calculated by comparing the same birth weight and GA category for twins versus singletons.For live twin births, the mean birth weight was 2,346 g and the mean GA was 37.14 weeks. The mean birth weight of stillborn twins was 747 g and the mean GA was 29.85 weeks.The overall FDR/PMR per 1,000 births for singletons was 5.4/6.9, and the lowest FDR and PMR was 0.6/1.1 for birth weight and GA (3.5–4.0 kg and 40- weeks/3.0–3.5 kg and 36–39 weeks) (Table 1) [see Additional file For singletons, the lowest FDR/PMR was found to be at 3.5–4.0 kg and 40- weeks/3.0–3.5 kg and 36–39 weeks, although the risk of fetal death was not significantly different at the neighbouring intervals Figure . In gestFor twins, the lowest FDR/PMR was found at 2.5–2.9 kg at 36–39 weeks, although the risk of fetal death/perinatal mortality was not significantly different at the neighbouring intervals  were 92.7 percent (singleton) and 90.0 percent (twins) for FDR, and 97.1 percent (singleton) and 89.3 percent (twins) for PMR.The category-specific comparisons of FDR/PMR for twins versus singletons is shown in Figure The optimal birth weight and GA were evaluated for singletons and twins. Even with premature GA, adequate intrauterine growth is consistently associated with the substantial reduction in the risks of fetal death. For each plurality, PMR or FDR is the lowest at the optimal birth weight and GA, the deviation from which makes PMR or FDR higher. If the deviation is the same, PMR or FDR is said to rise higher among the triplets than among twins, and also higher among twins than among singletons . Thus, tThe statistical analysis in this study has confirmed that intrauterine growth retardation is associated with the risk of fetal and neonatal death, as well as prematurity. This can be seen clearly in the results for the category with relatively large GA and relatively small birth weights ,5. PreviThe lengths of GA were filled in into birth/stillbirth certificates following obstetric records in the hospitals or clinics. Some of them were calculated from the last menstual period and others were identified using ultrasonic measurements. Although the assessment of GA with the last menstual period only may lead to over/under estimation, the proportions are so small that the overall conclusion would not be different, even if all the GA information were based on the ultrasonic measurements.This analysis also confirmed that the FDR/PMR for twins is lower than for singletons in earlier GA or lower birth weight ranges. This finding has been reported previously ,5. In otThese results imply that the singleton range of birth weight and GA maturity is actually at a level that is postmature for twins. In reference to biological evidence, it has been reported that fetal lung maturation occurs several weeks earlier in twins than in singletons . The incOverall, the results of this study are similar to the findings of Luke , whose sThe detailed differences between Luke's and our study are probably due to ethnic differences in the study population or differences in neonatal care practices. In addition to the different observation period, Luke's study was based on the period 1983–88, while our study was conducted between 1990–99. Although the observation period of this study is more recent, the FDR in Japan was much higher . This reflects differences in the reporting of fetal deaths and early neonatal deaths between Japan and the US. In Japan, early neonatal deaths with life durations as short as a few hours tend to be classified as fetal deaths. Moreover, the sample size of this study was smaller than that of Luke's, particularly in relation to twins, although our observation period was longer. However, this is not due to differences in the exhaustibility of data collection, but is simply due to differences in the general population sizes in Japan and the US.Recently, studies were performed with various approaches to deal with the issue about optimal birth weight and GA. Ananth et al. took medically indicated preterm delivery (labor induction and cesarean delivery) into consideration,17.The methodology of the present study was that of a conventional epidemiological approach. Recent publications have analyzed the PMR of multiple births by alternative fetuses with a risk approach,19, wherWe have clarified that the optimal GA was earlier and the optimal birth weight was lower in multiple births in comparison to singletons. More than 80 percent of mortality could be reduced by the attainment of optimal GA and birth weight in multiple pregnancies by taking particular care about pregnancy weight gain. It is hoped that the results of this study can contribute to the improvement of medical care guidelines providing clinical care for multiple pregnancies.The author(s) declare that they have no competing interests.All authors have made a substantial contribution to the publication. Noriko Kato, the principal author, performed all the research practice, analysis and reduction. Tomohiro Matsuda, who belongs to the same institute as the principal author, collaborated with the principal author to analyze the data and to discuss on the results.The pre-publication history for this paper can be accessed here:Click here for fileClick here for file


A 20-μg/m3 difference in levels of particulate matter ≤ 10 μm in aerodynamic diameter (PM10) during the third trimester was associated with a 21.7-g lower birth weight , but this association was reduced and not significant after adjusting for O3. In summary, O3 exposure during the second and third trimesters and CO exposure during the first trimester were associated with reduced birth weight.Exposures to ambient air pollutants have been associated with adverse birth outcomes. We investigated the effects of air pollutants on birth weight mediated by reduced fetal growth among term infants who were born in California during 1975–1987 and who participated in the Children’s Health Study. Birth certificates provided maternal reproductive history and residence location at birth. Sociodemographic factors and maternal smoking during pregnancy were collected by questionnaire. Monthly average air pollutant levels were interpolated from monitors to the ZIP code of maternal residence at childbirth. Results from linear mixed-effects regression models showed that a 12-ppb increase in 24-hr ozone averaged over the entire pregnancy was associated with 47.2 g lower birth weight , and this association was most robust for exposures during the second and third trimesters. A 1.4-ppm difference in first-trimester carbon monoxide exposure was associated with 21.7 g lower birth weight  and 20% increased risk of intrauterine growth retardation . First-trimester CO and third-trimester O A major research focus has been to investigate the effects of air pollution on birth weight, low birth weight , and intrauterine growth retardation (IUGR).A growing body of evidence indicates that maternal exposures to air pollutants, including ozone, carbon monoxide, particulate matter with an aerodynamic diameter of ≤ 10 μm or ≤ 2.5 μm  and birth weight in Los Angeles, California, in the 1970s. Subsequently, several studies examining the effects of air pollution on fetal growth have been conducted in the United States , a population-based study of children residing in 12 southern California communities.To further investigate the effects of OThe elements of the CHS have been described previously , 1999b. Birth weight, gestational age, and other reproductive data were obtained from California birth certificates. Birth certificate information for California-born children who participated in the CHS was obtained by computerized linkage of participants with the California Department of Health Services Birth Statistical Master Files and Birth Cohort Files. Of the 6,259 cohort participants, 5,013 were born in California according to parental report, and 4,842 were matched to a birth certificate record. Because preterm birth is associated with adverse birth outcomes and our analyses were focused on the effects of air pollutants on birth weight mediated by reduced fetal growth as opposed to reduced gestational age, we restricted our analyses in children who were born at term with gestational ages between 37 and 44 weeks, consistent with the methods used by earlier researchers. This criterion resulted in the exclusion of 941 children who were born before the 37th week of gestation, and our final sample consisted of 3,901 children. Data obtained from California birth certificates included birth weight, gestational age, maternal age at birth, maternal residence ZIP code at birth, parity, months since last live birth, gestational diabetes, and marital status. The estimated date of conception was assigned using the birth date and gestational age, corrected for the average 2-week difference between the last menstrual period and conception. First trimester was defined as gestational age < 13 weeks, second trimester was 13–27 weeks, and third trimester was 28 weeks to birth. We defined LBW as birth weight < 2,500 g in term infants and defined IUGR by less than the 15th percentile of predicted birth weight based on gestational age and sex in term infants.3 (O3[24hr]), 1000 hr to 1800 hr O3 (O3[10–6]), NO2, CO, PM10, and temperature by spatially interpolated monthly average levels to the geometric centroid coordinates of the ZIP code boundaries for the ZIP code region of the maternal birth residences.Air pollution estimates were assigned using the ZIP code of the maternal residence at birth and monthly average air pollution estimates for each ZIP code interpolated from monitoring data obtained from the U.S. Environmental Protection Agency’s (EPA) Aerometric Information Retrieval System through written request in 1999. Currently the 1999 data are available under the Air Quality System database of the U.S. EPA . Tempera3). Because the spatial gradients in monthly average data are smaller than hourly or daily data, the method was relative insensitive to the number of stations included in the interpolation and maximum interpolation radius. Three stations and a 50-km radius were selected because they preserved local gradients slightly better than did larger numbers of stations and greater distances. In cases where air monitoring data were available from a station located within 5 km of a ZIP code centroid, the assignments were based on the nearest station’s data rather than interpolation. For this cohort, 29% of the NO2 assignments and approximately 40% of the O3, PM10, and CO assignments were based on the nearest station’s data. Each mother’s exposures to O3, NO2, PM10, and CO during each trimester were estimated using weighted averages of the calendar month averages. Although other studies included SO2 exposures, it was not included in this study because ambient SO2 concentrations are generally low in California and are measured at too few monitoring stations to make reliable exposure assignments.The interpolation used inverse-distance-squared weighting based on data from up to the three nearest monitoring stations located within 50 km of the ZIP code centroid  were computed by fitting linear mixed-effects models using the SAS procedure GENMOD . Because of the nonlinearity in the relationship of birth weight with gestational age, a cubic polynomial in gestational age was necessary to adequately capture the nonlinearity. We therefore included linear, quadratic, and cubic terms for gestational age in all final models. The models also included maternal age, months since last live birth, parity, maternal smoking during pregnancy, SES, marital status at childbirth, gestational diabetes, and child’s sex, race/ethnicity, and school grades  of the CHS cohort as fixed effects, and CHS study community as a random effect. To account for confounding by seasonal determinants of birth weight, the adjusted analyses included six terms for the basis matrix of a b-spline on Julian day of birth, with knots at days 91, 183, and 274 , because3 that included three terms for average levels during each of the three trimesters.We considered the effects of pollutant exposures during the entire pregnancy and during each trimester. To illustrate the magnitude of the birth weight differences by air pollutant level, we presented the estimates scaled to the approximate interquartile ranges (IQRs) of average exposure for each pollutant. We also computed odds ratios (ORs) and 95% CIs for the association between pollutant levels and LBW and IUGR using appropriate logistic regression models that included the same adjustment variables as in the mixed-effects models. For pollutants that showed significant associations with birth weight in trimester-specific analysis, we fitted models that included average levels of those specific pollutants during specific trimesters. We fitted an additional model for O3[24hr] exposure averaged over the entire pregnancy and presented the difference in birth weight associated with each decile of O3[24hr] exposure relative to the lowest decile. We assessed departure from linear relationships between birth weight and pollutants by examining appropriate residual plots and by comparing nested models with linear terms and categorical terms for each pollutant using partial F-tests. All significance tests were two sided at the 0.05 level.For pollutants that were correlated with temperature and altitude, we conducted sensitivity analyses adding linear terms for elevation above sea level, temperature, and season of birth to the multivariate models. We also fitted a model with indicator variables for the deciles of On = 18) or gave twin births (n = 25).The sample included almost equal proportions of males and females . About 63[24hr] and O3[10–6] with correlation coefficient (r) > 0.9, and moderate positive correlation between O3 and temperature with r approximately 0.6. Daily O3[24hr] was also positively correlated with PM10 (r ~ 0.5) but negatively correlated with NO2 (r ~ −0.1) and CO (r ~ −0.3). Elevation was positively correlated with O3 (r ~ 0.3 −0.4) but negatively with CO (r ~ −0.3) and NO2 (r ~ −0.15). O3 levels in the first and second trimesters and the second and third trimesters were positively correlated (r = 0.31 in both instances), but levels in the first and third trimesters were negatively correlated .3 averaged over the entire pregnancy was associated with reduced birth weight for both the O3[24hr] and the O3[10–6] average metrics  across the IQR of 12 ppb. Exposures to PM10, NO2, and CO when averaged over the entire pregnancy were not significantly associated with birth weight.Maternal exposure to O metrics . For O3[3 levels and birth weight was stronger for exposure occurring during the second and third trimester for both the O3[24hr] and O3[10–6] average metrics  and 35.3 g , respectively. Trimester-specific analyses showed a statistically significant inverse association between CO concentrations in the first trimester and birth weight. Over an IQR in CO of 1.4 ppm, mean birth weight was lower by 21.7 g . The effects of PM10 were largest for the third trimester, and with each IQR increase in PM10 , birth weight was lower by 21.7 g .The inverse association between ambient O metrics . With ea3 exposure over the entire pregnancy [Table S1 of the http://ehp.niehs.nih.gov/members/2005/8111/supplemental.pdf)]. However, greater birth weight deficits were observed for the second-trimester O3 exposures after such adjustment compared with the estimates presented in 10, the effect estimate for the third trimester was reduced and was no longer statistically significant. However, the second-trimester PM10 results became stronger and achieved borderline significance.In sensitivity analyses where further adjustments were made for temperature, elevation, and season of birth, the effect estimates were somewhat reduced for the average O3[24hr] and CO, and birth weight was lower by 28.6 g  per 1.4-ppm increase in ambient CO levels . Over an IQR in CO of 1.4 ppm during the first trimester, the risk of IUGR increased by 20% . A 17-ppb difference in the third-trimester O3 exposures was associated with 40% increased risk of LBW ; however, the estimates had substantial uncertainty due to the small number of LBW newborns.Maternal O of IUGR . A 17-pp3[24hr] that was clearest above 30-ppb exposure levels  for the four uppermost deciles of exposure, in ranked order by decile median of exposure: −73.7 ; −91.6 ; −103.5 ; −148.3 ]. There were no consistent dose–response relationships between birth weight and CO and PM10 from exposure during pregnancy or by trimester (data not shown).We also observed a dose–response relationship of birth weight with average Oe levels . RelativThe crude effect estimates without any adjustment for maternal  or fetal  factors were similar to the adjusted estimates. The directions and magnitude of the effect estimates did not change in sensitivity analyses after we excluded the plural births, infants born to mothers with gestational diabetes, and subjects with missing covariate information on maternal race/ethnicity, smoking during pregnancy, parity, and SES.3 levels in the second and the third trimesters were independently associated with lower birth weight and IUGR in term infants through the mechanism of reduced fetal growth. Although PM10 exposure in the third trimester was associated with reduced birth weight, the PM10 effect was not statistically significant in a two-pollutant model that included PM10 and O3. A clear pattern of increasing deficits in birth weight with increasing levels of O3 was observed for 24-hr average O3 levels above 30 ppb, but no such trend was apparent for CO and PM10. NO2 levels were not associated with birth weight in this study. Although the differences in birth weight were small on average, those in the highest O3 exposure group had deficits of a magnitude equivalent (~ 150 g) to those observed after exposure to cigarette smoke.We observed that ambient CO levels in the first trimester and OOur finding of an inverse association between maternal CO exposure during the first trimester and birth weight and IUGR is consistent with earlier reports . Althoug2 delivery to fetal circulation. Because CO crosses the placental barrier . In Seoul, South Korea, with a median O3 level of 22.4 ppb, 3 in the third trimester and LBW. Our results are consistent with the findings from these studies. In the study of term infants in Los Angeles, conducted by 3 with birth weight were not reported. In addition, in this study, we observed significant reductions in birth weight with O3[24hr] concentrations ≥ 30 ppb. This may provide an explanation for not observing any association between O3 and birth weight in areas with lower ambient O3 levels. However, interpreting this observation as evidence for a threshold is not justified without further investigation.Of the more recent published reports that assessed the role of different ambient air pollutants on birth weight, a limited number assessed the effects of Oh weight . Chen et3 in reduced birth weight and suggest that the effect could be mediated through modulation of maternal inflammatory processes. In rats, neutrophilic inflammation was proportional to O3 dose, and pregnant rats were more susceptible to acute pulmonary inflammation from O3 than were virgin rats  due to higher alveolar ventilation produced by increased tidal volumes and decreased ascorbic acid levels in the RELF. 3 increased embryo toxicity in rats with evidence for a reduction in weight gain 6 days after birth. 3 over days 7–17 of gestation. Because pregnancy duration in mice is about 3 weeks  of LBW. Because a set cut-point of 2,500 g is used to define LBW, and the prevalence of LBW in term infants in developed countries is low, the use of LBW may not be ideal for assessing the impact of air pollution on birth weight in developed countries.Although third-trimester OIn contrast with earlier studies, the present study had information on maternal smoking and SES to adjust for potential confounding by these factors. Because maternal smoking during pregnancy may affect the associations between air pollutants and birth weight, and we did not have enough power to detect any significant effect modification, we restricted our analysis to mothers who did not smoke during their pregnancy with the index child and observed similar results (data not shown).2, but this would not account for the deficits in birth weight that we observed from exposures to the other pollutants. Because we did not have direct measures of maternal exposures to indoor and occupational pollutants during pregnancy, we could not address the effects of these exposures on the birth outcomes.The findings from this study must be interpreted in light of the methods used to assign exposure during the period of pregnancy. Air pollution exposures were assigned based on the centroid of the ZIP code of maternal residence at childbirth and may not reflect the actual exposure levels for the duration of the entire pregnancy. Studies have shown that about 20–25% of pregnant women change their residences during pregnancy . However3, PM10, NO2, and CO interpolated from monitoring stations < 5 km from the maternal birth residence ranged from 29.2 to 41.1%, whereas 51.2–61.3% were between 5 and 25 km, and the remaining 2.8–9.6% were interpolated from stations between 25 and 50 km for PM10, NO2, and CO and between 25 and 100 km for O3 [Table S2 of the supplemental material ]. We conducted sensitivity analyses to assess the influence of distance of the monitoring stations on the associations between air pollutants and birth outcomes excluding women living farther from these monitors, and the results showed little change (data not shown). Furthermore, a recent study in California showed high correlation (r ~ 0.9) of air pollutant levels between monitors located within 5 miles  from the maternal residence and those located at the county level . However, the CO effect estimates remained robust in a two-pollutant model, suggesting an independent CO effect on birth weight in the first trimester. PM10 and O3, on the other hand, were positively correlated in the third trimester (r ~ 0.5), and the effect of PM10 was reduced about 2-fold in the two-pollutant model. Because a strong negative correlation between the measurement errors in PM10 and O3 seems unlikely, the independent PM10 effects may be smaller.Although measurement errors of pollutants in single-pollutant models are likely to attenuate the magnitude of birth weight deficits associated with air pollutants, the findings from two-pollutant models as well as those adjusted for temperature and elevation should be evaluated with some caution given the correlation structure between these environmental factors. In two-pollutant models where levels of pollutants are correlated and the measurement error in one pollutant is larger than the other, Measures of maternal nutrition  were not available to assess the potential effects of these factors on the associations observed in this study. Although maternal nutrition may be a determinant of birth weight in the developing world, We also considered the possibility of bias from the potential effects of air pollutants on preterm births. In California, birth certificate data for birth weight have been found to be valid and reliable . However3 concentrations. The second- and third-trimester O3 levels were most strongly associated with deficits in birth weight. In addition, CO levels in the first trimester were associated with about a 22-g reduction in birth weight over an IQR of 1.4 ppm. These findings suggest that ambient CO in the first trimester and O3 in the second and third trimesters are determinants of birth weight and IUGR. Because exposures to the levels of ambient air pollutants observed in this study are common, and fetal growth is an important determinant for childhood and adult morbidity and mortality, our findings are likely to have important public health and regulatory implications.In conclusion, we observed an association between lower birth weight and IUGR with Osupplemental material


IGF-I promoter polymorphism was associated with birth weight and risk factors for cardiovascular disease (CVD) and type 2 diabetes (T2DM), and whether the birth weight – risk factor relationship was the same for each genotype.To investigate whether 264 subjects (mean age 36 years) had data available on birth weight, IGF-I promoter polymorphism genotype, CVD and T2DM risk factors. Student's t-test and regression analyses were applied to analyse differences in birth weight and differences in the birth weight – risk factors relationship between the genotypes.IGF-I promoter polymorphism had a 0.2 kg lower birth weight than men with the wild type allele (p = 0.009). Of the risk factors for CVD and T2DM, solely LDL concentration was associated with the genotype for the polymorphism. Most birth weight – risk factor relationships were stronger in the VC subjects; among others the birth weight – systolic blood pressure relationship: 1 kg lower birth weight was related to an 8.0 mmHg higher systolic blood pressureMale variant carriers (VCs) of the IGF-I gene is related to birth weight in men only, and to LDL concentration only. Furthermore, the genotype for this polymorphism modified the relationships between birth weight and the risk factors, especially for systolic and diastolic blood pressure.The polymorphism in the promoter region of the  Insulin-like growth factor-1 (IGF-I) is a peptide that is involved in fetal growth and cell differentiation  In additIGF-I gene has been identified, and is thought to influence the transcription rate of IGF-I, which in turn affects serum IGF-I levels [IGF-I gene might be relevant to the fetal origins hypothesis. This hypothesis suggests that an adverse environment during the intra-uterine period negatively affects fetal growth (often estimated by birth weight), and results in adaptations that permanently change the structure and functions of the body, which leads to an increased risk for disease, such as CVD and T2DM, at adult age [IGF-I gene was related to lower birth weight [IGF-I gene.A genetic polymorphism comprising a variable length cytosine-adenine (CA) repeat sequence in the promoter region of the I levels . Since Idult age . An altedult age ,12 A stuh weight . In addih weight . This hah weight -17 TheseIGF-I gene has now been analysed for the 192 bp polymorphism [IGF-I promoter polymorphism genotype associated with birth weight? 2) Is IGF-I promoter polymorphism genotype associated with risk factors for CVD and T2DM? 3) Is birth weight associated with risk factors for CVD and T2DM and finally 4) Do intra-uterine environment and the IGF-I promoter polymorphism genotype interact? Or, in other words, is the association between birth weight and risk factors for CVD and T2DM different for each genotype of this polymorphism?In the Amsterdam Growth and Health Longitudinal Study (AGAHLS), data on birth weight, and risk factors for CVD and T2DM have been collected. The morphism , in ordeIGF-I promoter polymorphism genotype, glycated hemoglobin (HbA1c), carotid intima-media thickness (IMT), blood pressure, anthropometry and serum low density lipoprotein (LDL) cholesterol levels. Three-hundred-ninety-one subjects completed the birth-weight questionnaire of whom 380 had written information or information from parents. For the purpose of the present study, subjects who were born pre-term , were one of a twin (11 subjects) or were of non-Caucasian ethnicity (9 subjects) were excluded. Another 69 subjects were not taken into account for the analyses because of errors or missing values in the genotyping or risk factor measurements. Finally, for 264 subjects (152 women) there were complete data sets on the IGF-I promoter polymorphism genotype, birth weight, and adult risk factors for CVD and T2DM. Subjects included for the analyses were smaller  and had less fat-free mass  compared to subjects not included for these analyses, but with data on the outcomes available (N = 109). On all other outcome variables the groups did not differ.  All subjects were apparently healthy at the time of the measurements, and none had been diagnosed with T2DM. All subjects gave written informed consent and the Medical Ethical Committee of the VU University Medical Center approved the protocol.The Dutch population described in this study are all participants of the AGAHLS. The AGAHLS is an observational study with repeated measurements, which started in 1976 to monitor boys and girls with a mean age of 13 years . During Data on birth weight were obtained by means of a questionnaire. The questions concerned birth weight, gestational age, being one of a twin, and ethnicity, and subjects were also asked about the source of the information. Only those who had received the information from their parents or had it in written documents were included, as this has been shown to be a valid method ,20 SubjeIGF-I promoter polymorphism genotypes were determined as described earlier [ earlier . In brieRietveld et al recently1c as an estimate of glucose metabolism (unfortunately no glucose measures were available). BMI was calculated as body weight (kg) divided by body height (m2). Standing height was measured with a stadiometer to the nearest 0.001 m. Body weight (kg) was measured to the nearest 0.1 kg using a spring balance scale , with subjects dressed only in underwear. Waist (at the level of the umbilicus) and hip circumference were measured with a flexible steel tape to the nearest 0.1 cm. WHR was calculated as the ratio between waist circumference and hip circumference. Fat mass (FM) was estimated from four skinfolds  with the Durnin and Womersley equation [The following risk factors for CVD and T2DM were measured: body mass index (BMI), waist circumference, waist-to-hip ratio (WHR), total fat mass (FM), total fat-free mass (FFM), carotid intima-media thickness (IMT), systolic and diastolic blood pressure , resting heart rate, LDL cholesterol levels and HbAequation . The fouequation . FFM wasIMT of the right common carotid artery was obtained by an ultrasound scanner equipped with a 7.5 MHz linear array probe , as described elsewhere in more detail -29 SBP a1c (%) were measured from blood samples (10 ml) taken from the antecubital vein between 8.30 and 12.30 a.m. with subjects in a non-fasting state. Standard methods were used to analyse the LDL concentration and external quality control took place with target samples from a World Health Organisation reference laboratory . HbA1c was determined by non-exchange high performance liquid chromatography with a modular Diabetes Monitoring System .Serum LDL and HbAIGF-I promoter polymorphism genotypes. Multiple linear regression analyses were applied to study the associations between birth weight and the risk factors for CVD and T2DM. The results of the regression analyses were presented as regression coefficients (β) and the corresponding 95% confidence intervals (CI) for two different models. The first model was a crude analysis, only adjusted for gender (and for SBP and DBP in case of IMT). The second was further adjusted for adult body weight.A t-test was used to analyse differences in birth weight between the IGF-I promoter polymorphism, multiple linear regression was performed between birth weight and all risk factors  for the two genotypes separately.To investigate whether the relationship between birth weight and the risk factors for CVD and T2DM were modified by the All analyses were performed with the Statistical Package of Social Science  version 10.1. The statistical significance was set at p-value ≤ 0.05.IGF-I promoter polymorphism. The remaining 75 subjects (41 women), 4 were homozygous for alleles with variant CA repeats and 71 were heterozygous for variant alleles. The distribution of genotypes was in Hardy-Weinberg equilibrium (p = 0.17).Table Population characteristics on all measured variables are presented in Table Subjects in the VC group had significantly higher LDL concentrations (p = 0.039). No other significant differences between the genotypes were observed.Table IGF-I promoter polymorphism genotypes. In most of the associations studied, the regression coefficient for birth weight was highest in the VC group, indicating a stronger effect of birth weight on the outcome variable. This difference was most marked in the association with SBP, in which a 1 kg lower birth weight was related to an 8.0 mmHg increase in adult SBP in the VC group, compared to a 1.4 mmHg increase in the WT group. Although, the difference between the VC group and WT group was not statistically significant (p = 0.08) for these kind of 'interactions' normally a higher significance level is used. In addition, the relationships between birth weight and DBP and FM were significant in the VC group and not in the WT group (p = 0.06 for the difference between VCs and WTs for DBP). The differences between VCs and WTs regarding all other relationships showed p-values > 0.10.Table For the associations between birth weight and adult FFM, waist circumference, LDL and resting heart rate, the regression coefficients were highest in the WT group, although none of these associations were statistically significant.IGF-I gene, birth weight, (as a measure of intra-uterine growth), and risk factors for CVD and T2DM were investigated, in order to obtain more insight into the genetic aspects of the fetal origins hypothesis [IGF-I gene had significantly lower birth weights. However, this trend was not observed in women. It is not clear, why this association was absent in women, as no other study has reported gender differences in the association between IGF-I genotype and birth weight [In this study, the associations between a polymorphism in promoter region of the pothesis ,6,30,31 resulted in a lower birth weight, but subjects who were heterozygous for the wild type allele did not differ in birth weight from the homozygous subjects [So far, results on the association between subjects . Neverthsubjects , Fraylinsubjects  and Day subjects  could nosubjects . SubjectIGF-I genotype and LDL concentrations disappeared after adjustment for BMI and there were no differences in HDL concentrations . Several studies have shown that lower IGF-I bio-activity is related to higher incidence of atherosclerotic cardiovascular disease, higher carotid IMT values, lower levels of HDL cholesterol, and impaired glucose tolerance [The results concerning risk factors for CVD and T2DM showed an increased risk in the VC group solely for LDL concentrations, all other risk factors did not differ between WT and VC groups. That only one risk factor was significantly different between the groups might be real or a result of chance, since we tested several associations. Moreover, the relationship between olerance ,35.(Howeolerance -38 Untilnd tertile the relationship between birth weight and FFM was significant (data not shown). Another significant association was found between birth weight and for SBP, which is in line with others and previously found in the AGAHLS[Another aim of the present study was to investigate whether birth weight was associated with risk factors for CVD and T2DM. This was found to be the case for FFM, however this association decreased after adjustment for body weight. When studying this association within tertiles of BMI, it was found that only in the 2he AGAHLS,40. No ohe AGAHLS-46 No ashe AGAHLS. HoweverIGF-I genotype could only explain 6% of the variance in birth weight in men, and only 1% of the variance in birth weight in women. The magnitude of the relationship between birth weight and risk factors for CVD and T2DM, however, seems to be dependent on genes (i.e. IGF-I promoter polymorphism) .Birth weight is considered to be mainly dependent on the intra-uterine environment, such as the availability of nutrients and oxygen . In the m) Table . This moIGF-I genotype was the same, with strong associations between birth weight and SBP and DBP in the VC . Furthermore, despite the fact that the AGAHLS is a longitudinal study, no data was available on infant growth, nor reliable data on birth length was available. If so, it was possible to study effects of IGF-I genotype on infant growth or interactions with infant growth.This study was conducted in 264 subjects only, which is considered few in studies on genetic associations. This might be a reason that we did not find significant associations between genotype and the risk factors. Subjects born pre term were excluded, since gestational age may be another factor associated with risk factors for CVD and T2DM, but with another underlying mechanism . We reanIGF-I promoter polymorphism genotype is related to birth weight in men only, that this genotype is not associated with risk factors for CVD and T2DM, and, most interestingly, that the IGF-I promoter polymorphism genotype modifies the relationship between birth weight and risk factors for CVD and T2DM, especially for SBP and DBP.From this study, it is concluded that β – regression coefficient95%CI – 95% confidence intervalAGAHLS – Amsterdam Growth and Health Longitudinal StudyBMI – body mass indexbp – base pairCA – cytosine adenineCVD – cardiovascular diseasesDBP – diastolic blood pressureT2DM – type 2 diabetesFFM – fat-free massFM – fat-mass1c – glycated hemoglobinHbAIGF-1 – insulin like growth factor 1IMT – intima-media thicknessLDL – low density lipoproteinSBP – systolic blood pressureVC – variant carrierWHR – waist-to-hip ratioWT – wild typeThe author(s) declare that they have no competing interests.IGF-I polymorphism and writing of the paper.The first three authors  equally contributed to the paper. They were involved in the statistical analysis, interpretations of the data, laboratory work to determine the JT, HD, CS, WvM, SL and HK were supervisors and involved in developing the design, assist in statistical analysis and interpretation of the results. They all have been involved in drafting the article or revising it critically for important intellectual content. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here: