Pregnant women have been identified as a high risk group for severe illness with 2009 pandemic influenza A(H1N1) virus infection (pH1N1). Obesity has also been identified as a risk factor for severe illness, though this has not been thoroughly assessed among pregnant women. The objectives of this study were to provide risk estimates for adverse maternal and neonatal outcomes associated with pH1N1 illness during pregnancy and to assess the role of obesity in these outcomes.We established a retrospective population-based cohort of all live births occurring in Florida during the first 15 months of the pandemic. Illness with pH1N1 during pregnancy was ascertained through record linkage with the Florida state notifiable disease surveillance database. Data from the birth record, including pre-pregnancy body mass index, were analyzed to assess risk of adverse outcomes associated with pH1N1 illness.A total of 194 women were identified through surveillance with pH1N1 illness during pregnancy. Children born to women with pH1N1 illness during pregnancy were at increased risk for low birth weight [OR (95%CI): 1.78 (1.11-2.860)], premature birth [2.21 (1.47-3.330)], and infant death [4.46 (1.80-11.00)], after adjusting for other factors. Women with pH1N1 illness during pregnancy were at increased risk for severe outcomes including admission to an intensive care unit. Obesity was an observed risk factor, both for the more severe pH1N1 illness detected through surveillance, and for severe maternal outcomes.Case-patients in this analysis likely represent the most severely ill subset of all women infected with pH1N1 during pregnancy, limiting the generalizability of these findings to more severely ill patients rather than influenza infection in general. Nevertheless, these results suggest that more severe pH1N1 illness during pregnancy is associated with adverse neonatal outcomes and that pregnant women should continue to be targeted for appropriate prophylaxis and early treatment. Infection with influenza virus can result in a spectrum of illness ranging from asymptomatic infection to severe illness and death. Soon after recognition of the novel 2009 pandemic influenza AH1N1) virus (pH1N1), pregnant women were identified as a high risk group for severe illness N1 virus . NumerouFlorida is the fourth most populous state in the U.S. with an estimated population in 2010 of more than 18.8 million residents . More thThe 2009 influenza pandemic began early in Florida, with cases identified in April 2009 and more than 1430 cases reported by June 30, 2009 [unpublished surveillance data]. The summer of 2009 was characterized by persistent transmission across the state, amplified by localized outbreaks in group settings. Following resumption of school, peak transmission was observed in October 2009 . In a naIn several of the initial case series of pregnant women with pH1N1 illness, data on birth outcomes was incomplete, and study designs and available data often did not permit control for other factors associated with adverse neonatal outcomes. Longer term follow-up was needed to ascertain pregnancy outcomes, as well as to fully characterize the impact on infant mortality beyond the perinatal period. Population cohort designs, derived from birth certificate data, may permit more precise risk estimates through a population-based comparison group and better control for confounding. In particular, obesity has been previously identified not only as a risk factor for severe pH1N1 illness–18, but Prior to the recognition of 2009 pH1N1, infection with a novel influenza virus was already a reportable condition in Florida . Thus, aOn August 3, 2009, the state issued new guidance to health care providers and laboratories to test for influenza and, if positive for pH1N1, report people with influenza that was life-threatening or resulted in death, or resulted in hospitalization of a pregnant woman. Providers and facilities were also asked to report people who were part of clusters or outbreaks of influenza-like illness. Despite the change in disease reporting guidelines, some providers continued for several weeks to report non-hospitalized cases of pandemic influenza that were laboratory confirmed. All individual case reports received by the FLDOH meeting the case definition of an acute respiratory illness, with laboratory confirmation of pH1N1 by a certified laboratory, were maintained in the state’s notifiable disease surveillance database. Illness on the more severe end of the spectrum is more likely to be apparent, lead to specific laboratory testing, and be captured through passive notifiable disease surveillance . StandarThe Florida birth registry is maintained by the FLDOH Office of Vital Statistics and includes records on all live births occurring in Florida. Records are submitted by hospitals and other medical providers and contain information on the newborn, as well as the mother and father. There are >330 variables contained in the comprehensive electronic birth record, including information on maternal and infant demographic variables; pre-pregnancy BMI, pre-natal exposures such as alcohol and tobacco use by the mother; obstetric history, medical care received during labor and delivery; and health status of the infant. For this analysis, we also used a variable indicating if the mother resided within the city limits, or in a more rural location outside the city limits. In addition, the electronic birth record is updated to indicate mortality for any child dying within five years following live birth. Electronic records of live births from the Florida birth registry were cross-referenced to the state notifiable disease database to identify children born to women with pH1N1 illness during their pregnancy. All pH1N1 confirmed case-patients with onset of illness between April 24, 2009 and May 31, 2010, who were pregnant at the time of their illness, were included. The record matching included a combination of automated methods and manual review, in an iterative process. Firstly, records in the birth registry were matched to the disease surveillance database by the mother’s social security number and date of birth. Other combinations of matching variables subsequently used included mothers first and last name, alone or in combination with social security number, or date of birth. All matched records were manually reviewed to ensure the accuracy of the match.Data were further compiled from de-identified records of a birth cohort of all live births occurring in Florida between June 1, 2009 and September 1, 2010. This period corresponds with the time interval of live births among women with reported pH1N1 illness. Records for women with multiple gestational  pregnancies were identified and later de-duplicated to also permit analysis of the cohort of pregnant women giving birth during the same interval. Records were excluded for births among non-Florida residents, and in instances in which adoption or foundling was indicated on the birth record. The database was updated in January 2012 to reflect any infant deaths following birth, occurring up to that time. For secondary analysis, an alternative pregnancy and birth comparison cohort was also constructed from the pre-pandemic period to include all live births occurring between January 1 and February 28, 2009. Illness due to pH1N1 infection during pregnancy was treated as the outcome variable when assessing disease risk and treated as the primary exposure variable for assessing risk of adverse maternal and neonatal outcomes. Women and children in the pregnancy and birth cohorts were categorized as pH1N1 illness in pregnancy  if the birth records matched to the pH1N1 notifiable disease surveillance database by the methods previously described. All women and their newborns who did not match to the disease surveillance database were defined as ‘unexposed’ or non-cases of pH1N1 illness during pregnancy. Measures of association between exposure and outcome were computed using univariate and multivariable logistic regression and expressed as odds ratios (OR) with 95 percent Wald confidence intervals (95% CI). Univariate relative risks (RR) were also computed for comparison with ORs, but were not presented in the results tables. Because minimal differences were generally noted between the univariate RRs and ORs and because outcome frequencies were generally uncommon and less than 10%, odds ratios were used throughout as approximate estimates of relative risk. To adjust for possible confounding, standard and stepwise multivariable logistic regression was used. Multivariable models were constructed using variables identified during univariate analyses as being associated with influenza, or known risk factors for adverse maternal and neonatal outcomes, while also attempting to minimize the exclusion of cohort members due to missing data for a particular variable. For all stepwise analysis, α=0.1 was the threshold used for variable entry into the model, and α=0.05 was used for retaining variables in the final model. Data analysis was conducted using SAS software, version 9.1 . Statistical power computations presented in the results were obtained using the computer program Power v3.0 .2]. BMI data in the Florida birth registry has previously been found to be generally reliable and valid [Data on pre-pregnancy BMI was available for approximately 94% of records and was expressed as [weight in kilograms/(height in meters)nd valid . Neverthnd valid  and analFor simplicity, adult BMI categories were used throughout the analysis, despite the fact that some gravida in the analysis were <20 years old, and standard classifications for BMI are different for children and adolescents . MaternaData regarding influenza vaccination history and antiviral treatment for influenza was missing from the surveillance case reports for a large proportion of case-patients. Furthermore, the majority of case-patients had illness onset before a vaccine specific for pH1N1 became available. Therefore, we did not attempt in this analysis to assess the role of vaccination or antiviral treatment for influenza on maternal and neonatal outcomes.This activity was reviewed by the Ethics and Human Research Protection Program of the FLDOH, and determined to involve analysis of existing and de-identified data, not human subjects research, and was therefore exempt from further review by an institutional review board.A total of 194 women with confirmed pH1N1 illness during pregnancy were reported to FLDOH. Of these, matching birth certificates were identified for 187 women (96%); 4 women gave birth to twins, resulting in a total of 191 live births . Of thesAmong pH1N1 case-patients, the temporal pattern of cumulative onset of influenza illness and subsequent birth is shown in Non-pH1N1 associated individuals in the birth and pregnancy cohort included, after exclusions, 300,398 children born to 295,747 women between June 1, 2009 and September 1, 2010. A total of 4,198 birth records were excluded from the cohort due to non-Florida residence of the mother , child adopted , or foundling (n=3). The alternative comparison birth and pregnancy cohort from the pre-pandemic period included, after exclusions, 24,008 children born to 23,679 women.Among the cohort of pregnant women giving birth between June 1, 2009 and September 1, 2010, univariate analysis indicated increased risk of pH1N1 illness detected through surveillance among non-white women, and those of Hispanic or Haitian ethnicity. Increased risk of detected and reported pH1N1 illness was also associated with being 25 or younger, unmarried, high school graduate or less education, being on Medicaid, receiving Women Infants and Children (WIC) Program food supplements, living within the city limits, having one or more previous live births, and being obese . InfluenWhen comparing the distribution of women with pH1N1 illness by variables listed in Neonatal outcomes among the cohort of live births occurring between June 2009 and September 2010, are shown in Illness with pH1N1 was not significantly associated with low birth weight, after adjusting for gestational age and other variables in the multivariable model. This suggests that the association between pH1N1 illness and low birth weight is primarily due to pre-term birth. No interaction was observed between pH1N1 illness and maternal obesity, with respect to the most severe neonatal outcomes of early preterm birth , and infant death (p=0.32). Of the 191 children born to women with pH1N1 illness, 8 (4%) died . This isBased on data available from the birth record, of the 187 women with pH1N1 illness and a live birth, 9 were admitted to ICU. This contrasts with results available from the notifiable disease database, which indicate that 41 (22%) women reported with pH1N1 illness were admitted to ICU. The cause for this discrepancy is unknown, but may be due to the timing of ICU admission following live birth, or incomplete knowledge of the mother’s clinical course by those completing the birth record. Despite this discrepancy, data from the birth record was used to analyze risk of ICU admission for the entire pregnancy cohort. Pregnant women with pH1N1 illness detected through surveillance, were 28 times more likely to be admitted to ICU than other women with a live birth who were not known to be pH1N1 infected . The oddThis analysis was repeated after recoding ICU admission to “Yes” for 32 women with pH1N1 illness previously coded “No” in the birth record, but for whom data from the notifiable disease database indicated ICU admission. The univariate odds ratio of maternal ICU admission associated with pH1N1 illness increased to 155.28 (95% CI: 108.69-221.83). The same variables were retained in the multivariable stepwise model. Following adjustment for covariates, the multivariable OR was 131.25 (95% CI: 88.21-195.28). This risk estimate, however, is likely to be unreliable, as case-patients were more likely to have complete information regarding ICU admission than non-case patients.Of the 8 women with pH1N1 illness who died, 6 gave birth to a live infant, and 4 of these 6 infants survived . Two of To address the possibility that some pregnant women with pH1N1 illness during the study interval were not reported to FLDOH, we searched fields in the birth record for text strings containing “H1N1”. We identified 41 birth records with “H1N1” text appearing in the record. Of these 41 births, 9 were from confirmed cases of pH1N1 ascertained through surveillance, and 32 were from women not contained in the notifiable disease database. In 15 of the 32 records, the “H1N1” text appears to relate to provision of H1N1 vaccine or prophylaxis, leaving 17 remaining records which may represent pH1N1 infections among pregnant women which were not otherwise identified through routine surveillance and case reporting. We conducted additional analysis adding these 17 pregnant women and births to confirmed pH1N1 cases, and excluding the 15 pregnant women and births for which H1N1 may refer to vaccine or chemoprophylaxis. The results of these analyses were not substantially different from previous results, and did not alter any of our conclusions; therefore, we did not utilize this approach when presenting the primary results of our analysis. Similarly, results did not differ notably when excluding or including birth records from adopted children; therefore, results are presented for analyses following exclusion of these records. Based on the available sample size and assuming an alpha-level of 0.05, the study analysis had 80% power to detect ORs of approximately 1.50 or greater for most of the risk factors presented in We observed a consistent, and statistically significant association between pH1N1 illness during pregnancy and adverse neonatal and maternal outcomes, including low birth weight, preterm birth, neonatal ICU admission, infant death, and maternal ICU admission. The observed associations with pH1N1 illness remained significant after adjusting for other observed and known risk factors for adverse neonatal and maternal outcomes. As the disease surveillance data sources used for this analysis are more likely to detect case-patients with more severe influenza illness, our findings apply more toward outcomes associated with more severe influenza illness, rather than influenza infection in general.While several previous case series have described neonatal outcomes of pH1N1 infected women ,12,27–30In addition to the adverse neonatal outcomes we observed, the pandemic had a striking impact on maternal mortality in Florida, as elsewhere. Data from the Florida Pregnancy-Associated Mortality Review  indicateWe identified younger age, racial and ethnic minorities, indicators of lower socio-economic status (SES), and obesity as risk factors for pH1N1 illness severe enough to be detected through our surveillance. Others have noted both an individual and ecological-level association between hospitalization for pH1N1 and indicators of low SES . One posObesity was both an observed risk factor for recognized and reported pH1N1 illness, as well as a risk factor for poor maternal outcomes among pregnant women, as indicated by ICU admission. Obesity may have important effects on immune response which leave obese individuals more susceptible to infection –38. The Others have previously identified obesity as a risk factor for severe illness with pH1N1 –18,40,41Pierce et al, used a similar approach to ours, however, the comparison cohort they used was smaller and taken exclusively from the pre-pandemic period . The disBy the end of 2009, an estimated 25% of residents in some areas of Florida were believed to have been infected with pH1N1, with the highest rates of infection noted among school-aged children 5-17 years, and infection rates approaching 50% among young adults 18-24 years . SeropreThe study is limited by imperfect disease surveillance and case ascertainment of all women with pH1N1 illness during pregnancy. Therefore, our findings are only generalizable to the more severe pH1N1 illness detected through our surveillance, not to pH1N1 infection in general. Imperfect disease surveillance may have led to both random and differential misclassification bias of pH1N1 illness, which was both an outcome and exposure variable in this analysis, possibly resulting in some bias in the risk estimates. This study was also limited by lack of comparative data for women without a live birth and missing data on pre-pregnancy BMI for approximately 6% of the women. Data available in the birth record regarding maternal morbidity, (e.g. ICU admission), also appears to be incomplete, somewhat limiting our conclusions regarding maternal outcomes. Prospective studies may help address all of these limitations. However, the advantages of our study over past reports include a very large comparison group with extensive information available from the birth record to facilitate control for confounding factors, as well as longer follow-up to allow ascertainment of child mortality, through the birth record, several months after birth. The present study uses a population-based cohort design to add to and further characterize the previously described risk of adverse maternal and neonatal outcomes associated with pH1N1 illness. In conclusion, we found increased risk of severe adverse maternal and neonatal outcomes associated with pH1N1 illness during pregnancy. Pregnant women should continue to be regarded as a high risk group for adverse outcomes of influenza virus infection and should continue to be targeted for enhanced prevention activities through vaccination and appropriate chemoprophylaxis and treatment for influenza, consistent with current recommendations ,49,50.


Lower birth weight is associated with higher insulin resistance in later life. The aim of this study was to determine whether cardiorespiratory fitness modifies the association of birth weight with insulin resistance in adults.2max) was assessed by a maximal graded exercise test on a cycle ergometer. Birth weight was reported according to the Maternal and Child Health Handbook records or the subject’s or his/her mother’s memory.The subjects were 379 Japanese individuals  aged 20–64 years born after 1943. Insulin resistance was assessed using a homeostasis model assessment of insulin resistance (HOMA-IR), which is calculated from fasting blood glucose and insulin levels. Cardiorespiratory fitness , although VO2max  was a stronger predictor of HOMA-IR than birth weight.The multiple linear regression analysis revealed that birth weight was inversely associated with HOMA-IR , even after adjustment for gender, age, current body mass index, mean blood pressure, triglycerides, HDL cholesterol, and smoking status. Further adjustments for VOThe results showed that the association of lower birth weight with higher insulin resistance was little modified by cardiorespiratory fitness in adult life. However, cardiorespiratory fitness was found to be a stronger predictor of insulin resistance than was birth weight, suggesting that increasing cardiorespiratory fitness may have a much more important role in preventing insulin resistance than an individual’s low birth weight. Low birth weight, a proxy for fetal underdevelopment, is associated with increased risk of insulin resistance 3), with insulin resistance, which was estimated using a validated insulin sensitivity index (QUICKI) in middle-aged men. It remains unclear whether CRF modifies the association of birth weight with insulin resistance in other racial groups. Because mean birth weight is lower in the Asian population Although a sedentary lifestyle and obesity, especially abdominal obesity, are known to be important in the development of insulin resistance The subjects were 379 Japanese individuals aged 20–64 years who had taken part in our previous research  The research project was approved by the Ethical Committee of WU, ACHSC, OSIH, and NIHN, respectively. Written informed consent was obtained from each participant.Maternal and Child Health Handbook (including the Handbook of Mothers and Children and the Pregnant Women and Nursing Mothers Notebook) records. The Maternal and Child Health Handbook is a unique tool that is provided to women in Japan who report their pregnancies to each municipal office. In Japan, birth weights have been recorded since July 1942, when the Pregnant Women and Nursing Mothers Notebook was distributed. Starting in 1948, the Handbook of Mothers and Children was distributed instead of the Notebook. In 1967, the Maternal and Child Health Handbook had taken the place of the Handbook of Mothers and Children. Those subjects who had lost the Handbook or Notebook were asked to report their birth weights from memory if the subject or his/her mother knew the subject’s birth weight precisely. The subjects’ reply rate was 41% (397/968). After excluding questionnaires that were not answered completely (n = 18), the completed questionnaires of 379 subjects  were selected for analysis. Of these subjects, 213  had Notebook or Handbook records of their birth weight, and 166  were able to recall their birth weight or obtain it from their mother.The subjects’ birth weights were obtained using a questionnaire-by-mail-survey between 2010 and 2011. We sent questionnaires to 968 participants born after 1943 out of 1,020 participants who enrolled in the above-described research. Data on their CRF, obesity measures, insulin resistance, and confounding variables were recorded in the above-described research, which had been stored at each institution. The questionnaire along with a detailed explanation of the project as described below was sent to 968 participants, using reply-paid envelopes. The subjects were asked to provide their birth weights through the 2). Abdominal circumference was measured at the umbilical region with an inelastic measuring tape at the end of normal expiration.Body mass index (BMI) was calculated from measured height and weight (kg/m2max). The initial work load was 30–60 W, and the work rate was increased thereafter by 15 W/min until the subject could not maintain the required pedaling frequency (60 rpm) 2) and carbon dioxide production (VCO2) were measured over 30-s intervals using an automated breath-by-breath gas analyzing system . The expired air was collected in Douglas bags, and an O2 and CO2 mass spectrometer  was used to analyze the O2 and CO2 concentrations (NIHN). The volume of expired air was determined using a dry gas volume meter  and converted to standard temperature, pressure and dry gas. During the latter stages of the test, each subject was verbally encouraged by the test operators to give maximal effort. VO2max was considered to have been achieved if at least two of the following four criteria were achieved: the VO2 curve showed a leveling off, the subject’s maximal heart rate was >95% the age-predicted maximal heart rate (220 − age), the respiratory exchange ratio exceeded 1.0, and the subject achieved an RPE of 19 or 20.CRF was assessed by a maximal graded exercise test on a cycle ergometer  and quantified in terms of maximal oxygen uptake (VOInsulin resistance was assessed using the homeostasis model assessment of insulin resistance (HOMA-IR), calculated as fasting blood glucose (mg/dL) × fasting insulin (µU/mL)/405. Fasting venous blood samples were collected after a fast of 12 h or more, and the concentrations of blood glucose and insulin were measured Several confounding variables were included in the analyses. In the general population insulin resistance is associated with hypertension, higher concentration of plasma triglycerides, and lower concentrations of high density lipoprotein (HDL) cholesterol 2max as an independent variable to examine how the association is altered by CRF. All models were adjusted for gender, age, one of two obesity measures , study location, mean blood pressure, triglycerides, HDL cholesterol, and smoking status. We also included an interaction term of CRF × birth weight. Multicollinearity in the regression model was assessed by examining the variance inflation factor. All statistical analyses were completed using SPSS 20.0J for Windows . The statistical significance level was set at p<0.05.Measured and calculated values are presented as means ± SD. HOMA-IR was log-transformed due to non-normal distribution in the analyses. Student’s t-test was used to determine the differences between males and females. Partial correlation analysis was used to test the associations between study variables controlled for gender and age as covariates. Multiple linear regression analyses were performed to assess the associations of birth weight and CRF with insulin resistance. We first entered the birth weight as an independent variable and HOMA-IR as a dependent variable. We then added VO2max, and HOMA-IR controlled for gender and age as covariates. Birth weight was correlated positively with current height  and weight  and inversely with HOMA-IR . Both BMI and abdominal circumference were significantly correlated with HOMA-IR . VO2max was inversely correlated with HOMA-IR .The characteristics of the subjects are shown in 2max made little difference in the relationship between birth weight and HOMA-IR  (model 2). Adjusting for abdominal circumference instead of BMI showed similar results  (model 3). This association was largely unaffected by further adjustment for VO2max  (model 4). In the final models (model 2 and 4), gender, age, and obesity variables  were found to be significant predictors of HOMA-IR . No significant associations were observed between an interaction term (CRF × birth weight) and HOMA-IR .2max as covariates .When we separately analyzed the subjects with recorded birth weight data (n = 213) and those with recalled birth weight data (n = 166), we found that the β-related birth weight and HOMA-IR were almost the same between two groups in the model including BMI and VOThis study was performed to examine the association of birth weight with insulin resistance, and how the association is influenced by CRF in adults. Birth weight was found to be significantly and inversely associated with HOMA-IR after adjustment for gender, age, obesity measurement, and other potential confounders . This reThe present study showed that the association of lower birth weight with insulin resistance was not modified by CRF. This finding is in contrast with the study by Laaksonen et al. The difference in race may be a potential reason for the discrepancy between our findings and those of Laaksonen et al. 2max (β = −0.376) in the model 2  was relatively small when compared with that of VO model 2 . CRF in Incidentally, macrosomia, defined as a birth weight of 4 kg or more, is known to be attributed in part to a maternal history of diabetes, which increases the risk of type 2 diabetes in adult offspring 2) in young women Recent trends in industrialized countries, such as the USA, Canada The present study has several limitations. First, as it was a retrospective study, larger sample sizes and long term follow-up studies are needed to confirm the effects of birth weight and adult CRF on insulin resistance. Second, data on gestational age were not available. Nonetheless, adjustment for gestational age has not attenuated the association of thinness at birth with insulin resistance in the previous study In summary, the present study showed that the association of lower birth weight with higher insulin resistance was little modified by CRF in adult life. However, CRF was a stronger predictor of insulin resistance than was birth weight. These results suggest a lifelong adverse effect of low birth weight on glucose metabolism, as well as an importance of lifestyle factors that can improve insulin resistance. Our data demonstrate that higher levels of CRF would not offset the adverse effects of low birth weight on insulin resistance; however, increasing CRF may have a much more important role in preventing insulin resistance than does an individual’s low birth weight.


The role of gene-gene and gene-environment interactions, as well as epigenetics, has the potential to further elucidate and improve understanding of the underlying mechanisms or pathways of spontaneous preterm birth. Refinement in study design and methodology is needed in future research for the development and validation of individual or group biochemical marker(s) for use independently or in conjunction with other potential risk factors such as genetic variants and environmental and behavioral factors in predicting spontaneous preterm birth across diverse populations.Preterm birth is a delivery that occurs at less than 37 completed weeks of gestation and it is associated with perinatal morbidity and mortality. Spontaneous preterm birth accounts for up to 75% of all preterm births. A number of maternal or fetal characteristics have been associated with preterm birth, but the use of individual or group biochemical markers have advanced some of the understanding on the mechanisms leading to spontaneous preterm birth. This paper provides a summary on the current literature on the use of biochemical markers in predicting spontaneous preterm birth in asymptomatic women. Evidence from the literature suggests fetal fibronectin, cervical interleukin-6, and  Preterm birth is defined as birth at less than 37 completed weeks of gestation and it accounts for approximately 75% of perinatal mortality and nearly half of the cases of long-term neurologic morbidity . The ratThe onset of preterm labor is thought to be brought on by multiple mechanisms or pathways that may have been initiated weeks to months before the actual presence of clinical symptoms , 8. VariThe identification of risk factors for predicting preterm birth is advantageous because it allows for the initiation of risk-specific treatment for at-risk women and these risk factors may provide insights into a better understanding of the mechanisms leading to preterm birth , 23. HowBiomarkers of sPTB are divided into mechanistic pathways and they include intrauterine infection and inflammation, extracellular matrix degradation, fetal stress, fetal anomalies, and estrogen metabolism pathways .Bacterial vaginosis (BV) is an alteration of the maternal vaginal flora in which normal lactobacilli are replaced by Gram-negative anaerobic bacteria  and diagα [TNF-α], and C-reactive protein [CRP]) have been evaluated as biomarkers in subsequent sPTB.Intrauterine infection is an important mechanism leading to preterm birth . BacteriInterleukin-6. IL-6, a proinflammatory cytokine, is a major mediator of host response to inflammation and infection. It can be analyzed from samples of maternal cervical fluids or serum and to date, IL-6 is one of the most well-studied biomarkers of sPTB [ of sPTB . In a ne of sPTB , cervica of sPTB , an incr of sPTB  further Evidence in the literature to date has not shown serum IL-6 to be a useful biomarker in predicting sPTB for asymptomatic women. Paternoster et al.  and KramC-Reactive Protein. C-reactive protein (CRP) is a maternal systemic inflammatory marker that has been evaluated in the literature as a potential marker for preterm birth. In a prospective nested case-control study, Hvilsom et al. [μg/mL (at 75th percentile) to 16.4 μg/mL (at 95th percentile), and elevated CRP concentrations in maternal serum (≥85th percentile) increased the risk of sPTB  compared to lower CRP concentrations (<85th percentile). In a subgroup analysis, women without a previous preterm birth but with CRP levels at the 90th percentile and the 95th percentile had an increased risk of sPTB  compared to women with CRP levels at <75th percentile. Catov et al. [μg/mL obtained <21 weeks of gestation) in asymptomatic women. Likewise, Riboni and colleagues [μg/mL) collected in mid-second trimester. Other studies, in contrast, showed weak [m et al.  examinedv et al.  reportedlleagues  found anwed weak  to no efwed weak  of elevaOther Inflammatory Cytokines, Tumor Necrosis Factor- α. In addition to the evaluation of IL-6 and CRP in predicting subsequent preterm birth, few earlier studies also evaluated the association between other common cytokines IL-1, IL-2, IL-8, and TNF-α but there was no evidence suggesting that elevated cytokine values were associated with an increased risk of sPTB [ of sPTB –31, 34.The presence of fetal fibronectin, thus far, is the most effective biochemical marker for predicting preterm birth , 35–39. The association between the presence of fetal fibronectin and sPTB in asymptomatic women was further examined in a meta-analysis by Honest et al. . The likThe fetal fibronectin test can be performed as a single test or in series. A sample is collected from the posterior vaginal fornix and cervix with a sterile swab and the sample is then placed in a buffer solution and shipped to the laboratory for assay. Ideally, this test should be used in clinical settings in conjunction with patient medical history and other clinical information to assess overall risk of sPTB.Corticotropin-releasing hormone (CRH) is expressed by the human placenta and the fetal membranes, and its highest level of production is seen during the third trimester . In a reIn contrast, analysis from a nested case-control study of 254 asymptomatic women showed that elevated maternal plasma CRH (>90th percentile) at 28 weeks of gestation was associated with sPTB at <35 weeks  but high levels of CRH at 24 or 28 weeks of gestation did not predict sPTB at <32 weeks of gestation or <37 weeks of gestation . A studyβ-human chorionic gonadotropin (hCG) and α-fetoprotein to be associated with an increased risk of sPTB in cervicovaginal fluids among asymptomatic pregnant women [α-fetoprotein were also associated with predicting early and late preterm births. Moawad et al. [α-fetoprotein at 24 and 28 weeks of gestation and subsequent sPTB. For α-fetoprotein measured at 24 weeks of gestation, elevated values (>90th percentile) were found to increase the risk of spontaneous preterm birth at <32 weeks  and for sPTB at <35 weeks . The levels of α-fetoprotein measured at 28 weeks of gestation were also associated with subsequent sPTB, but the effect estimates were weaker for subsequent sPTB.Several earlier studies have identified elevated levels of nt women , 31, 48.nt women . Elevated et al.  conducteEstriol is the major form of circulating estrogen during pregnancy  and measα-fetoprotein, and granulocyte colony-stimulating factor) had a collective sensitivity of 81% and specificity of 78% for the prediction of spontaneous preterm birth at <32 weeks of gestation and 60% sensitivity and 73% specificity for the prediction of spontaneous preterm birth at <35 weeks of gestation.In addition to examining individual biochemical markers for predicting preterm birth, there is a growing interest in developing assessment tools using multiple markers. Given the heterogeneity of pathways leading to spontaneous preterm birth, multiple markers increase sensitivity of prediction by combining risk predictors that address diverse causes of spontaneous preterm birth . In a neAlthough a number of individual or set of multiple biomarkers for sPTB have been explored and examined, high intra-individual variability makes accurate prediction and subsequent prevention of preterm birth challenging. Advances in molecular biology and improved sophistication in methodology and technology of genomics have allowed for many investigators to turn their focus on the functional contributions of genetic variants to better understand preterm birth overall, but more importantly, the racial disparity of preterm birth –58. AccoAlthough medical advances have improved the survival of preterm infants and the treatment of short- and long-term morbidities, little success has been attained in understanding and preventing preterm birth. Great efforts have been spent to characterize and define the utility of biologic fluids from various sources in predicting sPTB. Not only does identifying biochemical markers that are associated with sPTB allow researchers to gain a better understanding on the underlying mechanisms or pathways leading to preterm birth, but also, this valuable tool can guide in designing the most effective targeted intervention strategies aimed at women at risk for preterm birth.α-fetoprotein, in addition to fetal fibronectin, as potentially promising biochemical markers; however, little information on the sensitivity, specificity, and positive predictive value is known at this time to determine the clinical usefulness of these markers.Many studies have evaluated the association between individual or group biochemical marker(s) and sPTB among asymptomatic women; to date, results of a number of biochemical markers remain inconsistent. Understanding sPTB is challenging due to its multifactorial etiologies and pathophysiologic heterogeneity. Limitations from past studies on biomarkers of sPTB including the identification of appropriate study population (low risk versus high risk asymptomatic women), gestational age at the time of specimen collection, timing of collection relative to time of pregnancy outcome, and the definition of study outcome  may lead to discrepant findings. Furthermore, practicality and acceptability and maternal and fetal risks also are of great concern. In reviewing the literature, fetal fibronectin , thus far, is most effective in predicting sPTB in asymptomatic women. Along with its relatively high sensitivity, the required specimen collection procedure is minimally invasive and poses little to no maternal and fetal risks; the reliance of fetal fibronectin as a screening tool in clinical settings is justifiable in the management and for providing timely interventions for women with positive results. Cervical length, a biophysical marker measured by transvaginal ultrasound (not reviewed here), has been promoted by the medical community as a valuable screening tool for sPTB. While no evidence to date has suggested one marker outperforming another, fetal fibronectin and cervical length can be useful independently or jointly according to woman's a priori risk status for sPTB. Evidence in the current literature also has indicated cervical IL-6 and Additional research that improves understanding of the mechanisms of preterm birth is important. In addition to the development and validation of multiple biochemical markers to be used independently or in conjunction with other clinical and biophysical markers, demographic, and behavioral risk factors, future work in this area should include further refinement of study design and methodology in the evaluation of gene-gene and gene-environment interaction studies and the role of epigenetics in predicting sPTB across diverse populations.


However, there remains uncertainty about the effects of in utero exposure to HAART is associated with low birth weight and/or preterm birth in a population of South African women with advanced HIV disease. A retrospective observational study was performed on women with CD4 counts ≤250 cells/mm3 attending antenatal antiretroviral clinics in Johannesburg between October 2004 and March 2007. Low birth weight (<2.5 kg) and preterm birth rates (<37 weeks) were compared between those exposed and unexposed to HAART during pregnancy. Effects of different HAART regimen and duration were assessed.Our objectives were to investigate whether 3 increase, 95% CI 0.45-0.71, p < 0.001) and preterm birth . HAART exposure was associated with an increased preterm birth rate , with early nevirapine and efavirenz-based regimens having the strongest associations with preterm birth .Among HAART-unexposed infants, 27% (60/224) were low birth weight compared with 23% (90/388) of early HAART-exposed (exposed <28 weeks gestation) and 19% (76/407) of late HAART-exposed (exposed ≥28 weeks) infants (p = 0.05). In the early HAART group, a higher CD4 cell count was protective against low birth weight (AOR 0.57 per 50 cells/mmin utero HAART exposure was not associated with low birth weight. An association between NNRTI-based HAART and preterm birth was detected, but residual confounding is plausible. More advanced immunosuppression was a risk factor for low birth weight and preterm birth, highlighting the importance of earlier HAART initiation in women to optimize maternal health and improve infant outcomes.In this immunocompromised cohort,  Approximately one-third of women attending antenatal clinics in Gauteng Province are HIV infected . Use of Many European studies have detected an association between protease inhibitor-based HAART and preterm birth ,5, while3 or an AIDS-defining illness. Further, clade C is the most common HIV strain in the country, and HIV is predominately acquired during heterosexual sex, with insignificant parenteral transmission.Moreover, in these studies, many women acquired HIV from intravenous drug use, and a large portion smoked during pregnancy, making it difficult to directly compare these populations with those in low- and middle-income countries . In SoutThere is limited evidence about HAART and birth outcomes in Africa. A study in Abidjan, Côte d'Ivoire, compared women eligible for HAART from two cohorts, each with approximately 150 women . Low birWe previously examined the effects of different HAART regimens and duration of therapy on risk for MTCT , and nowThis study reports on a retrospective observational cohort of women attending integrated antenatal and antiretroviral (ANC-ARV) clinics at Rahima Moosa Mother and Child Hospital (RMH) and Charlotte Maxeke Johannesburg Academic Hospital (CMJH). Both clinics are referral centres for HIV-infected pregnant women in Johannesburg, but the latter provides care for patients with more complex medical conditions.3. CD4 cell counts were taken before HAART initiation for the HAART-exposed group, and during pregnancy or within three weeks postpartum for the HAART-unexposed group. Women attending the postnatal clinic between three weeks and two months after childbirth were included if they had a CD4 count result from during pregnancy. Most of the comparison group (HAART-unexposed women) had not received antenatal HAART because they were identified as HIV positive during labour or in the postnatal period (within three weeks of childbirth).Women attending ANC-ARV clinics at the hospitals and all mother-infant pairs at the postnatal clinic of RMH were eligible for the study if they: were HIV positive; had a singleton delivery between October 2004 and March 2007; attended an ANC-ARV clinic during pregnancy or the postnatal clinic less than two months postpartum; and had a CD4 count of ≤250 cells/mmWomen gave consent for their data to be included in the clinic database and used for research purposes. The study protocol was approved by the Human Research Ethics Committee of the University of the Witwatersrand (protocol number M070438).HIV status was determined with parallel rapid HIV tests . CD4 cell count was measured using a Beckman Coulter Epics XL MCL cytometer  or Beckman Coulter TQ PREP . HIV infection status was diagnosed in infants of more than six weeks of age with a DNA polymerase chain reaction (PCR) .At RMH, most pregnant women eligible for HAART initiated lopinavir/ritonavir, stavudine and lamivudine. First-line therapy at CMJH consisted of nevirapine, stavudine, and lamivudine. In both hospitals, efavirenz was initiated after the first trimester for women taking concomitant tuberculosis (TB) treatment. Women presenting in the first trimester of pregnancy who were receiving efavirenz-containing regimens were changed to lopinavir/ritonavir, while women beyond the first trimester continued efavirenz-based therapy. The HAART regimen was categorized by first regimen used in pregnancy.The primary aim of our study was to investigate the association between LBW, and HAART duration and regimen during pregnancy. LBW was defined as a birth weight below 2.5 kg and very low birth weight (VLBW) as less than 1.5 kg. For the study, early HAART was defined as initiation before 28 weeks of pregnancy and late HAART as initiation at ≥28 weeks of pregnancy. A secondary aim of the study was to examine associations between preterm birth and HAART exposure, with similar analyses of regimen type and duration. Preterm birth was defined as birth before 37 completed weeks of pregnancy and extremely preterm birth was defined at birth before 34 weeks of pregnancy.th percentile of expected weight for gestational age, birth weights above the 90th percentile as large for gestational age, and those between the 10th and 90th percentiles as appropriate for gestational age ) compared with nevirapine (20% [31/158]) and protease inhibitor-based regimens . There were no differences in rates of LBW by regimen in the late HAART group , and longer median weeks on HAART .Given that this initial analysis showed higher rates of LBW in women receiving efavirenz-based regimens from early in pregnancy, we compared characteristics of women in this group with women taking other regimens. Women taking early HAART and receiving efavirenz had higher rates of TB compared with those on nevirapine and protease inhibitor-based therapy , lower median CD4 counts . Rates of VLBW infants were similar in the early and late HAART groups and for all HAART regimens. Seven of the infants had known maternal risk factors for VLBW, including maternal history of previous miscarriage, previous preterm delivery, or hypertension. One infant in this group was HIV infected.Overall, only 2% (26/1228) of all infants in the cohort were classified as very low birth weight (VLBW). More HAART-unexposed than exposed infants were VLBW . The mean CD4 cell count of the VLBW group did not differ from the remainder of the cohort . There was a trend towards hypertension being associated with increased odds of LBW . In multivariate analysis, the effect of efavirenz exposure was removed , and unexpectedly, nevirapine-based HAART was associated with a reduced odds of LBW compared with HAART-unexposed women . Similar results were found in multivariate analysis of associations between HAART groups and LBW when modelling was restricted to only HIV-negative infants (data not shown).In univariate analysis evaluating associations between HAART and LBW, including both HIV-positive and HIV-negative infants, no significant associations were detected in the late HAART group Table . HoweverThe overall rate of preterm birth in the cohort was 13.3% (145/1093). Rates were higher among women exposed to HAART during pregnancy than those unexposed . In the analysis of early versus late HAART, infants whose mothers initiated treatment before 28 weeks had a higher rate of preterm birth compared with after 28 weeks . HAART exposure was not associated with increased rate of extremely premature birth .3 rise in maternal CD4 cell count was associated with a 31% decrease in the odds of preterm birth , in the early HAART group, every 50 cells/mmThe rate of LBW in this cohort (22%) was higher than the rate of 15% reported by UNICEF for all South African infants, regardless of HIV exposure . Many of3) confers increased risk for low birth weight, and initiation of treatment reduces this risk. There could also be site-specific reasons why non-nucleoside reverse transcriptase inhibitors (NNRTIs) and not PIs were significant in this analysis. Women who initiated NNRTIs tended to be from CMJH, which handled more complicated pregnancies [Unexpectedly, in the early HAART group, rates of LBW were lower in women on nevirapine-based HAART than in untreated women. Nevirapine has previously been associated with increased risk of LBW , as wellgnancies ,23.3).HAART-unexposed women had a high rate of LBW (27%) despite a relatively low preterm birth rate (5%). This might be explained by potential selection biases (discussed later). Additionally, HAART-unexposed women likely had a high risk of intra-uterine growth retardation due to their untreated advanced HIV infection with resultant immunological dysfunction ; however, in multivariate analysis, there was only a small attenuation in the odds ratio (from 6.4 to 5.6), and residual confounding may be present, particularly given the lack of data on TB among women in the cohort.3, reducing the confounding caused by large differences in the degree of immunosuppression.The finding of an association with early PI exposure during pregnancy and preterm birth is similar to many previous studies. In these studies, PI-based regimens were often prescribed for women with more advanced HIV disease, making it difficult to disentangle the role of HAART regimen and stage of disease on infant outcome. In our study, all women had CD4 counts <250 cells/mmAdditionally, the only PI used in our cohort was lopinavir/ritonavir as compared with previous studies evaluating unboosted PIs ,10. Our Information was only collected from women who were willing to be included in the clinics' databases. Characteristics of women declining participation may differ from those giving consent, thereby introducing selection bias. Also, bias was potentially introduced by the selection strategy for the control group (HAART-unexposed women), as these women received less antenatal care and had poorer health-seeking behaviours than their HAART-exposed counterparts. These factors could, in part, account for the higher rate of LBW in the HAART-unexposed group.Also, as the HAART-unexposed group were recruited postpartum, it is possible that a high mortality among infants born very preterm in this group partly explains the relatively low preterm birth rate (5%) noted in these women. Similarly, differences in how gestational age was assessed might have biased estimates of foetal age. HAART-unexposed women were more likely to have missed antenatal care, and have gestation determined by examination of infants at birth.in utero. Since more HAART-exposed than unexposed infants were born preterm, this factor is unlikely to have affected the study outcomes.The study design also has inherent limitations as preterm delivery might have occurred before HAART could be initiated. This could conceivably have spuriously elevated the preterm birth rate among HAART-unexposed infants, who would have received "late HAART" had they remained A considerable amount of data are missing for some study variables, mostly as the study was conducted within routine clinical settings and in two sites that collected different data. TB information was only available from CMJH women, and those exposed to early efavirenz-based HAART had the highest rates of TB as this regimen was specifically used with TB co-infection to minimize drug interactions. Because TB has been associated with intrauterine growth restriction and preterm birth ,29, incoSince haemodilution during pregnancy is associated with spuriously low CD4 cell counts, women whose CD4 counts were measured postpartum (mainly HAART-unexposed women) were potentially more immunologically suppressed than the HAART-exposed group.Differences in HAART prescribing protocols at CMJH and RMH could have affected the study outcomes. Women from CMJH tended to have more complicated pregnancies, for example, more frequent use of alcohol, higher rates of maternal hypertension or diabetes, and previous miscarriage. Baseline CD4 cell counts, however, were similar between the two hospitals. We were unable to include clinic site in the multivariate models due to its co-linearity with drug regimen.It is hard to differentiate the effects of maternal HIV disease and that of HAART exposure on infant outcomes. Indeed, the improvement in immune status of the HAART-exposed women probably contributed to increasing infants' birth weights. However, improved maternal immune status would not explain the higher preterm birth rate in the HAART-exposed as compared with the unexposed women, which seems independent of HIV disease stage and might be due to HAART exposure or to the potential biases we have described. Finally, it is important to note that the findings of this study are likely to pertain only to women with marked immunological suppression, and may not extend to women with less advanced HIV disease.3 associated with considerably reduced risk of both adverse outcomes. This finding highlights the importance of early HIV diagnosis and staging during pregnancy to accelerate HAART initiation in women who qualify.In this cohort of immunocompromised women from South African antenatal clinics, HAART exposure was not associated with LBW; the strongest predictor of LBW was lower maternal CD4 cell count. Early HAART exposure to any regimen and low maternal CD4 cell count were associated with increased rates of preterm birth. Of note, in this cohort, immunosuppression emerged as an important risk factor for both LBW and preterm birth, with every gain of 50 cells/mm3 may help minimize adverse pregnancy outcomes related to immune compromise [The recent South African guideline change to increase the CD4 count treatment threshold to 350 cells/mmmpromise . FurtherAIDS: Acquired immunodeficiency syndrome; ANC-ARV: Antenatal and antiretroviral (clinic); AOR: Adjusted odds ratio; CMJH: Charlotte Maxeke Johannesburg Hospital; CI: Confidence interval; HAART: Highly active antiretroviral therapy (triple therapy); HIV: Human immunodeficiency virus; LBW: Low birth weight (less than 2.5 kg); MTCT: Mother to child transmission (of HIV); NNRTI: Non-nucleoside reverse transcriptase inhibitor; PCR: Polymerase chain reaction; PI: Protease inhibitor (lopinavir/ritonavir in this study); RMH: Rahima Moosa Mother and Child Hospital; SD: Standard deviation; TB: Tuberculosis; UNICEF: United Nations Children's fund; VLBW: Very low birth weight (less than 1.5 kg).The authors declare that they have no competing interests.KV conceived of the study. KV, AC, HR, MC and VB participated in study design. VB and KV collected data. MC performed the statistical analysis. MC, KV and RH analyzed data. KV, RH, VB, MC and HR wrote and edited the manuscript. All authors read and approved the final manuscript.KV: MBBCH (Wits), DCH (SA), Dip HIV Man (SA), MSc (Wits)RH: MD, MPHVB: BSc (Wits), MBBCh (Wits), DTM&H (SA), Dip HIV Man (SA)MC: MBBCh (Wits) MSc (LSHTM) PhD (U.Gent) DFPH (UK)AC: MB.ChB. (UNZA), DCH (SA), Dip HIV Man (SA) FCP (SA) PaedHR: MBBChir (CANTAB MA (CANTAB) MRCGP (UK) DCH (SA) DRCOG (UK)


There has been a complete turnaround in scientific thinking about malnutrition as a protective factor to that of a major determinant of diabetes. Development of Type 2 diabetes is attributed to a combination of genetic susceptibility and precipitation factors in adult or early adult life. Current trials and preventive interventions are based on this gene-obesity model causing glucose intolerance necessitating food restriction for management. However when we compare the burden of low birth weight and intrauterine growth restriction with that of type 2 diabetes it can be hypothesised that good nutrition during intrauterine development and early childhood is more important. Foetal programming due to under nutrition can result in intergenerational transfer of long latency disorders.This hypothesis led to the establishment of the Pune maternal nutrition study and Pune children study involving cohorts. The Pune children study involving 400 children has completed 21 years of follow up and has shown an inverse relationship between birth weight and risk of diabetes mellitus measured by high glucose and high insulin levels. The maternal nutrition study which started with 2675 pregnant women in six villages has now completed 17 years. Both the mothers and children are being followed with very good follow up rates. The study involved consensus building among village leaders, consultation of experts, focus group discussions and training of local girls as Auxiliary Nurse Midwives (ANMs). The study involves assessment of weight and haemoglobin of young women, nutritional intake during pregnancy, foetal growth monitoring, biochemical assessments, storage of maternal and cord blood samples, detailed anthropometry at birth and continuing monitoring for cardiovascular disease risk markers. A steering committee of all stakeholders was constituted to oversee the study. The observations have shown that the intra abdominal fat content of Indian babies is higher. Low vitamin B12 levels, folate levels and high homocysteine levels are shown to be associated with low birth weight and insulin resistance in offspring. This demonstrates that maternal micro nutrient status influences risk of diabetes in the offspring and birth weight is a marker of intrauterine environment. Policy implications include ensuring the health of the young girl and addition of vitamin B12 along with folate for pregnant women. The biochemical estimation was made possible by storage of samples in biobanks which is a most useful resource for subsequent measurements, but there are ethical concerns and issues of subject approval.


Although linear growth during childhood may be affected by early-life exposures, few studies have examined whether the effects of these exposures linger on during school age, particularly in low- and middle-income countries.We conducted a population-based longitudinal study of 256 children living in the Brazilian Amazon, aged 0.1 y to 5.5 y in 2003. Data regarding socioeconomic and maternal characteristics, infant feeding practices, morbidities, and birth weight and length were collected at baseline of the study (2003). Child body length/height was measured at baseline and at follow-up visits (in 2007 and 2009). Restricted cubic splines were used to construct average height-for-age Z score (HAZ) growth curves, yielding estimated HAZ differences among exposure categories at ages 0.5 y, 1 y, 2 y, 5 y, 7 y, and 10 y.P = 0.017), and children whose families owned land were 0.34 Z taller by age 10 y (P = 0.023), when compared with poorer children. Mothers in the highest tertile for height had children whose HAZ were significantly higher compared with those of children from mothers in the lowest height tertile at all ages. Birth weight and length were positively related to linear growth throughout childhood; by age 10 y, children weighing >3500 g at birth were 0.31 Z taller than those weighing 2501 g to 3500 g (P = 0.022) at birth, and children measuring ≥51 cm at birth were 0.51 Z taller than those measuring ≤48 cm (P = 0.005).At baseline, median age was 2.6 y , and mean HAZ was −0.53 ; 10.2% of children were stunted. In multivariable analysis, children in households above the household wealth index median were 0.30 Z taller at age 5 y (Results suggest socioeconomic background is a potentially modifiable predictor of linear growth during the school-aged years. Maternal height and child’s anthropometric characteristics at birth are positively associated with HAZ up until child age 10 y. Linear growth during childhood may be influenced by the cumulative effects of many environmental exposures, including nutritional, psychosocial, and infectious factors . It is eStudies of the determinants of linear growth have focused largely on the period before the age of 5 y -8. Howev2. Child health indicators in Acrelândia are significantly lower than the country average: infant mortality rate was 71/1000 live births, and the Human Development Index was 0.680 according to data from 2000 [This longitudinal study was conducted in Acrelândia, a town located 100 km from Rio Branco, the capital of the state of Acre, in northwest Brazil. Acrelândia is a frontier town inhabited by migrants from southeast and south Brazil who are engaged in commercial agriculture and cattle raising. In 2003, the city had 8697 inhabitants (43% residing in the urban area), covering a territory of 1607.5 kmIn January 2003, we performed a population-based cross-sectional study in the urban area of Acrelândia . All houAs previously reported , in DeceChildren included in the analyses were not different from those who were not included in terms of sex, age, length/height, and the socioeconomic, maternal, and child characteristics investigated. Written informed consent for participation was obtained from parents or guardians before enrollment. This study was approved by the ethical review board of the School of Public Health, University of São Paulo, Brazil.At baseline of the study (2003), trained fieldworkers performed structured face-to-face interviews with each child’s mother or guardian during household visits. The following data were collected: demographic characteristics , socioeconomic status  and access to public services , maternal characteristics , child characteristics at birth , infant feeding practices (child’s age at introduction of weaning foods), and morbidity .Trained research assistants obtained anthropometric measurements from the children at a local Family Health Clinic (in 2003 and 2007 surveys) or at the households (in 2009), using standardized procedures and calibrated equipment . The datThe main outcome of interest was length/height-for-age and sex Z score (HAZ). HAZ was calculated according to the World Health Organization (WHO) Child Growth Standards  for chilPredictors of interest included maternal and household sociodemographic characteristics, child anthropometry at birth, infant feeding practices, and morbidities at baseline. A wealth index based on the presence of 14 home appliances was used to assess socioeconomic status . PrincipWe first compared the distribution of HAZ by categories of socioeconomic, maternal, and child characteristics at baseline, using tests of trend for ordinal predictors and the mean-comparison t-test for dichotomous predictors. We also examined the prevalence of stunting in relation to baseline characteristics using the Cochrane-Armitage and chi-square tests for ordinal and dichotomous variables, respectively.Subsequently, the associations of socioeconomic, maternal, and child characteristics with linear growth were assessed by estimating average HAZ-for-age growth curves for each category of the predictors of interest, using mixed-effect models for repeated measurements with restricted cubic splines. Cubic splines represent non-linear terms for age at each assessment that allow the smoothing of the relation between HAZ and age. Piecewise cubic polynomials are smoothly joined at joint points or “knots” . In thisP < 0.100) was an additional criterion for retaining a variable in the model at each level of determination.We obtained adjusted mean HAZ-for-age curves using multivariable mixed-effect models based on a hierarchical conceptual framework as proposed by Victora et al . The folP values are two-tailed. We used SAS 9.2  for all analyses.For both unadjusted and adjusted analyses, we estimated HAZ from the growth curves at ages 6 mo, 12 mo, 2 y, 5 y, 7 y, and 10 y, as the predicted values of the spline function, with values of predictor covariates at the reference category. Differences in the estimated values of HAZ and their 95% confidence intervals (CI) were calculated among the categories of each predictor at these ages. All reported Median age at recruitment was 2.6 y , 52.7% of the children were female, and 88.1% were mulatto. At baseline, mean HAZ was −0.53 , and 10.2% of the children were stunted. In 2003, HAZ was positively associated with wealth index, maternal education and height, non-smoking during pregnancy, and child’s birth weight and length. No association with child’s sex was observed , during which time a median of three height measurements was collected for each child . We estimated an average HAZ-for-age curve for the study population  compared with children from households below the median. Land ownership was positively related to HAZ during the school-aged years; by age 10 y, children whose families owned land were 0.34 Z taller (P = 0.023) than children from landless families. Inclusion of mother’s educational level did not appreciably change the estimates, and, after adjusting for socioeconomic variables, access to public services was not found to be related to HAZ.After multivariable adjustment, wealth and land ownership remained significantly related to HAZ Table . At agesMaternal height was related to HAZ at all ages. Mothers in the highest tertile of height had children whose HAZ was significantly higher compared with those of children whose mothers were in the lowest height tertile after adjusting for socioeconomic status. Smoking during pregnancy was not related to growth in height after adjusting for other covariates.P = 0.022) than those who weighed 2501 g to 3500 g. However, low-birth-weight babies were not significantly shorter than normal-weight babies after age 2 y. Shorter babies remained short during the school-aged years; the HAZ difference between extreme tertiles of birth length was 0.51 by age 10 y (P = 0.005). In a subsample comprising of 168 children with both birth weight and birth length information, the association between birth weight and linear growth was attenuated after further adjustment for birth length. By age 10 y, the HAZ difference between children weighing >3500 g and children weighing 2501 g to 3500 g at birth decreased to 0.19 (P = 0.315).Birth weight and birth length were positively and significantly related to linear growth throughout childhood. By age 10 y, children weighing >3500 g at birth were 0.31 Z taller .Early introduction of cow’s milk and the occurrence of diarrhea were related to HAZ at 12 mo and 10 y, respectively, but these associations were not statistically significant . However, children included in the analyses were not statistically different from those who were not included with respect to sex, age, length/height, and the socioeconomic, maternal, and child characteristics at baseline. Another limitation is that we lacked information on child’s father. Birth weight and length were obtained from child health cards rather than through direct measurement by the research team. Nonetheless, there is evidence that these birth weight records have high validity in Brazil . There aIn conclusion, we found that socioeconomic background, a potentially modifiable factor, is a predictor of linear growth during the school-aged years, and maternal height and infant characteristics at birth influence growth throughout childhood. Because height measured during late childhood is highly correlated with adult height, interventions to enhance population health should begin by focusing on distal determinants of linear growth and consider social inequalities in early life.The authors declare that they have no competing interests.BHL contributed to the study design and data collection; BHL, EV, and RAA participated in statistical data analyses; BHL conducted data analyses, interpreted results, and wrote the initial draft of the manuscript; MAC implemented and supervised all study protocols and was responsible for project management; BHL, EV and MAC participated in data interpretation and were involved in the review of the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/12/265/prepub


Children born small for gestational age (SGA) experience higher rates of morbidity and mortality than those born appropriate for gestational age. In Latin America, identification and optimal management of children born SGA is a critical issue. Leading experts in pediatric endocrinology throughout Latin America established working groups in order to discuss key challenges regarding the evaluation and management of children born SGA and ultimately develop a consensus statement.SGA is defined as a birth weight and/or birth length greater than 2 standard deviations (SD) below the population reference mean for gestational age. SGA refers to body size and implies length-weight reference data in a geographical population whose ethnicity is known and specific to this group. Ideally, each country/region within Latin America should establish its own standards and make relevant updates. SGA children should be evaluated with standardized measures by trained personnel every 3 months during year 1 and every 6 months during year 2. Those without catch-up growth within the first 6 months of life need further evaluation, as do children whose weight is ≤ -2 SD at age 2 years. Growth hormone treatment can begin in SGA children > 2 years with short stature (< -2.0 SD) and a growth velocity < 25th percentile for their age, and should continue until final height (a growth velocity below 2 cm/year or a bone age of > 14 years for girls and > 16 years for boys) is reached. Blood glucose, thyroid function, HbA1c, and insulin-like growth factor-1 (IGF-1) should be monitored once a year. Monitoring insulin changes from baseline and surrogates of insulin sensitivity is essential. Reduced fetal growth followed by excessive postnatal catch-up in height, and particularly in weight, should be closely monitored. In both sexes, gonadal function should be monitored especially during puberty.Children born SGA should be carefully followed by a multidisciplinary group that includes perinatologists, pediatricians, nutritionists, and pediatric endocrinologists since 10% to 15% will continue to have weight and height deficiency through development and may benefit from growth hormone treatment. Standards/guidelines should be developed on a country/region basis throughout Latin America. Low birth weight < 2500 g) is prevalent in many countries and poses a significant public health problem contributing to a variety of short- and long-term negative effects. While about half of low-birth-weight infants in the industrialized world are born preterm (< 37 weeks' gestation), most of these infants are born full term in the rest of the world . The Uni500 g is Higher rates of morbidity and mortality are more likely in children of low birth weight or born small for gestational age (SGA) than children born appropriate for gestational age (AGA) -5. HenceThe development of the 2007 consensus statement on the management of children born SGA by the International Societies of Pediatric Endocrinology and the Growth Hormone Research Society  promptedThe definition of SGA is unclear. The World Health Organization (WHO) defines children born SGA or after intrauterine growth retardation (IUGR) as those with birth weight below the 10th percentile of the recommended gender-specific birth weight for referenced gestational age. Where gestational age is not available, the birth weight of < 2500 g should be considered low birth weight . This deFor the purpose of this consensus, an SGA child is a child whose birth weight and/or birth length is at least 2 standard deviations (SD) below the mean for its gestational age .Notably, we recommend that the term SGA not be used as a synonym for IUGR. The term IUGR refers to insufficient growth of the fetus and should only be used if at least 2 assessments of intrauterine growth are available and the fetus is not growing appropriately. SGA refers to body size--a low weight and/or length for a known gestational age--and is preferred in the absence of information about fetal growth.Although many countries lack data on the actual incidence of children born SGA, there have been estimates ranging from 2.3% (< -2 SD) to 10% (< 10th percentile), depending on the definition used . In LatiConsidering the high morbidity and mortality rates in this population, prompt identification is critical. SGA newborns are 5 times more likely to die in the neonatal period and 4.7 times more likely to die in their first year of life . PrematuAccurate determination of gestational age is essential for a diagnosis of SGA. The menstrual history of the mother and the use of ultrasound, usually in week 16 of gestation, increase the accuracy of the estimation. When this information is not available, physical examination of the newborn can be helpful . Measuret al published refinements to these charts by recalculating percentiles and lambda-mu-sigma (LMS) values from birth to maturity and incorporating updated WHO data from birth to age 2 years  for injection) was approved by the US Food and Drug Administration (FDA) in July 2001 for the long-term treatment of growth failure in children born SGA who did not have sufficient catch-up growth by age 2 years ,41,42. TIn Europe, GH treatment was approved by the Committee for Proprietary Medicinal Products (CPMP) in June 2003 for children born SGA (birth weight and length < -2 SD) with short stature  and who fail to show catch-up growth by age 4 years or older .Argente and colleagues recently analyzed the outcome of very young SGA children, between ages 2-5 years, treated with GH . They reA clear dose-dependent increase in height velocity has been observed in children born SGA during the first years of treatment ,45. OptiBaseline studies including hormonal  and metabolic measurements  are mandatory before initiation of GH treatment. Careful follow-up during GH treatment is recommended. The child should be evaluated every 3 to 6 months  by a physician experienced using GH to determine if dose adjustment is necessary . Blood gTreatment with GH should continue if a positive growth response is observed within the first year of treatment (height velocity > +0.5 SDS) . TreatmeContinuous GH therapy is not associated with serious adverse events in short children who are born SGA -51. HoweGH treatment does not appear to be associated with an increased risk of malignancy . It is rCurrent data with regard to initiation, tempo, duration, and progression of puberty in children born SGA are limited and difficult to compare due to the differences in methodologies in the available literature . Some studies show a normal but earlier pubertal development; however, others report a late pubertal start -63.In human models, decreased pubertal growth has been observed . In femaWith regard to the age of pubertal initiation, most studies report an age similar to that for children born AGA ; howeverMenarcheal age has also been reported as being earlier or within normal range ,66,71-75Although bone age assessment is used to evaluate skeletal maturity, it has been suggested that use of bone age for final height prognosis is of limited value in children born SGA and thus should be used with caution .SGA children without catch-up growth who are treated with GH have a normal pubertal timing and progression . HoweverGirls born SGA with catch-up growth present with lower insulin sensitivity, and there are data showing an increased incidence of adrenal and ovarian hyperandrogenism clinically evident as precocious pubarche ,78,79. HThere is a preliminary report which suggests that the early use of metformin at a perimenarcheal age in low-birth-weight girls with a history of precocious pubarche prevents progression to polycystic ovary syndrome (PCOS); improves insulin sensitivity; and normalizes body composition, lipid profiles and GH secretion . In a suLittle is known about the long-term effects of IUGR or being born SGA and their relationship to hypothalamic-pituitary-gonadal function in males . Low birA significantly increased risk of developing cardiovascular disease (hypertension and dyslipidemia) and type 2 diabetes during adulthood has been associated with low birth weight -54,94. TThe second alternative hypothesis is the fetal insulin hypothesis which proposes that genetically determined insulin resistance results in impaired insulin-mediated growth in the fetus, as well as insulin resistance in adult life . There iThe most plausible explanation of this association, however, is the catch-up growth hypothesis. Children born SGA may present with a decreased insulin sensitivity early in life ,99-101. The pathophysiological mechanisms of insulin resistance are possibly secondary to a relative prolonged nutritional deficiency in the fetus, during which time the fetal metabolism constantly readjusts to slow growth with relative resistance to insulin, IGF-1, and GH. When this "adaptation" is inconsistent with postnatal nutrition, it may be associated with a rapid weight gain during infancy, and may result in considerable adaptation that develops a cluster of signs of metabolic syndrome ,102 withThe efficacy of GH treatment in children born SGA has been confirmed by several series and by results in final height under continuous treatment with GH ,57,105. In view of the fact that a high percentage of individuals with glucose intolerance have a fasting blood glucose level below 100 mg/dL, the OGTT is applicable in children and adolescents with risk factors such as obesity, family history, and hypertension. However, we do not recommend this be indicated as a general complementary test for children born SGA, rather, it should be individualized for children with rapid weight gain, acanthosis nigricans, dyslipidemia (high triglycerides), or a significant family history of metabolic syndrome .Improvements in lipid profile and blood pressure associated with the metabolic syndrome in SGA children receiving GH treatment has also been reported . DetermiUse of available population-, ethnic-, or country-specific reference data for birth weight and length, if available, is important for identification of SGA. However, accurate measurement of weight, length, and head circumference and, particularly, accurate gestational dating are more essential to a correct diagnosis of SGA . In caseObstetricians/gynecologists should refer pregnancies with diagnosis of IUGR to a high-risk obstetric clinic with special care for certain diseases  in order to reduce the severity of IUGR and the frequency of children born SGA. Although high-risk clinics are usually located in big cities, public health organizations should be aware of the needs of these patients and develop special networks for them. Neonatologists should be alert for the possible consequences of acute fetal distress that may occur during labor and/or delivery by caesarian section of an SGA infant, in addition to all the known complications such as respiratory distress, hypoglycemia, and hypokalemia.A program for medical dissemination and training of multidisciplinary team members is an important next step. Training on the adequate management of SGA term and preterm newborns must be provided to pediatricians and neonatologists. Immediate, medium-, and long-term complications must be discussed, with an emphasis on growth problems and metabolic alterations that may develop. Pediatricians are encouraged to share their knowledge via multidisciplinary workshops. Furthermore, it would be important to provide written materials on the monitoring of adequate growth, the recovery phase, and follow-up in order to detect growth and metabolic alterations in these patients. Policies involving the primary care physician and pediatrician for detection and referral to a pediatric endocrinologist for the examination and treatment of growth and metabolic alterations in those born SGA should be developed.Most children born SGA recover from their weight and height deficiency. However, 10% to 15% of children born SGA will continue to have short stature. GH treatment benefits growth potential in short-stature children born SGA. In both sexes, gonadal function should be taken into account, especially during puberty. Reduced fetal growth followed by excessive postnatal catch-up in height, and particularly in weight, should be monitored. Excessive weight gain is most frequently associated with metabolic risk later in life. Finally, children born SGA should be carefully followed by a multidisciplinary group that includes perinatologists, pediatricians, nutritionists, and pediatric endocrinologists, in order to improve growth, glucose homeostasis, and gonadal function.• Local charts endorsed by local Pediatrics Associations are recommended. If local charts are not available, WHO growth charts may be used from birth until age 5 years, after which the WHO Reference 2007 is recommended.• Most infants born SGA recover from their weight and height deficiency.• GH treatment benefits growth potential in short-stature children born SGA.• Gonadal function in both sexes should be taken into account, especially during puberty.• Children born SGA should not be allowed to gain weight too rapidly or excessively in an effort to circumvent the development of metabolic disturbances.• Children born SGA should be followed carefully by a multidisciplinary group.• A program for medical dissemination and training of multidisciplinary team members is needed.Margaret CS Boguszewski is a member of the KIGS Strategic Advisory Board; she has no financial information to declare. Durval Damiani received less than $10,000 in honoraria from Pfizer Inc. This study was funded by Pfizer Inc.All other authors declare that they have no competing interests.All the authors participated in the consensus meeting to discuss and vote on recommendations. MB, VM, AB, and IB helped draft the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/11/66/prepub


However, with age and the onset of menopause, women’s cardiovascular risk eventually becomes similar to that of men. This change in risk may, in part, be attributable to a shift to a more atherogenic lipid profile. Our objective was to evaluate standard- and sub-lipid parameters and the apo A1 remnant ratio: (apo A1/[VLDLWomen (N=711) >50 years of age undergoing coronary angiography were evaluated. Baseline clinical and angiographic characteristics, lipids, and sub-lipid levels  were collected. Cox regression analysis, adjusted by standard cardiovascular risk factors, was utilized to determine associations of lipid and sub-lipid tertiles(T) with death/myocardial infarction at 1 and 3 years.3-C+IDL-C) measure, or any other well-known ratio .Patients averaged 67.7±9.4 years and 53.6% had underlying severe (≥70% stenosis) coronary artery disease. The apo A1 remnant ratio was found to have stronger associations for 1 year  and 3 year  death/myocardial infarction than any individual lipid  or sub-lipid (apo A1, apo B, VLDLThe apo A1 remnant ratio was a significant predictor of short and intermediate-term death/myocardial infarction risk among women >50 years of age. Furthermore, this ratio was found to have greater predictive ability than traditional lipid and sub-lipid parameters and represents a potential new risk marker. Coronary heart disease (CHD) is the leading cause of death among men and women, although the risk in women temporally lags behind that of men 1). Nevertheless, the median survival for a woman age 55 to 64 with a first myocardial infarction (MI) is only 13.3 years compared to 17 years for a man . Neverth,3. This While low-density lipoprotein cholesterol (LDL-C), an atherogenic lipoprotein, has been recognized as the target of lipid lowering therapy, it is not always indicative of atherogenicity. Other lipoprotein parameters  have been shown to be more atherogenic, particularly in women, including apolipoprotein (apo) B, intermediate-density lipoprotein cholesterol (IDL-C), and subfractions of very low-density lipoprotein cholesterol (VLDL-C) -11. In aGofman et al. first reported over 60 years ago that remnant lipoproteins were associated with the development of CHD . Remnant3-C+IDL-C]), which takes into account the importance of both apo A1 and remnant lipoproteins, with their association to death and myocardial infarction (MI) among peri and post-menopausal women. Furthermore, the utility of this new ratio was compared to traditional lipid parameters, apo A1, apo B, and the ratios total cholesterol to HDL-C (TChol/HDL-C), TG/HDL-C, apo B/A1, and HDL-C/(VLDL3-C+IDL-C).It is well recognized that HDL-C has a strong inverse association with adverse CHD events among women. However, clinical events continue to occur even in patients who achieve “target” levels. The Framingham Heart Study reported that 43% of clinical events occurred in women with an HDL-C ≥50 mg/dL . Also, a3-C+IDL-C): 6.6±3.6, TChol/HDL-C ratio: 4.3±2.8, VLDL3-C+IDL-C: 22.1±9.1, HDL-C/(VLDL3-C+IDL-C): 2.1±1.4, and LDL-C/HDL-C: 2.5±1.8. Triglycerides and the TG/HDL-C ratio were non-normally distributed and therefore, the median levels are reported: 133.0 mg/dL and 2.9, respectively. Patient characteristics for the cohort are shown in Table A total of 711 women met inclusion criteria and were evaluated for this study. Average lipid and lipoprotein levels among the entire cohort were (mg/dL): HDL-C: 48.3±15.6, LDL-C: 106.7±37.3, non-HDL-C: 136.5±41.3, apo B: 76.7±18.3, apo B/A1 ratio: 0.66±0.18, apo A1: 119.7±20.3, apo A1/(VLDL3-C+IDL-C) were significantly associated with increased risk at 3 years when compared to tertile 3. Though significance was not achieved at 1 year for death/MI for both apo A1 and HDL-C/(VLDL3-C+IDL-C), tertile 1 vs. tertile 3 had clinically meaningful hazard ratios . The remnants, VLDL3-C+IDL-C, were associated with 1 year death/MI for tertile 3 vs. tertile 1. Tertile 3 vs. tertile 1 for the apo B/A1 ratio was a significant predictor of death/MI at both 1 and 3 years. Longitudinal associations of tertiles of the apo A1 remnant ratio are displayed in Figure Lipoprotein ratios and individual particles were the best predictors of short-term 1 year) and intermediate-term 3 year) death/MI risk Table . After a year dea year andWe evaluated whether we could better stratify risk prediction beyond tertiles. Therefore, using recursive partitioning, we determined that the cutoffs of ≤3.5 , >3.5-6.0 , and >6.0  were the ideal categorizations for stratifying death/MI risk. The sensitivity and specificity at 3.5 (cutoff between categories 1 and 2) were 0.786 and 0.870 at 1 year and 0.80 and 0.872 at 3 year, respectively. For the cutoff of 6.0 (between categories 2 and 3), the sensitivity and specificity were 0.286 and 0.438 at 1 year and 0.270 and 0.452 at 3 years, respectively. Therefore, the categories were good discriminators between those at low and moderate-to-high risk. Baseline characteristics across categories of the apo A1 remnant ratio are shown in Table 3-C+IDL-C (r=-0.76) were significantly correlated with the apo A1 remnant ratio and therefore could not be evaluated in the multivariable model. Longitudinal associations for 1 year and 3 year death/MI are shown in Figure Figure 3-C+IDL-C]) is a strong predictor of death/MI at 1 and 3 years. This is seen among both tertiles, as well as from categories derived from recursive partitioning. Furthermore, this ratio had greater predictive ability than traditional lipid parameters, apo A1, apo B, and ratios such as TChol/HDL-C, TG/HDL-C, apo B/A1, and HDL-C/(VLDL3-C+IDL-C). The power of this ratio is related to both the numerator (apo A1) and the remnant denominator (VLDL3-C+IDL-C).This study presents for the first time in women greater than 50 years of age that the novel apo A1 remnant ratio /HDL-C, to be predictive of CHD [3-C+ IDL-C) ratio, though predictive, to not achieve the same degree of predictive significance as the apo A1 remnant ratio. These results reinforce the importance of measuring apo A1, potentially above that of HDL-C, for determining death/MI risk among women >50 years.We found low levels of apo A1 to be associated with an 80% increase in 1 and 3 year death/MI risk, whereas levels of HDL-C were found to not be predictive. The apo A1 remnant ratio utilizes the predictive value of apo A1, which was found to be highly predictive of death/MI by tertiles and by categories. We evaluated whether HDL-C would elicit similar results as apo A1 when divided by the remnant lipoproteins since a previous investigation found the inverse of this ratio,  study, the TG/HDL-C ratio was found to predict cardiovascular events and mortality among women without prior MI or coronary revascularization, but non-HDL-C, the TChol/HDL-C ratio, and total cholesterol were not . HoweverThe apo B/A1 ratio was shown in INTERHEART, a large, international case–control study, to be one of the most predictive parameters for identifying CHD risk . It was In a recent meta-analysis that evaluated 233,455 subjects with 22,950 events, apo B was found to be superior to non-HDL-C, which in turn was superior to LDL-C in predicting cardiovascular risk  . FurtherResults of this study seem to suggest that lipids, or some of their components, might not be the best indicator of increased risk and those with a greater concentration of denser, more atherogenic particles are at higher risk than in those with abnormal lipid concentrations. Therefore, the apo A1 remnant ratio may be a parameter that may better stratify risk of women >50 years so that those found in the higher risk categories can be more aggressively treated. Interventions may include earlier introduction or more aggressive lipid-lowering therapy. In this study, there was a significant difference between the use of lipid lowering medications among the categories at baseline, though lipid lowering use was adjusted for in the multivariable model, use of these medications could have affected which stratification, and thus risk of the patient. Future studies should evaluate longitudinal use of lipid lowering therapy on apo A1 remnant ratio levels. The apo A1 remnant ratio is indicative of the number of anti-atherogenic particles over the number of atherogenic particles. Thus, particle numbers and their ratios might be more important factors than the amount of lipids carried per particle.This study shares the limitations of all nonrandomized, observational studies, including the possibility of selection bias and unadjusted confounding. The population studied was high-risk , predominantly white, and women >50 years of age; thus these results may not apply to lower-risk populations, men, women ≤50 years, and other ethnic groups. The menopausal status in all women was not known; however approximately 80% of women over the age of 50 are either peri- or post-menopausal . TherefoThe new parameter, the apo A1 remnant ratio, was found to be a significant predictor of short-term and intermediate-term death/MI risk among women >50 years of age and was more strongly associated with death/MI risk than traditional lipid parameters, apo A1, apo B, and well-recognized lipid ratios. Further, this new ratio brings attention to the role of remnant lipoproteins in women greater than 50 years of age and represents a potential new measurement of risk. The apo A1 remnant ratio should be evaluated as a potential new treatment target and should be tested in a larger cohort and among other populations.Study patients were drawn from the Intermountain Heart Collaborative Study (IHCS) registry from March, 1999 to January, 2007 ,49. The The Intermountain Healthcare Urban Central Institutional Review Board approved this study.Lipid levels were obtained during angiography hospitalization at the discretion of the attending cardiologist. Total cholesterol and triglycerides were quantified using dry-slide measurement on the VITROS 950 Analyzer . HDL-C was measured with the same instrument following treatment with VITROS HDL-Cholesterol Magnetic Reagent. LDL-C and VLDL-C were calculated from the total cholesterol and triglyceride measurements.At the time of angiography, blood samples were collected in EDTA and refrigerated at 4°C. Within 24 hours, samples were centrifuged and plasma and DNA were separated and stored cryogenically. Cholesterol concentrations of lipoprotein classes and their subclasses were measured on samples obtained at angiography using single vertical spin density gradient ultra-centrifugation based on the Vertical Auto Profile  . Apo A1 3-C+IDL-C) higher levels are desirable. However, lower levels are desired for triglycerides, LDL-C, non-HDL-C, apo B, apo B/A1 ratio, TG/HDL-C ratio, VLDL3-C+IDL-C, TChol/HDL-C ratio, and the LDL-C/HDL-C ratio.Lipids and lipoproteins were evaluated as tertiles. Tertile stratifications for the different parameters are displayed in Table 2 used as a surrogate for waist circumference. Family history was patient-reported if a first-order relative had suffered cardiovascular death, MI, or coronary revascularization before age 65 years. Smoking included active smokers or those with a >10 pack-year history. Clinical presentation included stable angina , unstable angina (progressive symptoms or symptoms at rest), or acute MI (creatine kinase-MB >6 mg/dL and creatine kinase-MB index >3% or a troponin I level >0.4 ng/mL). Treatment type was defined as treatment with medication only, percutaneous coronary intervention, or coronary artery by-pass surgery. Admission and discharge medications  were also available.In addition to age and gender, patient information collected included diabetes status , hypertension , renal failure , hyperlipidemia , and congestive heart failure . The metabolic syndrome was defined using ATP III criteria , with BMSignificant CAD was defined as the presence of one or more ≥ 70% obstructive lesions by coronary artery angiography. Assessment of CAD was made by review of angiograms by the patient’s cardiologist, and results were entered into the computer database in a format modified after the coronary artery surgery study protocol . On the Average length of follow-up was 3.9±2.1 years. Events included the composite outcome of death and non-fatal MI at 1 and 3 years. MI was defined as a hospitalization where a patient had a troponin I level ≥0.4 ng/mL or a discharge diagnosis of an MI (ICD-9 code 410). Deaths were determined by telephone survey, hospital records, and Utah State Health Department records (death certificates) and were verified through Social Security death records. Patients not listed as deceased in any registry were considered to be alive.t test, and the analysis variance (ANOVA) were used to examine lipid and lipoprotein tertiles to baseline characteristics. To confirm the associations of the composite outcome of death/MI determined by univariable analysis, multivariable Cox hazard regression  was performed to determine hazard ratios (HRs). Kaplan-Meier survival estimates and the log rank test were used to determine initial associations with 1 and 3 year death/MI. Available baseline risk factors used in the modeling included age, gender, hypertension, hyperlipidemia, diabetes status, smoking, family history of CAD, renal failure, prior MI, prior cerebrovascular accident, congestive heart failure, presentation , number of vessels with stenosis ≥70%, and discharge medications. Final models entered significant (p<0.05) and confounding (10% change in beta-coefficient) covariables. The proportional hazards assumption was met for all models. Two-tailed p-values are presented with 0.05 designated as nominally significant.The chi-square test, Student’s Apo: Apolipoprotein; MI: Myocardial infarction; T: Tertile; CHD: Coronary heart disease; HDL-C: High-density lipoprotein cholesterol; LDL-C: Low-density lipoprotein cholesterol; IDL-C: Intermediate-density lipoprotein cholesterol; VLDL-C: Very low-density lipoprotein cholesterol; TG: Triglyceride; CAD: Coronary artery disease; TChol: Total cholesterol; IHCS: Intermountain Heart Collaborative Study; ACEI: Ace-inhibitors; ARB: Angiotensin receptor blocker; ANOVA: Analysis variance; HR: Hazard ratio; NCEP ATP: National Cholesterol Education Panel Adult Treatment PanelHTM: none. JRN: consultant for Atherotech. KRK: employee of Atherotech. JLA: none. BDH: none. TLB: none. JBM: none.HTM participated in the study design, performed the statistical analysis, and the writing of the manuscript. JRN participated in the study design and writing of the manuscript. KRK participated in the study design and critical revision of the manuscript. JLA participated in the critical revision of the manuscript. BDH participated in the critical revision of the manuscript. TLB participated in data acquisition and the critical revision of the manuscript. JBM participated in the study design and critical revision of the manuscript. All authors read and approved the final manuscript.