Electropermeabilization (EP) based protocols such as those applied in medicine, food processing or environmental management, are well established and widely used. The applied voltage, as well as tissue electric conductivity, are of utmost importance for assessing final electropermeabilized area and thus EP effectiveness. Experimental results from literature report that, under certain EP protocols, consecutive pulses increase tissue electric conductivity and even the permeabilization amount. Here we introduce a theoretical model that takes into account this effect in the application of an EP-based protocol, and its validation with experimental measurements. The theoretical model describes the electric field distribution by a nonlinear Laplace equation with a variable conductivity coefficient depending on the electric field, the temperature and the quantity of pulses, and the Penne's Bioheat equation for temperature variations. In the experiments, a vegetable tissue model (potato slice) is used for measuring electric currents and tissue electropermeabilized area in different EP protocols. Experimental measurements show that, during sequential pulses and keeping constant the applied voltage, the electric current density and the blackened (electropermeabilized) area increase. This behavior can only be attributed to a rise in the electric conductivity due to a higher number of pulses. Accordingly, we present a theoretical modeling of an EP protocol that predicts correctly the increment in the electric current density observed experimentally during the addition of pulses. The model also demonstrates that the electric current increase is due to a rise in the electric conductivity, in turn induced by temperature and pulse number, with no significant changes in the electric field distribution. The EP model introduced, based on a novel formulation of the electric conductivity, leads to a more realistic description of the EP phenomenon, hopefully providing more accurate predictions of treatment outcomes. Exposure of biological membranes to specific pulsed electric fields induces the rise (permanent or transient) of membrane permeability, which is called electropermeabilization (EP) or electroporation. EP phenomenon is exploited in electrochemotherapy (ECT) ECT is one of the most explored approach among all EP techniques, consisting in the transient permeabilization of the cell membrane to let the introduction of a specific drug  with much more efficiency into the target cell. This treatment is nowadays of standard clinical use in Europe for cutaneous and subcutaneous tumors Besides animal tissues, simple fruit and vegetable tissue models  have been used to study the effects of EP treatments as electric field redistribution Treatment planning of EP-based medical interventions in tumors by numerical modeling has been evolving during the last decade tending to ensure that only targeted regions were treated, sparing as far as possible normal tissue that is meant to be preserved In general, it is recognized that conductivity changes during ECT are due to an increment in membrane conductance, a phenomenon that may occur mainly during the length-time of the first pulse The goal of this paper is to introduce a new conductivity formulation dependent on the electric field, the temperature and the train of pulses, and to show its effects in electroporation protocols. We called this formulation pulse-dependent-conductivity. We also present experimental results derived from potato tuber that validate this new formulation.Solanum tuberosum sp.) and the measurement of electric currents as well as electropermeabilized areas during the treatments. Potato tuber slices (4×5×2 cm3) were electroporated with an arrange of three pair of parallel surgical steel electrodes 2 cm long and 1 mm diameter, immersed 1 cm in the tissue, with 1 cm from anode to cathode and 0.5 cm between two electrodes of the same polarity  were applied by means of a square wave electroporator . Pulse amplitudes were chosen to correspond to those used in standard ECT and IRE protocols. Total electric currents were recorded all along the treatment by an oscilloscope DSOX2012A, 100 MHz, 2 channels  connected to the wire powering the 3 cathodes. Twelve hours after treatment, potato slices were photographed and dark areas were measured by the ImageJ software. Later diffusion processes may be involved in this darkening and may eventually lead to an overestimation of the electroporated area. Then we controlled that our initial clearer but visually evident electropermeabilized area were not significantly different from the darker one that was photographed some hours later. Experiments were repeated 3 times independently (N = 6).Twenty four square electric pulses  at the end of each pulse. Cathodes were separated 0.5 cm from each other and immersed 1 cm in the tissue so, in an area very close to the central cathode  over the cross section of area , the temperature (T) and the number of pulses applied (p); where bσ is the basal electric conductivity of the tissue; and Here, we introduced a new formulation for the electric conductivity fa the electric field coefficient. tF(T), taken from ta the temperature coefficient and www.curveexpert.net).Finally, The system above was solved, for each time step, in a fixed domain on a three-dimensional variable triangular mesh using finite elements and deterministic relaxation techniques. The computational model was implemented in Fortran 90 and executed on a I7-class computer under Linux. The model was also solved using the commercial finite element package Comsol  under Windows 7, simulating the application of the electric pulses through the addition of successive steps in which the applied voltage was switched on and off.In the Comsol implementation, it is possible to add different packages according to the physics of the problem. Here, we used the Electric Currents and the Bioheat Transfer packages. The former solves the Laplace's equation  and the latter, the Penne's bioheat equation (time-dependent). Both packages were solved time-dependently and were coupled through the electric field term of their respective equations. Up to eight electric pulses were simulated through 22 sequential time steps, each one with its own physical conditions. To avoid numerical errors due to different orders of magnitude in time lengths, it was necessary to use two steps for the “off” time between pulses. During the pulse application both packages are on, while during the time between pulses only the Bioheat Transfer package is present. µs pulses were delivered at 1 Hz through the described electrode configuration. All data presented in this figure  correspond to the end of each pulse. Experimental data  describe how, at applied voltages higher than 1000 V, electric current density , conductNumerical predictions with the pulse-dependent conductivity term are quantitatively close to experimental results of electric current density, both regarding initial values and slopes . In contAll results presented in In previous Comsol EP modeling present in literature, there is not a real inclusion of individual electric pulses µs and 1 Hz. Contrary to what was expected, although there are small local changes in the electric field intensity values, these changes do not induce significant changes in the averaged electric field distribution. These results were corroborated with those obtained with the Fortran code and are valid in the context of relatively homogeneous tissues as potato tissue. Future experimental and numerical studies would be necessary to fully adjust these analysis to more inhomogeneous and complex tissues as animal tumors.Mir reported that tissue conductivity changes could be important in the treatment outcome Based on these reports and on our own results, we hypothesize that the addition of pulses during the treatment progressively increases tissue conductivity  making cells more susceptible to permeabilization by the electric field. This fact may explain the enlargement of potato electroporated area observed in In this work a frequency of 1 Hz was considered due to its standard use in ECT clinical applications, but other studies have addressed the effect of pulse frequency on ECT effectiveness. Application of higher pulse frequencies (higher than those causing tetanic contraction) would have the advantage of reducing muscle contractions and related unpleasant sensations during the treatment. In vitro studies have determined that cell uptake in response to ECT does not change between 1 Hz to 8.3 kHz In summary, experimental measurements in potato tissue show that, during a train of pulses and keeping constant the applied voltage, electric current density and the blackened (electropermeabilized) area may increase. Our theoretical predictions agree with these experimental results. In particular, they confirm previous data that electric currents may increase during an ECT treatment at high voltage electric pulses with no significant changes in the electric field distribution. This would imply a rise in tissue electric conductivity, in turn induced by the pulse number and the temperature.We presented experimental measurements from a vegetable tissue model showing electric currents and tissue electropermeabilized area for different EP protocols revealing that, with increased number of pulses and keeping constant the applied electric voltage, the current density and the blackened (electropermeabilized) area increase. We also presented a new theoretical model describing the electric field distribution with a variable conductivity coefficient depending on the electric field, the temperature and the number of pulses applied. Theoretical predictions come close to experimental measurements and explain the current rise observed at high-voltage electric pulses by an increment in the electric conductivity with no significant changes in the electric field distribution. This in turn may be induced by the addition of pulses and the temperature rise. A direct consequence of these results is that, under certain conditions and taking into account the temperature, it is possible to obtain larger electropermeabilized areas with the same voltage applied by increasing the pulse number. The development of more realistic mathematical models as the one presented here will hopefully contribute to optimize experimental EP protocols and to predict better their treatment outcomes.


The reduction of the preterm delivery (PTD) rate is a maternal and child health target. Elevated rates have been found among several immigrant groups, but few studies have distinguished between PTD according to the mode of birth start. In addition, migrants’ birth outcomes have further been shown to be affected by the time in residence; however, the association to PTD subtypes has not previously been assessed. In this study we examined if the risk of spontaneous and non-spontaneous, or iatrogenic, PTD among immigrants in Norway varied according to the length of residence and the country of birth, and compared with the risks among the majority population.We linked population-based birth and immigration data for 40 709 singletons born to immigrant women from Iraq, Pakistan, the Philippines, Somalia, Sri Lanka and Vietnam and 868 832 singletons born to non-immigrant women from 1990–2009. Associations between the length of residence and subtypes of PTD were estimated as relative risks (RRs) with 95% confidence intervals (CIs) from multivariable models.In total, 48 191 preterm births occurred. Both spontaneous and non-spontaneous PTD rates were higher among immigrants (4.8% and 2.0%) than among non-immigrants (3.6% and 1.6%). Only non-spontaneous PTD was associated with longer lengths of residence (p trend <0.001). Recent immigrants (<5 years of residence) and non-immigrants had a similar risk of non-spontaneous PTD, whereas immigrants with lengths of residence of 5–9 years, 10–14 years and ≥15 years had adjusted RRs of 1.18 , 1.43  and 1.66 . The association was reduced after further adjustments for maternal and infant morbidity. Conversely, the risk of spontaneous PTD among immigrants was not mitigated by length of residence, but varied with country of birth according to the duration of pregnancy in term births.Non-spontaneous PTD increased with the length of residence whereas spontaneous PTD remained elevated regardless of the length of residence. Policies to improve birth outcomes in ethnically mixed populations should address the modifiable causes of PTD rather than aiming to reduce absolute PTD rates. Preterm delivery (PTD) is strongly associated with perinatal mortality and morbidity . As an iat term[Preterm rates among migrants to high-income countries vary by the maternal country of origin -7. In coat term,14. Howeat term,16. Diffat term,17.Preterm rates in migrants could be affected by pre-migration exposures as well as by exposures after migration. Although a ‘healthy migrant’ effect in terms of infant outcomes has been shown among certain migrant populations, such effects could be lost with increasing exposure to the host country . A proxyst, 1990, and December 31st, 2009, from the Medical Birth Registry of Norway (MBRN) with files from the National Population Register. The birth registry includes demographic data, information on maternal health before and during pregnancy, gestational length at birth and birth outcomes. The National Population Register contain information on the mother’s country of birth and country of origin, her first date of immigration to Norway and her education level. Unique personal identification numbers enabled linking of the two sets of registry data. The MBRN granted access to the birth data and the Regional Ethics Committee of Norway East approved the linkage to the Population Registry.We linked birth and immigration data for all births occurring during a 20 year period among the six largest immigrant groups and used births among non-immigrants as the reference. Norway was a suitable setting for this study because nearly all births in this country occur within the public health sector. We matched birth records dated between January 1We extracted data from records of singleton births among non-immigrant women and among immigrant women from six countries outside Scandinavia, which enabled an analysis by country of birth . We exclPTD was defined as delivery between completed gestational week 22 + 0 days and week 36 + 6 days. We classified PTD by mode of onset into ‘spontaneous PTD’ or ‘non-spontaneous PTD.’ Non-spontaneous PTD included births that required medically induced labor or a cesarean section before labor. Spontaneous PTD included births that began spontaneously, including preterm labor or prelabor rupture of membranes. Between 1990 and 1998, gestational length was determined based on the last menstrual period (LMP) reported at the first antenatal visit. From 1999 onward, findings from an early second-trimester routine ultrasound were primarily used (97.5%) to determine gestational length, and the LMP was used when ultrasound data were unavailable .The main exposures were country of birth and length of residence. Country of birth was the country where the woman’s mother resided at the time of delivery. Length of residence was calculated as the interval between the year of first immigration to Norway and the year of delivery. In the final analyses the length of residence was categorized as 0–4, 5–9, 10–14 or ≥15 years. The first category (0–4 years) was further subdivided into <2 years and ≥2 years; however, estimates were the same for the two subcategories, so the subcategories were subsequently collapsed.Based on the available literature, we selected co-factors associated with the length of residence and PTD ,28. We e• year of infant’s delivery• period of births, categorized as ‘1990-1998’ and ‘1999-2009’• maternal age at the time of delivery, in years• parity, defined as the number of previous deliveries• the size of the labor unit, as proxy for urban/rural residence• maternal smoking status before/ during pregnancy• age at migration, categorized as quartiles• period of arrival, categorized as ‘<1993’ or ‘≥1993’• gestational or pregestational diabetes• hypertensive disorders, including pregnancy-induced hypertension, preeclampsia and eclampsia• placenta previa• placental abruption• major birth defectsth and 95th percentiles, respectively, of the majority standard) as proxies for abnormal fetal growth [• small- for-gestational age (SGA) and large-for-gestational age (LGA) infants (5l growth .2 test and the χ2 test for trends. To directly assess the relative risks (RRs) of the outcomes with 95% confidence intervals (CIs) we used univariable and multivariable Poisson regression in generalized linear models to estimate the associations between the length of residence and subtypes of PTD. Robust variance estimator (Huber-White) was applied to the models to adjust for data dependencies in mothers who gave birth more than once. See Tables The means of the covariates were compared using the t-test/analysis of variance (ANOVA). Categorical covariates were compared using the χnon-immigrants with immigrants with various lengths of residence. In the first model, we adjusted for demographic covariates which included the year of delivery, maternal age, parity and the size of the labor unit. In the second model, we adjusted for maternal and fetal health-related covariates which included gestational and pregestational diabetes, hypertensive disorder, smoking , placenta disorders, SGA, LGA and major birth defects. Second, we applied the same models to immigrants only, where we also included the country of birth in the model. We used recent immigrants (0–4 years) as the reference. For these analyses among immigrants only, we needed a country reference group and chose Iraqi women, as this group had similar PTD rates as Norwegian women. Due to the relationships between age at the time of immigration, the year of arrival and the covariates already in the model, these variables were added separately to the model as categorical covariates; however, the pattern of the results remained unchanged. Interaction terms between the length of residence and age at immigration and between the length of residence and the country of birth were not significant. Models were checked for goodness of fit. A two-sided p-value of 0.05 was considered statistically significant. The analyses were conducted using SPSS version 20 .First, we compared An application of the models to live births only did not change the pattern of results; this was also the case when we excluded major birth defects and when we restricted the sample to women living in the capital area. To reduce bias arising from the change in the method of determining gestational length, we limited the analyses to 1999–2009, which did not change the association pattern either. Moreover, in the analyses limited to immigrants, we stratified by early  and late  PTD to assess whether the relationship with the length of residence remained consistent.at term between country groups . Overall, the PTD rate was 29% higher among immigrants (6.8%) compared with non-immigrants  (data not shown). The difference was due to a 21% reduction in spontaneous PTD rates, whereas non-spontaneous PTD rates were unaffected. Among non-immigrants, the PTD rate did not differ by dating method (both were 5.3%) (data not shown).term births.In this study, we compared the risk of spontaneous and non-spontaneous PTD among immigrants according to their time in residence with the risk of PTD among the majority population. Our results show that immigrants overall were more likely to experience either PTD subtype than non-immigrants. However, only non-spontaneous PTD was positively associated with length of residence. Among recent immigrants (residence <5 years), the risk of non-spontaneous PTD was similar to the risk among non-immigrants, whereas the risk increased by 18-66% with lengths of residence ≥5 years. Conversely, the risk of spontaneous PTD was not mitigated by length of residence, but varied with country of birth according to the duration of pregnancy in The influence of the length of residence on the likelihood of experiencing non-spontaneous PTD was robust across subanalyses and was independent of the age at immigration and the period of arrival. A trend in overall PTD was also present, consistent with findings from Canada ,29. Howedetection of risk conditions among women with longer residence. Improvements in the language skills of immigrants, as well as more knowledge on the part of providers, could improve communication and trust between the two. In turn, such processes are likely to affect the reporting and referral of complications [We found that the association between the length of residence and non-spontaneous PTD was mainly explained by an increase in maternal and fetal risk factors. Of these, diabetes and hypertensive disorder had the strongest influence. In the general population, studies from the US have shown increasing occurrence of diabetes , obesityications .After adjusting for a range of mediating factors, and relative to our reference of Iraqi women, Pakistani women retained an elevated risk of having a preterm obstetric intervention. This finding cannot be readily explained by our data and needs further investigation. Among other country groups, there were no significant differences relative to the reference.Education level, as a proxy measure for SEP, is closely associated to adverse infant outcome . In our term births, suggesting a bias in the use of a uniform cut-off point for PTD. Second, a change in gestational age dating from ultrasound to LMP dating resulted in inflated PTD rates among immigrants, confirming previous findings among non-white women [increased rather than decreased the PTD rate [Spontaneous PTD receives a great deal of attention because it constitutes the majority of PTD cases . Our reste women . The chaPTD rate ,41. As gThe strengths of this study include the population-based design, with minimal selection bias; the high quality and completeness of the data on exposures (length of residence and country of birth); and the ability to distinguish between the modes of labor onset. The study included births over a 20 year period and although there was a secular increase in preterm caesarean section over this period due to improvements in neonatal care, these changes were adjusted for. Additionally, differential misclassification of the modes of labor onset and the occurrence of preterm prelabor rupture of membranes is believed to be minimal and unlikely to affect the observed associations. However, the present study also had limitations. First, we did not have information on covariates such as maternal height, BMI and previous PTD. In addition, the routine registration of maternal and fetal morbidity can be suboptimal; however, a validation of pregestational diabetes and hypertensive disorders in the MBRN was found to be satisfactory ,43. Of SIn this study we found that migrants’ risk of non-spontaneous PTD increased with the length of residence in Norway, whereas this was not the case for spontaneous PTD. The increased risk of non-spontaneous PTD among immigrants with increasing length of residence was mainly explained by an increase in registered maternal and infant morbidity. This signifies that post-migration exposures contribute to rather than decrease the burden of preterm birth. This has implications for clinical care regarding the primary prevention of lifestyle and diet-associated pregnancy complications. An improved detection of risk conditions as an expression of improved obstetric care with migrants’ length of residence could also contribute to our findings; however, to clarify this further studies of the indications for preterm obstetric intervention is needed. Ethnic differences in the risk of both PTD subtypes persisted in adjusted models. The efforts to reduce the negative outcomes associated with PTD should focus on preventing the modifiable causes of maternal and fetal morbidity rather than aiming at reducing absolute PTD rates. Similar to other studies, this study stresses the need to distinguish immigrants by length of residence and country of birth to gain insights into ethnic variation in birth outcomes.PTD: Preterm delivery; SGA: Small-for-gestational age infant; LGA: Large-for-gestational age infant.The authors declare that they have no competing interests.All authors have fulfilled all conditions required for authorship. IKS, AKD and SV designed the study. IKS analysed the data and wrote the first draft of the manuscript. All authors contributed to the interpretation of the results, revised further drafts, and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2393/14/239/prepub


In Ghana, 32% of deliveries take place outside a health facility, and birth weight is not measured. Low birth weight (LBW) newborns who are at increased risk of death and disability, are not identified; 13%–14% of newborns in Ghana are LBW. We aimed at determining whether alternative anthropometrics could be used to identify LBW newborns when weighing scales are not available to measure birth weight.We studied 973 mother and newborn pairs at the Komfo Anokye Teaching and the Suntreso Government hospitals between November 2011 and October 2012. We used standard techniques to record anthropometric measurements of newborns within 24 hours of birth; low birth weight was defined as birth weight <2.5kg. Pearson's correlation coefficient and the area under the curve were used to determine the best predictors of low birth weight. The sensitivity, specificity and predictive values were reported with 95% confidence intervals at generated cut-off values.One-fifth (21.7%) of newborns weighed less than 2.5 kg. Among LBW newborns, the following measurements had the highest correlations with birth weight: chest circumference (r = 0.69), mid-upper arm circumference (r = 0.68) and calf circumference (r = 0.66); the areas under the curves of these three measurements demonstrated the highest accuracy in determining LBW newborns. Chest, mid-upper arm and calf circumferences at cut-off values of ≤29.8 cm, ≤9.4 cm and ≤9.5 cm respectively, had the best combination of maximum sensitivity, specificity and predictive values for identifying newborns with LBW.Anthropometric measurements, such as the chest circumference, mid-upper arm circumference and calf circumference, offer an opportunity for the identification of and subsequent support for LBW newborns in settings in Ghana, where birth weights are not measured by standardized weighing scales. The Millennium Development Goal 4 - to reduce deaths of children under-five years by two thirds - may be unattainable without halving newborn deaths, which now comprise 40% of all under-five deaths globally A major risk factor for neonatal mortality is low birth weight (LBW); a birth weight less than 2500 g. Every ten seconds, an infant from a developing country dies from a disease or infection that can be attributed to LBW A World Health Statistics report asserted that 15% of babies are born worldwide with LBW In Ghana, 32% of deliveries occur outside a health facility The goal of this study was to evaluate simple anthropometric measurements against the “gold standard” of assessing low birth weight using a calibrated scale in order to provide simple measurements that can be used to guide community health workers and unskilled delivery attendants to identify low birth weight babies, and promote essential newborn care.The Komfo Anokye Teaching Hospital (KATH), a tertiary health institution in Kumasi located in the Subin sub-metropolis was one of the two study sites. The Suntreso Government Hospital, a primary level referral facility located in the Bantama sub-metropolis of Kumasi was the second site.KATH operates as a national referral centre for the northern sector of Ghana. The Child Health Department of KATH has a Paediatric Emergency Unit, three specialist wards and a Mother Baby Unit (MBU). The MBU admits infants less than two months old. This unit has three main wings – a High Dependency Unit (HDU), a LBW and Kangaroo Mother Care Unit (KMC) and a Septic Unit. The HDU admits newborns who need special care and are referred from labor wards within KATH and surrounding district and private hospitals. The LBW and KMC units admit preterm and low birth weight babies for special care and KMC. The Septic Unit admits babies up to two months of age referred from the outpatient department of KATH and other hospitals with suspected sepsis. Mothers are accommodated in a separate room, but on the same floor of the unit. From the MBU records, the average monthly admission is about 150 cases, of which 90 are neonates (0–28 days). The 2010 MBU admission and discharge records show that low birth weight accounts for about 25% of admissions. According to the KATH labor ward records for 2010, there were about 13,000 deliveries, and approximately 1000 were low birth weight, accounting for 9% of all deliveries.The Suntreso Government Hospital (SGH) is a district hospital within the Bantama sub-metropolis, with 238 health facilities within its catchment area. These include private hospitals, maternity homes, pharmacy shops and community-based health planning and services (CHPS) zones. The hospital runs a 24-hour service with several units. The Maternity Unit of this hospital has an antenatal clinic, a labor ward, a theatre and a postnatal ward. There are 28 midwives in the unit and it records about 2,500 deliveries per year. About 5% of all live births are low birth weight. The MBU admits sick newborns delivered at SGH. Others are referred from the health facilities within the Bantama sub-metropolis. In order to reduce the congestion at the KATH MBU, moderately sick newborns are transferred to the SGH MBU to continue with their treatment; low birth weight accounts for 15% of admissions.The study was undertaken according to the tenets of internationally accepted Good Clinical Practice (GCP). The Committee on Human Research, Publications and Ethics (CHRPE) of the Kwame Nkrumah University of Science and Technology, and the Komfo Anokye Teaching Hospital approved the study (CHRPE/AP/155/12). A participant information leaflet/consent form was read aloud to the potential participant. If the mother/guardian did not understand English, it was read in the local language of her choice in the presence of a witness. The parent or guardian indicated their willingness to participate in the study with their newborn by signing and dating or thumb-printing the consent form. It was explained to parents/guardians that there would be some discomfort to the baby during the anthropometric measurements, and that trained health workers would undertake the measurements in order to minimize discomfort. It was also explained to parents/guardians that participating in the study was voluntary, and they had the right to discontinue at any time without any consequences to their newborn or themselves.We conducted an observational study that used a cross-sectional analytical design to study newborns delivered at or admitted to two public hospitals - Komfo Anokye Teaching Hospital and Suntreso Government Hospital in Kumasi, Ghana between November 2011 and October 2012.All mothers and their newborns delivered at or admitted to KATH and SGH.Newborns aged less than 24 hours, and who did not have major congenital malformations and/or birth injuries such as scalp swellings and limb fractures, and who were not less than 1.0 kg and very sick needing oxygen therapy.The sample size was determined by making assumptions mostly based on the area under the curve and correlation findings by Sreeramareddy and others Based on the KATH and SGH records, about 15,000 children are born annually at these hospitals. This translates into about 1,200 deliveries each month. Since the study had a 12-month duration and the representative sample was 940 babies, we considered recruiting at least 78 newborns each month into the study. In order to meet the study duration and also to remove the effect of season of delivery, newborns were recruited throughout the 12-month study period. The assumption was that in each month, out of the approximately 1,200 deliveries, one-in-two mothers would meet the study criteria, would not be discharged home before recruitment, and would also consent to participate, so we expected about 600 mothers each month; we used systematic random sampling method for selection of mother and newborn pairs. Every seventh mother who delivered at KATH or SGH during any given month was approached for recruitment into the study. When the monthly sample of 78 was obtained, recruitment for that month ceased. If for any reason, the monthly sample for any given month was not obtained, the sampling interval for the ensuing month was reduced and when the expected enrolment was achieved, the subsequent month returned to the initial sampling interval.Four research assistants who were health care assistants and nurses on the two MBUs and postnatal wards were trained to measure birth weight, length, head circumference, chest circumference, mid-upper arm circumference, thigh circumference, calf circumference and foot length. Two pediatricians supervised the research.Study participants were recruited from the postnatal wards and the MBUs of the two public hospitals. Midwives assessed the babies on the labor ward and if they were stable and well, they were transferred with their mothers to the postnatal ward and discharged in six hours. However, if a baby was assessed and found to be sick or at high risk of becoming sick, the baby was referred to the MBU for evaluation and management. This was part of the routine care provided for all mothers and babies.The research assistants screened the babies on the MBU and postnatal wards on a daily basis for inclusion into the study; we screened 1,090 newborns within 24 hours of birth.Information on mother's demographics, pregnancy and delivery history were obtained verbally from the mother or guardian, and any additional information were retrieved from the antenatal card and delivery records. Specific information on the mother's demographic characteristics obtained included: age, telephone number, place of residence, home address (with land marks), educational status, occupation, ethnicity, religion, marital status, and household income.Variables on mother's pregnancy and delivery history included gravidity, parity, last menstrual period (LMP), expected date of delivery, mode of delivery, date and time of delivery, baby's weight, sex, Apgar scores and gestational age. The gestational age was used to determine whether the newborn was term or preterm and was assessed by the mother's LMP and/or ultrasound report.The newborn's anthropometric measurements were taken within the first 24 hours of life. The methods and techniques used were based on standardized techniques and criteria described in published studies The data were entered into a database in EpiData version 3.1 and then transferred to STATA IC version 11.1  for analyses. Frequencies for the demographic characteristics, pregnancy and delivery history were determined. Continuous variables such as the birth weight and anthropometric measurements were reported using mean and standard deviation if not skewed. All anthropometric measurements were measured three times and their means were used in further analysis after being cleaned of abnormal values. Between-gender comparisons of continuous variables were performed using independent sample t-test. Pearson's correlation coefficient was determined between the various anthropometric measurements.Multiple methods were used to assess the accuracy of the anthropometric measures against weight taken using a calibrated scale for identifying the baby as “low birth weight”. First, pairwise correlation between birth weight groups and anthropometric measurements was determined. Second, non-parametric receiver operating characteristic (ROC) curve analysis was done, and ROC curves were used to evaluate the accuracy of various anthropometric measurements to predict LBW, indicated by the area under the curve (AUC). Next, pairwise comparison of the AUC of the measurements was done to determine the one with the highest AUC. Finally, sensitivity, specificity, negative and positive predictive values were calculated at all cut-off points for any anthropometric measurement. We chose as “optimum,” the cut-off points with the highest [(sensitivity + specificity)/2] ratio, at which there was a maximal correct classification of the anthropometric measurement. The sensitivity, specificity and predictive values were reported with 95%CI using these generated cut-offs.A total of one thousand and ninety (1090) newborns were screened, 117 (11.7%) were excluded while 973 (89.3%) were recruited between November 2011 and October 2012. Of the 117 who were excluded, 5% of mothers did not give consent, 27.4% had congenital malformations, 19.7% had scalp swellings and/or limb injuries, 13.7% were critically ill and receiving oxygen, 17.9% were more than 24 hours old and 16.2% weighed less than 1.0 kg. In terms of numbers, there was nearly the same number of male babies as there was for female babies in the study sample. A total of 211 (21.7%) newborns weighed less than 2.5 kg (LBW) and 762 (78.2%) were normal birth weight (NBW). Out of the 211 LBW (<2.5 kg) newborns, 183 (18.8%) weighed between 1.5 kg and 2.4 kg, while 28 (2.9%) were very low birth weight (VLBW) and weighed less than 1.5 kg. The overall mean birth weight was 2.9 kg with a standard deviation (SD) of 0.7. The mean weight of males  was significantly higher than that of females . Regarding gestational age of the newborns, 201 (20.7%) were preterm.Mothers had a modal age of 25–29 years, and 15.6% of mothers did not have any formal education at all. Most women (45.5%) were into sales and services or trading, while 9.9% were unemployed. Over 80% of mothers were either married (60.5%) or living together with their partner (25.1%). Birth weight correlated significantly with all the anthropometric measurements. Among LBW newborns, the highest correlations with birth weight were: ChC (r = 0.69), MUAC (r = 0.68), CaC (r = 0.66), and ThC (r = 0.65). To assess how accurately the anthropometrics matched up to the gold standard , AUC analysis was conducted. Using chest circumference (ChC) to identify LBW newborns proved to be the most accurate based on the fact that it had the highest AUC of 0.91 (95% CI: 0.89–0.94). Mid upper arm circumference  and calf circumference  were also very accurate. Other measures were less accurate, with the least accurate being foot length (FL) . In order to assess whether the most accurate measure, chest circumference, compares with the other anthropometrics, the AUC of chest circumference was compared with the AUC estimates of all anthropometric measurements in this study using Pearson's pairwise correlation method. When the p-values are not statically significant (p<0.05), the interpretation is that the AUC is no different from the chest circumference. As shown, the AUCs of the MUAC (p = 0.51) and of CaC (p = 0.20) were not significantly different from ChC in identifying LBW newborns. After adjusting for multiple comparisons, there were still no significant differences between the AUC of ChC and that of MUAC (p = 1.00) and CaC (p = 1.00). However, there were significant differences between the AUC of ChC and the AUC of ThC, OFC, length and FL. A ChC at a cut-off value of ≤29.8 cm had the highest positive predictive value (PPV) of 75.0% (95%CI:68.5%–80.7%) for identifying LBW newborns. Although a thigh circumference (ThC) with a cut-off value of ≤13.3 cm had the highest negative predictive value (NPV) of 93.2% (95%CI:91.0%–95.0%), all the other measurements also had high NPVs of 85% or above. In this study, ChC, MUAC and CaC were equally and highly accurate in identifying LBW newborns. A meta-analysis by Goto The measurement of ChC at the nipple line makes the method simple, reliable and operationally feasible. On the other hand, it requires the removal of the newborn's clothes in order to expose the trunk, increasing the risk of hypothermia. Per contra, measurements of MUAC and CaC do not require much exposure of the newborn, and therefore the risk of hypothermia is reduced. Maintaining the “warm chain,” and taking the measurement quickly could address these concerns with the measurement of ChC. Since the accuracy of ChC, MUAC and CaC were not significantly different in determining LBW, MUAC and CaC could be used if there are serious concerns with measuring ChC in the community setting. The measuring tapes used for these measurements are inexpensive, easy to carry around and maintain, and can be easily used by community health workers We suggest that cutoffs could be provided for community health workers and others attending deliveries to suggest which babies are most at risk. Based on the data from this study, a chest circumference ≤30, calf and mid upper arm circumferences ≤9.5 are concerning. Before providing national recommendations, further validation is required.One pertinent question that needs to be answered is, do we use all the best correlates and highly accurate measurements  observed in this study to identify LBW or chose a single measurement? Some studies Many studies have reported strong positive correlations between birth weight and several anthropometrics: 0.60–0.97 Any anthropometric measurement that is chosen as an alternative to birth weight should be very sensitive so that majority of LBW newborns would be identified for referral and extra care. At the same time it has to be highly specific in order to prevent unnecessary referrals of normal weight babies to higher level centres.Most studies have used various cut-off points ranging from 29.5 cm to 33.5 cm for ChC for predicting LBW newborns Several other studies selected cut-off values for MUAC ranging between 9.0 cm and 10.0 cm, which were comparable to the MUAC cut-off point of 9.4 cm observed in our study Results from our study further showed that MUAC and CaC had sensitivities of 71% and 72% respectively, with each having a specificity of approximately 93%. These figures are very similar to that for ChC in our study. Comparatively, some studies In this study, the number of baby boys and the number of baby girls was almost the same, and this finding is very similar to several studies conducted in Africa and Asia To conclude, ChC, MUAC and CaC measurements may offer a great opportunity for the identification of, and subsequent support for low birth weight newborns in areas in Ghana where birth weights are not measured. The Ghana Health Service may consider supporting community-based studies to test the validity and reliability of these anthropometric measurements for use in community settings in Ghana, where birth weight is not likely to be checked. Anthropometric measurements will contribute to obtaining a more comprehensive measurement, and account of the burden of low birth weight especially in the hard-to-reach areas and in marginalized populations.Our findings and recommendations should be read against the backdrop of certain potential limitations. The study was hospital-based and therefore may not be representative of the children born outside a health facility. Comparing studies with predictive values presents its own challenges as predictive values depend on prevalence, which could vary between studies without affecting the sensitivity/specificity of the measurements.


Prenatal chemical exposure has been frequently associated with reduced fetal growth by single pollutant regression models although inconsistent results have been obtained. Our study estimated the effects of exposure to single pollutants and mixtures on birth weight in 248 mother-child pairs. Arsenic, copper, lead, manganese and thallium were measured in cord blood, cadmium in maternal blood, methylmercury in maternal hair, and five organochlorines, two perfluorinated compounds and diethylhexyl phthalate metabolites in cord plasma. Daily exposure to particulate matter was modeled and averaged over the duration of gestation. In single pollutant models, arsenic was significantly associated with reduced birth weight. The effect estimate increased when including cadmium, and mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP) co-exposure. Combining exposures by principal component analysis generated an exposure factor loaded by cadmium and arsenic that was associated with reduced birth weight. MECPP induced gender specific effects. In girls, the effect estimate was doubled with co-exposure of thallium, PFOS, lead, cadmium, manganese, and mercury, while in boys, the mixture of MECPP with cadmium showed the strongest association with birth weight. In conclusion, birth weight was consistently inversely associated with exposure to pollutant mixtures. Chemicals not showing significant associations at single pollutant level contributed to stronger effects when analyzed as mixtures. Over the last decade, epidemiological studies have frequently shown that the intra uterine environment does not always sufficiently protect the fetus from environmental factors. Maternal stress, dietary factors, and exposure to environmental chemicals have a measurable influence on fetal growth and fetal development with consequences on birth outcome, child development and adult health ,2,3. Eviin vitro studies. Studies with perfluorinated compounds have so far yielded inconsistent results [Several xenobiotic chemicals are suspected obesogens because they have been associated with effects on fetal and/or postnatal growth in human birth cohorts and follow up studies. Most of the evidence points to organochlorines with endocrine properties such as polychlorinated biphenyls (PCBs), dichlorodiphenyldichloroethylene (DDE), hexachlorobenzene (HCB) or plasticizers such as phthalates, bisphenols and many more new chemicals that are present in consumer products are suspect ,7. Effec results . Meta an results ,13. One Most studies associate individual pollutant exposure to health outcomes. However, this does not comply with real life situations as humans are exposed to hundreds of manmade chemicals during their lifetime. Even at the start of life, human biomonitoring shows that complex mixtures of xenobiotic chemicals are present in the prenatal environment . EnvironStatistical analyses of multi-pollutant exposure are complex. Several approaches have been suggested to deal with health effects of complex exposures, among which most methods were applied to the field of air pollution ,22. Feweet al. [In the Flemish human environmental health survey (FLEHS), human biomonitoring is used to assess xenobiotic exposure at the start of life in a sample of the Flemish population that is representative for geographical distribution and is weighed for population density . Since Fet al. . Thus faData from the FLEHS II mother-child cohort were used. The study protocol has been described elsewhere . BrieflyThe birth outcome of interest was birth weight. The information was obtained from the medical records of the maternities. Covariate/confounder data of individual health socio-demographic and life style characteristics, reproductive history and health were obtained from questionnaires. The characteristics of the study population are presented in 3 and H2O2 [et al. [i.e., mono(2-ethyl-5-hydroxyhexyl)phthalate (MEHHP), and mono(2-ethyl-5-oxohexyl)phthalate (MEOHP). However, these could only be detected in a minority of the samples and are therefore not included in the analysis. Our analysis included 15 chemicals that were measured in individual samples. Lead (Pb), manganese (Mn), copper (Cu), thallium (Tl) and arsenic (As) were measured in cord blood, cadmium (Cd) was measured in maternal whole blood samples collected after birth in the maternity. The metals were measured by high resolution inductively coupled plasma-mass spectrometry  after micro-wave acid digestion using HNOand H2O2 . Persistand H2O2 ,32. CALUand H2O2 . The ser [et al. . Total m [et al. . Hg-MM a [et al. . Other m2.5), are continuously measured by a network of automatic monitoring sites [2.5 at the home address of individual participants. Daily concentrations were subsequently averaged over the whole duration of pregnancy.In Belgium, several air pollutants, including fine particulate matter  and Matlab . Statistical significance was defined as p-value < 0.05.Data pre-treatment was applied to improve the robustness of the statistical methods, meet the assumptions of statistical tests or improve graphical visualization of the data. Exposure biomarkers with measurements below the limit of detection (LOD) or quantification (LOQ), depending on which cut-off the measuring laboratory applied, were imputed by half the value of the LOD or LOQ. All exposure biomarkers were ln transformed, as the distributions were skewed. Then, the biomarker data were normalized, a priori fixed known confounders based on literature reviews, i.e., gestational age, gender of the newborn and smoking during pregnancy. Other influencing factors (covariates) were included when significant at the 0.05 level in the multiple regression model. The following covariates were considered: maternal age, parity, stress/pressure during pregnancy, maternal educational level, smoking before pregnancy, alcohol use before/during pregnancy, maternal height, maternal prepregnancy body-mass index (BMI), equivalent income, infections/complications during pregnancy, use of folic acid during pregnancy and caesarean section. We evaluated sex and smoking status as potential effect modifiers as indicated by several previous studies [p-value < 0.10 for the effect of the cross-product was taken as an indication for interaction. Informal diagnostic plots and formal tests were applied to check assumptions of normality (Kolmogorov–Smirnov test), constancy of variance  increase in Z-score of one pollutant. The exposure-response relations were adjusted for  studies ,44,45,46ral test ), indeperal test ). DetectPrincipal components regression (PCR) is a method to model a response variable when there are a large number of predictor variables (exposure biomarkers in this study), and those predictors are correlated or even collinear . New prea priori fixed known confounders  and for other influencing factors (covariates) that were determined as described in the paragraph above. Effect modification (interaction) by sex of the newborn and smoking status was considered when there was an indication for interaction  in the single pollutant regression models. We developed an algorithm to determine the least complex mixture that showed the highest association with birth weight . Alternatively, when significant associations at single pollutant level were lacking, the single pollutant association with the highest rank  was selected. Next, the association of mixtures composed of N chemicals was evaluated by comparing to the association of N-1 chemicals. The criteria to identify models having a stronger association with birth weight as compared to less complex mixtures were based on the estimate and p-value of the association between the average mixture Z-score and birth weight as depicted in Based on a dataset of 16 exposures, 65,519 different mixtures can be constituted consisting of 2 to 16 exposures. We quantified each possible mixture by averaging the Z-scores. Subsequently, linear regression models were used to quantify the effect on birth weight associated with an interquartile range (IQR) increase of a given mixture. As such, this approach was independent from the results obtained by PCA analysis. Pearson correlation was performed to decide whether pairs of exposure were highly correlated. Highly correlated variables were summed and considered as 1 exposure variable when deriving average Z-scores with other exposures. The exposure-response relations were adjusted for h weight . First, Our analysis included 248 singleton newborns with data on birth weight. The characteristics of the population are presented in p = 0.016) between increasing arsenic concentrations in cord blood and lower birth weight (p > 0.10). When including the interaction with sex in the model, thallium was negatively associated with birth weight in girls (p = 0.008), not in boys. The associations were not modified by smoking status when looking at the cross-product term of smoking status with the principal components. The adjusted R2 value when regressing birth weight in function of all explanatory variables except the exposure was equal to 0.3458. The additional fraction explained by the contaminant is very small (about 1%) (Single pollutant multiple linear regression models showed a significant inverse association (h weight . For an bout 1%) . i.e., it displays the associations between the principal components and birth weight, adjusted for gestational age, child’s sex, smoking of the mother during pregnancy, parity and maternal prepregnancy BMI. For the PCs composed from the whole PCA, none of the principal components were statistically significant (p < 0.05) associated with birth weight. However, since the models were built for a subset of 152 from 248 individuals, statistical power may be reduced. For the PCs resulting from the subset PCA, a significant negative association with birth weight was found for PC4 (p = 0.009) constituted by arsenic and cadmium. The associations were not modified by sex or smoking status.The exposure biomarker Z-scores quantified in the present study were clustered using PCA. As PCA works on the complete set of data for all exposures, only 157 individuals could be used in this analysis (further referred to as whole PCA). As a sensitivity analysis, PCA was also performed on 12 out of the 16 exposures  available for 217 individuals (further referred to as subset PCA). PCA identified six and four principal components (PCs) in the exposure data with eigenvalues >1 for the whole and subset PCA, respectively. The composition of the principal components is presented in i.e., PCB-180, PCB-153, and PCB-138) was z-transformed as a measure for PCB exposure in the approach exploring mixtures instead of considering the congeners separately. As for the separate PCBs, the sum of marker PCBs was not significantly associated with birth weight (p = 0.92). The models were adjusted for gestational age, child’s sex, smoking of the mother during pregnancy, parity and maternal prepregnancy BMI. When effect modification by sex was not assumed ; and cadmium, thallium, arsenic, MECPP, and methylmercury .The effect of stepwise combinations of increasing number of chemicals was compared based on the estimate and p-value of the association between mixture Z-scores and birth weight . Due to  assumed a, mixturi.e., PFOS, lead, cadmium, manganese, thallium, and methylmercury ; and PFOA, lead, cadmium, thallium, arsenic, and methylmercury . In boys, the mixture of MECPP with cadmium  and showed a stronger association with birth weight as compared to MECPP alone .Including effect modification by sex in the regression models, the effects of mixtures in girls b were stet al. [in utero or early-life exposure to As. Most studies focus on areas with high As concentrations in drinking water, far above 40 µg/L and exceeding the current WHO drinking water guidelines of 10 µg/L. Although epidemiologic reports that focus on the low exposure range are scarce, low exposure levels have been associated with reduced birth weight, birth length, and chest and head circumference before [In 248 mother-infant pairs characterized by 16 exposure parameters, only arsenic exposure measured in cord blood related significantly with birth weight in a single pollutant model adjusted for confounders and significant covariates. This was seen irrespective of gender and was described earlier and linked to inhibition of placental angiogenesis by arsenic . Potentiet al.  summarize before ,59. In Fe before .We applied in this study two different statistical models for testing the effects of combined exposures on birth weight as this exposure information is available in our cohort. One of the strengths of this study is that the selected statistical models were able to adjust for potential confounders. It is well known that variables such as sex, smoking, gestational age, prepregnancy BMI of the mother, and parity may have an influence on birth outcome ,62,63. Mp = 0.009). The negative association of maternal cadmium levels with birth weight was also found in the EDEN mother–child cohort study [Principal component analysis allowed identifying six mixtures that explained together 66% of the variability in exposure, but regression analysis did not show a significant association with birth weight. This may be partially due to the missing values for some of the exposures or confounders reducing statistical power (only 152 complete cases). As a sensitivity analysis, the PCA was constructed for a subset of exposures yielding a higher sample size and in the same time retaining as much as possible exposures. The resulting principal component constituted by cadmium and arsenic was negatively associated with birth weight (209 complete cases)  are not considered. A recently published study examined the effect of mixed prenatal exposures to potential obesogenic chemicals on overweight measured at Age 7 applying PCA regression . This stExploring the effect of mixtures, we build an algorithm to determine whether the estimated effect estimate of more complex mixtures on birth weight is more significant compared to mixtures composed of a smaller set of chemicals. The most significant associations, as derived from single pollutant associations, were selected as starting point . By an iterative approach more and more exposure parameters were included while the strength and significance of the association was evaluated. If both sexes were included in the analysis, cadmium, lead, PFOA, and MECPP enhanced the association with birth weight compared to arsenic alone and the significance increased. Also mercury and thallium contributed to mixtures that significantly reduced birth weight. Current literature on the associations between PFOA and PFOS and human fetal growth has been recently reviewed . Based oModels that included effect modification by sex, demonstrated that mixtures containing thallium and five other exposure markers  were 2.6 times stronger in reducing birth weight in girls than if arsenic alone was included in the analysis of the full cohort. In boys, the mixture of MECPP and Cd showed stronger associations with birth weight compared to MECPP alone. Our results confirm the sex specific effects of chemical exposures on birth outcome parameters as demonstrated in several studies and which has been linked to the endocrine disrupting effects of chemicals that act differently in developing males and females . In this study we focused on birth weight as a continuous outcome parameter. In the single pollutant model a decline in birth weight with about 90 g was found for an increase in As with the IQR, while in models considering mixtures an effect estimate of 235 g was found in girls for an IQR increase for a certain mixture. It is difficult to assess public health implication for a reduction in birth weight with several hundred grams. For this concern, it would be interesting to investigate the association of (mixtures of) pollutants with adverse birth outcomes, like low birth weight (<2500 g) and small for gestational age (SGA). In our study, only five and 17 babies were found with low birth weight and SGA, respectively. This makes the power of the hypothesis very small and the probability of separation of data points very likely. Future research on adverse health outcomes should be performed. However, relative risk estimates of later disease development associated with birth weight changes have been published in the context of type 2 diabetes . Although our approach for analyzing the effects of combined chemical exposures should be further refined, as a proof of concept we found that including different exposures strengthened the negative association of chemical exposure with birth weight. Whether this is due to independent action of the chemicals or to interactions between the chemicals could not be identified in our analysis. Future statistical models may benefit from taking advantage or including existing information on the mode of action of chemicals to construct mechanistically based exposure factors. Nevertheless the fraction explained by either a single pollutant or a mixture of pollutants is small compared to the fraction explained by the explanatory variables gestational age, child’s sex, smoking of the mother during pregnancy, parity and maternal prepregnancy BMI. However, the findings demonstrated that aside from known birth weight influencing parameters, also prenatal environmental exposure to a mixture of pollutants, may contribute significantly to changes in birth weight.p-value = 1.58E-12). The median levels of total As and toxicological relevant As were 16.2 µg/L  and 4.3 µg/L , respectively. Another limitation to identify exposures that have an important association with birth weight is related to the exposure gradient of the different chemicals in the cohort. If the exposure gradient is small as for example for PM exposures in our cohort, much larger cohorts are needed to identify significant effects. Arsenic, cadmium and MECPP showed the largest variability in exposure in our cohort. Not only the strength of the dose-response relation, but also the existing exposure gradient influences the estimate of the association. Exposure gradients are cohort specific, this may explain the inconsistency in results, which is frequently encountered in observational dose effect studies. With regards to arsenic it should be mentioned that different arsenic species may differ in toxicity. However, speciation analysis was not available in the cord blood samples. Although maternal urinary As concentrations were not analyzed in our cohort, we have urinary levels of total As and toxicologically relevant As , and dimethylarsinic acid (DMA)) in a cohort from 101 women aged between 20 and 40 sampled in the same campaign. In this population, which is representative for Flanders, toxicologically relevant As was about 25% of total arsenic in urinary samples. Total As and toxicologically relevant As were highly correlated  was z-transformed as a measure for PCB exposure in the approach exploring mixtures instead of considering the congeners separately. This avoids that the average z-score is predominantly determined by PCBs when two or more PCBs are in the mixture together with other compounds. Correlation coefficients for all other pairs were below 0.5 (except for the correlation between PCB-153 and DDE (r = 0.54)). As such, we decided to enter the z-scores of the other chemicals exposure markers as separate entities in the analysis. We explored a novel approach on our dataset by using the average of the z-scores of the components constituting a mixture as the predictor variable of birth weight in a regression model to obtain the estimated effect of mixture exposure on birth weight. All possible mixtures were compared. However, the approach has some limitations. For the interpretation of the results, one must be aware that this average z-score cannot reflect the relative toxic potency or interaction of the selected exposures in the mixture and that collinearity between the selected exposures is not fully taken into account in this measure of “total exposure”. Due to the high correlation between the PCB congeners (Pearson correlation coefficients between 0.77 and 0.9) the sum of three marker PCBs (To enhance comparability between the models, the estimated effect on birth weight was expressed for an increase in average z-score with the IQR. If the regression coefficient increased by adding an extra chemical, the estimated effect on birth weight was considered to be elevated. However, we cannot exclude that some bias was introduced by correlated exposures. Averaging z-scores of all possible combinations of exposures and algorithm based model building is a novel approach to identify exposures that contribute to the health effect. However, more research is needed to enhance the approach to solve its current limitations.All the significant associations that were observed in our study between prenatal chemical exposures and birth weight were negative associations, irrespective of the statistical models that were used. Of the 16 exposure parameters that were studied by single pollutant regression models, only cord arsenic levels showed a statistically significant negative association with birth weight. When considering effect modification by sex, exposure to thallium reduced birth weight significantly only in girls. Principal component regression with cadmium and arsenic as the main contributors to the principal component showed a negative association with birth weight. Exploring mixtures by a novel approach showed that the negative association of exposures with birth weight gained strength if up to five exposure parameters were included in the models. Combined exposure to arsenic, cadmium, lead, PFOA, and MECPP enhanced the association with birth weight compared to exposure to arsenic alone. Effects were even more pronounced if sex modification was considered. Effects in girls were enhanced, with the highest association for mixtures containing thallium, PFOS, lead, cadmium, and manganese. Lower birth weight is a risk factor for diseases later in life. Our analysis highlights the importance of preventing prenatal chemical exposure at the start of life.


To develop an index of the quality of nutritional care of premature infants based on the change in weight Z score from birth to discharge and to illustrate the use of this index in comparing the performance of different NICUs.Retrospective data analysis was performed to compare the growth of premature infants born in three perinatal centers. Infants with gestational age ≤ 32 weeks who survived to discharge from 2006 to 2010 were included. Weight Z scores at birth and discharge were calculated by the method of Fenton. Using data from one NICU as the reference, a multivariable linear regression model of change in weight Z score from birth to discharge was developed. Employing this model, a benchmark value of change in weight Z score was calculated for each baby. The difference between this calculated benchmark value and the baby’s observed change in weight Z score was defined as the performance gap for that infant. The average value of the performance gaps in a NICU serves as its quality care index.1,714 infants were included for analysis. Change in weight Z score is influenced by birth weight Z score and completed weeks of gestation; thus the model for calculating the benchmark change in weight Z score was adjusted for these two variables. We found statistically significant differences in the average performance gaps for the three units.A quality care index was developed based on change in weight Z score from birth to discharge adjusted for two initial risk factors. This objective, easily calculated index may be used as a measurement of the quality of nutritional care to rank the performance of different NICUs. Linking financial incentives to the quality of care, i.e. pay-for-performance, has become a popular approach to performance improvement in health care worldwide . ReimburTraditionally, quality measures of care for premature infants include outcome measures such as birth weight specific mortality and rates of complications of prematurity. While birth weight specific mortality is easy to define, it fails to address the surviving infants. Other neonatal outcome measures may suffer from bias or fraud, such as omitting poor outcomes in order to improve ratings without actually improving performance . FurtherOptimizing postnatal growth is an integral component of the management strategies of preterm infants and an important health outcome measure in the NICU. Degree of extrauterine growth restriction (EUGR) therefore may be used as one of the objective measures of quality of nutritional care of premature infants. However, the definitions of EUGR are not consistent in the literature and several methods have been proposed to quantify the degree of EUGR. By analyzing the data from three regional perinatal centers, we sought to illustrate the wide differences in the incidences of EUGR resulting from the use of different definitions and to develop an objective method quantifying EUGR which may be used as a simple and fair index of quality of nutritional care in NICUs.Data collection: Data were retrospectively retrieved from three regional perinatal centers, one from the United States  and other 2 centers from China (labeled as China 1 and China 2). Birth weight, gestational age, discharge age and discharge weight were collected from the individual perinatal data bases or medical records on all premature infants with gestational age ≤32 weeks who survived to discharge home from 2006 to 2010. The gestational age was determined based on the best obstetric estimate with >90% of those confirmed by early prenatal ultrasound. The postmenstrual age at discharge was calculated as the sum of gestational age plus chronological age at discharge. The study was approved by the Program for the Protection of Human Subjects of the Icahn School of Medicine at Mount Sinai and the Ethics Committees of The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University and The First Hospital of Jilin University. All patient records/information was anonymized and de-identified prior to analysis.Statistical analysis: For each infant in the study population, weight Z scores at birth and at discharge were calculated using the LMS tables published by Fenton & Sauve , 6. The Change in weight Z scores from birth to discharge was selected as the quantitative measure of EUGR for each patient. Arbitrarily using the Mount Sinai group as the reference NICU, we developed a multivariable linear regression model of change in weight Z score from birth to discharge as a function of birth weight Z score and completed weeks of gestation at birth. Then, for each baby in the study a benchmark value of change in weight Z score from birth to discharge was calculated using the baby’s birth weight Z score and completed weeks of gestation in the model equation. We then define the performance gap for each baby as the difference between the baby’s observed value of change in weight Z score and this calculated benchmark value (performance gap = observed change in weight Z score—benchmark change in weight Z score). The mean value of the performance gap for the babies in each NICU, which by definition must be zero for the reference NICU, was defined as the quality care index for that unit, and the values of the three NICUs were compared by ANOVA and the Bonferroni test. Data are presented as means and standard deviations, and P<0.05 is considered as statistically significant. All statistical analysis was performed by using IBM SPSS 20 .There were a total of 2444 infants  with gestational age ≤32 weeks admitted into the 3 NICUs. However, only 1,714 infants who survived to discharge home  were included in the data analysis. The babies not included in the analysis either died before discharge or were transferred out for medical, social, or economic reasons. The basic demographic characteristics of the three groups are shown in the th percentile) and the incidences of EUGR according to three different definitions are presented in the th percentile); 2. Change in weight Z score < -1.28; 3. Change in weight Z score < -2.0. As shown in the The incidence of intrauterine growth restriction (IUGR) defined as weight Z-score at birth <-1.28  + (-0.364 x birth weight Z score). The RWe show in the current study that, regardless of the definition, the incidence of EUGR differed between the three NICUs. We also illustrate that the degree of EUGR as measured by the change in weight Z score from birth to discharge in our reference population is influenced by birth weight Z score and gestational age. We develop a linear regression model using data from a reference NICU which allows calculation of benchmark values for change in weight Z score adjusted for birth weight Z score and completed weeks of gestation in babies from other NICUs. We define the performance gap for each baby in those NICUs as the difference between observed and benchmark changes in weigh Z score. We define the quality care index as the average performance gaps in that NICU. We demonstrate that the three NICUs differ significantly using this quality care index.The multiple morbidities that premature infants experience during their NICU stay often lead to postnatal growth failure , 8. It hPostnatal growth failure may have prolonged effects on outcomes, such as delaying the recovery from chronic lung disease, rate of later physical growth, and, possibly, cardiovascular and metabolic disorders in adult life . OptimalEUGR has been defined by some as discharge weight less than the 10th percentile , 19, 20,The major limitation of this study is the use of only two factors to adjust the model of EUGR. Certainly, the use of other prenatal factors such as gender, race, multiple gestations and the use of prenatal steroids would improve our model. However, adding those factors into the model will definitely increase the complexity and work load for reliable data collection. Furthermore, it has been shown before that adding those factors contributes very little to the explanation of growth differences of extremely premature infants between NICUs . AlthougObviously, birth weight specific mortality rate should always be considered if we apply this simple method to compare the quality of care among NICUs. Many other aspects of care, i,e, the incidence of bronchopulmonary dysplasia (BPD) and the neurodevelopmental outcome should be considered as well. Furthermore, unadjusted comparisons of outcomes among NICUs involving large numbers of transferred babies may be invalid unless the entire network is included as a whole unit. For example, Olsen et al  have shoIn summary, we have used data from three different NICUs to illustrate that a reference NICU can be used to determine benchmark values of change in weight Z score from birth to discharge for babies in other NICUs. A performance gap for each baby can readily be calculated as the difference between the observed and benchmark values. The average performance gap for babies in a NICU over a given time period may serve as a quality care index for that unit. In addition to birth weight specific mortality rate, incidence of BPD, and neurodevelopmental outcomes, this objective, easily calculated quality care index might be used as one of the measurements of care quality to rank the performance of different NICUs or to compare quality of nutritional care over time within one unit.


Background: Half the world’s population lives in urban areas. It is therefore important to identify characteristics of the built environment that are beneficial to human health. Urban greenness has been associated with improvements in a diverse range of health conditions, including birth outcomes; however, few studies have attempted to distinguish potential effects of greenness from those of other spatially correlated exposures related to the built environment.Objectives: We aimed to investigate associations between residential greenness and birth outcomes and evaluate the influence of spatially correlated built environment factors on these associations.Methods: We examined associations between residential greenness [measured using satellite-derived Normalized Difference Vegetation Index (NDVI) within 100 m of study participants’ homes] and birth outcomes in a cohort of 64,705 singleton births (from 1999–2002) in Vancouver, British Columbia, Canada. We also evaluated associations after adjusting for spatially correlated built environmental factors that may influence birth outcomes, including exposure to air pollution and noise, neighborhood walkability, and distance to the nearest park.Results: An interquartile increase in greenness  was associated with higher term birth weight  and decreases in the likelihood of small for gestational age, very preterm (< 30 weeks), and moderately preterm (30–36 weeks) birth. Associations were robust to adjustment for air pollution and noise exposures, neighborhood walkability, and park proximity.Conclusions: Increased residential greenness was associated with beneficial birth outcomes in this population-based cohort. These associations did not change after adjusting for other spatially correlated built environment factors, suggesting that alternative pathways  may underlie associations between residential greenness and birth outcomes.http://dx.doi.org/10.1289/ehp.1308049Citation: Hystad P, Davies HW, Frank L, Van Loon J, Gehring U, Tamburic L, Brauer M. 2014. Residential greenness and birth outcomes: evaluating the influence of spatially correlated built-environment factors. Environ Health Perspect 122:1095–1102;  More than half of the world’s population now live in urban environments, and it has been estimated that by 2050 this number will grow to 60% (approximately 6.4 billion people) . A diverOnly a few studies have examined associations between exposure to residential greenness during pregnancy and birth outcomes. Adverse birth outcomes, such as preterm birth and low birth weight, are important not only because of their immediate impacts on infant health but also because of the subsequent health and developmental consequences through the individual’s life course . In PortGiven this suggestive evidence and the large potential burden accompanying adverse birth outcomes, it is important to evaluate the robustness of the association between greenness and pregnancy outcomes and the specific pathways through which potential effects may operate. In particular, there is a need to distinguish the effect of residential greenness from other spatially correlated built-environment factors. Here we define built environment as urban design, land use, and the transportation system, encompassing patterns of human activity within the physical environment . There a2) exposures  in Vancouver, British Columbia, Canada, to examine associations between residential greenness and birth outcomes. We also evaluated the extent to which these associations may be mediated by additional spatially correlated factors related to the built environment  to help elucidate potential pathways of influence.Description of cohort. Linked administrative data were used to establish a birth cohort that comprised all births from the period 1999–2002 in the metropolitan area of Vancouver  and moderately preterm birth (30–36 weeks gestation) versus term birth (≥ 37 weeks gestation). We examined both very and moderate preterm birth separately to allow focus on the very preterm component, which is of greater clinical relevance. We also evaluated term (≥ 37 weeks of gestation) birth weight and fetal growth .Covariates. Individual-level covariates obtained through administrative records included the month and year of birth, infant sex, First Nations status, as well as parity, maternal age, and maternal smoking during pregnancy. No individual-level data were available for income or maternal level of education. We assigned subjects to neighborhood-level income quintiles and maternal education quartiles using census data  based on land surface reflectance of visible (red) and near infrared parts of spectrum (http://landsat.gsfc.nasa.gov/?p=3225) of the Vancouver region for 1999–2002. Average greenness values were extracted for 100- and 250-m areas around residential postal code centroids and both yearly and seasonal  greenness values were calculated. We did not assign the 30-m NDVI values to each residential postal code as postal codes typically reflect one side of a city block, and this area is better captured with a 100-m buffer distance. The 30-m NDVI was highly correlated with the 100-m (r = 0.80) and 250-m (r = 0.69) NDVI measures. The seasonal measures were also highly correlated (r > 0.94) with the annual measures, and we therefore present only the annual average NDVI results. Although there were slight differences in the actual NDVI mean values by season , the spatial pattern of NDVI did not change, which therefore resulted in a high correlation with seasonal values. The 100- and 250-m buffer areas were used to assign residential greenness exposure because these distances have been used in prior studies  air pollution models developed for the Vancouver metropolitan area for nitric oxide (NO), nitrogen dioxide (NO2), fine particulate matter , and black carbon (BC). The creation and evaluation of the models has been described previously , a physical model with a focus on transportation-related sources. The creation and evaluation of this model has been described previously , parity, maternal age  and maternal smoking during pregnancy (yes/no)] as well as census covariates  described previously. For the term birth weight analyses, a categorical variable for the completed weeks of gestation  was also included. Associations between greenness exposures and birth outcomes are presented corresponding both to an approximate IQR increase in exposure measures and by quartiles, because cubic regression splines  identified slightly nonlinear relationships. Incremental models are presented to evaluate how associations between residential greenness and birth outcomes change when air pollution and noise exposures, neighborhood walkability, and park distance are added. A number of sensitivity analyses were also conducted to determine how associations between residential greenness and birth outcomes changed based on residential mobility during pregnancy, when area contextual factors at the DA level  were entered into the models, and when models were stratified by area income, education, and visible minority status. Visible minority status is defined as persons, other than Aboriginal peoples, who are non-Caucasian in race or nonwhite in color.n = 64,705), as well as participants stratified by NDVI quartiles, are summarized in Descriptive statistics of the overall cohort with complete covariate and exposure information (2 (–0.42), PM2.5 (–0.36) and BC (–0.31), exposure to traffic (–0.05) and all noise (–0.20), and neighborhood walkability (–0.58) and distance to the nearest park (–0.05). 2 air pollution concentrations, all noise levels, and neighborhood walkability and parks. For reference, the PM2.5 exposure map is shown in Supplemental Material, Figure S1. The spatial autocorrelation of these exposure variables within the study area was measured by the Global Moran’s I spatial statistic . The resulting spatial autocorrelation for exposure variables were as follows: NDVI (I = 2.81), NO (I = 0.06), NO2 (I = 0.04), PM2.5 (I = 0.03), and BC (I = 0.03), neighborhood walkability (I = 0.92), park proximity (I = 0.38), road traffic noise (I = 0.47), and all transportation noise (I = 0.48). These spatial autocorrelation measures were sensitive to the spatial weights and distance thresholds used, with increasing autocorrelation generally seen for larger distances (data not shown).The associations between residential greenness and other built environment exposure measures and birth outcomes are shown in r = 0.92), and the individual variable coefficients are therefore difficult to interpret. Similar patterns were seen for preterm birth, moderate preterm birth, and SGA (data not shown).We used incremental models to examine how the associations between residential greenness and birth outcomes changed with the inclusion of the other built environment exposure variables. p < 0.01 for linear versus nonlinear spline function), with an inflection point occurring around the NDVI value of 0.15, after which the influence of residential greenness on birth outcomes becomes positive and linear. A map of NDVI values above and below this threshold is shown in Supplemental Material, Figure S3.Smooth exposure–response curves for residential greenness and birth outcomes from the unadjusted, adjusted, and fully adjusted models (including other built environment variables) are shown in Supplemental Material, Figure S2. For all outcomes there is a statistically significant nonlinear relationship  compared with women currently living in the highest income quintile who moved (37.3%). When the fully adjusted models were stratified by moving status, only slight differences were observed between movers and nonmovers (data not shown). For example, in movers a 0.1 increase in NDVI was associated with an increase in term birth weight of 20.1 g , compared to 21.9 g  for nonmovers.In place of detailed individual characteristics, we also explored a number of additional area-level variables  to determine their influence on associations between greenness and birth outcomes. Associations were robust to inclusion of all area-level variables except for those related to the proportion of visible minorities, which attenuated results, primarily for term birth weight (data not shown). For example, including percent Chinese or percent South Asian ethnicity by DA areas  reducedModels stratified by area income, education, and percent Chinese or percent South Asian were explored to further examine potential spatial and residual confounding . Associations were slightly stronger in the highest income quintile, especially for term birth weight where a 0.1 increase in NDVI was associated with a 32.4-g  higher average birth weight. However, with stratificaiton by area-level education and visible minority status, no clear gradients for any birth outcome were observed.We found that increased greenness within 100 m of residences measured using satellite-derived NDVI was associated with higher term birth weight and with reduced likelihood of very (< 30 weeks) and moderately (30–36 weeks) preterm births and SGA. These associations were robust to adjustment for air pollution and noise exposures, the walkability of residential neighborhoods, and distance to the nearest park. This suggests that the association between greenness and birth outcomes is independent of these spatially varying exposures related to the built environment, and that alternative pathways may link residential greenness to birth outcomes.2 air pollution exposures in the Spanish study reduced the magnitude of the association with NDVI within 100 m by 21% to 17.7 g. In the cohort study of 3,203 births in Munich, the strongest association was observed for NDVI within 500 m. For NDVI within 100 m (the metric used in our study), adjusting for NO2 exposure increased the estimated difference in birth weight from 12.2 g to 16.2 g  this is unlikely. There was a correlation of –0.30 between residential greenness and percentage of visible minorities, suggesting that spatial confounding may be an issue, although stratified analyses by visible-minority quartiles showed no obvious trend and the largest associations were generally seen for the lowest visible-minority quartile. Although the NDVI measure enabled us to quantify small-scale variations in greenness in a standardized and objective measure, NDVI does not distinguish between different types of vegetation , quality of greenness, or actual exposure to greenness, which may be important depending on the theorized pathways linking greenness to birth outcomes. In addition, the other built environment exposure variables were modeled at different spatial resolutions, which may incorporate differential exposure misclassification. Only residential history during pregnancy was available to assess NDVI, and 9 months represents a relatively short exposure period unless women had lived at their current residential address for longer periods of time. We did not have information on prior residential duration, but we examined residential mobility during pregnancy and found no change in our results. Long-term residential mobility remains a concern if individuals choose to live in neighborhoods based on characteristics that may influence birth outcomes and that are also related to residential greenness.A major strength of our analysis is that, unlike previous studies, we were able to estimate associations between residential greenness and birth outcomes after adjusting for a number of spatially correlated built environment variables. However, our ability to use a large population-based cohort derived from administrative data also incorporates inherent limitations related to the lack of individual covariates. Although a number of individual-level variables were available in these databases, no information was available for individual-level SES [although smoking during pregnancy and maternal age are useful surrogate measures, especially for the lower portion of the SES gradient  and otheResidential greenness represents a unique  exposure construct that may be important to health. We determined that increased residential greenness is associated with positive birth outcomes in a population birth cohort in Vancouver, British Columbia, Canada, and that this association persists after adjusting for exposures to air pollution, noise, residential neighborhood walkability, and park proximity. Further research is needed to evaluate the specific pathways that may link residential greenness exposure to birth outcomes, including other built environment features as well as psychosocial and psychological pathways.(4.7 MB) PDFClick here for additional data file.