The risk of birth defects related to SO2 in the first 3 months before pregnancy was between 1.191 and 1.566. In the first trimester stage the risk was between 1.104 and 1.348. The risk of birth defects related to NO2 before pregnancy was 1.285 (95%CI: 1.180–1.399), in the first trimester stage the risk was between 1.280 (95%CI: 1.197–1.368) and 1.380 (95%CI: 1.293–1.473). In the third month before delivery the risk was 1.484 (95%CI: 1.366–1.613). The risk of birth defects related to PM10 in the first month of pregnancy was 1.098 (95%CI: 1.057–1.140), and in the third month before delivery the risk was 1.296 (95%CI: 1.222–1.375). SO2 had a greater effect on the prophase of pregnancy, while NO2 and PM10 had an effect in the late third trimester.This study was performed to assess whether air pollution was positively associated with birth defects and if a specific pregnancy stage played a role. This was a population-based case-control study comprising 153,822 perinatal births in four cities located in Hunan province, China, during the period 2014 to 2016. Exposure to SO Birth defects are present in approximately 2.03% in the United States based a population study. In China, the estimated prevalence is approximately 4% to 6%. The prevalence rates of birth defects in Hunan province ranked third in China in 2011, fourth in 2012, and fifth in 2013.Birth defects as well as congenital anomalies, congenital disorders, and congenital malformations can be defined as structural or functional anomalies  that occur during intrauterine life and can be identified prenatally, at birth or later in life. Birth defects can contribute to long-term disability, which may have a significant impact on individuals, families, health-care systems, and societies. Birth defects accounted for 510,400 deaths worldwide in 2010, a total of 1% of all deaths, and ranked 23rd among all causes of death.–9. China has been experiencing exceptionally high levels of air pollution in recent years due to the booming economy. Therefore, an increasing number of studies have examined the effects of air pollution on birth defects in China.–14 The study in Xi’an, China, used a generalized additive model to investigate the relationship between birth defects and ambient air pollutants, showed nitrogen dioxide (NO2) increased risk of neural tube defects, congenital heart disease, congenital polydactyly, cleft palate, digestive system abnormalities and gastroschisis, and PM10 was associated with congenital heart disease and cleft lip with or without cleft palate. The hospital-based case-control study in Fuzhou, China, showed some positive associations between maternal exposure to ambient particles with an aerodynamic diameter of 10 mm or less (PM10) during the first 2 months of pregnancy and fetal cardiovascular malformations. The retrospective cohort study in Anqing city, Eastern China, suggested that exposure to ambient sulfur dioxide (SO2) during pregnancy may increase the risk of birth defects. The study in Lanzhou, China, investigated a cohort of 8969 singleton live births by using inverse distance weighting way for exposure assessment found positive associations for congenital malformations of cardiac septa with PM10 exposures in the second trimester and the entire pregnancy, and SO2 exposures in the entire pregnancy. In a word, there were differences in the studies in the selection of subgroups of birth defects, exposure window, exposure assessment method and adjustments for confounding factors, and the representativeness problem that each study conducted in different areas.Birth defects can occur during any stage of pregnancy. Most birth defects occur in the first 3 months of pregnancy, when the baby's organs are formed. This is a very important stage of development. However, some birth defects occur later in pregnancy, as the tissues and organs continue to grow and develop in the last 6 months of pregnancy. Maternal exposure to air pollution may increase the risk of birth defects. Many studies investigating the effect of maternal exposure to ambient air pollution on birth defects have been conducted worldwide2, NO2, and PM10 was associated with an elevated risk of birth defects during three pregnancy periods  in Hunan province, China. This study is the first to investigate the relationship between birth defects and ambient air pollution at a provincial level in China.In light of the inconclusive evidence on the occurrence of birth defects in the different stages of pregnancy, as well as the lack of studies in provincial areas in China with a high prevalence of birth defect, we conducted a study in Hunan province, China in order to obtain data on these issues. Therefore, the objective of this study was to investigate whether maternal exposure to SO22.12, and has a population of 71.47 million people, with 14 cities and 123 counties. We selected the following four cities, Changsha, Changde, Yongzhou, and Huaihua, which are located in central, north, south, and west of Hunan province respectively, and are selected as the air monitoring stations for nation. All birth defect monitoring hospitals in the four cities were selected. In total, 18 birth defect monitoring hospitals were included. The study period was from October 1, 2013 to September 30, 2016.We used a population-based case-control study design to examine the association between ambient pollution and birth defects in Hunan province, China. Hunan province is located in central China, covers 21.18 km2.2The study subjects were perinatal births including live births, stillbirths, and deaths within 7 days, and excluded twins or multiple births and family genetic history in the 18 birth defect monitoring hospitals in the four cities in Hunan province from October 1, 2013 to September 30, 2016. All the data were sourced from the Hunan province women and children health direct report management system, which included the birth defect registration card, the seasonal report on the number of perinatal births, and childbirth record. All the data was exported under the supervision of the health administration. Therefore, the study and the consent procedure were approved by the Medical Ethics Committee of Hunan province Maternal and Children Care Hospital.The birth defect registration card included information on maternal conditions, child conditions, birth defect diagnosis, early pregnancy, and family history. Maternal conditions included present address, ethnicity, age, cultural level, family income, number of pregnancies, and total previous live births. Child conditions included date of birth, sex, gestational age, number of children, weight, and outcome. Birth defects included 24 types were classified according to the International Classification of Diseases Clinical Modification Codes, tenth edition, (ICD-10) as congenital malformations, deformations, and chromosomal abnormalities (Codes Q00–Q99). Early pregnancy conditions included illness, drug administration and exposure to other harmful factors. Family history included abnormal reproductive history and a detailed family history. The childbirth record included maternal name, age, address, gestational week, gravidity, parity, delivery mode, and newborn conditions. The health monitoring data report was mainly the health administration data as the number of perinatal births. All data were eventually submitted to the relevant national departments after quality control by provincial relevant departments.2.3Cases were those with reported birth defects during the study period, and controls were a 25% random sample of live births born during the study period, without birth defects and sufficient information for the indicators. Pregnancies with missing childbirth record information or implausible gestational age information (<20 weeks or >44 weeks) were excluded.2.42, SO2, and PM10) from October 1, 2013 to September 30, 2016 were obtained from the Environment Protection Bureau of the corresponding city, which in all covered from 167 monitoring stations. Daily, monthly, and seasonal average levels of the three pollutants were computed based on these measurements. The concentrations of SO2, NO2, and PM10 were assigned to each maternal residence based on the nearest monitor to the residential address reported at the time of the first routine physical examination. On average, there were three monitoring stations in each county. Three monitoring stations were located predominantly in the central districts of each county. We estimated the date of conception by adding 14 days to the date of last menses.The daily concentrations of ambient air pollutants , maternal age , total previous live births , number of pregnancies , and season of conception , were entered for the final adjustments based on the previous studies and the data available.2.62, NO2, and PM10 and the risk of birth defects by calculating the odds ratio (OR) and 95% confidence intervals (CI). The χ2 test was conducted to examine the distributions of selected characteristics in the cases and controls. Percentile values were used to describe the pollutant concentration distribution. Microsoft Excel 2010 was used to enter data and SPSS 17.0 software was used for statistical analysis.We adopted binomial logistic regression to examine the association between SO33.1χ2 = 368.01, P < .01). Table N = 1498) and represented 29.83% of all birth defects.Table 3.2P < .001). These variables were considered as the confounding factors.The characteristics of the control group and the case group are presented in Table 3.32 was highest in Yongzhou city, in 2014, and in winter (P < .001). The level of NO2 was highest in Changsha area, in 2014, and in winter (P < .001). The level of PM10 was highest in Changde area, in 2015, and in winter (P < .001).Descriptive statistics of the concentrations of air pollutants during the study period are shown in Table 3.42 in the prophase of pregnancy, and in the first and third trimester, and summarizes the results of logistic regression analysis with/without adjusting for areas, year, season of conception, maternal age, gender of infant, total previous live births and number of pregnancies in the three pregnancy stages. There was difference between controls and cases for concentration of SO2 in the study period (P < .001). The concentration of SO2 was highest in the prophase of pregnancy. In the simple factor regression model without adjusting any variables, SO2 was a risk factor for birth defects in the first 3 months of each stage. In the multiple factor regression model, the risk of birth defects related to SO2 in the first to third month before pregnancy was 1.191 (95%CI: 1.107–2.202) to 1.566 (95%CI: 1.107–2.202), in the first to third month of pregnancy was 1.270 (95%CI: 1.202–1.342), 1.348 (95%CI: 1.264–1.438), and 1.104 (95%CI: 1.039–1.173), and in the second month before delivery was 1.130 (95%CI: 1.068–1.196).Table 3.52 in the prophase of pregnancy, and in the first and third trimester, and summarizes the results of logistic regression analysis with/without adjusting for covariates in the three stages. There was difference between controls and cases for concentration of NO2 in the study period (P < .001). The concentration of NO2 was highest in the pregnancy stage. In the simple factor regression model without adjusting any variables, NO2 was a risk factor for birth defects in the first 3 months of each stage. In the multiple factor regression model, the risk of birth defects related to NO2 in the second month before pregnancy was 1.285 (95%CI: 1.180–1.399), in the second and third month of the first trimester was 1.280 (95%CI: 1.197–1.368) and 1.380 (95%CI: 1.293–1.473), and in the third month of the third trimester was 1.484 (95%CI: 1.366–1.613).Table 3.610 in the prophase of pregnancy, and in the first and third trimester, and summarizes the results of logistic regression analysis with/without adjusting for covariates. There was difference between controls and cases for concentration of PM10 in the study period (P < .001). The concentration of PM10 was highest in the prophase of pregnancy. In the simple factor regression model without adjusting any variables, PM10 was a risk factor for birth defects in the first 3 months of each stage. In the multiple factor regression model, the risk of birth defects related to PM10 in the first month of the first trimester was 1.098 (95%CI: 1.057–1.140), and in the third month of the third trimester was 1.296 (95%CI: 1.222–1.375).Table 4 Approximately 6%–8% of birth defects were associated with exposure to air pollution. As no studies have been carried out at the provincial level in China, and based on the inconclusive evidence on the effect of air pollution on birth defects in the stages of pregnancy, we conducted this study based on the four cities as the selected air monitoring stations for nation to determine the association between air pollution and birth defects.Over the past few decades, birth defects were the most common cause of infant mortality. The etiology of birth defects is thought to be multifactorial, with environmental exposure to air pollution suspected to play a role.2 exposure and the prophase of pregnancy, pregnancy, and the second month before delivery following the adjustment of confounding factors. SO2 emissions are associated with coal combustion in power plants and industrial facilities. In the four selected cities, Huaihua and Yongzhou had higher SO2 concentrations as most energy enterprises are located in south and west Hunan province. The SO2 concentration was higher during autumn and winter as more energy is needed in cold seasons. Some studies on the effects of SO2 on birth defects have been conducted. For example, Martine Vrijheid conducted a systematic review and meta-analysis and concluded that SO2 exposure was related to an increased risk of coarctation of the aorta  and tetralogy of fallot . Dolk et al observed a significant association between SO2 and tetralogy of fallot. Giloba et al observed a significant association between SO2 and ventricular septal defects. Gianicolo et al found that exposure to the 90th percentile of SO2 increased the risk of congenital heart defects and ventricular septal defects. However, Esther Kai-Chieh Chen et al did not find that SO2 concentrations were significantly associated with birth defects. The difference maybe the methods used in the studies, such as case and control definition, exposure assessment, could affect the result.In this population-based case-control study, we found a positive association between SO2 exposure during the second month of the prophase of pregnancy, the second and third month of pregnancy, and the third month before delivery was associated with birth defects. The NO2 concentration was higher in Changsha city and during the cold season as Changsha is a provincial capital city and has more vehicles and more energy is used during the cold season. Some studies have shown the effects of NO2 on certain types of birth defects. Esther Kai-Chieh Chen et al conducted a systematic review and meta-analysis and concluded that NO2 concentration was significantly associated with coarctation of the aorta . Schembari et al concluded that NO2 was associated with coarctation of the aorta and digestive system defects. Dadvand et al showed an association between NO2 and congenital heart diseases, ventricular septal defects, cardiac septa malformations, and tetralogy of fallot. The different result also maybe the different methods used in the studies.This study showed that NO10 exposure during the second month of pregnancy, and the third month before delivery was associated with birth defects. The PM10 concentration was higher in Changde city and during the winter. PM10 exposure level was an average of 101 μg/m3, similar to a recent report by Zhang et al, in which the mean PM10 level was 101.7 μg/m3. The China National Ambient Air Quality Surveillance Network showed that annual levels of PM10 in one-third of cities in China exceeded 100 μg/m3. A significant association between PM10 and patent ductus arteriosus was observed in a study by Strickland et al Dolk et al observed a significant association between PM10 and omphalocele. Kim et al showed that congenital anomalies were influenced by exposure to PM10. Gianicolo et al found that exposure to SO2 increased the risk of atrial septal defect.This study showed that PM Air pollutants may participate in the formation of skeletal muscle during fetal development through mechanisms such as hemodynamics, oxidative stress, and cytotoxicity. SO2 and its derivatives absorbed into the blood had adverse effects on germ cells and the development of embryos, and impaired the function of germ cells and their microstructure. Exposure to NO2 during pregnancy can increase the lipid peroxidation level in the placenta, and cause abnormal growth and embryonic death. PM10 can directly enter the airway causing birth defects, and increase DNA adductions through the circulatory system. However, some studies have revealed no significant association between the air pollutants SO2, NO2, and PM10 and birth defects .,8,30,31To date, the effects of air pollution in the pathogenesis of birth defects is unclear.,13,32 Other studies suggested that third trimester exposure resulted in greater effects. It is still unknown whether the period of peak effect differs during the pregnancy stages. Thus, we determined the relationship between the three pregnancy stages and birth defects. Furthermore, we subdivided pregnancy into 3 month sections. In our study, a positive association was found between birth defects and SO2 exposure in the prophase of pregnancy, the first trimester and the third month before delivery. A positive association was also found between birth defects and NO2 exposure in the second month before pregnancy, the second and third month of pregnancy, and the third month before delivery. A positive association was also found between birth defects and PM10 exposure in the first month of pregnancy and in the third month before delivery.The advantages of this study are as follows: First, this study demonstrated the association between air pollution and birth defects at the provincial level in China by selecting four geographical locations in Hunan province. To date, there is no similar research at the provincial level in China. Second, some studies have reported that exposure during the first trimester was associated with an increased risk of birth defects.,21,30 while other studies used continuous exposure variables.,23,31,33 In this study, we estimated the effect of air pollution as categorized exposure in quartiles, as categorical variables increased the statistical power.Previous studies on this topic divided the exposure variables into categorical variables, Gender of infant, total previous live births and number of pregnancies as the confounders in this study were also considered in other studies,20,33 This study had some limitations. First, we did not use a distance-weighted calculation in the assessment of exposure, as the distance between maternal residence and the nearest monitoring station may produce inaccurate exposure estimates and thus lead to exposure misclassification. Improved exposure assessment methods, in particular more accurate spatial measurements or modeling are highly recommended for future birth defect research in relation to the effect of air pollution. Second, the exposure estimation was based on residential address, which may not adequately characterize the individual's actual exposure level. Furthermore, the recorded residence was not the only address during the pregnancy period. Reported rates of mobility between the time of conception and delivery vary widely, from approximately 9% to 32%. Third, this study was limited to reveal the impact of air pollution on birth defects, because other covariates, such as maternal disease history, coexisting comorbidities , and prenatal care, may also influence the results.In this study, the areas, years, season of conception, maternal age, gender of infant, total previous live births, and number of pregnancies were confounding factors. The season of conception and maternal age at conception were the most frequent confounders considered in this study. Social factors such as smoking, parental occupation, socioeconomic status, and educational level were not considered in this study, as this information was not available in the control group. Furthermore, the influence of social factors may be associated with maternal age.52, NO2, and PM10 had an effect on birth defects in the early first trimester. SO2 had the greatest effect in the prophase of pregnancy, while NO2 and PM10 had a greater effect in the late third trimester. We hope that health workers highlighted the impact of air pollution on birth defects when educating pregnant women. What is more, we hope the government focused on the impact of air pollution on birth defects now.Overall, our results indicated an association between exposure to air pollution and birth defects in Hunan province, China. The pollutants SOThe authors gratefully acknowledge all the members involved in the data collection of birth defect information, air quality and meteorological data in the four cities of Changsha, Changde, Yongzhou, and Huaihua.Conceptualization: Lili Xiong, Zenghui Xu.Data analysis: Lili Xiong, Zenghui Xu.Data collection: Lili Xiong, Zenghui Xu, Zhiyu Liu, Donghua Xie, Aihua Wang, Fanjuan Kong.Data curation: Lili Xiong, Zenghui Xu, Donghua Xie, Aihua Wang, Fanjuan Kong.Formal analysis: Lili Xiong.Funding acquisition: Lili Xiong.Methodology: Lili Xiong, Zenghui Xu.Project administration: Lili Xiong, Hua Wang, Zhiyu Liu.Supervision: Lili Xiong, Zenghui Xu, Zhiyu Liu, Hua Wang.Writing – original draft: Lili Xiong, Zenghui Xu.Writing – review & editing: Lili Xiong, Zenghui Xu, Hua Wang, Zhiyu Liu.


To assess the prevalence and associated factors of low birth weight among newborns delivered at Debre Markos Referral Hospital, Northwest Ethiopia.From the total of 368 newborn baby/mother pairs planned to be participated, 338 agreed and involved in the study giving a response rate of 91.2%. In this study, the prevalence of low birth weight was 21.6 . Being rural residence , duration of pregnancy , and having complications during pregnancy  were found to be factors significantly associated with low birth weight.The online version of this article (10.1186/s13104-019-4143-1) contains supplementary material, which is available to authorized users. Globally, low birth weight (LBW) continues to be a major public health problem and it is associated with a range of short-and long-term consequences. Overall, it is estimated that 15%–20% of all births worldwide are LBW, representing more than 20 million births a year . The regLow birth weight newborns are 20 times at higher risk of death as compared to normal birth weight newborns, unless interventions have been made , 7. BesiAs an intervention, the Ethiopian government recognized LBW as a serious public health problem and implemented numerous strategies. In addition, nongovernmental organizations (CU-ICAP and WHO) and professional associations including the Ethiopian Pediatric Society have been working to tackle this problem , 22. CurA hospital-based cross-sectional study was conducted from September 22 to October 25, 2017 at Debre Markos Referral Hospital, Northwest Ethiopia. Debre Markos town is located 300 km far away from Addis Ababa, the capital city of Ethiopia, and 256 km far from Bahir-Dar, the main city of Amhara Regional State. The hospital is expected to provide services for more than 3.5 million people in its catchment area. Apart from other services, the hospital provides ANC and delivery services for pregnant women.All mothers who gave birth at Debre Markos Referral Hospital from September 22 to October 25, 2017 were our source population. All newborn babies consecutively delivered at Debre Markos Referral Hospital during the study period were included. However, newborn babies whose mothers suffered from severe medical (diabetes mellitus) or surgical condition, twin delivery, mothers with unknown last menstrual period (LMP) with the absence of ultrasound evidence at the time of the study period were excluded from the study.The required sample size was calculated by using a single population proportion formula, and calculated using Open Epi Version 3. To calculate our sample size, the following statistical assumptions were considered: P = prevalence of low birth weight 32.1% taken from a study conducted in Ethiopia , Z α/2 =2 *0.32*0.68/(0.05)2 = 334. Finally, after adding 10% of none response rate the final sample size of our study was calculated as 368. All 368 newborn babies consecutively delivered at Debre Markos Referral Hospital during the study period were planned to be included.N = (1.96)Low birth weight was defined as the neonate birth weight less than 2500 grams.Birth interval was defined as the length of time between two successive live births.Data were collected using an interviewer administered structured questionnaires. The questionnaire was prepared after reviewing similar studies conducted in Ethiopia, and Ethiopian demographic and health survey, 2016. It was first prepared in English language, then two language experts translated to Amharic, and translated back to English to check for consistency. To ensure data quality, a 1-day training was given regarding data collection tool and data collection process for both data collectors and supervisor. In the data collection process, three female intern nursing students were involved. Every day, at the end of the data collection period, all questionnaires were reviewed and checked for any errors by the supervisor and data collectors.p value less than 0.2 were fitted into the multivariable logistic regression analysis for controlling the effect of confounders. Odds ratio with their 95% of CI was computed and variables having p-values less than 0.05 in the multiple logistic regression models were considered as significantly associated with the dependent variable.All filled questionnaires were checked for completeness, consistency, accuracy and entered into Epi-Data Version 3.1 and then, exported to SPSS software version 22 for data analysis. Frequency, proportion, and summary statistics (mean and median) were used to describe the study population in relation to the relevant variables. Bivariable logistic regression analysis was used to check the association between dependent and independent variables. Then, in the bivariable analysis those variables having From the total of 368 newborn baby/mother pairs planned to be participated, 338 agreed and involved in the study giving a response rate of 91.2%. The mean age of mothers was 29.9 years (SD = ± 6.7) and more than half of the respondents (61. 8%) were found within the age group of 21–34 years. Regarding religion, the majority (86.1%) of women are orthodox religion followers. Similarly, the majority (97.9%) of mothers were from Amhara Region. Concerning marital status, majority (93.5%) of the mothers were married, and about half (50.3%) of the mothers were from urban areas  of the pregnancies were intended. With regard to current pregnancy related problems, only 77 22.8%) developed the problems. Three hundred sixteen (93.5%) have no history of low birth weight. Two hundred eighty-nine (85.5%)) of the mothers had ANC follow up. Of which, 29 (8.6%) had four and above ANC follow up care (Table 2.8% deveTwo hundred twenty-even (67.2%) of the mothers were counseled about dietary intake during antenatal care follow up. Ninety-two (27.2%) of them took extra meal during pregnancy. Three hundred thirty-six (99.4%) of the respondents did not smoke during pregnancy. Regarding alcohol drinking one hundred ninety-two (56.5%) of the respondents did not drink alcohol during their pregnancy. Among three hundred thirty-eight newborns 149 (44%) were females . The mean birth weight of the neonates was 2945.6 g (SD ±  594.3 g).In the multivariable logistic regression analysis, place of residence , having complications during the current pregnancy, and duration of pregnancy (being preterm) were found to be an independent predictors of low birth weight. Accordingly, residence of the mother was strongly associated with low birth weight; mothers living in the rural areas were 2.0 times more likely to have LBW babies when compared to those mothers who live in urban area . In addition, mothers who had any form of complication during the current pregnancy were 2.6 times more likely to give LBW babies as compared to their counterparts . Moreover, duration of pregnancy was also another strong predictor of low birth weight. From this finding, preterm (< 37 weeks) babies were 7.6 to have LBW as compared to term (≥ 37 weeks)  . This finding is in line with studies conducted in Gondar University Referral Hospital (17.1%) , Jimma Z.5, 26%. The study found that mothers from rural areas were more likely to deliver LBW baby as compared to their urban counterparts. This finding is consistent with studies conducted in Bale Zone, Southwest Ethiopia, and Tigray, Northern Ethiopia , 18. HowIn this study, mothers who had complications during the current pregnancy were more likely to have LBW newborns as compared to mothers who hadn’t any pregnancy related complications. This finding contradicts with a previous study conducted in Ethiopia . This stFurthermore, gestational age was also another important factor, which strongly associated with the occurrence of LBW. Likewise, newborn babies born before gestational the age of 37 weeks were more likely to be LBW as compared to that of newborn babies born at the gestational age of 37 weeks and above. This finding is in concordance with previous studies conducted in Ethiopia , 16, 20.The study is a cross sectional study; therefore, it doesn’t show a cause and effect relationship as well as it doesn’t show seasonal variation in low birth weight. In addition, important factors like intrauterine infections during pregnancy, issues related to placental abnormalities and pre-pregnancy weight were not addressed due to lacking of data. Moreover, the study unable to include mothers who delivered at home because the study was conducted in the hospital.Additional file 1: Table S1. Nutritional, behavioral and neonatal factors of the respondents at Debre Markos Referral Hospital Northwest Ethiopia, 2018.Additional file 2: Table S2. Bivariable and multivariable logistic regression analysis of factors associated with low birth weight at Debre Markos Referral Hospital, Northwest Ethiopia, 2018.


Despite progress made towards increasing birth registration rates over the last dozen years, almost one in two children may still not get registered at birth in Niger according to a recent nationally representative household survey. What can be done to improve birth registration rates? This paper relies on a simple approach to measure how solving various obstacles to birth registration faced by parents could help increase birth registration rates. Controlling for other factors affecting birth registrations, the analysis relies on local-level reasons declared by households for not registering their children. The estimation method provides measures of potential gains in birth registration rates from different actions, including providing services closer to where households live, improving household knowledge about the fact that birth registration is both mandatory and beneficial for children, and reducing the out-of-pocket costs of birth registration. The analysis remains exploratory, but it provides hopefully useful insights about the likely benefits that could be derived from various policies utilized for increasing rates of birth registrations. Birth registration is defined as “the continuous, permanent and universal recording within the civil registry of the occurrence and characteristics of birth” . There iFrom a management and policy point of view, birth registration is a component of civil registration. Systems for birth registration are therefore part of broader civil registration and vital statistics (CRVS) systems. Civil registration is defined by the United Nations (UN) as the “universal, continuous, permanent and compulsory recording of vital events provided through decree or regulation in accordance with the legal requirements of each country” and vital statistics are “a collection of statistics on vital events in a lifetime of a person as well as relevant characteristics of the events themselves and of the person and persons concerned.”  While biInternational agencies such as the United Nations International Children’s Emergency Fund (UNICEF), the World Health Organization (WHO), and the World Bank Group (WBG) are supporting efforts by low- and middle-income countries to improve their CRVS systems . In someEstimates from a 2015 survey used in this paper put birth registration rates at 52% nationally, but regardless of which percentage estimate is used, which may depend on the survey, there is no doubt that major gains have been achieved. By comparison, in the 12 years preceding the 2006 Demographic and Health Surveys, the gains achieved were much smaller, at only 8 percentage points, from 24 to 32%.How did Niger achieve such gains? As described in the recent diagnostic conducted by the World Bank, the birth registration process became more efficient thanks to the introduction of auxiliary notification offices. Since 2008, the civil registration system has consisted of not only primary and secondary registration centers located in the administrative capitals of communes or communes’ substructures, but also of auxiliary notification offices in healthcare facilities where vital events occur. Staff in these auxiliary centers notify primary or secondary centers of vital events such as births, with these centers then completing the birth registration process and issuing official documents. This helped triple the number of registration centers between 2007 and 2012. In addition, the fact that births at healthcare facilities are now automatically registered reduces leakage. Finally, large mobile birth registration campaigns were implemented in the country between 2009 and 2011. Of these various initiatives, the creation of the auxiliary notification offices is probably the initiative that had the largest impact because it enabled parents and midwives to record births where the children were born.Despite major progress, much remains to be done. According to the national survey used in this paper, in 2015, almost one in two children was still at risk of not being registered. Guidance is available in the literature on interventions that can help boost birth registration rates  as well The paper relies on a simple approach to assess how solving various obstacles to birth registration could help. Controlling for other factors affecting birth registrations, the estimation provides measures of potential gains in birth registration rates from providing services closer to households, improving knowledge among parents about the fact that birth registration is both mandatory and beneficial for children, and reducing the out-of-pocket costs of birth registration. The analysis remains exploratory, but it provides hopefully useful insights about the likely benefits from various policies for increasing rates of birth registrations in countries such as Niger.The objective of the paper is to analyze the correlates of birth registration in Niger using regression analysis, with a specific focus on the reasons declared by parents as to why they have not registered their children at birth. The availability of data on those reasons helps in assessing the role of various constraints faced by parents in registering their children, after controlling for a wide range of variables that may also affect birth registration. In turn, the results can help inform policy options to increase birth registrations. This is done through simulations of the potential effect on overall birth registration rates of solving the various obstacles leading to low birth registration rates.The data used are from the nationally representative ENISED survey  implemented in Niger in 2015 by the National Statistical Office. The objectives of the survey were (a) to measure achievements towards achieving the Millennium Development Goals (MDG) and targets adopted in the 2012–2015 Economic and Social Development Plan (PDES in French), (b) to provide a baseline for the 2016–2020 PDES, and (c) to monitor progress towards the Sustainable Development Goals. The survey includes information among others on (i) the characteristics of dwellings; (ii) household members and population data; (iii) marriage and fertility; (iv) family planning; (v) maternal and child health; (vi) malaria; (vii) breastfeeding and nutritional status; (viii) under-5 mortality; (ix) maternal mortality; (x) birth registration; (xi) knowledge, attitudes, and practices of HIV/AIDS; (xii) justice, governance, and security; and (xiii) accessibility of selected services.Given that birth registration, the dependent variable, is a dichotomic variable, either a logit or probit regression could be used to assess the correlates of birth registration. This analysis relies on probit regressions, with the marginal effects at the mean of the sample reported together with their standard errors. These marginal effects represent the percentage point increase or decrease in the likelihood of birth registration associated with various variables.As is the case for any cross-sectional analysis of this nature, the marginal effects represent associations as opposed to true causal effects that could be obtained through experimental or quasi-experimental approaches. Nevertheless, estimates show an order of magnitude for the potential effects of variables on the likelihood for children to be registered. The sample for analysis includes all children under age 5 in the survey for which information is available on their birth registration status. Sample weights are used when providing basic statistics.The ENISED survey includes a range of variables that could affect the likelihood of birth registration. Apart from variables at the level of children and parents/households, the survey includes information on the reasons why parents have not registered their child. To capture local geographic effects affecting birth registration, a first approach consists of including the leave-out-mean (LOM) birth registration rate in the primary sampling unit in the independent variables. The LOM birth registration rate is computed for all other children in the primary sampling unit, but not the child being considered, to avoid issues of endogeneity. The LOM birth registration rate is thus a measure of the ease of birth registration at the local level based on the share of other children at the local level who have been registered. This variable is likely to capture mostly supply-side factors affecting birth registration rates, but it could also capture demand-side effects related, for example, at the local level to social norms or affordability issues.This LOM birth registration rate variable essentially captures all local effects that matter for birth registration, whether this relates to the distance to registration offices or other factors. A second approach to look at the potential impact of local effects consists of relying on LOM estimates of the shares of parents mentioning various reasons for nonregistration. This approach provides more information since the magnitude of the impact of various reasons for nonregistration as declared by other households in the primary sampling unit can be used to assess the impact of various constraints at the local level on each household individually. The approach is not perfect since reasons mentioned by other households need not apply to any given individual household, but it provides an order of magnitude of the gains that could be achieved under various scenarios whereby obstacles to birth registration are being removed locally.Note that birth registration rates tend to be higher among women who deliver their child in health facilities, while rates are lower for women delivering at home. This is also the case in Niger. Unfortunately, the data on the location of deliveries is available only for children born in the last 12 months, while the regression analysis is conducted for all children under 5 to have a larger sample size and give more time for the registration to be observed. Therefore, the variable where women deliver their children is not included in the regression analysis.Table The reasons invoked by parents for not registering their children include the lack of offices where birth registration can take place ; the remoteness of registration offices—which means that the offices are far from where households live (27.50%); the fact that parents do not know that they should register their children (29.90%); the fact that parents think that birth registration is not useful (14.96%); and the cost of birth registration (5.07%). Note that the remoteness of offices is subjectively declared by households—it is not based on an actual measure of the distance or time it might take for households to reach those offices as such measures are unfortunately not available in the survey.For those not registering their children, lack of availability and remoteness are cited more often in rural areas, while lack of utility and cost are cited more often in urban areas. As mentioned in the introduction, in recent years, major progress was made in reducing the distance to registration facilities. While acknowledging the benefits of this reform, estimates in Table Table While cost is not the main obstacle to birth registration, according to Table As background for the regression analysis, Table Consider first the characteristics of the population. Most of the population is rural (85.8%), and among urban households, more than a third live in the capital city of Niamey. The most populated region is Zinder, with 23.2% of the population, while the least populated region is Agadez, with 2.45%. Households are categorized according to five quintiles of wealth, with wealth measured through a factorial analysis of key assets owned by the households . The firThe vast majority of household heads and spouses have no education at all, especially in rural areas. While efforts related to Education for All and other international initiatives are paying off in terms of increasing school enrollment, most of the adult population did not benefit from such efforts at the time when they were of schooling age. For spouses, an additional variable of interest is whether they married as children, that is, before the age of 18. This is indeed the case for 84.54% of spouses . Just under a third of rural heads of household are polygamous and the proportion is just under one-fourth in urban areas. Most household heads are engaged in agriculture, with trading being the second most important employment category.Next, we consider birth registration rates. The rates are lower for girls than boys. They also vary by geographic location, with, for example, 9 in 10 children registered in Niamey and Tahoua versus only 1 in 3 registered in Zinder. Also, as expected, is the fact that birth registration rates are higher in the top quintile of wealth, especially in urban areas. In rural areas too, birth registration rates are much higher in the top two quintiles in comparison to the bottom three even if they do not reach the levels achieved in urban areas in those quintiles. There is also a clear difference in birth registration rates by the education level of the household head and the spouse, with higher educational attainment typically associated with higher birth registration rates, albeit with a few exceptions. Birth registration rates are also higher when the mother married at an adult age than when she did as a child. Finally, the occupation of the household head also shows a relationship with birth registration rates, for example with, as expected, much higher rates (93%) among household heads working in administration . The question is whether all those associations remain when controlling for other variables affecting birth registration rates.To measure the relationship between the various variables and the likelihood of birth registration while controlling for other factors affecting birth registration, probit regressions are estimated. Table Consider first the findings for child-level characteristics. There is evidence that girls are less likely to be registered at birth than boys, which may denote parental preferences for boys. Controlling for other variables, girls are less likely to be registered by about three percentage points in both models. There is a negative association in rural areas between the age of the child and the likelihood of birth registration. This may seem surprising but is likely related to the efforts undertaken by the government to increase birth registration rates in rural areas in the years preceding the survey. These efforts have led to higher birth registration rates among younger children. Whether a child has a disability or not does not seem to affect the birth registration rate.Consider next the parental and household characteristics. A higher level of educational attainment for the spouse is associated in a statistically significant way with a higher likelihood of birth registration for a child at the primary and secondary level . Gains are also observed for the educational attainment of the head of household, but they tend to be smaller and less often statistically significant. A higher socioeconomic status, as measured by the quintiles of wealth, also is a positive factor, starting with the fourth quintile in rural areas and the fifth quintile in urban areas .Occupations matter as well, especially for the head of household, with domestic work associated with a lower likelihood of birth registration than the reference category of agricultural workers. In rural areas, being in administration is associated with a large increase in the likelihood of birth registration as was the case for basic statistics, but this is not the case in urban areas where birth registration rates are higher. Trading—which may denote a different status depending on whether the household is in rural or other areas, is associated with a gain in birth registration in rural areas and a loss in urban areas versus heads of the household involved in agriculture. Occupational effects for spouses tend not to be statistically significant with a few exceptions.The marital status of the head of household, or the fact that the spouse married as a child, does not seem to have an effect. For the number of children in the household, effects in urban areas are negative for children aged 6–12 (possibly because of implications for standards of living or because the need to take care of those children reduces the time available to register children), while they are positive for older children . In urban areas, the effects are less likely to be statistically significant.Consider finally findings for geographic effects at the level of regions as well as the effects of the LOM variables at the level of primary sampling units. First, there are differences in the likelihood of birth registration between regions after controlling for other variables that may affect birth registration, but these effects are observed mostly in rural areas, and many are not statistically significant. Second, as mentioned in the introduction, the LOM variables capture local effects affecting birth registration in different geographic areas. When the LOM for birth registration is used, it is likely to capture supply-side factors , but it may also account for demand-side factors such as social norms or perceptions about the utility of birth registration. When the LOM variables for the obstacles to birth registration are used, the information provided is more granular.In the first model, there are clear local effects at work, with the magnitude of the effects being larger in urban than in rural areas. In the second model, the role of different factors can be explored since effects are available by the type of factor that leads parents not to register their children. In rural areas, all LOMs have large effects, but the largest effects in terms of the size of the marginal effects are observed for lack of availability and remoteness, followed by lack of knowledge, lack of utility, and cost. In urban areas, the ranking is different, as expected. Perceptions of a lack of utility matter more when they are observed according to the magnitude of the marginal effects, followed by lack of knowledge, lack of availability, and remoteness, with the marginal impact for costs not being statistically significant.Using the second model, predictions can be made as to the gains in birth registration rates that could be achieved if the obstacles mentioned by households were alleviated. Essentially, the simulations set at zero the proportion of households mentioning any specific constraint at the local level and rely on the estimates of marginal impacts to predict birth registration rates. The magnitudes of the gains thus depend on both the estimates of the marginal effects and the proportions of households citing each specific reason for not registering their children.The results are provided in Table Despite major progress in recent years towards higher birth registration rates, almost one in two children may still not be registered at birth in Niger according to a recent nationally representative household survey. What can be done to improve birth registration rates? The factors leading to low birth registration are multiple, but the analysis of the ENISED survey provided in this paper suggests that some factors may play a larger role than others. Child-level factors, parental and household level factors, and local-level factors have been considered.In terms of child-level characteristics, girls are less likely to be registered at birth than boys, even after controlling for a wide range of other factors that may affect birth registration. This may denote parental preferences for boys within the context of broader social norms that lead to multiple forms of disadvantage for girls and women, ranging from child marriage to lower levels of educational attainment, and lower earnings and labor force participation, than for men. Yet, while gender effects seem to be present, other factors have a larger effect on the likelihood of birth registration. Lack of educational attainment, especially for women, as well as lower levels of household wealth and less attractive employment for heads of household, are all associated with substantial reductions in the likelihood of birth registration for young children.Still, the factors that tend to have the largest effect on birth registration are local effects related to whether services are available to register children in proximity to households, whether parents know that they should register their children, whether they are convinced that there are benefits of doing so, and whether they can afford the cost of birth registration. These effects were captured using LOM variables at the level of the primary sampling units where households live. Simulations based on the regression analysis suggest that in both rural and urban areas, the largest gains in birth registration rates would be observed from solving issues related to remoteness, lack of knowledge, and lack of availability of services for birth registration. However, as expected, gains would be much smaller in urban than in rural areas. Issues of cost, while important, play a smaller role in leading to nonregistration.In a country as large as Niger, where population density is low, it should not come as a surprise that issues related to the lack of service availability or the remoteness of available services play an important role in the tendency for many children not to be registered at birth. But the approach used in this paper helps in quantifying those effects, while also pointing to other constraints, such as the fact that many parents do not know that they should register their children, or do not find it useful to do so. The policy responses to these various issues need to be varied and adapted to local realities. Different regions, or smaller geographic areas within broader regions, face different challenges. The good news is that information on the reasons leading parents to not register their children can be used to tailor appropriate interventions.


Subchondral bone cysts are a widely observed, but poorly understood, feature in patients with knee osteoarthritis (OA). Clinical quantitative computed tomography (QCT) has the potential to characterize cysts in vivo but it is unclear which specific cyst parameters  are associated with clinical signs of OA, such as disease severity or pain. The objective of this study was to use QCT-based image-processing techniques to characterize subchondral tibial cysts in patients with knee OA and to explore relationships between proximal tibial subchondral cyst parameters and subchondral bone density as well as clinical characteristics of OA , OA severity, pain) in patients with knee OA.The preoperative knee of 42 knee arthroplasty patients was scanned using QCT. Patient characteristics were obtained, including OA severity, knee pain, JSN, and alignment. We used 3D image processing techniques to obtain cyst parameters including: cyst number, cyst number per proximal tibial volume, cyst volume per proximal tibial volume, as well as maximum and average cyst volume across the proximal tibia, as well as regional bone mineral density (BMD) excluding cysts. We used Spearman’s correlation coefficients to explore associations between patient characteristics and cyst parameters.At both the medial and lateral compartments of the proximal tibia, greater cyst number and volume were associated with higher BMD. At the lateral region, cyst number and volume were also associated with lateral OA severity, lateral JSN, alignment and sex. Pain was not associated with any cyst parameters at any region.Cyst number and volume were associated with BMD at both the medial and lateral compartments. Lateral cyst number and volume were also associated with joint alignment, OA severity, JSN and sex. This is the first study to use clinical QCT to explore subchondral tibial cysts in patients with knee OA and provides further evidence of the relationships between subchondral cysts and clinical OA characteristics.The online version of this article (10.1186/s12891-018-2388-9) contains supplementary material, which is available to authorized users. Knee osteoarthritis (OA) is a painful and debilitating disease characterized by cartilage deterioration and altered subchondral bone. Recently, there has been increasing interest in the role of subchondral bone cysts in OA progression; in particular how subchondral bone cysts may influence pain –3, or hoSubchondral cysts are typically spherical or ellipsoidal cavities within the subchondral bone region and are related to both altered subchondral bone and cartilage degeneration in patients with OA –7. RecenSubchondral cysts are associated with higher localized stress , which cThe objective of this study was to use QCT and image-processing techniques to determine relationships between subchondral cyst parameters and subchondral BMD as well as clinical characteristics of OA  in patients with knee OA.Forty-two participants  with OA were recruited before total knee replacement. Study exclusion criteria included: pregnant women, patients having a revision replacement instead of primary knee replacement, and patients with a prior history of bone pathology at the knee joint. The Institutional Research Board of the New England Baptist Hospital approved the study. Informed written consent was obtained from all study participants. Patient selection, inclusion, and exclusion was intentionally very broad due to the exploratory nature of this study, as well as limited availability of participants scheduled for knee replacement surgery at the participating hospital.o  [o as varus alignment and an angle greater than 180o as valgus alignment. For this analysis, alignment was treated as a categorical variable, where participants exhibited either varus (− 1), neutral (0), or valgus (1) alignment. Pain severity was measured at the affected knee joint using the pain subsection of the Western Ontario McMasters Osteoarthritis Index (WOMAC) [The participating orthopaedic surgeon (CT) used standardized radiographs with Kellgren-Lawrence (KL) scoring  to class76-180o) . We defi (WOMAC) . Partici (WOMAC)  We used  (WOMAC)  to assesWe used a single energy clinical CT scanner  for bone imaging. A solid QCT spine reference phantom of known bone mineral densities  was included in all CT scans. Participants were oriented supine within the CT gantry and both legs were simultaneously scanned. Scans included the distal femur, patella, proximal tibia, but only the proximal tibia was analyzed with this study.CT scanning parameters included: 120 kVp tube voltage, 150 mAs tube current-time product, axial scanning plane, 0.625 mm isotropic voxel size , ~ 250 slices, ~ 60 s scan time. A standard bone kernel (BONE) was used for CT image post-processing. Effective radiation dose was ~ 0.073 mSv per scan, estimated using shareware software . For comparison, the average effective radiation dose during a transatlantic flight from Europe to North America is about 0.05 mSv .3 K2HPO4) values were obtained by converting grayscale Hounsfield units (HU) to BMD using subject-specific linear regression equations developed from known densities within the QCT phantom included in each axial image (r2 > 0.99) [Equivalent volumetric BMD (mg/cm > 0.99) .We used a custom algorithm  to isolate the subchondral region of the proximal tibia, by measuring a depth of 7.5 mm from the subchondral surface  were not included in this analysis to mitigate any errors due to noise. For cases where cysts were partially inside and partially outside the 7.5 mm depth, we only included these cysts if more than 50% of their total volume was inside the 7.5 mm depth.Cysts were identified and manually segmented using commercial software  and an interactive touch-screen tablet . A single user (WDB), trained by senior researchers with guidance from an Atlas  and prev3), cyst volume per total volume (%), total cyst volume (mm3), maximum cyst volume (mm3) and average cyst volume (mm3). To assess the repeatability of the cyst outcomes, a precision study was performed using recommended techniques (14 subjects scanned 3 times each = 42 image datasets) [RMS) ranged from 0.7 to 3.6%.We used a custom algorithm (Matlab 2016a) to measure the following cyst parameters across the subchondral region : number atasets)  whereby RMS) ranged from 0.9 to 2.4%.We also determined relationships between cyst parameters and subchondral BMD, excluding cysts. Segmented cyst volumes were subtracted from the previously defined subchondral volume of the proximal tibia Fig. d, to detProximal tibia imaged volumes were reoriented to a neutral position where medial and lateral plateaus were approximately parallel and divided into medial, central and lateral compartments, measured by using 40% of the maximum medial-lateral axis of each respective side Fig. d. We evap < 0.001 and p < 0.05.We report mean and standard deviation (SD) as well as median and range of cyst characteristics at total, medial, and lateral regions. As many of the measures exhibited wide and non-normal distributions, we used non-parametric Spearman’s rank correlations to determine associations between cyst parameters and participant characteristics  and clinical characteristics of OA . We report associations between cyst characteristics and participant characteristics  as these are known confounders for BMD , 24 and n = 42), total cyst number varied from none (0) to up to 30 over the total proximal tibia and up to 29 in the medial compartment and 11 in the lateral compartment . As medial OA is more commonly reported [Interestingly, there were no associations between cyst parameters and OA severity at either the total proximal tibia or the medial compartment, but lateral OA severity was associated with all lateral cyst parameters  and participant characteristics in vivo as had previously only been done ex vivo using non-clinical imaging tools such as micro-CT  and HR-Q3). It was also challenging to differentiate between small cysts and surrounding bone. Second, it was challenging to determine individual cysts with adjacent large cysts that would sometimes connect with one another in some participants. In these cases, these were counted as a single large cyst, but could also be regarded as multiple smaller cysts, which could have merged into a large cyst-like void. This could account for multiple large cysts within our study. Third, our alignment measurement was a custom in-house approach using CT reconstructions and relative joint space widths to approximate mechanical alignment. Although this technique has not been validated against full-limb radiographs, in these patients with late OA malalignment was evident with values ranging from − 18° to 8° from neutral position [This study has certain limitations to consider. First, our measurements use a larger voxel size than ex vivo approaches such as micro-CT and may ignore smaller cysts. It was difficult to reliably quantify any cysts smaller than 8 voxels , when investigating which structures are associated with pain.Additional file 1:Table S1 Mann-Whitney U tests determining differences in cyst characteristics between male and female participants. We report medians and ranges. Significant differences (p < 0.05) are bolded. With regards to why no results are provided for Males at the lateral compartment, this is because only 1 male had lateral cysts. (DOCX 17 kb)Additional file 2:Table S2 Differences in patient characteristics between males and females. Independent samples t-tests were used for continuous variables and Chi-squared tests were used for categorical variables . Significant differences are bolded. (DOCX 18 kb)Additional file 3:Table S3 Cyst parameters from participants only with cysts specific to each compartment, mean ± SD . (DOCX 19 kb)


Phosphatidylcholine (PC), the most abundant of the phospholipids, has several metabolic functions in organs such as the liver and the intestine, important structural- and signaling functions in biological membranes, and might have a role in the effects of Roux-en-Y gastric bypass (RYGB), an operation known to ameliorate metabolic diseases, including type 2 diabetes. We hypothesized that serum PC, as a reflection of phospholipid metabolism, changes after RYGB, and that changes are related to weight loss and possibly to changes in glucose metabolism (reflected in the HbA1c-level) as well as to changes in serum Apo A1, Apo B and Apo B/Apo A1 ratio.In a cohort of 220 RYGB patients, we studied changes in serum PC after RYGB in relation to serum Apo A1 and Apo B, the main apolipoproteins in HDL- and LDL/VLDL-particles, respectively, up to 2 years following RYGB-surgery.Serum PC reached its lowest levels 3 months postoperatively to later rebound to preoperative levels 24 months after RYGB. No difference was seen between patients with or without type 2 diabetes. Serum Apo A1 showed a similar pattern whereas serum Apo B concentrations stayed low after the initial decrease after RYGB. As a result, the Apo B / Apo A1 ratio constantly decreased during follow-up. There was a strong positive correlation between PC and Apo A1, and between PC and Apo B, but none between Apo A1 and Apo B. After RYGB surgery, both PC and Apo A1, but not Apo B, correlated positively to weight loss. In relation to total cholesterol, the molar ratio between serum PC and plasma cholesterol increased steadily after RYGB.We conclude that changes in PC and apolipoproteins after RYGB are highly dynamic, reflecting a large plasticity and capability of accommodating lipid metabolism including PC-, cholesterol- and apolipoprotein metabolism imposed by RYGB surgery, independent of glucose tolerance. We suggest that after RYGB and major weight loss, PC and Apo A1 might have a special role in the altered metabolism of lipoproteins.The online version of this article (10.1186/s12944-019-1111-7) contains supplementary material, which is available to authorized users. Within the research field of metabolic disease, increased attention has been given to lipids in biological membranes. For instance, major glycerophospholipids phosphatidylcholine (PC) and phosphatidylethanolamine, are suggested to be involved in development and progression of metabolic disease , as membRecently, we described how levels of sphingomyelin, another membrane lipid, related to diabetes status in an obese population operated with Roux-en-Y gastric bypass (RYGB) . The RYGPC is the most abundant phospholipid  with itsAfter RYGB, a decrease in PC levels as well as increased levels of PC, depending on the PC-subspecies have been reported –14. Graen = 220). Levels of Apo A1 and Apo B have both previously been shown to change after RYGB , but our concentrations were generally about 2.5 times higher. In a subsample of our material we also measured hydrogen peroxide and glutathione with commercial assays from Cell Biolabs, Inc. (STA-344) and Thermo Fisher Scientific (EIAGSHC), respectively. The concentrations of both analytes were very low and were not assumed to influence the measure of PC significantly. The size of the interference was higher (up to 16%) in the samples from the reference population, possibly due to differences in handling and storage conditions. Concentrations of PC in these samples were therefore adjusted according to the measures of free choline.Because endogenous free choline and possibly free hydrogen peroxide can interfere with the assay principle, we repeated the analysis with a lower set of standards and without phospholipase, as previously described . As the Serum Apo A1 and Apo B were measured with the immunoturbidimetric Tina-quant version 2 assays for Apolipoprotein A-1 and Apolipoprotein B respectively, on Cobas 6000 c501 module from Roche Diagnostics. The concentrations of Apo A1 and Apo B are reported in μmol/L.The methods for other routine measures such as HbA1c, Plasma Triglyceride, Plasma Total-, LDL-, HDL- and VLDL cholesterol have been described previously .P-values lower than 0.05 were considered statistically significant. Throughout the article, data are written as mean with a 95% confidence interval and correlations as correlation coefficients rs, with the degree of freedom and p-value.The IBM SPSS version 22 was used for all analyses. Normal distribution and homogeneity of variances of most parameters generally allowed for use of parametric tests, including the one-way ANOVA and Tukey post hoc test for multiple comparisons across groups, the independent t-test for comparing only two subgroups and the paired t-test for comparing the same group of patients before and after RYGB. To avoid impact of missing data, repeated paired t-tests have been used rather than a repeated measures ANOVA to detect changes following RYGB. Where Levene’s test of equality of variances was statistically significant, the one-way ANOVA was performed with a Welch-Satterthwaite correction followed by a Games-Howell post hoc test. For a few parameters without normal distribution, significant differences between subgroups found using the normal one-way ANOVA were confirmed with a Kruskal-Wallis H-test. This applied to Triglyceride, VLDL-cholesterol and HbA1c. The correlations between lipids-, lipoproteins and body weight were determined by Spearman’s correlation. 2) as well as at all time points after RYGB (24 months BMI: 29.7 (28.3–31.2) kg/m2) [The preoperative clinical characteristics for all patients, the three main patient subgroups and the reference population are shown in Table  29.7 28.–31.2 kg/) kg/m2) . Statin All 220 patients were represented with PC measurements at 3 months follow up and then dropped to 158, 147 and 89 at 6, 12 and 24 months, respectively  in the whole study population  and 1651 (1611–1690) μmol/L compared to 1540 (1468–1612) μmol/L 3 months after RYGB (p = 0.004). As shown in a supplementary table, no differences between patients with or without diabetes nor between the two diabetes subgroups were evident  μmol/L before surgery to 1615 (1580–1651) μmol/L 3 months after RYGB  μmol/L. In this population, the gender difference was smaller than in the study population and not significant. There were no correlations between PC and body weight, nor between PC and BMI in this population.p = 3,5 e− 9)  and continued to increase significantly during the remaining follow up period to a mean concentration of 61.13 (58.98–63.28) μmol/L at 24 months postoperatively  μmol/L to 47.05 (46.00–48.09) μmol/L 3 months after RYGB  = 0,141, p = 0.037), serum Apo B did not correlate to body weight, BMI or weight loss.For Apo B, changes in serum concentrations occurred immediately after RYGB, where a significant fall was observed from 1.88 1.81–1.94) μmol/L before surgery to 1.62 (1.56–1.67) μmol/L 3 months after RYGB,  μmol/L bp = 2 e− 4). Three months after RYGB, only the subgroup of diabetes patients with persistent hyperglycemia had lower ratios compared to the patients without diabetes and there was a significant difference between the two diabetes subgroups  decreased after RYGB in a linear manner in the whole study population Fig. p =  e− 4. Thp = 2.5 e− 16 and continued to increase during the rest of the follow up period in all patient subgroups  μmol/μmol before surgery to 24.9 (24.4–25.3) μmol/ μmol 3 months after RYGB, p = 1.4 e− 4) and increased linearly after RYGB in the group of patients without diabetes  compared to 0.453 (0.425–0.481)  μmol/L before surgery to 22.24 (21.39–23.09) μmol/L 3 months after RYGB, In the present study we report the dynamic development in the major apolipoproteins, cholesterol and PC after RYGB. In the short term, serum Apo A1 and PC exhibited a significant decrease, however, which turned to an increase, approaching the pre-surgery levels after 2 years. Interestingly, the cholesterol content of the Apo A1 particles constantly and robustly increased during the 24 months survey without a dip in levels at 3 months after surgery. The serum levels of Apo B also decreased after RYGB, but in contrast to Apo A1 the levels stayed below pre-surgery levels without any rebound. As a result, the Apo B / Apo A1 ratio constantly decreased during the first 2 years of follow-up after RYGB.Similar to what Graessler  and KaysThe size and direction of correlations between serum PC and Apo A1 and Apo B that we have reported here were similar to those previously reported by Kayser .The changes we observed in serum Apo A1, Apo B and the Apo B / Apo A1 ratio after RYGB were in agreement with results from previous studies , 17, 23.The linear increase in PC / cholesterol ratio after RYGB and the similar patterns of changes in relation to lipoproteins for both PC and cholesterol might suggest that levels of PC per HDL-particle increased in a similar manner as cholesterol. This is of course highly hypothetical, as this study does not measure HDL-PC levels, but it would agree well with results from Aron-Wisnewsky’s study on 34 morbidly obese women that showed an increase after RYGB in phospholipid content in a sub-fraction of large HDL that itself was statistically significantly increased after RYGB . PC is kIt is not known whether the changes in serum PC concentration are a result of the altered lipoprotein particle ensemble after RYGB or if PC-metabolism is driving the changes in lipoprotein numbers and composition. In the liver, PC is of general importance for secretion of VLDL particles and can, in addition to the common pathway, be synthesized through methylation of phosphatidylethanolamine . PC, delIn the groups of patients with diabetes, we observed no changes in ratios involving Apo B and or LDL-cholesterol. This might in part be explained by the large heterogeneity in these groups but can also be due to the higher frequency of statin therapy, a frequency that was not constant in the follow up period and that differed between the two diabetes subgroups. Therefore, changes in the group of patients without diabetes probably best resemble the “true” changes after RYGB. Some statins have also been shown to affect phospholipid concentrations –26. In oWe observed a fall in mean serum choline concentrations after RYGB to a much lower level that was constant during the rest of the follow up period. The supply of intestinal choline may be reduced by the by-pass of the phosphocholine-generating alkaline sphingomyelinase in the proximal intestine . A decreOne important confounder was the variation in time between sampling of the pre-surgical sample and date of surgery, some samples taken months before surgery. This means that some changes that we see might in part be attributable to life style changes before surgery, as for example described by Kjellmo, who reported of a preoperative 10% weight loss and significant decrease in Apo B .Furthermore, we do not have registrations on individual-level dietary intake. The observed changes in PC and apolipoproteins may partly be explained by the changes in total energy intake that generally are seen after RYGB . Less likely, changes in PC and apolipoproteins may result from changes in food preferences. However, it has previously been shown that food preferences were unchanged 6 months after metabolic surgery in a study-population similar to ours . StudiesIn conclusion, the most striking findings in the present study are the dynamic changes in circulating levels of the major apolipoproteins, cholesterol and PC. In the short term after RYGB, serum Apo A1 and PC exhibited a significant decrease, however, which turned to an increase approaching the pre-surgery levels after 2 years. This pattern was most pronounced for patients without diabetes but was also seen for patients with diabetes. The cholesterol content of the Apo A1 particles constantly and robustly increased during the 24 months survey without a dip in levels at 3 months after surgery. The levels of Apo B also decreased after RYGB, but in contrast to Apo A1 the levels stayed below pre-surgery levels without any rebound. As a result, the Apo B / Apo A1 ratio constantly decreased during follow-up. We interpret the findings as reflective of a large plasticity and capability of accommodating lipid metabolism imposed by RYGB. We suggest that after RYGB and major weight loss, PC and Apo A1 might have a special role in the altered metabolism of lipoproteins.Additional file 1:Figure S1. Changes in Weight, BMI and HbA1c at 3, 6, 12 and 24 months after Roux-en-y gastric bypass (RYGB) surgery in patients without diabetes mellitus (DM), patients with DM in remission after RYGB and patients with DM and continued hyperglycemia after RYGB. (PDF 83 kb)Additional file 2:Figure S2. Changes in PC, Apo A1, Apo B and Apo A1 / Apo B molar ratio at 3, 6, 12 and 24 months after Roux-en-y gastric bypass (RYGB) surgery in patients without diabetes mellitus (DM), patients with DM in remission after RYGB and patients with DM and continued hyperglycemia after RYGB. (PDF 101 kb)Additional file 3:Table S1. Serum levels of PC, free choline and apolipoprotein A1 & B before and after Roux-en-y gastric bypass surgery. (PDF 77 kb)Additional file 4:Table S2. Differences in Apo A1 and Apo B concentrations between female and male patients before and after Roux-en-y gastric bypass. (PDF 54 kb)Additional file 5:Table S3. Lipid- and lipoprotein concentrations before and after Roux-en-y gastric bypass surgery for patients with and without diabetes, in treatment or in no treatment with statin. (PDF 75 kb)


Both gestational diabetes mellitus (GDM) as well as overweight/obesity during pregnancy are risk factors for detrimental anthropometric and hormonal neonatal outcomes, identified to ‘program’ adverse health predispositions later on. While overweight/obesity are major determinants of GDM, independent effects on critical birth outcomes remain unclear. Thus, the aim of the present study was to evaluate, in women with GDM, the relative/independent impact of overweight/obesity vs. altered glucose metabolism on newborn parameters.EaCH)’ cohort study primarily focuses on early developmental origins of unfavorable health outcomes through pre- and/or early postnatal exposure to a ‘diabetogenic/adipogenic’ environment. It includes 205 mother-child dyads, recruited between 2007 and 2010, from women with treated GDM and delivery at the Clinic of Obstetrics, Charité – Universitätsmedizin Berlin, Germany. Recruitment, therapy, metabolite/hormone analyses, and data evaluation were performed according to standardized guidelines and protocols. This report specifically aimed to identify maternal anthropometric and metabolic determinants of anthropometric and critical hormonal birth outcomes in ‘EaCH’.The prospective observational ‘Early CHARITÉ (P < 0.05). However, consideration of and adjustment for maternal glucose during late pregnancy showed that no maternal anthropometric parameter  remained significant . In contrast, even after adjustment for maternal anthropometrics, third trimester glucose values , were clearly positively associated with critical birth outcomes .Group comparisons, Spearman’s correlations and unadjusted linear regression analyses initially confirmed that increased maternal prepregnancy body-mass-index (BMI) is a significant factor for elevated birth weight, cord-blood insulin and leptin (all independent determinants of increased birth weight, insulin and leptin. Rather, 3rd trimester glycemia seems to be crucial for respective neonatal outcomes. Thus, gestational care and future research studies should greatly consider late pregnancy glucose in overweight/obese women with or without GDM, for evaluation of critical causes and interventional strategies against ‘perinatal programming of diabesity’ in the offspring.Neither overweight/obesity nor gestational weight gain appear to be  Gestational diabetes mellitus (GDM) and maternal overweight/obesity are the most prevalent disorders/diseases during gestation, affecting > 10 and > 30% of pregnant women in westernized countries, respectively . Both GDFortunately, regular GDM screening and optimized treatment has become widely distributed since the past few years due to rapid progress in the GDM field. Moreover, greater emphasis worldwide has been placed on optimal management of glucose levels after a positive GDM screening test, especially as the HAPO study and large randomized controlled trials have strongly shown beneficial influences of treating GDM for birth outcomes –18. HoweThe 3rd trimester plays a major role for fetal growth, differentiation and maturation, in particular for growth of insulin-sensitive tissues, e.g. fat tissue . TreatmeEaCH)’ cohort was created to explore unreflected/unknown factors associated with the pre- and neonatal development in offspring of mothers with diabetes/overweight during pregnancy, and to characterize potential mechanisms and pathophysiological factors from the clinical to the molecular level. We initially focused on characterization of relations of maternal anthropometry, especially body-mass-index (BMI) and gestational weight gain (GWG), and maternal glucose metabolism on critical anthropometric and cord-blood hormone outcomes at birth.In order to contribute to a clearer understanding of such important perinatal risk factors, the ‘Early CHARITÉ  and job description were recorded and used for socio-economic status (SES) categorization, as applied previously , 24. The2) was calculated. Maternal height and weight before conception, weight change in the 1st, 2nd and 3rd trimester as well as the last weight measured within one week prior to delivery were abstracted/calculated from the ‘Mutterpass’. This ‘Mutterpass’ is a standardized maternity record/documentation in Germany, containing essential information about pregravid health/conditions, regular screening/medical examinations throughout pregnancy as well as clinically important perinatal data [2, overweight: 25.0–29.9 kg/m2, obese: ≥30.0 kg/m2). Total gestational weight gain (GWG) was calculated as the difference between prepregnancy weight and nearest weight to delivery and categorized in line with the Institute of Medicine (IOM) guidelines from 2009 using the labels inadequate, adequate and excessive weight gain, respectively [Paternal height and weight was recorded via standardized questionnaire at enrollment and the BMI  were treated by diet and moderate physical activity only, while 37% (n = 76) received additional insulin therapy to achieve glycemic control. Insulin-sensitizing drugs (e.g. metformin) were not applied here. Overall, women were instructed to monitor blood glucose at least 4-times daily, i.e., morning FG and three 1-h PPG values, using the Accu-Chek glucose meter . From these individual profiles, mean FG  and mean PPG levels  were calculated from three days within the 32nd and 36th week of gestation, respectively. As marker for long-term glycemic status, glycated hemoglobin A1c (HbA1c) was assessed in the third trimester (mean ± SD: 33.2 ± 2.5 weeks’ gestation), and, additionally, at delivery by standardized high-performance liquid chromatography  at the clinic’s central laboratory. Based on recent guidelines from the American Diabetes Association [Gestational diabetes screening was conducted generally between the 24th–28th week of pregnancy (mean ± SD: 25.6 ± 3.8) using 75-g oral glucose tolerance test (oGTT) according to the guidelines of the German Society of Gynecology and Obstetrics at the time of recruitment . RespectA variety of maternal parameters, including parity, history of GDM, comorbidities , mode of delivery, gestational age at birth, were abstracted from the standardized ‘Mutterpass’ and medical records, respectively. Gestational hypertension and preeclampsia were diagnosed according to the guidelines of the German Society of Gynecology and Obstetrics . Mode of3 × 100), and macrosomia (defined as birth weight ≥ 4000 g). Furthermore, based on sex- and ethnic-specific birth weight for gestational age percentiles [Information about infant’s sex, preterm birth (< 37 weeks’ gestation), placental weight, birth weight, length and head circumference was abstracted from medical records. Placental weight was measured immediately after delivery with umbilical cord attached. Additional anthropometric outcomes included relative birth weight (g/cm), ponderal index , C-peptide and leptin  according to manufacturers’ instructions. The 90th percentile cut-offs in this study were the following: insulin 34.2 μU/mL, C-peptide 2.2 ng/mL, and leptin 29.6 ng/mL.r < 0.7) and variance inflation factor (< 2.5). The following parameters were tested as independent variables for their association with birth outcomes. Anthropometry: maternal prepregnancy weight and BMI, GWG in 1st, 2nd and 3rd trimester, total and net GWG; Metabolism: FG, 1-h and 2-h glucose, and area under the curve (AUC) of glucose at oGTT, mean FG and PPG at 32nd and 36th weeks’ gestation, HbA1c in 3rd trimester and at delivery. Birth outcomes were: placental weight, birth weight, relative birth weight, cord-blood insulin and leptin. All regressions are shown as crude and adjusted models. Model I included general parameters: maternal age, SES, ethnic origin, smoking in pregnancy, parity, height (except for pre-pregnancy BMI), type of therapy (diet vs. insulin), gestational age, mode of delivery, and infant’s sex. To evaluate independent associations of maternal anthropometry and metabolism with birth outcomes, further adjustment models were applied. For maternal anthropometry, model II contained all parameters of model I plus mean FG and PPG at 32nd and 36th weeks’ gestation and HbA1c partum. Accordingly, the applied model II for maternal metabolism included all parameters of model I plus prepregnancy weight and net GWG. In addition, forward step-wise regression analyses were carried out to identify categorical predictors of anthropometric/hormonal birth outcomes, considering paternal and maternal parameters (max. n = 118–153). In line with previous studies in this research area [2) were calculated for each individual  predictor entered into the final models. These coefficients estimate the contribution of each factor to the total variability of the outcome variable. Finally, owing to small numbers of unfavorable categorical anthropometric and cord-blood hormone outcomes logistic regression analyses  were just performed for LGA , using the same adjustment models as described above. Additionally, percentages of relevant maternal anthropometric and metabolic variables/exposures in newborns with unfavorable anthropometric and cord-blood hormone outcomes were compared with those in reference groups that had no respective outcomes. In general, missing data analysis according to Little’s MCAR test was performed and indicated random distribution. A P-value < 0.05 was considered significant (two-tailed). All calculations were performed using SPSS v. 24.0 .Descriptive statistics are presented as means ± standard deviations (SD) or numbers and percentages, respectively. All continuous variables were tested for normal distribution using Kolmogorov-Smirnov test and evaluation of distribution plots. Group comparisons were analyzed by one-way ANOVA followed by Tukey’s post hoc test or Kruskal-Wallis test followed by Dunn’s post hoc test and Fisher’s exact or Chi-square tests, respectively. Spearman’s correlation coefficients (r) and/or linear regression models  were calculated to assess relationships between paternal and/or maternal anthropometric/metabolic parameters and neonatal anthropometric and cord-blood hormone outcomes. For regression analyses, normal distribution was achieved for respective variables by transformation using the method described by Templeton . Furtherr = 0.23, P < 0.01).Major parameters across maternal prepregnancy BMI categories are presented in Table Maternal data showed no difference in age across prepregnancy BMI groups Table . Overallr = − 0.30, P < 0.001; net GWG: r = − 0.32, P < 0.001).The GDM cohort as a whole was overweight, in terms of mean BMI, before pregnancy. Around 40% were classified as normal weight and around 30% as obese. More than half of the women in the overweight/obese groups showed excessive GWG, according to IOM criteria, as compared to only around one-third in normal weight women. Furthermore, there was a continuous decrease in inadequate GWG across prepregnancy BMI groups. Total GWG was lowest in obese women, while normal weight and overweight mothers gained similar amounts of weight during gestation. However, the calculated net GWG, i.e., excluding placental and newborn weight, showed a decrease across all BMI categories Table . Both tor = 0.40, P < 0.001; FG at 36th weeks: r = 0.27, P < 0.001). Compared to normal weight women, insulin therapy was more abundant in the overweight and obese groups, respectively. Each glucose variable in 3rd trimester, i.e., mean glucose and HbA1c levels, increased significantly with maternal prepregnancy BMI, in contrast to oGTT variables at 24–28 weeks’ gestation  nor correlation analyses .Paternal BMI showed no relation to r = 0.36, P < 0.001) but clearly with 3rd trimester glucose variables . In contrast, the only relationship of net GWG was an inverse correlation with AUC glucose at oGTT .Bivariate associations between maternal anthropometry and glycemia revealed that prepregnancy BMI positively correlated only with FG among oGTT measurements . Glucose variables at oGTT were not related to birth outcomes, with the exception of a weak positive correlation between FG and placental weight. However, mean FG at 32nd weeks’ gestation and HbA1c levels in 3rd trimester and at delivery were significantly positively associated with all birth outcomes, including birth weight  and relative birth weight .Furthermore, prepregnancy BMI, but not net GWG, was significantly positively associated with birth outcomes, i.e., placental weight, relative birth weight, cord-blood insulin and leptin Table , Fig. 2.The influence of maternal anthropometry on birth outcomes was further investigated in detail by comprehensive regression analyses Table . There wIn order to identify potential metabolic determinants responsible for these observations, regression analyses with a variety of glucose variables were carried out Table . GlucoseForward step-wise regression analyses with key paternal and maternal general, anthropometric, and metabolic parameters in  relevant categories were then performed to identify major predictors for critical birth outcomes Table . Aside fP = 0.023). However, after adjustment for 3rd trimester glucose according to Model II variables (see above), neither pregravid BMI  nor total GWG  nor net GWG  were significantly related to LGA.Finally, logistic regression analysis was performed. Because of low numbers of adverse clinical endpoints, analysis was restricted to the outcome LGA. Indeed, crude, unadjusted evaluation revealed increased prepregnancy BMI as risk factor for LGA  and cord-blood outcomes (insulin and leptin > 90th percentiles), percentages of relevant anthropometric and metabolic variables/exposures, grouped according to clinical/guideline cut-offs, were compared to respective internal reference groups which did not show these adverse outcomes Fig. . FollowiMaternal overweight/obesity and GDM are associated with adverse short- and long-term outcomes in the offspring , 7, the Our observations are in line with data from other cohort studies showing that treatment of GDM, i.e., achieving good metabolic control, can significantly reduce the potential effects of maternal (prepregnancy) BMI status on adverse anthropometric perinatal outcomes –39. BeyoFurthermore, some studies reported that increased maternal GWG is an independent factor for adverse anthropometric outcomes in women with GDM –46. Agai, on both hormones. Here, however, not glucose at the time of oGTT but in later pregnancy appeared critically linked to adverse birth outcomes. Since both clinical as well as experimental studies demonstrated the particular importance of, especially, hyperinsulinism for long-term ‘diabesity programming’, this observation seems to deserve particular attention [In addition to neonatal anthropometry, our study also shows that maternal glycemia in 3rd trimester, but not maternal anthropometry per se, is independently related to critical cord-blood hormones shown to promote fetal ‘malprogramming’. While causal factors for adverse neonatal anthropometric outcomes are intensively studied, determinants of cord-blood insulin and leptin are less considered in clinical studies, although probably even more important mechanistically for the long-term development of metabolic disorders , 47–49. ttention , 20, 57.The HAPO study clearly showed a linear positive relationship between maternal glucose concentrations at oGTT screening, in particular FG, and critical birth outcomes, e.g. birth weight and cord-blood C-peptide > 90th percentiles, respectively . MoreoveAlthough our data might appear to challenge the impact of maternal overweight for adverse birth outcomes, this would not be correct. Of course, maternal overweight/obesity and increased gestational weight gain play an important detrimental role, just due to tight links with glucose metabolism (insulin sensitivity). As shown here, not all initial associations of adverse birth outcomes with maternal 3rd trimester glucose withstood adjustment to maternal anthropometry. Furthermore, applying step-wise regression analyses with common categorical parameters to our dataset, pregravid overweight/obesity and excessive GWG remained predictors for relative birth weight and showed higher percentages in LGA offspring as compared to the internal reference group. However, all of these effects were rather weak and could not be confirmed using continuous variable analyses. Compared to maternal anthropometric parameters, glucose in 3rd trimester was clearly better related to birth outcomes, in particular placental weight, macrosomia and cord-blood insulin as well as leptin, the latter mainly reflecting neonatal adiposity. Taken together, our data therefore indicates that the impact of (higher) maternal weight status and GWG on critical birth outcomes is ultimately to a major extent attributable to maternal glycemia in late pregnancy, but not at the time of oGTT, i.e., potentially even independent of a negative oGTT screening test. This might have far ranging implications for clinical care.Our study suggests, that especially maternal glucose at 32nd weeks’ gestation as well as HbA1c levels, integrative characterizing 3rd trimester glycemia, are positively related to fetal (over-) growth and (adverse) cord-blood hormone outcomes, respectively. HbA1c at delivery showed particular pronounced effects. This appears plausible, as in general the 3rd trimester is the period of major fetal growth, e.g. due to accelerated fat accumulation, and intrauterine differentiation and maturation . FurtherUnexpectedly, glucose values at oGTT were, with few exceptions, not significantly related to birth outcomes, which may be a consequence of GDM treatment. Even more surprising was the negative association between 1-h glucose at oGTT above the guideline cut-off (> 180 mg/dL) and birth weight/relative birth weight in step-wise regression analyses on categorical variables. While the majority of women in the total cohort exceeded this threshold, earlier and stricter treatment was applied to these women, possibly resulting in relatively lower birth weights. Moreover, relative frequencies of multiparous gestation, insulin therapy, preterm delivery and SGA outcome were non-significantly higher in women with glucose > 180 mg/dL at oGTT as compared to those below this cut-off. Possibly, all of this might cumulatively provide an explanation for this finding, which was not observed in the other analyses here.Also worthy to note, paternal anthropometry has been suggested to be directly related to fetal growth and birth weight . As no aLastly, like all observational studies also the present one had some limitations, which may have influenced the results. First, as only women with sufficient German/English language skills were included into the study, a selection bias could be present here, which appears unavoidable. Secondly, maternal self-reported weight before pregnancy was used for data evaluation. General concordance, however, has been shown for self-reported vs. measured maternal prepregnancy weight . FurtherOf note, in BMI group comparisons, the anthropometric outcomes birth weight, relative birth weight and LGA were similar in prepregnancy overweight and obese mothers and did not further increase in the latter, despite higher glycemia in 3rd trimester in the obese. Multiple reasons may explain these observations. For example, factors generally associated with fetal growth restriction and lower birth weight were (much) more abundant in the obese group, e.g. smoking, pregnancy-related hypertensive disorders, preterm delivery, and the mean gestational age at delivery was lower. As highlighted above, adjustment to such potential confounder variables is crucial for analyses and interpretation. Therefore, among a number of covariates, all general predictor variables, e.g. those identified in step-wise regression, were included in the adjustment models. Finally, since sex-specific differences were observed regarding determinants of the investigated fetal/birth outcomes , adjustmIn summary and conclusion, in a cohort of women with treated GDM maternal BMI and GWG were not associated with birth outcomes critical for ‘perinatal programming’ after consideration of maternal 3rd trimester glucose metabolism. While glucose at oGTT showed almost no relationships with endpoints, glucose metabolism in later pregnancy was strongly and independently associated with anthropometric and cord-blood hormone outcomes at birth. Thus, maternal overweight does not independently contribute to the detrimental birth outcomes addressed here, while it appears mandatory to strictly manage and scientifically consider, respectively, 3rd trimester glucose in gestational care and future research studies on the short- and long-term consequences of GDM and/or overweight/obesity during pregnancy.