Both short and long birth intervals are associated with many risk factors and about 29% of births are short birth intervals in Ethiopia. The purpose of this study is to model the birth intervals of adult women aged 15–49 years using accelerated failure time and shared frailty models in order to analyze the birth intervals of Ethiopian women.The data was obtained from the 2016 Ethiopian Demographic and Health Survey (EDHS). Accelerated failure time with different baseline and shared frailty models are used for the analysis to identify important demographic and socio-economic factors affecting the length of birth intervals and correlates of the birth intervals respectively.The data consists of 9147 women, of which about 7842 (85.5%) are closed interval and the rest of 1323(14.5%) are open interval. Accelerated failure time (AFT) result revealed that women education level, husbands education level, age at first birth, marital status, religion and family wealth index are significant factors affecting birth interval of women in Ethiopia.Women with closely spaced births tend to have larger family sizes when compared with women with longer inter-birth interval. Longer successive birth interval tends to reduce the total fertility rate of women. Furthermore, improvements in socio-economic status and level of education of women associate with reduced fertility, improved maternal and child wellbeing, and longer birth interval. High fertility is defined as a total fertility rate of 5.0 or higher. Total fertility rate represents the average lifetime births per woman implied by the age-specific fertility rates prevailing in one historical period . Birth oIn the societies where births are confined to marriage, reproduction starts from the onset of effective marriage, and the birth interval following effective marriage depends on the demographic characteristic of women at the earlier stages of married life . Ever siBirth interval refers to the time length between two successive live births and longer birth interval allow full gestation and growth of next pregnancy . Births A Latin American study revealed that short birth intervals adversely affect mothers’ health and chances of survival of their children. Shorter birth intervals (less than 24 months) increased maternal risks and it also led to several serious outcomes for neonates .In addition to many health implications, closely spaced birth intervals inflates population growth and challenges in many development efforts for a given country. It distracted women from becoming productive members of society. Moreover, the limited resources the family invests for caring to the new born will cause the other children to receive inadequate share of the resources. Differences in a country’s fertility levels can be attributed to the differences in the length of the reproductive life of women and differences in experiences of women that cause them to conceive conducted by .According to the 2007 population census of Ethiopia, the annual population growth rate within 1994–2007 was estimated to be 2.6%. Studying the effect of various socio-economic and demographic factors affecting birth interval is essential to formulate a policy that motivates people towards longer birth interval .Birth history analysis provides useful information about reproduction and family formation. Further, fertility depends not only on the decision of couples but also on socio-economic, demographic, health-related, tradition-related, and emotional factors. Fertility factors affect child spacing and birth intervals reveal reproduction patterns. Analysis of the childbearing process reveal about the dynamics of fertility transitions .Human fertility is a function of a variety of factors. The factors vary from place to place depending on specific conditions conducted by Lindstrom and Kiros  and YohaThe data for this study was extracted from the dataset of Ethiopian Demographic and Health Survey .The Ethiopian Demographic and Health Survey  which is part of worldwide DHS project and the fourth survey belonging to the Central Statistical Agency (CSA) collected from18 January 2016 to 27 June 2016. In this analysis, successive birth Interval which refers to the age gap between successive children for each mother measured in months was used as a dependent variable.Parametric shared and accelerated failure model and Kaplan Meier’s plot were applied to analyse the data. Kaplan–Meier was used to see the differences in birth interval and life table method was applied to include censored observation introduced by Kleinbaum and Klein . The accHere we can consider the log-scale of the AFT model with respect to time given analogous to the classical linear regression approach. In this approach, the natural logarithm of the survival time Y = log (T) is modeled. This is the natural transformation made in linear models to convert positive variables to observations on the entire real line. A linear model is assumed for Y;where Statistical models and methods proposed to model failure time data assume that the observations are statistically independent of each other. However, this does not hold in many applications. The concept of frailty provides a suitable way to introduce random effects in the model to account for association and unobserved heterogeneity.Estimation of the frailty model can be parametric or semi-parametric. In the former case, a parametric density is assumed for the event times, resulting in a parametric baseline hazard function. Estimation is then conducted by maximizing the marginal log-likelihood .The dependent variable for this study was whether or not birth had occurred during the interval. The case was coded 0 if the event (i.e. birth) did not occur and 1 if it happened. For all cases that were censored by the year of interview, the observations were coded 0 on the dependent variable.Descriptive analysis was conducted to get information about the distribution of the variables. The data consisted of 9147 women of which about 7842 (85.5%) were closed interval and the rest 1323(14.5%) were open interval. Summary of results of socio-economic and demographic variables of this study are presented in Table According to Table P value is 0.0213. The median survival time of time-to-birth interval for contraceptive users i.e., 38 months with , was greater than that of non-users (32 months) with 95% CI  and its P value is < 0.001. Women who have a job had a median survival time of 34 months with 95% CI  which was greater than that of jobless women (33 months) with 95% CI  based on P value is < 0.001. The median time of birth intervals for illiterate (who can’t read and write) women was 30 months with 95% CI  which is less than that of women having primary education (36 months) with 95% CI  and secondary school and above education (79 months) with 95% CI  and its P value is < 0.001. The overall mean and median survival time of birth intervals for Ethiopian women is 37 months with 95% CI  and 32 months with 95% CI , respectively.The median survival time of time-to-birth interval for rural women, is 33 months with 95% CI  is less than that of urban women, 34 months with its 95% CI  and its P < 0.001).The survival plot of time-to-birth interval by contraceptive use is given in Fig. The survival plot of time-to-birth interval of women by access to mass media is shown in Fig. For time-to-birth interval data, multivariable AFT models of Weibull, log-logistic, and log-normal distribution were fitted including all the covariates significant in the univariate analysis at 10% level of significance. To compare the efficiency of different models, Akaki information criteria (AIC) which is the most common applicable criterion to select model was used. Based on the AIC, the model having a minimum AIC value was selected. Accordingly, Log-logistic AFT model  was the best one of the time-to-birth interval data set of the given alternative among the covariates significant in the univariate analysis.Covariates insignificant in the multivariate analysis were removed from the model using backward elimination technique. Accordingly, Knowledge of ovulatory cycle, family’s access to mass media, contraceptive and employment status of women were excluded. The final model kept the covariate age of women at first birth, family wealth index, women’s marital status, religion and educational level of both spouses.As shown in Table P value was less than the level of significance which implies that husbands attending secondary school and above level of education and primary level of education had longer survival of time-to-birth interval.Using uneducated women, who cannot read and write, as reference, the acceleration factors for women attending primary education and secondary school and above level of education are estimated to be 1.002 and 1.11, respectively. This implies that women attending secondary school and above level of education had longer survival of time-to-birth interval, while for women attending primary level education, it was insignificant. Likewise, using uneducated husbands as reference, the acceleration factor for husbands attending primary education and secondary school and above level of education are estimated 1.5 and 2.8 with 95% CI  and  respectively and Using single marital status as reference, the acceleration factor for women whose marital status are married, divorced, widowed and separated are estimated to be 1.04, 1.1, 1.07 and 1.01 respectively. Moreover, using singles as reference, women whose marital status is married, divorced, widowed, and separated have longer survival of time to birth interval. The acceleration factors for families whose wealth index are middle and rich are 1.029 and 1.029 respectively. It also indicated that compared to families of poor wealth index, middle and rich wealth index families had longer survival of time to birth interval.To identify baseline distribution and associated risk factors and to analyze the survival of time to birth interval, three AFT models were fitted and compared. The log-Logistic AFT model was selected based on AIC value. The main focus of this study was to investigate risk factors associated with the survival of time to birth interval using parametric shared frailty models. For the data on time-to-birth interval, the three parametric baseline distributions with Gamma frailty and inverse Gaussian distribution were fitted by using regional states of the women as frailty term. The effect of random component (frailty) was significant for both log-normal-gamma shared frailties, log-logistic gamma shared frailty models, and Weibull-gamma shared frailty model. The AIC value for all parametric frailty models is summarized and the given log-logistic gamma shared frailty model had smaller AIC value . This indicates that log-logistic gamma shared frailty model is a more suited and efficient model to describe time to birth interval dataset.P value of < 0.001. This indicates that the frailty component had significant contribution to the model but the associated Kendall’s tau . The estimated value of theta .From Table P value for all age categories was less than the level of significant (α = 0.05). As compared to women whose age group was less than or equal to 15, all the categories of age of women at first birth 16–20, 21–25, and ≥ 26 respectively have shorter birth interval. Additionally, the confidence interval did not include one indicating that the age of women at first birth was statistically significant for the survival of time-to-birth interval. Using orthodox religion of women as reference, the acceleration factors for Muslim women were 1.02, 1.012 and 1.07. This indicates that Muslim women and other follower had longer survival of time-to birth interval than women who follow orthodox religion, respectively.The age of women at first birth was statistically significant in determining the time-to-birth interval of Ethiopian women. The acceleration factor for all categories of age at first birth was 1.05, 1.20 and 1.37, with 95% confidence interval ,  and ) respectively, yielding a significant Using uneducated women as reference, the acceleration factors for women attending primary level of education and secondary school and above level of education are estimated to be 1.002 and 1.114 respectively. This implies that women have secondary school and above level of education have longer survival of time-to-birth interval. Among women in their primary level of education however, the interval was not significant. Taking uneducated husbands as reference, the acceleration factors for husbands attending primary level of education and secondary school and above level of education are estimated to be 1.48 and 2.77 respectively. This implies that husbands attending secondary school and above level of education and primary level of education have longer survival of time-to-birth interval. Taking single marital status as reference, the acceleration factor for the marital status of women such as married, divorced, widowed and separated are estimated to be 1.04, 1.10, 1.074 and 1.12, respectively. This indicates that compared to the single women, women who were married, divorced, widowed and separated have longer survival of time-to-birth interval. The acceleration factor of families belonging to middle and rich wealth index were 1.03 and 1.04, respectively which imply that families who have middle and rich wealth index have longer survival of time to birth interval.From Table The main goal of the study was to model the determinants of time-to-birth interval of women in Ethiopia and to know the trend of the two data set using AFT and parametric shared frailty models based on three baseline distributions. The aim of frailty model is not only to account heterogeneity subjects among different regions but also to measure the dependence or correlation within the same region. Gamma distribution is selected for the frailty term due to its mathematical tractability and its flexibility in case of hazard function , 25 and This finding indicates that the husband’s education level is important covariate for determining birth interval of women. The result showed that compared to uneducated husbands, husbands whose level of education is primary or secondary school have women who have a longer birth interval. Compared with husbands who are uneducated, husbands who have primary and secondary school level of education decelerate the survival of birth interval 1.48 and 2.78 times respectively. This finding is consistent with the results of the study conducted by Hidayat et al.  in IndonAnother important factor affecting the survival of birth interval is the educational level of women. This finding shows that women who have secondary school and above level of education have a longer survival of birth interval than uneducated women. Consequently, they decelerate the survival of birth interval 1.11 times that of the uneducated. This finding is similar with results of studies by .Religion is a covariate affecting the survival of time to birth interval of women. Muslim and other religion follower women have longer survival of time to birth interval than women orthodox in their religion. Muslim women decelerate the survival of time to birth interval 1.02 times that of women who are orthodox followers in their religion. On the other hand, women who are follower of other religions decelerate the survival time to birth interval 1.09 times that of women whose religion is orthodox. This finding is consistent with studies conducted in Ethiopia by , 18. AgeAnother important factor affecting the survival of birth interval of women is marital status of women. This finding showed that women whose marital status was married, divorced, widowed, and separated had longer survival of birth interval than single women. The acceleration factor for women that decelerate the survival of birth interval of women who are married, divorced, widowed and separated in their marital status are respectively 1.04, 1.07,1.05 and 1.09 times that of women’s whose marital status are single which is confirmed with the finding of . Wealth This study aimed at modeling the determinant of time-to-birth interval among women who have at least one child in Ethiopia drawing on two datasets of central statistics agency and using parametric AFT model. Keeping other factors constant, women who have longer birth interval tend to have smaller family size when compared with women who have shorter inter-birth intervals. Differences in exposure to the risk of pregnancy and in the length of time between births when women are exposed to child bearing causes differences in fertility levels between different populations or between groups within the same populations. Helping women achieve healthy pregnancy and safe birth is one of the priorities of every country’s family planning program.This study attempted to investigate determinants of successive birth interval in Ethiopia. The findings indicate that age of women at first birth, educational level of women and husbands, religion, marital status, and family wealth index significantly affect length of birth interval of Ethiopian women. Modernization that induces cultural changes and new sexual and reproductive orientations in the youth led to emergent patterns of marriage and fertility that subsequently affect the length of successive birth interval.Longer successive birth interval is likely to reduce the total fertility rate of a woman. Hence, given the prevalence of low level of education among women, improving the socio-economic status of women adjust their fertility and improves maternal and child wellbeing through well-spaced birth interval.


There is a knowledge gap on abnormal birth weight in urban Nigeria where specific community contexts can have a significant impact on a child’s health. Abnormal birth weight, classified into low birth weight and high birth weight, is often associated with adverse health outcomes and a leading risk for neonatal morbidity and mortality. The study used datasets from the birth recode file of 2013 and 2018 Nigeria Demographic and Health Survey (NDHS); a weighted sample of pooled 9,244 live births by 7,951 mothers within ten years (2008–2018) in urban Nigeria. The effects of individual, healthcare utilization and community-level variables on the two abnormal birth weight categories were explored with a multinomial logistic regression models using normal birth weight as a reference group. In urban Nigeria, the overall prevalence of ABW was 18.3%; high birth weight accounted for the majority (10.7%) of infants who were outside the normal birth weight range. Predictors of LBW were community (region), child characteristic (the type of birth) and household  while that of HBW were community (regions), child characteristics , maternal characteristic (education) and healthcare utilization (ANC registration). LBW was significantly more prevalent in the northern part while HBW was more common in the southern part of urban Nigeria. This pattern conforms to the expected north-south dichotomy in health indicators and outcomes. These differences can be linked to suggested variation in regional exposure to urbanization in Nigeria. Urbanization has been linked to improved child health outcomes because of the assumed advantage in access to improved health care services, higher education and its associated benefits and good infrastructure . HoweverBirth weight is a strong predictor of child’s health and development –13 A lowAlthough there is evidence of increasing birth weight in some developing countries , ABW is Even in Nigeria, the largest African population with rapid urbanization and most complex urban system , 10, fewThis study, therefore, examines abnormal birth weight categories-LBW and HBW- in urban settings in Nigeria. The main questions guiding the study include: what is the prevalence of ABW (LBW and HBW) in urban Nigeria? What are the odds of ABW in urban Nigeria at the community and individual levels? These questions will be answered by exploring community and individual contexts of abnormal birth weight (ABW) in urban Nigeria using a nationally representative NDHS 2013 and 2018 dataset which covers records of livebirths from 2008 to 2018.The study used datasets from the birth recode files of 2013 and 2018 Nigeria Demographic and Health Survey (NDHS). The two NDHS data sets are the fifth and sixth in the series of nationally representative surveys that collect information on basic demographic and health indicators in Nigeria. Detailed survey methodology, including sample design and data collection procedure, was published in the NDHS Reports for the survey years , 49. TheThe birth recode file contains birth-related information of live births obtained from eligible women age 15 to 49 years in the 36 states and the Federal Capital Territory. The analytical sample for this study was based on (i) live births in the last five years preceding the survey (ii) availability of numerical values for the birth weight from written record or mothers report (iii) urban residence. There were 3818 and 5604 live births in the five years preceding the survey with reported numerical values for weight at delivery in the urban areas of Nigeria for NDHS 2013 and 2018 respectively. This gives a weighted sample of pooled 9,244 livebirths by 7,951 mothers within ten years (2008–2018) in urban Nigeria.Birth weight, measured in grams, is the outcome variable in this study. Information on birth weight was obtained from written records or mothers report. The continuous variable was categorized into low birth weight (LBW = less than 2500), normal birth weight (NBW = 2500g-4000g) and high birth weight (HBW = above 4000g). Further classification combined LBW and HBW to estimate the abnormal birthweight (<2500g and >4000g).2); normal weight (18.5–24.9 kg/m2), overweight and obese (25.0 kg/m2 and above), (vi) Maternal age at delivery was computed as the difference between mother and baby’s date of birth and grouped into below 20 years, 20-34years and 35-49years; (vii) Maternal education was classified into no formal education, primary education and secondary/higher education; (viii) Wealth index was regrouped into poor, middle and rich.The exposure variables were grouped into individual, healthcare utilization and community levels. The community variable, region, was based on geopolitical delineations in the country and categorized into North Central, North East, North West, South East, South South and South West. Individual-level variables consist of infant, and maternal characteristics were birth order, sex of the child, preceding birth interval, maternal age at delivery, maternal education. (i) Type of birth was classified into singleton and multiple; (ii) Preceding birth interval grouped into less than 24 months and 24 months and above; (iii) Sex of child as male and female; (iv) Birth order was grouped into two: 1–3 and 4+; (v) Maternal Body Mass Index was classified into underweight  Prenatal care by a skilled provider was defined as births whose mothers received antenatal care from a skilled healthcare provider. Skilled healthcare workers (SHW) in NDHS are doctor, nurse/midwife and auxiliary nurse/midwife. This was grouped into yes or no.Healthcare utilization was examined because of the assumed proximity of health care facilities to urban residents, which predispose them to access proper care during pregnancy and its associated outcome. Antenatal care utilization was measured in terms of early ANC registration, more than 4 ANC visits and prenatal care by a skilled healthcare worker. This was assessed as (i) ANC visit, defined as the number of ANC visits by the mother of the index birth, categorized into two—below 4 visits, and 4 visits or more; (ii) ANC registration, defined as the month of first ANC registration by mothers of the index birth, grouped into the first trimester and after 1The statistical analysis was at bivariable and multivariable levels. At the bivariable level, cross-tabulation and Chi-Square test of association between birth weight and selected factors at the individual, healthcare and community levels was examined. This showed the percentages of NBW, LBW and HBW in urban Nigeria between 2008 and 2018. Also, the yearly distribution of NBW, LBW and HBW was presented to show the pattern over the ten years covered by NDHS 2013 and 2018.The effects of individual, healthcare utilization and community-level variables on the two abnormal birth weight categories were explored with a multinomial logistic regression model using normal birth weight as a reference group. This is to predict the odds of low and high weights in urban Nigeria. Model 1 has community-level variable (region) to show the odds of low and high birth weights in urban Nigeria. Model 2 included individual-level characteristics of the child and mother  and health care utilization variables. The risk of low and high birth weights in urban Nigeria was presented as odds ratio with a 95% confidence interval.Ethical clearance to conduct Nigeria Demographic and Health Surveys was obtained from National Health Research Ethics Committee of Nigeria (NHREC) and the ICF Institutional Review Board., United States. NDHS data are public access data and permission were granted to download the dataset for this study by Demographic and Health Survey Program of ICF Macro.The percentage distribution of birth weights by background characteristics is presented in For the LBW Models, model 1 shows that community-level variable  was significantly associated with LBW in urban Nigeria. The odds of LBW among infants in the North West , North East , North Central  and South South  were significantly higher than the South West. South East has the lowest odds of LBW in Model 1 , which was not significantly lower than South West. The inclusion of individual and healthcare utilization variables in Model 2 removed the significance of geopolitical region on LBW except North West which increased significantly by 64%. All the included variables for LBW in Model 2 were not significant except for singleton type of birth , birth order of 1–3  and maternal body mass index for overweight/obese . Multiple births had 81% higher risk of LBW than singleton births. Higher birth order of more than 3 has a higher risk of LBW than lower birth order.For the HBW models, model 1 shows that odds of HBW were significantly lower in North West  and North East  than South West. The odds of having infants with HBW were substantially higher in South South  and South East  than other regions. The regional pattern of HBW changed in model 2 as North West  remained the only region that was significantly different from the South West. Infants in the South West were about five times more likely to be HBW than the North West. Mothers in the South East  and South South  reported the highest odds of HBW. Maternal BMI, sex of the child, maternal education and ANC registration were significant predictors of HBW in urban Nigeria. Overweight/obese mothers were 1.6 times more likely to have HBW than mothers with normal weight . Male infants were at higher odds of HBW . Women with primary education had the lowest odds  of having macrosomia infants than other education categories. Also, delayed onset of ANC  increased the risk of HBW by 24%.This is the first study that examined abnormal birth weights in urban Nigeria using NDHS pool dataset. The findings show that the prevalence of ABW in urban Nigeria was 18.3 percent, which implies that at least one out of six livebirths in urban Nigeria for the study period was either low weight at birth infant or macrosomia infant. High birth weight accounted for the majority of infants who are outside the normal birth weight range values of 2,500g to 4,000g in urban Nigeria. This is a high prevalence of HBW (10.7 percent) than LBW (7.5 percent) in urban Nigeria. Community, maternal and child characteristics as well as healthcare utilization are significantly associated with both categories of abnormal birth weight- LBW and HBW- in urban Nigeria.This pattern of a higher proportion of HBW among abnormal birth weights is in contrast to findings in similar African countries- Ghana and Ethiopia –30 whereThe literature suggests that common factors that affect LBW and HBW are maternal and child characteristics, healthcare utilization and community variables , 47, 51.Although this result is based on data from urban areas of Nigeria, a study  that useThe regional differences in the reported pattern of ABW in urban areas conform to the expected north-south dichotomy in health indicators and outcomes in Nigeria , 49. TheOn the other hand, the southern regions have rapidly adapted urban advantage of education and urban lifestyle, with its adverse consequence. As suggested by another study , one of Moreover, the regional dichotomy in LBW and HBW is supported by the estimates on nutritional status of women of reproductive age which showed the variation in the burden of undernutrition and over nutrition in northern and southern Nigeria. The recent 2019 Nigeria Demographic and Health Survey  reportedMaternal BMI, an anthropometric measure of maternal nutrition, can affect the growth and development of the fetus. An underweight mother is likely to be malnourished in some important nutritional components during pregnancy and can lead to LBW while overweight mothers have macrosomia babies. Some previous studies , 19 suppFurthermore, studies , 33 haveThis study has some limitations. Maternal BMI is used as a proxy for the maternal anthropometric parameter at birth because the information collected during the NDHS may not be completely applicable at the birth of the index child, which may be within five years preceding the survey. While maternal weight and nutrition have been found as a significant risk factor to birth weight, other factors such as maternal education and household wealth index considered in this study are likely to predict maternal nutritional status and anthropometric measures in pregnancy. Another limitation of the study is the non-distinction of full-term or preterm birth in the NDHS dataset since preterm babies are known to have lower birth weight, and general low reporting of birth weight in Nigeria with estimates of 16 percent and 24 percent reported birth weight in NDHS 2013 and 2018 respectively. The study also recognized the limitation of non-inclusion of other factors like maternal infections that can contribute to preterm birth and LBW, which were not captured in the Nigerian Demographic and Health Survey.Nigeria is a pronatalist society and it is important to note that abnormal birth weight is high in urban Nigeria. This study also provides empirical evidence on the prevalence of macrosomia from analysis of a nationally representative survey data that covers ten years in urban Nigeria. While previous focus had been more on the reduction of LBW, the findings from this study provide a basis to incorporate measures that can reduce HBW as well as improve child health outcome in the context of rapid urbanization. Interventions on ABW in urban Nigeria should be designed around community and socioeconomic indicators. Future studies can explore the rural-urban differentials in high birth weight in Nigeria. 29 Oct 2020PONE-D-20-16572Abnormal birth weight in urban Nigeria: an examination of related factorsPLOS ONEDear Dr. Fayehun,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. 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Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The authors have used national datasets to explore an important issue of abnormal birthweight – considering not only small babies but also large babies in the context of urbanization. The findings show a higher proportion of macrosomia in urban Nigeria, which does not get as much attention as LBW in sub-Saharan Africa.Methods• Clarity in your methods that you modeled odds of LBW and HBW separately and not ABW pooled, which is how it reads.Results• In the results  you do not need to repeat your methods and just present the results.• Results on Table 1: remove references to more LBW and more HBW among those who did not receive ANC from skilled providers – your results show there was no significant difference in birth weight based on this variable.• The results text could be abbreviated to the main points. Paragraphs 1-4 referring to table 1 would be better as one paragraph and summarized to the main highlights.• Results paragraph 6: The inclusion of individual and health care utilization didn’t decrease the odds of regional variation but the odds ratios were no longer significant when accounting for individual and healthcare variables, except in the North West and North East. Be careful with the language since “X decreases Y” implies a causal relationship. Your description in Paragraph 7 for HBW is much better.• Results should include the numerical results, you sometimes present them and sometimes do not. Please be succinct and present the main findings and numerical results together . But also check the results, it appears the 95% CI for LBW Model 2 type of birth has a typo. Paragraph 7 reporting HBW models should also be revised to follow this approach.Discussion• The discussion could use some better organization. It was a bit hard to follow the main points you were trying to make. Maybe start the first paragraph of the discussion to highlight your main findings and then unpack each main finding in one paragraph.• For your first finding… It seemed to me that you are mainly saying: HBW were a bigger concern than LBW in urban Nigeria. You are right in saying we focus much more on LBW in sub-Saharan Africa but with urbanization we need to also be focusing on the issue of overnutrition and the negative implications for newborns. It would be helpful to have some data to support this on the burden of overnutrition in Nigeria to help support this claim for readers who are not so familiar with the data in urban Nigeria.• Please also make sure each time you refer to studies , that you always put the reference.• There are other factors that can contribute to preterm birth and LBW that are importantly missing from your study (because they are not part of DHS datasets), like maternal infections.• Shorter birth intervals are often associated with preterm (and thus often LBW) births but your study didn’t find that. Any thoughts why?• In the paragraph on the region, you talk about the north having lower health statistics in general but many that you are talking about, such as stunting are also directly related to one of your outcomes of LBW. What factors, perhaps not measured in your study, may be accounting for these types of poor health outcomes in the North – instability? Food insecurity?• You mention in the limitations that you don’t have data on preterm births. That is fine, but Nigeria has a relatively high rate of preterm birth which may be why you are seeing factors we would expect to have an association with LBW – such as maternal undernutrition – not being significant in your study if Nigeria’s low weight births are driven by prematurity rather than intrauterine growth restriction.• Limitations – should also likely include quality of the birthweight data. In your intro you mention birthweight is often not taken and so you are relying on maternal report of birthweight or review of records when available and so if birthweight is not taken, then mothers may not have had much information to refer to when reporting.Minor typographical issues to correct. There is no need to respond to these in your response to reviewers, but I am just noting them as small observations I had as I read the paper.• Consistent use of commas (or not) for reporting values in the thousands in text and tables• Consistent use of decimal when reporting results • When reporting the statistic for significance, please include the “p” rather than just stating the value ;• Table 1 – the “chi” symbol is not showing up in the table note• Use “*” to present p<0.05 in Table 1 the same way you do in Table 2 for ease to the reader• Make sure there is a space between the numbers and the word “Percent”Reviewer #2: The authors must be congratulated on an excellent piece of work. The study is well designed and conducted. The methodology is comprehensive, the results clearly presented, the discussion is relevant and the conclusions and limitations appropriate. The manuscript is very well written and adheres to both scientific and language norms.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool, AttachmentReviewer comments ABW in Nigeria.docxSubmitted filename: Click here for additional data file. 7 Nov 2020Response to Reviewers' commentMethods• Clarity in your methods that you modeled odds of LBW and HBW separately and not ABW pooled, which is how it reads. Response: Done. Page 7Results• In the results  you do not need to repeat your methods and just present the results.Response: Done. We deleted the repetition• Results on Table 1: remove references to more LBW and more HBW among those who did not receive ANC from skilled providers – your results show there was no significant difference in birth weight based on this variable.Response: Done. We removed the statement.• The results text could be abbreviated to the main points. Paragraphs 1-4 referring to table 1 would be better as one paragraph and summarized to the main highlights. Response: Done. Thank you. We summarized the main highlight to one paragraph as suggested.• Results paragraph 6: The inclusion of individual and health care utilization didn’t decrease the odds of regional variation but the odds ratios were no longer significant when accounting for individual and healthcare variables, except in the North West and North East. Be careful with the language since “X decreases Y” implies a causal relationship. Your description in Paragraph 7 for HBW is much better.Response: Done. We rephrased the sentence. Thank you.• Results should include the numerical results, you sometimes present them and sometimes do not. Please be succinct and present the main findings and numerical results together . But also check the results, it appears the 95% CI for LBW Model 2 type of birth has a typo. Paragraph 7 reporting HBW models should also be revised to follow this approach. Response: Done. We corrected the singleton birth estimate typo. Estimates included in the paragraphs. Thank youDiscussion• The discussion could use some better organization. It was a bit hard to follow the main points you were trying to make. Maybe start the first paragraph of the discussion to highlight your main findings and then unpack each main finding in one paragraph. Response: Done. We revised this section. We highlighted the main findings in the first paragraph and discussed the significance of these findings in the subsequent paragraphs • For your first finding… It seemed to me that you are mainly saying: HBW were a bigger concern than LBW in urban Nigeria. You are right in saying we focus much more on LBW in sub-Saharan Africa but with urbanization we need to also be focusing on the issue of overnutrition and the negative implications for newborns. It would be helpful to have some data to support this on the burden of overnutrition in Nigeria to help support this claim for readers who are not so familiar with the data in urban Nigeria. Response: Done. We included some data to show the burden of over nutrition and undernutrition in southern and northern part of Nigeria respectively.• Please also make sure each time you refer to studies , that you always put the reference. Response: Done. Reference inserted• There are other factors that can contribute to preterm birth and LBW that are importantly missing from your study (because they are not part of DHS datasets), like maternal infections. Response: Done. We included this as part of the study limitation• Shorter birth intervals are often associated with preterm (and thus often LBW) births but your study didn’t find that. Any thoughts why?Response: This may be due to the quality of data set we have. As noted in the limitation, there is a general low reporting of birth weights in Nigeria.• In the paragraph on the region, you talk about the north having lower health statistics in general but many that you are talking about, such as stunting are also directly related to one of your outcomes of LBW. What factors, perhaps not measured in your study, may be accounting for these types of poor health outcomes in the North – instability? Food insecurity? Response: As noted in the discussion, there is variations in the adoption of western education, urbanization rates and pace over time because of broad tendencies and the geographical difference in the dynamics of the various cultural, social and economic factors. • You mention in the limitations that you don’t have data on preterm births. That is fine, but Nigeria has a relatively high rate of preterm birth which may be why you are seeing factors we would expect to have an association with LBW – such as maternal undernutrition – not being significant in your study if Nigeria’s low weight births are driven by prematurity rather than intrauterine growth restriction. Responses: Noted. Because of lack of data, we cannot specifically say this is the situation among the study population of urban residents in Nigeria.• Limitations – should also likely include quality of the birthweight data. In your intro you mention birthweight is often not taken and so you are relying on maternal report of birthweight or review of records when available and so if birthweight is not taken, then mothers may not have had much information to refer to when reporting. Responses: Done. We have included limitations about the quality of birthweight dataMinor typographical issues to correct. There is no need to respond to these in your response to reviewers, but I am just noting them as small observations I had as I read the paper. • Consistent use of commas (or not) for reporting values in the thousands in text and tables• Consistent use of decimal when reporting results Response: Corrected in the result section• When reporting the statistic for significance, please include the “p” rather than just stating the value ; Response: Corrected in the result section• Table 1 – the “chi” symbol is not showing up in the table note• Use “*” to present p<0.05 in Table 1 the same way you do in Table 2 for ease to the readerResponse: Corrected in Table 1• Make sure there is a space between the numbers and the word “Percent”Response: Corrected.AttachmentResponse to reviewer comments on ABW in Nigeria.docxSubmitted filename: Click here for additional data file. 10 Nov 2020Abnormal birth weight in urban Nigeria: an examination of related factorsPONE-D-20-16572R1Dear Dr. Fayehun,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Tanya Doherty, PhDAcademic EditorPLOS ONEAdditional Editor Comments :Thank you for addressing the reviewer comments. Your paper is now deemed suitable for publication.Reviewers' comments: 12 Nov 2020PONE-D-20-16572R1 Abnormal birth weight in urban Nigeria: an examination of related factors Dear Dr. Fayehun:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. 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A recent Genome-wide association meta-analysis (GWAS) of refractive error reported shared genetics with anthropometric traits such as height, BMI and obesity. To explore a potential relationship with refractive error and ocular structure we performed a life-course analysis including both maternal and child characteristics using data from the Avon Longitudinal Study of Parents and Children cohort.Measures collected across the life-course were analysed to explore the association of height, weight, and BMI with refractive error and ocular biometric measures at age 15 years from 1613children. The outcome measures were the mean spherical equivalent (MSE) of refractive error (dioptres), axial length , and radius of corneal curvature . Potential confounding variables; maternal age at conception, maternal education level, parental socio-economic status, gestational age, breast-feeding, and gender were adjusted for within each multi-variable model.Maternal height was positively associated with teenage AXL  and RCC , increased maternal weight was positively associated with AXL . Birth length was associated with an increase in teenage AXL  and flatter RCC  and increasing birth weight was associated with flatter RCC . An increase in teenage height was associated with a lower MSE , an increase in AXL  and flatter RCC . Weight at 15 years was associated with an increase in AXL .At each life stage  height and weight, but not BMI, demonstrate an association with AXL and RCC measured at age 15 years. However, the negative association between refractive error and an increase in height was only present at the teenage life stage. Further research into the growth pattern of ocular structures and the development of refractive error over the life-course is required, particularly at the time of puberty. The influence of prenatal factors in the development of conditions such as heart disease, diabetes, and obesity is well reported, with maternal health and the prenatal environment known to influence development throughout the life-course . Early lALSPAC is a birth cohort of mothers and their children born between 1991 and 1992 residing in the county of Avon, South West England. A variety of measures have been collected prospectively from the participants, with the methodology of collection of ALSPAC measures detailed previously elsewhere .https://www.bristol.ac.uk/alspac/researchers/our-data/).The ALSPAC study website contains details of all the data that is available through a fully searchable data dictionary and variable search tool. (n = 825) and covariable (n = 117) data; the final cohort for this study is 1613  of refractive error (dioptres), axial length , and radius of corneal curvature . All outcome measures were collected from the participants at age 15 years. Non-cycloplegic autorefraction was used to estimate the refractive error . This was measured in both eyes and then used to calculate the MSE . AXL and RCC were measured using Zeiss IOL master . The mean measure of both eyes for each outcome measure was used in the analyses, coded as continuous variables.We examined variables previously identified as potentially being associated with myopia: height , 8, weigPotential confounding variables previously reported to be associated with myopia throughout the life course were adjusted for within each life stage model: Maternal age at conception (years) , maternap < 0.20) were included in the multivariable linear regression models. In each multi-variable model interactions between gender and height and gender and weight were included, retaining those that were significant in the final models.All statistical analyses were performed using Stata (v 15). Initially, univariable linear regression was performed to examine the relationship between each exposure variable and each covariable (listed above) with each of the three outcome measures  at each life stage; those with the strongest associations , maternal height (cm), pre-natal weight (kg), maternal education level, and parental socio-economic status.No prenatal association was found between maternal height or weight with MSE. Maternal height was positively associated with a longer teenage AXL  and greater RCC , increased maternal weight was also associated with an increase in AXL  Table .The multivariable model of the birth life stage included gestational age (weeks), birth weight (g), and length at birth (cm). No association was found between birth length or weight with MSE. Birth length was associated with an increase in teenage AXL  and flatter RCC  respectively. An increase in birth weight was also associated with flatter RCC .Factors included in the teenage life stage model included weight (kg) and height (cm) at 15 years of age. An increase in teenage height was associated with a reduction in MSE , an increase in AXL  and flatter RCC . Weight at 15 years was also associated with an increase in AXL .The anthropometric measures of height and weight, but not BMI, across the life-course demonstrate an association with the optical biometric measures of AXL and RCC measured at age 15 years. However the negative association between refractive error (MSE) and an increase in height was only found to be associated at the teenage life stage (age 15 years) and no other life stage.BMI is commonly used as a measure of obesity in adults however in children and adolescents there is no agreed definition of BMI relating to health outcomes, this is due to greater variation in body fat content in comparison to adults , 13. HeiThe association we report of increasing maternal height with increasing offspring AXL and RCC is comparable to previous reporting of a relationship between height and ocular dimensions , we addiThe lack of association of MSE in the prenatal and birth models we report is similar to findings in a study of Singapore Chinese children who demonstrated an association between AXL and birth length and weight but not refractive error at age 7–9 years . RefractPrevious studies reporting the relationship between refractive error, height and weight have reported varying results, with Rosner et al. finding no association between myopia and stature in conscripted male teenagers  and RahiA study of the allelic score from 180 SNPs associated with adult height has been undertaken for this ALSPAC cohort with children having an above average increase in the height allelic score having a flatter corneal curvature . A GWAS Dopamine has been suggested as a possible hormonal mechanism influencing the development of myopia with lower levels of dopamine and increased axial length reported in low light levels . There aOur data indicates an association between anthropomorphic measures, ocular biometry and refractive error and supports the theory that refractive error results from a complex interaction of genetic and environmental factors , adding Our findings are consistent with a small number of studies reporting association between anthropomorphic measures and ocular parameters , 5, 17 a


Birth weight influences not only brain development, but also mental health outcomes, including depression, but the underlying mechanism is unclear.The phenotypic data of 12,872–91,009 participants (59.18–63.38% women) from UK Biobank were included to test the associations between the birth weight, depression, and brain volumes through the linear and logistic regression models. As birth weight is highly heritable, the polygenic risk scores (PRSs) of birth weight were calculated from the UK Biobank cohort  to estimate the effect of birth weight-related genetic variation on the development of depression and brain volumes. Finally, the mediation analyses of step approach and mediation analysis were used to estimate the role of brain volumes in the association between birth weight and depression. All analyses were conducted sex stratified to assess sex-specific role in the associations.p = 2.29 × 10−6). Positive associations were observed between birth weight and brain volumes, such as gray matter  and white matter . Depression was also associated with brain volume, such as left thalamus  and right thalamus . Additionally, significant mediation effects of brain volume were found for the associations between birth weight and depression through steps approach and mediation analysis, such as gray matter  and right thalamus .We observed associations between birth weight and depression (odds ratio [OR] = 0.968, 95% confidence interval [CI] = 0.957–0.979, Our results showed the associations among birth weight, depression, and brain volumes, and the mediation effect of brain volumes also provide evidence for the sex-specific of associations. Barker’s hypothesis suggested that early in development, especially during life in the intrauterine life, adverse effects can lead to permanent changes in physiology and metabolism, resulting in an increased risk of disease in adulthood . Birth wPrevious studies also observed relationship between birth weight and depression. Warrington et al. conducted a study about maternal and fetal genetic effects on birth weight, and demonstrated genetic correlation between birth weight and mental disorder through linkage disequilibrium (LD) score regression, such as major depressive disorder and bipolar disorder (BD) . HoweverGenetic factors contribute greatly to the variations of birth weight, brain volume and depression. Resent genome-wide association studies (GWAS) meta-analyses of own birth weight identified 146 independent single-nucleotide polymorphisms (SNPs) at genome-wide significance . Twin anPolygenic risk score (PRS) analysis is a powerful approach that aggregates the effects of genetic variants from GWAS summary data to identify the relationship between traits and diseases. From the Suffolk County Mental Project, an inception cohort study of first-admission patients with psychosis, Jonas et al. indicated that schizophrenia (SZ) PRS was the strongest predictors of diagnostic shifts from affective to nonaffective psychosis and could predict whether patients who appear to have a mood disorder with psychotic at first admission will eventually be diagnosed with a SZ spectrum disorder . AnotherUtilizing the UK Biobank cohort, we first tested the associations between birth weight, depression, and brain volumes. The PRSs of birth weight were then calculated from the individual-level genotype data of UK Biobank cohort. Linear and logistic regression models were then performed to evaluate the genetic impact of birth weight on depression and brain volume. Finally, the mediation model was used to estimate the role of brain volume in the association between birth weight and depression. All analyses were conducted sex stratified to assess sex-specific role in the associations.This study attempted to explore: (a) associations between birth weight on brain volumes; (b) associations between brain volumes on depression; and (c) associations between birth weight on depression, and whether brain volumes plays a mediating role in it.Study individuals were from the UK Biobank health resource, which has performed a large prospective population-based cohort study, comprising linked health, hospital-record and genetic data of 502,656 participants aged 40–69 years in 2006 and 2010. All participants agreed to use their anonymous data and samples for any health-related research, to reconnect for further substudies . The preParticipants were asked to enter their own birth-weight through verbal interview with 277,000 participants completed (UK Biobank field ID: 20022). In order to obtain a comprehensive and accurate control group of depressed and nondepressed patients, Patient Health Questionnaire (PHQ-9) and another strict criterion based on composite international diagnostic interview short-form (CIDI-SF) ,19 were r2 > 0.5) were pruned. We removed the participants, who reported inconsistencies between self-reported gender and genetic gender, who were genotyped but not imputed, and who withdraw their consents. Additionally, individuals were restricted to only “white British” based on self-reported ethnicity (UK Biobank field ID: 21000). UK Biobank participants was used to obtain relatively independent SNPs through King software.A total of 488,377 participants were genotyped undertaking either the UK Bileve array or the UK Biobank axiom array under favorable quality control. Details of the array design, genotyping, and quality control procedures have been described elsewhere . These gp value <5.0 × 10−8 to calculate PRSs for all individuals. The GWAS summary statistics of European-only meta-analysis of own birth weight including 298,142 individuals was used in the present study. More details about the GWAS of birth weight were described in the previous study [The GWAS summary statistics of birth weight  was fromus study .n  and i  denote the number of genetic markers and the sample size, respectively. nβ represents the effect value of risk allele of the nth significant SNP related to birth weight obtained from the previous study [ni represents the risk allele dosage of the nth SNP of the ith individual. At last, 626 SNPs associated with birth weight driven from EGG consortium were used for PRS calculation by using PLINK’s“--score” command [The PRS of birth weight was calculated as the sum of allele, weighted by their effect sizes, defined by  command . We condWe applied a widely used approach for mediation analysis: the causal steps approach, which was described by Kenny et al.  , as well as birth weight PRS and depression . In women, depression was associated with birth weight phenotype  and PRS . In men, depression was only associated with birth weight PRS   .Table 2.B = 0.131, p = 3.51 × 10−74), gray and white matter , and thalamus . More additional details were provided in Table S1 in the Supplementary Material. In men and women, we obtained the similar results that birth weight was significant associated with each of the brain volumes. Detailed information was provided in the As shown in B = 0.027, p = 8.80 × 10−7), gray and white matter , and thalamus . More additional details were provided in Table S1 in the Supplementary Material. In men, we obtained the similar results that birth weight PRS was significant associated with each of the brain volumes, except the volume of gray matter in VIIIa cerebellum. And in women, birth weight PRS was only associated with the brain volume of gray matter, white matter, gray and white matter, left accumbens, and gray matter in frontal pole. Detailed information was provided in the As shown in p = 0.016), gray and white matter , left thalamus , and right thalamus . More additional details were provided in Table S4 in the Supplementary Material. In men, we only obtained that depression was significant associated with gray matter and gray matter in right VIIIa cerebellum. And in women, depression was associated with the brain volume of gray and white matter, thalamus, accumbens and gray matter in VIIIa cerebellum. Detailed information was provided in the As shown in p value >0.05). After gender classified, we observed the same results. Detailed information was provided in the We observed no significant association between birth weight (both phenotype and PRS) and depression, when one of the brain volumes was used as a covariate (all Through the causal steps approach, parts of the brain volumes were the complete mediators between birth weight and depression. For birth weight phenotype, the brain volumes included gray matter, gray and white matter, left thalamus, right thalamus, left accumbens, and gray matter in left VIIIa cerebellum. In men, gray matter and gray matter in left VIIIa cerebellum played the mediation effects between birth weight and depression. And in women, left and right thalamus, left and right accumbens and gray matter in left VIIIa cerebellum played the mediation effects between birth weight and depression.For birth weight PRS, the brain volumes included the brain volumes included gray matter, gray and white matter, left and right thalamus, left accumbens, and gray matter in left VIIIa cerebellum. In men, only gray matter played the mediation effects between birth weight and depression. And in women, only left accumbens played the mediation effects between birth weight and depression. More additional details were provided in We obtained the similar results from mediation analyses through R package. The indirect path from birth weight PRS that were based on a GWAS to depression via elevated levels of one of the brain volumes, including gray matter, gray and white matter, left thalamus, right thalamus, and left accumbens. More additional details were provided in Tables S10–S12 in the Supplementary Material.We conducted a large observational and genetic PRS study to evaluate the associations between birth weight, brain volume, and depression using UK Biobank population cohort. We observed phenotypic associations for birth weight versus brain volumes, birth weight versus depression, and depression versus brain volumes. Further PRS analysis also provided evidence for genetic predispositions between birth weight, depression and brain volumes. It is interesting that the correlation between birth weight and depression was not significant after adjusting the impact of brain volume, suggesting that brain volumes might be an important mediator between birth weight and depression.Previous studies have demonstrated that birth weight was associated with brain development –27, whicMeanwhile, association was also observed between brain volume and depression in this study. It has been suggested that decreased volume of the hippocampus, anterior cingulate cortex, prefrontal cortex, striatum and amygdala, and impaired white matter integrity are often observed in depressed adults . Merz etAs described in the introduction section, the association between birth weight and depression remains controversial . Some ofBased on the results, higher birth weight was associated with higher brain volumes, higher brain volumes were associated with lower morbidity of depression, and the weak association between depression and birth weight, we inferred that the brain volumes might play an important role for the observed association between birth weight and depression. This hypothesis was supported by the fact that the association between birth weight and depression disappeared, after adjusting the one of brain volumes as a covariate in regression analysis and significant indirect path results from the mediation approach. The possible mechanism is that the low brain volume of low birth weight leads to neuropathologic changes in adulthood, resulting in the risk of depression. Also, birth weight may affect the risk of depression through other mediating variables, so that more researches are expected.Using the individual-level phenotypic and genetic and data from the UK Biobank, the large sample size and a wide range of variables make our conclusions more rigorous and convincing. Using PRS method to explore the effect of birth weight on depression and brain volume is a powerful method to reduce the impact of nongenetic confounding factors on our study results.There were some limitations to this study. First, depression was measured retrospectively by self-report through an online questionnaire and birth weight was collected from participants’ recall, which may increase the likelihood of measurement errors. The conclusions are mainly applicable to middle-aged and elderly European populations, lacking comparisons among the young and the interracial populations. Second, the study is a cross-sectional study. Therefore, a causal relationship between depression and brain volume cannot be established. Third, it could be at birth persons with low birth weight had different brain development at birth, through the brain dysplasia of low birth weight ,30. AlthDue to treatment for depression can only alleviate rather than cure the condition, and the burden of depression outcome continues to grow. Therefore, the identification and prevention of the high-risk group of depression is an effective and key measure. Our study showed that birth weight was positively correlated with depression, negatively correlated with brain volumes and brain volume might an important mediator between birth weight and depression. Therefore, this study suggested that paying more attention to the birth weight and brain development might be helpful for early prevention and treatment of depression.


The resulting methodology is applicable to a wide range of substrates, from electron-rich units to electron-deficient units with large steric end groups. Aryl halides have been confirmed to be able to couple with dithienophthalimide (DTI) via direct C-H arylation, showing high regioselectivity. Varying the functional end groups onto the DTI core has been demonstrated to fine tune the emission colors to cover most of the visible spectra. The results suggest a facile strategy towards highly selective direct C-H arylation, opening the prospects towards efficient construction of π-conjugated molecules for various potential optoelectronic applications.Controllable direct C-H arylation with high regioselectivity is highly desirable yet remains a formidable challenge. Herein, a facile regioselective direct C-H arylation is developed for efficient construction of a variety of symmetrical dithienophthalimide-based  For  carbons –33. In c carbons –39. Due  carbons –43. Dire carbons , thienop carbons , and thi carbons . In ordeFor direct C-H arylation, the regioselectivity is a critical issue since the diverse C-H groups may lead to the formation of a variety of isomers and structural defects –50. The π-conjugated materials in the solid films with a broad scope ranging from 400 nm to 780 nm. The aromatic halides were successfully converted into target diarylated DTI derivatives with high yields. The general potential of this reaction has been studied by using several aryl substituents such as electron-rich groups , electron-deficient groups , and large steric groups (mesitylene)  building block and afford a series of symmetrical DTI-based conjugated molecules . This woitylene) . Interes3 was proven to be effective to afford the target material DTI2Mes with an isolated yield of 30%. The stronger base Cs2CO3 resulted in a higher yield . When the catalyst Pd(OAc)2 changed to Pd2(dba)3, the yield of DTI2Mes was further raised to 44%. Moreover, under the same conditions, a higher yield of DTI2Mes was obtained with using direct C-H arylation in o-xylene 3 (0.03 equiv.), P(2-MeOPh)3 (0.12 equiv.), PivOH (1.0 equiv.), and Cs2CO3 (3.0 equiv.) in o-xylene at 120°C for 24 h. Under the optimized conditions, the substrate (BrMes) with large steric hindrance groups was successfully coupled with DTI to afford product DTI2Mes in high yields (84%). Then, representative electron-rich groups including fluorene, pyrene, carbazole, and triphenylamine were examined to afford donor-acceptor type conjugated molecules in moderate to good isolated yields (58-72%). However, when using electron-rich bromothiophenes as the reaction substrates, only trace target compounds were obtained mainly due to the undesired homocoupling reactions and debromination byproducts of bromothiophenes. The reaction yield of DTI with BrCz was lower than that of its derivative (BrCzR), due to the existence of NH reactive groups in carbazole molecules which are prone to nucleophilic substitution. Subsequently, examination of the substrate scope was extended to electron-deficient (hetero)aryl bromides . Unfortunately, we failed to isolate pure products DTI2PDI and DTI2DPP because of the quite low yields. DTI2NTI with naphthalimide (NTI) as acceptor-type end groups was successfully obtained at a 63% yield. The favorable isolated yields of different substrates for the diaryl products suggest that direct C-H arylation is an attractive synthetic methodology for the construction of diverse organic π-conjugated molecules based on DTI.Investigation of the (hetero)aryl bromide substrate was carried out by optimizing the reaction conditions: Pdπ-conjugated molecules, which would subsequently limit the optoelectronic performance. Generally, it is difficult for the substrates with multiple C-H bonds to carry out selective C-H arylation, and the reaction conditions are also critical to determine the reactivity of the protons. Surprisingly, the C-H arylation based on DTI exhibits quite high selectivity. Although the reaction was also carried out through traditional Suzuki or Stille cross couplings, it was not applicable to construct selective DTI-based conjugated molecules due to the difficulty in purifying the dibrominated DTI  of DTI is lower than that of the β-position , which indicates that the C-H bond at the α-position is more active than that at the β-position. The activation energy is lower for reactivity at the α-position relative to the β-position, which may be due to the higher reaction activity and inherent electron bias of DTI. As such, the CMD state is regioselectivity-determining. The computational studies support the regioselectivity of C-H arylation based on DTI. Moreover, the Mulliken charge distribution of DTI was calculated with DFT at the B3LYP/6-31G level  transition between electron donor and electron acceptor [λonset) of DTI, DTI2Mes, DTI2NTI, DTI2F, DTI2Py, DTI2CzR, and DTI2TPA shifted towards the longer wavelength and the optical band gap (Egopt) gradually decreased from 2.78 eV to 2.17 eV. According to the results, DTI-based molecules with stronger electron-donating end groups demonstrate a larger extent of ICT characteristics, which confirm the electron-deficient nature of the DTI unit.UV-Vis absorption spectra of the DTI-based molecules were performed to explore the influence of end groups on light-harvesting performance. The analysis results of the materials are summarized in acceptor , 67. ForThe emissive properties of all the DTI-based molecules were measured in solutions and in films Figures . The emiπ-conjugated molecules exhibited negative shifts in oxidation potentials and little shift in the reduction potentials as compared to those of the DTI unit. According to the results, the end groups of DTI showed little effect on LUMO energy levels but obviously raised the HOMO energy levels, leading to a considerable band gap reduction and a substantial red shift in the onset of absorption, which was consistent with the trend based on optical band gaps (Egopt) and theoretical band gaps .To reveal the electronic properties, electrochemical properties were studied by cyclic voltammetry (CV) Figure . The resπ-π stacking. The torsion angle between the end groups and the core for DTI2Mes is 90° owing to the extra bulkiness of mesitylene . The maximum current efficient is 3.8 cd/A and 3.2 cd/A for devices I and II, respectively  and DTI2CzR (device II) was fabricated by solution processing. A single-emissive-layer OLED with the configuration ITO/PEDOT:PSS (40 nm)/DTI2F or DTI2CzR/TmPyPB (60 nm)/LiF (0.8 nm)/Al (100 nm) was fabricated . PEDOT:Py Figure . The simπ-conjugated molecules. The resulting methodology is effective and applicable for a wide range of substrates from electron-rich units to electron-deficient units with large steric end groups. In addition, direct C-H arylation of DTI is highly selective and ecofriendly as compared with the traditional Suzuki or Stille cross-coupling routes. Aryl halides have been confirmed to be able to couple with DTI via direct C-H arylation, showing high regioselectivity. According to this green methodology, various symmetrical new conjugated molecules based on DTI were successfully synthesized in a one-pot procedure, affording good to excellent yields. Varying the functional end groups onto the DTI core has been demonstrated to fine tune the emission colors to cover most of the visible spectra, which are potential active materials for organic optoelectronics, i.e., OLEDs. According to these photophysical and eletrochemical properties, the conjugated molecules are good candidates for high-performance solution-processable optoelectronic devices. Preliminary OLED measurements show that devices based on DTI2F and DTI2CzR achieved a maximum brightness of 7200 cd/m2 and 6100 cd/m2, respectively. The results suggest a facile strategy towards highly selective direct C-H arylation for the efficient construction of π-conjugated molecules for organic optoelectronic applications.In this work, we have developed a facile selective direct C-H arylation methodology for efficient construction of a variety of symmetrical DTI-based


Maternal nutrition during pregnancy is linked with birth outcomes including fetal growth, birth weight, congenital anomalies and long-term health through intra-uterine programming. However, a woman’s nutritional status before pregnancy is a strong determinant in early embryo-placental development, and subsequently outcomes for both mother and child. Therefore, the aim of this study was to investigate the association between dietary macronutrient intake in the preconception period with birth weight.We studied a group of 1698 women from the Dutch Perined-Lifelines linked birth cohort with reliable detailed information on preconception dietary macronutrient intake (using a semi quantitative food frequency questionnaire) and data available on birth weight of the offspring. Birth weight was converted into gestational age adjusted z-scores, and macronutrient intake was adjusted for total energy intake using the nutrient residual method. Preconception BMI was converted into cohort-based quintiles. Multivariable linear regression was performed, adjusted for other macronutrients and covariates.2 (SD 4.2) and median daily energy intake was 1812 kcal (IQR 1544–2140). Mean birth weight was 3578 grams (SD 472). When adjusted for covariates, a significant association  between polysaccharides and birth weight was shown . When linear regression analyses were performed within cohort-based quintiles of maternal BMI, positive significant associations between total protein, animal protein, fat, total carbohydrates, mono-disaccharides and polysaccharides with birth weight were shown in the lowest quintile of BMI independent of energy intake, intake of other macronutrients and covariates.Mean maternal age was 29.5 years (SD 3.9), preconception BMI: 24.7 kg/mOut of all macronutrients studied, polysaccharides showed the strongest association with birth weight, independent of energy intake and other covariates. Our study might suggest that specifically in women with low preconception BMI a larger amount of macronutrient intake was associated with increased birth weight. We recommend that any dietary assessment and advise during preconception should be customized to preconception weight status of the women. It has been widely acknowledged that adequate maternal nutrition, including maternal dietary intake before and during pregnancy, is a fundamental prerequisite for optimal growth, development and long term health of the offspring. Previous studies described deleterious effects of severe macronutrient deficiency on pregnancy outcome that depend on the stage of gestation , 2. WorlAlthough severe under nutrition and extreme low energy intakes are not very common for pregnant women in the western world today, differences in the contribution of macronutrients to the total energy intake potentially are. Godfrey et al (1997) examined the effect of maternal diet during pregnancy on the ponderal index (measure for weight in relation to height) of the offspring in the Southampton Women Survey ,  offspring.This study is part of the Perined-Lifelines linked birth cohort, a cohort linked between the Dutch national birth registry (Perined)  and the The Perined-Lifelines linked birth cohort was created by linking two existing databases; a large population-based cohort study  and theAmong the women in the Perined-Lifelines linked birth cohort, the inclusion criteria for the present analyses were delivery of a live born baby at term  and availability of information on birth weight of their offspring. Women with unreliable data for dietary intake were excluded from the analyses. Reliability of reported dietary intake was based on the ratio of reported energy intake and basal metabolic rate , 16; ratMacronutrient intake  in the period prior to pregnancy was assessed with a 110 item semi-quantitative, food-frequency questionnaire (FFQ)  that wom2), normal weight (BMI 18.5–25.0 kg/m2), overweight (BMI > 25.0 kg/m2). To understand to what extent possible associations could be attributed to specific groups of BMI, and which BMI group may potentially benefit most from changes in lifestyle, BMI quintiles were generated by use of the distribution within the study, whereby quintile 1 was defined as ‘low’ BMI (lowest 20% in this cohort), quintiles 2 to 4 as ‘normal’ BMI (middle 60% of this cohort and used as the reference) and ‘high’ BMI was based on quintile 5 (20% highest BMI in this cohort). The maximum possible time between the FFQ and birth of the child is the time between the FFQ at baseline and the follow-up questionnaire where the women filled in they delivered a child since the previous questionnaire. Maternal age was age at enrollment/baseline in Lifelines. Maternal education was assigned in three categories: low , intermediate  and high  education. Maternal ethnicity was classified as either ‘white/European’ and ‘other’. Maternal smoking was divided into ‘smoking’ or ‘non-smoking’ as indicated at baseline. Maternal alcohol use was divided into ‘alcohol use’  and ‘no alcohol use’ [Preconception maternal BMI was calculated based on measured height and weight at the Lifelines research sites at enrolment (baseline) to Lifelines. Height and body weight were measured without shoes and heavy clothing with the SECA 222 stadiometer and the SECA 761 scale. For the description of the cohort it was first grouped using the WHO classification: underweight  and birth weight  (outcome) were estimated by linear regression. Adjusted analyses were performed using multivariable linear regression, using different multivariable models (different covariates included). Based on the R-squared and Akaike Information Criteria (AIC), estimators of the relative quality of statistical models of a given set of data, the best model will be reported . Least Absolute Shrinkage and Selection Operation (LASSO) regression analyses was performed to examine the strongest predictor of birth weight out of all the macronutrients and covariates . LASSO iLinear regression analyses between macronutrient intake and birth weight were performed within the complete cohort. To test whether the association of macronutrients intake with birth weight is modified by maternal BMI, two different sets of analyses were conducted. Firstly, interaction terms between macronutrients intake and categorical BMI (cohort based quintiles) were included into the regression model within the complete cohort, and secondly separately regression models were fitted within each strata of BMI (cohort based quintiles). Statistical significance was assumed at P < 0.05. Analyses were performed in SPSS version 23 .A total of 2,368 women from The Lifelines Cohort Study could be linked to available data in Perined. After excluding women who did not have reliable, or missing dietary intake reported (resp. n = 427 and n = 168), pre-term births  and unknown sex of the child (n = 1), 1,698 women remained available for analyses. The characteristics of the study cohort, presented as three groups of BMI; ‘low’ BMI , ‘normal’ BMI , and ‘high’ BMI , are summarised in As shown in When characteristics of the cohort were compared between groups of BMI using the WHO classification, the results were in line with results reported in The study cohort was representative in terms of diet quality in comparison with the complete Lifelines Cohort study , 23. TheA range of linear regression models with different combinations of covariates were considered to investigate which model showed the best explaining variance of birth weight outcome. The model with the best goodness of fit (based on the R-squared and AIC) was the model with adjustment for intake of other macronutrients, maternal BMI, maternal age, smoking, alcohol, education level, urbanization level, parity, sex of newborn, ethnicity and energy intake  . Linear regression analysis within this model showed that increased intake of polysaccharides was associated with increased birth weight  . In addiAdditional analyses were performed with possible outliers of BMI (n = 29) excluded, however did this not affect the results. Therefore, the results showed here are with these cases included.Lasso regression analysis was performed including all macronutrients, covariates and birth weight, to check which variables are the strongest predictor for birth weight. No robust statistical associations were found between macronutrients and birth weight. However, lasso regression models exhibited a robust statistical association between maternal preconception BMI , parity  and sex of the child  with birth weight, with maternal BMI being the only modifiable factor.To investigate if the association between preconception macronutrient intake with birth weight can be attributed to specific groups of BMI, linear regression analyses were performed within cohort based BMI quintiles . These analyses showed that within the group of women with the lowest BMI , there was a significant positive association between animal protein, fat, total carbohydrates, mono-and disaccharides and polysaccharides and birth weight . AdditioLinear regression analyses within quintiles of BMI showed consistent positive significant associations between specific macronutrients intake and birth weight. As shown in The aim of this study was to investigate the relationship between maternal macronutrient intake and birth weight of the offspring in a representative group of women from fertile age in a western Caucasian population, with the majority having a normal BMI according to the WHO definition .To the best of our knowledge, this is the first large cohort study to explore the relationship between maternal dietary macronutrient intake in the preconception period and birth weight of the offspring. Within this (relatively) healthy, homogenous population, with minimal variation in adjusted birth weight, we observed that out of all the macronutrients studied, preconception intake of polysaccharides appears to have the strongest association with birth weight, independent of energy intake and maternal characteristics. However, in line with other studies, maternal BMI, parity and sex of the child showed a more robust association with birth weight than maternal intake of macronutrients.We evaluated the association of maternal macronutrient intake with offspring’s birth weight for specific groups of BMI and found that within the group of women with a lower preconception BMI, higher macronutrient intake (except for plant protein) was associated with an increased birth weight, independent of energy intake and maternal characteristics. However, the interaction term between BMI quintiles and macronutrient intake was not significant. An association between total energy intake  and birth weight was not shown in this cohort, both when analyses were performed in the complete cohort as in BMI quintiles. Therefore, the association between an increase of specific macronutrients intake and birth weight was not explained by total energy intake.We showed that higher maternal intake of polysaccharides during preconception was associated with higher birth weight of the offspring. This finding is in agreement with a study which investigated this association during pregnancy . Sharma We did not find any significant association between maternal intake of the other macronutrients and birth weight when we performed analysis within the complete cohort. Our study participants were adequately nourished  and therThese observations are in line with the study from Switkowski et al. who also reported such a ‘U-shaped’ association with decreasing birth weight upon increments in protein intake among a group of pregnant women (n = 1961) . In addiAlthough studies investigating macronutrient intake during preconception and birth weight are scarce, several epidemiological studies showed an association between dietary intake during pregnancy and birth weight. However, contradictory results have been reported. On the one hand, Haste et al. , GodfreyIn order to investigate which of the variables  were the strongest predictor of birth weight, we performed LASSO regression analysis. Maternal BMI, parity and sex of the child appeared to be the strongest predictors of birth weight within our study. This finding is in line with a study from Radesky et al., who investigated the association between nutrients and dietary patterns with the risk of gestational diabetes mellitus, and showed that pre-pregnancy BMI might be of greater importance than the maternal diet for the development of gestational diabetes . IndividAdjusted linear regression showed a positive significant association between all the macronutrients (except plant protein) independently and birth weight in the lowest quintile of BMI (20% lowest BMI within our cohort). Although our results showed that the interaction term between specific macronutrients intake and birth weight in quintiles of BMI was not significant, we do not think this completely invalidates our findings. Other studies have found similar results, showing stronger associations between fruit and vegetable intake with increased birth weight among lean pregnant women . The samThe fact that we only find and association in the lowest quintile of BMI, and not in the other quintiles, without the interaction term being significant, could potentially be due to the fact that women in the lowest quintile differ in terms of demographical information where we have not (been able to) adjusted for. Characteristics with a yet unknown epidemiological or biological influence can potentially explain the differences found between the BMI quintiles. In addition, although less likely, it could be due to the fact that the BMI quintiles are not randomized and so perhaps the lowest BMI quintile has the highest heterogeneity/variation in variables. Future studies that will focus on dietary intake in the preconception period, should pay attention to different groups of maternal BMI, also to those having low BMI within the preconception period.This study has several strengths. This is a large cohort comprising of 1698 women containing detailed reliable dietary data from their preconception period and pregnancy outcome of their offspring. Dietary intake was assessed using a food frequency questionnaire, allowing detailed information about food types and amounts to be recorded without influencing the participant’s eating behaviour, decreasing chance of bias. Additionally, in order to minimize the confounding effect of how maternal intake affects birth weight, we adjusted for maternal age, preconception BMI, sex of the child, parity, gravidity, smoking, alcohol intake , 50–54. The maximum time between dietary assessment and conception among the women in our cohort is very short making it less plausible that dietary intake has changed in between these two time points. Besides this, diet tends to be quite stable over time , and chaThere are few limitations, relevant to any study that explores dietary intake. The data in this cohort were not adjusted for maternal weight gain in pregnancy, since we only have weight of the mother during the preconception period and not during or after pregnancy. It is known that weight gain during pregnancy is associated with birth weight, and it may confound the association with maternal BMI. Therefore, the effect that we have found in this study could be related, at least in part, to differences in maternal weight gain.Information on placental weight was unfortunately not available in our cohort. Together with birth weight it can give valuable information on potential growth restriction or risk for adverse outcomes for the offspring . In the Our study included mostly women of Caucasian ethnicity, which limits extrapolation of the results to other ethnicities. However, the homogeneity of the study population makes the risk of possible confounding less likely.When analyses were performed within cohort-based birth weight quintiles, no statistically significant association was shown between macronutrients intake and birth weight. This could be due to several reasons. First, from an epidemiologically point of view, maternal BMI is potentially more informative, and is having a stronger association with macronutrients, rather than birth weight on its own. From a statistical point of view, the distribution of birth weight is lower in the birth weight quintiles compared to distribution of birth weight in the BMI quintiles, making it more difficult to find a significant association.Although we showed a negative association between preconception energy intake and maternal BMI, we consider this association very weak. The effect size was very low, with a R-squared/AIC close to zero and thus not likely to affect our results. The fact that women with the highest BMI had the lowest energy intake based on the FFQ, may be due to underreporting which has been described in literature before .The primary advantage of representing diet as macronutrients is that such information can be directly related to our fundamental knowledge of biology . CalculaIn conclusion, to the best of our knowledge, this is a first large study investigating dietary macronutrient intake in the preconception phase and its association with pregnancy outcome in a homogenous cohort. Out of all the macronutrients studied, polysaccharides showed the strongest association with birth weight, independent of energy intake and covariates.This study underlines the importance of investigating dietary intake in the preconception phase and its association with pregnancy outcome. We recommend that future studies should focus on dietary intake in the preconception period, whereby different groups of women according to their preconception BMI need be made for analyses. With this, in future, dietary assessment and advise during the preconception phase can be tailored to weight status of the mother.S1 Table1Adjusted for intake of other macronutrients, maternal BMI, maternal age, smoking, alcohol, education level, urbanization level, parity, sex of newborn, ethnicity. 2 Coefficients are expressed as z-scores, i.e. the unit for the coefficients is one standard deviation (SD).(DOCX)Click here for additional data file.