Official data on birth is important to monitor the specific targets of SDGs. About 2.7 million children under age five years do not have official birth registration document in India. Unavailability of birth registration document may deprive the children from access to government-aided essential services such as fixed years of formal education, healthcare, and legal protection. This study examines the effect of socioeconomic, demographic and health care factors on birth registration in India. We also examined the spatial pattern of completeness of birth registration that could be useful for district level intervention.We used data from the National Family Health Survey (NFHS-4), 2015–16. We carried out the descriptive statistics and bivariate analysis. Besides, we used multilevel binary logistic regression to identify significant covariates of birth registration at the individual, district, and state levels. We used GIS software to do spatial mapping of completeness of birth registration at district level.The birth registration level was lower than national average (80.21%) in the 254 districts. In Uttar Pradesh, 12 out of 71 districts recorded lower than 50% birth registration. Also, some districts from Arunachal Pradesh, J&K, and Rajasthan recorded lower than 50% birth registration. We also found a lower proportion of children are registered among children of birth order three and above (62.83%) and rural resident (76.62%). Children of mothers with no formal education, no media exposure, poorest wealth quintile, OBC and muslims religion have lower level of birth registration. Multilevel regression result showed 25 percent variation in birth registration lie between states while the remaining 75 percent variation lie within states. Moreover, children among illiterate mother , Muslims households , and poorest wealth quintile  showed lower odds for child’s birth registration.We strongly suggest linking the birth registration facilities with health institutions. Birth registration is the formal recording of the occurrence and characteristics of birth by the civil registrar with legal requirements. UNICEF documented "the child should be registered immediately after birth and shall have the right from birth to a name and right to acquire nationality" . The conMoreover, the quality of vital statistics is indispensible to monitor children’s development. Timely birth registration is essential for generating an up-to-date and reliable vital statistics . CompletDespite government agencies and UNICEF’s effort to universalize birth registration globally, about 166 million children under age five and 40 million infants were not officially documented . MoreoveIn India, the Births, Deaths and Marriage Registration Act, was enacted in 1886, suggested voluntary registration of births and deaths. However, it was not adequately implemented across India. After independence, India’s Government introduced the Registration of Births and Deaths Act in 1969, which mandates registration of all births and deaths within 21 days . DespiteThere has been increased research around the impact of under-registration, but previous studies were focused on the need and benefits associated with functional registration systems , 7, 12. Does a child have a birth certificate or has child’s birth ever been registered by the civil authority" [We used data from National Family Health Survey, 2015–16 (NFHS-4). It provides essential information on household populations, housing characteristics, basic demographic and socioeconomic characteristics of respondents, fertility, family planning, maternal and child health, infant and child mortality, nutrition, morbidity including adult health issues, women empowerment, and domestic violence at the nation, state and district level. This survey was conducted under the Ministry of Health and Family Welfare (MoHFW) leadership and managed by the International Institute of Population Sciences (IIPS), Mumbai. The NFHS provides information on the number of dejure children under age five registered by the civil registrar. In the survey, a question on birth registration was asked as "thority" .Two stages stratified random sampling approach was adopted in this survey. Primary Sampling Units (PSUs)  are selected using probability proportional to population size at the first stage. Subsequently, an equal number of households were selected from each PSU through systematic random sampling. In total, 6,99,686 women and 1,12,122 men were interviewed in this survey. We included a total of 2,25,867 children under age five years from 640 districts and 36 states/UTs of India in the final analysis sample.A dependent variable birth registered was defined as one equals to children under age five years who have a birth certificate or ever been registered by the civil authority, otherwise 0.We considered demographic, socioeconomic, and healthcare characteristics to identify factors associated with children’s birth registration. We categorized child age as 0–1,1–3, and 3–5 years, sex of the child , and birth order as 1,2,3 and 3+. Other demographic and socioeconomic characteristics include the place of residence , sex of the head of household , mothers age in years , mother’s level of education , religion , caste , wealth quintile . We categorized marital status into two categories (currently married and separated/divorced/widow). We defined mothers’ exposure to media into three categories  based on their response to how often they read the newspaper, listen to the radio, and watch television. Mothers who did not read newspaper, not listen to radio and not watch television less than or at least once in a week were categorised as having no media exposure. Mothers exposed to any one or two of the three forms of media were categorised as having partial media exposure. Mothers exposed to all the three forms of media were categorised as having full media exposure. Besides we included a healthcare variable. We divided children’s vaccination status into three categories . No vaccination refers to children aged 12–23 months who did not receive any vaccines since birth, partial vaccination indicates children received at least one but not all recommended vaccines and full vaccination refers who received all 13 recommended vaccines.Furthermore, we considered district-level factors such as the proportion of SCs, the proportion of children (12–23 months) receiving full immunization, and the proportion of institutional birth. We generated the district level variables by aggregating individual or household level information at the district level.We presented the descriptive statistics of dependent and independent variables included in this study. Further, we analyzed bivariate distribution to examine the association of demographic, socioeconomic and health care variables with children’s birth registration. Also, we performed chi-square test to identify the significance of such associations. We applied multilevel binary logistic regression models with random intercept and fixed slope to calculate odds ratio (OR)/Adjusted odds ratio (AOR) at three levels  with 95 percent of confidence interval (CI) and p-value. When the p-value was lesser than 0.05, odds ratios were considered statistically significant. Multilevel analysis generates variance at each level, providing the technical advantage of assessing unobserved effects at each level. The hierarchical model of the survey justified the application of multilevel modelling in this study. We fitted four models. Firstly, we run the null model. Second model included only demographic variables whereas the third model included demographic and socioeconomic variables. Finally, the fourth model was adjusted for demographic, socioeconomic, and district-level variables. We used Akaike Information Criteria (AIC) and log-likelihood for model comparison. The model with the lowest value of AIC and the highest log-likelihood value was considered the best fit. Besides, we checked multicollinearity using the Variance Inflation Factor (VIF). We found no evidence of collinearity among the included independent variables (mean VIF = 1.34). We explained the fourth model in detail as there was a similar pattern in the second, third and fourth models. We also estimated Intra Class Correlation (ICC) to find the percentage variance explained at district and state level. All analysis was performed using R (version 4.0.2). Further, we also mapped the district-wise proportion of registered children using the Geographic Information System (GIS). Besides, we mapped the predicted estimates of birth registration level using the GIS software.The mathematical equation of the three-level model is shown below:πijk = p(Yijk = 1) is the probability of a child i in the district j, from state k, registered birth. Yijk would equal one if a child were registered, otherwise 0. The probability is defined as a function of an intercept and the explanatory variables. β0jk = β0 + μ0jk, where β0jk shows that intercept was random at jth (district) and kth (state) levels. The variables X1ijk to Xnijk were exploratory variables and their corresponding regression coefficients  were fixed effects.Where σu2)u0jk is the random state effect assumed to be normally distributed with Nv0jk is the random district effect assumed to be normally distributed with N and independent of random effects at level 2 and level 3.eijk is the random errors assumed to be normal with N than Hindus households (80.15%). Besides, a lower percentage of children was registered among STs (76%) and OBC (78.09%). Nearly 94.44 percent of children are registered among the richest household, whereas about 64.32 percent of children are registered among the poorest household. It is also found that the proportion of registered children were lower among female-headed household (77.20%).We found as compared with children age 0–1 year, children between age group 1–3 years and 3–5 years have higher  and lower  likelihood of birth registration. Interestingly, female children have a higher likelihood of birth registration as compared to male children . Besides, children of birth order 2  showed lower likelihood of birth registration as compared with children of birth order 1. Place of resident was found to be significantly associated with child’s birth registration. We found as compared with children living in urban areas, children living in rural areas have a lower likelihood of birth registration .Mother’s characteristics were found to be significantly associated with child’s birth registration. As compared with mothers among younger age group (15–24) years, mothers among age group 25–34 years  and 35–49 years  have a higher likelihood of birth registration for their children. A lower odds of birth registration was observed among primary educated  and illiterate mothers  as compared to higher educated mothers. Besides, mothers who had exposed to partial  and no  media showed a lower likelihood for their child’s birth registration as compared with mothers exposed to full media. Wealth status of household was also found to be significantly associated. We found as compared with mothers among richest wealth quintile, mothers belong to poorest  and poorer  wealth quintile showed a lower likelihood for birth registration of their children.The result also showed that living in a district with higher proportion of SCs households increases the odds of child’s birth registration . However, we found the result was not significant. Moreover, residing in a district with higher proportion of institutional birth  and proportion of vaccinated children  showed a higher odds of child’s birth registration.Birth registration is a legal process, but it is essential for proving fundamental rights and essential services such as education and health facility to children. It protects children from unlawful activities such as child labour, trafficking, and child marriage. Registration of Birth and Death (RBD) act, 1969, mandates registration of all births and deaths within 21 days of the event . There hThis study showed higher birth registration among female children. A higher birth registration among female children could be attributed to financial benefits schemes such as Balika Samridhi Yojna. Each female child is entitled to 500 rupees post-birth and receives a scholarship from India’s Government to complete a set of years of schooling . A previChildren in rural areas are less likely to register, which is not unusual; the distance to the registration center includes higher financial and indirect opportunity costs for the family. A higher proportion of institutional birth results to higher registered birth in urban areas. The higher birth registration among institutional births could be attributed to the fact that it is the duty of medical officers to register all births delivered in the health facilities. Previous studies also supported our finding , 13, 22.This study showed that younger mothers 15–24 years) have a lower likelihood of birth registration of their children. A lower practice of birth registration among young mothers could be attributed to less awareness of the registration process and a childcare experience. This study found a significant positive association between children’s birth registration and the mother’s education level. Mothers who completed formal years of education have more access to institutional health care, media exposure, and knowledge on the registration process. Besides, an educated woman has exposure to social network of the other educated person which increases the odds of her child’s birth registration. Previous studies documented a similar finding , 17, 24. years haMoreover, this study showed significant positive association between the child’s vaccination and his/her birth registration. Living in a district with higher proportion of immunised children significantly increases the odds of birth registration. Considering the fact, registration centers are open within some health care facilities may have contributed to this finding. A previous study documented vaccination services provide an opportunity for health workers to be alerted to absence of birth certificate, leading vaccination to be viewed as potential driver to register a child’s birth. Besides, another study showed that in 43 countries having a vaccination card makes children more likely to be registered . This stDespite a comprehensive analysis, this study has some limitations. The quality of findings may be affected by recall or reporting biases. Mainly, possession of the birth certificate is socially desirable behavior and may lead to overestimating registered birth; however, birth certificate was requested to confirm the reporting. Also, this study examined the association between birth registration and the independent variables as it is based on cross sectional data, it does not establish causal link.Birth registration provides access to government-aided essential services such as healthcare, education, and legal protection. Health officials and policymakers frequently use birth registration data in framing health policies and socioeconomic development programs. Birth registration level vary significantly between and within states, indicates need for the adequate programmes at lower administrative level. Children’s age, birth order, place of residence, religious affiliation, and vaccination appear to be significant determinants of birth registration. We strongly suggest linking the birth registration facilities with health institutions. We also suggest periodic awareness campaigns on birth registration benefits among underprivileged population groups and low-performing districts. Establishing a community-based birth registration unit, i.e., registration unit at primary and community healthcare, may ensure accessibility and improve birth registration completeness.S1 Table(XLSX)Click here for additional data file. 31 May 2021PONE-D-21-06116Determinants of Birth Registration in India: Evidence from NFHS 2015-16PLOS ONEDear Dr. Kumar,Thank you for submitting your manuscript to PLOS ONE. 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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: No**********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 manuscript was well written and the statistical analysis is sound. Below is the minor correction that the authors should make.1. P values of 0.000 should be written as p < 0.001 just like appeared in notes of the results2. “insignificant” should read “not significant” (lines 276 and 280)Reviewer #2: I understand that this paper studies the determinants of birth registration in India using a nationally representative and the latest round of NFHS 2015-16. The authors carried out the bivariate analysis and multilevel binary logistic regression to identify significant covariates at the individual, district, and state levels to determine the likelihood of birth registration. Authors also did spatial mapping to present the status of birth registration across districts in India using GIS.However, I have concerns that the manuscript is not written well to merit publication in PlosOne. Additionally, I have concerns over the methodology and presentation of this manuscript. I have listed my concerns below:1. To start with, I believe the abstract is not written well. It lacks the standard presentation style and is not very smooth to read. I believe in the very first statement the authors need to present the research problem clearly and succinctly. And, in the next sentence the authors need to write why it is important to study the problem. Then the data description, methodology, results, and conclusion need to follow in a nice and smooth manner. I feel while everything is there the writing lacks a coherent presentation style. More importantly the authors need to bring in what is the significant value addition of this research, which I feel is overall lacking.2. Overall, the manuscript is not well written. The background sections are not well motivated and lacks a robust literature review. Introduction seems very disjoint. It fails to captivate the reader into the topic. I recommend rewriting the background section with a strong literature review that will motivate the study with a nice flow in writing. Also, the authors fail to review one important previous study on this topic on India that was published on PLoS ONE, Mohanty and Gebremedhin (2018) that I believe is an important precursor for this manuscript. Please see below:Mohanty I, Gebremedhin TA (2018) Maternal autonomy and birth registration in India: Who gets counted? PLoS ONE 13(3): e0194095.https://doi.org/10.1371/journal.pone.01940953. In the final paragraph of the Introduction section (line no:108-109) the authors identified the gap that few previous studies attempted to investigate the civil registration systems design and functional status. However, all through the manuscript there was no further discussion on this issue nor did the authors made any attempt to include any variables in the model that would have represented differences in the Civil registration systems design and function/practice across districts/states in India. Also, on several other places in the manuscript, I find similar orphan sentences initiating a discussion or reporting a result that were not closed properly.4. On line no: 109-111, the authors wrote, there is a lack of systematic research examining predictors of birth registration in India at an individual and community level while they have failed to refer the publication Mohanty and Gebremedhin (2018), which is an important pre-cursor of this study and the authors need to bring out comparison between the present study and Mohanty Gebremedhin (2018) highlighting the significant added value of this manuscript.5. On line no: 119 on Materials and methods section (Data Source) the authors need to rephrase writing – they have used the most recent round of a nationally representative demographic and Health Survey on India, National Family Health Survey, 2015-16 (NFHS-4).6. In the Study design and samples section, I disagree with the authors decision to select the sample only for the districts (n=258) where the birth registration level was lower than the national average. This action may have led to significant bias in the regression results while the model would fail to identify the facilitators (motivating factors) that positively influence the birth registration. I believe this is an important lacking in the model that the authors need to address to qualify their manuscript for publication. This is a significant methodological failing if there are no other systemic or contextual differences between the districts where the birth registration level was lower than the national average and where it was higher. If the authors are interested to study the difference between these two groups of districts, they can choose to include an indicator variable in the model and interact that indicator variable with other important variables to study the differential effect. However, presently in this shape the model suffers from sample selection bias.7. Also, I believe it would be useful if the authors present what proportion of the dependent variable represent children who have a birth certificate compared to those who are ever been registered by the civil authority but, do not have a birth certificate.8. I believe it is useful that the authors generated a map of level of birth registration of children under age five years, Indian districts, 2016 using GIS. However, it would be useful and will add significant value to the research undertaken in this manuscript if the authors generate another map with the multi-level logistic regression model’s predicted estimates and compare the two maps.9. The Table 1 where the authors presented their bivariate analysis, is redundant and does not improve the overall presentation of the manuscript since the authors did run a multi-level logistic regression model in the later part and presented the results in Table 2. However, it is required that the authors present a descriptive statistic table  of the variables included in the final model. This is useful information for the readers to assess the model.10. On line no: 225-227, the authors reported that about 59% of children are registered among no vaccinated children, whereas 71% of children are registered among children who received at least one vaccine. And the vaccination status is later coming up as statistically significant in the bivariate and multi-variate regression models. However, I believe it raises an important question here, which one comes first in the sequence of occurrence, or which one is the cause? Do the families need to register the birth first and then go for vaccination or, it is other way round? It is important to bring in what is required and what is practice and if there is a variation in practice across districts/states. Also, is there an endogeneity issue here?11. On line no: 229-231 the authors reported that nearly 64% of children are registered among currently married mothers, whereas only 58% of children were registered among divorced or widowed marital status. I believe these figures are misleading without an idea on the descriptive statistics of the sample. For example, it will be useful to interpret these statistics with reference to what proportion of the children in the sample belongs to a single mother with a divorce/widow status. The same argument applies to all the descriptions on Table 1, which I believe is redundant.12. In Table 2 in presenting the results of the multi-level logistic regression analysis the authors presented the coefficients and not the odds ratios. I believe presenting odds ratios are the accepted standard for logistic regression.13. The manuscript is lacking a discussion on the list of variables that were included in the multi-level regression analysis at different levels and the proportion of variations in the model explained by variables included at different levels. For example, if within district differences account for most of the variation in the model or is it within states/individuals. A discussion on ICC or Variance Partition Coefficient (VPC) to represent the percentage variance explained by the different levels and it’s policy implications would be useful.14. Again, the discussion section is poorly written, and it is not clearly bringing out the significant added value of this study over previous studies. In most places the authors present their results and then in the next sentence they are saying previous literature showed similar findings. I believe the authors need to discuss their results with supporting literature and possible explanations and greater policy implications.15. On line no: 320 it is reported that in many countries, a single mother cannot register their children. Since this manuscript is on India, I believe the authors need to bring out a discussion on India.16. On line no: 320-321 the authors need to explain what do they mean by different media kinds and how do they construct/define this variable in their regression.17. On line no: 329, the authors wrote that the cost associated with registration is a barrier to birth registration. I believe they need to discuss this further, which cost – direct/indirect.18. Overall the manuscript needs to be grossly rewritten with a strong literature review and the major issues in the methodology, presentation and mapping and discussion sections need to**********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, AttachmentDeterminants of birth registration in India.docxSubmitted filename: Click here for additional data file. 2 Aug 2021Response to reviewersReviewer #1:The manuscript was well written and the statistical analysis is sound. Below is the minor correction that the authors should make.1. P values of 0.000 should be written as p < 0.001 just like appeared in notes of the results.Response- We thank you for this suggestion. Now, p-value of 0.000 has been changed to p<0.0012. “insignificant” should read “not significant” (lines 276 and 280)Response- We thank you for this suggestion. We changed insignificant to not significant.Reviewer #2: I understand that this paper studies the determinants of birth registration in India using a nationally representative and the latest round of NFHS 2015-16. The authors carried out the bivariate analysis and multilevel binary logistic regression to identify significant covariates at the individual, district, and state levels to determine the likelihood of birth registration. Authors also did spatial mapping to present the status of birth registration across districts in India using GIS.However, I have concerns that the manuscript is not written well to merit publication in PlosOne. Additionally, I have concerns over the methodology and presentation of this manuscript. I have listed my concerns below:1. To start with, I believe the abstract is not written well. It lacks the standard presentation style and is not very smooth to read. I believe in the very first statement the authors need to present the research problem clearly and succinctly. And, in the next sentence the authors need to write why it is important to study the problem. Then the data description, methodology, results, and conclusion need to follow in a nice and smooth manner. I feel while everything is there the writing lacks a coherent presentation style. More importantly the authors need to bring in what is the significant value addition of this research, which I feel is overall lacking.Response: We have revised the abstract as per your suggestions.2. Overall, the manuscript is not well written. The background sections are not well motivated and lacks a robust literature review. Introduction seems very disjoint. It fails to captivate the reader into the topic. I recommend rewriting the background section with a strong literature review that will motivate the study with a nice flow in writing. Also, the authors fail to review one important previous study on this topic on India that was published on PLoS ONE, Mohanty and Gebremedhin (2018) that I believe is an important precursor for this manuscript. Please see below:Mohanty I, Gebremedhin TA (2018) Maternal autonomy and birth registration in India: Who gets counted? PLoS ONE 13(3): e0194095.https://doi.org/10.1371/journal.pone.0194095Response: Thank you for your observation and wonderful suggestion. We revised the background section and added a few important literature to make it more informative. We referred the study you mentioned. 3. In the final paragraph of the introduction section (line no:108-109), the authors identified the gap that few previous studies attempted to investigate the civil registration systems design and functional status. However, all through the manuscript there was no further discussion on this issue nor did the authors made any attempt to include any variables in the model that would have represented differences in the Civil registration systems design and function/practice across districts/states in India. Also, on several other places in the manuscript, I find similar orphan sentences initiating a discussion or reporting a result that were not closed properly.Response: I thank you for this observation. NFHS does not provide information on quality and function status of civil registration system. Therefore, we could not include such variables in the model. Besides, this study primarily focuses on covariates of birth registration. Furthermore, I have revised the discussion section and supported our results with previous literature.4. On line no: 109-111, the authors wrote, there is a lack of systematic research examining predictors of birth registration in India at an individual and community level while they have failed to refer the publication Mohanty and Gebremedhin (2018), which is an important pre-cursor of this study and the authors need to bring out comparison between the present study and Mohanty Gebremedhin (2018) highlighting the significant added value of this manuscript.Response: I thank you for this important observation. We have reviewed the suggested literature . The literature included demographic, socioeconomic and women empowerment variables, examined the variation in birth registration level at the district and community level. However, the literature was primarily focussed on the variables representing mother’s social and economic, and bargaining power in the household and its association with her child’s birth registration. The study did not present birth registration percent at district level due to small sample size. In addition, the referred study was based on 2011-12 and may not present true situation regarding birth registration level. On the other hand, our study included a large sample size (225867) from a recent large-scale survey, NFHS-2015-16, may provide robust results useful for decision making to increase birth registration level in India and its states and districts. In addition to multi-level modelling, our study showed spatial mapping of birth registration level by district of India. Our study showed considerable variation in birth registration level due to the state and district level factors, demographic, socioeconomic, and health care characteristics that is still not widely explored in India.5. On line no: 119 on Materials and methods section (Data Source) the authors need to rephrase writing – they have used the most recent round of a nationally representative demographic and Health Survey on India, National Family Health Survey, 2015-16 (NFHS-4).Response: Thank you for this suggestion. We have rephrased the sentence now. (please see line no. 129)6. In the Study design and samples section, I disagree with the authors decision to select the sample only for the districts (n=258) where the birth registration level was lower than the national average. This action may have led to significant bias in the regression results while the model would fail to identify the facilitators (motivating factors) that positively influence the birth registration. I believe this is an important lacking in the model that the authors need to address to qualify their manuscript for publication. This is a significant methodological failing if there are no other systemic or contextual differences between the districts where the birth registration level was lower than the national average and where it was higher. If the authors are interested to study the difference between these two groups of districts, they can choose to include an indicator variable in the model and interact that indicator variable with other important variables to study the differential effect. However, presently in this shape the model suffers from sample selection bias.Response: We thank you for this suggestion. We have revised the analysis for all districts of India now. . 7. Also, I believe it would be useful if the authors present what proportion of the dependent variable represent children who have a birth certificate compared to those who are ever been registered by the civil authority but, do not have a birth certificate.Response: Thank you for this suggestion. We have added a descriptive statistics table for a dependent and all independent variables (Table 1). Table 1 shows proportion of children who have birth certificate and ever registered children but do not have birth certificate.8. I believe it is useful that the authors generated a map of level of birth registration of children under age five years, Indian districts, 2016 using GIS. However, it would be useful and will add significant value to the research undertaken in this manuscript if the authors generate another map with the multi-level logistic regression model’s predicted estimates and compare the two maps.Response: Thank you for your suggestion. We have incorporated this important suggestion. We have added another map of multi-level logistic regression model’s predicted estimates of birth registration level. Also, we have compared the two maps in the revised manuscript .9. The Table 1 where the authors presented their bivariate analysis is redundant and does not improve the overall presentation of the manuscript since the authors did run a multi-level logistic regression model in the later part and presented the results in Table 2. However, it is required that the authors present a descriptive statistic table  of the variables included in the final model. This is useful information for the readers to assess the model..Response: Thank you for this important suggestion. Now, we have included descriptive statistics of dependent and independent variables with full sample size. However, we showed proportion, standard errors and confidence interval for each variable because the variables included in our study are categorical in nature.10. On line no: 225-227, the authors reported that about 59% of children are registered among no vaccinated children, whereas 71% of children are registered among children who received at least one vaccine. And the vaccination status is later coming up as statistically significant in the bivariate and multi-variate regression models. However, I believe it raises an important question here, which one comes first in the sequence of occurrence, or which one is the cause? Do the families need to register the birth first and then go for vaccination or, it is other way round? It is important to bring in what is required and what is practice and if there is a variation in practice across districts/states. Also, is there an endogeneity issue here?Response: Usually, birth registration is done at the time of birth and vaccinations are done afterwards according to vaccination schedules. Because of our study is of cross -sectional in nature, information on both vaccination and registration status was collected at the time of survey. Our study shows partial and fully vaccinated children are more likely to get registered their birth, but because of lack of timing of birth registration data, we cannot infer which one causes which. We can simply infer the association between vaccination and birth registration. Previous studies also showed vaccination drive alert health care worker to the absence of a birth certificate . India’s health policy does not mandatorily require birth certificate of children to vaccinate them; therefore, birth certificate should not directly affect child’s vaccination. We have mentioned this point in the limitation of the study (line no. 434-436). 11. On line no: 229-231 the authors reported that nearly 64% of children are registered among currently married mothers, whereas only 58% of children were registered among divorced or widowed marital status. I believe these figures are misleading without an idea on the descriptive statistics of the sample. For example, it will be useful to interpret these statistics with reference to what proportion of the children in the sample belongs to a single mother with a divorce/widow status. The same argument applies to all the descriptions on Table 1, which I believe is redundant.Response: We thank you for this observation and suggestion. Now, we have included descriptive statistics of a dependent and independent variables in the revised manuscript (Table 1).12. In Table 2 in presenting the results of the multi-level logistic regression analysis the authors presented the coefficients and not the odds ratios. I believe presenting odds ratios are the accepted standard for logistic regression.Response: We revised the model now, and have presented odds ratio, confidence interval and p-value for each explanatory variable included in the model (Please see table 3).13. The manuscript is lacking a discussion on the list of variables that were included in the multi-level regression analysis at different levels and the proportion of variations in the model explained by variables included at different levels. For example, if within district differences account for most of the variation in the model or is it within states/individuals. A discussion on ICC or Variance Partition Coefficient (VPC) to represent the percentage variance explained by the different levels and it’s policy implications would be useful.Response: We included discussion on ICC and other district level explanatory variables in the revised manuscript. .14. Again, the discussion section is poorly written, and it is not clearly bringing out the significant added value of this study over previous studies. In most places, the authors present their results and then in the next sentence they are saying previous literature showed similar findings. I believe the authors need to discuss their results with supporting literature and possible explanations and greater policy implications.Response: We have revised the discussion section in the light of your comments.15. On line no: 320 it is reported that in many countries, a single mother cannot register their children. Since this manuscript is on India, I believe the authors need to bring out a discussion on India.Response: We have added a few points on marital status and birth registration in the context of India (line no. 391-399). However, we have not found any published study based on India’s dataset that clearly highlights association between marital status and child’s birth registration.16. On line no: 320-321 the authors need to explain what do they mean by different media kinds and how do they construct/define this variable in their regression.Response: We have defined the different forms of media, how we constructed this variable in the material and methods section of the revised manuscript (line no. 165-171).17. On line no: 329, the authors wrote that the cost associated with registration is a barrier to birth registration. I believe they need to discuss this further, which cost – direct/indirect.Response: We have included that both direct  and indirect cost  is barriers to birth registration (line no. 411-415).18. Overall the manuscript needs to be grossly rewritten with a strong literature review and the major issues in the methodology, presentation and mapping and discussion sections need toResponse: We have revised the manuscript on the basis of your suggestions. 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Adolescents face significant barriers to access and utilization of sexual and reproductive health services in many low-income settings, which in turn may be associated with adverse consequences such as early pregnancy, sexually transmitted infections, unsafe abortion and mortality. There is evidence suggesting that limited access to sexual and reproductive health information and services among adolescents contributes to these outcomes. We aimed to find out the factors that affect the fertility of adolescents aged 15 to 19 years in Zambia and to identify possible drivers of adolescents’ fertility.Secondary analysis of the ZDHS 2013/14 data was carried out to find out the factors that affect the fertility rate of adolescents aged 15 to 19 years using multivariate logistic regression (n = 3666).Overall, 23.1% of adolescents had given birth at least once in the 5 years leading to the survey , and 49.8% were rural-based while 50.2% were urban-based. The median number of schooling was 8 years (IQR 6–10). About 52% of the adolescents were in the poorer, poor and medium wealth quintiles while the other 48% were in the rich and richer quintiles. Factors found to affect fertility include residence, wealth status, educational attainment, marriage and abortion. An urban-based adolescent with a lower socioeconomic status was 2.4 times more likely to give birth compared to rural-based poorer adolescents . Although odds of giving birth were much higher among rural-based married adolescents  compared to urban married adolescents , and these relationships both statistically significant, higher educational attainment  and abortion  reduced these odds, particularly for rural-based adolescents.Despite response aimed at reducing adolescent fertility, low wealth status, low educational attainment and early marriage remain significant drivers of adolescent fertility in Zambia. There is a need to address sexual and reproductive health needs of urban-based adolescents with a lower socioeconomic status. Adolescents go through serious challenges related to accessing and using sexual and reproductive health services in many low-income settings, and may also be related to negative consequences such as early pregnancy, sexually transmitted infections and unsafe abortion and death. Research has revealed that limited access to sexual and reproductive health information and services among young people contributes to these negative consequences. This analysis aimed to find out the factors that affect the fertility of 3666 adolescents aged 15 to 19 years in Zambia and to identify possible drivers of adolescents’ fertility, using the Zambia Demographic and Health Survey conducted in 2013/2014. A little over a quarter of the adolescents had given birth at least once in the five years leading to the survey. About half of the young people were rural-basedwhile the other half were urban-based, with an average of about 8 years in school. The rural-based adolescents had slightly lower average years in school compared to the urban-based; 7 years and 9 years respectively. Living in a rural area, residing in a home with a low wealth status and being married were all linked to higher chances of giving birth, while terminating a pregnancy and having more years of education were linked to lower chances of giving birth among the adolescents. Urban-based adolescents with lower wealth status were also linked to higher chances of giving birth compared to urban-based adolescents with higher wealth status. These results suggest that while residing in rural areas and being married increase the chances of higher fertility, the adolescents in urban areas but with lower wealth status also need interventions aimed at reducing their fertility. The Guttmacher–Lancet Commission report on accelerating progress for sexual and reproductive health and rights (SRHR) for all states that “progress in SRHR requires confrontation of the barriers embedded in laws, policies, the economy, and in social norms and values—especially gender inequality—that prevent people from achieving sexual and reproductive health” . GloballEducational attainment has globally been a factor in the definition of socioeconomic status, and it has often been argued that low socioeconomic status is linked to reduced access to quality education and health services. Other Socioeconomic empowerment factors; key in understanding fertility preferences among women include increased skills development, increased decision-making power, and more control over household resources . FertiliFertility rates must be reduced; to address the morbidity and mortality associated with early childbearing. Adolescent sexual and reproductive health-focused interventions have been undertaken , particuWith an overall aim of improving the health status of Zambians, the Reproductive, Maternal, Newborn, Child and Adolescent Health and Nutrition Communication and Advocacy Strategy 2018–2021 aims “to effectively target and serve adolescents and youth with quality accessible sexual and reproductive health information and services in and out of school” . BearingA deeper understanding of the factors affecting adolescent fertility is required to fill up the dearth of information necessary to inform programs and the health care system that aims to meet the sexual and reproductive health needs of this population cohort. This study aimed to explore the determinants of adolescent fertility in Zamia.This study was undertaken in Zambia, a southern Africa country with approximately 13 million people and an annual growth rate of about 2.8. . This anData were collected during the 2013/2014 Zambia Demographic and Health Survey. The survey used a two-stage stratified cluster sample design, clusters selected during the first stage and households selected during the second stage. After dividing Zambia into ten provinces, stratification was done by splitting each province into urban and rural clusters, creating 20 sampling strata. The sampling frame consisted of 25, 631 convenient geographical areas with an average size of 130 households or 600 people. In the first stage, 722 clusters  were selected with probability proportional to size. In the second stage, a complete list of households served as the sampling frame in the selection of households for enumeration. About 25 households were selected in each cluster. During the second stage of selection, a representative sample of 18,052 households was selected.Data on the fertility of female adolescents between 15 and 19 years old were extracted for this sub-study from the 2013/2014 Zambia Demographic and Health Survey. This selection included all female adolescents who were permanent residents of the households or visitors in the households on the night before the survey began. The total number of adolescents 15 to 19 years old included in this analysis was 3, 666, representing 22.5% of the total sample of women 15 to 49.The variable ‘births’ was taken as the dependent variable in this analysis, defined as whether an adolescent had ever given birth or not. This study focused on ‘births’ as a binary variable (0 for no birth and 1 for at least one birth). For the explanatory variables, Bongaarts’ proximate determinants of fertility , as theyOther variables extracted were abstinence as a binary variable (0 for no abstinent and 1 for abstinent girls). In the 2013/14 ZDHS report, abstinence is defined as girls who are not sexually active and have not given birth before. Age was continuous, but was also taken as categorical since the range was narrow, age at first sex, which was considered as count data but later regrouped into the following age ranges of consent for sex; 10–14, 15, 16–19, type of residence , educational attainment was taken as education level  and number of years in school which was regrouped to realign it into the current Zambian education system; no education, lower primary, upper primary, junior secondary, senior secondary and tertiary education). Knowledge of contraception was considered as a binary variable (0 for no knowledge and 1 for knowledge of at least one method), wealth status as a binary variable  and wealth quintiles were considered as categorical  and finally religion was defined as a categorical variable . The total number of covariates was 15.All analyses were conducted using Stata version 13 . Data weDuring the analysis, the weights were taken into account at each stage of the analysis, ensuring nationally representative estimates. Proportions were used to describe the data. To test the association of each of the independent variables and births, univariate standard logistic regression was used to obtain the odds ratios and 95% confidence intervals (CIs). Variables that were correlated, with a correlation coefficient > 0.8 were dropped from the multivariable logistic regression. Variables that predicted failure or success perfectly were not included in the analysis. The final model was arrived at using an investigator-led backward step-wise approach and was tested using the Hosmer–Lemeshow goodness of fit test. However, variables that were relevant according to literature were maintained in the final model.The analysis also controlled for the potential confounders: age, wealth and educational status. Age was adjusted for as a linear effect. Survey data is prone to biases such as missingness and failure to recall events that have already passed. However, incomplete and missing data were found to be low (less than 5%) enough to be inconsequential  and hencIn the ZDHS, All the respondents in the survey provided verbal consent when the data were collected. Authorization to survey in 2013 was granted by the Ministry of Health of Zambia and the Institutional Review Board of ICF International, and the Centers for Disease Control and Prevention (CDC) in Atlanta, USA . For thiOf the total sample size (n = 3666) of the adolescents, and given that 99.4% response was recorded among all women 15 to 49 years old, non-participation was assumed to be in this range because there were almost no losses of significant records based on completeness. Details of participation rates for the 2013/14 ZDHS are published in the report . DistribThe overall median number of schooling was 8 years (IQR 6–10) and significant rural vs. urban differences were observed (7 years [IQR 6–8] vs. 9 years [IQR 7–10] respectively (p < 0.001). Regarding wealth status, 52% of the adolescents were in the poorer, poor and medium wealth quintiles while the other 48% were in the rich and richer quintiles. About 70% of the adolescents who had sex after their first marriage had already given birth at least once.The determinants of adolescent fertility included marriage, knowledge of contraception, contraception use and abortion. About 23.1% of the adolescents had given birth in the last 5 years, and the number of births increased with increase in age. A majority of the adolescents (over 90%) were reported to know of contraception by mentioning at least one contraception method, while contraception use was reported at a low 10%. Over 80% of adolescents were unmarried, while 51% had had sex before. Sixty cases of adolescent girls had terminated a pregnancy (abortion), representing 1.6% of the girls included in this analysis. Abstinence was also low (9.8%) among the adolescents, despite almost half of them reporting that they had never had sex, and 30% reporting that they had not been sexually active. Further investigation revealed that abstinence was captured as post-partum abstinence. Table In the univariate variable selection procedure, age, age at first sex, residence, educational attainment, wealth status, marital status, abortion (termination of pregnancy), contraceptive use and knowledge of contraception all had a statistically significant association with adolescent births outcome. Table Having attained junior secondary education was associated with reduced odds of having given birth, compared to those who had no education . Following adjustment for age and educational attainment, the poor adolescents were 1.7 times more likely to have given birth, compared to the rich adolescents . The odds of having given birth increased with age .Adjusting for age, wealth and educational attainment, the odds of having given birth for adolescents were significantly higher among the adolescents who knew at least one contraceptive method, compared to those that did not know any method . Married adolescents were more likely to have given birth, compared to those who were not married, adjusting for socio-demographic variables  and this relationship was statistically significant. There was also a strong relationship between contraceptive use and giving birth  compared to those who did not use any contraceptive method, adjusting for socio-demographic variables. Abortion (ever terminated a pregnancy) was the only proximate determinant associated with reduced odds of giving birth , adjusting for socio-demographic variables. However, this relationship was not statistically significant.We also present adolescent fertility determinants by rural and urban residence. Table Adjusting for age, wealth and educational attainment, the odds of giving birth for rural adolescents were significantly higher among the adolescents who knew at least one contraceptive method, compared to those that did not know any method . Interestingly, there were no urban adolescents who and given birth and did not know at least one contraceptive method. While married adolescents were more likely to give birth, compared to the unmarried, adjusting for socio-demographic variables, the odds of giving birth were much higher among rural married adolescents  compared to urban married adolescents , and these relationship were both statistically significant.In addition, and adjusting for socio-demographic variables, the odds of giving birth and using at least one contraceptive method were significantly higher among urban adolescents  compared to rural adolescents . Finally, abortion (ever terminated a pregnancy) among rural adolescents was significantly associated with reduced odds of giving birth , adjusting for socio-demographic variables.We report a high proportion of adolescents who had ever given birth (in the last 5 years leading to the survey) than expected and a further look at the observation shows that being in a lower-income household alone was associated with increased chances of giving birth, while higher educational attainment reduced these chances when other factors were adjusted. These findings also consistently show these patterns of association for both rural and urban areas, suggesting a strong link between socio-economic status and fertility in general, and further indicating the presence of differential inequities that may be at play in the study population. Other studies have indicated similar observations among adolescent boys and girls , 28–30.Higher wealth status increased protection against ever giving birth among the adolescents, particularly for those based in urban areas. A study in rural Zambia highlighted that early childbearing was often a source of economic and social security, while schooling was viewed as a deterrent of early child bearing . RemarkaHigher educational attainment was strongly linked to reduced odds of ever giving birth. In addition to reduced fertility, literature also suggests that higher educational attainment is linked to higher wealth status , suggestMarital status was another significant determinant of adolescent fertility in this study; married adolescents were more likely to give birth compared to the unmarried. There is an indication that marriage continues to contribute to early childbearing, especially with 70% of the married adolescents already giving birth at least once. These findings were consistent with evidence from 24 African countries , 36. MarWhile marriage was linked to increased odds of ever giving birth, these odds were also linked to contraception use, indicating that ever giving birth increased access to SRH services for adolescents and the health systems responds more married adolescents and those who had ever given birth compared to those that had not. Also, studies have found that married adolescents are less likely to face stigma for early pregnancy, accessing contraceptives and sexual and reproductive health services due to their marital status . This obThe ZDHS reports indicate that knowledge of contraception is ‘universal', and our observation too was that there was a significant relationship between knowledge of contraception and ever giving birth, especially in rural areas. Paradoxically, it has been noted in other studies that adolescents have inadequate information about conception, contraception and abortion , 42, 43 Zambian health system’s response through postpartum contraception  has beenInterestingly, abortion had a significant relationship with reduced fertility for rural-based adolescents although they were expected to have had limited access to safe abortion services, and this could be an indicator of unsafe abortion among rural adolescents. A study in rural India reported that abortions were the preferred method for fertility control . The finWhile some interventions are on occasion inclusive of the rural-based adolescents from lower-income households, urban-based adolescents from lower-income households also need specific interventions that respond to their unique structural position. Additionally, an increase in age was significantly associated with giving birth, particularly for rural-based adolescents and this was consistent with a study in Ethiopia . This stIn the 2013/2014 ZDHS, the ‘births’ variable has three levels, reporting those who had given birth up to at least 3 times. In this analysis, the variable 'births' was binary to ensure an adequate number of observations for the analysis. This analysis was based on a cross-sectional survey that included questions that were answered retrospectively. As such, causality could not be established, and there was uncertainty on the exact estimates as respondents were asked to recall past events. Besides, some of the data may have been under-reported due to the discomfort of discussing sensitive topics such as abortion among adolescents. This may have led to an underestimation of some variables such as abortion. However, abortion could be evaluated further to see its relationship with adolescent fertility. Despite these limitations, the study results remain valid and are useful for informing policy and practice, as well as a basis for more research on adolescent fertility. The results from this analysis are based on a sample with national representation; therefore, are generalizable to all locations in Zambia.In conclusion, finding that births were higher in lower socioeconomic groups while groups with higher educational attainment were significantly linked to lower chances of giving birth among adolescents suggests a key indicator of the linkage between lower poverty levels and reduced fertility. Also, this suggests that the bulk of past and current programmatic response to the high fertility rates in Zambia may have taken a supermarket approach, missing those most in need and at risk- lowly educated and predominantly poor adolescents, who are also more likely to be married- another significant driver of fertility. The fact that most of these programs may also be concentrated in urban areas may further suggest the presence of systemic supply-driven programmatic inequality thus widening the gap even more. The morality of this is what must be questioned, examined further and curtailed. The inherent problematic nature of the response is evident in that the provision of contraception to young people who have given birth is present, but the adolescents only know about and use contraception when they have already given birth at least once, indicating a delayed response to the fertility control needs of the adolescent.These findings suggest a critical need of policy shift and adjustment to target most-at-risk adolescents, such as urban-based adolescents with a lower socioeconomic status, rural adolescents, as well as repacking contraception awareness programs in mediums that are acceptable and understood by most of the population. Specific policy focus could draw lessons from interventions that have been successful elsewhere-; multi-sectoral strategies for keeping girls in school, rolling out Comprehensive Sexuality Education and an increase in the provision of inclusive youth-friendly SRH services that delay the onset of childbearing adolescents and delays subsequent pregnancies for those who have given birth before. In general, this calls for context-specific programming, informed by context differentials but grounded in messaging and communication that resonates well with the adolescents and the rest of the community members. This innovation is what will help reach out to adolescents in the different socio-cultural contexts also including other population subgroups, thereby providing a specific response to the different and unique groups of adolescents in Zambia- and attaining the Universal Health Coverage goals of leaving no one behind.


Decision-making at the border of viability remains challenging for the expectant parents and the medical team. The preterm infant is dependent on others making the decision that will impact them for a lifetime in hopefully their best interest. Besides survival and survival without neurodevelopmental impairment, other relevant outcome measures, such as the quality of life of former preterm infants and the impact on family life, need to be integrated into prenatal counselling. Recommendations and national guidelines continue to rely on arbitrarily set gestational age limits at which treatment is not recommended, can be considered and it is recommended. These guidelines neglect other individual prognostic outcome factors like antenatal steroids, birth weight and gender. Besides individual factors, centre-specific factors like perinatal treatment intensity and the attitude of healthcare professionals significantly determine the futures of these infants at the border of viability. A more comprehensive approach regarding treatment recommendations and relevant outcome measures is necessary. The prognosis of extremely preterm infants has dramatically improved during recent decades. Still today, the implementations of antenatal steroids and postnatal surfactant therapy are listed as the decisive milestones for this positive development. However, it needs to be acknowledged that plenty of further improvements, including respiratory management, better nutritional support, and nosocomial infection prevention programs, among others, have contributed to the better outcomes of extremely preterm infants. In this context, neonatologists around the world have taken into account not only the survival of preterm infants, but also their long-term health status and the long-term sequelae of all organs affected by premature delivery. In many countries of the industrialised world, guidelines and therapy recommendations refer to what is considered the border of viability when specific recommendations are made whether a preterm infant should be actively treated or not. The border of viability has changed over recent decades, and is continuously shifting towards lower gestational ages. Sweden and Japan are among the countries at the forefront of providing care for the most immature extremely preterm infants ,2. The lCurrently, new treatment options such as artificial wombs are studied in premature lambs . TherefoWhen the treatment outcomes of preterm infants are considered, data are mostly available for survival and survival without neurodevelopmental disability. Generally, survival and survival without NDI has improved for extremely preterm infants over the last two decades, but for those born at 22–23 weeks, this is not universally true. Data from the Neonatal Research Network (USA) from 2000 to 2011 show an improvement of survival and survival without the NDI of infants born at 23–24 weeks, although for the group of infants born at 22 weeks, there was no improvement, and survival was only 2–5%; for infants at 23 weeks’ gestation, survival without neurodevelopmental impairment (NDI) increased from 7% to 13% .Improvements in survival could also be achieved in those infants born at 22–23 weeks of gestation in Sweden. The one-year survival of all live born infants significantly increased from 10% to 30% for those born at 22 weeks of gestation, and from 52% to 61% for those born at 23 weeks of gestation, although not statistically significant . OverallImprovements in survival and in survival free of major disabilities of extremely preterm infants have led to an adjustment in national guidelines in some countries, for example, in the Dutch guidelines, the threshold for active treatment was lowered from 26 + 0/7 to 25 + 0/7 in 2006 .Most national guidelines for the treatment of preterm infants at the border of viability focus on gestational age limits, where treatment should be provided, should not be provided, and can be provided. In the “grey zone” area where treatment can be provided, it is a joint decision of the parents together with the medical team ,7. The pOther factors beyond gestational age impact the prognosis, including baseline factors, such as antenatal steroids ,19, gendThe application of antenatal steroids is known to improve preterm outcomes. In a recent European cohort study of the EPICE  network antenatal steroids given even shortly before preterm birth reduced the risk of death or severe brain damage . For anthttps://www.nichd.nih.gov/research/supported/EPBO/use; accessed on 21 February 2022), while one shortcoming is that only weeks and not days can be entered, and the variation in outcome between “early” versus “late” 23 weeks has been described [Other individual factors, such as female sex, increased birth weight and singleton birth, were associated with reductions in risk of death and neurodevelopmental impairment. . Therefoescribed .Gestational age determined by last menstrual period or ultrasound is known to be imprecise. Dating by last menstrual period, which is common in many parts of the world if ultrasound is not available, is prone to imprecision, as the accurate recollection of this date cannot be assumed. A first trimester ultrasound provides an estimate of gestational age, but errors of up to 7 days have been described ,27,28.Based on the scientific data, it needs to be acknowledged that the borders of viability are set arbitrarily and cannot reflect the gradual increases in outcome prognosis, as survival and disability-free survival increase steadily with increasing gestational age . This seAlthough gestational age does influence these relevant outcome measures and of course has to be considered when treatment options are discussed, the variability of survival and disability free survival is considerable. Survival rates of preterm infants before 28 weeks vary between 0%  and 70% Birth weight , neonataBronchopulmonary dysplasia (BPD), retinopathy of prematurity (ROP) and serious brain injury  are neonatal morbidities with a significant negative influence on the neurodevelopmental outcome of preterm infants. Each additional morbidity aggravates the odds of poor outcome. For very low birthweight infants surviving without any morbidity, the probability of a poor outcome at 5 years of age was only 11% . In seveObviously, over the lifetime of a former preterm infant, more outcome measures than survival and survival without NDI are relevant. Therefore, several birth cohorts have been followed into later childhood, adolescence, and adulthood. Overall, academic achievement for preterm infants is lower than for their term counterparts . In a poIn most studies, social functioning is assessed with indicators, such as educational attainment, income level, being employed or being in a romantic relationship. With this approach, former preterm infants often have lower levels of social functioning ,41. How One of the challenges in predicting longer-term outcome is that current preterm infants in adulthood received a very different neonatal care, as medical treatment has greatly advanced during the last 10–20 years; therefore, outcome is possibly even better. On the other hand, preterm infants today are treated at much lower gestational ages than several years ago, with unknown longer-term consequences. Currently, no cohort data on QoL in adolescence of those born at 22–23 weeks of gestation exist. Being aware of these uncertainties during counselling and decision-making and interpreting data cautiously is important .The outcome for the individual preterm infant has to be at the centre of the decision regarding treatment at the border of viability. However, the family as a whole will greatly be affected, and therefore also needs to be considered. Some parents worry about the possible burden that the preterm infant will place on their marriage and family life. Maternal depression scores are higher in mothers of preterm infants compared to those of term infants postnatally, whereas at three months, this difference disappears . The impParental education and socioeconomic status have been described as risk factors for the poorer neurodevelopmental outcome of preterm infants. In a recent study, parental educational level did not modify the relationship between gestational age and educational attainment in adulthood, although across all gestational age groups up to term age, lower parental education level was associated with lower educational attainment at 25 years .The International Network for Evaluating Outcomes of Neonates (iNeo) compared outcome data of 10 national and regional neonatal networks of infants born at 24–29 weeks of gestational age. Overall survival rates varied from 78% to 87%, with the greatest difference for infants born at the lower gestational ages. The difference at 24 weeks’ gestation was 35% versus 84% survival, and followed an identical pattern for those born at 25–29 weeks of gestation, but with less pronounced differences . BesidesSeveral studies have shown that more active perinatal support leads to increased survival rates ,30,51. CThe relative value of a preterm life is often viewed as less than that of older children. In a questionnaire-based study, physicians and university students were investigated regarding the likelihood of resuscitation of different patients with the same outcome regarding survival and survival with or without neurological impairment. The just-delivered 24-week preterm infant was the least likely to be resuscitated, although the chance of survival and survival without disability was the same as that of a 2-month-old with meningitis, a baby just born with a known malformation, and a 50-year-old in a car accident . AttitudIt becomes evident from our review and the available extensive scientific data on the topic that, more than gestational age, survival and survival without NDI need to be considered for decision-making at the border of viability.Clearly, the outcome has changed over the last decade, especially among those born at 22–24 weeks of gestation, leading to the adaptation of guidelines in several countries . HoweverIf the decision for treatment has been taken, it is important to actively manage the perinatal period, as this yields the best results. Redirection of care should always be an option if severe complications occur, medical treatment becomes futile , and theSurvival without neurodevelopmental impairment does not equal a good quality of life. Moreover, although preterm infants cannot be asked at the beginning of their life whether they wish for treatment or not, we can consider the judgement of those who were preterm 10–20 years ago regarding outcomes like quality of life in adolescence and adulthood. Obviously, shorter-term outcomes  can be assessed timelier, and will remain important prognostic factors, but they need to be interpreted cautiously and in light of a whole lifetime. Possibly the most important influenceable factor is the attitude of each individual caring for these most vulnerable patients and their families. If the care for these infants is done with utmost perinatal intensity and with a positive attitude, outcomes of preterm infants at the border of viability will continue to improve, regardless of where the border is seen within the physiologic limits of nature.


BACKGROUND: The relationships between birth weight and serum lipid concentrations in premenopausal Japanese women were not well identified and also diet and serum hormone status in these women would be considered.METHODS: A total of 59 premenopausal Japanese women completed a self-administered questionnaire including basic demographic information, disease histories, and menstrual and reproductive histories. They were asked to obtain information on birth weight recorded in mother-and-baby notebook issued by municipality from their mother. Diet was assessed by daily diet records from day 2 through day 10 of the menstrual cycle. Blood sample was collected on day 11 of the cycle to measure serum lipid and hormone concentrations .RESULTS: Birth weight was significantly correlated with HDL cholesterol , but no with total cholesterol and triglyceride after controlling for age. Neither estrogen nor sex hormone-binding globulin was significantly correlated with serum lipid concentrations after controlling for age and the number of days prior to the next menses. The correlation between birth weight and HDL cholesterol was not affected after additional adjustment for serum estrogen and intakes of protein, calcium, and iron.CONCLUSION: These data suggest that intrauterine growth may be associated with lipid profile. The studies suggested that cardiovascular disease originates impaired development in utero. However, these findings have remained to be poorly understood. Serum lipid concentrations are regarded as well-established predictors of the development of cardiovascular disease.3 It is worth studying relationship between birth weight and serum lipid profile. Few studies have evaluated this association. We examined this association in premenopausal women aged 20-46 years using baseline data from participants in a dietary soymilk-supplementation study. Collection of serum sex hormone levels in the intervention study enabled us to consider their possible confounding effects on the relationship among birth weight and serum lipid concentrations.The association between low birth weight and high death rate from cardiovascular disease was reported in two previous studies for men and women,4 After excluding one woman who did not provided information on birth weight, 59 women were studied in the present study. None of the women had a history of cancer, endogenous diseases, chronic liver diseases, and cardiovascular diseases. They were not also taking hormonal medications. The details of the subjects were described in the other report.4 The study was approved by the local review board, and each woman provided a written informed consent.Study subjects consisted of 59 premenopausal women who participated in dietary-soymilk-intervention study. A total of 72 female students and teachers at a course given at a nurses’ training school were invited to the intervention study in 1997. Of these, 60 women participated in the study.The subjects responded to a self-administered questionnaire providing basic demographic information, disease history, and menstrual and reproductive histories. In Japan, birth weight is recorded in mother-and-baby notebook issued by municipalities by law. The women were asked to obtain this information from their mothers who must keep the notebooks.5Exercise was assessed by asking the average hours per week spent performing various kinds of activities during the previous year. The details including its validity are described elsewhere.th revised edition). Fatty acid composition was based on data published by Sasaki et al.6 The onset date of the following menstruation was reported by the subjects.A fasting blood sample was collected on the morning of the day 11 of the menstrual cycle. The first day of the menstrual bleeding was defined as the day 1. Diet was assessed by a series of daily diet records from the day 2 through the day 10 of the cycle before the initiation of dietary intervention. Intake of macro- and micro-nutrients was estimated from the diet records using the Standard Table of Food Composition in Japan , and triglyceride (TG), was determined by enzymatic assay using an Auto Analyzer . The reagent used was L-type Wako cholesterol purchased from Wako Junyaku, Osaka, Japan. HDL cholesterol was precipitated with heparin and calcium. Serum concentrations of estrone, estradiol, and sex hormone-binding globulin were determimed by radioimmunoassay using kits purchased from Eiken Chemical Co. Ltd.,(Tokyo), Diagnostic Products Corporation, Japan (Chiba), and Pharmacia & Upjohn Co., Ltd.,(Tokyo), respectively. The intra-assay coefficients of variation were 1.14% for total cholesterol, 1.36% for HDL cholesterol, 1.13% for TG, 7.4% for estrone, 2.5% for estradiol, and 7.8% for sex hormone-binding globulin.We used Spearman correlation coefficients to evaluate the relations between birth weight and serum hormone levels to serum lipid concentrations. Partial correlations were calculated after controlling for potential confounders. By including the following variables in the models, we examined the potential confounding effects of age, body mass index (BMI), smoking status, status of student/teacher, parity, exercise habits, age at menarche, birth order, mother’s age at birth, and intake of alcohol and macro- and micronutrients. Some blood samples could not be collected on the day 11 of the cycle because of school holidays. Actual sampling dates ranged from the day 9 through the day 13 of the cycle. Even the samples were obtained at the same day according to the menstrual cycle, length of menstrual cycle varies among the subjects and this should affect estrogen concentrations. Therefore, to evaluate the relationships between serum estrogen and lipid concentrations, the number of days prior to the next menses was used for adjustment as covariates after categorizing it into <19, 19-23, and 24+ days.Descriptive characteristics and means for lipid and hormone levels are presented in Neither estrogen nor sex hormone-binding globulin was significantly correlated with serum lipid concentration after controlling for age and the number of days prior to the next menses . Among t7 but was unrelated to HDL cholesterol in men studied by Byberg et al.8 Birth weight was inversely associated with TG in boys and girls aged 7-11 years, although there was no significant association between birth weight and HDL cholesterol.9Birth weight was positively associated with HDL cholesterol in postmenopausal women from the Rancho Bernardo Study,7 in which the elevated HDL cholesterol was associated with high birth weight in postmenopausal women. This consistency suggests that sex hormone profile should not show substantial interrelations between birth weight and HDL cholesterol. We found that there was no significant confounding effect of serum estrogen and sex hormone-binding globulin on the association between birth weight and HDL cholesterol in premenopausal women. We speculate that maternal nutritional status can partially explain the link between birth weight and future lipid profile. Nutritional status during developmentally sensitive periods may cause the alternation of metabolism.Our finding of a positive correlation between birth weight and HDL cholesterol in premenopausal women is consistent with the result from the Rancho Bernado Study,10 reported that HDL cholesterol is related to three domains in premenopausal women: body measurements, sex hormone status, and carbohydrate metabolism. We could not include measurements of insulin resistance or glucose levels. We cannot deny a possibility that the association of low birth weight with low HDL cholesterol may be mediated by impaired carbohydrate metabolism.In the present study, we examined potential confounding effects of several variables including sex hormones, demographic factors, diet, smoking, and exercise. Sowers et al.Lipid concentrations were determined by a single measurement and this may have distorted the relationship between birth weight and HDL cholesterol. When we reanalyzed an association between birth weight and HDL cholesterol after 2 months of soymilk supplementation, this association was still significant  after controlling for age and group status. However, blood was drawn again on the day 11 of the menstrual cycle. As lipoprotein concentrations have been reported to fluctuate by phase of the menstrual cycle, it had been desirable that lipoprotein concentrations were measured repeatedly at different points in time. Lack of significant positive association between BMI and TG in our study may be due to the inclusion of few obese women (at most 25.6 of BMI). However, we cannot deny a possibility of effects due to the measurement error. Cyclic fluctuations in food intake occur in women across the menstrual cycle, with a periovulatory nadir and peak in the luteal phase. Diet record kept from the day 2 through the day 10, may have not been sensitive enough to reflect the interindividual variation in diet.