Several studies have shown that unskilled birth attendance is associated with maternal and neonatal morbidity, disability, and death in sub-Saharan Africa (SSA). However, little evidence exists on prevailing geospatial variations and the factors underscoring the patterns of unskilled birth attendance in the region. This study analysed the geospatial disparities and factors associated with unskilled birth attendance in SSA.The study is based on data from thirty (30) SSA countries captured in the latest (2010–2019) demographic and health surveys (DHS). A total of 200,736 women aged between 15–49 years were included in the study. Geospatial methods including spatial autocorrelation and hot spot analysis as well as logistic regression models were used to analyse the data.There were random spatial variations in unskilled birth attendance in SSA, with the main hotspot located in Chad, whereas South Africa and the Democratic Republic of Congo showed coldspots. Residence , wealth status, education, maternal age at the time of the survey and age at birth, desire for birth, occupation, media exposure, distance to a health facility, antenatal care visits, and deaths of under-five children showed significant associations with unskilled birth attendance.Random geospatial disparities in unskilled birth attendance exist in SSA, coupled with various associated socio-demographic determinants. Specific geospatial hotspots of unskilled birth attendance in SSA can be targeted for specialised interventions to alleviate the prevailing disparities. Historically, traditional or unskilled birth attendants defined as “persons who assist a mother during childbirth and who initially acquired their skills by delivering babies themselves or through apprenticeship to other traditional birth attendants” , have beEmploying the services of unskilled birth attendants in the management of pregnancy and child delivery is known to be associated with a high risk of maternal and neonatal morbidity, disability, and even death . UnskillGiven the assumption that many women in SSA continue to utilise the services of unskilled birth attendants rather than professional or skilled birth attendants, it is important to understand the factors accounting for these utilisations. Understanding these factors is essential for developing context-specific interventions tailored toward more specific population characteristics which in turn can inform efforts to reduce maternal deaths. However, to date, no empirical study, to the best of our knowledge, has examined the geospatial distribution and factors associated with the utilisation of maternal and neonatal services from unskilled birth attendants in the whole of SSA. Also, there are limited studies that have explored the spatial distribution of the utilisation of unskilled birth services in SSA. The available studies on unskilled birth attendants were mostly focused on only single countries in Africa, e.g., Olakunde, Adeyinka (5) for Nigeria, or explored perceptions of women about unskilled birth attendants from a qualitative perspective, e.g.,- Gurara, Muyldermans 7) for Ethiopia, and Selepe and Thomas (8) for South Africa  for Ethi.Previous studies focused on skilled birth attendance among women in SSA have suggested that availability of a healthcare facility, distance between home and the healthcare facility, socio-economic status of pregnant women, place of residence, birth parity, ethnicity, previous contact with a healthcare system, and levels of education are associated with the use of services from skilled birth attendants during pregnancy and delivery , 13–16. The study analysed data from a pool of the latest demographic and health surveys (DHS) of thirty (30) countries in sub-Saharan Africa (SSA), conducted between 2010 and 2019. The surveys comprised nationally representative samples of women in their reproductive age groups (15–49 years), and the participants were selected based on a two-stage stratified cluster sampling procedure. The DHS generates reliable data on fertility, family planning, infant and child mortality, maternal and child health, among others, and was therefore deemed suitable for this study. Both standard and continuous DHS data were obtained for countries such as Angola, Burkina Faso, Burundi, Cameroon, Chad, Comoros, Congo, Cote D’Ivoire, Democratic Republic of Congo, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Malawi, Mali, Mozambique, Namibia, Nigeria, Rwanda, Sierra Leone, South Africa, Tanzania, Togo, Uganda, Zambia, and Zimbabwe. The unit of analysis comprised 200,736 women aged from 15 to 49 years selected from various households in these countries. The sample was limited to the last births of women within the five years preceding the surveys.The outcome of interest was unskilled birth attendance. This was based on the person who assisted during the delivery of the last child. This comprised multiple categories of persons such as a doctor, nurse/midwife, community health officer/nurse, traditional birth attendant, traditional health volunteer, community/village health volunteer, relatives, and others. In this study, we created a binary outcome where deliveries assisted by traditional birth attendants, traditional health volunteers, community/village health volunteers, relatives, and others were measured as unskilled birth attendance while all others were considered skilled birth attendance , 17.Additionally, various explanatory variables, of which most have been established by previous studies relating to the study outcome –19, wereWe initially estimated the proportion of unskilled birth attendance by country and the socio-demographic characteristics of the respondents. We conducted a bivariate analysis of each explanatory variable and the outcome variable. All explanatory variables that had significant associations with the outcome variable were added to the multivariate model. Next, a multivariate analysis was performed using a logistic regression model to estimate associations between unskilled birth attendance and all the explanatory variables . A multicollinearity test was performed for each variable which showed a mean-variance inflation factor (VIF) of 2.01 for the variables in the models. Unadjusted (Model 1) and adjusted odds ratios (Model 2) were then calculated for each variable at a 95% confidence interval. Stata (Version 14) was used to process and analyse the data. The results were sample-weighted to address any over-sampling and under-sampling in the total sample.Regarding the geospatial analysis, the proportions data on unskilled birth attendance were merged with the shapefiles for each country using ArcMap version 10.5. Spatial autocorrelation  tool was used to explore the distribution of unskilled birth attendance in SSA after a hypothesis was set:1: the distribution of unskilled birth attendance in SSA is not randomHThis spatial autocorrelation  tool was used to assess whether the distribution of unskilled birth attendance in SSA is random, clustered, or dispersed across the selected countries. The results to determine the type of distribution is dependent on the Moran’s I index and the z-score or p-value. A positive and negative Moran’s I index value implies a likelihood of clustering and dispersion respectively. The z-score or p-value indicates statistical significance, and the null hypothesis is accepted if the z-score is -1.65–1.65 and if the p-value is not statistically significant. In addition, a hotspot analysis (Getis-Ord G) was conducted to identify areas with relatively higher (hotspot) and lower (coldspot) occurrence of unskilled birth attendance among the selected countries based on z-score and p-value. A higher z-score and a lower p-value show a higher probability of a phenomenon occurring at a place. The Anselin Local Moran’s I cluster, and outlier analysis were also conducted to ascertain statistically significant spatial outliers. This output showed outliers in the distribution using permutations such as high-high, low-low, high-low, low-high, and not significant.Of the 200,736 women included in the study, the majority (8%) were from Burundi and the minority (1%) were from Lesotho. Chad had the highest proportion (69%) of women who utilised the services of unskilled birth attendants whereas the least proportion (3%) were from South Africa. Overall, about one in four women (27%) in SSA utilised the services of an unskilled birth attendant during pregnancy or delivery .Over 40 percent of respondents without education, from the poorest households, and those who had less than four antenatal visits utilised the services of an unskilled birth attendant. More than one-third of respondents without media exposure (36.7%), with four or more children (34.3%), with permission (35.7%), and who were distanced from a health facility (36.5%) utilised services from an unskilled birth attendant. Additionally, about one-third of rural residents utilised the services of unskilled birth attendants .The findings showed that place of residence, wealth status, age, level of education, marital status, occupation, age at first birth, birth order, mass media exposure, permission, getting the money needed for care, distance to a health facility, desire for birth, antenatal care visits, experience of death of an under-five child, and country of residence had a significant relationship with unskilled birth attendance .A higher likelihood of utilising the services of unskilled birth attendants was observed among rural women  compared to urban women. Those with the poorest wealth status were more likely  to utilise the services of unskilled birth attendants compared to those with the richest wealth status. Women who had desired to have children later  and those who had a big problem getting money needed for care  had a higher likelihood of utilising the services of unskilled birth attendants compared to those who desired to have children then and those who did not have a big problem getting money needed for care .Our findings also showed that teenagers (less than 20 years) had a higher likelihood  of utilising the services of unskilled birth attendants during delivery compared to women aged 20–29 years. Women who had their first birth at age 30–49 years  were less likely to utilise the services of unskilled birth attendants compared to those who had their first birth when they were less than 20 years of age. Women with no formal education had higher odds  of utilising the services of unskilled birth attendants during delivery compared with those with primary education. Women who were not exposed to mass media had a higher likelihood  of utilising the services of unskilled birth attendants during delivery compared to those who were exposed to mass media .Furthermore, the women who saw distance to a healthcare facility as a big problem had a higher likelihood  of utilising the services of unskilled birth attendants during delivery compared to women who stated that distance to healthcare facilities was not a big problem. Women who had less than 4 antenatal care visits had higher odds  of utilising the services of unskilled birth attendants during delivery compared to women who had 4 or more antenatal care visits. Women who had experienced the demise of their under-five child were more likely  to utilise the services of unskilled birth attendants during delivery compared to those who had not experienced the death of their under-five child .Results from the spatial autocorrelation analysis  revealedAlthough the occurrence of unskilled birth attendance was found to be random, the Hotspot Analysis  showed tResults from the cluster and outlier analysis  showed nThis study examined levels of unskilled birth attendance among women in sub-Saharan Africa (SSA) and the factors associated with the utilisation of such services. The study further examined hot and cold spot countries in SSA where women utilised pregnancy and child delivery services from unskilled birth attendants. Consistent with a previous study , we founFindings that women with the poorest wealth status as well as those who had a big problem getting money needed for care were more likely to utilise the services of unskilled birth attendants compared to those with the richest wealth status, as well as those who had no big problem getting money needed for care, demonstrate the important role played by financial capital in promoting the use of skilled birth attendants in SSA. In line with findings in a survey involving 80 low and middle-income countries across the world , our finThe findings further showed that teenage pregnancy (pregnancy among women below 20 years old) is a risk factor for the utilisation of services from unskilled birth attendants and this confirms a similar study indicating that early age at first childbirth is associated with low-skilled assistance during delivery . MultiplMoreover, we found that women with low levels of education as well as those who were less exposed to media messages were more likely to utilise the services of unskilled birth attendants compared to highly educated women and those exposed to mass media. A possible reason for these findings is that educated women are likely to be more knowledgeable about the risks associated with utilising services of unskilled birth attendants and the mass media, particularly, the print media, is an important source of maternal health information for educated women compared with women who are less educated . AdditioConcerning the issue of distance and clinical attendance, the findings showed that women who saw distance to a healthcare facility as a big problem as well as those who had less than 4 antenatal care visits had a higher likelihood of utilising the services of unskilled birth attendants during delivery compared to women who stated that distance to healthcare facilities was not a big problem as well as those who had more than 4 antenatal care visits. These findings are consistent with previous country-specific studies in SSA , 31–33. Our findings indicate that women who had ever experienced the demise of their under-five children and those who had desired to have children later were likely to utilise services from unskilled birth attendants. These results are quite difficult to explain due to a lack of adequate published papers on these specific variables. Nevertheless, the findings may imply that many women who had lost their under-five children in previous deliveries as well as those who were not desiring an immediate child had no alternatives to services from unskilled birth attendants due to some preceding factors highlighted in this study, such as long distance to healthcare facilities, low-income status, poor maternal education, among others.Overall, the findings indicate the need to amplify education for women in SSA on the benefits of seeking professional care and suggest a call for improvements in the psychosocial interactions between healthcare professionals and women in SSA. They also show a reflection of outcomes from previous studies focused on skilled birth attendance among women in SSA , 13–16. The outcomes from our geospatial analysis further suggest significant spatial variations in unskilled birth attendance among women in the thirty (30) SSA countries, but those variations did not occur by chance. This means that although the use of services from unskilled birth attendants during pregnancy and delivery in SSA is a holistic problem, the situation varies by country of residence. Notably, with an outstanding level of unskilled birth attendance (69%), Chad can be classified as a hotspot and a high-risk country for unskilled birth attendance compared to its neighbouring countries. A possible reason is that the country has a relatively high incidence of unskilled birth attendance compared to its neighbouring countries. On the other hand, South Africa (3%) can also be classified as a coldspot country where women predominantly seek maternal health care from skilled birth attendants. The findings indicate that even though the geospatial distributions of unskilled birth attendance were random, there appeared to be some notable geospatial variations in unskilled birth attendance among women in some parts of SSA ranging from hotspots to coldspots as observed by . The govThis study is characterised by a few strengths. The geospatial aspect of the analysis provided a novel and deeper insight into the context of unskilled birth attendance in sub-Saharan Africa (SSA). To the best of our knowledge, this is also the first study on unskilled birth attendance that has employed nationally representative samples drawn from thirty (30) SSA countries. We used a large dataset comprising 200,736 women aged between 15–49 years which increased the statistical power of our analysis. Nevertheless, the study is constrained by some shortcomings. First, it is worth noting that many of the surveys were collected in different periods which may impact the findings due to possible changes in outcomes over time as many sub-Saharan African countries do not collect their DHS data in the same year and at the same period. Second, some sub-Saharan African countries were excluded from the study because they lacked data on the outcome variable. Third, the outcome was self-reported and there is a possibility of social desirability and recall bias in the responses as women from cultural orientations where utilisation of unskilled birth services is stigmatised may provide favourable responses to conform to the ethos of their cultural orientations. Lastly, contextual factors such as cultural norms and attitudes of health service providers would have been interesting to examine in this study, but such variables were not captured in the DHS dataset.The multiple factors associated with unskilled birth attendance among the women in this study imply that there is a need for multi-faceted and local-specific policies and programmes in addressing the problem of unskilled birth attendance in SSA. Thus, a “one size fits all” approach may not be efficient in addressing unskilled birth attendance among women in the region. Some possibly useful strategies may include the provision of routine localised or rural health education for pregnant women about the importance of utilising the services of skilled birth attendants. Governments in SSA need to also make it a priority to extend healthcare facilities to rural areas to bridge the distance gap and improve the accessibility of skilled birth services for pregnant women in disadvantaged settings.It is also important to recognise that although there is a general advocate for skilled birth attendance, there are some situations where service use from unskilled birth attendants may be non-negotiable. For instance, access to healthcare can be challenging in many conflict-affected countries or areas in protracted armed conflicts where healthcare workers have vacated their posts due to fear of persecution . Some reThis study has confirmed that many women in sub-Saharan Africa (SSA) continue to utilise the services of unskilled birth attendants during pregnancy and delivery. The study also concludes that women in rural areas, with low income, aged below 20 years, with no or low levels of education, less exposed to mass media information, distanced away from healthcare facilities, and with low levels of antennal attendance  are likely to utilise the services of unskilled birth attendants. These findings suggest that multiple interventions focused on these contextual factors are needed in SSA. We propose an integrated approach where skilled birth attendants are prioritised, but in situations where there are shortages of skilled birth attendants, unskilled birth attendants can be trained, licensed, and monitored to save the lives of pregnant women. Extending maternal education and healthcare facilities or centres to rural areas should be a priority for managers of healthcare systems in SSA. Intensifying education for pregnant women about the importance of using skilled or professional healthcare during pregnancy, delivery, and post-delivery periods is also needed. Future studies can enhance a deeper understanding of these results by exploring our findings from qualitative perspectives. 5 Jul 2022 <div> PONE-D-21-36273 </div>  <div> Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveys </div>  <div> PLOS ONEDear Dr. Dickson,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. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.plosone@plos.org. 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There are some major and minor issues that should be considered.Abstract: please consider to limit the abstract to 250 words. Background section is longer than other parts. The result section of abstract is not supported by Effect size. Please revise this section.Method :Please indicate confounders that the model was adjusted for.Line 153-154: both lines are not essential. H1 is enough if authors insist in mentioning it in this section.Result:Line 171: It is not common to start the results with tables at first. It is suggested to revise this line.Line 192-193: same as above.Line 199-206: It is suggested to re-analysis the variables (making variables reverse) to have risk factor instead of preventive factor for better interpretation and understanding of readers.Please indicate the confounders which were adjusted in this model.Line236: unlike other analysis , authors selected 90% confidence interval for this analysis. 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If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, AttachmentPONE-D-21-36273 #Comments and suggestions.docxSubmitted filename: Click here for additional data file.AttachmentPONE-D-21-36273.pdfSubmitted filename: Click here for additional data file. 12 Sep 2022PONE-D-21-36273Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveysPLOS ONEDear Prof. Tsegaye Lolaso Lenjebo,We are grateful to you and the reviewers for your comments on our paper entitled " Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveys". We would also take this opportunity to thank the reviewers for finding merit in this paper and suggesting that it can be suitable for publication in your renowned journal if we incorporate some major revisions. We have taken notice of all the comments raised by the reviewers and have responded accordingly as follows. Please be informed that the reviewers' comments are in black texts whereas our responses are in red texts. Responses to the Editor’s Comments3. Please include a separate caption for each figure in your manuscript.Response: Thank you. We have included a separate caption for each figure as recommended.4. Please include your tables as part of your main manuscript and remove the individual files. Please note that supplementary tables (should remain/ be uploaded) as separate "supporting information" files.Response: Thank you. We have included the tables as part of the main manuscript and removed the individual files as recommendedhttp://journals.plos.org/plosone/s/licenses-and-copyright.5. We note that Figures 2 &3 in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software . For more information, see our copyright guidelines: We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission: a. You may seek permission from the original copyright holder of Figures 2 & 3 to publish the content specifically under the CC BY 4.0 license. http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:We recommend that you contact the original copyright holder with the Content Permission Form (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0  remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.The following resources for replacing copyrighted map figures may be helpful:http://viewer.nationalmap.gov/viewer/USGS National Map Viewer (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/The Gateway to Astronaut Photography of Earth (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.htmlMaps at the CIA (public domain): http://earthobservatory.nasa.gov/NASA Earth Observatory (public domain): http://landsat.visibleearth.nasa.gov/Landsat: http://eros.usgs.gov/#USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://www.naturalearthdata.com/Natural Earth (public domain): Response: We can confirm that Figures 1-3 were created or constructed by the authors based on the study data using ArcMap version 10.5. Permission from a copyright holder is not applicable in this context. We have, therefore, provided a source in the manuscript showing that the Figures were self-created by the authors.Responses to the Reviewers' comments:Reviewer #1: The manuscript entitled “Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveys” was reviewed carefully. There are some major and minor issues that should be considered.Response: Thank you. We have addressed the concerns as follows.Abstract: please consider to limit the abstract to 250 words. Background section is longer than other parts.Response: Thank you. We have reduced the abstract to 227 words and have cut down the background section as recommended.The result section of abstract is not supported by Effect size. Please revise this section.Response: Thank you. This section has been revised.Method :Please indicate confounders that the model was adjusted for.Response: Thank you. The section under the analytical procedure has been revised as recommended.Line 153-154: both lines are not essential. H1 is enough if authors insist in mentioning it in this section.ResponseThank you for the comment. H0 has been deleted accordingly.Result:Line 171: It is not common to start the results with tables at first. It is suggested to revise this line.ResponseThe entire sentence has been deleted. Thank you for your observation Line 192-193: same as above.ResponseThe entire sentence has been deleted. Thank you for your observation Line 192-193: same as above.Response The entire sentence has been deleted. Thank you for your observationLine 199-206: It is suggested to re-analysis the variables (making variables reverse) to have risk factor instead of preventive factor for better interpretation and understanding of readers.Response: Thank you. This section has been re-analysed and revised as suggested. Please indicate the confounders which were adjusted in this model.Response Thank you. This has been added. Please see the “Analytical procedure” section under the Methods.Line 236: unlike other analysis, authors selected 90% confidence interval for this analysis. Please give some reasons for this discrepancy.Response: Thank you for this observation. The tool used for running the Getis Ord G spatial analysis generates a seven-level categorised output based on confidence level. These seven-level categorised outputs are segmented into three, coldspot , random and hotspot . Our output automatically revealed that the distribution of unskilled birth attendance is spatially and significantly clustered at 90% confidence level. Unlike the other models where we had the liberty to select 95% confidence interval levels, we did not have control over the confidence interval for the geospatial analysis as the software automatically selected the 90% confidence interval based on the level of significance within the spatial distribution clusters. Tables:Please indicate percentage with 95% CI.Response: Please be informed that the Footnotes in Table 3 show the meaning of the * in the table. Thus, *p<0.05 equals 95% CIDiscussion:Line 2: 254-262 : the structure of scientific writing is not suitable for this part and is much more related to introduction. Please consider that the first paragraph of discussion should answer the research question of the introduction based on the eye-catching results of this study. Please revise.Response Thank you. The structure has been revised as recommendedThe main key home massage of this study which makes this distinguish from other local mentioned published articles that authors had mentioned in introduction is not crystal clear in this manuscript. Please discuss it with more prominent evidence.Response Thank you. The Discussion section of the manuscript has been revised to show the key variables and the take-home message. Reviewer #2: I found the paper good. The finding is supported by the analysis technique. It covers large geographical areas and it generates valuable information for public health authorities in the study areas. Response: Thank you for this positive feedback.There are some grammatical errors and editorial issues that are highlighted yellow in the document.Response: Thank you for the highlights. The issues have been resolved.However, there is similar topic done in Ghana by similar authors and I have raised a question regarding this issue in my comments and suggestions that I will attach to you.Response: Thank you. We have explained this in the main comment. Comments and suggestionsLine-38: “older current age and age at birth”• The association direction for age at birth is not specified.• Does the word “older” applies for both or not? If it applies for both then better if you write separately as older current age, older age at birth …Response Thank you for the observation. The results section of the abstract has been revised.Line 38 and 39:• The two variables; rich wealth status Vs not having money problems for healthcare• Both are complementary to each other. So, I recommend to select and use one. Wealth status is better.• Response Thank you for the observation. The results section of the abstract has been revised.Line 43:• Why Burundi?• Lowest proportion is from South Africa (SA) • Then what is the implication behind the result? All counties have higher odds? Response: Thank you. The analysis has been redone and South Africa has been made the reference category. The section has been revised.Line 78-79:• Add something about the spatial pattern of the issue in addition to what you stated.Response: Thank you. An additional sentence has been included to show that there are limited studies utilising spatial analysis to explore the distribution of unskilled birth attendance in SSA.Line 93:• The word “Explored” is not the appropriate action verb for such type of quantitative analysis. Better to use “identified” or “examined” …Response: Thank you for this observation. The word “explored” has been replaced with “examined”Line 95: • The same comment as line 93 (Exploring???)Response. Thank you. The word “Exploring” has been replaced with “Examining”• Line 101: • Could it be different for countries? If it the year is different how you handle the analysis? How do you control the effect of time? So, it is good if you make DHS data sets which are produced in the same year across different countries. Otherwise, the result is biased due to time effect or make it time series analysis?• Response: Thank you for this important observation. We agree with the reviewer that the differences in survey years may affect the results due to possible effect of time. However, DHS data for sub-Saharan African countries are commonly collected in different years and at different periods. This has been a notable limitation of most studies using pooled DHS data of various countries. As a result, we have added this as one of the limitations of the study. Line 180-187:• The description is not as such important as far as these variables are included in the regression model. The proportion (percentage) here is crude and it doesn’t add any value. So, delete it and try to include all variables into the model and report their adjusted effect on the outcome. Response: Thank you for this comment. While we appreciate the reviewer’s suggestion, in this instance, we plead to disagree. The description of participants is commonly provided in this type of public health research to give readers information on the number of respondents in each variable category. It also sets the basis for interpreting the results  and helps in identifying possible limitations induced by small samples in the variable categories. Line 194:• Make is showed i.e.) add “ed”Response: This has been rectified. Thank youLine 202: • Delete (Table 3).; as it is reported at the end of the paragraph.Response The expression “Table 3” has been deleted in the line as suggested. Thank you.Line 213: • Delete the word “see” as it is not important (be consistent).Response. Thank you. The word “see” has been deleted as recommended.Line 222: • A dd (Table 3) immediately after the word child.Response: Thank you. The expression “Table 3” has been added as suggested.Line 254-258:• The paragraph you stated as a starting point and discussion is not directly addressed through this analysis. So, I recommend to write based on the study objectives. This study didn’t address the effect of unskilled birth attendance on maternal death though it is addressed by other studies. So, try to focus on the study objectives. This study has nothing related to this issue.• Start with your main finding and then try to compare to others studies and policy implications• The proportion of the outcome is not discussed well. so, discuss the percentage in relation to expected proportion based on global initiativesResponse: Thank you. We acknowledge this, have deleted the part not related to the analysis and have revised the Discussion section. Line 263-265• Delete it; what is the important? Or make it short (paraphrase it). Response: Thank you. This has been done.• Line 266-280: • It is good you have stated some important statement for discussion. But these significant variables must be discussed separately with their corresponding justification. E.g.) why younger women higher odds of utilizing the service? Labor and child birth experience Vs Woman’s age and then Vs unskilled birth attendance?• So, the same is true for other variables found to be significant in the final model need to be discussed. Response: Thank you. The discussion has been revised as recommended.Line 283:• The use of conjunction  is not correct for under five demise Vs Unskilled birth attendance. • The reasoning stated in the document is not convincing. So, try to make it informative and convincing? Imogie (it is single study) and it is difficult to compare this study where it is the analysis many countries with a single study in Nigeria?Response● The word interestingly has been deleted. The discussion has been revised as recommended. Thank you for the observation.• Line 281-296:• The reasoning or justification need to be modified. Response: Thank you. The discussion has been revised as recommended.Line 297-307:• What could be the reason for hotspot for some countries and coldspot for some countries? Justification if you can?Response: The probable cause of hotspot could be due to the high incidence of unskilled birth attendance among neighbouring countries and vice versa. A further explanation has now been included in the manuscript.• Line 309-316: regarding the strength• Statements about strength of the study need to be paraphrased. Please come to the point in short . Using logistic model can not be a strength. The spatial can be a strength. Response: The strength subsection has been revised as recommended. Thank youLine 316-327:• Please try to state your own study or analysis limitation. • And then what are the potential limitation that you will share with DHS protocol.• Being cross-sectional can’t be a limitation for your analysis. • Still this subsection needs to paraphrased. Response: This subsection has been revised as recommended by the reviewer.Line 357: delete the “.” Before the referenceResponse: Thank you. This has been done.   The points stated under “Implications for policy and practice” can be written under discussion and conclusion based on the variables you discussed. Under discussion you can finalize with its public health policy and implementation implications�   Response Thank you for this suggestion. While we appreciate the reviewer’s suggestion, on this occasion, we plead to maintain the section on “Implications for policy and practice” as that section deals with high-level implications that are not specific to a particular variable.�🡺 Similar topic is done in Ghana by similar author; so, why you include Ghana in this analysis? What makes different from that study? What is new?🡺 Response: While we acknowledge that a similar topic has been done for Ghana please be informed that only one out of the five current authors was part of the previous study conducted in Ghana. More importantly, we included Ghana in the analysis to enable us to directly compare the previous findings on Ghana  to the remaining 29 Sub-Saharan African countries included in this study. In addition, the previous study on Ghana did not include the following important variables captured in our study: age at first birth, marital status, getting medical help for self: permission to go, getting medical help for self: getting money needed for treatment, desire for children, antenatal care visits, and under-five mortality.   The key legends for figure 2 and 3 Vs the colours in the figure are not comparable and this hide the information that can be captured from the figures.�   Response: Thank you. Although the two figures may be comparing the distribution of unskilled birth attendance, the colours can be different since they are analysed by two different tools. Also, using the same colours for the two would not be possible because the colour grading used in figure 2 shows magnitude whereas that of figure 3 does not.�Thank you.AttachmentResponses to Reviewers.docxSubmitted filename: Click here for additional data file. 31 Oct 2022 <div> PONE-D-21-36273R1 </div>  <div> Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveys </div>  <div> PLOS ONEDear Dr. Dickson,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. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.Please submit your revised manuscript by Dec 15 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at  </div> A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.An unmarked version of your revised paper without tracked changes. 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For instructions see: We look forward to receiving your revised manuscript.Kind regards,Kannan Navaneetham, PhDAcademic EditorPLOS ONE[Note: HTML markup is below. Please do not edit.]Reviewers' comments:https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  3 Dec 2022PONE-D-21-36273Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveysPLOS ONEDear Prof. Tsegaye Lolaso Lenjebo,We are grateful to you and the reviewers for your comments on our paper entitled " Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveys". We would also take this opportunity to thank the reviewers for finding merit in this paper and suggesting that it can be suitable for publication in your renowned journal if we incorporate some major revisions. We have taken notice of all the comments raised by the reviewers and have responded accordingly as follows. Please be informed that the reviewers' comments are in black texts whereas our responses are in red texts. Responses to the Editor’s Comments3. Please include a separate caption for each figure in your manuscript.Response: Thank you. We have included a separate caption for each figure as recommended.4. Please include your tables as part of your main manuscript and remove the individual files. Please note that supplementary tables (should remain/ be uploaded) as separate "supporting information" files.Response: Thank you. We have included the tables as part of the main manuscript and removed the individual files as recommendedhttp://journals.plos.org/plosone/s/licenses-and-copyright.5. We note that Figures 2 &3 in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software . For more information, see our copyright guidelines: We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission: a. You may seek permission from the original copyright holder of Figures 2 & 3 to publish the content specifically under the CC BY 4.0 license. http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:We recommend that you contact the original copyright holder with the Content Permission Form (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0  remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.The following resources for replacing copyrighted map figures may be helpful:http://viewer.nationalmap.gov/viewer/USGS National Map Viewer (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/The Gateway to Astronaut Photography of Earth (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.htmlMaps at the CIA (public domain): http://earthobservatory.nasa.gov/NASA Earth Observatory (public domain): http://landsat.visibleearth.nasa.gov/Landsat: http://eros.usgs.gov/#USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://www.naturalearthdata.com/Natural Earth (public domain): Response: We can confirm that Figures 1-3 were created or constructed by the authors based on the study data using ArcMap version 10.5. Permission from a copyright holder is not applicable in this context. We have, therefore, provided a source in the manuscript showing that the Figures were self-created by the authors.Responses to the Reviewers' comments:Reviewer #1: The manuscript entitled “Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveys” was reviewed carefully. There are some major and minor issues that should be considered.Response: Thank you. We have addressed the concerns as follows.Abstract: please consider to limit the abstract to 250 words. Background section is longer than other parts.Response: Thank you. We have reduced the abstract to 227 words and have cut down the background section as recommended.The result section of abstract is not supported by Effect size. Please revise this section.Response: Thank you. This section has been revised.Method :Please indicate confounders that the model was adjusted for.Response: Thank you. The section under the analytical procedure has been revised as recommended.Line 153-154: both lines are not essential. H1 is enough if authors insist in mentioning it in this section.ResponseThank you for the comment. H0 has been deleted accordingly.Result:Line 171: It is not common to start the results with tables at first. It is suggested to revise this line.ResponseThe entire sentence has been deleted. Thank you for your observation Line 192-193: same as above.ResponseThe entire sentence has been deleted. Thank you for your observation Line 192-193: same as above.Response The entire sentence has been deleted. Thank you for your observationLine 199-206: It is suggested to re-analysis the variables (making variables reverse) to have risk factor instead of preventive factor for better interpretation and understanding of readers.Response: Thank you. This section has been re-analysed and revised as suggested. Please indicate the confounders which were adjusted in this model.Response Thank you. This has been added. Please see the “Analytical procedure” section under the Methods.Line 236: unlike other analysis, authors selected 90% confidence interval for this analysis. Please give some reasons for this discrepancy.Response: Thank you for this observation. The tool used for running the Getis Ord G spatial analysis generates a seven-level categorised output based on confidence level. These seven-level categorised outputs are segmented into three, coldspot , random and hotspot . Our output automatically revealed that the distribution of unskilled birth attendance is spatially and significantly clustered at 90% confidence level. Unlike the other models where we had the liberty to select 95% confidence interval levels, we did not have control over the confidence interval for the geospatial analysis as the software automatically selected the 90% confidence interval based on the level of significance within the spatial distribution clusters. Tables:Please indicate percentage with 95% CI.Response: Please be informed that the Footnotes in Table 3 show the meaning of the * in the table. Thus, *p<0.05 equals 95% CIDiscussion:Line 2: 254-262 : the structure of scientific writing is not suitable for this part and is much more related to introduction. Please consider that the first paragraph of discussion should answer the research question of the introduction based on the eye-catching results of this study. Please revise.Response Thank you. The structure has been revised as recommendedThe main key home massage of this study which makes this distinguish from other local mentioned published articles that authors had mentioned in introduction is not crystal clear in this manuscript. Please discuss it with more prominent evidence.Response Thank you. The Discussion section of the manuscript has been revised to show the key variables and the take-home message. Reviewer #2: I found the paper good. The finding is supported by the analysis technique. It covers large geographical areas and it generates valuable information for public health authorities in the study areas. Response: Thank you for this positive feedback.There are some grammatical errors and editorial issues that are highlighted yellow in the document.Response: Thank you for the highlights. The issues have been resolved.However, there is similar topic done in Ghana by similar authors and I have raised a question regarding this issue in my comments and suggestions that I will attach to you.Response: Thank you. We have explained this in the main comment. Comments and suggestionsLine-38: “older current age and age at birth”• The association direction for age at birth is not specified.• Does the word “older” applies for both or not? If it applies for both then better if you write separately as older current age, older age at birth …Response Thank you for the observation. The results section of the abstract has been revised.Line 38 and 39:• The two variables; rich wealth status Vs not having money problems for healthcare• Both are complementary to each other. So, I recommend to select and use one. Wealth status is better.• Response Thank you for the observation. The results section of the abstract has been revised.Line 43:• Why Burundi?• Lowest proportion is from South Africa (SA) • Then what is the implication behind the result? All counties have higher odds? Response: Thank you. The analysis has been redone and South Africa has been made the reference category. The section has been revised.Line 78-79:• Add something about the spatial pattern of the issue in addition to what you stated.Response: Thank you. An additional sentence has been included to show that there are limited studies utilising spatial analysis to explore the distribution of unskilled birth attendance in SSA.Line 93:• The word “Explored” is not the appropriate action verb for such type of quantitative analysis. Better to use “identified” or “examined” …Response: Thank you for this observation. The word “explored” has been replaced with “examined”Line 95: • The same comment as line 93 (Exploring???)Response. Thank you. The word “Exploring” has been replaced with “Examining”• Line 101: • Could it be different for countries? If it the year is different how you handle the analysis? How do you control the effect of time? So, it is good if you make DHS data sets which are produced in the same year across different countries. Otherwise, the result is biased due to time effect or make it time series analysis?• Response: Thank you for this important observation. We agree with the reviewer that the differences in survey years may affect the results due to possible effect of time. However, DHS data for sub-Saharan African countries are commonly collected in different years and at different periods. This has been a notable limitation of most studies using pooled DHS data of various countries. As a result, we have added this as one of the limitations of the study. Line 180-187:• The description is not as such important as far as these variables are included in the regression model. The proportion (percentage) here is crude and it doesn’t add any value. So, delete it and try to include all variables into the model and report their adjusted effect on the outcome. Response: Thank you for this comment. While we appreciate the reviewer’s suggestion, in this instance, we plead to disagree. The description of participants is commonly provided in this type of public health research to give readers information on the number of respondents in each variable category. It also sets the basis for interpreting the results  and helps in identifying possible limitations induced by small samples in the variable categories. Line 194:• Make is showed i.e.) add “ed”Response: This has been rectified. Thank youLine 202: • Delete (Table 3).; as it is reported at the end of the paragraph.Response The expression “Table 3” has been deleted in the line as suggested. Thank you.Line 213: • Delete the word “see” as it is not important (be consistent).Response. Thank you. The word “see” has been deleted as recommended.Line 222: • A dd (Table 3) immediately after the word child.Response: Thank you. The expression “Table 3” has been added as suggested.Line 254-258:• The paragraph you stated as a starting point and discussion is not directly addressed through this analysis. So, I recommend to write based on the study objectives. This study didn’t address the effect of unskilled birth attendance on maternal death though it is addressed by other studies. So, try to focus on the study objectives. This study has nothing related to this issue.• Start with your main finding and then try to compare to others studies and policy implications• The proportion of the outcome is not discussed well. so, discuss the percentage in relation to expected proportion based on global initiativesResponse: Thank you. We acknowledge this, have deleted the part not related to the analysis and have revised the Discussion section. Line 263-265• Delete it; what is the important? Or make it short (paraphrase it). Response: Thank you. This has been done.• Line 266-280: • It is good you have stated some important statement for discussion. But these significant variables must be discussed separately with their corresponding justification. E.g.) why younger women higher odds of utilizing the service? Labor and child birth experience Vs Woman’s age and then Vs unskilled birth attendance?• So, the same is true for other variables found to be significant in the final model need to be discussed. Response: Thank you. The discussion has been revised as recommended.Line 283:• The use of conjunction  is not correct for under five demise Vs Unskilled birth attendance. • The reasoning stated in the document is not convincing. So, try to make it informative and convincing? Imogie (it is single study) and it is difficult to compare this study where it is the analysis many countries with a single study in Nigeria?Response● The word interestingly has been deleted. The discussion has been revised as recommended. Thank you for the observation.• Line 281-296:• The reasoning or justification need to be modified. Response: Thank you. The discussion has been revised as recommended.Line 297-307:• What could be the reason for hotspot for some countries and coldspot for some countries? Justification if you can?Response: The probable cause of hotspot could be due to the high incidence of unskilled birth attendance among neighbouring countries and vice versa. A further explanation has now been included in the manuscript.• Line 309-316: regarding the strength• Statements about strength of the study need to be paraphrased. Please come to the point in short . Using logistic model can not be a strength. The spatial can be a strength. Response: The strength subsection has been revised as recommended. Thank youLine 316-327:• Please try to state your own study or analysis limitation. • And then what are the potential limitation that you will share with DHS protocol.• Being cross-sectional can’t be a limitation for your analysis. • Still this subsection needs to paraphrased. Response: This subsection has been revised as recommended by the reviewer.Line 357: delete the “.” Before the referenceResponse: Thank you. This has been done.   The points stated under “Implications for policy and practice” can be written under discussion and conclusion based on the variables you discussed. Under discussion you can finalize with its public health policy and implementation implications�   Response Thank you for this suggestion. While we appreciate the reviewer’s suggestion, on this occasion, we plead to maintain the section on “Implications for policy and practice” as that section deals with high-level implications that are not specific to a particular variable.�🡺 Similar topic is done in Ghana by similar author; so, why you include Ghana in this analysis? What makes different from that study? What is new?🡺 Response: While we acknowledge that a similar topic has been done for Ghana please be informed that only one out of the five current authors was part of the previous study conducted in Ghana. More importantly, we included Ghana in the analysis to enable us to directly compare the previous findings on Ghana  to the remaining 29 Sub-Saharan African countries included in this study. In addition, the previous study on Ghana did not include the following important variables captured in our study: age at first birth, marital status, getting medical help for self: permission to go, getting medical help for self: getting money needed for treatment, desire for children, antenatal care visits, and under-five mortality.   The key legends for figure 2 and 3 Vs the colours in the figure are not comparable and this hide the information that can be captured from the figures.�   Response: Thank you. Although the two figures may be comparing the distribution of unskilled birth attendance, the colours can be different since they are analysed by two different tools. Also, using the same colours for the two would not be possible because the colour grading used in figure 2 shows magnitude whereas that of figure 3 does not.�Thank you.AttachmentResponses to Reviewers.docxSubmitted filename: Click here for additional data file. 13 Jan 2023Factors associated with unskilled birth attendance among women in Sub-Saharan Africa: a multilevel geospatial analysis of demographic and health surveysPONE-D-21-36273R2Dear Dr. Dickson,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,Kannan Navaneetham, PhDAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 24 Jan 2023PONE-D-21-36273R2 Factors associated with unskilled birth attendance among women in sub-Saharan Africa: a multivariate-geospatial analysis of demographic and health surveys Dear Dr. Dickson: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. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staffon behalf ofProf. Kannan Navaneetham Academic EditorPLOS ONE


Neonatal intensive care units (NICU) are specialized units that provide medical attention to neonates, and thus have become a vital aspect in the provision of critical care to infants who are faced with special challenges following birth.To determine antepartum and intrapartum factors that predispose to NICU admissions in the Nandom Municipal of the Upper West Region of Ghana.This was a cross‐sectional retrospective study, spanning from January 1, 2021 to December 31, 2021. Records covering 1777 women who were delivered or had their babies referred to the St. Theresa's Hospital in the Nandom Municipality were involved in the study. Descriptive statistics and multinomial logistic regression analysis were used to compare variables, and statistical significance was determined where the p‐value was less than 0.05.p = 0.004) and admission to NICU. Nulliparous mothers (p = 0.027) and mothers who presented with multiple pregnancy (p < 0.001) were more likely to have their babies sent to NICU. Both preterm delivery (p < 0.001) and post‐term delivery (p < 0.001) were prone to admission to NICU. Also, instrumental delivery (p < 0.001), cesarean section (p < 0.001), low birth weight (p < 0.001), and male infants (p = 0.003) had an increased risk of being admitted to NICU. Furthermore, severe (p < 0.001) and moderate (p < 0.001) birth asphyxia in the first minute following delivery were significantly associated with NICU admission whereas severely asphyxiated babies at 5 min (p < 0.001) were associated with NICU admission.From the study, the rate of NICU admission was 10.4%. There was a significant association between mothers who attended less than four antenatal sessions (The study revealed a relatively high NICU admission rate in the study area, and the predictors are multifaceted. Tailored intervention programs aimed at curbing these predictors will be required to reduce the rate of NICU admissions in the Nandom Municipality of Ghana. Where they are available, factors associated with neonatal admission to the NICU appear to be variable and could be dependent on the healthcare environment. Knowledge of these associated factors will provide useful information regarding resourcing, preparedness and smooth operation of the NICUs. This study, therefore, explored the “feto‐maternal” predictors of NICU admissions in the Nandom Municipality of the Upper‐West region of Ghana.22.1The Nandom Municipality is one of the 11 administrative municipalities and districts that make up the Upper West Region of Ghana. The municipality constitutes the north‐western corner of the Upper West Region of Ghana, geographically defined by longitudes 2°25 W and 2°45 W and latitudes 10°20 N and 11°00 S. The north‐western boundary of the municipality is also the international boundary between Ghana and the republic of Burkina Faso, whereas to the East, it shares boundary with the Lambussie district and to the south the Lawra Municipality. The municipality has a total land mass of 404.6 square km constituting approximately, 3.1% of the Upper West Region's total land mass. The Municipality is rural as 86% of the members of the municipality's 84 communities live in rural areas, and the population density is approximately 133 per square km.2.2A retrospective design was employed to carry out this study. The study population included all births delivered at St. Theresa's Hospital or referred to the hospital. The period reviewed covered January 1, 2021 to December 31, 2021. To extract relevant data from the maternal delivery record books, a structured questionnaire was designed based on the captioned information in the records book. The questionnaire was coded on a Google Form for uniformity and pretesting. After the necessary corrections to the tool, relevant socio‐demographic, maternal, and neonatal data for the study were extracted onto a Google Form. In all, a total of 1777 births were reviewed over the study period, and thus served as the sample size.2.3The data collected via the Google Form was extracted into Microsoft Excel for data cleaning, and subsequently exported into the IBM Statistical Package for Social Sciences (SPSS) software version 26 for analysis. The variables were categorized and descriptive statistics applied. Where applicable, multinomial logistic analysis was done for differences between the categorical variables and outcome variables, and a p‐value below 0.05 was considered statistically significant.2.4This study was approved by the University for Development Studies Institutional Review Board (UDS/RBI/107/22). Permission was granted by the hospital through the Medical Superintendent and the Maternity Ward In‐charge to carry out the study using the hospital's records. The data were anonymously collected and kept confidential.3From January 1 to December 31, 2021, 1777 babies were put to birth by 1772 mothers in St. Theresa's hospital, Nandom, of which, 10.4% (185/1777) of the babies were admitted to the NICU of the hospital. Mothers' ages ranged from 13 to 48 years, with a mean age of 28 ± 6 years, and 57.1%  of them were within the age range of 20–30 years. The literacy rate among 1385 mothers was 71.0% with a majority of 41.7% of the educated ones attaining Junior High School level of education. While 68.0% (924/1359) of the mothers were self‐employed, only 7.6% (103/1359) of them were engaged in formal employment. The mothers' demographic characteristics did not influence the babies' admission to the NICU (Table p = 0.004) compared to those whose mothers achieved the recommended ANC attendance. The odds of NICU admissions among babies whose mothers failed to adhere to the minimum standards of four times ANC attendance before delivery was twice compared to those who achieved the recommended 4 or more ANC attendance (Table Although 92.8% (1225/1644) of mothers achieved the recommended 4 or more ANC attendance before delivery, ANC attendance significantly influenced the proportion of babies admitted to the NICU. A higher proportion of babies whose mothers did not attain the minimum ANC attendance (<4 times) was admitted to the NICU  of the babies were delivered through spontaneous vaginal delivery (SVD), 2.6% (46) by instruments‐assisted delivery, whereas caesarian delivery was 23.1% (408). A significantly higher proportion of babies delivered through instruments assisted delivery (43.8% (14/46)) and through caesarian section (20.0% (68/408)) were admitted to the NICU, with odds of 6 and 2 respectively (Table  of the bp < 0.001) of being admitted to the NICU and 31.4% (66) of the preterm babies were admitted to the unit with four times risk (p < 0.001). Multiple babies per delivery were significantly associated with admission to the NICU compared to singletons. Although 94.4% (1666) of the babies were singletons, the proportion of multiple babies admitted to the unit was significantly higher with respect to the single babies , Table Babies delivered at term gestation constituted 81.6%  while 16.1% 276) and 2.3% (39) of the babies were delivered preterm and post‐term respectively, yet in comparison to babies delivered at term, 44.4%76 and 2.p < 0.001). Male babies constituted 52.6% (1422/1762) of the babies born and concerning NICU admission, 12.5% of them were admitted to the unit and this was significant (p = 0.003) when compared to their female counterparts. Birth asphyxia at birth was assessed to be severe in 3.2% (56) and moderate in 32.2% (567) of the babies, of which 50.0%p = 0.028), Table The babies' birth weight varied from 1.2 to 4.6 Kg, with a mean birth weight of 3.2 ± 3 Kg and 80.7%  of the babies were born with normal birth weight (2.5–3.9 Kg). Whereas 25.5% of low‐weight and 15.0% of overweight babies were admitted to the NICU, babies with low birth weight were more likely to be admitted to the NICU . However, slightly over 10% of the babies were borne by teenage mothers, yet there was no significant association between teenage pregnancy and admission to NICU in contrast with other findings where teenage pregnancy was found to be one of the major associated factors to NICU admission.ANC attendance was found to be associated with NICU admission in our study. Though our review showed that nine out of every 10 women achieved the recommended minimum of 4 ANC attendance per pregnancy, mothers whose ANC attendance was less than four sessions were twice likely to have their babies admitted to the NICU. This is similar to an observation made by Manjavidze et al.Parity, Mode of delivery, gestational age and multiple gestations were observed to be associated with NICU admission. Infants of nulliparous mothers were about three times more likely to be admitted to NICU as compared to other mothers. Clapp et al.Multiple pregnancy was identified as a significant contributor to the admission of neonates to the NICU. Some studies support the assertion that multiple pregnancy is a risk factor for NICU admission.Prematurity was found to have a strong association with admission to NICU from our study. Babies who were born before 37 weeks of gestation were about four times more likely to be admitted to NICU as compared to those who were born at term. Desalew et al.As per the findings of our study, there was an increased risk of NICU admission following cesarean section and instrumental delivery. Babies born by cesarean section were two times more likely to be admitted to NICU as compared to those who delivered by spontaneous vaginal delivery (SVD). This finding is comparable to the results from a study conducted by Fallah et al.Neonatal factors such as birth weight, sex, asphyxia, and congenital defects were found to be associated with admission to the NICU. Barker et al.The results of our study show a slight preponderance towards the male child being admitted to NICU. The males were almost twice likely to be sent to NICU as compared to their female counterparts. Similar findings were reported by Desalew et al.According to the results of our study, severe and moderate birth asphyxia were found to be associated with an increased risk for admission to the NICU. After a minute following delivery, babies who recorded Apgar score below 3 were 15 times more likely to be admitted to NICU. Those who were moderately asphyxiated at 1 min were four times as likely to be admitted to NICU as compared to those with mild asphyxia. Birth asphyxia has been shown to increase the likelihood of neonatal morbidity and mortality.5In conclusion, the prevalence of NICU admission was 10.4%. Mothers who attended less than four antenatal sessions had an increased risk of having their babies admitted to NICU. The study found that nulliparity and multiple pregnancy were risk factors for the admission of babies to NICU. Also, preterm babies and those born post‐term had an increased risk of admission to NICU, likewise babies delivered by cesarean section and instrumental delivery. Low birth weight babies, male babies, Apgar score, and birth asphyxia were associated with admission of babies to the NICU. These factors could provide the bases for healthcare providers to put in place preventive strategies aimed at reducing neonatal admissions in the study area.Maroun Soribang Ziem: Data curation. Fidelis Adam Saaka: Data curation. Ezekiel Kofi Vicar: Data curation. Eugene Dogkotenge Kuugbee: Resources. Akosua Bonsu Karikari: Writing – review & editing. Sebastian Yidana Ninimiya: Resources. Juventus Benogle Ziem: Writing – review & editing. Williams Walana: Formal analysis; Writing – original draft.The authors declare no conflict of interest.This study did not receive any external funding.The lead author Williams Walana affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned  have been explained.


Higher perfluoroheptanoic acid (PFHpA) and perfluoroheptane sulphonate (PFHpS) were associated with increased Apgar-1 scores. PFOA (Odds ratio (OR): 2.17, 95% CI: 1.27, 3.71, p = 0.004) and PFNS  were also risk factors to preterm birth. In addition, the quantile-based g-computation showed that PFASs mixture exposure was significantly associated with Apgar-1  and preterm birth . In conclusion, PFASs were widely distributed in the maternal serum, which was influenced by maternal characteristics and significantly associated with several birth outcomes. Further investigation should focus on the placenta transfer and toxicities of PFASs.Perfluoroalkyl substances (PFASs) exposure is suggested to interfere with fetal growth. However, limited investigations considered the roles of parity and delivery on PFASs distributions and the joint effects of PFASs mixture on birth outcomes. In this study, 506 birth cohorts were investigated in Hangzhou, China with 14 PFASs measured in maternal serum. Mothers with higher maternal ages who underwent cesarean section were associated with elevated PFASs burden, while parity showed a significant but diverse influence. A logarithmic unit increment in perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluorononane sulfonate (PFNS) was significantly associated with a reduced birth weight of 0.153 kg : −0.274, −0.031,  Perfluoroalkyl substances (PFASs) comprise a group of synthetic fluorinated chemicals that have been widely used in cleaning products, textiles, adhesive food packaging, and fire foam for decades ,2,3,4. TAmong the above matrix, PFASs in maternal serum are commonly used to reveal the prenatal and in-uterus exposure because of the data feasibility and sample availability . For expFor fetuses, chemical exposure during gestation periods could adversely affect child and adult growth ,24,25,26Given the aforementioned data, this study monitored 14 PFASs in maternal serum from 506 mother-infant pairs in Hangzhou, China. We aimed to (1) measure PFASs profiles in maternal serum before delivery, (2) explore the potential sociodemographic predictors of PFASs exposure, and (3) provide epidemiologic evidence on both joint and individual associations between PFASs exposure and birth outcomes .Maternal-neonatal pairs were recruited, and prenatal maternal serum was collected at the Women’s Hospital School of Medicine, Zhejiang University in Hangzhou, China from October 2020 to September 2021. The eligible mothers were older than 20 y and excluded from reporting serious medical treatment history, including neoplastic diseases, cardiovascular diseases, renal failure, aortic surgery, chronic liver failure, gestational hypertension, and other medical conditions  and the Birth weight (kg) and Apgar scores (Apgar-1 and Apgar-5) were collected from the delivery records. The World Health Organization defines preterm birth as birth occurring before 37 completed weeks of gestation .Blood samples were collected at the hospital , and written consent was obtained from each donor) and then centrifuged at 4000 rpm for 20 min to separate and extract the serum. Finally, the serum was transferred to a polypropylene tube and stored at −4 °C for further analysis.Native standards of perfluoroalkyl sulfonic acids (PFSAs), perfluoroalkyl carboxylic acids (PFCAs), and corresponding isotopically labeled internal standards were supplied by Wellington Laboratories . The ammonium hydroxide, high-performance liquid chromatography-grade (HPLC-grade) methanol, and formic acid were purchased from J&K Chemicals . A total of 14 PFASs and corresponding internal standards are available in Solid-phase extraction was conducted to extract the PFASs from the serum samples. The procedures are presented in detail in SI. All serum samples were spiked with isotopically labeled internal standards. Cartridges were activated after the precondition. Prepared samples were subsequently passed through the cartridges, which were then washed  . All 14 target compounds were analyzed on a UPLC-tandem electrospray equipped with the Xevo TQ-Striple quadrupole mass spectrometry system . The MS parameters of the target analytes are listed in All laboratory utensils were polypropylene and moistened with Milli-Q water and HPLC-grade methanol three times before use. To check for potential background contamination between batches, procedure blanks for every 20 samples were included. The PFASs in the present study were quantified using the internal-standard method. Calibration consisted of native PFASs containing internal calibration. The process blank sample, matrix spiked sample, and three groups of parallel samples were repeated twice for each group for the quality control measures in the pretreatment process. The mean matrix spiked recoveries ranged from 86.7% to 107%. The corresponding internal standard, correlation coefficient, detection limit, quantification limit, and method detection limit of each target compound are shown in n (%), were selected to express the demographic characteristics. All data were assessed for normality and homogeneity via the Kolmogorov–Smirnov test and the Bartlett test [10-transformed before further analysis [Descriptive statistical analyses, including the mean ± standard deviation (SD) and ett test . PFASs canalysis . The Spep < 0.05 was regarded as statistically significant. All analyses were performed using SPSS  and R (version 4.2.0) with the “qgcomp” package.Univariate and multivariate linear regression models were utilized to determine the associations between the concentration of each PFAS compound and birth outcomes. For continuous outcome variables of birth weight and Apgar scores, the results were expressed as estimated changes in each unit per log-unit increase in PFASs in the maternal serum ). For the categorical dependent variable of preterm birth, binary logistic regression models were used to estimate the odds ratios (ORs) and 95% CI for preterm birth and PFASs exposures . For the2, with an average gestation age of 265 ± 28.3 d. About 41.3% were primiparous, and nearly 51.2% of mothers had spontaneous labor. Of the newborns, 52.9% were male. There were 89 neonates born with preterm birth and the percentage was 17.6%. The average birth weight was 3.11 (SD = 0.75) kg and the average neonatal Apgar-1 and Apgar-5 scores were 9.88 and 9.99, respectively. Approximately 2.6% and 2.0% of newborns had Apgar-1 and Apgar-5 scores below 8. All the demographic information is shown in The pregnant women included in the study were aged 31.3 (SD = 4.28) y on average at delivery. Prenatal BMI was 26.7 ± 3.16 kg/mFourteen PFASs homologs were analyzed in the maternal serum. Except for PFTeDA, PFHxS, and PFHpS, all compounds exhibited high detection frequencies exceeding 80%. As shown in Compared with the previous studies in the past three years, the median PFOA concentrations were higher than those of Shenyang, China 3.27 ng/mL) , Odense,7 ng/mL ,p < 0.05) . In this study, no significant associations between BMI and serum PFAS were noted. Lipophilic persistent organic pollutants can usually accumulate and become enriched in adipose tissue, which was described as the BMI of the mothers. However, mixed results were found for PFASs mainly bound to albumin-positive, null, and inverse associations between BMI and PFASs concentrations [Higher maternal age (>35 years) was significantly associated with higher concentrations of PFOA, PFNA, PFDA, PFUnDA, PFOS, and PFPeS than those in the lower age groups ( < 0.05) . Our fintrations ,59.p < 0.05). Nevertheless, PFOA, PFDA, PFUnDA, PFNA, PFOS, PFNS, and PFHxS exhibited a reverse trend in that the concentrations were significantly higher in multiparous women than in primiparas. It can be seen that parity was associated with higher concentrations of seven PFASs but the differences between nulliparous and parous women became smaller for PFOS, PFNS, PFOA, and PFHpS. In this study, we cannot draw the conclusion that parity was a strong negative or positive predictor of maternal PFAS status for individual differences between study subjects. However, a prior study has reported that a Swedish birth cohort observed that parity was inversely associated with eight serum PFASs except for PFOS, PFNA, and PFOA concentrations declined as parity increased [Parity played a significant role in PFASs exposure. Primiparous mothers tend to have significantly higher levels of PFDoA and PFTrDA than multiparous ones  than in those who had spontaneous delivery. In this study, the majority of pregnant women who delivered their babies via C-section were in the elderly group, who tend to accumulate PFASs for a longer time. The poor contractile force and guiding extension tension of the uterus of elderly pregnant women can easily prolong the delivery time, and the fetus delivered via C-section also had the problem of excessive birth size.p = 0.014), 0.217 kg , and 0.137 kg . When adjusted for all covariates, the negative associations remained but were not significant for PFOA: −0.110 kg . Moreover, PFNA, PFUnDA, PFTeDA, and PFHpS exhibited a negative correlation with birth weight in both models, although these data were not significant. Given that PFASs had strong inter-correlations, we, therefore, performed quantile-based g-computations to further explore the joint effects of PFASs on birth outcomes. However, there was no significant association between the PFASs mixture and birth weight  and 0.117 . Quantile g-computation model indicated that increasing all PFASs in the mixture by one quartile was significant with a 0.324 increase in Apgar-1  , in the fully adjusted models, per logarithmic unit increase in PFHpA and PFHpS exposure was associated with increased Apgar-1 scores of 0.065  . However= 0.013) . To datep = 0.004) and 1.59 fold  greater per log-ng/mL of PFOA and PFNS concentration in maternal serum. This was in accordance with numerous studies, for example, elevated odds of preterm birth were found in association with higher maternal PFOA, PFBA, and PFNA from a family-based birth cohort study in coastal China [Binary logistic regressions were performed to present the associations between each PFASs compound exposure and preterm birth. As al China . Similaral China . A nearlal China . Neverthal China . Two final China ,72. A thp = 0.005) and PFDS , which inhibited the preterm development. The inverse associations were unexpected and we did not find directly comparable results from other studies. Moreover, the joint exposure model indicated an overall inverse dose-response relationship that increasing all PFASs in the mixture by one quartile was similarly associated with a modest reduction in the preterm incidence   . PFOS, P= 0.019) . To datePFASs were widely distributed in the maternal serum, with PFOA, PFOS, and PFHpA the most abundant PFASs. Maternal age, BMI, parity and delivery mode were considered as influencing factors of the PFASs burden. Multivariate linear regression suggested that prenatal exposure to PFOA, PFOS, and PFNS significantly reduced neonatal birth weight. PFHpA and PFHpS exposure was associated with increased Apgar-1 scores. PFOA and PFNS were identified as risk factors to preterm birth.There are some limitations in the present study including the mixed conclusions with the deficiency of both maternal and neonatal evaluation biomarkers. We brought new insights regarding the occurrence of PFASs in humans and Apgar scores. However, we cannot draw the conclusion that PFASs improve the neonatal development on the Apgar since PFHpA and PFHpS were not major components in the total PFASs exposure. Moreover, the plancenta transfer for PFASs from mothers to fetus is not investigated in this study. In this respect, overarching investigations of the active transport mechanism, prenatal exposure, and reproductive risks of PFASs with a larger sample size are warranted.