{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T08:51:28Z","timestamp":1785919888547,"version":"3.56.0"},"update-to":[{"DOI":"10.12688\/wellcomeopenres.25241.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000}}],"reference-count":26,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["207522"],"award-info":[{"award-number":["207522"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["092654"],"award-info":[{"award-number":["092654"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["wellcomeopenresearch.org"],"crossmark-restriction":false},"short-container-title":["Wellcome Open Res"],"abstract":"<ns5:p>Background Neonatal mortality remains a significant challenge in Sub-Saharan Africa. Outborn neonates - those born outside the admitting hospital - are particularly vulnerable, yet their outcomes remain under-characterized in many low-resource urban settings. This study examines the burden, characteristics, and mortality risk among outborn neonates admitted to public neonatal units in Nairobi, Kenya. Methods We conducted a retrospective cohort study across four high-volume public hospitals in Nairobi County, Kenya. A stratified random sample of 400 outborn neonates admitted between January and December 2023 was reviewed using medical records. To estimate outborn prevalence and the Population Attributable Fraction (PAF) for mortality, we analyzed registry data from 9,021 neonatal admissions with complete outcome and place-of-birth information. Referral distances were calculated using geocoded coordinates of referring and receiving facilities. Multivariable logistic regression identified factors independently associated with inpatient neonatal mortality. Results Outborn neonates accounted for 17% of neonatal admissions, with a mortality rate of 25.6%, double that of inborn (12.5%; crude RR=2.05, p&lt;0.001). The PAF was 15.0% (95% CI: 12.3-17.7%), indicating that one in seven neonatal deaths could be attributed to outborn status. Key factors were significantly associated with increased odds of mortality including; extremely low birth weight (&lt;1000g; AOR=7.8, 95% CI: 2.6, 23), very low birth weight (1000-1499g; AOR= 4.7 95% CI:2.3, 9.7), hypothermia (AOR=2.2, 95% CI: 1.1, 4.5), respiratory distress (AOR=2.1, 95% CI: 1.2, 3.8), and referral distance &gt;12.1 km (AOR=2.6, 95% CI: 1.1, 6.6). Most deaths (68%) occurred within three days of admission. Conclusion Outborn neonates in Nairobi\u2019s public hospitals face substantially higher early mortality, primarily driven by low birth weight, hypothermia, respiratory distress, and longer referral distances. Interventions targeting improved stabilization, timely referral, and early neonatal care are urgently needed. These findings provide actionable evidence to inform policies aimed at reducing neonatal mortality and advancing progress toward SDG 3.2.<\/ns5:p>","DOI":"10.12688\/wellcomeopenres.25241.2","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T14:44:08Z","timestamp":1785854648000},"page":"217","update-policy":"https:\/\/doi.org\/10.12688\/wellcomeopenres.crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Outborn Neonates in Nairobi's Public Hospitals: Mortality Burden and Risk Factors"],"prefix":"10.12688","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5593-1211","authenticated-orcid":false,"given":"John","family":"Wainaina","sequence":"first","affiliation":[{"name":"School of Public Health Nairobi Nairobi County 00200 Jomo Kenyatta University of Agriculture and Technology"},{"name":"Graduate School Nairobi Nairobi County 00100 Kenya Medical Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Gachohi","sequence":"additional","affiliation":[{"name":"School of Public Health Nairobi Nairobi County 00200 Jomo Kenyatta University of Agriculture and Technology"},{"name":"Global Health Kenya Nairobi Kenya 00100 Washington State University"},{"name":"Washington State University Pullman WA 99164 Paul G, Allen School of Global Health"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0851-3711","authenticated-orcid":false,"given":"Jalemba","family":"Aluvaala","sequence":"additional","affiliation":[{"name":"Department of Paediatrics and Child Health Nairobi Nairobi County 00100 University of Nairobi"},{"name":"Health Services and Implementation Cluster Nairobi Nairobi County 00100 KEMRI-Wellcome Trust Research Programme Nairobi"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2560","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"ref1","article-title":"Neonatal mortality.","year":"2024 March 2024 cited 2025 January 19"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"491-499","DOI":"10.1159\/000530496","article-title":"Ending Preventable Neonatal Deaths: Multicountry Evidence to Inform Accelerated Progress to the Sustainable Development Goal by 2030.","volume":"120","author":"J Lawn","year":"2023","journal-title":"Neonatology."},{"key":"ref3","doi-asserted-by":"publisher","first-page":"412-418","DOI":"10.1016\/j.pedneo.2021.04.001","article-title":"Neonatal mortality among outborn versus inborn babies.","volume":"62","author":"W Chen","year":"2021","journal-title":"Pediatr. 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Health."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1542\/peds.2023-061957","article-title":"Standards for Levels of Neonatal Care: II, III, and IV.","volume":"151","author":"A Stark","year":"2023","journal-title":"Pediatrics."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1038\/s41597-019-0142-2","article-title":"A spatial database of health facilities managed by the public health sector in sub Saharan Africa.","volume":"6","author":"J Maina","year":"2019","journal-title":"Sci. Data."},{"key":"ref12","article-title":"Haversine Formula \u2013 Calculate geographic distance on earth.","author":"A Upadhyay","year":"2019 cited 2025 5th July 2025"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1186\/s12940-019-0492-4","article-title":"Estimation and application of population attributable fraction in ecological studies.","volume":"18","author":"C Lin","year":"2019","journal-title":"Environ. 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Res."},{"key":"ref27","article-title":"Outborn neonatal admissions and mortality in Nairobi public hospitals, Kenya, January\u2013December 2023.","author":"J Wainaina","year":"2025","journal-title":"Harvard Dataverse."}],"container-title":["Wellcome Open Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2\/iparadigms","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T08:34:11Z","timestamp":1785918851000},"score":1,"resource":{"primary":{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,4]]},"references-count":26,"URL":"https:\/\/doi.org\/10.12688\/wellcomeopenres.25241.2","relation":{"has-version":[{"id-type":"doi","id":"10.12688\/wellcomeopenres.25241.1","asserted-by":"subject"}],"has-review":[{"id-type":"doi","id":"10.21956\/wellcomeopenres.30077.r163288","asserted-by":"subject"},{"id-type":"doi","id":"10.21956\/wellcomeopenres.30077.r163288","asserted-by":"object"}]},"ISSN":["2398-502X"],"issn-type":[{"value":"2398-502X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,4]]},"assertion":[{"value":"Indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2#article-reports","order":0,"name":"referee-status","label":"Referee status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.21956\/wellcomeopenres.27818.r153412, Hassib Narchi, United Arab Emirates University, Abu Dhabi, 27 Apr 2026, version 1, 3 approved with reservations","URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v1#referee-response-153412","order":0,"name":"referee-response-153412","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>John Wainaina<\/b>; \n<i>Posted: 14 Jul 2026<\/i>; \n<b>REVIEWER 1: DR. NARCHI<\/b> \n<i>We thank Dr. Narchi for a thorough and constructive review. We have addressed each point below and indicated the corresponding manuscript revision.<\/i>  \n<i><b>METHODS<\/b><\/i> The source of the expected outborn mortality prevalence of 26% used to calculate the sample size should be mentioned (previous studies, hospital audits, etc,).&nbsp;  \n<i>We agree this needs an explicit citation. This estimate was drawn from Wainaina et al. (2023) (ref. 7), which reported ~26% mortality among referred-in neonates across three first-referral hospitals in Nairobi \u2013 largely similar population base extended in the present study. We have added this citation directly to the Methods sentence.<\/i>  The Geocoding method and analysis to calculate the distances involved in the transfer is very interesting but not accurate. it was applied only when the sources of referrals were hospitals. Furthermore, it calculated a straight line between the referring and the admitting centre which is not always correct. It does not take into consideration the traffic conditions on these roads (congestions, rush hours) nor the state of these roads (maintained in good conditions, narrow or not, not always on a flat terrain)not the time of the day for each transfer (less congestion at night, etc). It would have been more realistic and relevant if the time taken for each transfer was used instead of the geospatial distance, although the authors acknowledge its difficulty. These issues may impact on the results of the study and hence, the recommendations made.  \n<i>We agree this is a genuine limitation and did not intend to imply the Haversine distance approximates actual transit experience. We have expanded the Strengths and Limitations paragraph to explicitly state that straight-line distance does not capture road quality, congestion, time-of-day effects, or actual travel time, and that this may bias the distance\u2013mortality association toward or away from the null in ways we cannot determine with available data. We have noted that time-stamped transfer data would be a valuable addition for future work, as the reviewer suggests. <\/i> &nbsp;  With many missing variable data (between 15 and 27%), the multiple inputation (MICE) method which was used might not be correct as it is only adequate and reliable if less than 29% of the data are missing.&nbsp;This issue would certainly impact on the results and their interpretation.  \n<i>Imputation was restricted to the covariates included in the final regression model, and only those with \u226420% missingness - this is stated in the Methods (&quot;MICE was applied to covariates with \u226420% missingness&quot;). The 15\u201327% range reflects missingness across all variables abstracted in Table 1, not the subset modeled; several higher-missingness variables (e.g., resuscitation at birth, 27% missing) were not imputed or included in the regression at all. We have revised the Methods sentence to make this distinction explicit.<\/i> \n<i>On the general reliability of MICE at this level of missingness: we don't think a fixed percentage cutoff is the right standard, as there is no consensus threshold in the missing-data literature (e.g., White, Royston &amp; Wood, 2011, Stat Med https:\/\/doi.org\/10.1002\/sim.4067 , show MICE performing well beyond 20\u201330% missingness under Missing at Random (MAR) with adequately specified models). However, we agree that results would be more unreliable with increasing missingness.<\/i> &nbsp;  \n<i><b><u>RESULTS<\/u><\/b><\/i> The calculation of the Population Attributable Mortality for outborn neonates should explicitly describe if the relative risk (RR) used in the calculation was the crude or the adjusted RR, as the result and its interpretation are likely to be different.  \n<i>The RR of 2.05 used in the PAF calculation was the crude RR, derived directly from the raw mortality rates (25.6% vs 12.5%) in the full registry dataset (which lacks individual-level covariates needed for adjustment). We will state this explicitly in the Results and note it as a limitation - the PAF estimate assumes the crude RR approximates the causal effect of outborn status, which may be confounded by unmeasured factors (birth weight, gestational age, etc., which are disproportionately more common among outborn admissions).<\/i>  In the paragraph Factors associated with mortality, the authors should clarify if the OR with 95% conficence intervals refers to the raw OR or the adjusted OR. The neonates referred over a distance &gt; 12 km had an adjusted OR of death of 2.6 when compared to a shorter distance and not 0.39 as reported, this would change completely the interpretation of that paragraph.  \n<i>Thank you for catching a real error. We have corrected the Results text to read: &quot;Neonates referred from &gt;12.1 km had significantly increased odds of death compared to those from \u22643.4 km (aOR = 2.6; 95% CI: 1.1\u20136.6; p = 0.041)... A similar trend was seen for distances of 7.4\u201312.1 km (aOR = 2.2; 95% CI: 0.88\u20135.5; p = 0.10).&quot; We have also re-checked all other aOR values transcribed into prose throughout Results and Discussion against Table 4 to rule out similar transcription errors elsewhere.<\/i> &nbsp;  \n<i><b><u>DISCUSSION<\/u><\/b><\/i> LBW as a predictor of mortality should not be restricted to 1000-1499 g, but also include &lt; 1000 g  \n<i>We agree and this was an oversight. Extremely low birth weight (&lt;1000g) carried an even stronger association (aOR 7.8, 95% CI 2.6\u201323.0) than the 1000\u20131499g category. We have revised the paragraph to lead with the &lt;1000g finding and discuss both categories together as evidence of a birth-weight gradient in mortality risk.<\/i> &nbsp;  \n<u>TABLE 1<\/u>. All the variables should be logically ordered by their values to facilitate reading. In all the rows mentioning the number of missing data, the percentage of missing data should be added. The row Resuscitation at birth is very vague: ventilatory support, ?chest compression? medications?&nbsp; One row mentions respiratory distress and another one is labelled&nbsp;distress syndrome. Probably the authors meant surfactant deficiency for the latter and other cuases for the former (transient tachypnea, meconium aspiration, pneumonia, etc). This should be clarified. Another column reports LBW and prematurity together, although they do not mean exactly the same thing. This could be confusing.  &nbsp; \n<i>We have reordered all categorical variables into ascending\/logical order. We have also added missing-data percentages alongside each missing-data row count.<\/i> \n<i>&quot;Resuscitation at birth&quot; has been clarified as bag-mask ventilation, based on what the abstraction tool captured.<\/i> \n<i>We have updated &quot;Respiratory distress&quot; to \u201crespiratory distress signs\u201d (clinical signs of inner chest wall indrawing and or severe grunting during admission examination)<\/i> \n<i>We have clarified that &quot;LBW\/Prematurity&quot; reflects a single combined diagnosis category as recorded in the original medical records and abstraction tool - i.e., clinicians entered &quot;low birth weight\/prematurity&quot; as one diagnostic label at the point of care. We have added a table footnote stating this explicitly, so readers don't mistake it for a derived variable and understand why its counts don't nest cleanly with the standalone birth weight or gestational age rows.<\/i> &nbsp; &nbsp;  \n<u>TABLE 2<\/u> The total on inborn + outborn neonates per year is 9026 and not 9021 as stated in the text.  &nbsp; \n<i>Thank you for pointing this out, however, upon rechecking total against the source registry data, we note that (10,421 \u2212 1,394 missing = 9,027 - univariate datapoint) are the total inborn and outborn (place of birth data). However, for analysis involving place of birth and outcomes, a few were missing either and thus 9,021 as stated in text \u2013 this is well captured in the methods and results.<\/i>  \n<u>TABLE 4<\/u> All the variables should be logically ordered by their values to facilitate reading.  \n<i>This has been actioned in the new version of this paper.<\/i> &nbsp;  \n<u>OVERALL<\/u> In addition, the authors should address all the discrepancies and contradictions between the text and the tables. \n<i>We have done a full pass reconciling every number quoted in text against its source table.<\/i>  \n<u>CONCLUSIONS<\/u> I hope that the authors find these suggestions helpful and improve the manuscript which should make strong contribution to neonatal health issues in Sub-Sharan Africa and help achieve the Sustainable Development Goal (SDG) of reducing neonatal mortality.  \n<i>Thank you for the opportunity to improve this paper through your kind review.<\/i>","URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2#referee-comment-6656","order":1,"name":"referee-comment-6656","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.27818.r153419, Olufunke Bolaji, Paediatrics, Federal Teaching Hospital Ido-Ekiti (Ringgold ID: 605037), Ido Ekiti, Ekiti, 30 Apr 2026, version 1, 3 approved with reservations","URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v1#referee-response-153419","order":2,"name":"referee-response-153419","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>John Wainaina<\/b>; \n<i>Posted: 14 Jul 2026<\/i>; We thank Dr. Bolaji for her positive assessment and constructive suggestions. We address each point below.  1. \n<b>More concise title.<\/b> \n<i>We appreciate the suggestion. However, we'd like to retain &quot;Burden,&quot; since the population-level mortality burden (prevalence of outborn admissions, attributable fraction) is one of the paper's two central findings, alongside the individual-level risk factor analysis - dropping it would understate that contribution. We propose instead: &quot;Outborn Neonates in Nairobi's Public Hospitals: Mortality Burden and Risk Factors,&quot; which shortens the title while preserving both core results.<\/i>  2. \n<b>Clarity on &quot;among these vulnerable populations&quot; in the Background.<\/b> \n<i>Agreed - the antecedent is unclear in the original sentence: We have revised the sentence to: <\/i> \n<i>&quot;Neonates in Sub-Saharan Africa remain broadly at elevated risk of death, but outborn neonates \u2013 referrals in, and other categories of babies born outside the admitting hospital, such as at home, during transit, or at other healthcare facilities - represent a unique sub-group with heightened risks of morbidity and mortality.&quot;<\/i>  3. \n<b>Arrange GA categories sequentially in Table 1.<\/b> \n<i>Agreed - we have reordered across in Tables 1 through 4.<\/i>  4. \n<b>RDS diagnosis count inconsistency vs. LBW\/Prematurity denominator.<\/b> \n<i>This is a good catch and concern. At MLKH, LBW\/Prematurity = 31 but RDS = 55; at PMH, 32 vs. 34 - counts that would be implausible if RDS occurred only as a complication of prematurity\/LBW. In practice, &quot;respiratory distress syndrome&quot; was recorded as a clinical working diagnosis at admission (based on presentation) rather than a confirmed surfactant-deficiency diagnosis, and diagnosis fields were not mutually exclusive or nested - a neonate could carry an RDS diagnosis independent of how LBW\/Prematurity was coded. We have clarified this in Table 1 to help readers appreciate that fact.<\/i>  5. \n<b>Arrange length-of-stay categories sequentially.<\/b> \n<i>Agreed - we have reordered across all levels as appropriate across all tables.<\/i>  6. \n<b>Categories should read &lt; 3 days for length of stay for survivors and deaths and ALL since this was what was referred to in the prose.<\/b> \n<i>We have streamlined the tables and prose to read as intended.<\/i> &nbsp;  7. \n<b>More recent reference than Rakholia et al. (2014).<\/b> \n<i>We have added a recent study from Uganda (2023) to strengthen that discussion.<\/i>","URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2#referee-comment-6657","order":3,"name":"referee-comment-6657","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.30077.r163288, Alexander G Stevenson, African Neonatal Network, Kigali, 05 Aug 2026, version 2, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/11-217\/v2#referee-response-163288","order":4,"name":"referee-response-163288","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This work was supported by Wellcome Trust (207522) and (092654). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":5,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}