Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries

Funding Information: M.B.A. holds a Tier 2 Canada Research Chair in the Developmental Origins of Chronic Disease at the University of Manitoba and is a Fellow in the Canadian Institutes for Advanced Research (CIFAR) Humans and the Microbiome Program. Her effort on this project was partly supported by HDR UK and ICODA. K.K.C.M. declares support from The Innovation and Technology Commission of the Hong Kong Special Administrative Region Government, and Hong Kong Research Grants Council Collaborative Research Fund Coronavirus Disease (COVID-19) and Novel Infectious Disease Research Exercise (Ref: C7154-20G) and grants from C W Maplethorpe Fellowship, National Institute of Health Research UK, European Commission Framework Horizon 2020 and has consulted for IQVIA Ltd. A.S. is supported by ICODA and HDR UK, and has received a research grant from HDR UK to the BREATHE Hub. He participates on the Scottish and UK Government COVID-19 Advisory Committees, unremunerated. S.J.S. is supported by a Wellcome Trust Clinical Career Development Fellowship (209560/Z/17/Z) and HDR UK, and has received personal fees from Hologic and Natera outside the submitted work. D.B. is supported by a National Health and Medical Research Council (Australia) Investigator Grant (GTN1175744). I.C.K.W. declares support from The Innovation and Technology Commission of the Hong Kong Special Administrative Region Government, and Hong Kong Research Grants Council Collaborative Research Fund Coronavirus Disease (COVID-19) and Novel Infectious Disease Research Exercise (Ref: C7154-20G), and grants from Hong Kong Research Grant Council, National Institute of Health Research UK, and European Commission Framework Horizon 2020. H.Z. is supported by a UNSW Scientia Program Award and reports grants from European Commission Framework Horizon 2020, Icelandic Centre for Research, and Australia’s National Health and Medical Research Council. H.Z. was an employee of the UNSW Centre for Big Data Research in Health, which received funding from AbbVie Australia to conduct research, unrelated to the current study. I.I.A.A., C.D.A., K.A., A.I.A., L.C., S.S., G.E.-G., O.W.G., L. Huicho, S.H., A.K., K.L., V.N., I.P., N.R.R., T.R., T.A.H.R., V.L.S., E.M.S., L.T., R.W. and H.Z. received funding from HDRUK (grant #2020.106) to support data collection for the iPOP study. K.H., R.B., S.O.E., A.R.-P. and J.H. receive salary from ICODA. M.B. received trainee funding from HDRUK (grant #2020.106). J.E.M. received trainee funding from HDRUK (grant #2020.109). Other relevant funding awarded to authors to conduct research for iPOP include: M.G. received funding from THL, Finnish Institute for Health and Welfare to support data collection. K.D. received funding from EDCTP RIA2019 and HDRUK (grant #2020.106) to support data collection. R.B. received funding from Alzheimer’s Disease Data Initiative and ICODA for the development of federated analysis. A.D.M. received funding from HDR UK who receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust; and Administrative Data Research UK, which is funded by the Economic and Social Research Council (grant ES/S007393/1). N.A. received funding from the National Institutes of Health (R35GM138353). O.S received funding from NordForsk (grant #105545). The remaining authors declare no competing interests. Funding Information: Funding and in-kind support: This work was supported by the International COVID-19 Data Alliance (ICODA), an initiative funded by the Bill and Melinda Gates Foundation and Minderoo as part of the COVID-19 Therapeutics Accelerator and convened by Health Data Research (HDR) UK, in addition to support from the HDR UK BREATHE Hub. Several ICODA partners contributed to the study, including: Cytel (statistical support), the Odd Group (data visualization) and Aridhia Informatics (development of federated analysis using a standardized protocol ([Common API] https://github.com/federated-data-sharing/ ) to be used in future work). Additional contributors: We acknowledge the important contributions from the following individuals: A. C. Hennemann and D. Suguitani (patient partners from Prematuridade: Brazilian Parents of Preemies’ Association, Porto Alegre, Brazil); N. Postlethwaite (implementation of processes supporting the trustworthy collection, governance and analysis of data from ICODA, HDR UK, London, UK); A. S. Babatunde (led data acquisition from University of Uyo Teaching Hospital, Uyo, Nigeria); N. Silva (data quality, revision and visualization assessment from Methods, Analytics and Technology for Health (M.A.T.H) Consortium, Belo Horizonte, Brazil); J. Söderling (data management from the Karolinska Institutet, Stockholm, Sweden). We also acknowledge the following individuals who assisted with data collection efforts: R. Goemaes (Study Centre for Perinatal Epidemiology (SPE), Brussels, Belgium); C. Leroy (Le Centre d'Épidémiologie Périnatale (CEpiP), Brussels, Belgium); J. Gamba and K. Ronald (St. Francis Nsambya Hospital, Kampala, Uganda); M. Heidarzadeh (Tabriz Medical University, Tabriz, Iran); M. J. Ojeda (Pontificia Universidad Católica de Chile, Santiago, Chile); S. Nangia (Lady Hardinge Medical College, New Delhi, India); C. Nelson, S. Metcalfe and W. Luo (Maternal Infant Health Section of the Public Health Agency of Canada, Ottawa, Canada); K. Sitcov (Foundation for Health Care Quality, Seattle, United States); A. Valek (Semmelweis University, Budapest, Hungary); M. R. Yanlin Liu (Mater Data and Analytics, Brisbane, Australia). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Funding Information: Funding and in-kind support: This work was supported by the International COVID-19 Data Alliance (ICODA), an initiative funded by the Bill and Melinda Gates Foundation and Minderoo as part of the COVID-19 Therapeutics Accelerator and convened by Health Data Research (HDR) UK, in addition to support from the HDR UK BREATHE Hub. Several ICODA partners contributed to the study, including: Cytel (statistical support), the Odd Group (data visualization) and Aridhia Informatics (development of federated analysis using a standardized protocol ([Common API] https://github.com/federated-data-sharing/) to be used in future work). Additional contributors: We acknowledge the important contributions from the following individuals: A. C. Hennemann and D. Suguitani (patient partners from Prematuridade: Brazilian Parents of Preemies’ Association, Porto Alegre, Brazil); N. Postlethwaite (implementation of processes supporting the trustworthy collection, governance and analysis of data from ICODA, HDR UK, London, UK); A. S. Babatunde (led data acquisition from University of Uyo Teaching Hospital, Uyo, Nigeria); N. Silva (data quality, revision and visualization assessment from Methods, Analytics and Technology for Health (M.A.T.H) Consortium, Belo Horizonte, Brazil); J. Söderling (data management from the Karolinska Institutet, Stockholm, Sweden). We also acknowledge the following individuals who assisted with data collection efforts: R. Goemaes (Study Centre for Perinatal Epidemiology (SPE), Brussels, Belgium); C. Leroy (Le Centre d'Épidémiologie Périnatale (CEpiP), Brussels, Belgium); J. Gamba and K. Ronald (St. Francis Nsambya Hospital, Kampala, Uganda); M. Heidarzadeh (Tabriz Medical University, Tabriz, Iran); M. J. Ojeda (Pontificia Universidad Católica de Chile, Santiago, Chile); S. Nangia (Lady Hardinge Medical College, New Delhi, India); C. Nelson, S. Metcalfe and W. Luo (Maternal Infant Health Section of the Public Health Agency of Canada, Ottawa, Canada); K. Sitcov (Foundation for Health Care Quality, Seattle, United States); A. Valek (Semmelweis University, Budapest, Hungary); M. R. Yanlin Liu (Mater Data and Analytics, Brisbane, Australia). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Publisher Copyright: © 2023, The Author(s).Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from −90% to +30%, were reported in many countries following early COVID-19 pandemic response measures (‘lockdowns’). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95–0.98, P value <0.0001), second (0.96, 0.92–0.99, 0.03) and third (0.97, 0.94–1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96–1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88–1.14, 0.98), third (0.99, 0.88–1.12, 0.89) and fourth (1.01, 0.87–1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02–1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03–1.15, 0.002), third (1.10, 1.03–1.17, 0.003) and fourth (1.12, 1.05–1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways.Peer reviewe

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways

Changes in preterm birth and stillbirth during COVID-19 lockdowns in 26 countries.

Preterm birth (PTB) is the leading cause of infant mortality worldwide. Changes in PTB rates, ranging from -90% to +30%, were reported in many countries following early COVID-19 pandemic response measures ('lockdowns'). It is unclear whether this variation reflects real differences in lockdown impacts, or perhaps differences in stillbirth rates and/or study designs. Here we present interrupted time series and meta-analyses using harmonized data from 52 million births in 26 countries, 18 of which had representative population-based data, with overall PTB rates ranging from 6% to 12% and stillbirth ranging from 2.5 to 10.5 per 1,000 births. We show small reductions in PTB in the first (odds ratio 0.96, 95% confidence interval 0.95-0.98, P value <0.0001), second (0.96, 0.92-0.99, 0.03) and third (0.97, 0.94-1.00, 0.09) months of lockdown, but not in the fourth month of lockdown (0.99, 0.96-1.01, 0.34), although there were some between-country differences after the first month. For high-income countries in this study, we did not observe an association between lockdown and stillbirths in the second (1.00, 0.88-1.14, 0.98), third (0.99, 0.88-1.12, 0.89) and fourth (1.01, 0.87-1.18, 0.86) months of lockdown, although we have imprecise estimates due to stillbirths being a relatively rare event. We did, however, find evidence of increased risk of stillbirth in the first month of lockdown in high-income countries (1.14, 1.02-1.29, 0.02) and, in Brazil, we found evidence for an association between lockdown and stillbirth in the second (1.09, 1.03-1.15, 0.002), third (1.10, 1.03-1.17, 0.003) and fourth (1.12, 1.05-1.19, <0.001) months of lockdown. With an estimated 14.8 million PTB annually worldwide, the modest reductions observed during early pandemic lockdowns translate into large numbers of PTB averted globally and warrant further research into causal pathways

In Depth Analysis of the Leading Causes of Maternal Mortality Due to Cesarean Section in Iran

Objective: Despite the declining trend of maternal mortality (MMR) in Iran between 1990 and 2013, direct causes are still the major reasons for maternal death. One of these direct causes is complications of cesarean section (CS). Since the rate of CS in Iran is quite high (47.9%) and the trend continues to rise, there is an alarming threat of the possibility of increasing MMR in the country as a result of cesarean section complications, especially in repeated cases. In this study, we attempted to determine the indications of CS in reported maternal mortality, with special attention to risk factors predisposing to CS and/or to maternal mortality. Materials and methods: A retrospective study was implemented for the period between March 2009 and March 2012. All nationally reported data regarding maternal death during pregnancy, labor and 42 days after parturition during these 3 years was collected and input to software specially designed for this project. Subsequently, cases of maternal death related to pregnancy termination by cesarean section were selected for analysis. Results: There were 393 cases of maternal death with cesarean section as the termination method. Indications of CS were mostly emergency and repeat and the leading causes of death were postpartum hemorrhage and hypertensive disorders. Most of these deaths occurred in academic hospitals and the most common type of delay was brought about by hospital management, specifically personnel issues. Conclusion: Based on this study, acknowledging CS as a serious health threat endangering every achievement in the maternal health program is the most important policy and efforts should be focused on provision of guidelines for realistic CS indications, standardized CS procedures, and post CS care as well as propagation of training courses in risk management and high risk case-finding protocols

Effect of ambient air pollution and temperature on the risk of stillbirth: a distributed lag nonlinear time series analysis

OBJECTIVES: This study aimed to determine the effect of ambient air pollution and temperature on stillbirth in Tehran. METHODS: In this time-series study, the effect of O(3) (ppb), CO (ppm), NO(2) (ppb), SO(2) (ppb), PM(2.5) (μg/m(3)), and minimum, maximum, and mean daily temperature (°C) on stillbirth was evaluated in Tehran, Iran between March 2015 and March 2018. Using a quasi-Poisson regression model in combination with a Distributed Lag Non-linear Models (DLNM), the Relative Risk (RR) was estimated through comparing the high temperature (99th, 95th, and 75th percentiles) and low temperature (1st, 5th, and 25th percentiles) with the median. The effect of air pollution was estimated for each 1-, 5-, or 10-unit increase in the concentration during lags (days) 0–21. RESULTS: Among air pollutants, only a 5-ppm increase in the SO(2) concentration in lag 0 increased the risk of stillbirth significantly (RR = 1.062; 1.002–1.125). The largest effect of heat was observed while comparing the 99th percentile of minimum daily temperature (26.9 °C) with the median temperature (13.2 °C), which was not statistically significant (RR = 1.25; 0.95–1.65). As for cold, a non-significant protective effect was observed while comparing the 1st percentile of maximum daily temperature (3.1 °C) with the median temperature (23.2 °C) (RR = 0.92; 0.72–1.19). CONCLUSION: Each 5-ppm increase in the mean daily SO(2) in lag 0 increased the risk of stillbirth by 6% while other air pollutants had no significant effects on stillbirth. In lags 0 and 1, the heat increased the risk of stillbirth while the cold had protective effects, which were not statistically significant

Profile of neonatal mortality in the Islamic Republic of Iran in 1391

Background: The first duty of any government is to ensure the health of&nbsp;its children and neonates. Today's countries are classified as declining mortality in this group. To increase neonatal survival rate, classified causes of newborn mortality are&nbsp;the&nbsp;Core&nbsp;Strategy and&nbsp;Policies. This study was aimed to determine the classification of causes of&nbsp;neonatal death&nbsp;in Iran. Methods: Neonatal mortality&nbsp;refers to deaths of young children, typically those less than 28 days of age. It is measured by the neonatal mortality rate (NMR), which is the number of deaths of neonates per 1000 live births.This study was used data from 11693 neonatal deaths (from 22 weeks gestational age to neonatal death less than 30 days), in IRAN's hospitals in 2012 that registered in the Perinatal Mortality Surveillance System (hospital-based system). Demographic characteristics and other factors associated with neonatal death were investigated. To aid in cause of death analyses, burden of disease analyses, and comparative risk assessment we classified the causes of death according to International statistical classification of diseases version 10 (ICD 10), divided into three cause mortality strata. Results: The most common cause of neonatal mortality was &quot;certain conditions originating in the perinatal period&quot; (77.92%) with the highest incidence of &nbsp;&quot;disorders related to length of gestation and fetal growth&quot; (37.7%) in this group. Also 2419 (20/82%) of deaths caused by &quot;Congenital malformations, deformations and chromosomal abnormalities&quot; and 147 (1/26%) cases had occurred as a result of &quot;accidents and injuries&quot;. The greatest cause of death in the neonates with weight over one thousand grams was &quot;certain conditions originating in the perinatal period&quot; (71/29%), with the highest percentage in the disorders related to &quot;length of gestation and fetal growth&quot; (29/65%). Conclusion: Policies and interventions should be in line with the priority given to the most common causes of death in prenatal care, prevention and treatment of complications of pregnancy and delivery

Profile of neonatal mortality in Iran in 1391

Background: The first duty of any government is to ensure the health of its children and neonates. Today's countries are classified as declining mortality in this group. To increase neonatal survival rate, classified causes of newborn mortality are the core strategy and policies. This study was aimed to determine the classification of causes of neonatal death in Iran. Methods: Neonatal mortality refers to deaths of young children. It is measured by the neonatal mortality rate (NMR), which is the number of deaths of neonates per 1000 live births. This study was used data from 11693 neonatal deaths (from 22 weeks gestational age to neonatal death less than 30 days), in Iran's hospitals in 2012 that registered in the perinatal mortality surveillance system (hospital-based system). Demographic characteristics and other factors associated with neonatal death were investigated. To aid in cause of death analysis, burden of disease analysis, and comparative risk assessment we classified the causes of death according to international statistical classification of diseases version 10 (ICD 10), divided into three cause mortality strata. Results: Results showed the most common cause of neonatal mortality was &quot;certain conditions originating in the perinatal period&quot; (77.92%) with the highest incidence of &quot;disorders related to length of gestation and fetal growth&quot; (37.7%) in this group. Also it shows that 20.82% of deaths caused by &quot;congenital malformations, deformations and chromosomal abnormalities&quot; and 1.26% cases had occurred as a result of &quot;accidents and injuries&quot;. The greatest cause of death in the neonates with weight over one thousand grams was &quot;certain conditions originating in the perinatal period&quot; (71.29%), with the highest percentage in the disorders related to &quot;length of gestation and fetal growth&quot; (29.65%). Conclusion: According to this study the &quot;certain conditions originating in the perinatal period&quot; special &quot;disorders related to length of gestation and fetal growth&quot; was the main cause of neonatal mortality. Also &quot;congenital malformations, deformations and chromosomal abnormalities&quot; was the second cause of neonatal mortality

Neonatal mortality rate in Iran: the Iranian Perinatal Mortality Surveillance System

Background: Neonatal mortality is the major proportion of children mortality under five years and it is considered as the main health indicator in the first year of life. This paper has aimed to review the neonatal mortality in the numbers recorded at the Iranian Perinatal Mortality Surveillance System (IPMSS) by Iran Ministry of Health and Medical Education. Methods: A descriptive study was done in 2014. For assessment of sampling quality and quantity, 24 hospitals randomly were selected. Recorded information, related to perinatal mortality (deaths from 22 completed weeks of gestation until 30 completed days after birth inclusive of stillbirths and neonatal mortality) from selected hospitals, was compared with recorded data in IPMSS. Results: Results showed that, out of 1,725 perinatal deaths occurred in hospitals, 1,480 (85.80%) deaths were recorded in IPMSS. Of 1,041 neonatal deaths that occurred in hospitals (in hospital wards and delivery rooms), 875 (84.05%) were in IPMSS. It shows that a correction coefficient for hospital neonatal mortality was 1.1904. Based on analyzing process, correction coefficients for stillbirth reported by hospitals, stillbirth for all over the country and perinatal death were 1.130, 1.1775 and 1.2443, respectively. Considering these correction coefficients – that enabled to calculate 15,130 neonatal deaths – and 1,421,689 live births (according to Statistics Center) in 2012, neonatal mortality rate was 10.64 in 1,000 live births. Conclusion: Our data showed some problems in the registration system. Although implementation and supervision of such Surveillance System are not easy, they are essential and provide valuable data in perinatal audit and neonatal health care practices

Determination of Predictive Power of CRIB-II and SNAPPE-II in Mortality Risk of Neonates with Low Gestational Age or Birth Weight Admitted to the Neonatal Intensive Care Unit

Background: Risk scoring systems evaluate neonatal outcomes using perinatal and neonatal status. The present study aimed to predict the mortality risk of preterm or low birth weight infants using the Clinical Risk Index for Babies (CRIB-II) and Score for Neonatal Acute Physiology Perinatal Extension (SNAPPE-II) scoring systems.Methods: This prospective cohort study investigated the preterm neonates admitted to the Neonatal Intensive Care Unit (NICU) of Vali-e-Asr Hospital, Tehran, Iran, with the birth weight of ˂1500g or a gestational age˂32weeks using the CRIB-II and SNAPPE-II scoring systems within the first 12 h after birth. The area under the curve, sensitivity, specificity, positive and negative predictive values of the scoring systems, as well as the association between neonate factors and neonatal death were calculated in this study.Results: Out of 344 neonates under study, 253casessurvived after24hof birth and 91 newborns died. The total CRIB-II scores in survived and deceased infants were 6.12 and 10.28, respectively. The area under the receiver operating characteristic (ROC) curve with a cut-off point of 8.5 was obtained at 0.838. Moreover, the sensitivity, specificity, positive predictive value, and negative predictive value were estimated at 74.4%, 78.65%, 55.37%, and 89.68%, respectively, for the CRIB-II system. Total scores of SNAPPE-II in survived and deceased infants were 16.9 and 51.6, respectively. The area under the ROC curve with a cut-off point of 27.5 was determined at 0.887. Sensitivity (84.44%) and specificity (79.05%) were calculated for the SNAPPE-II. Furthermore, positive and negative predictive values were 58.91% and 93.46%, respectively.Conclusion: This study demonstrated that the CRIB-II and SNAPPE-II scoring systems can be useful mortality predictors for at-risk neonates

Effects of Community-Based Newborn Care Intervention on Neonate Health Status in a District of Tehran (Iran)

Objective: To identify the effects of community-based interventions on the Neonatal Health Index in one district of Tehran-Iran. Materials and methods: A community and healthcare center-based study was carried out from January 2011 through September 2014. The population of the study included newborns from mothers residing in the 4th district of Tehran, Iran. Demographic data of mothers and infants were recorded in questionnaires before and after intervention. Interventions were implemented in hospitals, participants' homes, and health centers. The primary outcomes were comparison of mean birth weight, weight gain during the first 3-7 days, first week visit rate, hospitalization rate between the before and after intervention groups. Results: The populations in the before and after intervention groups were 274 and 250, respectively. A significant difference was seen between the gestational ages (P value = 0.007) of the two groups. Mean birth height in the first group was 50.35 ± 3.48 and in the second group was 55 ± 5.32 cm (P value = 0.04). Neonatal complications in the second group were 6.9% lower than in the first group (P value = 0.048). In the first group 41 neonates (15%) were hospitalized in the NICU while in the second group 12 cases (4.8%) were hospitalized (P value = 0.018). Seven cases (2.6%) in the first group and one case (0.4%) in the second group were resuscitated (P value = 0.0001). Conclusion: The results of implementing community-based newborn care strategies witnessed at the first week postnatal visit included improvements inneonatal gestational growth, management of neonates with potentially serious illnesses, diagnosis of warning signs and neonatal care practices