Trends, Patterns and Cause-Specific Determinant Of Perinatal Mortality at Geita Regional Referral Hospital In Tanzania: A Hospital-Based Retrospective Study

Trends, Patterns and Cause-Specific Determinant Of Perinatal Mortality at Geita Regional Referral Hospital In Tanzania: A Hospital-Based Retrospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trends, Patterns and Cause-Specific Determinant Of Perinatal Mortality at Geita Regional Referral Hospital In Tanzania: A Hospital-Based Retrospective Study Mfaume Kibwana, Sadock P. Mathias, Omary Sukari This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4395259/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Perinatal mortality is a sensitive issue that concerns the lives of newborn babies. In Tanzania, the perinatal mortality rate is high, accounting for 38/1000 live births. Objective A study titled "Patterns, Trends, and Specific Determinants of Perinatal Mortality" was conducted at Geita Regional Referral Hospital in 2023/24. Results The study found that several factors were significantly associated with perinatal deaths, including premature complication, severe birth asphyxia, unknown factors, neonatal sepsis, and aspiration pneumonia, anemia in pregnancy, eclampsia, pre-eclampsia, and malaria in pregnancy. Recommendation: The study recommended several measures, including using Community Health Care workers and FHCWs to offer health education on focused antenatal care and safe motherhood, improving ANC clinics, providing proper and increased allocation of human resources, and allowing trained nurses or anesthetists to perform caesarian sections. Pregnant women should also be alerted about their subsequent visit/appointment. Motivations, coating folic acid tablets and combining them with antiemetics to become user-friendly, additionally, traditional medicine labs should take samples of local herbs used by pregnant mothers to detect their chemical compositions and provide advice accordingly. In conclusion Reducing perinatal mortality in the Geita region requires a multisectoral approach and more investment we can make save the lives of many newborn babies BACKGROUND Perinatal mortality is a significant public health challenge in low and middle-income countries. It refers to the death of any newborn that occurs between GA of 28 and 7 days after birth. Globally, about 2.5 million children die in the first month after birth, which amounts to 7000 neonatal deaths every day. Unfortunately, in Tanzania, efforts to reduce perinatal mortality did not meet the United Nations Millennium Development Goal (MDG) in 2020. The highest burden of perinatal deaths is in developing countries, which account for about 98% of all deaths. Tanzania has a high perinatal mortality rate estimated to be 69/1000 births in 2004 and 38/1000 in 2022. A recent national survey reported perinatal mortality for pregnancies lasting seven months or more to be 36/1000, ranging between 24/1000 and 60/1000 in the different zones in sub-Saharan Africa (SSA), neonatal mortality has historically been higher in rural areas compared with urban ones and is posited to be related to a combination of socioeconomic factors (maternal education, nutrition, care affordability) and care accessibility (more births occurring in health facilities, shorter distance and travel time to health facilities( 1 )Yet some countries, particularly in sub-Saharan Africa including Tanzania still have high rates of under-5 mortality in 2023 ( 2 ). Unless these countries can accelerate reductions in child deaths at an extraordinary pace, their achievement of proposed SDG targets is unlikely. Improving the evidence base on drivers that might hasten the pace of progress for child survival, ranging from cost-effective intervention packages to innovative financing mechanisms, is vital to charting the pathways for ultimately ending preventable child deaths by 2030( 3 ). Perinatal deaths continue to be a major concern in low-resource settings, with inappropriate maternal health care provision during pregnancy, labor, delivery, and postpartum periods being one of the main contributing factors ( 4 ). Lack of proper newborn care immediately after delivery and within the first 7 days of life also plays a significant role. To improve under-five mortality rates (U5MRs) in Tanzania, it is essential to have nationally representative and country-specific evidence on the risk factors for neonatal, post-neonatal, and infant, child, and U5 mortalities. Unfortunately, this data is scarce due to the dearth of vital registration or population-based surveillance data at the national level. To achieve the SDG-3 agenda, relevant data is necessary to guide efforts and refine programs for high-priority groups. This study aimed to investigate the trends and determinants of neonatal, post-neonatal, infant, child, and U5 mortalities in Tanzania between 2004 and 2016 ( 5 ). It is disheartening to know that the first month of life is the most vulnerable period in terms of child survival. Shockingly, almost half of all under-five deaths in 2020 occurred during the neonatal period, which is the first 28 days of life. In comparison to 1990, this figure has increased from 40 to 47 per cent. Unfortunately, the chances of survival for children start to diverge from the earliest ages. Sub-Saharan Africa has the highest neonatal mortality rate in the world, with 27 deaths per 1,000 live births, followed by Southern Asia at 23 deaths ( 6 ). It is alarming to learn that a child born in sub-Saharan Africa is 11 times more likely to die in the first month of life than a child born in the region of Australia and New Zealand. Also, a child born in a high-income country has a risk of death in the first month that is just one-tenth the risk to a child born in a low-income country. At the country level, neonatal mortality rates in 2020 ranged from 1 death per 1,000 live births to 44. The risk of dying before the 28th day of life for a child born in the highest-mortality country was about 56 times higher than in the lowest-mortality country. These statistics highlight the need for more attention and resources to be directed towards neonatal care and support, particularly in low-income countries ( 7 ). To successfully implement perinatal death reviews, it is crucial to clearly define the roles and responsibilities of those involved and to monitor progress routinely. In low-income settings, perinatal death reviews can be implemented effectively and sustained by focusing on learning, solution-oriented responses, influencing those in positions of authority, holding individuals accountable for results, and ensuring observable quality of care improvements. These measures are essential for making a positive impact on maternal and neonatal mortality rates ( 8 ). However, despite this improvement, the country has not yet achieved the Millennium Development Goal of reducing perinatal, neonatal, and maternal mortality rates. This is especially true for Geita Regional Referral Hospital, where there are still concerns regarding the high number of deaths per year, with reports indicating around 900 PMR cases in 2022/23. Trends of perinatal deaths It is crucial to recognize that over 51,000 newborns lose their lives annually in Tanzania, with the majority of these deaths being preventable ( 9 – 11 ). Although there has been a decline in the infant mortality rate in Tanzania, there remains a significant gap in under-5 mortality rates between low-income and high-income countries ( 12 – 14 ). It is imperative to implement strategies aimed at preventing perinatal deaths, such as providing counseling on pregnancy spacing and promoting increased contraceptive use ( 15 , 16 ). Furthermore, enhancing maternal and newborn care and addressing factors like education and family size can play a vital role in reducing perinatal mortality ( 17 , 18 ). However, it is important to acknowledge the challenges in obtaining high-quality data on maternal and newborn deaths and their causes, as this data is essential for informing policy decisions and implementing evidence-based interventions ( 19 ). Understanding the magnitude and clinical causes of maternal and perinatal mortality are basic requirements for policy setting, program design, innovation testing, and the implementation of evidence based interventions. Outcome captured at health facilities presents an opportunity for health care staff and decision-makers to reflect on what they could do better ( 20 – 22 ). Various factors such as place of residence, occupation, education level, and ANC attendance are significantly associated with Birth Preparedness and Complications Readiness ( 23 ). According to WHO, it is recommended to end preventable deaths of newborns and children under 5 years of age by 2030. The Geita Region in Tanzania, like other sub-Saharan African countries, requires attention to reduce perinatal mortality. It is worth noting that over the past decade, Tanzania has experienced a slight decrease in the perinatal mortality rate ( 24 ). A majority of maternal causes and fetal causes of perinatal mortality are preventable through supportive working aids and focused antenatal health care. Strategies to reduce this gap need to address the overall resource situation and general health system characteristics. However, given the limited resources in African countries, it may be important to target groups of particularly vulnerable mothers and babies in attempts to reduce mortality ( 25 ). The study aimed to determine the specific factors contributing to perinatal mortality to improve maternal and child health services to reduce maternal and perinatal mortality rates, health promotion, society ownership, awareness, and informing policy. MATERIAL AND METHODS Our study design was carefully crafted to ensure a comprehensive understanding of the issue at hand. We interviewed healthcare workers with varying levels of experience and conducted a simple random sampling of mothers who lost their babies. We included nurses, doctors, paraprofessionals, and mothers who lost their babies at the postnatal unit, as well as pregnant women who experienced perinatal death in their previous pregnancy. We evaluated all departments, including antenatal clinics and labor wards, to gain insight into what happens from pregnancy to delivery. We also interviewed workers from M-mama and traditional birth attendants to ensure a holistic approach to our research. We collected both qualitative and quantitative data, with interviews being recorded using Android devices with a super recorder application installed. Transcription and translation were conducted, and qualitative analysis was done thematically. For quantitative data, we collected and analyzed discussed perinatal mortality records for one year using SPSS version 23. While our study provides valuable insights, it is important to note that inadequate funding limited its scope to GRRH which may limit the generalizability of the findings to other settings. If we had more resources, we could have extended this study to district council hospitals to gain a broader understanding of the situation in the Geita region. Nonetheless, our findings offer important information that can be used to address this issue and improve the care provided to mothers and babies. RESULTS Table 1:1 Represents perinatal mortality among pregnancy women by Social demographic characteristics in Geita region. Variables Macerated Stillbirth (MSB) Fresh Stillbirth (FSB) Early perinatal deaths (EPD) Age < 20 21-30 Above 30 73 (31.88%) 18 (19.56%) 12 (35.53%) 98 (42.79%) 53 (57.61%) 13 (38.24%) 58 (25.33%) 21 (22.83%) 9 (26.23%) Education level No education primary Secondary college University 29 (69.05%) 6 (14.28%) 7 (16.67%) 9 (69.23%) 3 (23.08%) 1 (7.69%) 3 (33.33%) 2 (22.22%) 4 (44.45%) 1 (100.0%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) Unknown causes 169 (73.79%) 1 (1.09%) 0 (0.00%) Peripartum birth asphyxia 12 (5.24%) 0 0 (0.00%) Intrapartum birth asphyxia 20 (8.73%) 71 (77.17%) 0 (0.00%) Severe birth asphyxia 0 (0.00%) 5 (5.43%) 20 (58.82%) antepartum Haemorrhage (APH) 0 (0.00%) 2 (2.17%) 0 (0.00%) Malaria in pregnancyy 2 (0.87%) 0 (0.00%) 1 (2.94%) Eclampsia 10 (4.37%) 1 (1.09%) 0 (0.00%) Premature complication 0 (0.00%) 0 (0.00%) 8 (23.53%) Pre-Eclampsia 3 (1.31%) 5 (5.43%) 0 (0.00%) Hypertension 7 (3.05%) 2 (2.17%) 0 (0.00%) Congenital malformation 0 (0.00%) 5 (5.43%) 0 (0.00%) Hepatitis B 1 (0.44%) 0 (0.00%) 0 (0.00%) syphilis 0 (0.00%) 0 (0.00%) 1 (2.94%) Anemia in pregnancy 3 (1.31%) 0 (0.00%) 1 (2.94%) Sepsis 2 (0.87%) 0 (0.00%) 2 (5.88%) Aspiration pneumonia 0 (0.00%) 0 (0.00%) 1 (2.94%) Source; Geita Regional Referral Hospital (GRRH) discussed perinatal deaths The table 1.1 above represents perinatal mortality among pregnant women in the Geita region, based on their social demographic characteristics. The data is divided into three categories: Macerated Stillbirth (MSB), Fresh Stillbirth (FSB), and Early Perinatal Deaths (EPD). The table shows that the highest percentage of MSB occurred among pregnant women above the age of 30 (35.53%), while the highest percentage of FSB occurred among pregnant women between the ages of 21-30 (57.61%). The highest percentage of EPD occurred among pregnant women between the ages of 21-30 (22.83%). In terms of education level, the highest percentage of MSB occurred among pregnant women with no education (69.05%), while the highest percentage of FSB occurred among pregnant women with secondary education (44.45%). The only case of EPD in the education category occurred among pregnant women with college education. The data also shows that unknown causes were responsible for the highest percentage of MSB (73.79%) while intrapartum birth asphyxia was responsible for the highest percentage of FSB (77.17%). Severe birth asphyxia was responsible for the highest percentage of EPD (58.82%). Table 1: 2 Multiple linear regressions to show Perinatal mortality associated factors. Model B Std. Error t Sig. Age categories 21-30 9.23 2.462 3.386 0.0241 31 and above 8.743 1.956 2.847 0.0458 Education level Primary 5.39 2.65 2.401 0.148 Secondary 2.026 4.641 0.744 0.461 Collage 1.478 5.923 0.593 0.037 Unknown cause 4.583 1.582 2.896 0.006 Premature complication 5.65 2.063 -2.738 0.009 Severe birth asphyxia 5.25 1.769 -2.967 0.005 Neonatal sepsis 6.158 2.961 -2.111 0.04 Anaemia 7.27 4.035 -1.797 0.079 Aspiration pneumonia 7.279 2.961 -2.449 0.018 Anaemia in pregnancy 6.211 1.831 -2.111 0.04 Hypertension 6.456 4.035 -1.549 0.129 Eclampsia 7.25 2.791 -2.449 0.018 Pre-eclampsia 5.523 2.063 -2.544 0.015 Malaria in pregnancy 8.23 2.238 -3.24 0.002 Syphilis 7.15 4.265 1.797 0.079 Hepatitis B 9.214 4.035 1.797 0.079 Congenital malformation 3.251 2.041 -0.806 0.425 Peripartum asphyxia 2.572 4.015 0.682 0.499 (Constant) 8.25 1.119 7.373 0.000 Source; (GRRH) discussed perinatal deaths Table 1.2 shows the results of a multiple linear regression analysis that was conducted to identify the factors associated with perinatal mortality. The table has different columns that include Model, B, Std. Error, t, and Sig. The Model column shows the independent variables that were included in the analysis, while the B column shows the beta coefficients, which represent the strength and direction of the relationship between each independent variable and the dependent variable (perinatal mortality). The Std. Error column shows the standard error of the estimate, which indicates how far the observed values are likely to deviate from the true regression line. The t column shows the t-value, which measures the size of the difference relative to the variation in the sample data. Finally, the Sig. column shows the significance level, which indicates the probability of obtaining the observed results by chance. From the table, we can see that several factors are associated with perinatal mortality, including age categories, education level, and various health conditions such as premature complication, severe birth asphyxia, neonatal sepsis, aspiration pneumonia, among others. The results suggest that older mothers (31 and above) have a higher risk of perinatal mortality than younger mothers (21-30). Furthermore, it appears that having a college education is associated with a lower risk of perinatal mortality compared to having only a primary or secondary education. Additionally, several health conditions are associated with an increased risk of perinatal mortality, including Unknown cause, premature complication, severe birth asphyxia, and neonatal sepsis, and aspiration pneumonia, malaria in pregnancy, eclampsia, pre-eclampsia, syphilis, and hepatitis B. However, some factors such as congenital malformation and peripartum asphyxia do not appear to have a significant association with perinatal mortality. The constant term has a coefficient estimate of 8.25, which represents the expected level of perinatal mortality when all the other variables are equal to zero. The constant term is significant (p < 0.001), which indicates that there are other factors not included in the model that may also be associated with perinatal mortality. Table 2: Association between Sex of Children and perinatal mortality Variable Categories Macerated Stillbirth (MSB) Fresh Stillbirth (FSB) Early perinatal Mortality (EPM) Sex Male 98 (42.79%) 36 (39.13%) 13 (38.24%) Female 131 (57.21%) 56 (60.87%) 21 (61.76%) Total 229 (100%) 92 (100%) 34 (100%) Source; (GRRH) discussed perinatal deaths Table 2 shows the association between the sex of children and perinatal mortality. The variables are Macerated Stillbirth (MSB), Fresh Stillbirth (FSB), and Early Perinatal Mortality (EPM). The categories are Male and Female. The table shows that there were a total of 229 cases of perinatal mortality, out of which 42.79% were male and 57.21% were female. In terms of MSB, 98 cases were male and 131 were female. For FSB, 36 cases were male and 56 were female. Lastly, for EPM, 13 cases were male and 21 were female. The findings from the qualitative interviews reveal important insights into the challenges faced by mothers during pregnancy and childbirth. One of the key issues highlighted is the low antenatal attendance by mothers, with some attending as few as one to five visits instead of the recommended eight visits. One participant commented; "A lot of mothers are not aware of the importance of antenatal care and the risks associated with not attending early enough. Some mothers only come to the clinic to ask RCH card when they are already experiencing complications, which make it difficult to manage their health effectively."(Midwife RCH-Geita ) The lack of early visits can lead to serious health complications for both the mother and the baby, such as congenital malformations and malaria. A grandmultparous interviewed during the study commented; "I didn't see the need to attend antenatal clinics regularly since I was feeling okay, it was a fifth pregnancy and my four children were well. But when I developed complications later on, I regretted not attending all the visits." (Postnatal mother –GRRH) Furthermore, economic barriers and geographical location are also significant challenges, especially for mothers who live far away from the healthcare facility. In some cases, mothers may opt to seek the services of traditional birth attendants due to a lack of transport or financial resources. However, this can lead to delays in referral and treatment, which can have fatal consequences for both the mother and the baby. One participant commented; "I only attended two antenatal visits because the healthcare facility is far from my house and I don't have enough money to pay for transport. I know it's not enough, but what can I do? I have to look for money to feed my family." (FGD Pregnant RCH-Geita ) In addition to these challenges, there are also issues related to screening for pregnancy at ANC clinics, as well as the availability of skilled human resources for reproductive health. For instance, some mothers are not tested for certain conditions, while others face delays in getting referrals due to a lack of equipped ambulances or trained staff.one participant commented "I had to wait for hours before being referred to a hospital for further tests. The facility had no ambulance and the midwife had to call around to find a private vehicle to take me. It was a very stressful experience"(postnatal mother –GRRH) Overall, these findings underscore the need for better education and awareness among mothers, as well as improved access to healthcare services and skilled human resources. It is imperative that these issues are addressed to ensure better health outcomes for mothers and their babies. DISCUSSION The findings of this study highlight several factors that contribute to perinatal mortality in Geita Regional Referral Hospital. These factors include premature complications, severe birth asphyxia, neonatal sepsis, and aspiration pneumonia, anemia in pregnancy, eclampsia, pre-eclampsia, and malaria in pregnancy. The study also found that poor antenatal attendance and poor screening were significant contributing factors to these deaths. The findings of this study are consistent with previous research on perinatal mortality in low and middle-income countries. A study conducted in Nigeria found that maternal factors, including anemia, eclampsia, and antepartum hemorrhage, were significant contributors to perinatal mortality rates ( 26 ). Similarly, a study in Ghana found that maternal factors, including hypertension and anemia, were associated with increased perinatal mortality rates ( 27 ). Another study conducted in Tanzania found that poor antenatal attendance and inadequate prenatal care were significant contributing factors to perinatal mortality rates ( 28 ). The study recommended the use of community health workers to improve antenatal attendance and the provision of comprehensive prenatal care to reduce perinatal mortality rates. Previous research has also highlighted the importance of investing in maternal and child health to reduce perinatal mortality rates. The United Nations' Every Newborn Action Plan (ENAP) emphasizes the need for increased investment in maternal and child health to achieve the Sustainable Development Goals (SDGs) and reduce perinatal mortality rates ( 29 , 30 ). Overall, the findings of this study emphasize and highlights the need for a comprehensive approach to address perinatal mortality rates in low and middle-income countries, including Tanzania. By implementing the recommended measures and investing more in maternal and child health, we can make a significant impact in reducing perinatal mortality rates and achieving the the UN's Sustainable Development Goals. RECOMMENDATIONS There were several recommendations made during the discussion on improving maternal health. The participants agreed that providing education to mothers and involving the community in addressing pregnancy-related issues is crucial. Educating mothers on timely clinic attendance and the importance of seeking medical attention from service providers, particularly at the RCH clinic, is essential. The referral system needs to be improved, and clinics should prioritize testing mothers for all necessary tests upon arrival while also improving the skills of service providers. Mothers should be encouraged to seek medical attention early when they notice any health problems It was noted that many pregnant mothers do not use folic acid tablets due to mild adverse effects such as nausea and vomiting. Therefore, service providers should provide education to mothers about the use of medicines given to them. Additionally, all RCH commodities should be made readily available to reduce challenges, along with IPC compliance. Mothers should be encouraged to visit the clinic early so that any health problems can be diagnosed and treated early. Service providers' advice should also be followed. It is recommended that mothers attend eight visits, with each visit tested for HB and RBG, to improve maternal health. The transport system and decision-making for referrals and training provision should be improved, and on-the-job training for service providers should be provided. It was suggested that all pregnant women attending within 12 weeks of pregnancy or earlier be given the current card. Coating folic acid tablets and combining them with anti-emetics can help improve adherence to medication. Additionally, CHWs should remind pregnant women to attend subsequent visits within the appointment schedule. Men should also be involved and educated as they are decision-makers in the family. Male involvement is also crucial, and male partners/husbands should be educated about the importance of proper nutrition for both the mother and child. Conclusion To effectively reduce perinatal mortality in the Geita Region, it is necessary to adopt a multisectoral approach and invest more resources. By bringing together various sectors and stakeholders, we can work towards improving the quality of maternal care, increasing access to healthcare services, and addressing the underlying social and economic factors that contribute to poor health outcomes. With greater investment and collaboration, we can create a safer and healthier environment for mothers and their infants in the Geita Region. Abbreviations CODAC Causes of Death and Associated Conditions GRRH Geita Regional Referral Hospital MDG Millennium Development Goal PMR Perinatal Mortality Rate GA Gestational Age TZS Tanzanian Shillings MLCC Midwife-Led Continuity of Care. MOH Ministry of Health U5M Under 5 Mortality SDGs Sustainable Development Goals (ENAP) Every Newborn Action Plan NIMR National Institute for Medical Research of Tanzania UNCEF United Nations Children’s Fund WHO World Health Organization Declarations ACKNOWLEDGEMENT We would like to express our sincere gratitude to all the participants who participated in this study and shared their valuable time and experiences. We also thank the management of Geita Regional Referral Hospital for allowing us to conduct this study and providing necessary resources to facilitate the research. We are also grateful to the staff of the hospital for their cooperation and support during the data collection process. Special thanks go to our research assistants for their dedication and hard work in collecting and managing the data. Finally, we thank our families and friends for their support and encouragement throughout the study. Availability of data and materials The raw data used in this study were generated at Geita Regional Referral Hospital from the discussed perinatal deaths for quantitative data. Qualitative data were obtained through focused group discussions, in-depth interviews, and key informant interviews. The corresponding authors [SPM & MK] hold the data that support the findings of this study and they are available upon request. Ethical Approval The study protocol was reviewed and approved by the Ethics Committee of National Institute for Medical Research-Tanzania with approval number NIMR /HQ/R.8a/vol. IX/4510 before the commencement of the study. Informed consent was obtained from all participants, and their confidentiality and privacy were protected throughout the study. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. 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Progress on drinking water and sanitation: 2014 update. World Health Organization and United Nations Children's Fund; 2014. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4395259","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":310280724,"identity":"81a7ebf3-7927-4534-87f4-ed4568390ba0","order_by":0,"name":"Mfaume Kibwana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYDCCAwwMH0A0vwSYKyFDjBbGGSBacgYDYwNQCw/xWgxugLUwENbCd/t0YsPPtm1yxrebjz+6UWPBw8B++OgGfFokz+VubOxtu21sdudYYnPOMaDDeNLSbuDTYnCGd/sD3rbbidtu5Bg257ABtUjwmBHSsrHxb9vt+s0zQFr+EamlGWhLgoEEUEtuGxFaJEFaZM7dNpxxIy1xdm6fBA8bIb/wgRz2puy2PP+M5AOfc77VyfGzHz6GVwsmYCNN+SgYBaNgFIwCbAAAnvNOX07yB2IAAAAASUVORK5CYII=","orcid":"","institution":"Geita Regional Referral Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Mfaume","middleName":"","lastName":"Kibwana","suffix":""},{"id":310280725,"identity":"c8f7c9a8-7fdd-4368-89b3-5e29bb1ed700","order_by":1,"name":"Sadock P. Mathias","email":"","orcid":"","institution":"Geita Regional Referral Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sadock","middleName":"P.","lastName":"Mathias","suffix":""},{"id":310280726,"identity":"843302b0-64a5-4bef-a428-02985a4d7fdd","order_by":2,"name":"Omary Sukari","email":"","orcid":"","institution":"Presdent's Ofifice Regional Administration and Local Government-Geita","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Omary","middleName":"","lastName":"Sukari","suffix":""}],"badges":[],"createdAt":"2024-05-09 12:51:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4395259/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4395259/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59212161,"identity":"9df8ce57-28fa-4670-8f53-2e2847085515","added_by":"auto","created_at":"2024-06-27 17:41:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":434085,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4395259/v1/257c04f0-a75f-4dfc-ae30-0e0e07fa801c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trends, Patterns and Cause-Specific Determinant Of Perinatal Mortality at Geita Regional Referral Hospital In Tanzania: A Hospital-Based Retrospective Study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003ePerinatal mortality is a significant public health challenge in low and middle-income countries. It refers to the death of any newborn that occurs between GA of 28 and 7 days after birth. Globally, about 2.5\u0026nbsp;million children die in the first month after birth, which amounts to 7000 neonatal deaths every day. Unfortunately, in Tanzania, efforts to reduce perinatal mortality did not meet the United Nations Millennium Development Goal (MDG) in 2020. The highest burden of perinatal deaths is in developing countries, which account for about 98% of all deaths. Tanzania has a high perinatal mortality rate estimated to be 69/1000 births in 2004 and 38/1000 in 2022. A recent national survey reported perinatal mortality for pregnancies lasting seven months or more to be 36/1000, ranging between 24/1000 and 60/1000 in the different zones in sub-Saharan Africa (SSA), neonatal mortality has historically been higher in rural areas compared with urban ones and is posited to be related to a combination of socioeconomic factors (maternal education, nutrition, care affordability) and care accessibility (more births occurring in health facilities, shorter distance and travel time to health facilities(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)Yet some countries, particularly in sub-Saharan Africa including Tanzania still have high rates of under-5 mortality in 2023 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Unless these countries can accelerate reductions in child deaths at an extraordinary pace, their achievement of proposed SDG targets is unlikely. Improving the evidence base on drivers that might hasten the pace of progress for child survival, ranging from cost-effective intervention packages to innovative financing mechanisms, is vital to charting the pathways for ultimately ending preventable child deaths by 2030(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePerinatal deaths continue to be a major concern in low-resource settings, with inappropriate maternal health care provision during pregnancy, labor, delivery, and postpartum periods being one of the main contributing factors (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Lack of proper newborn care immediately after delivery and within the first 7 days of life also plays a significant role. To improve under-five mortality rates (U5MRs) in Tanzania, it is essential to have nationally representative and country-specific evidence on the risk factors for neonatal, post-neonatal, and infant, child, and U5 mortalities. Unfortunately, this data is scarce due to the dearth of vital registration or population-based surveillance data at the national level. To achieve the SDG-3 agenda, relevant data is necessary to guide efforts and refine programs for high-priority groups. This study aimed to investigate the trends and determinants of neonatal, post-neonatal, infant, child, and U5 mortalities in Tanzania between 2004 and 2016 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is disheartening to know that the first month of life is the most vulnerable period in terms of child survival. Shockingly, almost half of all under-five deaths in 2020 occurred during the neonatal period, which is the first 28 days of life. In comparison to 1990, this figure has increased from 40 to 47 per cent. Unfortunately, the chances of survival for children start to diverge from the earliest ages. Sub-Saharan Africa has the highest neonatal mortality rate in the world, with 27 deaths per 1,000 live births, followed by Southern Asia at 23 deaths (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). It is alarming to learn that a child born in sub-Saharan Africa is 11 times more likely to die in the first month of life than a child born in the region of Australia and New Zealand. Also, a child born in a high-income country has a risk of death in the first month that is just one-tenth the risk to a child born in a low-income country. At the country level, neonatal mortality rates in 2020 ranged from 1 death per 1,000 live births to 44. The risk of dying before the 28th day of life for a child born in the highest-mortality country was about 56 times higher than in the lowest-mortality country. These statistics highlight the need for more attention and resources to be directed towards neonatal care and support, particularly in low-income countries (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo successfully implement perinatal death reviews, it is crucial to clearly define the roles and responsibilities of those involved and to monitor progress routinely. In low-income settings, perinatal death reviews can be implemented effectively and sustained by focusing on learning, solution-oriented responses, influencing those in positions of authority, holding individuals accountable for results, and ensuring observable quality of care improvements. These measures are essential for making a positive impact on maternal and neonatal mortality rates (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, despite this improvement, the country has not yet achieved the Millennium Development Goal of reducing perinatal, neonatal, and maternal mortality rates. This is especially true for Geita Regional Referral Hospital, where there are still concerns regarding the high number of deaths per year, with reports indicating around 900 PMR cases in 2022/23.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eTrends of perinatal deaths\u003c/h2\u003e \u003cp\u003eIt is crucial to recognize that over 51,000 newborns lose their lives annually in Tanzania, with the majority of these deaths being preventable (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Although there has been a decline in the infant mortality rate in Tanzania, there remains a significant gap in under-5 mortality rates between low-income and high-income countries (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). It is imperative to implement strategies aimed at preventing perinatal deaths, such as providing counseling on pregnancy spacing and promoting increased contraceptive use (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Furthermore, enhancing maternal and newborn care and addressing factors like education and family size can play a vital role in reducing perinatal mortality (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, it is important to acknowledge the challenges in obtaining high-quality data on maternal and newborn deaths and their causes, as this data is essential for informing policy decisions and implementing evidence-based interventions (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnderstanding the magnitude and clinical causes of maternal and perinatal mortality are basic requirements for policy setting, program design, innovation testing, and the implementation of evidence based interventions. Outcome captured at health facilities presents an opportunity for health care staff and decision-makers to reflect on what they could do better (\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eVarious factors such as place of residence, occupation, education level, and ANC attendance are significantly associated with Birth Preparedness and Complications Readiness (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). According to WHO, it is recommended to end preventable deaths of newborns and children under 5 years of age by 2030. The Geita Region in Tanzania, like other sub-Saharan African countries, requires attention to reduce perinatal mortality. It is worth noting that over the past decade, Tanzania has experienced a slight decrease in the perinatal mortality rate (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA majority of maternal causes and fetal causes of perinatal mortality are preventable through supportive working aids and focused antenatal health care. Strategies to reduce this gap need to address the overall resource situation and general health system characteristics. However, given the limited resources in African countries, it may be important to target groups of particularly vulnerable mothers and babies in attempts to reduce mortality (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study aimed to determine the specific factors contributing to perinatal mortality to improve maternal and child health services to reduce maternal and perinatal mortality rates, health promotion, society ownership, awareness, and informing policy.\u003c/p\u003e \u003c/div\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cp\u003eOur study design was carefully crafted to ensure a comprehensive understanding of the issue at hand. We interviewed healthcare workers with varying levels of experience and conducted a simple random sampling of mothers who lost their babies. We included nurses, doctors, paraprofessionals, and mothers who lost their babies at the postnatal unit, as well as pregnant women who experienced perinatal death in their previous pregnancy. We evaluated all departments, including antenatal clinics and labor wards, to gain insight into what happens from pregnancy to delivery. We also interviewed workers from M-mama and traditional birth attendants to ensure a holistic approach to our research.\u003c/p\u003e \u003cp\u003eWe collected both qualitative and quantitative data, with interviews being recorded using Android devices with a super recorder application installed. Transcription and translation were conducted, and qualitative analysis was done thematically. For quantitative data, we collected and analyzed discussed perinatal mortality records for one year using SPSS version 23.\u003c/p\u003e \u003cp\u003eWhile our study provides valuable insights, it is important to note that inadequate funding limited its scope to GRRH which may limit the generalizability of the findings to other settings. If we had more resources, we could have extended this study to district council hospitals to gain a broader understanding of the situation in the Geita region. Nonetheless, our findings offer important information that can be used to address this issue and improve the care provided to mothers and babies.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eTable 1:1\u003c/strong\u003e \u003cstrong\u003eRepresents\u0026nbsp;\u003c/strong\u003eperinatal mortality among pregnancy women by Social demographic characteristics in Geita region.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"672\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003eMacerated Stillbirth (MSB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003eFresh Stillbirth (FSB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003eEarly perinatal deaths (EPD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" rowspan=\"4\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026lt; 20\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 21-30\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Above 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e73 (31.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"bottom\"\u003e\n \u003cp\u003e18 (19.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"bottom\"\u003e\n \u003cp\u003e12 (35.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e98 (42.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"bottom\"\u003e\n \u003cp\u003e53 (57.61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"bottom\"\u003e\n \u003cp\u003e13 (38.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e58 (25.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"bottom\"\u003e\n \u003cp\u003e21 (22.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"bottom\"\u003e\n \u003cp\u003e9 (26.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" rowspan=\"6\" valign=\"bottom\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;No education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;primary\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Secondary\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;college\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;University\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e29 (69.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"bottom\"\u003e\n \u003cp\u003e6 (14.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"bottom\"\u003e\n \u003cp\u003e7 (16.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e9 (69.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (23.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"bottom\"\u003e\n \u003cp\u003e1 (7.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (33.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (22.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"bottom\"\u003e\n \u003cp\u003e4 (44.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e1 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.06976744186046%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.13953488372093%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.7906976744186%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eUnknown causes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e169\u0026nbsp;(73.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u0026nbsp;(1.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003ePeripartum birth asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e12\u0026nbsp;(5.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eIntrapartum birth asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e20\u0026nbsp;(8.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e71\u0026nbsp;(77.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eSevere birth asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u0026nbsp;(5.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003e20\u0026nbsp;(58.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eantepartum Haemorrhage (APH)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u0026nbsp;(2.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eMalaria in pregnancyy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u0026nbsp;(0.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u0026nbsp;(2.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eEclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e10\u0026nbsp;(4.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u0026nbsp;(1.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003ePremature complication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u0026nbsp;(23.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003ePre-Eclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u0026nbsp;(1.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u0026nbsp;(5.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e7 (3.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u0026nbsp;(2.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eCongenital malformation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u0026nbsp;(5.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eHepatitis B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u0026nbsp;(0.44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003esyphilis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e1\u0026nbsp;(2.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eAnemia in pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u0026nbsp;(1.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"top\"\u003e\n \u003cp\u003e1\u0026nbsp;(2.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eSepsis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e2\u0026nbsp;(0.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u0026nbsp;(5.88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.01190476190476%\" valign=\"bottom\"\u003e\n \u003cp\u003eAspiration pneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.00595238095238%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.982142857142858%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u0026nbsp;(2.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource; Geita Regional Referral Hospital (GRRH) discussed perinatal deaths\u003c/p\u003e\n\u003cp\u003eThe table 1.1 above represents perinatal mortality among pregnant women in the Geita region, based on their social demographic characteristics. The data is divided into three categories: Macerated Stillbirth (MSB), Fresh Stillbirth (FSB), and Early Perinatal Deaths (EPD).\u003c/p\u003e\n\u003cp\u003eThe table shows that the highest percentage of MSB occurred among pregnant women above the age of 30 (35.53%), while the highest percentage of FSB occurred among pregnant women between the ages of 21-30 (57.61%). The highest percentage of EPD occurred among pregnant women between the ages of 21-30 (22.83%).\u003c/p\u003e\n\u003cp\u003eIn terms of education level, the highest percentage of MSB occurred among pregnant women with no education (69.05%), while the highest percentage of FSB occurred among pregnant women with secondary education (44.45%). The only case of EPD in the education category occurred among pregnant women with college education.\u003c/p\u003e\n\u003cp\u003eThe data also shows that unknown causes were responsible for the highest percentage of MSB (73.79%) while intrapartum birth asphyxia was responsible for the highest percentage of FSB (77.17%). Severe birth asphyxia was responsible for the highest percentage of EPD (58.82%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: 2\u0026nbsp;\u003c/strong\u003eMultiple linear regressions to show Perinatal mortality associated factors.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eAge categories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 21-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e9.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e3.386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.0241\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 31 and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e8.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.0458\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e4.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Collage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e5.923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eUnknown\u0026nbsp;cause\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e4.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003ePremature complication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e5.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-2.738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eSevere birth asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e5.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-2.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eNeonatal sepsis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e6.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-2.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eAnaemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e7.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e4.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-1.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eAspiration pneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e7.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-2.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eAnaemia in pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e6.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-2.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e6.456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e4.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-1.549\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eEclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e7.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-2.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003ePre-eclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e5.523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-2.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eMalaria in pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e8.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eSyphilis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e7.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e4.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eHepatitis B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e9.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e4.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003eCongenital malformation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e3.251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e-0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003ePeripartum asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e2.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e4.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.980551053484604%\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e8.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e1.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.614262560777957%\"\u003e\n \u003cp\u003e7.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.176661264181522%\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource; (GRRH) discussed perinatal deaths\u003c/p\u003e\n\u003cp\u003eTable 1.2 shows the results of a multiple linear regression analysis that was conducted to identify the factors associated with perinatal mortality. The table has different columns that include Model, B, Std. Error, t, and Sig.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The Model column shows the independent variables that were included in the analysis, while the B column shows the beta coefficients, which represent the strength and direction of the relationship between each independent variable and the dependent variable (perinatal mortality). The Std. Error column shows the standard error of the estimate, which indicates how far the observed values are likely to deviate from the true regression line. The t column shows the t-value, which measures the size of the difference relative to the variation in the sample data. Finally, the Sig. column shows the significance level, which indicates the probability of obtaining the observed results by chance.\u003c/p\u003e\n\u003cp\u003eFrom the table, we can see that several factors are associated with perinatal mortality, including age categories, education level, and various health conditions such as premature complication, severe birth asphyxia, neonatal sepsis, aspiration pneumonia, among others.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results suggest that older mothers (31 and above) have a higher risk of perinatal mortality than younger mothers (21-30). Furthermore, it appears that having a college education is associated with a lower risk of perinatal mortality compared to having only a primary or secondary education.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Additionally, several health conditions are associated with an increased risk of perinatal mortality, including Unknown cause, premature complication, severe birth asphyxia, and neonatal sepsis, and aspiration pneumonia, malaria in pregnancy, eclampsia, pre-eclampsia, syphilis, and hepatitis B.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;However, some factors such as congenital malformation and peripartum asphyxia do not appear to have a significant association with perinatal mortality.\u003c/p\u003e\n\u003cp\u003eThe constant term has a coefficient estimate of 8.25, which represents the expected level of perinatal mortality when all the other variables are equal to zero. The constant term is significant (p \u0026lt; 0.001), which indicates that there are other factors not included in the model that may also be associated with perinatal mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Association\u003c/strong\u003e between Sex of Children and perinatal mortality\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.627118644067796%\" valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.35593220338983%\" valign=\"top\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.864406779661017%\" valign=\"top\"\u003e\n \u003cp\u003eMacerated Stillbirth (MSB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eFresh Stillbirth (FSB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.152542372881356%\" valign=\"top\"\u003e\n \u003cp\u003eEarly perinatal Mortality (EPM)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.627118644067796%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.35593220338983%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.864406779661017%\" valign=\"top\"\u003e\n \u003cp\u003e98 (42.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e36 (39.13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.152542372881356%\" valign=\"top\"\u003e\n \u003cp\u003e13 (38.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.54320987654321%\" valign=\"top\"\u003e\n \u003cp\u003e131 (57.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.279835390946502%\" valign=\"top\"\u003e\n \u003cp\u003e56 (60.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.25102880658436%\" valign=\"top\"\u003e\n \u003cp\u003e21 (61.76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.925925925925927%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.54320987654321%\" valign=\"top\"\u003e\n \u003cp\u003e229 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.279835390946502%\" valign=\"top\"\u003e\n \u003cp\u003e92 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.25102880658436%\" valign=\"top\"\u003e\n \u003cp\u003e34 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource; (GRRH) discussed perinatal deaths\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 2 shows the association between the sex of children and perinatal mortality. The variables are Macerated Stillbirth (MSB), Fresh Stillbirth (FSB), and Early Perinatal Mortality (EPM). The categories are Male and Female. The table shows that there were a total of 229 cases of perinatal mortality, out of which 42.79% were male and 57.21% were female. In terms of MSB, 98 cases were male and 131 were female. For FSB, 36 cases were male and 56 were female. Lastly, for EPM, 13 cases were male and 21 were female.\u003c/p\u003e\n\u003cp\u003eThe findings from the qualitative interviews reveal important insights into the challenges faced by mothers during pregnancy and childbirth. One of the key issues highlighted is the low antenatal attendance by mothers, with some attending as few as one to five visits instead of the recommended eight visits. One participant commented;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;A lot of mothers are not aware of the importance of antenatal care and the risks associated with not attending early enough. Some mothers only come to the clinic to ask RCH card when they are already experiencing complications, which make it difficult to manage their health effectively.\u0026quot;(Midwife RCH-Geita\u003c/em\u003e)\u003c/p\u003e\n\u003cp\u003eThe lack of early visits can lead to serious health complications for both the mother and the baby, such as congenital malformations and malaria.\u0026nbsp;A grandmultparous interviewed during the study commented;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;I didn\u0026apos;t see the need to attend antenatal clinics regularly since I was feeling okay, it was a fifth pregnancy and my four children were well. But when I developed complications later on, I regretted not attending all the visits.\u0026quot; (Postnatal mother \u0026ndash;GRRH)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFurthermore, economic barriers and geographical location are also significant challenges, especially for mothers who live far away from the healthcare facility. In some cases, mothers may opt to seek the services of traditional birth attendants due to a lack of transport or financial resources. However, this can lead to delays in referral and treatment, which can have fatal consequences for both the mother and the baby.\u0026nbsp;One participant commented;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;I only attended two antenatal visits because the healthcare facility is far from my house and I don\u0026apos;t have enough money to pay for transport. I know it\u0026apos;s not enough, but what can I do? I have to look for money to feed my family.\u0026quot; (FGD Pregnant RCH-Geita\u003c/em\u003e)\u003c/p\u003e\n\u003cp\u003eIn addition to these challenges, there are also issues related to screening for pregnancy at ANC clinics, as well as the availability of skilled human resources for reproductive health. For instance, some mothers are not tested for certain conditions, while others face delays in getting referrals due to a lack of equipped ambulances or trained staff.one participant commented\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;I had to wait for hours before being referred to a hospital for further tests. The facility had no ambulance and the midwife had to call around to find a private vehicle to take me. It was a very stressful experience\u0026quot;(postnatal mother \u0026ndash;GRRH)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOverall, these findings underscore the need for better education and awareness among mothers, as well as improved access to healthcare services and skilled human resources. It is imperative that these issues are addressed to ensure better health outcomes for mothers and their babies.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe findings of this study highlight several factors that contribute to perinatal mortality in Geita Regional Referral Hospital. These factors include premature complications, severe birth asphyxia, neonatal sepsis, and aspiration pneumonia, anemia in pregnancy, eclampsia, pre-eclampsia, and malaria in pregnancy. The study also found that poor antenatal attendance and poor screening were significant contributing factors to these deaths. The findings of this study are consistent with previous research on perinatal mortality in low and middle-income countries. A study conducted in Nigeria found that maternal factors, including anemia, eclampsia, and antepartum hemorrhage, were significant contributors to perinatal mortality rates (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Similarly, a study in Ghana found that maternal factors, including hypertension and anemia, were associated with increased perinatal mortality rates (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother study conducted in Tanzania found that poor antenatal attendance and inadequate prenatal care were significant contributing factors to perinatal mortality rates (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The study recommended the use of community health workers to improve antenatal attendance and the provision of comprehensive prenatal care to reduce perinatal mortality rates.\u003c/p\u003e \u003cp\u003ePrevious research has also highlighted the importance of investing in maternal and child health to reduce perinatal mortality rates. The United Nations' Every Newborn Action Plan (ENAP) emphasizes the need for increased investment in maternal and child health to achieve the Sustainable Development Goals (SDGs) and reduce perinatal mortality rates (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, the findings of this study emphasize and highlights the need for a comprehensive approach to address perinatal mortality rates in low and middle-income countries, including Tanzania. By implementing the recommended measures and investing more in maternal and child health, we can make a significant impact in reducing perinatal mortality rates and achieving the the UN's Sustainable Development Goals.\u003c/p\u003e"},{"header":"RECOMMENDATIONS","content":"\u003cp\u003eThere were several recommendations made during the discussion on improving maternal health. The participants agreed that providing education to mothers and involving the community in addressing pregnancy-related issues is crucial. Educating mothers on timely clinic attendance and the importance of seeking medical attention from service providers, particularly at the RCH clinic, is essential. The referral system needs to be improved, and clinics should prioritize testing mothers for all necessary tests upon arrival while also improving the skills of service providers. Mothers should be encouraged to seek medical attention early when they notice any health problems\u003c/p\u003e \u003cp\u003eIt was noted that many pregnant mothers do not use folic acid tablets due to mild adverse effects such as nausea and vomiting. Therefore, service providers should provide education to mothers about the use of medicines given to them. Additionally, all RCH commodities should be made readily available to reduce challenges, along with IPC compliance.\u003c/p\u003e \u003cp\u003eMothers should be encouraged to visit the clinic early so that any health problems can be diagnosed and treated early. Service providers' advice should also be followed. It is recommended that mothers attend eight visits, with each visit tested for HB and RBG, to improve maternal health. The transport system and decision-making for referrals and training provision should be improved, and on-the-job training for service providers should be provided.\u003c/p\u003e \u003cp\u003eIt was suggested that all pregnant women attending within 12 weeks of pregnancy or earlier be given the current card. Coating folic acid tablets and combining them with anti-emetics can help improve adherence to medication. Additionally, CHWs should remind pregnant women to attend subsequent visits within the appointment schedule. Men should also be involved and educated as they are decision-makers in the family. Male involvement is also crucial, and male partners/husbands should be educated about the importance of proper nutrition for both the mother and child.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTo effectively reduce perinatal mortality in the Geita Region, it is necessary to adopt a multisectoral approach and invest more resources. By bringing together various sectors and stakeholders, we can work towards improving the quality of maternal care, increasing access to healthcare services, and addressing the underlying social and economic factors that contribute to poor health outcomes. With greater investment and collaboration, we can create a safer and healthier environment for mothers and their infants in the Geita Region.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCODAC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Causes of Death and Associated Conditions \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGRRH \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Geita Regional Referral Hospital\u003c/p\u003e\n\u003cp\u003eMDG \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Millennium Development Goal\u003c/p\u003e\n\u003cp\u003ePMR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Perinatal Mortality Rate\u003c/p\u003e\n\u003cp\u003eGA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Gestational Age\u003c/p\u003e\n\u003cp\u003eTZS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Tanzanian Shillings\u003c/p\u003e\n\u003cp\u003eMLCC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Midwife-Led Continuity of Care.\u003c/p\u003e\n\u003cp\u003eMOH\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ministry of Health\u003c/p\u003e\n\u003cp\u003eU5M \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Under 5 Mortality\u003c/p\u003e\n\u003cp\u003eSDGs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sustainable Development Goals\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(ENAP)\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Every Newborn Action Plan\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNIMR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;National Institute for Medical Research of Tanzania\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUNCEF\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;United Nations Children\u0026rsquo;s Fund\u003c/p\u003e\n\u003cp\u003eWHO \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eACKNOWLEDGEMENT\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to all the participants who participated in this study and shared their valuable time and experiences. We also thank the management of Geita Regional Referral Hospital for allowing us to conduct this study and providing necessary resources to facilitate the research. We are also grateful to the staff of the hospital for their cooperation and support during the data collection process. Special thanks go to our research assistants for their dedication and hard work in collecting and managing the data. Finally, we thank our families and friends for their support and encouragement throughout the study.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe raw data used in this study were generated at Geita Regional Referral Hospital from the discussed perinatal deaths for quantitative data. Qualitative data were obtained through focused group discussions, in-depth interviews, and key informant interviews. The corresponding authors [SPM \u0026amp; MK] hold the data that support the findings of this study and they are available upon request.\u003c/p\u003e\n\u003cp\u003eEthical Approval\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the Ethics Committee of National Institute for Medical Research-Tanzania with approval number NIMR /HQ/R.8a/vol. IX/4510 before the commencement of the study. Informed consent was obtained from all participants, and their confidentiality and privacy were protected throughout the study. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eCompeting interests; none\u003c/p\u003e\n\u003cp\u003eFunding; no fund received\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eMK contributed equally to intellectual input, study design, data analysis, and interpretation of results.\u003c/p\u003e\n\u003cp\u003eSPM contributed equally to intellectual input, study design, data analysis, and interpretation of results.\u003c/p\u003e\n\u003cp\u003eOS read and revised the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMacharia PM, Beov\u0026aacute; L, Pinchoff J, Semaan A, Pembe AB, Christou A et al. Neonatal and perinatal mortality in the urban continuum: a geospatial analysis of the household survey, satellite imagery and travel time data in Tanzania. 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World Health Organization and United Nations Children's Fund; 2014.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4395259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4395259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePerinatal mortality is a sensitive issue that concerns the lives of newborn babies. In Tanzania, the perinatal mortality rate is high, accounting for 38/1000 live births.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA study titled \"Patterns, Trends, and Specific Determinants of Perinatal Mortality\" was conducted at Geita Regional Referral Hospital in 2023/24.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study found that several factors were significantly associated with perinatal deaths, including premature complication, severe birth asphyxia, unknown factors, neonatal sepsis, and aspiration pneumonia, anemia in pregnancy, eclampsia, pre-eclampsia, and malaria in pregnancy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecommendation:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study recommended several measures, including using Community Health Care workers and FHCWs to offer health education on focused antenatal care and safe motherhood, improving ANC clinics, providing proper and increased allocation of human resources, and allowing trained nurses or anesthetists to perform caesarian sections. Pregnant women should also be alerted about their subsequent visit/appointment. Motivations, coating folic acid tablets and combining them with antiemetics to become user-friendly, additionally, traditional medicine labs should take samples of local herbs used by pregnant mothers to detect their chemical compositions and provide advice accordingly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn conclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReducing perinatal mortality in the Geita region requires a multisectoral approach and more investment we can make save the lives of many newborn babies\u003c/p\u003e","manuscriptTitle":"Trends, Patterns and Cause-Specific Determinant Of Perinatal Mortality at Geita Regional Referral Hospital In Tanzania: A Hospital-Based Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-17 07:52:12","doi":"10.21203/rs.3.rs-4395259/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"90ffeea8-2c0a-42a7-b534-970496335016","owner":[],"postedDate":"June 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-01T07:41:24+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-17 07:52:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4395259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4395259","identity":"rs-4395259","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}