Cox PH Approach for Determining the Contributing Factors of Infant and Child Mortality in Nigeria: A Regional Analysis

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Despite ongoing efforts to mitigate these rates, Nigeria continues to exhibit some of the highest infant and child mortality rates in Africa. This research delves into the primary factors contributing to these mortality rates across various regions of Nigeria utilizing data from the Nigeria Demographic and Health Survey (NDHS). By employing the Cox proportional hazards (PH) model, this study identified several significant determinants of mortality rates, including family size, birth order, preceding birth interval, maternal education, maternal age, age at first birth, lack of breastfeeding, wealth index, religious affiliation, availability of toilet facilities, and child sex. Among these factors, lack of breastfeeding emerged as the most critical determinant, demonstrating the highest hazard ratio. These findings elucidate key factors influencing infant and child mortality, providing valuable insights for policymakers and healthcare professionals to devise targeted interventions to reduce mortality rates in Nigeria. Cox PH socioeconomic demographic environmental determinants infant mortality child mortality Nigeria. 1. Introduction Infant and child mortality rates are crucial indicators of a community's health, especially in low- and middle-income countries. According to the World Health Organization (WHO) and [ 17 ], these rates reflect the proportion of deaths among infants and children before their first birthday and within the first five years of life. In 2021, the WHO reported that nearly five million children under the age of five died worldwide. Historically, child mortality rates decreased from 150 per 1,000 live births in 1970 to approximately 115 per 1,000 live births by 1980. However, between 1990 and 2000, there was a troubling increase, with 10.5 million deaths, highlighting ongoing and significant challenges. Sub-Saharan Africa bears the highest burden of child mortality, with Nigeria being one of the most affected countries. As of 2022, Nigeria's child mortality rate was 111 per 1,000 live births, which is significantly higher than that in developed nations. Despite global progress in reducing infant mortality, Nigeria continues to report one of the highest rates in Africa, failing to meet the Sustainable Development Goal 4 target of reducing child mortality to 72 per 1,000 by 2015. The determinants of infant and child mortality are complex, and involve socioeconomic, environmental, and demographic factors. Effective public health interventions require a thorough understanding of these determinants. Research has consistently shown strong correlations between these factors and mortality rates. Environmental factors, such as maternal socioeconomic status, access to electricity, types of cooking fuel, and sources of drinking water, significantly impact infant mortality [ 16 ]. Socioeconomic factors, including access to resources, healthcare, and adequate nutrition, are also critical. For example, socioeconomic status is a strong predictor of neonatal mortality, with middle and lower socioeconomic classes facing greater risks than the wealthiest class [ 13 ]. Demographic factors, such as maternal age at marriage and childbirth, birth spacing, and maternal physical characteristics, also play significant roles in mortality [ 14 ]. Various studies across different countries and regions have explored these relationships using methodologies such as logistic regression, principal component analysis, and survival analysis to identify key predictors and outcomes. [ 11 ] Identified maternal factors, including parity and age at first childbirth, as significant predictors of child mortality. [ 15 ] Emphasized household environmental factors are major contributors. [ 1 ] highlighted the impact of both individual and community-level factors, including regional disparities and healthcare access, on mortality rates in Nigeria. Research by [ 2 ] and [ 12 ] further stressed the importance of maternal characteristics, healthcare access, and socioeconomic status in determining child mortality rates. Studies by [ 8 ] and [ 19 ] supported these findings, identifying maternal education, antenatal care, and household income as critical determinants. Recent studies by [ 23 ] and [ 18 ] expanded the analysis to include macroeconomic and urban environmental factors, while [ 9 ] focused on regional disparities within Nigeria. The complex interplay of socioeconomic, demographic, and environmental factors underscores the need for targeted interventions to reduce mortality rates and improve child health outcomes. This article aims to analyze data on these multifaceted determinants to identify the primary contributors to infant and child mortality across various regions of Nigeria. 2. Literature Review Recent research has delved deeply into the socioeconomic, demographic, and environmental factors impacting infant and child mortality. Some of these studies include the following: [ 7 ] analyzed data from five rounds of India's National Family Health Survey, focusing on scheduled casts (SCs) and scheduled tribes (STs) in Bihar, West Bengal, and Tamil Nadu. They found that STs had the highest child mortality rates, influenced by factors such as residence, maternal education, socioeconomic status, and family size. [ 22 ] Examined factors contributing to high infant and child mortality in 14 African countries from 2000 to 2018, identifying public health spending, number of physicians, globalization, economic growth, education, governance, and HIV incidence as significant determinants. [ 20 ] used logistic regression to analyze 41,668 Nigerian households and revealed the highest infant mortality rates in the Northwest and Northeast Regions. Key factors included lack of skilled antenatal care, young maternal age, and absence of antenatal care visits. [ 21 ] developed a predictive model for child mortality in Sierra Leone using 2008 and 2013 Demographic and Health Survey data, highlighting household size, maternal contraceptive use, wealth, child sex, and birth weight as crucial predictors. [ 3 ] Studied child mortality in Guinea using 2018 survey data and identified higher risks among children born to non-Christian mothers, those with low birth weight, and those lacking postpartum checkups. [ 5 ] Analyzed maternal and healthcare practices in Nigeria with 2018 survey data and found that 71% of infant deaths occurred within the first year, with maternal age, education, diet, and postpartum care being significant factors. [ 6 ] reviewed trends in infant mortality in Nigeria from 2003 to 2013, noting a general decline, particularly in the North and South-South regions, and emphasizing the need for targeted government interventions. [ 10 ] investigated the impact of socioeconomic and demographic characteristics on infant mortality in Nigeria, identifying maternal age, education, location, and wealth as key determinants. [ 4 ] Chad’s 2014-15 survey data revealed that child mortality was highest among certain ethnic groups and regions, with maternal education and birth order also being significant factors. [ 24 ] Evaluated child mortality in Ethiopia using 2016 survey data, linking higher mortality to male children, firstborns, rural residences, lack of breastfeeding, multiple births, and larger family sizes. 3. Materials and Methods 3.1 Data Source The data for this study were sourced from the 2018 Nigeria Demographic and Health Survey (NDHS), which used a multistage sampling approach, standardized tools, and trained interviewers. This survey is one of the most comprehensive and provides detailed information on demographic factors, infant and child mortality rates, and birth histories from surveyed mothers. The NDHS includes demographic, socioeconomic, and environmental data. The 2018 NDHS Birth Recode data file, which contains the most recent demographic and health information on Nigeria's population, was utilized for this study. After data cleaning, the total sample size was 33,781, with infants aged 0 to 12 months (n = 16,891) and children aged 0 to 60 months (n = 16,890) being the focus of the study. 3.2 Variable Description Table 1 The outcome variable in this study was infant and child mortality. Variables Description Current age of Mother The current age of the mother Age at first birth Mother age at first birth Place of residence Place of residence (Urban and Rural) Mother’s education Education level of mother Child Child age Family Family size Toilet Toilet facilities Wealth index Wealth index of the house hold Source of water Access to clean drinking water Religion Religious belief Region Region Birth Order Birth Order Sex Sex of child Preceding birth interval Preceding birth interval in months Delivery Types of delivery Nutrition Lack of Breastfeeding 3.3 Cox proportional hazards model 4. Results Table 1 shows that in this region, significant determinants of infant mortality include education (HR=1.0485, CI=1.0032-1.0959, p=0.0354), lack of breastfeeding (HR=6.8021, CI=6.2215-7.4370, P<2e-16), family size (HR=1.0138, CI=1.0021-1.0255, P=0.0204), maternal current age (HR=0.6487, CI=0.6007-0.7005, P<2e-16), age at first birth (HR=1.3945, CI=1.2783-1.5213, P=6.88e-14), birth order (HR=1.0859, CI=1.0552-1.1176, P=1.83e-06), and preceding birth interval (HR=1.0043, CI=1.0025-1.0062, P=4.84e-06). A lack of breastfeeding, with an HR of 6.8021, represents the highest risk factor for infant mortality in this region. Table 2 highlights the significant determinants of infant mortality in this region, which include lack of breastfeeding (HR=7.1641, CI=6.5816-7.7982, P value <2e-16), maternal current age (HR=0.6747, CI=0.6302-0.7223, P value <2e-16), age at first birth (HR=1.3480, CI=1.2286-1.4789, P value=2.76e-10), birth order (HR=1.0751, CI=1.0510-1.0998, P value=4.07e-10), and preceding birth interval (HR=1.0069, CI=1.0050-1.0088, P value=3.53e-13). A lack of breastfeeding was identified as the highest risk factor for infant mortality in this region, with an HR of 7.1641. Table 3 identifies the significant determinants of infant mortality in this region as follows: religion (HR=1.1164, CI=1.0066-1.2381, P=0.0371), lack of breastfeeding (HR=7.7952, CI=7.2518-8.3793, P<2e-16), maternal current age (HR=0.6528, CI=0.6152-0.6927, P<2e-16), age at first birth (HR=1.2484, CI=1.1464-1.3594, P<1.37e-07), birth order (HR=1.0840, CI= 1.0635-1.1048 P<2e-16), and preceding birth interval (HR=1.0063, CI=1.0046-1.0080, P=2.82e-13). Among these factors, lack of breastfeeding poses the highest risk of infant mortality in this region, with an HR of 7.7952. Table 4 highlights the key determinants of infant mortality in this region: wealth index (HR=1.0552, CI=1.0009-1.1124, P=0.0461), lack of breastfeeding (HR=6.1020, CI=5.4532-6.8280, P<2e-16), family size (HR=1.0281, CI=1.0083-1.0482, P=0.0052), maternal current age (HR=0.5952, CI=0.5402-0.6558, P<2e-16), age at first birth (HR=1.2795, CI=1.1517-1.4215, P=4.4e-06), birth order (HR=1.0561, CI=1.0183-1.0954, P=0.0034), and access to toilet facilities (HR=0.9962, CI=0.9927-0.9997, P=0.0335). Among these factors, lack of breastfeeding presents the highest risk for infant mortality, with an HR of 6.1020. Table 5 presents the significant determinants associated with infant mortality in this region. These determinants included education (HR=1.0831, CI=1.0149-1.1559, P=0.0161), wealth index (HR=0.9393, CI=0.8914-0.9898, P=0.0191), lack of breastfeeding (HR=8.2040, CI=7.2583-9.2729, P <2e-16), family size (HR=1.0358, CI=1.0063-1.0663, P=0.0172), maternal current age (HR=0.6789, CI=0.6180-0.7458, P=6.49e-16), age at first birth (HR=1.454, CI=1.3159-1.6077, P=2.25e-13), child sex (HR=0.8894, CI=0.8120-0.9741), birth order (HR=1.0774, CI=1.0308-1.1261, P=0.0010), and preceding birth interval (HR=1.004, CI=1.0019-1,0060 A lack of breastfeeding emerged as the highest risk factor for infant mortality in this region, with an HR of 8.2040, indicating a significant likelihood of occurrence. Table 6 presents significant determinants associated with infant mortality in this region. These determinants included lack of breastfeeding (HR=7.7584, CI=6.8290-8.8144, P<2e-16), maternal current age (HR=0.6244, CI=0.5670-0.6877, P=2.80e-08), age at first birth (HR=1.3508, CI=1.2148-1.5021, P=2.80e-08), birth order (HR=1.0858, CI=1.0423-1.1312, P=8.09e-05), preceding birth interval (HR=1.0037, CI=1.0017-1.0058, P=0.0003), and access to toilet facilities (HR=0.9958, CI=0.9919-0.9997, P=0.0345). Among these factors, lack of breastfeeding poses the highest risk of infant mortality in this region, with an HR of 7.7584, indicating a substantial likelihood of occurrence. Table 7 highlights the significant determinants influencing child mortality in this region. These determinants included lack of breastfeeding (HR=7.7254, CI=7.0655-8.4470, P value <2e-16), family size (HR=1.0196, CI=1.0078-1.0316, P value=0.0011), maternal current age (HR=0.6223, CI=0.5761-0.6722, P value <2e-16), age at first birth (HR=1.4535, CI=1.3315-1.5866, P value=2e-16), birth order (HR=1.0920, CI=1.0612-1.1238, P value=1.79e-09), and preceding birth interval (HR=1.0037, CI=1.0029-1.0066, P value=4.12e-07). A lack of breastfeeding emerged as the primary risk factor for child mortality in this area, with an HR of 7.7254, indicating a significant likelihood of occurrence. Table 8 presents the significant factors influencing child mortality in this region. These factors included wealth index (HR=1.0684, CI=1.0259-1.1127, P=0.0014), lack of breastfeeding (HR=7.9633, CI=7.0742-8.3667, P<2e-16), maternal current age (HR=0.6313, CI=0.5892-0.6765, P<2e-16), age at first birth (HR=1.4258, CI=1.2985-1.5655, P=1.04e-13), birth order (HR=1.0902, CI=1.0655-1.1155, P=1.49e-13), and preceding birth interval (HR=1.0077, CI=1.0059-1.0096, P<2e-16). Among these factors, lack of breastfeeding was the most significant risk factor for child mortality in this region, with an HR of 7.9633, indicating a high likelihood of occurrence. Table 9 examines crucial determinants influencing child mortality in this region. These determinants included religion (HR=1.2530, CI=1.1302-1.3892, P=1.82e-05), A lack of breastfeeding (HR=8.7094, CI=8.1009-9.3636, P<2e-16), family size (HR=1.0086, CI=1.0012-1.0160, .P=0.0221), maternal current age (HR=0.6330, CI=0.5967-0.6714, P<2e-16), age at first birth (HR=1.2804, CI=1.1758-1.3943,P=1.32e-08), Birth order P=1.0929, CI=1.0723-1.1138, P<2e-16), and preceding birth interval (HR=1.0080, CI=0.9920-1.0064, P<2e-16). Notably, lack of breastfeeding emerged as the primary risk factor for child mortality in this region, with an HR of 8.7094, suggesting a substantial likelihood of occurrence. Table 10 outlines the significant determinants affecting child mortality in this region. These determinants included religion (HR=1.0183, CI=1.0007-1.0363, P=0.0419), lack of breastfeeding (HR=7.7424, CI=6.8947-8.6945, P<2e-16), family size (HR=1.0329, CI=1.0130-1.0532, P=0.0011), maternal current age (HR=0.6690, CI=0.6224-0.7190, P<2e-16), birth order (HR=1.0929, CI=1.0723-1.1138, P<2e-16), and access to toilet facilities (HR=0.9964, CI=0.9929-0.9999, P=0.0457). Notably, lack of breastfeeding emerged as the most significant risk factor for child mortality in this region, with an HR of 7.7424, indicating a considerable likelihood of occurrence. Table 11 presents the significant determinants influencing child mortality in this region. These determinants included education (HR=1.0920, CI=1.0229-1.1659, P=0.0083), A lack of breastfeeding (HR=11.8318, CI=10.3866-13.4781, P<2e-16), family size (HR=1.0375, CI=1.0082-1.0676, P=0.01186), maternal current age (HR=0.6724, CI=0.6124-0.7383, P<2e-16), child sex (HR=0.8532, CI=0.7788-0.9347, P=0.0007), birth order (HR=1.0665, CI=1.0206-1.1145, P=0.0041), and type of place of residence (HR=0.8826, CI=0.7861-0.9909, P=0.0345). Notably, lack of breastfeeding emerged as the most significant risk factor for child mortality in this region, with an HR of 11.8318, indicating a substantial likelihood of occurrence. Table 12 highlights the significant determinants impacting child mortality in this region. These determinants included lack of breastfeeding (HR=9.9257, CI=8.7114-11.3093, P<2e-16), maternal current age (HR=0.5773, CI=0.5225-0.6378, P<2e-16), age at first birth (HR=1.4329, CI=1.2876-1.5946, P=4.29e-11), birth order (HR=1.0992, CI=1.0540-1.1463, P=1.01e-05), preceding birth interval (HR=1.0040, CI=1.0020-1.0060, P=0.0001), and access to toilet facilities (HR=0.9959, CI=0.9919-0.9999, P=0.0458). Notably, lack of breastfeeding emerged as the most significant risk factor for child mortality in this region, with an HR of 9.9257, indicating a substantial hazard of occurrence. Conclusion This research undertakes a comprehensive examination of the socioeconomic, demographic, and environmental determinants influencing infant and child mortality across diverse regions of Nigeria. Using the Cox proportional hazards (PH) model, this study meticulously explored the impact of various factors on mortality rates. The key determinants included family size, birth order, preceding birth interval, maternal education, maternal age, age at first birth, lack of breastfeeding practices, wealth index, religious affiliation, access to sanitation facilities, and child gender. The findings underscore the critical influence these factors exert on infant and child mortality across different regions. Notably, lack of breastfeeding was the most significant determinant, exhibiting the highest hazard ratio. This finding underscores the elevated risk of mortality for infants and children lacking adequate breastfeeding compared to their counterparts with adequate breastfeeding. This study’s identification of pivotal determinants affecting infant and child mortality offers invaluable insights for policymakers and healthcare practitioners. These insights are essential for designing targeted interventions aimed at reducing mortality rates and improving child health outcomes across Nigeria. Declarations Author contributions All the authors: - Kumur John Haganawiga, Surya Kant Pal and Anu Sirohi contributed equally to the manuscript. Data Availability Upon request, the data used to produce the analysis are easily accessible from: - https://dhsprogram.com/data/dataset_admin/index.cfm;jsessionid=971FE73C83645153237026AB73FCA1D6.cfusion?CFID=289480980&CFTOKEN=a119d1ee5e1f4694-728ED256-B9CE-75C5-27311C0F39BFC954 Conflicts of interest The authors certify that they have no competing interests. Funding source This research received funding from nowhere. Acknowledgments The Demographic and Health Survey Programme and USAID provided the data, which the authors gratefully acknowledge. References Adedini, S.A., Odimegwu, C., Imasiku, E.N., Ononokpono, D.N. and Ibisomi, L., 2015. Regional variations in infant and child mortality in Nigeria: a multilevel analysis. Journal of Biosocial Science, 47(2), pp.165-187. Adeolu, M., Akpa, O.M., Adeolu, A.T. and Aladeniyi, I.O., 2016. 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Heliyon, 6(3), pp. 1-7. Yihuna, Y.K., Lakew, A.K., Takele, N.M., Agelu, S.W. and Enigda, A.A., 2023. Determinants associated with infant mortality in Ethiopia: Using the recent 2019 Ethiopia mini demographic and health survey. MedRxiv, pp.1-10. Zakaria, M., Tariq, S. and Ul Husnain, M.I., 2020. Socioeconomic, macroeconomic, demographic, and environmental variables as determinants of child mortality in South Asia. Environmental Science and Pollution Research, 27, pp.954-964. Zewudie, A.T., Gelagay, A.A. and Enyew, E.F., 2020. Determinants of under-five child mortality in Ethiopia: analysis using Ethiopian demographic health survey, 2016. International Journal of Pediatrics, 2020, pp. 1-9. Tables Tables 1 to 12 are available in the Supplementary Files section Additional Declarations No competing interests reported. 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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-4582093","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":316184009,"identity":"eedaf023-bccc-45d8-ac55-bb74b74248d0","order_by":0,"name":"Kumur John Haganawiga","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYBACCTDJw5DAwN4AZBhYkKKF5wBIiwSxWhiAWiQSkPl4gOSM7DTpChmbPHPJ51c3/CiQYOBv707Aq0VaIneb5BmetGLL2TllN3uADpM4c3YDXi1yIC0NPIcTN9zOSbvBA9RiIJFLrJabZ9Ju/iFGizRcyw32Y7eJskWy5+1mywaetMQNZ3LYbssYSPAQ9IvE8dyNNxt7bBI3HD/+7OabPzZy/O29+LWAAWMPiOQxAJOElYPBDxDB/oBI1aNgFIyCUTDSAACMqUe4WKpqQgAAAABJRU5ErkJggg==","orcid":"","institution":"Sharda University","correspondingAuthor":true,"prefix":"","firstName":"Kumur","middleName":"John","lastName":"Haganawiga","suffix":""},{"id":316184013,"identity":"fd87d87b-c95c-4b60-b0e6-293d7f1ef803","order_by":1,"name":"Surya Kant Pal","email":"","orcid":"","institution":"Sharda University","correspondingAuthor":false,"prefix":"","firstName":"Surya","middleName":"Kant","lastName":"Pal","suffix":""},{"id":316184017,"identity":"133c2d3d-1c79-424c-9e01-32530f6fe3c7","order_by":2,"name":"Anu Sirohi","email":"","orcid":"","institution":"Sharda University","correspondingAuthor":false,"prefix":"","firstName":"Anu","middleName":"","lastName":"Sirohi","suffix":""}],"badges":[],"createdAt":"2024-06-14 12:33:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4582093/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4582093/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81098483,"identity":"7559d3cc-690e-4a3b-8be0-256f6ac38c7b","added_by":"auto","created_at":"2025-04-22 08:17:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":489644,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4582093/v1/de848907-191a-45fa-855e-fe4c7c0326d7.pdf"},{"id":59587825,"identity":"f177a68c-68ad-44cb-bfc9-34a7595cc577","added_by":"auto","created_at":"2024-07-03 14:07:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":94672,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4582093/v1/0ab2cd258533f45f0b51561b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cox PH Approach for Determining the Contributing Factors of Infant and Child Mortality in Nigeria: A Regional Analysis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eInfant and child mortality rates are crucial indicators of a community's health, especially in low- and middle-income countries. According to the World Health Organization (WHO) and [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], these rates reflect the proportion of deaths among infants and children before their first birthday and within the first five years of life. In 2021, the WHO reported that nearly five million children under the age of five died worldwide. Historically, child mortality rates decreased from 150 per 1,000 live births in 1970 to approximately 115 per 1,000 live births by 1980. However, between 1990 and 2000, there was a troubling increase, with 10.5\u0026nbsp;million deaths, highlighting ongoing and significant challenges.\u003c/p\u003e \u003cp\u003eSub-Saharan Africa bears the highest burden of child mortality, with Nigeria being one of the most affected countries. As of 2022, Nigeria's child mortality rate was 111 per 1,000 live births, which is significantly higher than that in developed nations. Despite global progress in reducing infant mortality, Nigeria continues to report one of the highest rates in Africa, failing to meet the Sustainable Development Goal 4 target of reducing child mortality to 72 per 1,000 by 2015.\u003c/p\u003e \u003cp\u003eThe determinants of infant and child mortality are complex, and involve socioeconomic, environmental, and demographic factors. Effective public health interventions require a thorough understanding of these determinants. Research has consistently shown strong correlations between these factors and mortality rates.\u003c/p\u003e \u003cp\u003eEnvironmental factors, such as maternal socioeconomic status, access to electricity, types of cooking fuel, and sources of drinking water, significantly impact infant mortality [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Socioeconomic factors, including access to resources, healthcare, and adequate nutrition, are also critical. For example, socioeconomic status is a strong predictor of neonatal mortality, with middle and lower socioeconomic classes facing greater risks than the wealthiest class [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDemographic factors, such as maternal age at marriage and childbirth, birth spacing, and maternal physical characteristics, also play significant roles in mortality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Various studies across different countries and regions have explored these relationships using methodologies such as logistic regression, principal component analysis, and survival analysis to identify key predictors and outcomes.\u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] Identified maternal factors, including parity and age at first childbirth, as significant predictors of child mortality. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Emphasized household environmental factors are major contributors. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] highlighted the impact of both individual and community-level factors, including regional disparities and healthcare access, on mortality rates in Nigeria.\u003c/p\u003e \u003cp\u003eResearch by [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] and [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] further stressed the importance of maternal characteristics, healthcare access, and socioeconomic status in determining child mortality rates. Studies by [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] supported these findings, identifying maternal education, antenatal care, and household income as critical determinants.\u003c/p\u003e \u003cp\u003eRecent studies by [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] expanded the analysis to include macroeconomic and urban environmental factors, while [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] focused on regional disparities within Nigeria. The complex interplay of socioeconomic, demographic, and environmental factors underscores the need for targeted interventions to reduce mortality rates and improve child health outcomes. This article aims to analyze data on these multifaceted determinants to identify the primary contributors to infant and child mortality across various regions of Nigeria.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eRecent research has delved deeply into the socioeconomic, demographic, and environmental factors impacting infant and child mortality. Some of these studies include the following:\u003c/p\u003e \u003cp\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] analyzed data from five rounds of India's National Family Health Survey, focusing on scheduled casts (SCs) and scheduled tribes (STs) in Bihar, West Bengal, and Tamil Nadu. They found that STs had the highest child mortality rates, influenced by factors such as residence, maternal education, socioeconomic status, and family size. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] Examined factors contributing to high infant and child mortality in 14 African countries from 2000 to 2018, identifying public health spending, number of physicians, globalization, economic growth, education, governance, and HIV incidence as significant determinants. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] used logistic regression to analyze 41,668 Nigerian households and revealed the highest infant mortality rates in the Northwest and Northeast Regions. Key factors included lack of skilled antenatal care, young maternal age, and absence of antenatal care visits. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] developed a predictive model for child mortality in Sierra Leone using 2008 and 2013 Demographic and Health Survey data, highlighting household size, maternal contraceptive use, wealth, child sex, and birth weight as crucial predictors. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] Studied child mortality in Guinea using 2018 survey data and identified higher risks among children born to non-Christian mothers, those with low birth weight, and those lacking postpartum checkups. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] Analyzed maternal and healthcare practices in Nigeria with 2018 survey data and found that 71% of infant deaths occurred within the first year, with maternal age, education, diet, and postpartum care being significant factors. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] reviewed trends in infant mortality in Nigeria from 2003 to 2013, noting a general decline, particularly in the North and South-South regions, and emphasizing the need for targeted government interventions. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] investigated the impact of socioeconomic and demographic characteristics on infant mortality in Nigeria, identifying maternal age, education, location, and wealth as key determinants. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Chad\u0026rsquo;s 2014-15 survey data revealed that child mortality was highest among certain ethnic groups and regions, with maternal education and birth order also being significant factors. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Evaluated child mortality in Ethiopia using 2016 survey data, linking higher mortality to male children, firstborns, rural residences, lack of breastfeeding, multiple births, and larger family sizes.\u003c/p\u003e"},{"header":"3. Materials and Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Data Source\u003c/h2\u003e\n \u003cp\u003eThe data for this study were sourced from the 2018 Nigeria Demographic and Health Survey (NDHS), which used a multistage sampling approach, standardized tools, and trained interviewers. This survey is one of the most comprehensive and provides detailed information on demographic factors, infant and child mortality rates, and birth histories from surveyed mothers. The NDHS includes demographic, socioeconomic, and environmental data. The 2018 NDHS Birth Recode data file, which contains the most recent demographic and health information on Nigeria\u0026apos;s population, was utilized for this study. After data cleaning, the total sample size was 33,781, with infants aged 0 to 12 months (n\u0026thinsp;=\u0026thinsp;16,891) and children aged 0 to 60 months (n\u0026thinsp;=\u0026thinsp;16,890) being the focus of the study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Variable Description\u003c/h2\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe outcome variable in this study was infant and child mortality.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent age of Mother\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe current age of the mother\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at first birth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMother age at first birth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlace of residence (Urban and Rural)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother\u0026rsquo;s education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation level of mother\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChild age\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamily size\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eToilet\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eToilet facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWealth index of the house hold\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of water\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccess to clean drinking water\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReligious belief\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth Order\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBirth Order\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex of child\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreceding birth interval\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreceding birth interval in months\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTypes of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNutrition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of Breastfeeding\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Cox proportional hazards model\u003c/h2\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003eTable 1 shows that in this region, significant determinants of infant mortality include education (HR=1.0485, CI=1.0032-1.0959, p=0.0354),\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003elack of breastfeeding\u0026nbsp;(HR=6.8021, CI=6.2215-7.4370, P\u0026lt;2e-16), family size (HR=1.0138, CI=1.0021-1.0255, P=0.0204), maternal current age (HR=0.6487, CI=0.6007-0.7005, P\u0026lt;2e-16), age at first birth (HR=1.3945, CI=1.2783-1.5213, \u0026nbsp;P=6.88e-14), birth order (HR=1.0859, CI=1.0552-1.1176, P=1.83e-06), and preceding birth interval (HR=1.0043, CI=1.0025-1.0062, P=4.84e-06). A lack of breastfeeding, with an HR of 6.8021, represents the highest risk factor for infant mortality in this region.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 2 highlights the significant determinants of infant mortality in this region, which include lack of breastfeeding (HR=7.1641, CI=6.5816-7.7982, P value \u0026lt;2e-16), maternal current age (HR=0.6747, CI=0.6302-0.7223, P value \u0026lt;2e-16), age at first birth (HR=1.3480, CI=1.2286-1.4789, P value=2.76e-10), birth order (HR=1.0751, CI=1.0510-1.0998, P value=4.07e-10), and preceding birth interval (HR=1.0069, CI=1.0050-1.0088, P value=3.53e-13). A lack of breastfeeding was identified as the highest risk factor for infant mortality in this region, with an HR of 7.1641.\u003c/p\u003e\n\u003cp\u003eTable 3 identifies the significant determinants of infant mortality in this region as follows: religion (HR=1.1164, CI=1.0066-1.2381, P=0.0371), lack of breastfeeding (HR=7.7952, CI=7.2518-8.3793, P\u0026lt;2e-16), maternal current age (HR=0.6528, CI=0.6152-0.6927, P\u0026lt;2e-16), age at first birth (HR=1.2484, CI=1.1464-1.3594, P\u0026lt;1.37e-07), birth order (HR=1.0840, CI= 1.0635-1.1048 P\u0026lt;2e-16), and preceding birth interval (HR=1.0063, CI=1.0046-1.0080, P=2.82e-13). Among these factors, lack of breastfeeding poses the highest risk of infant mortality in this region, with an HR of 7.7952.\u003c/p\u003e\n\u003cp\u003eTable 4 highlights the key determinants of infant mortality in this region: wealth index (HR=1.0552, CI=1.0009-1.1124, P=0.0461), lack of breastfeeding (HR=6.1020, CI=5.4532-6.8280, P\u0026lt;2e-16), family size (HR=1.0281, CI=1.0083-1.0482, P=0.0052), maternal current age (HR=0.5952, CI=0.5402-0.6558, P\u0026lt;2e-16), age at first birth (HR=1.2795, CI=1.1517-1.4215, P=4.4e-06), birth order (HR=1.0561, CI=1.0183-1.0954, P=0.0034), and access to toilet facilities (HR=0.9962, CI=0.9927-0.9997, P=0.0335). Among these factors, lack of breastfeeding\u003cdel cite=\"mailto:Curie\" datetime=\"2024-06-16T11:16\"\u003e\u0026nbsp;\u0026nbsp;\u003c/del\u003e\u003cins cite=\"mailto:Curie\" datetime=\"2024-06-16T11:16\"\u003e\u0026nbsp;\u003c/ins\u003epresents the highest risk for infant mortality, with an HR of 6.1020.\u003c/p\u003e\n\u003cp\u003eTable 5 presents the significant determinants associated with infant mortality in this region. These determinants included education (HR=1.0831, CI=1.0149-1.1559, P=0.0161), wealth index (HR=0.9393, CI=0.8914-0.9898, P=0.0191), lack of breastfeeding (HR=8.2040, CI=7.2583-9.2729, P \u0026lt;2e-16), family size (HR=1.0358, CI=1.0063-1.0663, P=0.0172), maternal current age (HR=0.6789, CI=0.6180-0.7458, P=6.49e-16), age at first birth (HR=1.454, CI=1.3159-1.6077, P=2.25e-13), child sex (HR=0.8894, CI=0.8120-0.9741), birth order (HR=1.0774, CI=1.0308-1.1261, P=0.0010), and preceding birth interval (HR=1.004, CI=1.0019-1,0060 A lack of breastfeeding emerged as the highest risk factor for infant mortality in this region, with an HR of 8.2040, indicating a significant likelihood of occurrence.\u003c/p\u003e\n\u003cp\u003eTable 6 presents significant determinants associated with infant mortality in this region. These determinants \u0026nbsp;included lack of breastfeeding (HR=7.7584, CI=6.8290-8.8144, P\u0026lt;2e-16), maternal current age (HR=0.6244, CI=0.5670-0.6877, P=2.80e-08), age at first birth (HR=1.3508, CI=1.2148-1.5021, P=2.80e-08), birth order (HR=1.0858, CI=1.0423-1.1312, P=8.09e-05), preceding birth interval (HR=1.0037, CI=1.0017-1.0058, P=0.0003), and access to toilet facilities (HR=0.9958, CI=0.9919-0.9997, P=0.0345). Among these factors, lack of breastfeeding poses the highest risk of infant mortality in this region, with an HR of 7.7584, indicating a substantial likelihood of occurrence.\u003c/p\u003e\n\u003cp\u003eTable 7 highlights the significant determinants influencing child mortality in this region. These determinants included lack of breastfeeding (HR=7.7254, CI=7.0655-8.4470, P value \u0026lt;2e-16), family size (HR=1.0196, CI=1.0078-1.0316, P value=0.0011), maternal current age (HR=0.6223, CI=0.5761-0.6722, P value \u0026lt;2e-16), age at first birth (HR=1.4535, CI=1.3315-1.5866, P value=2e-16), birth order (HR=1.0920, CI=1.0612-1.1238, P value=1.79e-09), and preceding birth interval (HR=1.0037, CI=1.0029-1.0066, P value=4.12e-07). A lack of breastfeeding emerged as the primary risk factor for child mortality in this area, with an HR of 7.7254, indicating a significant likelihood of occurrence.\u003c/p\u003e\n\u003cp\u003eTable 8 presents the significant factors influencing child mortality in this region. These factors included wealth index (HR=1.0684, CI=1.0259-1.1127, P=0.0014), lack of breastfeeding (HR=7.9633, CI=7.0742-8.3667, P\u0026lt;2e-16), maternal current age (HR=0.6313, CI=0.5892-0.6765, P\u0026lt;2e-16), age at first birth (HR=1.4258, CI=1.2985-1.5655, P=1.04e-13), birth order (HR=1.0902, CI=1.0655-1.1155, P=1.49e-13), and preceding birth interval (HR=1.0077, CI=1.0059-1.0096, P\u0026lt;2e-16). Among these factors, lack of breastfeeding was the most significant risk factor for child mortality in this region, with an HR of 7.9633, indicating a high likelihood of occurrence.\u003c/p\u003e\n\u003cp\u003eTable 9 examines crucial determinants influencing child mortality in this region. These determinants included religion (HR=1.2530, CI=1.1302-1.3892, P=1.82e-05), A lack of breastfeeding (HR=8.7094, CI=8.1009-9.3636, P\u0026lt;2e-16), family size (HR=1.0086, CI=1.0012-1.0160, .P=0.0221), maternal current age (HR=0.6330, CI=0.5967-0.6714, P\u0026lt;2e-16), age at first birth (HR=1.2804, CI=1.1758-1.3943,P=1.32e-08), Birth order P=1.0929, CI=1.0723-1.1138, P\u0026lt;2e-16), and preceding birth interval (HR=1.0080, CI=0.9920-1.0064, P\u0026lt;2e-16). Notably, lack of breastfeeding emerged as the primary risk factor for child mortality in this region, with an HR of 8.7094, suggesting a substantial likelihood of occurrence.\u003c/p\u003e\n\u003cp\u003eTable 10 outlines the significant determinants affecting child mortality in this region. These determinants included religion (HR=1.0183, CI=1.0007-1.0363, P=0.0419), lack of breastfeeding (HR=7.7424, CI=6.8947-8.6945, P\u0026lt;2e-16), family size (HR=1.0329, CI=1.0130-1.0532, P=0.0011), maternal current age (HR=0.6690, CI=0.6224-0.7190, P\u0026lt;2e-16), birth order (HR=1.0929, CI=1.0723-1.1138, P\u0026lt;2e-16), and access to toilet facilities (HR=0.9964, CI=0.9929-0.9999, P=0.0457). Notably, lack of breastfeeding emerged as the most significant risk factor for child mortality in this region, with an HR of 7.7424, indicating a considerable likelihood of occurrence.\u003c/p\u003e\n\u003cp\u003eTable 11 presents the significant determinants influencing child mortality in this region. These determinants included education (HR=1.0920, CI=1.0229-1.1659, P=0.0083), A lack of breastfeeding (HR=11.8318, CI=10.3866-13.4781, P\u0026lt;2e-16), family size (HR=1.0375, CI=1.0082-1.0676, P=0.01186), maternal current age (HR=0.6724, CI=0.6124-0.7383, P\u0026lt;2e-16), child sex (HR=0.8532, CI=0.7788-0.9347, P=0.0007), birth order (HR=1.0665, CI=1.0206-1.1145, P=0.0041), and type of place of residence (HR=0.8826, CI=0.7861-0.9909, P=0.0345). Notably, lack of breastfeeding emerged as the most significant risk factor for child mortality in this region, with an HR of 11.8318, indicating a substantial likelihood of occurrence.\u003c/p\u003e\n\u003cp\u003eTable 12 highlights the significant determinants impacting child mortality in this region. These determinants included lack of breastfeeding (HR=9.9257, CI=8.7114-11.3093, P\u0026lt;2e-16), maternal current age (HR=0.5773, CI=0.5225-0.6378, P\u0026lt;2e-16), age at first birth (HR=1.4329, CI=1.2876-1.5946, P=4.29e-11), birth order (HR=1.0992, CI=1.0540-1.1463, P=1.01e-05), preceding birth interval (HR=1.0040, CI=1.0020-1.0060, P=0.0001), and access to toilet facilities (HR=0.9959, CI=0.9919-0.9999, P=0.0458). Notably, lack of breastfeeding emerged as the most significant risk factor for child mortality in this region, with an HR of 9.9257, indicating a substantial hazard of occurrence.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis research undertakes a comprehensive examination of the socioeconomic, demographic, and environmental determinants influencing infant and child mortality across diverse regions of Nigeria. Using the Cox proportional hazards (PH) model, this study meticulously explored the impact of various factors on mortality rates. The key determinants included family size, birth order, preceding birth interval, maternal education, maternal age, age at first birth, lack of breastfeeding practices, wealth index, religious affiliation, access to sanitation facilities, and child gender. The findings underscore the critical influence these factors exert on infant and child mortality across different regions. Notably, lack of breastfeeding was the most significant determinant, exhibiting the highest hazard ratio. This finding underscores the elevated risk of mortality for infants and children lacking adequate breastfeeding compared to their counterparts with adequate breastfeeding. This study’s identification of pivotal determinants affecting infant and child mortality offers invaluable insights for policymakers and healthcare practitioners. These insights are essential for designing targeted interventions aimed at reducing mortality rates and improving child health outcomes across Nigeria.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAuthor contributions\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors: - Kumur John Haganawiga, Surya Kant Pal and Anu Sirohi contributed equally to the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUpon request, the data used to produce the analysis are easily accessible from: - https://dhsprogram.com/data/dataset_admin/index.cfm;jsessionid=971FE73C83645153237026AB73FCA1D6.cfusion?CFID=289480980\u0026amp;CFTOKEN=a119d1ee5e1f4694-728ED256-B9CE-75C5-27311C0F39BFC954\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors certify that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received funding from nowhere.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Demographic and Health Survey Programme and USAID provided the data, which the authors gratefully acknowledge.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdedini, S.A., Odimegwu, C., Imasiku, E.N., Ononokpono, D.N. and Ibisomi, L., 2015. Regional variations in infant and child mortality in Nigeria: a multilevel analysis. Journal of Biosocial Science, 47(2), pp.165-187.\u003c/li\u003e\n\u003cli\u003eAdeolu, M., Akpa, O.M., Adeolu, A.T. and Aladeniyi, I.O., 2016. Environmental and socioeconomic determinants of child mortality: evidence from the 2013 Nigerian demographic health survey. Am J Public Health Res, 4(4), pp.134-41.\u003c/li\u003e\n\u003cli\u003eAhinkorah, B.O., Budu, E., Seidu, A.A., Agbaglo, E., Adu, C., Osei, D., Banke-Thomas, A. and Yaya, S., 2022. Socioeconomic and proximate determinants of under-five mortality in Guinea. Plos One, 17(5), pp.1-13.\u003c/li\u003e\n\u003cli\u003eAhinkorah, B.O., Seidu, A.A., Budu, E., Armah-Ansah, E.K., Agbaglo, E., Adu, C., Hagan, J.E. and Yaya, S., 2020. Proximate, intermediate, and distal predictors of under-five mortality in Chad: analysis of the 2014\u0026ndash;15 Chad demographic and health survey data. 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Our world in data.\u003c/li\u003e\n\u003cli\u003eSalgado, M., Madureira, J., Mendes, A.S., Torres, A., Teixeira, J.P. and Oliveira, M.D., 2020. Environmental determinants of population health in urban settings. A systematic review. BMC Public Health, 20, pp.1-11.\u003c/li\u003e\n\u003cli\u003eShifa, G.T., Ahmed, A.A. and Yalew, A.W., 2018. Socioeconomic and environmental determinants of under-five mortality in Gamo Gofa Zone, Southern Ethiopia: a matched case control study. BMC international health and human rights, 18(1), pp.1-11.\u003c/li\u003e\n\u003cli\u003eShobiye, D.M., Omotola, A., Zhao, Y., Zhang, J., Ekawati, F.M. and Shobiye, H.O., 2022. Infant mortality and risk factors in Nigeria in 2013\u0026ndash;2017: A population-level-study. Eclinical-Medicine, 51, pp.10-22.\u003c/li\u003e\n\u003cli\u003eTagoe, E.T., Agbadi, P., Nakua, E.K., Duodu, P.A., Nutor, J.J. and Aheto, J.M.K., 2020. A predictive model and socioeconomic and demographic determinants of under-five mortality in Sierra Leone. Heliyon, 6(3), pp. 1-7.\u003c/li\u003e\n\u003cli\u003eYihuna, Y.K., Lakew, A.K., Takele, N.M., Agelu, S.W. and Enigda, A.A., 2023. Determinants associated with infant mortality in Ethiopia: Using the recent 2019 Ethiopia mini demographic and health survey. MedRxiv, pp.1-10.\u003c/li\u003e\n\u003cli\u003eZakaria, M., Tariq, S. and Ul Husnain, M.I., 2020. Socioeconomic, macroeconomic, demographic, and environmental variables as determinants of child mortality in South Asia. Environmental Science and Pollution Research, 27, pp.954-964.\u003c/li\u003e\n\u003cli\u003eZewudie, A.T., Gelagay, A.A. and Enyew, E.F., 2020. Determinants of under-five child mortality in Ethiopia: analysis using Ethiopian demographic health survey, 2016. International Journal of Pediatrics, 2020, pp. 1-9.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 12 are available in the Supplementary Files section\u003c/p\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":"Cox PH, socioeconomic, demographic, environmental determinants, infant mortality, child mortality, Nigeria.","lastPublishedDoi":"10.21203/rs.3.rs-4582093/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4582093/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eIn low- and middle-income countries, infant and child mortality rates serve as crucial indicators of public health. Despite ongoing efforts to mitigate these rates, Nigeria continues to exhibit some of the highest infant and child mortality rates in Africa. This research delves into the primary factors contributing to these mortality rates across various regions of Nigeria utilizing data from the Nigeria Demographic and Health Survey (NDHS). By employing the Cox proportional hazards (PH) model, this study identified several significant determinants of mortality rates, including family size, birth order, preceding birth interval, maternal education, maternal age, age at first birth, lack of breastfeeding, wealth index, religious affiliation, availability of toilet facilities, and child sex. Among these factors, lack of breastfeeding emerged as the most critical determinant, demonstrating the highest hazard ratio. These findings elucidate key factors influencing infant and child mortality, providing valuable insights for policymakers and healthcare professionals to devise targeted interventions to reduce mortality rates in Nigeria.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Cox PH Approach for Determining the Contributing Factors of Infant and Child Mortality in Nigeria: A Regional Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 14:07:40","doi":"10.21203/rs.3.rs-4582093/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":"b09f3892-de43-4043-a185-d61048ab3ae6","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-22T08:09:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-03 14:07:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4582093","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4582093","identity":"rs-4582093","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}