Abstract
Neonatal mortality is high in developing countries, and reducing neonatal mortality is an indispensable part of the third Sustainable Development Goal. This study estimated the prevalence of neonatal mortality and the impact of maternal education, economic status, and utilization of antenatal care (ANC) services on neonatal mortality in developing countries. We used a cross-sectional study design to integrate data from 21 developing countries to acquire a wider perspective on neonatal mortality. A meta-analysis was conducted using the latest Demographic and Health Survey data from 21 developing countries. In addition, sensitivity analysis was adopted to assess the stability of the meta-analysis. The random-effects model indicated that women with higher education were less likely to experience neonatal death than mothers with up to primary education (odds ratio [OR] 0.820, 95% confidence interval [CI] 0.740–0.910). Women with higher socioeconomic status were less likely to experience neonatal death than mothers with lower socioeconomic status (OR 0.823, 95% CI 0.747–0.908). Mothers with ANC were less likely to experience neonatal death than those with no ANC (OR 0.374, 95% CI 0.323–0.433). Subgroup analysis showed that maternal education and ANC were more effective in Asian countries. In this study, mothers’ lower educational level, poor economic status, and lack of ANC were statistically significant factors associated with neonatal death in developing countries. The effect of these factors on neonatal death differed in different regions.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
1 Introduction
The neonatal phase, which is the first 4 weeks (28 days) from birth, is the most vulnerable phase of human life for acquiring diseases [1]. Neonatal death is an indicator of a country’s demographic, biological, and socioeconomic conditions as well as the health system, public health, and population growth rate [2, 3]. Although the neonatal mortality rate has decreased worldwide, the decline is slower than the under-5 child mortality and is still unacceptably high at 37 per 1000 live births [4, 5]. Globally, about 7000 babies die daily; most of these deaths occur within the first week, and nearly 2.6 million babies die in the first month of life [6]. About 78% of these neonatal deaths occur in developing countries, particularly in South Asia and Sub-Saharan Africa [7, 8], which account for 39% of all global neonatal deaths and are among the top 10 countries with the highest neonatal mortality rate [9, 10]. To address maternal, neonatal, child, and adolescent health issues, sustainable development goals (SDGs) to build on millennium development goals (MDGs) were introduced in 2015 [11]. The first three targets of the health goals of SDGs are a continuation of the MDGs. The most important target is to decrease under-5 deaths to below 25 deaths per 1000 live births and to reduce neonatal mortality to below 12 deaths per 1000 live births [12, 13]. To fulfill the SDGs, it is essential to explore the factors determining neonatal death. Furthermore, to initiate the proper steps and appropriate strategies for reducing neonatal mortality rate, identifying the causes of neonatal death and triggering factors of neonatal mortality should be the first step [14]. Neonatal deaths are influenced by multiple factors and represent a complex interaction among these factors [15]. The majority of neonatal deaths occur among the poor and most deprived with low socioeconomic status, less education, and less or no access to health care [16].
In this study, we estimated the impact of maternal education, economic status, and utilization of antenatal care (ANC) services on neonatal death and their consistency in 21 developing countries in Asia and Sub-Saharan Africa. This study explored the impact of maternal education, wealth index, and ANC access on neonatal mortality in 21 developing countries using the latest Demographic and Health Survey (DHS) data. The effect of maternal education and ANC on neonatal death was different in Asia compared to developing countries in Africa. This study recommends raising awareness regarding neonatal mortality and implementing strategies to achieve the SDG by 2030.
2 Materials and Methods
2.1 Study Design
We used a cross-sectional study design to apply meta-analysis techniques to data from 21 developing countries. The data were obtained from the DHS.
2.2 Data Source and Extraction
We conducted a meta-analysis utilizing recently accessible datasets (accessed in June 2020) from the Monitoring and Evaluating to Assess and Use Results DHS (MEASURE DHS) (www.measuredhs.com). We accessed recently available DHS data for 20 developing countries [17]: Afghanistan (2015), Angola (2015–16), Benin (2017–18), Chad (2014–15), Cambodia (2014), Ethiopia (2016), Ghana (2014), Guinea (2018), India (2015–16), Indonesia (2017), Kenya (2014), Lesotho (2014), Myanmar (2015–16), Nepal (2016), Nigeria (2018), Pakistan (2017–18), Sierra Leone (2013), Timor-Leste (2016), Zambia (2013–14), and Zimbabwe (2015). One of the primary goals of the DHS program is to provide high-quality, accessible data for analyses such as in the form of a questionnaire. The DHS database contains information from 91 countries (http://dhsprogram.com/data/available-datasets.com). We have selected Bangladesh and 20 other developing countries, followed homogenous sampling schema. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Fig. 1) clearly illustrates the process of identifying and including DHS datasets for the random-effects meta-analysis [18].
2.3 Variables
In this study, we considered neonatal mortality as the dependent variable. We measured this as a two-category dummy variable, and the two distinct levels were “Yes” if neonatal death occurred and “No” if death did not occur. We included maternal education, ANC services, and wealth index as independent variables. We combined secondary and above primary education for the variable maternal education, and up to primary education as another category. We changed the variable’s wealth index label to “living below the poverty line.” We combined poorer and poorest and labeled them “Yes” if the individuals were poor or lived below the poverty line; we combined middle, richer, and richest and labeled them “No” for individuals who lived above the poverty line. For binary logistic regression, we subcategorized mothers who received ANC into two categories: “Yes” for at least one ANC visit; and “No” for no ANC visit.
2.4 Statistical Analyses
We used SPSS Statistics 23.0 (SPSS Inc., Chicago, IL, USA) and R 3.6.2 for Windows (Bell Laboratories, Murray Hill, NJ, USA) to conduct the statistical analyses. We applied meta-analysis techniques to the DHS data from 21 developing countries. Heterogeneity was assessed by enumerating the I2- and P-values among datasets [19]. We performed a random-effects model in the meta-analytical approach, as significant heterogeneity was found by which we estimated DerSimonian and Laird’s pooled effect [20]. Forest plots were used to display 95% confidence intervals (CIs), summary measure, and the weight of each study for the most significant determinants. Subgroup analysis was used to compare the effect of selected factors on neonatal mortality among the different groups [21]. As a summary measure, we used the odds ratio (OR), and all findings were weighted to handle bias due to undersampling and oversampling. Sensitivity analyses indicated that the included country had a similar influence on the overall estimate (Supplementary information, Appendixes 1–3).
3 Results
3.1 Background Characteristics of the Selected Datasets
The percentage of neonatal mortality was highest (3.6%) in Nigeria. In Afghanistan, maternal education up to primary level was highest (92.6%), whereas living below the poverty line was highest in Timor-Leste (64.5%), and the percentage of no ANC was highest in Afghanistan (Table 1).
3.2 Binary Logistic Regression Model
3.3 Random-Effects Model in Meta-analysis of 20 Developing Countries
Our study used the random-effects model, which showed high between-study variation (heterogeneity). Table 2 shows the results of the random-effects model of 21 developing countries’ data, and Table 3 shows the summary effect of different explanatory variables. For maternal education, the overall OR was 0.820 (95% CI 0.740–0.910; P ≤ 0.0306), showing that mothers who had above primary education were 0.820 times or 18.0% less likely to experience neonatal death compared to mothers who had up to primary education. About 61.3% of the variation (I2 = 61.3%) was found for this variable. For living below the poverty line, I2 was found to be 70.7%, where the overall OR was 0.823 (95% CI 0.747–0.908; P ≤ 0.0001), which revealed that the odds of neonatal mortality was 0.823 times or 17.7% lower among individuals who do not live below the poverty line compared to those who live below the poverty line. About 86.3% of the variation (I2 = 86.3%) was found for ANC. The overall OR was 0.374 (95% CI 0.323–0.433; P ≤ 0.0001), which means that neonatal death was 0.374 times or 62.6% less likely among women who received ANC compared to women who did not have access to ANC.
From Fig. 2a, the overall estimate of the random effects model for maternal education is 0.82. The 95% CI of the overall estimate (0.74–0.91) also does not overlap with one, so it can be concluded that women who were educated above the primary level were 18% less likely to experience neonatal death as compared to women who were educated up to primary level.
From Fig. 2b, the overall estimate of the random effects model for ANC utilization is 0.37; the 95% confidence interval of the overall estimate (0.32–0.43) also does not overlap with one, so it can be concluded that women who utilized ANC during their pregnancy were 63% less likely to experience neonatal death compared to those who did utilize ANC.
3.4 Subgroup Analyses of Different Factors
From Table 4 and Fig. 3a, it can be seen that maternal education with respect to region had a significant impact on neonatal mortality. For instance, having above primary education was a better predictor for reducing neonatal mortality in Asian countries (OR 0.76) than in African countries (OR 0.87).
Table 4 and Fig. 3b show that ANC utilization with respect to region had a significant impact on neonatal mortality. For instance, receiving ANC during pregnancy compared to not receiving ANC was a better indicator of reduced neonatal mortality in the Asian region (OR 0.35) than in the African region (OR 0.39).
4 Discussion
In our study, maternal education, wealth index, and ANC utilization had a substantial effect on neonatal death in developing countries. Our results demonstrated that the probability of neonatal death was reduced among mothers with education above primary level compared to mothers with education up to primary level. The positive impact of maternal education on neonatal survival is supported worldwide [22, 23]. Even when we control for the other factors of neonatal death, maternal education remains essential for child survival [23]. Maternal education improves awareness about a child’s health and healthcare facilities and enhances the healthcare-seeking behaviors of mothers [24]. Neonatal mortality is greatly influenced by ANC utilization in developing countries. Overall estimates from our meta-analysis showed that neonatal death was less likely in women who used ANC compared to those who did not, in accordance with previous studies [25, 26]. ANC utilization is one of the key strategies recommended to reduce neonatal death globally [27, 28]. Proper healthcare facilities improve pregnancy outcomes, and ANC utilization provides an opportunity for prompt detection of complications and early inception of breastfeeding. With follow-up ANC visits, pregnancy complications can be identified and addressed, which can lead to quality essential newborn care that increases survival [29]. Presently, for an uncomplicated pregnancy, at least eight ANC visits are necessary for better survival of neonates, as suggested by the World Health Organization [30]. However in our study, we found that in some countries, more than 50% of women did not have a single ANC visit throughout their pregnancy, which indicates that this essential service is severely underutilized in developing countries. From our meta-analysis, the odds of neonatal mortality were lower among individuals who live above the poverty line compared to those who live below the poverty line, in accordance with previous research [31, 32]. As poverty results in shortage of food, hygiene products, and secure drinking water, which immediately affects health outcomes, children from low-income families fare worse than those from high-income families. Additionally, children from low-income families have less access to health care services, which leads to more risk of neonatal death [33, 34]. Studies from Nepal and Nigeria showed a high risk of neonatal death among women with low socioeconomic status [35]. Our study found that more than 50% of women are living under the poverty line in almost all countries, which must be the focus to reduce neonatal death in developing countries.
Additionally, ANC and maternal education were more effective in Asian countries than in African countries. This may be due to the fact that the socioeconomic structure and household environmental indicators of Asian countries are relatively better than those of African countries [17, 35, 36].
Our study had some limitations. The DHS data utilized in this study covered a wide range and different time points. To estimate the OR from random-effects meta-analysis, we had to create 2 × 2 cross-tabulation for which each variable was divided into two categories. This is a limitation of doing a meta-analysis from cross-sectional datasets. Moreover, we were not able to incorporate all of the possible risk factors due to missing values of a particular variable in some of the countries. The range of years in the dataset of various countries, some of which date back several decades, might not reflect the actual data scenario.
5 Conclusion
To fulfill the SDG for the reduction of neonatal mortality rate by 2030, we need to implement different control programs focusing on risk factors of neonatal mortality. This study demonstrated the effect of maternal education, ANC, and wealth index on neonatal mortality using data from 21 developing countries. Proper steps and interventions should be initiated, focusing on the indicators identified in this study. Efforts toward increasing maternal education and utilization of ANC services must be ensured across developing countries, especially in African countries.
Availability of data and material
The secondary datasets DHS for 21 developing countries that were analyzed in the current study are freely available on the following website: http://dhsprogram.com/data/available-datasets.cfm
Abbreviations
- ANC:
-
Antenatal care
- SDGs:
-
Sustainable Development Goals
- MDGs:
-
Millennium Development Goals
- DHS:
-
Demographic and Health Survey
References
Yego F, D’Este C, Byles J, Nyongesa P, Williams JS. A case-control study of risk factors for fetal and early neonatal deaths in a tertiary hospital in Kenya. BMC Pregnancy Childb. 2014;14(1):1–9.
Bhutta ZA, Qadir M. Addressing maternal nutrition and risks of birth asphyxia in developing countries. Arch Pediatr Adolesc Med. 2009;163(7):671–2.
Nagalo K, Dao F, Tall FH, Yé D. Ten years morbidity and mortality of newborns hospitalized at the Clinic El-Fateh Suka (Ouagadougou, Burkina Faso). Pan Afr Med J. 2013;14:153.
Bryce J, Victora CG, Black RE. The unfinished agenda in child survival. The Lancet. 2013;382(9897):1049–59.
Alkema L, Chou D, Hogan D, Zhang S, Moller A-B, Gemmill A, et al. Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group. The lancet. 2016;387(10017):462–74.
Estimation UNIGfCM. Levels & Trends in Child Mortality: Report 2017: Estimates Developed by the UN Inter-Agency Group for Child Mortality Estimation. United Nations Children's Fund; 2017.
Liu L, Oza S, Hogan D, Chu Y, Perin J, Zhu J, et al. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals. The Lancet. 2016;388(10063):3027–35.
Målqvist M. Neonatal mortality: an invisible and marginalised trauma. Glob Health Action. 2011;4(1):5724.
Devine S, Taylor G, UNICEF. Every child alive: the urgent need to end newborn deaths. Unicef; 2018. https://reliefweb.int/report/world/every-child-alive-urgent-need-end-newborn-deaths-enar. Accessed 10 Oct 2021
Lopez AD. Levels & Trends in Child Mortality: Report 2014, Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation: United Nations Inter-agency Group for Child Mortality Estimation (UN IGME); 2014.
Bhutta ZA. Community–based primary health care: a core strategy for achieving sustainable development Goals for health. J Glob Health. 2017;7(1):010101.
Kumar S, Kumar N, Vivekadhish S. Millennium development goals (MDGS) to sustainable development goals (SDGS): Addressing unfinished agenda and strengthening sustainable development and partnership. Indian J Community Med. 2016;41(1):1.
You D, Hug L, Ejdemyr S, Idele P, Hogan D, Mathers C, et al. Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. The Lancet. 2015;386(10010):2275–86.
Tekelab T, Akibu M, Tagesse N, Tilhaun T, Yohanes Y, Nepal S. Neonatal mortality in Ethiopia: a protocol for systematic review and meta-analysis. Syst Rev. 2019;8(1):1–4.
de Souza S, Duim E, Nampo FK. Determinants of neonatal mortality in the largest international border of Brazil: a case-control study. BMC Public Health. 2019;19(1):1–9.
Ndayisenga T. Maternal and newborn risk factors associated with neonatal mortality in Gitwe district hospital in Ruhango district, Rwanda. Int J Med Public Health. 2016;6(2):98–102.
Bank W. Countries and Economies 2019. https://data.worldbank.org/country. Accessed 5 Oct 2021
Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62(10):e1–34.
Rücker G, Schwarzer G, Carpenter JR, Schumacher M. Undue reliance on I 2 in assessing heterogeneity may mislead. BMC Med Res Methodol. 2008;8(1):1–9.
DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88.
Borenstein M, Hedges LV, Higgins JP, Rothstein HR. Fixed-effect versus random-effects models. Introd Meta-anal. 2009;77:85.
Bhutta ZA, Darmstadt GL, Hasan BS, Haws RA. Community-based interventions for improving perinatal and neonatal health outcomes in developing countries: a review of the evidence. Pediatrics. 2005;115(Supplement 2):519–617.
Gakidou E, Cowling K, Lozano R, Murray CJ. Increased educational attainment and its effect on child mortality in 175 countries between 1970 and 2009: a systematic analysis. The Lancet. 2010;376(9745):959–74.
Caldwell JC. Cultural and social factors influencing mortality levels in developing countries. Ann Am Acad Pol Soc Sci. 1990;510(1):44–59.
Bhatti SH, Mamuna HI, Aftab M, Aslam M, Aslam N, Shah SMA, et al. Risk factors of neonatal mortality in Faisalabad. Pakistan Pak J Pharm Sci. 2017;30(2):663–5.
Ononge S, Mirembe F, Wandabwa J, Campbell OM. Incidence and risk factors for postpartum hemorrhage in Uganda. Reprod Health. 2016;13(1):1–7.
Lucas AO, Stoll BJ, Bale JR. Improving birth outcomes: meeting the challenge in the developing world. 2003.
Singh A, Pallikadavath S, Ram F, Alagarajan M. Do antenatal care interventions improve neonatal survival in India? Health Policy Plan. 2014;29(7):842–8.
Rarani MA, Rashidian A, Khosravi A, Arab M, Abbasian E, Morasae EK. Changes in socio-economic inequality in neonatal mortality in Iran between 1995–2000 and 2005–2010: an Oaxaca decomposition analysis. Int J Health Policy Manag. 2017;6(4):219.
Tunçalp Ӧ, Pena-Rosas JP, Lawrie T, Bucagu M, Oladapo OT, Portela A, et al. WHO recommendations on antenatal care for a positive pregnancy experience—going beyond survival. BJOG. 2017;124(6):860–2.
Ghosh R, Bharati P. Determinants of infant and child mortality in periurban areas of Kolkata city, India. Asia Pac J Public Health. 2010;22(1):63–75.
Islam R, Hossain M, Rahman M, Hossain M. Impact of Sociodemographic factors on child mortality in Bangladesh: an multivariate approach. Int J Psychol Behav Sci. 2013;3(1):34–9.
Huda TM, Tahsina T, Arifeen SE, Dibley MJ. The importance of intersectoral factors in promoting equity-oriented universal health coverage: a multilevel analysis of social determinants affecting neonatal infant and under-five mortality in Bangladesh. Glob Health Action. 2016;9(1):29741.
Paudel D, Shrestha IB, Siebeck M, Rehfuess EA. Neonatal health in Nepal: analysis of absolute and relative inequalities and impact of current efforts to reduce neonatal mortality. BMC Public Health. 2013;13(1):1–13.
Anand A, Roy N. Transitioning toward sustainable development goals: the role of household environment in influencing child health in Sub-Saharan Africa and South Asia using recent demographic health surveys. Front Public Health. 2016;4:87.
Berendsen B, Dietz T, Nordholt HS, van der Veen R. Asian tigers, African lions: comparing the development performance of Southeast Asia and Africa. Brill. 2013.
Acknowledgements
We would like to thank the National Institute of Population Research and Training (NIPORT) Bangladesh and Monitoring and Evaluating to Assess and Use Results DHS (MEASURE DHS) for allowing us to use DHS data of 21 developing countries for the analyses.
Funding
No funding was received for this study.
Author information
Authors and Affiliations
Contributions
MAI conceptualized the study, performed the data analyses, interpreted the data, and wrote the first draft of the manuscript. NJS was responsible for manuscript writing and revisions. ZAB was responsible for significant editing and critical revisions of the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no competing interests to declare.
Ethics declaration statement
Not applicable.
Consent to participate statement
Not applicable.
Consent to publication
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Islam, M.A., Butt, Z.A. & Sathi, N.J. Prevalence of Neonatal Mortality and its Associated Factors: A Meta-analysis of Demographic and Health Survey Data from 21 Developing Countries. Dr. Sulaiman Al Habib Med J 4, 145–152 (2022). https://doi.org/10.1007/s44229-022-00013-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s44229-022-00013-y