Population modifiable risk factors associated with neonatal mortality in 35 sub-Saharan Africa countries: analysis of data from demographic and health surveys

Kedir Y Ahmed; Subash Thapa; Tahir A Hassen; Teketo Kassaw Tegegne; Abel F Dadi; Daniel Bogale Odo; Habtamu Mellie Bizuayehu; Desalegn Markos Shifti; Sewunet Admasu Belachew; Getiye Dejenu Kibret; Daniel Bekele Ketema; Zemenu Yohannes Kassa; Erkihun Amsalu; Meless G Bore; Abdulbasit Seid; Yonatan M Mesfin; Kelemu Tilahun Kibret; M Mamun Huda; Shakeel Mahmood; Anayochukwu E Anyasodor; Allen G Ross

doi:10.1016/j.eclinm.2024.102682

Population modifiable risk factors associated with neonatal mortality in 35 sub-Saharan Africa countries: analysis of data from demographic and health surveys

EClinicalMedicine. 2024 Jun 20:73:102682. doi: 10.1016/j.eclinm.2024.102682. eCollection 2024 Jul.

Authors

Kedir Y Ahmed¹, Subash Thapa¹, Tahir A Hassen², Teketo Kassaw Tegegne³, Abel F Dadi^{4

5}, Daniel Bogale Odo⁶, Habtamu Mellie Bizuayehu⁷, Desalegn Markos Shifti⁸, Sewunet Admasu Belachew⁷, Getiye Dejenu Kibret⁹, Daniel Bekele Ketema^{10

11}, Zemenu Yohannes Kassa^{12

13}, Erkihun Amsalu^{14

15}, Meless G Bore^{13

16}, Abdulbasit Seid¹⁷, Yonatan M Mesfin¹⁸, Kelemu Tilahun Kibret¹⁹, M Mamun Huda¹, Shakeel Mahmood¹, Anayochukwu E Anyasodor¹, Allen G Ross¹

Affiliations

¹ Rural Health Research Institute, Charles Sturt University, Orange, NSW 2800, Australia.
² Center for Women's Health Research, College of Health, Medicine and Wellbeing, The University of Newcastle, NSW, Australia.
³ Institute for Physical Activity and Nutrition, Deakin University, Geelong, VIC, Australia.
⁴ Menzies School of Health Research, Charles Darwin University, Australia.
⁵ Addis Continental Institute of Public Health, Addis Ababa, Ethiopia.
⁶ National Centre for Aboriginal and Torres Strait Islander Wellbeing Research, National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT, Australia.
⁷ First Nations Cancer and Wellbeing (FNCW) Research Program, School of Public Health, The University of Queensland, Qld, Australia.
⁸ Child Health Research Centre, The University of Queensland, Qld, Australia.
⁹ Faculty of Medicine, Health and Human Sciences, Macquarie University, Australia.
¹⁰ The George Institute for Global Health, University of New South Wales (UNSW), Sydney, Australia.
¹¹ School of Public Health, College of Medicine and Health Science, Debre Markos University, Ethiopia.
¹² College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia.
¹³ School of Nursing and Midwifery, University of Technology Sydney, Sydney, Australia.
¹⁴ Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Australia.
¹⁵ St. Paul Hospital Millennium Medical College, Addis Ababa, Ethiopia.
¹⁶ School of Nursing, College of Medicine and Health Science, Hawassa University, Hawassa, Ethiopia.
¹⁷ Australian Living Evidence Collaborations, School of Public Health and Prevention Medicine, Monash University, Australia.
¹⁸ SAEFVIC, Infection and Immunity, Murdoch Children's Research Institute, 50 Flemington Road, Parkville, VIC, Australia.
¹⁹ Global Centre for Preventive Health and Nutrition, Institute for Health Transformation, School of Health and Social Development, Faculty of Health, Deakin University, Geelong, VIC, Australia.

Abstract

Background: Sub-Saharan Africa (SSA) has the highest burden of neonatal mortality in the world. Identifying the most critical modifiable risk factors is imperative for reducing neonatal mortality rates. This study is the first to calculate population-attributable fractions (PAFs) for modifiable risk factors of neonatal mortality in SSA.

Methods: We analysed the most recent Demographic and Health Surveys data sets from 35 SSA countries conducted between 2010 and 2022. Generalized linear latent and mixed models were used to estimate odds ratios (ORs) along with 95% confidence intervals (CIs). PAFs adjusted for communality were calculated using ORs and prevalence estimates for key modifiable risk factors. Subregional analyses were conducted to examine variations in modifiable risk factors for neonatal mortality across Central, Eastern, Southern, and Western SSA regions.

Findings: In this study, we included 255,891 live births in the five years before the survey. The highest PAFs of neonatal mortality among singleton children were attributed to delayed initiation of breastfeeding (>1 h after birth: PAF = 23.88%; 95% CI: 15.91, 24.86), uncleaned cooking fuel (PAF = 5.27%; 95% CI: 1.41, 8.73), mother's lacking formal education (PAF = 4.34%; 95% CI: 1.15, 6.31), mother's lacking tetanus vaccination (PAF = 3.54%; 95% CI: 1.55, 4.92), and infrequent antenatal care (ANC) visits (PAF = 2.45; 95% CI: 0.76, 3.63). Together, these five modifiable risk factors were associated with 39.49% (95% CI: 21.13, 48.44) of neonatal deaths among singleton children in SSA. Our subregional analyses revealed some variations in modifiable risk factors for neonatal mortality. Notably, delayed initiation of breastfeeding consistently contributed to the highest PAFs of neonatal mortality across all four regions of SSA: Central, Eastern, Southern, and Western SSA.

Interpretation: The PAF estimates in the present study indicate that a considerable proportion of neonatal deaths in SSA are preventable. We identified five modifiable risk factors that accounted for approximately 40% of neonatal deaths in SSA. The findings have policy implications.

Funding: None.

Keywords: Neonatal mortality; Population attributable fractions; Sub-Saharan Africa; Sustainable development goals (SDGs).