Association between concurrence of multiple risk factors and under-5 mortality: a pooled analysis of data from Demographic and Health Survey in 61 low-and-middle-income countries

Yuhao Kong; Shaoru Chen; Ning Ma; Zekun Chen; Peter Karoli; John Lapah Niyi; Pengyang Fan; Günther Fink; Xiaoxiao Jiang Kwete; Fernando C Wehrmeister; Feng Cheng; Dongqing Wang; Melkamu Aderajew Zemene; Samwel Maina Gatimu; Nuruzzaman Khan; Ashfikur Rahman; Lelisa Fekadu; Gebretsadik Shibre; Lhuri Dwianti Rahmartani; Justice Moses K Aheto; Pascal Geldsetzer; Zhihui Li

doi:10.1016/j.eclinm.2024.102583

Association between concurrence of multiple risk factors and under-5 mortality: a pooled analysis of data from Demographic and Health Survey in 61 low-and-middle-income countries

EClinicalMedicine. 2024 Apr 5:71:102583. doi: 10.1016/j.eclinm.2024.102583. eCollection 2024 May.

Authors

Yuhao Kong¹, Shaoru Chen¹, Ning Ma¹, Zekun Chen¹, Peter Karoli², John Lapah Niyi³, Pengyang Fan¹, Günther Fink⁴, Xiaoxiao Jiang Kwete⁵, Fernando C Wehrmeister^{6

7}, Feng Cheng^{1

8}, Dongqing Wang⁹, Melkamu Aderajew Zemene¹⁰, Samwel Maina Gatimu¹¹, Nuruzzaman Khan¹², Ashfikur Rahman¹³, Lelisa Fekadu¹⁴, Gebretsadik Shibre¹⁵, Lhuri Dwianti Rahmartani¹⁶, Justice Moses K Aheto^{17

18}, Pascal Geldsetzer^{19

20}, Zhihui Li^{1

8}

Affiliations

¹ Vanke School of Public Health, Tsinghua University, Beijing, China.
² National Institute for Medical Research, Dar es salaam, Tanzania.
³ Ghana Health Service, Gushegu Municipal Health Directorate, Gushegu, Ghana.
⁴ Swiss TPH and University of Basel, Basel, Switzerland.
⁵ Global Health Research and Consulting, Yaozhi, Yangzhou, China.
⁶ Department of Epidemiology, Universidade Federal de Pelotas, Pelotas, Brazil.
⁷ Institute for Global Public Health, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada.
⁸ Institute for Healthy China, Tsinghua University, 100084, Beijing, China.
⁹ Department of Global and Community Health, College of Public Health, George Mason University, Fairfax, VA, USA, 22030.
¹⁰ Department of Public Health, College of Health sciences, Debre Tabor University, Debre Tabor, Ethiopia.
¹¹ Diabetes Foot Foundation of Kenya, Kenya.
¹² Centre for Women's Health Research, Faculty of Health and Medicine, University of Newcastle, Australia.
¹³ Development Studies Discipline, Social Science School, Khulna University, Bangladesh.
¹⁴ Health Economist, Health Economics and Financing Program, Africa CDC, Addis Ababa, Ethiopia.
¹⁵ Department of Reproductive, Family, and Population Health, School of Public Health, Addis Ababa University, Addis Ababa, Ethiopia.
¹⁶ Faculty of Public Health, Department of Epidemiology, Universitas Indonesia, Depok, Jawa Barat, Indonesia.
¹⁷ Department of Biostatistics, School of Public Health, University of Ghana, Ghana.
¹⁸ WorldPop, School of Geography and Environmental Science, University of Southampton, United Kingdom.
¹⁹ Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
²⁰ Chan Zuckerberg Biohub - San Francisco, CA, USA.

Abstract

Background: Exposure to multiple risk factors is prevalent in low-and middle-income countries (LMICs), challenging one-directional strategies to address preventable under-5 mortality (U5M). This study aims to assess the associations between concurrence of multiple risk factors and U5M in LMICs.

Methods: We extracted data from the Demographic and Health Surveys conducted between 2010 and 2021 across 61 LMICs. Our primary outcome was U5M, defined as deaths from birth to 59 months. Binary logistic regression model was applied to ascertain the association between U5M and a total of 20 critical risk factors. Upon identifying the risk factors demonstrating the strongest associations, we investigated the simultaneous presence of multiple risk factors in each individual and assessed their combined effects on U5M with logistic regression models.

Findings: Of the 604,372 under-5 children, 18,166 (3.0%) died at the time of the survey. Unsatisfied family planning needs was the strongest risk factor for U5M (odds ratio [OR]: 2.0, 95% confidence interval [CI]: 1.9-2.1), followed by short birth interval (<18 months; OR: 2.0, 95% CI: 1.9-2.1), small birth size (OR: 2.0, 95% CI: 1.8-2.1), never breastfed or delayed breastfeeding (OR: 2.0, 95% CI: 1.9-2.0), and low maternal education (OR: 1.6, 95% CI: 1.4-1.8). 66.7% (66.6%-66.8%) of the children had 2 or more leading risk factors simultaneously. Simultaneous presence of multiple leading risk factors was significantly associated with elevated risk of U5M and children presenting with all 5 leading risk factors exhibited an exceedingly high risk of U5M (OR: 5.2, 95% CI: 4.3-6.3); a dose-response relationship between the number of risk factors and U5M was also observed-with the increment of numbers of leading risk factors, the U5M showed an increasing trend (p-trend < 0.001).

Interpretation: Exposure to multiple risk factors is very common in LMICs and underscores the necessity of developing multisectoral and integrated approaches to accelerate progress in reducing U5M in line with the SDG 3.2.

Funding: This research is funded by Research Fund, Vanke School of Public Health, Tsinghua University.

Keywords: Concurrence of multiple risk factors; Low-and middle-income countries; Under-5 mortality.