Survival analysis of maternal, household, environmental, and child-level determinants of under-five mortality in Nigeria

Abstract

Background

In Africa, Nigeria bears the highest burden of under-five mortality, with an estimated 850,000 under-five deaths from preventable causes reported in 2024. Existing evidence has not applied a time to event approach using recent nationwide data to examine factors associated with child mortality in this high-burden setting. The current study employed a time to event approach to examine factors affecting under-five mortality across a 59-month life course.

Methods

Retrospective data from the 2024 Nigeria Demographic and Health Survey was used. We analyzed data for 27,604 under-fives. Descriptive statistics, Kaplan-Meier survival estimates and Cox proportional hazards model were performed to determine the time to death.

Results

Of the 27,604 under-five children included, 7.97% had died. Nearly half (47.8%) of deaths occurred within the first 28 days of life. Adjusted results showed that multiple births increased under-five mortality (AHR = 5.51, 95% CI: 4.70–6.46; p = 0.001), whereas longer birth intervals reduced risk (AHR = 0.11–0.73; p = 0.001). High birth order increased mortality (AHR = 1.92, 95% CI: 1.10–3.36; p = 0.022). Maternal post-secondary education (AHR = 0.70, 95% CI: 0.55–0.90; p = 0.005), delayed first birth (AHR = 0.87, 95% CI: 0.79–0.97; p = 0.012), and residence in southern regions were protective, whereas rural residence (AHR = 1.23, 95% CI: 1.09–1.38; p = 0.001) and lack of mosquito nets (AHR = 1.82, 95% CI: 1.61–2.06; p = 0.001) increased mortality.

Conclusion

Under-five mortality is highest in the neonatal period and is shaped by birth spacing, multiple births, and inequality. Improving early interventions, optimal spacing, and reducing regional disparities are key to improving child survival.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12887-026-07522-x.

Introduction

The under-five mortality rate (U5MR) measures the likelihood of death before age five per 1,000 live births [1]. In 2023, the major global causes of under-five deaths included complications from prematurity, respiratory infections, birth-related complications, malaria, and diarrheal diseases [1]. Although global under-five mortality declined significantly from 77 to 37 deaths per 1,000 live births between 2000 and 2023, child mortality remains a major health concern. Approximately 4.8 million children died before age five in 2023, with the highest burden occurring in low-income countries [1, 2]. Most deaths are still caused by preventable and treatable conditions, particularly infectious diseases [3].

Progress toward the Sustainable Development Goal (SDG) targets for neonatal and under-five survival remains insufficient in many countries [1]. Without accelerated interventions, child deaths before age five may rise to 30 million globally by 2030, with sub-Saharan Africa expected to contribute the majority of cases [1, 2]. In 2023, the region recorded nearly 2.7 million under-five deaths, representing over half of worldwide child mortality [1, 2]. The high mortality burden in sub-Saharan Africa is largely associated with malaria, neonatal complications, prematurity, respiratory infections, and diarrheal illnesses.

[3].

Nigeria continues to experience major child health challenges driven by insecurity, weak health systems, and infectious diseases [4]. Conflict linked to the Boko Haram insurgency has displaced populations and disrupted access to healthcare, nutrition, and other essential services, increasing children’s vulnerability [4]. The country is among those with the highest under-five mortality rates globally, recording 105 deaths per 1,000 live births in 2023, while an estimated 850,000 preventable under-five deaths occur each year [5–7]. Leading causes of mortality include malaria, respiratory infections, neonatal complications, diarrheal diseases, and meningitis [3].

Nigeria still records severe maternal and child health burdens despite several policy initiatives. National programmes such as the RMNCAH + N strategy and the Child Survival Action Plan (2025–2029) were introduced to expand immunization, improve nutrition, and strengthen childhood disease management [8–10]. Nevertheless, child survival outcomes remain poor, with 2023 estimates indicating 105 under-five deaths per 1,000 live births and nearly 850,000 avoidable child deaths each year [7, 10]. These persistent mortality levels indicate the continued need for stronger investments and broader cross-sector partnerships. Mosley and Chen’s framework explains that under-five mortality and child morbidity are driven by proximate determinants such as maternal characteristics, environmental conditions, nutrition, injuries, and health care practices. These are in turn shaped by broader social, household, cultural, institutional, and environmental factors influencing child health outcomes indirectly [11].

Evidence on under-five mortality shows that child survival is influenced by a wide range of interconnected factors, including place of residence, environmental exposures, household wealth, maternal characteristics, access to healthcare, and child-specific conditions. Studies from Nigeria, Gambia, Sudan, and Ethiopia report marked regional inequalities in mortality patterns [12–15]. In addition, environmental threats such as air pollution and exposure to zoonotic diseases have been associated with higher child death rates in countries like Nepal [16, 17]. However, the exploration of these risk factors in relation to under-5 mortality is very limited in Africa. Across several African settings, mortality is more common among children from poorer households, those with limited maternal care, younger mothers, short birth intervals, multiple births, delayed breastfeeding, and male children [12, 18–20]. Studies indicate that child deaths can have lasting consequences for surviving siblings. In several sub-Saharan African contexts, loss of a child beyond the neonatal stage has been associated with disruptions in surviving children’s development, including impaired growth and reduced educational engagement [21]. Further evidence suggests that the emotional and psychological burden of bereavement becomes more severe when individuals experience repeated sibling deaths before age 25 [22].

UNICEF emphasizes continuous monitoring of neonatal and under-five mortality, as child mortality reflects public health, socio-economic conditions, and child well-being [1]. Limited evidence on determinants hinders interventions and responses [11, 16]. To date, a limited number of studies have examined factors influencing child survival, particularly using time-to-event methods to account for censored data. The main objective of this study was to investigate the maternal, household, environmental, and child-level determinants of under-five mortality in Nigeria using survival analysis methods based on the 2024 Nigeria Demographic and Health Survey. The current study made noteworthy contributions to child mortality research by adopting a time to event approach, which enabled the examination of how individual experiences over time, including social, economic, and environmental factors, influence under-five health trajectories and outcomes. This approach accounted for four unique stages of under-five mortality: (1) early neonatal mortality (2), late neonatal mortality (3), infant mortality, and (4) child mortality along the under-five growth and development pathway. Each of those stages have important implications for targeted public health interventions [23].

Methods

Study design, setting, and population

A retrospective cohort-type analytical approach was adopted using secondary data obtained from the 2024 Nigeria Demographic and Health Survey, which provides nationally representative demographic and health information for Nigeria. The survey was carried out from December 2023 to May 2024 across the 36 states and the Federal Capital Territory through collaboration between the National Population Commission, the Federal Ministry of Health and Social Welfare, and ICF. Sampling followed a stratified two-stage cluster procedure involving the selection of enumeration areas and households to ensure broad population coverage [24]. The analysis relied on the Children’s Recode dataset, which contains information on children aged below five years derived from maternal birth histories and household interviews [24].

Measurement and variables

The survival-time variable was constructed from children’s age in months and age at death as recorded in the NDHS (NBKR) dataset. For children who died, survival time was defined as the reported age at death in completed months, representing time from birth to death. Children who were alive at the time of the survey contributed censored observations, with survival time defined as their age in completed months at the interview. Children who had not yet reached 60 months of age were right-censored at their current age, while those who survived to 60 months without experiencing the event were administratively censored at 59 completed months. Neonatal deaths recorded as age 0 were assigned a small constant (ε = 0.1 months) to avoid left-censoring issues [25]. The event indicator was derived from variable b5 (“is [name] still living?”), coded as 1 for deaths and 0 for censored observations. Because the NDHS is based on retrospective birth histories, all censoring was administrative, with no loss to follow-up, allowing construction of a single continuous time-to-event variable for survival analysis.

Independent variables were classified into child, maternal, household, and environmental factors. Child-level variables included sex (male/female), birth order (1, 2, 3–5, 6+), birth weight (large, normal, small), gestation type (singleton/twin), and birth intervals categorized as short, long, longer, firstborn, or open intervals. Maternal variables comprised age groups, education level, age at first birth, religion, marital status, health insurance coverage, and employment status. Household factors included place of delivery, maternal healthcare decision-making authority, and wealth quintiles. Environmental variables included urban/rural residence, region, cooking fuel type, drinking water source, sanitation facilities, smoking status, and household electricity access. Categorization of the above variables has also been presented elsewhere [26].

Data analysis and management

Stata version 15 was used for analysis [27]. The complex survey design of the 2024 Nigeria DHS was incorporated in the Cox regression analysis using Stata survey procedures. Sampling weights (v005) were normalized (wgt = v005/1,000,000) and applied to adjust for unequal selection probabilities. Clustering was accounted for using the primary sampling unit variable (v021), and stratification was incorporated using v022. In Stata, the survey design was specified using svyset v021 [pweight = wgt], strata(v022), after which the Cox proportional hazards model was estimated using svy: stcox. This ensured that hazard ratios and standard errors were adjusted for the complex multistage sampling design of the DHS.

Descriptive statistics were generated to summarize children’s socio-demographic characteristics and survival outcomes. The survival data were declared using the stset command in Stata. Time-to-event analytical techniques were then applied to investigate factors associated with under-five mortality. In particular, the Kaplan–Meier estimator and Cox proportional hazards modelling were preferred over standard regression approaches because they are better suited for analyzing mortality timing [28, 29], and transitions across stages of early childhood development. The Kaplan–Meier (KM) method and Cox proportional hazards (PH) model are also well suited to handle censored data unlike standard generalized linear models (GLMs) [28, 30].

Survival data were prepared in Stata by defining the time-to-event structure and identifying censored and failure observations.

Survival time was measured in completed months from birth until death or censoring. Children who died before reaching five years of age were classified as having experienced the event of interest (under-five mortality). Children who were alive at the time of the survey interview were treated as right-censored at their age in completed months because the event of interest had not occurred by the end of observation. In addition, children who survived beyond 59 completed months were administratively censored at 60 months, which corresponds to the upper age limit for under-five mortality analysis.

Initial Cox regression analyses were performed to examine the relationship between under-five mortality and each explanatory factor independently. Only variables meeting the 5% significance threshold were included in the final multivariable model. To improve model reliability, diagnostic tests for multicollinearity were undertaken and highly correlated predictors were omitted. Assessment of the proportional hazards assumption using Schoenfeld residual tests indicated statistically significant evidence of departures from proportionality for succeeding birth interval (p < 0.001), distance to a health facility (v467c) (p = 0.002), and two categories of the number of under-five children in the household (p = 0.0001 and p = 0.0089). The global Schoenfeld residual test was also statistically significant (χ² = 191.18, df = 59, p < 0.001) (Table 1, Supplementary File 1). However, graphical assessment using log(-log) survival plots showed that the curves were approximately parallel across categories, with no substantial crossing or systematic divergence over time. The observed departures were mainly confined to the tails of the curves, where relatively few observations remained at risk (Fig. 1, Supplementary File 1). Given the large sample size, the statistical tests may have been sensitive to relatively small departures from proportionality. Considering the statistical and graphical evidence together, the observed departures were judged unlikely to materially affect the study findings, and the standard Cox proportional hazards model was retained for the final analysis.

Table 1.

Distribution of under-fives by individual, maternal, household and environmental factors

Child characteristics	N(%)	CHR (95% CI)	P value	AHR (95% CI)	P value
Child is alive
No/dead	2206(7.97)
Yes/alive	25,398(92.03)
Sex of the child
Male (RC)	13,963(50.6)
female	13,636(49.4)	0.951(0.875–1.034)	0.241	0.933(0.858–1.015)	0.104
Succeeding birth intervals
Short (≤ 17 months) (RC)	1213(4.4)
Long (18–33 months)	5139(18.6)	0.373(0.328–0.425)	0.001	0.497(0.436–0.567)	0.001
Longer (≥ 34 months)	2584(9.4)	0.227(0.191–0.269)	0.001	0.326(0.272–0.39)	0.001
Under-fives in open birth intervals	18,663(67.6)	0.2(0.177–0.226)	0.001	0.106(0.093–0.121)	0.001
Preceding birth intervals
Short (≤ 17 months) (RC)	1924(7)
Long (18–33 months)	9867(35.8)	0.606(0.531–0.693)	0.001	0.726(0.634–0.831)	0.001
Longer (≥ 34 months)	7689(27.9)	0.417(0.36–0.484)	0.001	0.467(0.4-0.545)	0.001
Very long	2534(9.2)	0.368(0.299–0.452)	0.001	0.308(0.246–0.385)	0.001
Under-fives in open birth intervals	5585(20.2)	0.59(0.509–0.684)	0.001	0.69(0.407–1.169)	0.168
Birth order
First born (RC)	5508(20)
Second born	5070(18.4)	0.819(0.711–0.942)	0.005	1.429(0.856–2.385)	0.172
3–5	11,353(41.1)	0.853(0.76–0.957)	0.007	1.579(0.923–2.702)	0.095
6+	5668(20.5)	1.32(1.168–1.491)	0.001	1.923(1.1-3.363)	0.022
Gestation type
Single (RC)	26,564(96.3)
Twins	1035(3.8)	2.822(2.441–3.261)	0.001	5.51(4.7–6.46)	0.001
Mother’s characteristics
Age
15–19 (RC)	950(3.4)
20–24	5155(18.7)	0.721(0.58–0.895)	0.003	0.951(0.754–1.199)	0.670
25–29	7439(27)	0.586(0.473–0.725)	0.001	0.907(0.701–1.173)	0.456
30–34	6595(23.9)	0.562(0.453–0.697)	0.001	0.863(0.648–1.149)	0.312
35–39	4497(16.3)	0.546(0.437–0.684)	0.001	0.838(0.611–1.15)	0.274
40–44	2239(8.1)	0.652(0.513–0.83)	0.001	1.01(0.717–1.424)	0.954
45–49	724(2.6)	0.825(0.616–1.104)	0.196	1.369(0.923–2.029)	0.118
Education level
No education (RC)	12,214(44.3)
Primary	3194(11.6)	0.893(0.786–1.016)	0.085	1.098(0.953–1.264)	0.196
Secondary	9208(33.4)	0.608(0.55–0.671)	0.001	0.889(0.768–1.028)	0.113
Post-secondary	2983(10.8)	0.408(0.339–0.49)	0.001	0.704(0.551–0.899)	0.005
Marital status
Never in union (RC)	516(1.9)
Married	26,246(95.1)	1.339(0.934–1.92)	0.112
Widowed	298(1.1)	0.986(0.555–1.752)	0.962
Separated	539(2)	1.583(1.013–2.474)	0.044
Religion
Christian (RC)	2208(8)
Muslim	8061(29.2)	1.213(0.981–1.499)	0.074	1.19(0.954–1.485)	0.123
No religion and traditional	17,330(62.8)	2.029(1.666–2.472)	0.001	1.325(1.041–1.685)	0.022
Age of respondent at first birth
10–17 (RC)	7981(28.9)
18–29	18,447(66.8)	0.719(0.659–0.785)	0.001	0.873(0.785–0.97)	0.012
30–47	1171(4.2)	0.453(0.344–0.595)	0.001	0.784(0.567–1.083)	0.140
Currently working
No (RC)	11,055(40.1)
Yes	16,544(59.9)	0.795(0.731–0.865)	0.001	1.041(0.949–1.142)	0.39
Has health insurance
No (RC)	26,871(97.4)
Yes	728(2.6)	0.548(0.388–0.773)	0.001	0.923(0.644–1.324)	0.664
Household characteristics
Place of delivery
Home (RC)	8476(30.7)
Health facility	7402(26.8)	0.873(0.774–0.985)	0.027	1.175(1.026–1.344)	0.019
Not asked	11,721(42.5)	0.951(0.859–1.053)	0.334	0.522(0.464–0.587)	0.001
Wealth index
Poorest (RC)	7232(26.2)
Poorer	5597(20.3)	1.014(0.909–1.13)	0.809	1.081(0.96–1.217)	0.199
Middle	5332(19.3)	0.687(0.607–0.778)	0.001	0.904(0.765–1.067)	0.232
Richer	5091(18.5)	0.6(0.526–0.685)	0.001	0.915(0.728–1.15)	0.446
Richest	4347(15.8)	0.453(0.388–0.529)	0.001	0.818(0.594–1.127)	0.220
Getting money to go for treatment is perceived to be a big problem
Yes (RC)	14,760(53.5)
No	12,839(46.5)	0.887(0.815–0.965)	0.005	0.949(0.863–1.043)	0.279
Number of under-fives in a household
1 (RC)	8925(32.3)
2	10,666(38.7)	0.319(0.288–0.353)	0.001	0.176(0.158–0.197)	0.001
3	4814(17.4)	0.318(0.276–0.366)	0.001	0.107(0.091–0.125)	0.001
4+	3194(11.6)	0.356(0.303–0.418)	0.001	0.1(0.083–0.120)	0.001
Decision maker on the mother’s own health
Wife alone (RC)	2961(10.7)
Both husband and wife	9447(34.2)	1.312(1.104–1.56)	0.002	1.211(1.014–1.445)	0.034
Solely someone else	13,838(50.1)	1.766(1.499–2.082)	0.001	1.326(1.11–1.582)	0.002
Widowed/divorced	1353(4.9)	1.396(1.09–1.788)	0.008	1.089(0.845–1.404)	0.508
All under-fives slept under mosquito nets
No (RC)	5847(21.2)
Some	2730(9.9)	1.071(0.893–1.285)	0.459	1.505(1.237–1.83)	0.001
All	9569(34.7)	1.173(1.031–1.335)	0.015	1.004(0.881–1.145)	0.948
No in the household	9453(34.3)	1.796(1.59–2.028)	0.001	1.822(1.609–2.062)	0.001
Environmental factors
Region
Northwest (RC)	8564(31)
Northeast	5880(21.3)	0.921(0.829–1.023)	0.124	0.842(0.752–0.942)	0.003
Northcentral	5029(18.2)	0.619(0.546–0.702)	0.001	0.676(0.581–0.787)	0.001
Southeast	2979(10.8)	0.535(0.454–0.63)	0.001	0.703(0.557–0.888)	0.003
South-south	2649(9.6)	0.43(0.356–0.519)	0.001	0.576(0.446–0.744)	0.001
Southwest	2498(9.1)	0.408(0.335–0.498)	0.001	0.504(0.392–0.647)	0.001
Type of residence
Urban (RC)	10,633(38.5)
Rural	16,966(61.5)	1.697(1.545–1.863)	0.001	1.227(1.09–1.382)	0.001
Long distance to health facility is perceived to be a big problem
Yes (RC)	8292(30)
No	19,307(70)	0.858(0.785–0.937)	0.001	1.013(0.916–1.12)	0.796
Type of energy used for cooking
Wood/charcoal (RC)	22,246(80.6)
Electricity/gas	4911(17.8)	0.528(0.46–0.605)	0.001	1.038(0.826–1.305)	0.749
Kerosene	442(1.6)	0.721(0.497–1.047)	0.086	1.137(0.765–1.69)	0.524
Source of water for drinking
Piped water/tank/bore hole/ rainwater (RC)	13,980(50.7)
Well/spring	7712(27.9)	1.378(1.256–1.513)	0.001	1.101(0.995–1.22)	0.064
Dam/ River	3217(11.7)	1.05(0.915–1.205)	0.486	1.022(0.874–1.195)	0.786
Commercial bottled water	2690(9.8)	0.678(0.566–0.811)	0.001	1.18(0.951–1.465)	0.132
Stool disposal
No facility (RC)	342(1.2)
Bucket/hanging latrine/open pit	7090(25.7)	0.981(0.691–1.391)	0.913	1.222(0.853–1.75)	0.275
flush	8612(31.2)	0.581(0.408–0.827)	0.003	1.243(0.848–1.823)	0.265
pit/compositing latrine	11,555(41.9)	0.944(0.668–1.336)	0.746	1.164(0.813–1.668)	0.408
Respondent smokes tobacco
Yes (RC)	122(0.4)
No	27,477(99.6)	0.976(0.524–1.816)	0.938
Household has electricity
No (RC)	15,431(55.9)
Yes	12,168(44.1)	0.661(0.606–0.722)	0.001	1.061(0.928–1.213)	0.386

95% CI 95% Confidence Interval, AHR Adjusted Hazard Ratio, CHR Crude Hazard Ratio, CI Confidence Interval, KM Kaplan–Meier, NBKR NDHS Birth History Recode dataset, NDHS Nigeria Demographic and Health Survey, N (%) Number and percentage of observations, p p-value, PH Proportional Hazards, RC Reference Category

Fig. 1.

Kaplan-Meier under-five survival curves by selected factors

Ethical considerations

Because this study relied on publicly available secondary data, no new ethics committee approval was required. Access to the 2024 NDHS dataset was formally requested and granted through the DHS Program data portal (http://dhsprogram.com/data/availabledatasets.cfm), and the dataset was received in fully de-identified form. The original 2024 NDHS was conducted in line with the Declaration of Helsinki, ensuring ethical standards for human research. Ethical oversight was provided by the Institutional Review Board of ICF International, and written informed consent was obtained from all eligible respondents who supplied information on children under five, including both living and deceased cases.

Findings

Description of the study population by individual, maternal, household and environmental factors

Among the sample, 7.97% of children were dead with an almost equal sex distribution. Most children were of birth order 3–5 (41.1%), born as singletons (96.3%), and within open birth intervals (67.6%). Mothers were mainly aged 25–34 years (50.9%), with 44.3% having no education and only 10.8% attaining post-secondary education; most were married (95.1%) and working (59.9%), but health insurance coverage was very low (2.6%). Unfavorable socioeconomic conditions were prevalent, with many in poor wealth groups, limited healthcare affordability, and low decision-making autonomy. Most households were rural, used biomass fuel, lacked electricity, and had varied access to mosquito nets, water, and sanitation (Table 1).

Kaplan-Meier estimates of under-five survival by selected factors

Kaplan–Meier survival analysis showed a steady decline in under-five survival from birth to 59 months, with the sharpest drop occurring in the neonatal period; nearly half of deaths occurred within the first 28 days. Survival patterns varied significantly by residence, with urban children showing consistently higher survival than rural children. Marked regional disparities were observed, as the Southwest and South South had higher survival probabilities, while the Northeast and Northwest showed the lowest and steepest declines. A clear wealth gradient was also evident, with poorest households experiencing the lowest survival. Maternal education showed a protective effect, with higher survival among children of more educated mothers (Fig. 1).

Socioeconomic, maternal, and environmental determinants of under-five mortality: unadjusted Cox regression results

The crude Cox regression analysis identified several child, maternal, household, and environmental factors associated with under-five mortality. Among child characteristics, twins had a substantially higher hazard of death than singleton births (CHR = 2.82, 95% CI: 2.44–3.26; p = 0.001). The magnitude of the association suggests that children from twin pregnancies constitute a particularly vulnerable group requiring enhanced survival interventions. Compared with short succeeding birth intervals (≤ 17 months), longer succeeding birth intervals were associated with a reduced hazard of under-five mortality at 18–33 months (CHR = 0.37, 95% CI: 0.33–0.43; p = 0.001), ≥ 34 months (CHR = 0.23, 95% CI: 0.19–0.27; p = 0.001), and among children in open birth intervals (CHR = 0.20, 95% CI: 0.18–0.23; p = 0.001). Similarly, compared with short preceding birth intervals (≤ 17 months), longer preceding birth intervals were protective at 18–33 months (CHR = 0.61, 95% CI: 0.53–0.69; p = 0.001), ≥ 34 months (CHR = 0.42, 95% CI: 0.36–0.48; p = 0.001), very long intervals (CHR = 0.37, 95% CI: 0.30–0.45; p = 0.001), and among children in open preceding birth intervals (CHR = 0.59, 95% CI: 0.51–0.68; p = 0.001). Compared with first-born children, second-born children (CHR = 0.82, 95% CI: 0.71–0.94; p = 0.005) and those of birth order 3–5 (CHR = 0.85, 95% CI: 0.76–0.96; p = 0.007) had lower mortality hazards, whereas children of birth order six or higher had a higher mortality hazard (CHR = 1.32, 95% CI: 1.17–1.49; p = 0.001). Compared with mothers aged 15–19 years, maternal age of 20–24 years (CHR = 0.72, 95% CI: 0.58–0.90; p = 0.003), 25–29 years (CHR = 0.59, 95% CI: 0.47–0.73; p = 0.001), 30–34 years (CHR = 0.56, 95% CI: 0.45–0.70; p = 0.001), and 35–39 years (CHR = 0.55, 95% CI: 0.44–0.68; p = 0.001) were associated with lower mortality hazards. Compared with mothers with no formal education, secondary (CHR = 0.61, 95% CI: 0.55–0.67; p = 0.001) and post-secondary education (CHR = 0.41, 95% CI: 0.34–0.49; p = 0.001) were associated with lower mortality hazards. Compared with Christian mothers, children of mothers with no religion or traditional religion had a higher mortality hazard (CHR = 2.03, 95% CI: 1.67–2.47; p = 0.001). Compared with mothers whose first birth occurred at ages 10–17 years, first birth at ages 18–29 years (CHR = 0.72, 95% CI: 0.66–0.79; p = 0.001) and 30–47 years (CHR = 0.45, 95% CI: 0.34–0.60; p = 0.001) were associated with lower mortality hazards. Compared with mothers who were not currently working, those who were currently working had a lower mortality hazard (CHR = 0.80, 95% CI: 0.73–0.87; p = 0.001), while mothers with health insurance had a lower mortality hazard than those without health insurance (CHR = 0.55, 95% CI: 0.39–0.77; p = 0.001). Compared with mothers who had never been in a union, separated mothers had a higher mortality hazard (CHR = 1.58, 95% CI: 1.01–2.47; p = 0.044). Household factors showed that, compared with home delivery, health facility delivery was associated with a lower mortality hazard (CHR = 0.87, 95% CI: 0.77–0.99; p = 0.027). Compared with the poorest households, children from middle (CHR = 0.69, 95% CI: 0.61–0.78; p = 0.001), richer (CHR = 0.60, 95% CI: 0.53–0.69; p = 0.001), and richest households (CHR = 0.45, 95% CI: 0.39–0.53; p = 0.001) had lower mortality hazards. Compared with mothers who perceived getting money for treatment as a big problem, those who did not perceive it as a big problem had a lower mortality hazard (CHR = 0.89, 95% CI: 0.82–0.97; p = 0.005). Compared with households with one under-five child, households with two (CHR = 0.32, 95% CI: 0.29–0.35; p = 0.001), three (CHR = 0.32, 95% CI: 0.28–0.37; p = 0.001), and four or more under-five children (CHR = 0.36, 95% CI: 0.30–0.42; p = 0.001) had lower mortality hazards. Compared with households where the wife alone made decisions regarding her own health, shared decision-making between husband and wife (CHR = 1.31, 95% CI: 1.10–1.56; p = 0.002), decision-making by someone else (CHR = 1.77, 95% CI: 1.50–2.08; p = 0.001), and widowed/divorced decision-making status (CHR = 1.40, 95% CI: 1.09–1.79; p = 0.008) were associated with higher mortality hazards. Compared with households where no under-five slept under a mosquito net, households where all under-fives slept under mosquito nets had a higher mortality hazard (CHR = 1.17, 95% CI: 1.03–1.34; p = 0.015), while households with no mosquito nets had the highest mortality hazard (CHR = 1.80, 95% CI: 1.59–2.03; p = 0.001). Compared with the Northwest region, children from the Northcentral (CHR = 0.62, 95% CI: 0.55–0.70; p = 0.001), Southeast (CHR = 0.54, 95% CI: 0.45–0.63; p = 0.001), South South (CHR = 0.43, 95% CI: 0.36–0.52; p = 0.001), and Southwest (CHR = 0.41, 95% CI: 0.34–0.50; p = 0.001) regions had lower mortality hazards. Compared with urban residents, rural residents had a higher mortality hazard (CHR = 1.70, 95% CI: 1.55–1.86; p = 0.001). Compared with respondents who perceived distance to a health facility as a big problem, those who did not had a lower mortality hazard (CHR = 0.86, 95% CI: 0.79–0.94; p = 0.001). Compared with households using wood or charcoal for cooking, those using electricity or gas had a lower mortality hazard (CHR = 0.53, 95% CI: 0.46–0.61; p = 0.001). Compared with households using piped water, tank water, boreholes, or rainwater, those using commercial bottled water had a lower mortality hazard (CHR = 0.68, 95% CI: 0.57–0.81; p = 0.001), whereas households using well or spring water had a higher mortality hazard (CHR = 1.38, 95% CI: 1.26–1.51; p = 0.001). Compared with households with no toilet facility, those using flush toilets had a lower mortality hazard (CHR = 0.58, 95% CI: 0.41–0.83; p = 0.003). Compared with households without electricity, those with electricity had a lower mortality hazard (CHR = 0.66, 95% CI: 0.61–0.72; p = 0.001). No significant associations were observed for child sex, maternal age 40–44 and 45–49 years, primary education, married and widowed marital status, Muslim religion, poorer wealth category, partial mosquito net use, Northeast region, kerosene use, dam/river water, bucket/hanging latrine/open pit and pit/compositing latrine stool disposal methods, tobacco smoking, and other variables with p > 0.05.

Socioeconomic, maternal, and environmental determinants of under-five mortality: adjusted Cox regression results

The multivariable Cox regression analysis identified several independent predictors of under-five mortality across child, maternal, household, and geographic factors. Among child characteristics, twins had a markedly higher risk of death than singleton births (AHR = 5.51, 95% CI: 4.70–6.46; p = 0.001). The magnitude of the association suggests that children from twin pregnancies constitute a particularly vulnerable group requiring enhanced survival interventions. Compared with short succeeding birth intervals (≤ 17 months), longer succeeding birth intervals were strongly protective, reducing mortality at 18–33 months (AHR = 0.50, 95% CI: 0.44–0.57; p = 0.001), ≥ 34 months (AHR = 0.33, 95% CI: 0.27–0.39; p = 0.001), and among children in open birth intervals (AHR = 0.11, 95% CI: 0.09–0.12; p = 0.001). Similarly, compared with short preceding birth intervals (≤ 17 months), longer preceding birth intervals were protective at 18–33 months (AHR = 0.73, 95% CI: 0.63–0.83; p = 0.001), ≥ 34 months (AHR = 0.47, 95% CI: 0.40–0.55; p = 0.001), and very long preceding birth intervals (AHR = 0.31, 95% CI: 0.25–0.39; p = 0.001). Compared with first-born children, those of birth order six or higher had an increased mortality risk (AHR = 1.92, 95% CI: 1.10–3.36; p = 0.022). Compared with children of mothers with no formal education, maternal post-secondary education reduced mortality risk (AHR = 0.70, 95% CI: 0.55–0.90; p = 0.005). Compared with mothers who had their first birth at ages 10–17 years, delayed first birth at 18–29 years was associated with a lower mortality risk (AHR = 0.87, 95% CI: 0.79–0.97; p = 0.012). Compared with children of Christian mothers, children of mothers with no religion or traditional religion had higher mortality (AHR = 1.33, 95% CI: 1.04–1.69; p = 0.022). Household factors showed that, compared with households having one under-five child, households with two (AHR = 0.18, 95% CI: 0.16–0.20; p = 0.001), three (AHR = 0.11, 95% CI: 0.09–0.13; p = 0.001), and four or more under-five children (AHR = 0.10, 95% CI: 0.08–0.12; p = 0.001) had lower mortality risk. Compared with households where the wife alone made decisions regarding her own health, households in which decisions were made jointly by the husband and wife and those in which decisions were made by someone else had 21% and 33% higher hazards of under-five mortality, respectively (AHR = 1.21, 95% CI: 1.01–1.45 and AHR = 1.33, 95% CI: 1.11–1.58). Compared with households where no under-five slept under a mosquito net, households where only some children slept under mosquito nets had a higher mortality risk (AHR = 1.51, 95% CI: 1.24–1.83; p = 0.001), while households with no mosquito nets had the highest mortality risk (AHR = 1.82, 95% CI: 1.61–2.06; p = 0.001). Compared with the Northwest region, all other regions had lower mortality, including the Northeast (AHR = 0.84, 95% CI: 0.75–0.94; p = 0.003), Northcentral (AHR = 0.68, 95% CI: 0.58–0.79; p = 0.001), Southeast (AHR = 0.70, 95% CI: 0.56–0.89; p = 0.003), South South (AHR = 0.58, 95% CI: 0.45–0.74; p = 0.001), and especially the Southwest (AHR = 0.50, 95% CI: 0.39–0.65; p = 0.001). Compared with urban residence, rural residence increased mortality risk (AHR = 1.23, 95% CI: 1.09–1.38; p = 0.001). Compared with home delivery, health facility delivery showed a modest increase in mortality risk (AHR = 1.18, 95% CI: 1.03–1.34; p = 0.019), while children aged 3–5 years (their mothers not asked about place of delivery) had a lower mortality risk (AHR = 0.52, 95% CI: 0.46–0.59; p = 0.001). No significant associations were found for child sex, open preceding birth intervals, second and third-to-fifth birth order, maternal age groups, primary and secondary education, marital status, Muslim religion, age at first birth of 30–47 years, current employment, health insurance, wealth index, perceived financial barriers to treatment, perceived distance to a health facility, cooking fuel type, drinking water source, stool disposal, household electricity, widowed/divorced decision-making status, or universal mosquito net use (all p > 0.05) (Table 1).

Discussion

Using time to event analysis, the study assessed factors influencing child mortality in Nigeria and found that, among the 27,604 children under five included in the study, 7.97% had died. Nearly half (47.8%) of these deaths occurred within the first 28 days of life. The under-five mortality rate (7.97%) reported in the current study is comparable to estimates from The Gambia (8.7%) [15] and Ethiopia (8.4%) [20]. This similarity may reflect shared socio-demographic conditions and health system challenges across many sub-Saharan African countries (United Nations Inter-Agency Group for Child Mortality Estimation, 2025; WHO, 2024a).

The current study reported the concentration of under-five deaths during the neonatal period. WHO reported a smaller decline in neonatal mortality (44%; from 31 deaths per 1,000 live births in 2000 to 17 in 2023) compared with the reduction among children aged 1–59 months (58%; from 47 deaths per 1,000 live births in 2000 to 20 in 2023) [2]. Similarly, UNICEF noted that the first month of life is the most vulnerable period in the human life cycle and that progress in reducing mortality during this stage has been slower than for the remaining under-five age groups [1].

Short birth intervals were associated with an increased risk of under-five mortality, consistent with evidence from Sudan [13]. This association may be explained by maternal depletion, whereby closely spaced pregnancies reduce the time needed to restore nutrient reserves and physical strength, leading to poorer maternal health outcomes. In addition, short intervals limit resources available for childcare and breastfeeding, thereby increasing children’s vulnerability to malnutrition and infection [31]. These findings highlight the importance of improving access to contraception and strengthening education on optimal birth spacing in Nigeria.

Higher under-five mortality was observed among children whose mothers reported traditional or no religious affiliation. Comparable evidence from Ghana indicates elevated mortality risks among children of Muslim and traditionalist mothers relative to Christian counterparts [32]. Such differences are likely driven by broader socio-cultural and community contexts associated with religious identity rather than religion itself acting as a direct cause [32]. Lack of maternal autonomy in healthcare decisions was associated with higher under-five mortality. This aligns with earlier evidence showing that maternal decision-making autonomy has context-specific effects: it can improve illness detection and reporting, potentially increasing recorded morbidity, while also enabling timely care-seeking that reduces mortality [33, 34]. Household decision-making is context-dependent and influenced by cultural, socioeconomic, and family factors [35]. Therefore, the observed association between joint or other decision-making arrangements and higher under-five mortality should not be interpreted as a causal effect of these decision-making patterns. Overall, these findings highlight the complex role of maternal empowerment.

Absence of mosquito net use was associated with higher under-five mortality. This is consistent with evidence that insecticide-treated nets (ITNs) improve child survival [36]. ITNs reduce malaria transmission by serving as both a physical barrier and a chemical repellent against Anopheles mosquitoes, thereby limiting Plasmodium infection [37]. Integrating ITN distribution with other child health interventions, such as vaccination programmes, may improve uptake and reduce childhood illness and mortality.

Residence in the southern regions was associated with lower under-five mortality than residence in the Northwest. Similar regional disparities have been reported in Sudan [13] and The Gambia, where higher mortality was observed in Janjanbureh, Kuntaur, and Mansakonko than in Banjul [15]. Although the present study did not directly assess the factors underlying these regional differences, they may reflect contextual variations in socioeconomic conditions, access to and quality of healthcare services, maternal education, poverty levels, and the effects of insecurity and conflict, particularly in parts of northern Nigeria [4]. These factors can influence the utilization of maternal and child health services, nutrition, immunization coverage, and timely care-seeking, thereby contributing to regional differences in child survival. Overall, the findings underscore the importance of addressing persistent socioeconomic and geographic inequalities through region-specific interventions to reduce under-five mortality.

Rural residence was associated with higher under-five mortality, consistent with evidence from pastoral communities in Ethiopia [20]. This disparity may be due to better access to health facilities and improved living conditions in urban areas compared with rural settings [14]. Strengthening rural health and social services could reduce these inequalities. Senegal’s progress in achieving universal health coverage, which reduced child mortality by 70% between 2000 and 2024, illustrates this potential [1].

The finding that health facility delivery was associated with a modestly higher risk of under-five mortality compared with home delivery should be interpreted with caution. Although facility-based delivery is generally expected to improve maternal and neonatal outcomes, the observed association in this study may reflect reverse causation and referral bias. In many settings, including Nigeria, complicated pregnancies and high-risk births are more likely to be referred to or managed in health facilities, meaning that the underlying risk status of the mother or newborn may drive both the place of delivery and subsequent mortality risk [38]. Consequently, health facility delivery may disproportionately capture high-risk cases rather than cause higher mortality [38]. In contrast, children aged 3–5 years (for whom information on place of delivery was not collected) exhibited a lower risk of mortality, reflecting the expected decline in mortality risk with increasing child age. Overall, these findings highlight the importance of interpreting place of delivery as a proxy marker of underlying risk and healthcare-seeking patterns rather than a direct causal determinant of child survival.

In this study, mortality was higher among twins than singletons, consistent with evidence from Sudan [13]. Similarly, recent DHS-based evidence from 31 sub-Saharan African countries reported higher odds of neonatal mortality among twins [39]. This association is biologically plausible because twins are more susceptible to prematurity, low birth weight, fetal growth restriction, breastfeeding difficulties, and competition for maternal and placental resources, which may increase neonatal vulnerability. This finding underscores the need for strengthened antenatal, delivery, and postnatal monitoring of twin pregnancies and newborns, with particular attention to prematurity, low birth weight, feeding challenges, and other modifiable risks.

Limitations and strengths

This study has several limitations. First, although the analyses adjusted for a wide range of child, maternal, household, and community characteristics, residual confounding from unmeasured or inadequately measured factors, such as genetic predisposition, environmental exposures, or healthcare quality, cannot be excluded. Second, the study relied on retrospective birth-history data from the 2024 Nigeria Demographic and Health Survey, which are subject to recall bias, particularly for events that occurred several years before the survey. The observed association between the number of under-five children in the household and under-five mortality should be interpreted cautiously. Although the variable was included to account for household composition and caregiving context, it was measured at the survey date and may partly reflect previous child survival. Consequently, the apparent protective association may be influenced by reverse causation or residual endogeneity and should not be interpreted as evidence that a larger number of under-five children reduces mortality risk. Finally, the cross-sectional, retrospective design of the DHS limits causal inference because information on exposures and outcomes was collected at a single point in time. Despite these limitations, the survey employed rigorous data collection procedures, including multi-level quality checks and supervision. Field staff were also trained in research ethics and interviewing techniques, which helped improve data reliability [24].

Conclusion

Using the time to event analysis, the study found that under-five mortality in Nigeria is heavily concentrated in early childhood, with nearly half (47.8%) of all under-five deaths occurring during the neonatal period. The study identified maternal, household, and environmental factors associated with child survival. Kaplan–Meier results showed lower survival among children from rural areas, poorer households, and less educated mothers. Multivariable analysis identified birth-related factors—especially multiple births and short birth intervals—as key determinants, while longer spacing were associated with improved survival. Higher maternal education and delayed childbearing were protective. Mortality was also higher in rural and northern regions, and among households lacking mosquito nets or where mothers had limited decision-making power. Overall, the findings demonstrate the value of the time to event approach in identifying critical early-life risks and structural inequalities that shape child survival outcomes. The study therefore recommends strengthening interventions across the continuum of care, particularly during the neonatal period, while addressing socioeconomic and regional inequalities that influence child survival.

Abbreviations

AHR

Adjusted Hazard Ratio

CI

Confidence Interval

DHS

Demographic and Health Survey

EA

Enumeration Area

FMFBNP

Federal Ministry of Finance, Budget, and National Planning

FMoH

Federal Ministry of Health

FMoHSW

Federal Ministry of Health and Social Welfare, National Population Commission

IRB

Institutional Review Board

MOH

Ministry of Health

NDHS

Nigeria Demographic and Health Survey

NP C

National Population Commission

RMNCAH + N

Reproductive, Maternal, Newborn, Child, Adolescent Health plus Nutrition

SDG

Sustainable Development Goal

U5MR

Under-five mortality rate

UN

United Nations

UNICEF

United Nations Children’s Fund

WHO

World Health Organization

Authors’ contributions

IA and PR conceived the study. IA designed the study. He analyzed data with support from PR. IA drafted the manuscript, with substantial contributions by PR. All authors read and approved the final manuscript.

Funding

None.

Data availability

Data are from the Demographic and Health Survey. The dataset is open to qualified researchers free of charge. To request access to the dataset, please apply at http://dhsprogram.com/data/Access-Instructions.cfm.

Declarations

Ethics approval and consent to participate

All data were obtained from the 2024 Nigeria Demographic and Health Survey (UDHS). Data collection was conducted in accordance with Helsinki declaration for conducting research involving humans. Written informed consent was obtained from both the adult participants and the parent(s)/ guardian(s) of all under-16s prior to the interviews. Procedures and questionnaires for standard DHS surveys have been reviewed and approved by the Institutional Review Board (IRB) of ICF International. We obtained approval to use the data from the DHS repository (http://dhsprogram.com/data/availabledatasets.cfm).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.